diff --git a/.Rbuildignore b/.Rbuildignore index b84fd208..5c2415db 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -1,6 +1,16 @@ vignettes/jss835 vignettes/RcppEigen-intro-nojss.* NEWS.org -vignettes/jss.bst +vignettes/rnw .travis.yml debian +^.*\.Rproj$ +^\.Rproj\.user$ +.*\.tar\.gz$ +^patches +^.editorconfig$ +^eigen-?\.?\.? +^\.github +^\.codecov.yml +^\.covrignore +^local diff --git a/.codecov.yml b/.codecov.yml new file mode 100644 index 00000000..9ec35288 --- /dev/null +++ b/.codecov.yml @@ -0,0 +1,17 @@ +comment: false +coverage: + status: + project: + default: + target: 70% # the (on purpose low) required coverage value + threshold: 2% # the permitted delta in hitting the target + patch: + default: + target: 0% # the (on purpose low) required coverage value + +# layout: "header, diff, tree, changes" +# behavior: default +# require_changes: false # if true: only post the comment if coverage changes +# branches: null +# flags: null +# paths: null diff --git a/.covrignore b/.covrignore new file mode 100644 index 00000000..3b88999b --- /dev/null +++ b/.covrignore @@ -0,0 +1,2 @@ +inst/include/Eigen/* +inst/include/unsupported/Eigen/* diff --git a/.editorconfig b/.editorconfig new file mode 100644 index 00000000..9c5e0b52 --- /dev/null +++ b/.editorconfig @@ -0,0 +1,23 @@ +# EditorConfig is awesome: http://EditorConfig.org + +# top-most EditorConfig file +root = true + +# Unix-style newlines with a newline ending every file +[*] +end_of_line = lf +insert_final_newline = true +trim_trailing_whitespace = true + +# Matches multiple files with brace expansion notation +# 4 space indentation +[*.{c,cpp,h,hpp,R,r}] +indent_style = space +indent_size = 4 + +# Tab indentation (no size specified) +[Makefile] +indent_style = tab + +[README.md] +trim_trailing_whitespace = false diff --git a/.github/workflows/ci.yaml b/.github/workflows/ci.yaml new file mode 100644 index 00000000..bcd742d9 --- /dev/null +++ b/.github/workflows/ci.yaml @@ -0,0 +1,43 @@ +# Run CI for R using https://eddelbuettel.github.io/r-ci/ + +name: ci + +on: + push: + pull_request: + +env: + _R_CHECK_FORCE_SUGGESTS_: "false" + +jobs: + ci: + strategy: + matrix: + include: + - {os: macOS-latest} + - {os: ubuntu-latest} + + runs-on: ${{ matrix.os }} + + steps: + - name: Checkout + uses: actions/checkout@v6 + + - name: Setup + uses: eddelbuettel/github-actions/r-ci@master + + - name: Dependencies + run: ./run.sh install_all + + - name: Test + run: ./run.sh run_tests + + - name: Verify OpenMP on macOS + if: ${{ matrix.os == 'macOS-latest' }} + run: R CMD INSTALL . && Rscript -e 'RcppEigen::EigenNbThreads()' + + - name: Coverage + if: ${{ matrix.os == 'ubuntu-latest' }} + env: + CODECOV_TOKEN: ${{ secrets.CODECOV_TOKEN }} + run: ./run.sh coverage diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..56843bca --- /dev/null +++ b/.gitignore @@ -0,0 +1,7 @@ +.Rproj.user +.Rhistory +.RData +.Ruserdata +src/*.o +src/*.so +src/*.dll diff --git a/.travis.yml b/.travis.yml deleted file mode 100644 index 0a0d626d..00000000 --- a/.travis.yml +++ /dev/null @@ -1,35 +0,0 @@ -# Sample .travis.yml for R projects. -# -# See https://github.com/craigcitro/r-travis -# https://github.com/eddelbuettel/r-travis/ - -language: c - -env: - global: - - R_BUILD_ARGS="--no-build-vignettes --no-manual" - - R_CHECK_ARGS="--no-build-vignettes --no-manual --as-cran" - -script: - - ./travis-tool.sh run_tests - -before_install: - - curl -OL http://raw.github.com/eddelbuettel/r-travis/master/scripts/travis-tool.sh - - chmod 755 ./travis-tool.sh - - ./travis-tool.sh bootstrap - - sudo add-apt-repository -y ppa:edd/misc - - sudo apt-get update -q - -install: - - ./travis-tool.sh install_aptget r-cran-rcpp r-cran-matrix r-cran-inline r-cran-runit r-cran-pkgkitten -# Note: if Rcpp from Github is needed, use following line and remove Rcpp from previous line -# - ./travis-tool.sh install_github RcppCore/Rcpp - -after_failure: - - ./travis-tool.sh dump_logs - -notifications: - email: - on_success: change - on_failure: change - diff --git a/ChangeLog b/ChangeLog index 5d551bbf..96656e32 100644 --- a/ChangeLog +++ b/ChangeLog @@ -1,3 +1,639 @@ +2026-06-04 Dirk Eddelbuettel + + * inst/include/Eigen/: Sync with upstream Eigen 5.0.1 + * inst/include/unsupported/Eigen/: Idem + + * inst/include/Eigen/CholmodSupport: Apply previous patch + * inst/include/Eigen/src/CholmodSupport/CholmodSupport.h: Idem + * inst/include/Eigen/src/Core/util/DisableStupidWarnings.h: Idem + * inst/include/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h: Idem + * inst/include/Eigen/src/Core/arch/AltiVec/PacketMath.h: New one-line patch + +2026-05-03 Dirk Eddelbuettel + + * vignettes/rnw/RcppEigen-Introduction.Rnw: Moved, also update three + URLs to https + * vignettes/rmw/Makefile: Added to ensure proper bibtex processing + * vignettes/RcppEigen-Introduction.pdf: Use precompiled pdf + * vignettes/RcppEigen-Introduction.pdf.asis: Added + * DESCRIPTION (VignetteBuilder): Added Rcpp + * .Rbuildignore: Exclude vignettes/rnw + +2026-01-15 Dirk Eddelbuettel + + * .github/workflows/ci.yaml: Switch to actions/checkout@v6 + +2026-01-07 Dirk Eddelbuettel + + * README.md: Another pair of URL updates for Eigen + * man/fastLm.Rd: Idem + +2025-12-30 Dirk Eddelbuettel + + * inst/tinytest/test_misc.R: Additional tests predicate + + * R/init.R: Some additional #nocov tags + +2025-12-29 Dirk Eddelbuettel + + * DESCRIPTION: Roll micro release and date + +2025-12-28 Dirk Eddelbuettel + + * configure.ac: Detect OpenMP compile and link options + * configure.: Idem + * R/init.R: Set multithreading core count on startup, show startup + message, add two helper accessor functions + * src/Makevars.in: Support OpenMP use for multithreading + * src/Makevars.win: Idem + * src/RcppEigen.cpp: Add thread setter, add typed version getter, + edits to old version getter + * src/RcppExport.cpp: Export new compiled functions + * R/RcppExport.R: Idem + * NAMESPACE: Export several helper functions + * man/RcppEigen-package.Rd: Document thread count setting options + * man/RcppEigen_throttle_cores.Rd: Document additional helpers + * cleanup: Minor extension + +2025-12-26 Dirk Eddelbuettel + + * inst/include/Eigen/src/CholmodSupport/CholmodSupport.h: Comment-out + another SuiteSparse reference + + * patches/eigen-5.0.0.diff: Updated against git commit of Eigen 5.0.0 sync + +2025-12-25 Dirk Eddelbuettel + + * inst/include/Eigen/: Sync with upstream Eigen 5.0.0 (aka 3.5.0) + * inst/include/unsupported/Eigen/: Idem + + * patches/eigen-5.0.0.diff: Summary of changes applied + + * inst/include/RcppEigenForward.h: No longer use deprecated type + * inst/include/RcppEigenWrap.h: Idem + * inst/tinytest/cpp/rcppeigen.cpp: Adjust test to non-deprecated map + * inst/tinytest/cpp/sparse.cpp: Skip test of deprecated type + * inst/tinytest/test_sparse.R: Idem + + * src/fastLm.cpp (SVD::SVD): Update to current form of option setting + +2025-08-26 Dirk Eddelbuettel + + * inst/tinytest/test_misc.R: Add minimal test for EigenNbThreads() + + * inst/include/RcppEigenWrap.h: Add #nocov comments + +2025-08-23 Dirk Eddelbuettel + + * .github/workflows/ci.yaml (jobs): Re-enable coverage + +2025-04-04 Dirk Eddelbuettel + + * .github/workflows/ci.yaml: Switch to r-ci with included bootstrap + +2024-08-23 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.4.0.2 + * inst/NEWS.Rd: Release 0.3.4.0.2 + + * DESCRIPTION (Authors@R): Correct two ORCID tag typos + +2024-08-14 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.4.0.1 + * inst/NEWS.Rd: Release 0.3.4.0.1 + +2024-08-13 Dirk Eddelbuettel + + * inst/include/Eigen/src/misc/blas.h: Conditionally comment out + xerbla which is now also provided by r-devel (CRAN request) + +2024-08-12 Dirk Eddelbuettel + + * DESCRIPTION (Authors@R): Added, with ORCID IDs + +2024-05-16 Dirk Eddelbuettel + + * README.md: Use tinyverse.netlify.app for dependency badge + +2024-03-01 Dirk Eddelbuettel + + * .github/workflows/ci.yaml (jobs): Update to actions/checkout@v4, + add r-ci-setup actions + +2024-02-28 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.4.0.0 + +2024-02-12 Tomas Kalibera + + * inst/include/unsupported/Eigen/CXX11/src/ThreadPool/ThreadYield.h: + Support clang on Windows by including 'sched.h' header + +2024-01-17 Yixuan Qiu + + * DESCRIPTION (Version, Date): Release candidate 0.3.3.99.0 + + * inst/include/Eigen: Upgraded to Eigen 3.4.0 + * inst/include/unsupported/Eigen: Idem + * patches/eigen-3.4.0.diff: Carried local CRAN patches forward + * patches/howToDiff.md: Idem + +2023-11-01 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.3.9.4 + * inst/NEWS.Rd: Release 0.3.3.9.4 + +2023-10-05 Mikael Jagan + + * DESCRIPTION: Package 'Matrix' is now only a Suggests: + * NAMESPACE: Remove unconditional imports from package Matrix + + * inst/include/Eigen/CholmodSupport: No longer need to include + RcppEigenCholmod.h + * inst/include/Eigen/src/CholmodSupport/CholmodSupport.h: Small + wrapper adjustments conditional on Matrix use + * inst/include/RcppEigenCholmod.h: Updated + * inst/include/RcppEigenForward.h: Simplified + * inst/include/RcppEigenWrap.h: Ditto + * inst/include/RcppEigenStubs.cpp: New shorter helper + * inst/include/RcppEigenStubs.h: Removed + +2023-07-21 Dirk Eddelbuettel + + * DESCRIPTION (Date, Version): Roll micro version and date + + * README.md: Add r-universe badge + +2023-07-20 Dirk Eddelbuettel + + * src/RcppEigen.cpp (EigenNbThreads): Add simple threads reporter + + * R/fastLm.R (fastLmPure): Simpler call to `fastLm_Impl()` + + * src/init.c: Replaced by auto-generated section in RcppExports.cpp + * src/RcppExports.cpp: Regenerated + * R/RcppExports.R: Idem + + * src/Makevars: Document possible use of '-fopenmp' + * src/Makevars.win: Idem + +2023-04-18 Dirk Eddelbuettel + + * README.md: Use app.codecov.io as base for codecov link + +2023-03-10 Dirk Eddelbuettel + + * DESCRIPTION (Date, Version): Roll minor version + + * R/RcppEigen.package.skeleton.R: No longer set Imports: RcppEigen in + DESCRIPTION and NAMESPACE + +2023-02-12 Dirk Eddelbuettel + + * inst/CITATION: Convert to bibentry() style with person() + +2022-11-04 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.3.9.3 + * inst/NEWS.Rd: Release 0.3.3.9.3 + + * src/init.c: Add 'void' for proper prototype pleasing clang-15 + + * R/fastLm.R (summary.fastLm,print.fastLm): Refer to correct and full + variable name df.residual in the returned object + + * .github/workflows/ci.yaml (jobs): Update to actions/checkout@v3 + +2022-09-15 Jonah Gabry + + * inst/skeleton/rcppeigen_hello_world.cpp: Correct typo + +2022-04-08 Dirk Eddelbuettel + + * DESCRIPTION (Depends): Add a versioned dependency on R 3.6.0 or + later because of our use of FCONE to support USE_FC_LEN_T + +2022-04-05 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.3.9.2 + * inst/NEWS.Rd: Release 0.3.3.9.2 + +2022-04-04 Dirk Eddelbuettel + + * src/fastLm.cpp: Add FCONE in two calls for improved Fortran and C + character interface per Writing R Extensions, Section 6.6.1 + +2022-01-16 Dirk Eddelbuettel + + * inst/tinytest/test_wrap.R: Added (optional) large memory wrap tests + * inst/tinytest/cpp/wrap.cpp: Added C++ part of test + + * .codecov.yml: Added to not trigger PR fail for small additions + +2022-01-16 Mikael Jagan + + * inst/include/RcppEigenWrap.h: Refine use plain dense wrap() change + +2022-01-15 Mikael Jagan + + * inst/include/RcppEigenWrap.h: Use R_xlen_t for vectors rows + cols + +2021-12-29 Dirk Eddelbuettel + + * README.md: Add total downloads badge + +2021-12-08 Dirk Eddelbuettel + + * README.md: Remove unused continuous integration artifact and badge + +2021-10-13 Dirk Eddelbuettel + + * inst/CITATION: Refinment of doi use + +2021-10-10 Dirk Eddelbuettel + + * inst/CITATION: Switch JSS url to doi form per JSS request + * README.md: Idem + +2021-07-19 Dirk Eddelbuettel + + * inst/include/RcppEigenWrap.h: Two more #nocov tags + * src/fastLm.cpp: One more #nocov tag + +2021-07-18 Dirk Eddelbuettel + + * inst/tinytest/test_fastLm.R: Add tests for summary + * src/fastLm.cpp: Add a few #nocov tags + +2021-07-17 Dirk Eddelbuettel + + * DESCRIPTION (Date, Version): Roll minor version + + * R/RcppEigen.package.skeleton.R (RcppEigen.package.skeleton): Also + import RcppEigen in DESCRIPTION + +2021-06-07 Dirk Eddelbuettel + + * DESCRIPTION (Date, Version): Roll minor version + + * inst/tinytest/test_misc.R: New test file + * inst/tinytest/test_fastLm.R: Added tests + + * R/fastLm.R: Add single one-line nocov tag + + * .Rbuildignore: Add .covignore and .codecov.yml + +2021-06-06 Dirk Eddelbuettel + + * README.md: Added coverage badge + + * .github/workflows/ci.yaml (jobs): Turn on coverage + * .covrignore: Added + * .codecov.yml (ignore): Idem + + * R/RcppEigen.package.skeleton.R: Set nocov + +2021-05-09 Dirk Eddelbuettel + + * DESCRIPTION (URL): Add GitHub repo to URL field + +2021-01-02 Dirk Eddelbuettel + + * R/RcppEigen.package.skeleton.R: Wrap any() around grepl() + +2020-12-25 Dirk Eddelbuettel + + * .github/workflows/ci.yaml: Small tweaks to CI YAML file + +2020-12-17 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): CRAN Release 0.3.3.9.1 (following + coordinated update of reverse dependency StanHeaders) + * inst/NEWS.Rd: Release 0.3.3.9.1 + +2020-12-14 Dirk Eddelbuettel + + * .github/workflows/ci.yaml: Add CI runner using r-ci + * README.md: Add new badge + +2020-12-05 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.3.9.0 + + * inst/include/Eigen: Upgraded to Eigen 3.3.9 + * inst/include/unsupported/Eigen: Idem + * patches/eigen-3.3.9.diff: Carried local CRAN patches forward + + * .travis.yml: Switch to r-ci using focal and bspm + + * README.md: Updated URLs to https and/or redirect location + * inst/CITATION: Idem + * man/RcppEigen-package.Rd: Idem + * man/fastLm.Rd: Idem + +2020-08-16 Dirk Eddelbuettel + + * README.md: Add JSS badge + +2020-03-29 Dirk Eddelbuettel + + * README.md: Added commit badge, edited + +2020-01-22 Dirk Eddelbuettel + + * README.md: README.md: Add a Debian badge + +2019-11-16 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.3.7.0 + + * inst/include/Eigen: Upgraded to Eigen 3.3.7 + * inst/include/unsupported/Eigen: Idem + * patches/eigen-3.3.7.diff: Carried local CRAN patches forward + +2019-11-01 Dirk Eddelbuettel + + * R/unit.test.R (compile_unit_tests): Removed as no longer needed + +2019-10-31 Dirk Eddelbuettel + + * inst/tinytest/test_transform.R: Switch from RUnit to tinytest + * inst/tinytest/test_wrap.R: Idem + + * inst/tinytest/cpp/transform.cpp: Added using Rcpp Attributes + * inst/tinytest/cpp/wrap.cpp: Idem + + * inst/tinytest/cpp/sparse.cpp: More idiomatic Eigen code + * inst/tinytest/test_sparse.R: Idem + + * .editorconfig: Added + +2019-10-30 Dirk Eddelbuettel + + * DESCRIPTION (Suggests): Switch from RUnit to tinytest + * .travis.yml (install): Ditto + + * tests/tinytest.R: Converted to tinytest + + * test_sparse.R: Converted to tinytest + * cpp/sparse.cpp: Added using Rcpp Attributes + +2019-10-29 Dirk Eddelbuettel + + * test_fastLm.R: Converted to tinytest + * test_RcppEigen.R: Idem + * test_solution.R: Idem + + * cpp/rcppeigen.cpp: Added using Rcpp Attributes + * cpp/solution.cpp: Idem + +2019-10-28 Dirk Eddelbuettel + + * tests/tinytest.R: Renamed from tests/doRUnit.R + * inst/tinytest/test_fastLm.R: Renamed from inst/unitTests/runit* + * inst/tinytest/test_RcppEigen.R: Idem + * inst/tinytest/test_solution.R: Idem + * inst/tinytest/test_sparse.R: Idem + * inst/tinytest/test_transform.R: Idem + * inst/tinytest/test_wrap.R: Idem + +2019-10-13 Dirk Eddelbuettel + + * README.md: Added CRAN + BioConductor badges for reverse depends, + add StackOverflow badge to recommend help searches under 'Rcpp' + + * DESCRIPTION (Version, Date): Roll minor version + + * R/RcppEigen.package.skeleton.R (RcppEigen.package.skeleton): Test for + example_code outside of haveKitten test; remove force argument if unused + +2019-05-24 Dirk Eddelbuettel + + * vignettes/RcppEigen-Introduction.Rnw: Update vignette to use + RcppEigen:::eigen_version() instead of .Call() + +2019-03-29 Dirk Eddelbuettel + + * inst/skeleton/rcppeigen_hello_world.cpp: Rework first example to + not rely on Eigen RNG which R CMD check would complain about. + +2019-02-16 James Joseph Balamuta + + * R/runit.RcppEigen.R: Removed listing RcppEigen in Imports during + skeleton package creation. + +2018-11-24 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.3.5.0 + +2018-11-23 Dirk Eddelbuettel + + * inst/include/Eigen: Updated to release 3.3.5 + * inst/include/unsupported: Idem + * patches/eigen-3.3.5.diff: Diff of local patches + +2018-09-02 Dirk Eddelbuettel + + * .travis.yml: Switch Travis CI to R 3.5 repo + +2018-05-30 Michael Weylandt + + * inst/examples/lmBenchmark.R: Update benchmark script to use + microbenchmark and to use exposed fastLm functions from Rcpp + packages rather than invoking .Call directly + +2018-05-25 Ralf Stubner + + * inst/include/RcppEigenWrap.h: Use Rf_xlength and R_xlen_t to + support long vectors + +2018-02-07 Dirk Eddelbuettel + + * patches/eigen-3.3.4.diff: Diff to upstream Eigen 3.3.4, + cherry-picked in the 3.3.4 branch of Yixuan + +2018-02-05 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.3.4.0 + + * inst/include/Eigen/src/Core/arch/CUDA/Half.h (Eigen): Condition use + of long long and unsigned long on C++11 + + * inst/include/Eigen/src/Core/arch/SSE/Complex.h (Eigen): Comment-out + use of diagnostic-suppressing pragma for gcc + clang to satisfy CRAN + * inst/include/Eigen/src/Core/util/DisableStupidWarnings.h: Idem + +2018-02-04 Yixuan Qiu + + [ In RcppEigen 0.3.3.* branch ] + * inst/include/Eigen: Updated to the upstream 3.3 branch of Eigen + based on version 3.3.4 + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + * README.md: Idem + + * inst/include/Eigen/src/Core/util/DisableStupidWarnings.h: + Patch from upstream Eigen that has not been ported to the 3.3 branch + (cf GitHub issue #48) + +2017-11-19 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.3.3.1 + + * R/inline.R: Use '::' not ':::' for Rcpp.plugin.maker + +2017-08-26 Dirk Eddelbuettel + + * .travis.yml (before_install): Use https for curl fetch + +2017-06-06 Yu Gong + + * inst/include/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h: + Also permit compilation under Haiku-OS + +2017-05-28 Dirk Eddelbuettel + + * inst/examples/lmBenchmark.R (do_bench): Remove spurious argument in + call to RcppEigen:::Eigen_SSE() (cf github issue #44) + +2017-04-29 Dirk Eddelbuettel + + * DESCRIPTION: Release 0.3.3.3.0 + + [ which again owes a very big thank you to Yixuan for doing the work! ] + +2017-04-27 Dirk Eddelbuettel + + * .travis.yml: Switch to using run.sh for Travis CI + +2017-04-27 Yixuan Qiu + + [ In RcppEigen 0.3.3.* branch ] + + * inst/include/Eigen/src/Core/arch/CUDA/Half.h: Fixed compiler warning + on 'long long' type in C++ 98 mode + +2017-03-14 Dirk Eddelbuettel + + * DESCRIPTION (Version, Date): Release 0.3.2.9.1 + + * src/init.c (R_init_RcppEigen): Call R_registerRoutines() + and R_useDynamicSymbols() + + * NAMESPACE: Use .registration=TRUE on useDynLib + + * R/fastLm.R (fastLmPure): Remove erroneous fourth argument from .Call + +2017-03-13 Martin Maechler + + * inst/include/RcppEigenCholmod.h: Synchronize with Matrix package + +2017-02-21 Yixuan Qiu + + [ In RcppEigen 0.3.3.* branch ] + + * inst/include/Eigen: Updated to release 3.3.3 of Eigen + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + * README.md: Idem + +2017-01-20 Yixuan Qiu + + [ In RcppEigen 0.3.3.* branch ] + + * inst/include/Eigen: Updated to release 3.3.2 of Eigen + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + * README.md: Idem + + * inst/unitTests/runit.RcppEigen.R, inst/unitTests/runit.sparse.R: + Explicitly convert matrix size to `double` type such that Rcpp can + properly return the value to R, thanks to ChingChuan and Dirk + +2017-01-20 ChingChuan Chen + + [ In RcppEigen 0.3.3.* branch ] + + * inst/include/Eigen: Updated to release 3.3.1 of Eigen + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + + * inst/examples/lmBenchmark.R: Fixed function names + +2016-12-22 Dirk Eddelbuettel + + * DESCRIPTION (URL, BugReports): Added / updated + +2016-11-12 Yixuan Qiu + + [ In RcppEigen 0.3.3.* branch ] + + * inst/include/Eigen: Updated to release 3.3.0 of Eigen + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + * README.md: Idem + + * inst/include/RcppEigenForward.h, inst/include/RcppEigenWrap.h: + Added exporters for the new Map > type + * inst/unitTests/runit.sparse.R: Unit tests for the new type + +2016-08-20 Dirk Eddelbuettel + + * DESCRIPTION: Release 0.3.2.9.0 with big thanks to Yixuan for doing + the work! + +2016-08-19 Yixuan Qiu + + * inst/include/Eigen: Updated to release 3.2.9 of Eigen + + * README.md: Updated version number and fixed the NOTE from CRAN URL + check + +2016-04-30 Dirk Eddelbuettel + + * README.md: Expanded + +2016-04-28 James Joseph Balamuta + + * inst/include/RcppEigenWrap.h: Added an exporter class for + Map::RowVectorX per http://stackoverflow.com/questions/36920689/ + * inst/include/unitTests/runit.RcppEigen.R: Added row exporter unit + test. + +2016-02-29 Dirk Eddelbuettel + + * DESCRIPTION (Version): Release 0.3.2.8.1 + * inst/NEWS.Rd: Release 0.3.2.8.1 + * debian/*: Changes for Debian release of 0.3.2.8.1 + +2016-02-28 Yixuan Qiu + + * inst/include/Eigen/src/SparseCore/CompressedStorage.h, + inst/include/Eigen/src/SparseCore/SparseBlock.h, + inst/include/Eigen/src/SparseCore/SparseMatrix.h, + inst/include/Eigen/src/SparseCore/SparseRedux.h, + inst/include/Eigen/src/SparseCore/SparseVector.h: + Another patch from upstream to fix UBSAN null pointer errors + +2016-02-23 Dirk Eddelbuettel + + * DESCRIPTION (Version): Release 0.3.2.8.0 + * DESCRIPTION (Author): Added Yixuan Qiu + + * inst/NEWS.Rd: Release 0.3.2.8.0 + +2016-02-22 Yixuan Qiu + + * inst/include/Eigen: Updated to release 3.2.8 of Eigen + * inst/include/unsupported: Idem + * DESCRIPTION: Idem + * README.md: Idem + + * inst/include/Eigen/src/SparseCore/CompressedStorage.h, + inst/include/Eigen/src/Core/util/Memory.h: Applied patch from + upstream to fix UBSAN errors + 2016-01-20 Dirk Eddelbuettel * DESCRIPTION: Release 0.3.2.7.0 diff --git a/DESCRIPTION b/DESCRIPTION index bd6c00fe..cf12c938 100644 --- a/DESCRIPTION +++ b/DESCRIPTION @@ -1,32 +1,39 @@ Package: RcppEigen Type: Package Title: 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library -Version: 0.3.2.7.0 -Date: 2016-01-19 -Author: Douglas Bates, Dirk Eddelbuettel and Romain Francois; - the authors of Eigen for the included version of Eigen -Maintainer: Dirk Eddelbuettel +Version: 0.4.9.9-2 +Date: 2026-06-04 +Authors@R: c(person("Doug", "Bates", role = "aut", + comment = c(ORCID = "0000-0001-8316-9503")), + person("Dirk", "Eddelbuettel", role = c("aut", "cre"), email = "edd@debian.org", + comment = c(ORCID = "0000-0001-6419-907X")), + person("Romain", "Francois", role = "aut", + comment = c(ORCID = "0000-0002-2444-4226")), + person("Yixuan", "Qiu", role = "aut", + comment = c(ORCID = "0000-0003-0109-6692")), + person("Authors of", "Eigen", role = "cph", + comment = "Authorship and copyright in included Eigen library as detailed in inst/COPYRIGHTS")) Copyright: See the file COPYRIGHTS for various Eigen copyright details Description: R and 'Eigen' integration using 'Rcpp'. - 'Eigen' is a C++ template library for linear algebra: matrices, - vectors, numerical solvers and related algorithms. It supports dense - and sparse matrices on integer, floating point and complex numbers, - decompositions of such matrices, and solutions of linear systems. Its - performance on many algorithms is comparable with some of the best - implementations based on 'Lapack' and level-3 'BLAS'. - . - The 'RcppEigen' package includes the header files from the 'Eigen' C++ - template library (currently version 3.2.7). Thus users do not need to - install 'Eigen' itself in order to use 'RcppEigen'. - . - Since version 3.1.1, 'Eigen' is licensed under the Mozilla Public License - (version 2); earlier version were licensed under the GNU LGPL version 3 or - later. 'RcppEigen' (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under - the GNU GPL version 2 or later, as is the rest of 'Rcpp'. + 'Eigen' is a C++ template library for linear algebra: matrices, vectors, + numerical solvers and related algorithms. It supports dense and sparse + matrices on integer, floating point and complex numbers, decompositions of + such matrices, and solutions of linear systems. Its performance on many + algorithms is comparable with some of the best implementations based on + 'Lapack' and level-3 'BLAS'. The 'RcppEigen' package includes the header + files from the 'Eigen' C++ template library. Thus users do not need to + install 'Eigen' itself in order to use 'RcppEigen'. Since version 3.1.1, + 'Eigen' is licensed under the Mozilla Public License (version 2); earlier + version were licensed under the GNU LGPL version 3 or later. 'RcppEigen' + (the 'Rcpp' bindings/bridge to 'Eigen') is licensed under the GNU GPL + version 2 or later, as is the rest of 'Rcpp'. License: GPL (>= 2) | file LICENSE -Depends: R (>= 2.15.1) LazyLoad: yes +Depends: R (>= 3.6.0) LinkingTo: Rcpp -Imports: Matrix (>= 1.1-0), Rcpp (>= 0.11.0), stats, utils -Suggests: inline, RUnit, pkgKitten -URL: http://eigen.tuxfamily.org +Imports: Rcpp (>= 0.11.0), stats, utils +Suggests: Matrix, inline, tinytest, pkgKitten, microbenchmark +URL: https://github.com/RcppCore/RcppEigen, https://dirk.eddelbuettel.com/code/rcpp.eigen.html +BugReports: https://github.com/RcppCore/RcppEigen/issues +RoxygenNote: 6.0.1 +VignetteBuilder: Rcpp diff --git a/NAMESPACE b/NAMESPACE index a1f4c4f5..1270ac43 100644 --- a/NAMESPACE +++ b/NAMESPACE @@ -1,18 +1,20 @@ -useDynLib(RcppEigen) +useDynLib("RcppEigen", .registration=TRUE) -importClassesFrom("Matrix", "dgCMatrix", "dgeMatrix", "dsCMatrix", "dtCMatrix") -importFrom(Rcpp, "evalCpp") -importFrom(utils, "packageDescription", "package.skeleton") -importFrom(stats, "model.frame", "model.matrix", "model.response", "fitted", "coef", "printCoefmat", "pt") -#exportPattern("^[[:alpha:]]+") -export(fastLm, - fastLmPure, - RcppEigen.package.skeleton +importFrom("Rcpp", "evalCpp") +importFrom("utils", "packageDescription", "package.skeleton", "packageVersion") +importFrom("stats", "model.frame", "model.matrix", "model.response", "fitted", "coef", "printCoefmat", "pt", "na.omit") +export("fastLm", + "fastLmPure", + "RcppEigen.package.skeleton", + "EigenNbThreads", + "EigenSetNbThreads", + "RcppEigen_throttle_cores", + "RcppEigen_reset_cores" ) -S3method(fastLm, default) -S3method(fastLm, formula) -S3method(predict, fastLm) -S3method(print, fastLm) -S3method(summary, fastLm) -S3method(print, summary.fastLm) +S3method("fastLm", "default") +S3method("fastLm", "formula") +S3method("predict", "fastLm") +S3method("print", "fastLm") +S3method("summary", "fastLm") +S3method("print", "summary.fastLm") diff --git a/R/RcppEigen.package.skeleton.R b/R/RcppEigen.package.skeleton.R index acef346d..184919b2 100644 --- a/R/RcppEigen.package.skeleton.R +++ b/R/RcppEigen.package.skeleton.R @@ -1,6 +1,6 @@ ## RcppEigen.package.skeleton.R: makes a skeleton for a package that wants to use RcppEigen ## -## Copyright (C) 2011 - 2015 Douglas Bates, Dirk Eddelbuettel and Romain Francois +## Copyright (C) 2011 - 2023 Douglas Bates, Dirk Eddelbuettel and Romain Francois ## ## This file is part of RcppEigen. ## @@ -19,12 +19,12 @@ RcppEigen.package.skeleton <- function(name= "anRpackage", list = character(), environment = .GlobalEnv, - path = ".", force = FALSE, - code_files = character(), + path = ".", force = FALSE, + code_files = character(), example_code = TRUE) { - - env <- parent.frame(1) - + + env <- parent.frame(1) # #nocov start + if (!length(list)) { fake <- TRUE assign("Rcpp.fake.fun", function() {}, envir = env) @@ -40,51 +40,53 @@ RcppEigen.package.skeleton <- function(name= "anRpackage", list = character(), ## first let the traditional version do its business call <- match.call() call[[1]] <- skelFunUsed + if ("example_code" %in% names(call)) { + call[["example_code"]] <- NULL # remove the example_code argument + } if (! haveKitten) { # in the package.skeleton() case - if ("example_code" %in% names(call)) { - call[["example_code"]] <- NULL # remove the example_code argument - } if (fake) { call[["list"]] <- "Rcpp.fake.fun" } + } else { + if (force) { + call[["force"]] <- NULL + } } - + tryCatch(eval(call, envir = env), error = function(e) { cat(paste(e, "\n")) # print error stop(paste("error while calling `", skelFunName, "`", sep="")) }) - + message("\nAdding RcppEigen settings") - - ## now pick things up + + ## now pick things up root <- file.path(path, name) - + ## Add Rcpp to the DESCRIPTION DESCRIPTION <- file.path(root, "DESCRIPTION") if (file.exists(DESCRIPTION)) { - x <- cbind(read.dcf(DESCRIPTION), - "Imports" = sprintf("Rcpp (>= %s), RcppEigen (>= %s)", - packageDescription("Rcpp")[["Version"]], - packageDescription("RcppEigen")[["Version"]]), + x <- cbind(read.dcf(DESCRIPTION), + "Imports" = sprintf("Rcpp (>= %s)", + packageDescription("Rcpp")[["Version"]]), "LinkingTo" = "Rcpp, RcppEigen") write.dcf(x, file = DESCRIPTION) - message(" >> added Imports: Rcpp, RcppEigen") + message(" >> added Imports: Rcpp") message(" >> added LinkingTo: Rcpp, RcppEigen") } - - ## add a useDynLib to NAMESPACE, + + ## add a useDynLib to NAMESPACE, NAMESPACE <- file.path(root, "NAMESPACE") lines <- readLines(NAMESPACE) - if (! grepl("useDynLib", lines)) { + if (!any(grepl("useDynLib", lines))) { lines <- c(sprintf("useDynLib(%s)", name), - "import(RcppEigen)", "importFrom(Rcpp, evalCpp)", ## ensures Rcpp instantiation lines) writeLines(lines, con = NAMESPACE) message(" >> added useDynLib and importFrom directives to NAMESPACE") } - + ## lay things out in the src directory src <- file.path(root, "src") if (!file.exists(src)) { @@ -100,13 +102,13 @@ RcppEigen.package.skeleton <- function(name= "anRpackage", list = character(), file.copy(file.path(skeleton, "Makevars"), Makevars) message(" >> added Makevars file with RcppEigen settings") } - + Makevars.win <- file.path(src, "Makevars.win") if (!file.exists(Makevars.win)) { file.copy(file.path(skeleton, "Makevars.win"), Makevars.win) message(" >> added Makevars.win file with RcppEigen settings") } - + if (example_code) { file.copy(file.path(skeleton, "rcppeigen_hello_world.cpp"), src) message(" >> added example src file using Eigen classes") @@ -116,13 +118,12 @@ RcppEigen.package.skeleton <- function(name= "anRpackage", list = character(), Rcpp::compileAttributes(root) message(" >> invoked Rcpp::compileAttributes to create wrappers") } - + if (fake) { rm("Rcpp.fake.fun", envir = env) unlink(file.path(root, "R" , "Rcpp.fake.fun.R")) unlink(file.path(root, "man", "Rcpp.fake.fun.Rd")) } - - invisible(NULL) -} + invisible(NULL) # #nocov end +} diff --git a/R/RcppExports.R b/R/RcppExports.R index 52a03303..27fba4ff 100644 --- a/R/RcppExports.R +++ b/R/RcppExports.R @@ -1,15 +1,29 @@ -# This file was generated by Rcpp::compileAttributes +# Generated by using Rcpp::compileAttributes() -> do not edit by hand # Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393 -fastLm_Impl <- function(X, y, type) { - .Call('RcppEigen_fastLm_Impl', PACKAGE = 'RcppEigen', X, y, type) +eigen_version <- function(single) { + .Call(`_RcppEigen_eigen_version`, single) } -eigen_version <- function(single) { - .Call('RcppEigen_eigen_version', PACKAGE = 'RcppEigen', single) +eigen_version_typed <- function() { + .Call(`_RcppEigen_eigen_version_typed`) } Eigen_SSE <- function() { - .Call('RcppEigen_Eigen_SSE', PACKAGE = 'RcppEigen') + .Call(`_RcppEigen_Eigen_SSE`) +} + +#' @rdname RcppEigen_throttle_cores +EigenNbThreads <- function() { + .Call(`_RcppEigen_EigenNbThreads`) +} + +#' @rdname RcppEigen_throttle_cores +EigenSetNbThreads <- function(n) { + invisible(.Call(`_RcppEigen_EigenSetNbThreads`, n)) +} + +fastLm_Impl <- function(X, y, type) { + .Call(`_RcppEigen_fastLm_Impl`, X, y, type) } diff --git a/R/fastLm.R b/R/fastLm.R index 2616465a..691e8e06 100644 --- a/R/fastLm.R +++ b/R/fastLm.R @@ -1,6 +1,6 @@ ## fastLm.R: Rcpp/Eigen implementation of lm() ## -## Copyright (C) 2011 - 2015 Douglas Bates, Dirk Eddelbuettel and Romain Francois +## Copyright (C) 2011 - 2023 Douglas Bates, Dirk Eddelbuettel and Romain Francois ## ## This file is part of RcppEigen. ## @@ -21,7 +21,7 @@ fastLmPure <- function(X, y, method = 0L) { stopifnot(is.matrix(X), is.numeric(y), NROW(y)==nrow(X)) - .Call("RcppEigen_fastLm_Impl", X, y, method, colnames(X), PACKAGE="RcppEigen") + fastLm_Impl(X, y, method) } fastLm <- function(X, ...) UseMethod("fastLm") @@ -54,7 +54,7 @@ summary.fastLm <- function(object, ...) { object$coefficients <- cbind(Estimate = coef, "Std. Error" = se, "t value" = tval, - "Pr(>|t|)" = 2*pt(-abs(tval), df=object$df)) + "Pr(>|t|)" = 2*pt(-abs(tval), df=object$df.residual)) ## cf src/stats/R/lm.R and case with no weights and an intercept f <- object$fitted.values @@ -66,7 +66,7 @@ summary.fastLm <- function(object, ...) { object$r.squared <- mss/(mss + rss) df.int <- if (object$intercept) 1L else 0L n <- length(f) - rdf <- object$df + rdf <- object$df.residual object$adj.r.squared <- 1 - (1 - object$r.squared) * ((n - df.int)/rdf) class(object) <- "summary.fastLm" object @@ -82,7 +82,7 @@ print.summary.fastLm <- function(x, ...) { printCoefmat(x$coefficients, P.values=TRUE, has.Pvalue=TRUE, ...) cat("\nResidual standard error: ", formatC(x$s, digits=digits), " on ", - formatC(x$df), " degrees of freedom\n", sep="") + formatC(x$df.residual), " degrees of freedom\n", sep="") cat("Multiple R-squared: ", formatC(x$r.squared, digits=digits), ",\tAdjusted R-squared: ",formatC(x$adj.r.squared, digits=digits), "\n", sep="") @@ -109,7 +109,7 @@ predict.fastLm <- function(object, newdata=NULL, ...) { if (!is.null(object$formula)) { x <- model.matrix(object$formula, newdata) } else { - x <- newdata + x <- newdata # #nocov } y <- as.vector(x %*% coef(object)) } diff --git a/R/init.R b/R/init.R new file mode 100644 index 00000000..6d87356a --- /dev/null +++ b/R/init.R @@ -0,0 +1,61 @@ +## init.R: Startup +## +## Copyright (C) 2025 Dirk Eddelbuettel +## +## This file is part of RcppEigen. +## +## RcppEigen is free software: you can redistribute it and/or modify it +## under the terms of the GNU General Public License as published by +## the Free Software Foundation, either version 2 of the License, or +## (at your option) any later version. +## +## RcppEigen is distributed in the hope that it will be useful, but +## WITHOUT ANY WARRANTY; without even the implied warranty of +## MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the +## GNU General Public License for more details. +## +## You should have received a copy of the GNU General Public License +## along with RcppEigen. If not, see . + +.pkgenv <- new.env(parent=emptyenv()) + +.onLoad <- function(libname, pkgname) { # nocov start + ## simple fallback: 'Ncpus' (if set) or else all cpus seen by OpenMP + ncores <- getOption("Ncpus", EigenNbThreads()) + ## consider OMP_THREAD_LIMIT (cf Writing R Extensions), gets NA if envvar unset + ompcores <- as.integer(Sys.getenv("OMP_THREAD_LIMIT")) + ## keep the smaller value, omitting NA + ncores <- min(na.omit(c(ncores, ompcores))) + .pkgenv[["nb_threads"]] <- ncores + RcppEigen_throttle_cores(ncores) +} + +.onAttach <- function(libname, pkgname) { + if (interactive()) { + packageStartupMessage("RcppEigen ", packageVersion("RcppEigen"), + " using ", .pkgenv[["nb_threads"]], " cores. See ", + "'help(\"RcppEigen-package\")' for details.") + } +} + +##' Throttle (or Reset) (Rcpp)Eigen Core Usage +##' +##' Helper functions to throttle use of cores by RcppEigen-internal code. +##' On package load, the initial value is saved and used to reset the value. +##' @param n Integer value of desired cores, default is the value set at package +##' startup reflecting the smallest value among the total number of available +##' cores (or one if compiled without OpenMP support), the value of option +##' \code{Ncpus} and the value of environment variable \code{OMP_THREAD_LIMIT}. +##' @return Only \code{EigenNbThreads()} returns a value, the current value of +##' the number of cores used. The other functions are invoked for their side +##' effect of affecting the count of cores used. +##' @seealso \code{\link{RcppEigen-package}} +RcppEigen_throttle_cores <- function(n) { + if (missing(n)) n <- .pkgenv[["nb_threads"]] + EigenSetNbThreads(n) +} + +##' @rdname RcppEigen_throttle_cores +RcppEigen_reset_cores <- function() { + EigenSetNbThreads(.pkgenv[["nb_threads"]]) # nocov end +} diff --git a/R/inline.R b/R/inline.R index 3d28eb96..dcf2f755 100644 --- a/R/inline.R +++ b/R/inline.R @@ -1,4 +1,4 @@ -## Copyright (C) 2011 Douglas Bates, Dirk Eddelbuettel and Romain Francois +## Copyright (C) 2011 - 2017 Douglas Bates, Dirk Eddelbuettel and Romain Francois ## ## This file is part of RcppEigen. ## @@ -15,10 +15,8 @@ ## You should have received a copy of the GNU General Public License ## along with RcppEigen. If not, see . -inlineCxxPlugin <- - Rcpp:::Rcpp.plugin.maker( - include.before = "#include ", - package = "RcppEigen" -# , LinkingTo = c("RcppEigen", "Rcpp") - ) +inlineCxxPlugin <- Rcpp::Rcpp.plugin.maker(include.before = "#include ", + package = "RcppEigen" +# , LinkingTo = c("RcppEigen", "Rcpp") + ) diff --git a/R/unit.test.R b/R/unit.test.R deleted file mode 100644 index 9d14f3a1..00000000 --- a/R/unit.test.R +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (C) 2011 Douglas Bates, Dirk Eddelbuettel and Romain Francois -# -# This file is part of RcppEigen. -# -# RcppEigen is free software: you can redistribute it and/or modify it -# under the terms of the GNU General Public License as published by -# the Free Software Foundation, either version 2 of the License, or -# (at your option) any later version. -# -# RcppEigen is distributed in the hope that it will be useful, but -# WITHOUT ANY WARRANTY; without even the implied warranty of -# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the -# GNU General Public License for more details. -# -# You should have received a copy of the GNU General Public License -# along with RcppEigen. If not, see . - -compile_unit_tests <- function( definitions, includes = "", cxxargs = "" ){ - signatures <- lapply(definitions, "[[", 1L) - bodies <- lapply(definitions, "[[", 2L) - cxxfunction <- get( "cxxfunction", asNamespace("inline" ) ) - fun <- cxxfunction( signatures, bodies, plugin = "RcppEigen", - includes = sprintf( "using namespace std;\n%s", paste( includes, collapse = "\n") ), - cxxargs = cxxargs - ) - fun -} diff --git a/README.md b/README.md index cb5188f4..77f83609 100644 --- a/README.md +++ b/README.md @@ -1,16 +1,79 @@ -## RcppEigen +## RcppEigen: R and Eigen via Rcpp -[![Build Status](https://travis-ci.org/RcppCore/RcppEigen.svg)](https://travis-ci.org/RcppCore/RcppEigen) [![License](http://img.shields.io/badge/license-GPL%20%28%3E=%202%29-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-2.0.html) [![License](http://img.shields.io/badge/license-MPL2-brightgreen.svg?style=flat)](http://www.mozilla.org/MPL/2.0/) [![CRAN](http://www.r-pkg.org/badges/version/RcppEigen)](http://cran.rstudio.com/package=RcppEigen) [![Downloads](http://cranlogs.r-pkg.org/badges/RcppEigen?color=brightgreen)](http://www.r-pkg.org/pkg/RcppEigen) +[![CI](https://github.com/RcppCore/RcppEigen/workflows/ci/badge.svg)](https://github.com/RcppCore/RcppEigen/actions?query=workflow%3Aci) +[![License](https://img.shields.io/badge/license-GPL%20%28%3E=%202%29-brightgreen.svg?style=flat)](https://www.gnu.org/licenses/gpl-2.0.html) +[![License](https://img.shields.io/badge/license-MPL2-brightgreen.svg?style=flat)](https://www.mozilla.org/MPL/2.0/) +[![CRAN](https://www.r-pkg.org/badges/version/RcppEigen)](https://cran.r-project.org/package=RcppEigen) +[![r-universe](https://rcppcore.r-universe.dev/badges/RcppEigen)](https://rcppcore.r-universe.dev/RcppEigen) +[![Dependencies](https://tinyverse.netlify.app/badge/RcppEigen)](https://cran.r-project.org/package=RcppEigen) +[![Coverage Status](https://codecov.io/gh/RcppCore/RcppEigen/graph/badge.svg)](https://app.codecov.io/github/RcppCore/RcppEigen?branch=master) +[![Debian package](https://img.shields.io/debian/v/r-cran-rcppeigen/sid?color=brightgreen)](https://packages.debian.org/sid/r-cran-rcppeigen) +[![Last Commit](https://img.shields.io/github/last-commit/RcppCore/RcppEigen)](https://github.com/RcppCore/RcppEigen) +[![Downloads (monthly)](https://cranlogs.r-pkg.org/badges/RcppEigen?color=brightgreen)](https://www.r-pkg.org:443/pkg/RcppEigen) +[![Downloads (total)](https://cranlogs.r-pkg.org/badges/grand-total/RcppEigen?color=brightgreen)](https://www.r-pkg.org:443/pkg/RcppEigen) +[![CRAN use](https://jangorecki.gitlab.io/rdeps/RcppEigen/CRAN_usage.svg?sanitize=true)](https://cran.r-project.org/package=RcppEigen) +[![BioConductor use](https://jangorecki.gitlab.io/rdeps/RcppEigen/BioC_usage.svg?sanitize=true)](https://cran.r-project.org/package=RcppEigen) +[![JSS](https://img.shields.io/badge/JSS-10.18637%2Fjss.v052.i05-brightgreen)](https://doi.org/10.18637/jss.v052.i05) -[Rcpp](http://dirk.eddelbuettel.com/code/rcpp.html) Integration for the [Eigen](http://eigen.tuxfamily.org) Templated Linear Algebra Library -[Eigen](http://eigen.tuxfamily.org) is a C++ template library for linear -algebra: matrices, vectors, numerical solvers and related algorithms. It -supports dense and sparse matrices on integer, floating point and complex -numbers, decompositions of such matrices, and solutions of linear -systems. Its performance on many algorithms is comparable with some of the -best implementations based on `Lapack` and level-3 `BLAS`. +### Synopsis -The RcppEigen package includes the header files from the Eigen C++ -template library (currently version 3.2.7). Thus users do not need to -install Eigen itself in order to use RcppEigen. +[Eigen](https://libeigen.gitlab.io/) is a C++ template library for linear algebra: +matrices, vectors, numerical solvers and related algorithms. It supports dense and sparse +matrices on integer, floating point and complex numbers, decompositions of such matrices, +and solutions of linear systems. Its performance on many algorithms is comparable with +some of the best implementations based on `Lapack` and level-3 `BLAS`. + +RcppEigen provides an interface from R to and from [Eigen](https://libeigen.gitlab.io/) by +using the facilities offered by the [Rcpp](http://dirk.eddelbuettel.com/code/rcpp.html) +package for seamless R and C++ integration. + +### Examples + +A few examples are over at the [Rcpp Gallery](https://gallery.rcpp.org/tags/eigen/). A simple one is + +```c++ +#include + +// [[Rcpp::depends(RcppEigen)]] + +using Eigen::Map; // 'maps' rather than copies +using Eigen::MatrixXd; // variable size matrix, double precision +using Eigen::VectorXd; // variable size vector, double precision +using Eigen::SelfAdjointEigenSolver; // one of the eigenvalue solvers + +// [[Rcpp::export]] +VectorXd getEigenValues(Map M) { + SelfAdjointEigenSolver es(M); + return es.eigenvalues(); +} +``` + +which can be turned into a function callable from R via a simple + +``` +sourceCpp("eigenExample.cpp") +``` + +due to the two Rcpp directives to use headers from the RcppEigen package, and to export +the `getEigenValues()` function -- but read [the full +post](https://gallery.rcpp.org/articles/eigen-eigenvalues/) for details. + + +### Status + +The package is mature and under acthttps://libeigen.gitlab.io/ive development, following the +[Eigen](https://libeigen.gitlab.io/) release cycle. + +### Documentation + +The package contains a pdf vignette which is a pre-print of the [paper by +Bates and Eddelbuettel](https://doi.org/10.18637/jss.v052.i05) in JSS (2013, v52i05). + +### Authors + +Douglas Bates, Dirk Eddelbuettel, Romain Francois, and Yixuan Qiu + +### License + +GPL (>= 2) diff --git a/cleanup b/cleanup index b54b4aa6..8b956a2e 100755 --- a/cleanup +++ b/cleanup @@ -4,5 +4,6 @@ rm -f src/*.o src/*.so \ inst/doc/RcppEigen-unitTests.out \ inst/doc/RcppEigen-unitTests.aux \ inst/doc/RcppEigen-unitTests.log \ - */*~ *~ + */*~ *~ \ + config.log config.status src/Makevars rm -rf autom4te.cache diff --git a/configure b/configure new file mode 100755 index 00000000..585e5b37 --- /dev/null +++ b/configure @@ -0,0 +1,4559 @@ +#! /bin/sh +# Guess values for system-dependent variables and create Makefiles. +# Generated by GNU Autoconf 2.72 for RcppEigen 0.3.4.0.2-1. +# +# Report bugs to . +# +# +# Copyright (C) 1992-1996, 1998-2017, 2020-2023 Free Software Foundation, +# Inc. +# +# +# This configure script is free software; the Free Software Foundation +# gives unlimited permission to copy, distribute and modify it. +## -------------------- ## +## M4sh Initialization. ## +## -------------------- ## + +# Be more Bourne compatible +DUALCASE=1; export DUALCASE # for MKS sh +if test ${ZSH_VERSION+y} && (emulate sh) >/dev/null 2>&1 +then : + emulate sh + NULLCMD=: + # Pre-4.2 versions of Zsh do word splitting on ${1+"$@"}, which + # is contrary to our usage. Disable this feature. + alias -g '${1+"$@"}'='"$@"' + setopt NO_GLOB_SUBST +else case e in #( + e) case `(set -o) 2>/dev/null` in #( + *posix*) : + set -o posix ;; #( + *) : + ;; +esac ;; +esac +fi + + + +# Reset variables that may have inherited troublesome values from +# the environment. + +# IFS needs to be set, to space, tab, and newline, in precisely that order. +# (If _AS_PATH_WALK were called with IFS unset, it would have the +# side effect of setting IFS to empty, thus disabling word splitting.) +# Quoting is to prevent editors from complaining about space-tab. +as_nl=' +' +export as_nl +IFS=" "" $as_nl" + +PS1='$ ' +PS2='> ' +PS4='+ ' + +# Ensure predictable behavior from utilities with locale-dependent output. +LC_ALL=C +export LC_ALL +LANGUAGE=C +export LANGUAGE + +# We cannot yet rely on "unset" to work, but we need these variables +# to be unset--not just set to an empty or harmless value--now, to +# avoid bugs in old shells (e.g. pre-3.0 UWIN ksh). This construct +# also avoids known problems related to "unset" and subshell syntax +# in other old shells (e.g. bash 2.01 and pdksh 5.2.14). +for as_var in BASH_ENV ENV MAIL MAILPATH CDPATH +do eval test \${$as_var+y} \ + && ( (unset $as_var) || exit 1) >/dev/null 2>&1 && unset $as_var || : +done + +# Ensure that fds 0, 1, and 2 are open. +if (exec 3>&0) 2>/dev/null; then :; else exec 0&1) 2>/dev/null; then :; else exec 1>/dev/null; fi +if (exec 3>&2) ; then :; else exec 2>/dev/null; fi + +# The user is always right. +if ${PATH_SEPARATOR+false} :; then + PATH_SEPARATOR=: + (PATH='/bin;/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 && { + (PATH='/bin:/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 || + PATH_SEPARATOR=';' + } +fi + + +# Find who we are. Look in the path if we contain no directory separator. +as_myself= +case $0 in #(( + *[\\/]* ) as_myself=$0 ;; + *) as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + test -r "$as_dir$0" && as_myself=$as_dir$0 && break + done +IFS=$as_save_IFS + + ;; +esac +# We did not find ourselves, most probably we were run as 'sh COMMAND' +# in which case we are not to be found in the path. +if test "x$as_myself" = x; then + as_myself=$0 +fi +if test ! -f "$as_myself"; then + printf "%s\n" "$as_myself: error: cannot find myself; rerun with an absolute file name" >&2 + exit 1 +fi + + +# Use a proper internal environment variable to ensure we don't fall + # into an infinite loop, continuously re-executing ourselves. + if test x"${_as_can_reexec}" != xno && test "x$CONFIG_SHELL" != x; then + _as_can_reexec=no; export _as_can_reexec; + # We cannot yet assume a decent shell, so we have to provide a +# neutralization value for shells without unset; and this also +# works around shells that cannot unset nonexistent variables. +# Preserve -v and -x to the replacement shell. +BASH_ENV=/dev/null +ENV=/dev/null +(unset BASH_ENV) >/dev/null 2>&1 && unset BASH_ENV ENV +case $- in # (((( + *v*x* | *x*v* ) as_opts=-vx ;; + *v* ) as_opts=-v ;; + *x* ) as_opts=-x ;; + * ) as_opts= ;; +esac +exec $CONFIG_SHELL $as_opts "$as_myself" ${1+"$@"} +# Admittedly, this is quite paranoid, since all the known shells bail +# out after a failed 'exec'. +printf "%s\n" "$0: could not re-execute with $CONFIG_SHELL" >&2 +exit 255 + fi + # We don't want this to propagate to other subprocesses. + { _as_can_reexec=; unset _as_can_reexec;} +if test "x$CONFIG_SHELL" = x; then + as_bourne_compatible="if test \${ZSH_VERSION+y} && (emulate sh) >/dev/null 2>&1 +then : + emulate sh + NULLCMD=: + # Pre-4.2 versions of Zsh do word splitting on \${1+\"\$@\"}, which + # is contrary to our usage. Disable this feature. + alias -g '\${1+\"\$@\"}'='\"\$@\"' + setopt NO_GLOB_SUBST +else case e in #( + e) case \`(set -o) 2>/dev/null\` in #( + *posix*) : + set -o posix ;; #( + *) : + ;; +esac ;; +esac +fi +" + as_required="as_fn_return () { (exit \$1); } +as_fn_success () { as_fn_return 0; } +as_fn_failure () { as_fn_return 1; } +as_fn_ret_success () { return 0; } +as_fn_ret_failure () { return 1; } + +exitcode=0 +as_fn_success || { exitcode=1; echo as_fn_success failed.; } +as_fn_failure && { exitcode=1; echo as_fn_failure succeeded.; } +as_fn_ret_success || { exitcode=1; echo as_fn_ret_success failed.; } +as_fn_ret_failure && { exitcode=1; echo as_fn_ret_failure succeeded.; } +if ( set x; as_fn_ret_success y && test x = \"\$1\" ) +then : + +else case e in #( + e) exitcode=1; echo positional parameters were not saved. ;; +esac +fi +test x\$exitcode = x0 || exit 1 +blah=\$(echo \$(echo blah)) +test x\"\$blah\" = xblah || exit 1 +test -x / || exit 1" + as_suggested=" as_lineno_1=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_1a=\$LINENO + as_lineno_2=";as_suggested=$as_suggested$LINENO;as_suggested=$as_suggested" as_lineno_2a=\$LINENO + eval 'test \"x\$as_lineno_1'\$as_run'\" != \"x\$as_lineno_2'\$as_run'\" && + test \"x\`expr \$as_lineno_1'\$as_run' + 1\`\" = \"x\$as_lineno_2'\$as_run'\"' || exit 1" + if (eval "$as_required") 2>/dev/null +then : + as_have_required=yes +else case e in #( + e) as_have_required=no ;; +esac +fi + if test x$as_have_required = xyes && (eval "$as_suggested") 2>/dev/null +then : + +else case e in #( + e) as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +as_found=false +for as_dir in /bin$PATH_SEPARATOR/usr/bin$PATH_SEPARATOR$PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + as_found=: + case $as_dir in #( + /*) + for as_base in sh bash ksh sh5; do + # Try only shells that exist, to save several forks. + as_shell=$as_dir$as_base + if { test -f "$as_shell" || test -f "$as_shell.exe"; } && + as_run=a "$as_shell" -c "$as_bourne_compatible""$as_required" 2>/dev/null +then : + CONFIG_SHELL=$as_shell as_have_required=yes + if as_run=a "$as_shell" -c "$as_bourne_compatible""$as_suggested" 2>/dev/null +then : + break 2 +fi +fi + done;; + esac + as_found=false +done +IFS=$as_save_IFS +if $as_found +then : + +else case e in #( + e) if { test -f "$SHELL" || test -f "$SHELL.exe"; } && + as_run=a "$SHELL" -c "$as_bourne_compatible""$as_required" 2>/dev/null +then : + CONFIG_SHELL=$SHELL as_have_required=yes +fi ;; +esac +fi + + + if test "x$CONFIG_SHELL" != x +then : + export CONFIG_SHELL + # We cannot yet assume a decent shell, so we have to provide a +# neutralization value for shells without unset; and this also +# works around shells that cannot unset nonexistent variables. +# Preserve -v and -x to the replacement shell. +BASH_ENV=/dev/null +ENV=/dev/null +(unset BASH_ENV) >/dev/null 2>&1 && unset BASH_ENV ENV +case $- in # (((( + *v*x* | *x*v* ) as_opts=-vx ;; + *v* ) as_opts=-v ;; + *x* ) as_opts=-x ;; + * ) as_opts= ;; +esac +exec $CONFIG_SHELL $as_opts "$as_myself" ${1+"$@"} +# Admittedly, this is quite paranoid, since all the known shells bail +# out after a failed 'exec'. +printf "%s\n" "$0: could not re-execute with $CONFIG_SHELL" >&2 +exit 255 +fi + + if test x$as_have_required = xno +then : + printf "%s\n" "$0: This script requires a shell more modern than all" + printf "%s\n" "$0: the shells that I found on your system." + if test ${ZSH_VERSION+y} ; then + printf "%s\n" "$0: In particular, zsh $ZSH_VERSION has bugs and should" + printf "%s\n" "$0: be upgraded to zsh 4.3.4 or later." + else + printf "%s\n" "$0: Please tell bug-autoconf@gnu.org and edd@debian.org +$0: about your system, including any error possibly output +$0: before this message. Then install a modern shell, or +$0: manually run the script under such a shell if you do +$0: have one." + fi + exit 1 +fi ;; +esac +fi +fi +SHELL=${CONFIG_SHELL-/bin/sh} +export SHELL +# Unset more variables known to interfere with behavior of common tools. +CLICOLOR_FORCE= GREP_OPTIONS= +unset CLICOLOR_FORCE GREP_OPTIONS + +## --------------------- ## +## M4sh Shell Functions. ## +## --------------------- ## +# as_fn_unset VAR +# --------------- +# Portably unset VAR. +as_fn_unset () +{ + { eval $1=; unset $1;} +} +as_unset=as_fn_unset + + +# as_fn_set_status STATUS +# ----------------------- +# Set $? to STATUS, without forking. +as_fn_set_status () +{ + return $1 +} # as_fn_set_status + +# as_fn_exit STATUS +# ----------------- +# Exit the shell with STATUS, even in a "trap 0" or "set -e" context. +as_fn_exit () +{ + set +e + as_fn_set_status $1 + exit $1 +} # as_fn_exit + +# as_fn_mkdir_p +# ------------- +# Create "$as_dir" as a directory, including parents if necessary. +as_fn_mkdir_p () +{ + + case $as_dir in #( + -*) as_dir=./$as_dir;; + esac + test -d "$as_dir" || eval $as_mkdir_p || { + as_dirs= + while :; do + case $as_dir in #( + *\'*) as_qdir=`printf "%s\n" "$as_dir" | sed "s/'/'\\\\\\\\''/g"`;; #'( + *) as_qdir=$as_dir;; + esac + as_dirs="'$as_qdir' $as_dirs" + as_dir=`$as_dirname -- "$as_dir" || +$as_expr X"$as_dir" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \ + X"$as_dir" : 'X\(//\)[^/]' \| \ + X"$as_dir" : 'X\(//\)$' \| \ + X"$as_dir" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X"$as_dir" | + sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{ + s//\1/ + q + } + /^X\(\/\/\)[^/].*/{ + s//\1/ + q + } + /^X\(\/\/\)$/{ + s//\1/ + q + } + /^X\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + test -d "$as_dir" && break + done + test -z "$as_dirs" || eval "mkdir $as_dirs" + } || test -d "$as_dir" || as_fn_error $? "cannot create directory $as_dir" + + +} # as_fn_mkdir_p + +# as_fn_executable_p FILE +# ----------------------- +# Test if FILE is an executable regular file. +as_fn_executable_p () +{ + test -f "$1" && test -x "$1" +} # as_fn_executable_p +# as_fn_append VAR VALUE +# ---------------------- +# Append the text in VALUE to the end of the definition contained in VAR. Take +# advantage of any shell optimizations that allow amortized linear growth over +# repeated appends, instead of the typical quadratic growth present in naive +# implementations. +if (eval "as_var=1; as_var+=2; test x\$as_var = x12") 2>/dev/null +then : + eval 'as_fn_append () + { + eval $1+=\$2 + }' +else case e in #( + e) as_fn_append () + { + eval $1=\$$1\$2 + } ;; +esac +fi # as_fn_append + +# as_fn_arith ARG... +# ------------------ +# Perform arithmetic evaluation on the ARGs, and store the result in the +# global $as_val. Take advantage of shells that can avoid forks. The arguments +# must be portable across $(()) and expr. +if (eval "test \$(( 1 + 1 )) = 2") 2>/dev/null +then : + eval 'as_fn_arith () + { + as_val=$(( $* )) + }' +else case e in #( + e) as_fn_arith () + { + as_val=`expr "$@" || test $? -eq 1` + } ;; +esac +fi # as_fn_arith + + +# as_fn_error STATUS ERROR [LINENO LOG_FD] +# ---------------------------------------- +# Output "`basename $0`: error: ERROR" to stderr. If LINENO and LOG_FD are +# provided, also output the error to LOG_FD, referencing LINENO. Then exit the +# script with STATUS, using 1 if that was 0. +as_fn_error () +{ + as_status=$1; test $as_status -eq 0 && as_status=1 + if test "$4"; then + as_lineno=${as_lineno-"$3"} as_lineno_stack=as_lineno_stack=$as_lineno_stack + printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: $2" >&$4 + fi + printf "%s\n" "$as_me: error: $2" >&2 + as_fn_exit $as_status +} # as_fn_error + +if expr a : '\(a\)' >/dev/null 2>&1 && + test "X`expr 00001 : '.*\(...\)'`" = X001; then + as_expr=expr +else + as_expr=false +fi + +if (basename -- /) >/dev/null 2>&1 && test "X`basename -- / 2>&1`" = "X/"; then + as_basename=basename +else + as_basename=false +fi + +if (as_dir=`dirname -- /` && test "X$as_dir" = X/) >/dev/null 2>&1; then + as_dirname=dirname +else + as_dirname=false +fi + +as_me=`$as_basename -- "$0" || +$as_expr X/"$0" : '.*/\([^/][^/]*\)/*$' \| \ + X"$0" : 'X\(//\)$' \| \ + X"$0" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X/"$0" | + sed '/^.*\/\([^/][^/]*\)\/*$/{ + s//\1/ + q + } + /^X\/\(\/\/\)$/{ + s//\1/ + q + } + /^X\/\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + +# Avoid depending upon Character Ranges. +as_cr_letters='abcdefghijklmnopqrstuvwxyz' +as_cr_LETTERS='ABCDEFGHIJKLMNOPQRSTUVWXYZ' +as_cr_Letters=$as_cr_letters$as_cr_LETTERS +as_cr_digits='0123456789' +as_cr_alnum=$as_cr_Letters$as_cr_digits + + + as_lineno_1=$LINENO as_lineno_1a=$LINENO + as_lineno_2=$LINENO as_lineno_2a=$LINENO + eval 'test "x$as_lineno_1'$as_run'" != "x$as_lineno_2'$as_run'" && + test "x`expr $as_lineno_1'$as_run' + 1`" = "x$as_lineno_2'$as_run'"' || { + # Blame Lee E. McMahon (1931-1989) for sed's syntax. :-) + sed -n ' + p + /[$]LINENO/= + ' <$as_myself | + sed ' + t clear + :clear + s/[$]LINENO.*/&-/ + t lineno + b + :lineno + N + :loop + s/[$]LINENO\([^'$as_cr_alnum'_].*\n\)\(.*\)/\2\1\2/ + t loop + s/-\n.*// + ' >$as_me.lineno && + chmod +x "$as_me.lineno" || + { printf "%s\n" "$as_me: error: cannot create $as_me.lineno; rerun with a POSIX shell" >&2; as_fn_exit 1; } + + # If we had to re-execute with $CONFIG_SHELL, we're ensured to have + # already done that, so ensure we don't try to do so again and fall + # in an infinite loop. This has already happened in practice. + _as_can_reexec=no; export _as_can_reexec + # Don't try to exec as it changes $[0], causing all sort of problems + # (the dirname of $[0] is not the place where we might find the + # original and so on. Autoconf is especially sensitive to this). + . "./$as_me.lineno" + # Exit status is that of the last command. + exit +} + + +# Determine whether it's possible to make 'echo' print without a newline. +# These variables are no longer used directly by Autoconf, but are AC_SUBSTed +# for compatibility with existing Makefiles. +ECHO_C= ECHO_N= ECHO_T= +case `echo -n x` in #((((( +-n*) + case `echo 'xy\c'` in + *c*) ECHO_T=' ';; # ECHO_T is single tab character. + xy) ECHO_C='\c';; + *) echo `echo ksh88 bug on AIX 6.1` > /dev/null + ECHO_T=' ';; + esac;; +*) + ECHO_N='-n';; +esac + +# For backward compatibility with old third-party macros, we provide +# the shell variables $as_echo and $as_echo_n. New code should use +# AS_ECHO(["message"]) and AS_ECHO_N(["message"]), respectively. +as_echo='printf %s\n' +as_echo_n='printf %s' + +rm -f conf$$ conf$$.exe conf$$.file +if test -d conf$$.dir; then + rm -f conf$$.dir/conf$$.file +else + rm -f conf$$.dir + mkdir conf$$.dir 2>/dev/null +fi +if (echo >conf$$.file) 2>/dev/null; then + if ln -s conf$$.file conf$$ 2>/dev/null; then + as_ln_s='ln -s' + # ... but there are two gotchas: + # 1) On MSYS, both 'ln -s file dir' and 'ln file dir' fail. + # 2) DJGPP < 2.04 has no symlinks; 'ln -s' creates a wrapper executable. + # In both cases, we have to default to 'cp -pR'. + ln -s conf$$.file conf$$.dir 2>/dev/null && test ! -f conf$$.exe || + as_ln_s='cp -pR' + elif ln conf$$.file conf$$ 2>/dev/null; then + as_ln_s=ln + else + as_ln_s='cp -pR' + fi +else + as_ln_s='cp -pR' +fi +rm -f conf$$ conf$$.exe conf$$.dir/conf$$.file conf$$.file +rmdir conf$$.dir 2>/dev/null + +if mkdir -p . 2>/dev/null; then + as_mkdir_p='mkdir -p "$as_dir"' +else + test -d ./-p && rmdir ./-p + as_mkdir_p=false +fi + +as_test_x='test -x' +as_executable_p=as_fn_executable_p + +# Sed expression to map a string onto a valid CPP name. +as_sed_cpp="y%*$as_cr_letters%P$as_cr_LETTERS%;s%[^_$as_cr_alnum]%_%g" +as_tr_cpp="eval sed '$as_sed_cpp'" # deprecated + +# Sed expression to map a string onto a valid variable name. +as_sed_sh="y%*+%pp%;s%[^_$as_cr_alnum]%_%g" +as_tr_sh="eval sed '$as_sed_sh'" # deprecated + + +test -n "$DJDIR" || exec 7<&0 &1 + +# Name of the host. +# hostname on some systems (SVR3.2, old GNU/Linux) returns a bogus exit status, +# so uname gets run too. +ac_hostname=`(hostname || uname -n) 2>/dev/null | sed 1q` + +# +# Initializations. +# +ac_default_prefix=/usr/local +ac_clean_files= +ac_config_libobj_dir=. +LIBOBJS= +cross_compiling=no +subdirs= +MFLAGS= +MAKEFLAGS= + +# Identity of this package. +PACKAGE_NAME='RcppEigen' +PACKAGE_TARNAME='rcppeigen' +PACKAGE_VERSION='0.3.4.0.2-1' +PACKAGE_STRING='RcppEigen 0.3.4.0.2-1' +PACKAGE_BUGREPORT='edd@debian.org' +PACKAGE_URL='' + +ac_subst_vars='LTLIBOBJS +LIBOBJS +PKG_LIBS +PKG_CXXFLAGS +OPENMP_FLAG +CXXCPP +OBJEXT +EXEEXT +ac_ct_CXX +CPPFLAGS +LDFLAGS +CXXFLAGS +CXX +target_alias +host_alias +build_alias +LIBS +ECHO_T +ECHO_N +ECHO_C +DEFS +mandir +localedir +libdir +psdir +pdfdir +dvidir +htmldir +infodir +docdir +oldincludedir +includedir +runstatedir +localstatedir +sharedstatedir +sysconfdir +datadir +datarootdir +libexecdir +sbindir +bindir +program_transform_name +prefix +exec_prefix +PACKAGE_URL +PACKAGE_BUGREPORT +PACKAGE_STRING +PACKAGE_VERSION +PACKAGE_TARNAME +PACKAGE_NAME +PATH_SEPARATOR +SHELL' +ac_subst_files='' +ac_user_opts=' +enable_option_checking +' + ac_precious_vars='build_alias +host_alias +target_alias +CXX +CXXFLAGS +LDFLAGS +LIBS +CPPFLAGS +CCC +CXXCPP' + + +# Initialize some variables set by options. +ac_init_help= +ac_init_version=false +ac_unrecognized_opts= +ac_unrecognized_sep= +# The variables have the same names as the options, with +# dashes changed to underlines. +cache_file=/dev/null +exec_prefix=NONE +no_create= +no_recursion= +prefix=NONE +program_prefix=NONE +program_suffix=NONE +program_transform_name=s,x,x, +silent= +site= +srcdir= +verbose= +x_includes=NONE +x_libraries=NONE + +# Installation directory options. +# These are left unexpanded so users can "make install exec_prefix=/foo" +# and all the variables that are supposed to be based on exec_prefix +# by default will actually change. +# Use braces instead of parens because sh, perl, etc. also accept them. +# (The list follows the same order as the GNU Coding Standards.) +bindir='${exec_prefix}/bin' +sbindir='${exec_prefix}/sbin' +libexecdir='${exec_prefix}/libexec' +datarootdir='${prefix}/share' +datadir='${datarootdir}' +sysconfdir='${prefix}/etc' +sharedstatedir='${prefix}/com' +localstatedir='${prefix}/var' +runstatedir='${localstatedir}/run' +includedir='${prefix}/include' +oldincludedir='/usr/include' +docdir='${datarootdir}/doc/${PACKAGE_TARNAME}' +infodir='${datarootdir}/info' +htmldir='${docdir}' +dvidir='${docdir}' +pdfdir='${docdir}' +psdir='${docdir}' +libdir='${exec_prefix}/lib' +localedir='${datarootdir}/locale' +mandir='${datarootdir}/man' + +ac_prev= +ac_dashdash= +for ac_option +do + # If the previous option needs an argument, assign it. + if test -n "$ac_prev"; then + eval $ac_prev=\$ac_option + ac_prev= + continue + fi + + case $ac_option in + *=?*) ac_optarg=`expr "X$ac_option" : '[^=]*=\(.*\)'` ;; + *=) ac_optarg= ;; + *) ac_optarg=yes ;; + esac + + case $ac_dashdash$ac_option in + --) + ac_dashdash=yes ;; + + -bindir | --bindir | --bindi | --bind | --bin | --bi) + ac_prev=bindir ;; + -bindir=* | --bindir=* | --bindi=* | --bind=* | --bin=* | --bi=*) + bindir=$ac_optarg ;; + + -build | --build | --buil | --bui | --bu) + ac_prev=build_alias ;; + -build=* | --build=* | --buil=* | --bui=* | --bu=*) + build_alias=$ac_optarg ;; + + -cache-file | --cache-file | --cache-fil | --cache-fi \ + | --cache-f | --cache- | --cache | --cach | --cac | --ca | --c) + ac_prev=cache_file ;; + -cache-file=* | --cache-file=* | --cache-fil=* | --cache-fi=* \ + | --cache-f=* | --cache-=* | --cache=* | --cach=* | --cac=* | --ca=* | --c=*) + cache_file=$ac_optarg ;; + + --config-cache | -C) + cache_file=config.cache ;; + + -datadir | --datadir | --datadi | --datad) + ac_prev=datadir ;; + -datadir=* | --datadir=* | --datadi=* | --datad=*) + datadir=$ac_optarg ;; + + -datarootdir | --datarootdir | --datarootdi | --datarootd | --dataroot \ + | --dataroo | --dataro | --datar) + ac_prev=datarootdir ;; + -datarootdir=* | --datarootdir=* | --datarootdi=* | --datarootd=* \ + | --dataroot=* | --dataroo=* | --dataro=* | --datar=*) + datarootdir=$ac_optarg ;; + + -disable-* | --disable-*) + ac_useropt=`expr "x$ac_option" : 'x-*disable-\(.*\)'` + # Reject names that are not valid shell variable names. + expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null && + as_fn_error $? "invalid feature name: '$ac_useropt'" + ac_useropt_orig=$ac_useropt + ac_useropt=`printf "%s\n" "$ac_useropt" | sed 's/[-+.]/_/g'` + case $ac_user_opts in + *" +"enable_$ac_useropt" +"*) ;; + *) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--disable-$ac_useropt_orig" + ac_unrecognized_sep=', ';; + esac + eval enable_$ac_useropt=no ;; + + -docdir | --docdir | --docdi | --doc | --do) + ac_prev=docdir ;; + -docdir=* | --docdir=* | --docdi=* | --doc=* | --do=*) + docdir=$ac_optarg ;; + + -dvidir | --dvidir | --dvidi | --dvid | --dvi | --dv) + ac_prev=dvidir ;; + -dvidir=* | --dvidir=* | --dvidi=* | --dvid=* | --dvi=* | --dv=*) + dvidir=$ac_optarg ;; + + -enable-* | --enable-*) + ac_useropt=`expr "x$ac_option" : 'x-*enable-\([^=]*\)'` + # Reject names that are not valid shell variable names. + expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null && + as_fn_error $? "invalid feature name: '$ac_useropt'" + ac_useropt_orig=$ac_useropt + ac_useropt=`printf "%s\n" "$ac_useropt" | sed 's/[-+.]/_/g'` + case $ac_user_opts in + *" +"enable_$ac_useropt" +"*) ;; + *) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--enable-$ac_useropt_orig" + ac_unrecognized_sep=', ';; + esac + eval enable_$ac_useropt=\$ac_optarg ;; + + -exec-prefix | --exec_prefix | --exec-prefix | --exec-prefi \ + | --exec-pref | --exec-pre | --exec-pr | --exec-p | --exec- \ + | --exec | --exe | --ex) + ac_prev=exec_prefix ;; + -exec-prefix=* | --exec_prefix=* | --exec-prefix=* | --exec-prefi=* \ + | --exec-pref=* | --exec-pre=* | --exec-pr=* | --exec-p=* | --exec-=* \ + | --exec=* | --exe=* | --ex=*) + exec_prefix=$ac_optarg ;; + + -gas | --gas | --ga | --g) + # Obsolete; use --with-gas. + with_gas=yes ;; + + -help | --help | --hel | --he | -h) + ac_init_help=long ;; + -help=r* | --help=r* | --hel=r* | --he=r* | -hr*) + ac_init_help=recursive ;; + -help=s* | --help=s* | --hel=s* | --he=s* | -hs*) + ac_init_help=short ;; + + -host | --host | --hos | --ho) + ac_prev=host_alias ;; + -host=* | --host=* | --hos=* | --ho=*) + host_alias=$ac_optarg ;; + + -htmldir | --htmldir | --htmldi | --htmld | --html | --htm | --ht) + ac_prev=htmldir ;; + -htmldir=* | --htmldir=* | --htmldi=* | --htmld=* | --html=* | --htm=* \ + | --ht=*) + htmldir=$ac_optarg ;; + + -includedir | --includedir | --includedi | --included | --include \ + | --includ | --inclu | --incl | --inc) + ac_prev=includedir ;; + -includedir=* | --includedir=* | --includedi=* | --included=* | --include=* \ + | --includ=* | --inclu=* | --incl=* | --inc=*) + includedir=$ac_optarg ;; + + -infodir | --infodir | --infodi | --infod | --info | --inf) + ac_prev=infodir ;; + -infodir=* | --infodir=* | --infodi=* | --infod=* | --info=* | --inf=*) + infodir=$ac_optarg ;; + + -libdir | --libdir | --libdi | --libd) + ac_prev=libdir ;; + -libdir=* | --libdir=* | --libdi=* | --libd=*) + libdir=$ac_optarg ;; + + -libexecdir | --libexecdir | --libexecdi | --libexecd | --libexec \ + | --libexe | --libex | --libe) + ac_prev=libexecdir ;; + -libexecdir=* | --libexecdir=* | --libexecdi=* | --libexecd=* | --libexec=* \ + | --libexe=* | --libex=* | --libe=*) + libexecdir=$ac_optarg ;; + + -localedir | --localedir | --localedi | --localed | --locale) + ac_prev=localedir ;; + -localedir=* | --localedir=* | --localedi=* | --localed=* | --locale=*) + localedir=$ac_optarg ;; + + -localstatedir | --localstatedir | --localstatedi | --localstated \ + | --localstate | --localstat | --localsta | --localst | --locals) + ac_prev=localstatedir ;; + -localstatedir=* | --localstatedir=* | --localstatedi=* | --localstated=* \ + | --localstate=* | --localstat=* | --localsta=* | --localst=* | --locals=*) + localstatedir=$ac_optarg ;; + + -mandir | --mandir | --mandi | --mand | --man | --ma | --m) + ac_prev=mandir ;; + -mandir=* | --mandir=* | --mandi=* | --mand=* | --man=* | --ma=* | --m=*) + mandir=$ac_optarg ;; + + -nfp | --nfp | --nf) + # Obsolete; use --without-fp. + with_fp=no ;; + + -no-create | --no-create | --no-creat | --no-crea | --no-cre \ + | --no-cr | --no-c | -n) + no_create=yes ;; + + -no-recursion | --no-recursion | --no-recursio | --no-recursi \ + | --no-recurs | --no-recur | --no-recu | --no-rec | --no-re | --no-r) + no_recursion=yes ;; + + -oldincludedir | --oldincludedir | --oldincludedi | --oldincluded \ + | --oldinclude | --oldinclud | --oldinclu | --oldincl | --oldinc \ + | --oldin | --oldi | --old | --ol | --o) + ac_prev=oldincludedir ;; + -oldincludedir=* | --oldincludedir=* | --oldincludedi=* | --oldincluded=* \ + | --oldinclude=* | --oldinclud=* | --oldinclu=* | --oldincl=* | --oldinc=* \ + | --oldin=* | --oldi=* | --old=* | --ol=* | --o=*) + oldincludedir=$ac_optarg ;; + + -prefix | --prefix | --prefi | --pref | --pre | --pr | --p) + ac_prev=prefix ;; + -prefix=* | --prefix=* | --prefi=* | --pref=* | --pre=* | --pr=* | --p=*) + prefix=$ac_optarg ;; + + -program-prefix | --program-prefix | --program-prefi | --program-pref \ + | --program-pre | --program-pr | --program-p) + ac_prev=program_prefix ;; + -program-prefix=* | --program-prefix=* | --program-prefi=* \ + | --program-pref=* | --program-pre=* | --program-pr=* | --program-p=*) + program_prefix=$ac_optarg ;; + + -program-suffix | --program-suffix | --program-suffi | --program-suff \ + | --program-suf | --program-su | --program-s) + ac_prev=program_suffix ;; + -program-suffix=* | --program-suffix=* | --program-suffi=* \ + | --program-suff=* | --program-suf=* | --program-su=* | --program-s=*) + program_suffix=$ac_optarg ;; + + -program-transform-name | --program-transform-name \ + | --program-transform-nam | --program-transform-na \ + | --program-transform-n | --program-transform- \ + | --program-transform | --program-transfor \ + | --program-transfo | --program-transf \ + | --program-trans | --program-tran \ + | --progr-tra | --program-tr | --program-t) + ac_prev=program_transform_name ;; + -program-transform-name=* | --program-transform-name=* \ + | --program-transform-nam=* | --program-transform-na=* \ + | --program-transform-n=* | --program-transform-=* \ + | --program-transform=* | --program-transfor=* \ + | --program-transfo=* | --program-transf=* \ + | --program-trans=* | --program-tran=* \ + | --progr-tra=* | --program-tr=* | --program-t=*) + program_transform_name=$ac_optarg ;; + + -pdfdir | --pdfdir | --pdfdi | --pdfd | --pdf | --pd) + ac_prev=pdfdir ;; + -pdfdir=* | --pdfdir=* | --pdfdi=* | --pdfd=* | --pdf=* | --pd=*) + pdfdir=$ac_optarg ;; + + -psdir | --psdir | --psdi | --psd | --ps) + ac_prev=psdir ;; + -psdir=* | --psdir=* | --psdi=* | --psd=* | --ps=*) + psdir=$ac_optarg ;; + + -q | -quiet | --quiet | --quie | --qui | --qu | --q \ + | -silent | --silent | --silen | --sile | --sil) + silent=yes ;; + + -runstatedir | --runstatedir | --runstatedi | --runstated \ + | --runstate | --runstat | --runsta | --runst | --runs \ + | --run | --ru | --r) + ac_prev=runstatedir ;; + -runstatedir=* | --runstatedir=* | --runstatedi=* | --runstated=* \ + | --runstate=* | --runstat=* | --runsta=* | --runst=* | --runs=* \ + | --run=* | --ru=* | --r=*) + runstatedir=$ac_optarg ;; + + -sbindir | --sbindir | --sbindi | --sbind | --sbin | --sbi | --sb) + ac_prev=sbindir ;; + -sbindir=* | --sbindir=* | --sbindi=* | --sbind=* | --sbin=* \ + | --sbi=* | --sb=*) + sbindir=$ac_optarg ;; + + -sharedstatedir | --sharedstatedir | --sharedstatedi \ + | --sharedstated | --sharedstate | --sharedstat | --sharedsta \ + | --sharedst | --shareds | --shared | --share | --shar \ + | --sha | --sh) + ac_prev=sharedstatedir ;; + -sharedstatedir=* | --sharedstatedir=* | --sharedstatedi=* \ + | --sharedstated=* | --sharedstate=* | --sharedstat=* | --sharedsta=* \ + | --sharedst=* | --shareds=* | --shared=* | --share=* | --shar=* \ + | --sha=* | --sh=*) + sharedstatedir=$ac_optarg ;; + + -site | --site | --sit) + ac_prev=site ;; + -site=* | --site=* | --sit=*) + site=$ac_optarg ;; + + -srcdir | --srcdir | --srcdi | --srcd | --src | --sr) + ac_prev=srcdir ;; + -srcdir=* | --srcdir=* | --srcdi=* | --srcd=* | --src=* | --sr=*) + srcdir=$ac_optarg ;; + + -sysconfdir | --sysconfdir | --sysconfdi | --sysconfd | --sysconf \ + | --syscon | --sysco | --sysc | --sys | --sy) + ac_prev=sysconfdir ;; + -sysconfdir=* | --sysconfdir=* | --sysconfdi=* | --sysconfd=* | --sysconf=* \ + | --syscon=* | --sysco=* | --sysc=* | --sys=* | --sy=*) + sysconfdir=$ac_optarg ;; + + -target | --target | --targe | --targ | --tar | --ta | --t) + ac_prev=target_alias ;; + -target=* | --target=* | --targe=* | --targ=* | --tar=* | --ta=* | --t=*) + target_alias=$ac_optarg ;; + + -v | -verbose | --verbose | --verbos | --verbo | --verb) + verbose=yes ;; + + -version | --version | --versio | --versi | --vers | -V) + ac_init_version=: ;; + + -with-* | --with-*) + ac_useropt=`expr "x$ac_option" : 'x-*with-\([^=]*\)'` + # Reject names that are not valid shell variable names. + expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null && + as_fn_error $? "invalid package name: '$ac_useropt'" + ac_useropt_orig=$ac_useropt + ac_useropt=`printf "%s\n" "$ac_useropt" | sed 's/[-+.]/_/g'` + case $ac_user_opts in + *" +"with_$ac_useropt" +"*) ;; + *) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--with-$ac_useropt_orig" + ac_unrecognized_sep=', ';; + esac + eval with_$ac_useropt=\$ac_optarg ;; + + -without-* | --without-*) + ac_useropt=`expr "x$ac_option" : 'x-*without-\(.*\)'` + # Reject names that are not valid shell variable names. + expr "x$ac_useropt" : ".*[^-+._$as_cr_alnum]" >/dev/null && + as_fn_error $? "invalid package name: '$ac_useropt'" + ac_useropt_orig=$ac_useropt + ac_useropt=`printf "%s\n" "$ac_useropt" | sed 's/[-+.]/_/g'` + case $ac_user_opts in + *" +"with_$ac_useropt" +"*) ;; + *) ac_unrecognized_opts="$ac_unrecognized_opts$ac_unrecognized_sep--without-$ac_useropt_orig" + ac_unrecognized_sep=', ';; + esac + eval with_$ac_useropt=no ;; + + --x) + # Obsolete; use --with-x. + with_x=yes ;; + + -x-includes | --x-includes | --x-include | --x-includ | --x-inclu \ + | --x-incl | --x-inc | --x-in | --x-i) + ac_prev=x_includes ;; + -x-includes=* | --x-includes=* | --x-include=* | --x-includ=* | --x-inclu=* \ + | --x-incl=* | --x-inc=* | --x-in=* | --x-i=*) + x_includes=$ac_optarg ;; + + -x-libraries | --x-libraries | --x-librarie | --x-librari \ + | --x-librar | --x-libra | --x-libr | --x-lib | --x-li | --x-l) + ac_prev=x_libraries ;; + -x-libraries=* | --x-libraries=* | --x-librarie=* | --x-librari=* \ + | --x-librar=* | --x-libra=* | --x-libr=* | --x-lib=* | --x-li=* | --x-l=*) + x_libraries=$ac_optarg ;; + + -*) as_fn_error $? "unrecognized option: '$ac_option' +Try '$0 --help' for more information" + ;; + + *=*) + ac_envvar=`expr "x$ac_option" : 'x\([^=]*\)='` + # Reject names that are not valid shell variable names. + case $ac_envvar in #( + '' | [0-9]* | *[!_$as_cr_alnum]* ) + as_fn_error $? "invalid variable name: '$ac_envvar'" ;; + esac + eval $ac_envvar=\$ac_optarg + export $ac_envvar ;; + + *) + # FIXME: should be removed in autoconf 3.0. + printf "%s\n" "$as_me: WARNING: you should use --build, --host, --target" >&2 + expr "x$ac_option" : ".*[^-._$as_cr_alnum]" >/dev/null && + printf "%s\n" "$as_me: WARNING: invalid host type: $ac_option" >&2 + : "${build_alias=$ac_option} ${host_alias=$ac_option} ${target_alias=$ac_option}" + ;; + + esac +done + +if test -n "$ac_prev"; then + ac_option=--`echo $ac_prev | sed 's/_/-/g'` + as_fn_error $? "missing argument to $ac_option" +fi + +if test -n "$ac_unrecognized_opts"; then + case $enable_option_checking in + no) ;; + fatal) as_fn_error $? "unrecognized options: $ac_unrecognized_opts" ;; + *) printf "%s\n" "$as_me: WARNING: unrecognized options: $ac_unrecognized_opts" >&2 ;; + esac +fi + +# Check all directory arguments for consistency. +for ac_var in exec_prefix prefix bindir sbindir libexecdir datarootdir \ + datadir sysconfdir sharedstatedir localstatedir includedir \ + oldincludedir docdir infodir htmldir dvidir pdfdir psdir \ + libdir localedir mandir runstatedir +do + eval ac_val=\$$ac_var + # Remove trailing slashes. + case $ac_val in + */ ) + ac_val=`expr "X$ac_val" : 'X\(.*[^/]\)' \| "X$ac_val" : 'X\(.*\)'` + eval $ac_var=\$ac_val;; + esac + # Be sure to have absolute directory names. + case $ac_val in + [\\/$]* | ?:[\\/]* ) continue;; + NONE | '' ) case $ac_var in *prefix ) continue;; esac;; + esac + as_fn_error $? "expected an absolute directory name for --$ac_var: $ac_val" +done + +# There might be people who depend on the old broken behavior: '$host' +# used to hold the argument of --host etc. +# FIXME: To remove some day. +build=$build_alias +host=$host_alias +target=$target_alias + +# FIXME: To remove some day. +if test "x$host_alias" != x; then + if test "x$build_alias" = x; then + cross_compiling=maybe + elif test "x$build_alias" != "x$host_alias"; then + cross_compiling=yes + fi +fi + +ac_tool_prefix= +test -n "$host_alias" && ac_tool_prefix=$host_alias- + +test "$silent" = yes && exec 6>/dev/null + + +ac_pwd=`pwd` && test -n "$ac_pwd" && +ac_ls_di=`ls -di .` && +ac_pwd_ls_di=`cd "$ac_pwd" && ls -di .` || + as_fn_error $? "working directory cannot be determined" +test "X$ac_ls_di" = "X$ac_pwd_ls_di" || + as_fn_error $? "pwd does not report name of working directory" + + +# Find the source files, if location was not specified. +if test -z "$srcdir"; then + ac_srcdir_defaulted=yes + # Try the directory containing this script, then the parent directory. + ac_confdir=`$as_dirname -- "$as_myself" || +$as_expr X"$as_myself" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \ + X"$as_myself" : 'X\(//\)[^/]' \| \ + X"$as_myself" : 'X\(//\)$' \| \ + X"$as_myself" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X"$as_myself" | + sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{ + s//\1/ + q + } + /^X\(\/\/\)[^/].*/{ + s//\1/ + q + } + /^X\(\/\/\)$/{ + s//\1/ + q + } + /^X\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + srcdir=$ac_confdir + if test ! -r "$srcdir/$ac_unique_file"; then + srcdir=.. + fi +else + ac_srcdir_defaulted=no +fi +if test ! -r "$srcdir/$ac_unique_file"; then + test "$ac_srcdir_defaulted" = yes && srcdir="$ac_confdir or .." + as_fn_error $? "cannot find sources ($ac_unique_file) in $srcdir" +fi +ac_msg="sources are in $srcdir, but 'cd $srcdir' does not work" +ac_abs_confdir=`( + cd "$srcdir" && test -r "./$ac_unique_file" || as_fn_error $? "$ac_msg" + pwd)` +# When building in place, set srcdir=. +if test "$ac_abs_confdir" = "$ac_pwd"; then + srcdir=. +fi +# Remove unnecessary trailing slashes from srcdir. +# Double slashes in file names in object file debugging info +# mess up M-x gdb in Emacs. +case $srcdir in +*/) srcdir=`expr "X$srcdir" : 'X\(.*[^/]\)' \| "X$srcdir" : 'X\(.*\)'`;; +esac +for ac_var in $ac_precious_vars; do + eval ac_env_${ac_var}_set=\${${ac_var}+set} + eval ac_env_${ac_var}_value=\$${ac_var} + eval ac_cv_env_${ac_var}_set=\${${ac_var}+set} + eval ac_cv_env_${ac_var}_value=\$${ac_var} +done + +# +# Report the --help message. +# +if test "$ac_init_help" = "long"; then + # Omit some internal or obsolete options to make the list less imposing. + # This message is too long to be a string in the A/UX 3.1 sh. + cat <<_ACEOF +'configure' configures RcppEigen 0.3.4.0.2-1 to adapt to many kinds of systems. + +Usage: $0 [OPTION]... [VAR=VALUE]... + +To assign environment variables (e.g., CC, CFLAGS...), specify them as +VAR=VALUE. See below for descriptions of some of the useful variables. + +Defaults for the options are specified in brackets. + +Configuration: + -h, --help display this help and exit + --help=short display options specific to this package + --help=recursive display the short help of all the included packages + -V, --version display version information and exit + -q, --quiet, --silent do not print 'checking ...' messages + --cache-file=FILE cache test results in FILE [disabled] + -C, --config-cache alias for '--cache-file=config.cache' + -n, --no-create do not create output files + --srcdir=DIR find the sources in DIR [configure dir or '..'] + +Installation directories: + --prefix=PREFIX install architecture-independent files in PREFIX + [$ac_default_prefix] + --exec-prefix=EPREFIX install architecture-dependent files in EPREFIX + [PREFIX] + +By default, 'make install' will install all the files in +'$ac_default_prefix/bin', '$ac_default_prefix/lib' etc. You can specify +an installation prefix other than '$ac_default_prefix' using '--prefix', +for instance '--prefix=\$HOME'. + +For better control, use the options below. + +Fine tuning of the installation directories: + --bindir=DIR user executables [EPREFIX/bin] + --sbindir=DIR system admin executables [EPREFIX/sbin] + --libexecdir=DIR program executables [EPREFIX/libexec] + --sysconfdir=DIR read-only single-machine data [PREFIX/etc] + --sharedstatedir=DIR modifiable architecture-independent data [PREFIX/com] + --localstatedir=DIR modifiable single-machine data [PREFIX/var] + --runstatedir=DIR modifiable per-process data [LOCALSTATEDIR/run] + --libdir=DIR object code libraries [EPREFIX/lib] + --includedir=DIR C header files [PREFIX/include] + --oldincludedir=DIR C header files for non-gcc [/usr/include] + --datarootdir=DIR read-only arch.-independent data root [PREFIX/share] + --datadir=DIR read-only architecture-independent data [DATAROOTDIR] + --infodir=DIR info documentation [DATAROOTDIR/info] + --localedir=DIR locale-dependent data [DATAROOTDIR/locale] + --mandir=DIR man documentation [DATAROOTDIR/man] + --docdir=DIR documentation root [DATAROOTDIR/doc/rcppeigen] + --htmldir=DIR html documentation [DOCDIR] + --dvidir=DIR dvi documentation [DOCDIR] + --pdfdir=DIR pdf documentation [DOCDIR] + --psdir=DIR ps documentation [DOCDIR] +_ACEOF + + cat <<\_ACEOF +_ACEOF +fi + +if test -n "$ac_init_help"; then + case $ac_init_help in + short | recursive ) echo "Configuration of RcppEigen 0.3.4.0.2-1:";; + esac + cat <<\_ACEOF + +Some influential environment variables: + CXX C++ compiler command + CXXFLAGS C++ compiler flags + LDFLAGS linker flags, e.g. -L if you have libraries in a + nonstandard directory + LIBS libraries to pass to the linker, e.g. -l + CPPFLAGS (Objective) C/C++ preprocessor flags, e.g. -I if + you have headers in a nonstandard directory + CXXCPP C++ preprocessor + +Use these variables to override the choices made by 'configure' or to help +it to find libraries and programs with nonstandard names/locations. + +Report bugs to . +_ACEOF +ac_status=$? +fi + +if test "$ac_init_help" = "recursive"; then + # If there are subdirs, report their specific --help. + for ac_dir in : $ac_subdirs_all; do test "x$ac_dir" = x: && continue + test -d "$ac_dir" || + { cd "$srcdir" && ac_pwd=`pwd` && srcdir=. && test -d "$ac_dir"; } || + continue + ac_builddir=. + +case "$ac_dir" in +.) ac_dir_suffix= ac_top_builddir_sub=. ac_top_build_prefix= ;; +*) + ac_dir_suffix=/`printf "%s\n" "$ac_dir" | sed 's|^\.[\\/]||'` + # A ".." for each directory in $ac_dir_suffix. + ac_top_builddir_sub=`printf "%s\n" "$ac_dir_suffix" | sed 's|/[^\\/]*|/..|g;s|/||'` + case $ac_top_builddir_sub in + "") ac_top_builddir_sub=. ac_top_build_prefix= ;; + *) ac_top_build_prefix=$ac_top_builddir_sub/ ;; + esac ;; +esac +ac_abs_top_builddir=$ac_pwd +ac_abs_builddir=$ac_pwd$ac_dir_suffix +# for backward compatibility: +ac_top_builddir=$ac_top_build_prefix + +case $srcdir in + .) # We are building in place. + ac_srcdir=. + ac_top_srcdir=$ac_top_builddir_sub + ac_abs_top_srcdir=$ac_pwd ;; + [\\/]* | ?:[\\/]* ) # Absolute name. + ac_srcdir=$srcdir$ac_dir_suffix; + ac_top_srcdir=$srcdir + ac_abs_top_srcdir=$srcdir ;; + *) # Relative name. + ac_srcdir=$ac_top_build_prefix$srcdir$ac_dir_suffix + ac_top_srcdir=$ac_top_build_prefix$srcdir + ac_abs_top_srcdir=$ac_pwd/$srcdir ;; +esac +ac_abs_srcdir=$ac_abs_top_srcdir$ac_dir_suffix + + cd "$ac_dir" || { ac_status=$?; continue; } + # Check for configure.gnu first; this name is used for a wrapper for + # Metaconfig's "Configure" on case-insensitive file systems. + if test -f "$ac_srcdir/configure.gnu"; then + echo && + $SHELL "$ac_srcdir/configure.gnu" --help=recursive + elif test -f "$ac_srcdir/configure"; then + echo && + $SHELL "$ac_srcdir/configure" --help=recursive + else + printf "%s\n" "$as_me: WARNING: no configuration information is in $ac_dir" >&2 + fi || ac_status=$? + cd "$ac_pwd" || { ac_status=$?; break; } + done +fi + +test -n "$ac_init_help" && exit $ac_status +if $ac_init_version; then + cat <<\_ACEOF +RcppEigen configure 0.3.4.0.2-1 +generated by GNU Autoconf 2.72 + +Copyright (C) 2023 Free Software Foundation, Inc. +This configure script is free software; the Free Software Foundation +gives unlimited permission to copy, distribute and modify it. +_ACEOF + exit +fi + +## ------------------------ ## +## Autoconf initialization. ## +## ------------------------ ## + +# ac_fn_cxx_try_compile LINENO +# ---------------------------- +# Try to compile conftest.$ac_ext, and return whether this succeeded. +ac_fn_cxx_try_compile () +{ + as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack + rm -f conftest.$ac_objext conftest.beam + if { { ac_try="$ac_compile" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_compile") 2>conftest.err + ac_status=$? + if test -s conftest.err; then + grep -v '^ *+' conftest.err >conftest.er1 + cat conftest.er1 >&5 + mv -f conftest.er1 conftest.err + fi + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } && { + test -z "$ac_cxx_werror_flag" || + test ! -s conftest.err + } && test -s conftest.$ac_objext +then : + ac_retval=0 +else case e in #( + e) printf "%s\n" "$as_me: failed program was:" >&5 +sed 's/^/| /' conftest.$ac_ext >&5 + + ac_retval=1 ;; +esac +fi + eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno + as_fn_set_status $ac_retval + +} # ac_fn_cxx_try_compile + +# ac_fn_cxx_try_cpp LINENO +# ------------------------ +# Try to preprocess conftest.$ac_ext, and return whether this succeeded. +ac_fn_cxx_try_cpp () +{ + as_lineno=${as_lineno-"$1"} as_lineno_stack=as_lineno_stack=$as_lineno_stack + if { { ac_try="$ac_cpp conftest.$ac_ext" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_cpp conftest.$ac_ext") 2>conftest.err + ac_status=$? + if test -s conftest.err; then + grep -v '^ *+' conftest.err >conftest.er1 + cat conftest.er1 >&5 + mv -f conftest.er1 conftest.err + fi + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } > conftest.i && { + test -z "$ac_cxx_preproc_warn_flag$ac_cxx_werror_flag" || + test ! -s conftest.err + } +then : + ac_retval=0 +else case e in #( + e) printf "%s\n" "$as_me: failed program was:" >&5 +sed 's/^/| /' conftest.$ac_ext >&5 + + ac_retval=1 ;; +esac +fi + eval $as_lineno_stack; ${as_lineno_stack:+:} unset as_lineno + as_fn_set_status $ac_retval + +} # ac_fn_cxx_try_cpp +ac_configure_args_raw= +for ac_arg +do + case $ac_arg in + *\'*) + ac_arg=`printf "%s\n" "$ac_arg" | sed "s/'/'\\\\\\\\''/g"` ;; + esac + as_fn_append ac_configure_args_raw " '$ac_arg'" +done + +case $ac_configure_args_raw in + *$as_nl*) + ac_safe_unquote= ;; + *) + ac_unsafe_z='|&;<>()$`\\"*?[ '' ' # This string ends in space, tab. + ac_unsafe_a="$ac_unsafe_z#~" + ac_safe_unquote="s/ '\\([^$ac_unsafe_a][^$ac_unsafe_z]*\\)'/ \\1/g" + ac_configure_args_raw=` printf "%s\n" "$ac_configure_args_raw" | sed "$ac_safe_unquote"`;; +esac + +cat >config.log <<_ACEOF +This file contains any messages produced by compilers while +running configure, to aid debugging if configure makes a mistake. + +It was created by RcppEigen $as_me 0.3.4.0.2-1, which was +generated by GNU Autoconf 2.72. Invocation command line was + + $ $0$ac_configure_args_raw + +_ACEOF +exec 5>>config.log +{ +cat <<_ASUNAME +## --------- ## +## Platform. ## +## --------- ## + +hostname = `(hostname || uname -n) 2>/dev/null | sed 1q` +uname -m = `(uname -m) 2>/dev/null || echo unknown` +uname -r = `(uname -r) 2>/dev/null || echo unknown` +uname -s = `(uname -s) 2>/dev/null || echo unknown` +uname -v = `(uname -v) 2>/dev/null || echo unknown` + +/usr/bin/uname -p = `(/usr/bin/uname -p) 2>/dev/null || echo unknown` +/bin/uname -X = `(/bin/uname -X) 2>/dev/null || echo unknown` + +/bin/arch = `(/bin/arch) 2>/dev/null || echo unknown` +/usr/bin/arch -k = `(/usr/bin/arch -k) 2>/dev/null || echo unknown` +/usr/convex/getsysinfo = `(/usr/convex/getsysinfo) 2>/dev/null || echo unknown` +/usr/bin/hostinfo = `(/usr/bin/hostinfo) 2>/dev/null || echo unknown` +/bin/machine = `(/bin/machine) 2>/dev/null || echo unknown` +/usr/bin/oslevel = `(/usr/bin/oslevel) 2>/dev/null || echo unknown` +/bin/universe = `(/bin/universe) 2>/dev/null || echo unknown` + +_ASUNAME + +as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + printf "%s\n" "PATH: $as_dir" + done +IFS=$as_save_IFS + +} >&5 + +cat >&5 <<_ACEOF + + +## ----------- ## +## Core tests. ## +## ----------- ## + +_ACEOF + + +# Keep a trace of the command line. +# Strip out --no-create and --no-recursion so they do not pile up. +# Strip out --silent because we don't want to record it for future runs. +# Also quote any args containing shell meta-characters. +# Make two passes to allow for proper duplicate-argument suppression. +ac_configure_args= +ac_configure_args0= +ac_configure_args1= +ac_must_keep_next=false +for ac_pass in 1 2 +do + for ac_arg + do + case $ac_arg in + -no-create | --no-c* | -n | -no-recursion | --no-r*) continue ;; + -q | -quiet | --quiet | --quie | --qui | --qu | --q \ + | -silent | --silent | --silen | --sile | --sil) + continue ;; + *\'*) + ac_arg=`printf "%s\n" "$ac_arg" | sed "s/'/'\\\\\\\\''/g"` ;; + esac + case $ac_pass in + 1) as_fn_append ac_configure_args0 " '$ac_arg'" ;; + 2) + as_fn_append ac_configure_args1 " '$ac_arg'" + if test $ac_must_keep_next = true; then + ac_must_keep_next=false # Got value, back to normal. + else + case $ac_arg in + *=* | --config-cache | -C | -disable-* | --disable-* \ + | -enable-* | --enable-* | -gas | --g* | -nfp | --nf* \ + | -q | -quiet | --q* | -silent | --sil* | -v | -verb* \ + | -with-* | --with-* | -without-* | --without-* | --x) + case "$ac_configure_args0 " in + "$ac_configure_args1"*" '$ac_arg' "* ) continue ;; + esac + ;; + -* ) ac_must_keep_next=true ;; + esac + fi + as_fn_append ac_configure_args " '$ac_arg'" + ;; + esac + done +done +{ ac_configure_args0=; unset ac_configure_args0;} +{ ac_configure_args1=; unset ac_configure_args1;} + +# When interrupted or exit'd, cleanup temporary files, and complete +# config.log. We remove comments because anyway the quotes in there +# would cause problems or look ugly. +# WARNING: Use '\'' to represent an apostrophe within the trap. +# WARNING: Do not start the trap code with a newline, due to a FreeBSD 4.0 bug. +trap 'exit_status=$? + # Sanitize IFS. + IFS=" "" $as_nl" + # Save into config.log some information that might help in debugging. + { + echo + + printf "%s\n" "## ---------------- ## +## Cache variables. ## +## ---------------- ##" + echo + # The following way of writing the cache mishandles newlines in values, +( + for ac_var in `(set) 2>&1 | sed -n '\''s/^\([a-zA-Z_][a-zA-Z0-9_]*\)=.*/\1/p'\''`; do + eval ac_val=\$$ac_var + case $ac_val in #( + *${as_nl}*) + case $ac_var in #( + *_cv_*) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: cache variable $ac_var contains a newline" >&5 +printf "%s\n" "$as_me: WARNING: cache variable $ac_var contains a newline" >&2;} ;; + esac + case $ac_var in #( + _ | IFS | as_nl) ;; #( + BASH_ARGV | BASH_SOURCE) eval $ac_var= ;; #( + *) { eval $ac_var=; unset $ac_var;} ;; + esac ;; + esac + done + (set) 2>&1 | + case $as_nl`(ac_space='\'' '\''; set) 2>&1` in #( + *${as_nl}ac_space=\ *) + sed -n \ + "s/'\''/'\''\\\\'\'''\''/g; + s/^\\([_$as_cr_alnum]*_cv_[_$as_cr_alnum]*\\)=\\(.*\\)/\\1='\''\\2'\''/p" + ;; #( + *) + sed -n "/^[_$as_cr_alnum]*_cv_[_$as_cr_alnum]*=/p" + ;; + esac | + sort +) + echo + + printf "%s\n" "## ----------------- ## +## Output variables. ## +## ----------------- ##" + echo + for ac_var in $ac_subst_vars + do + eval ac_val=\$$ac_var + case $ac_val in + *\'\''*) ac_val=`printf "%s\n" "$ac_val" | sed "s/'\''/'\''\\\\\\\\'\'''\''/g"`;; + esac + printf "%s\n" "$ac_var='\''$ac_val'\''" + done | sort + echo + + if test -n "$ac_subst_files"; then + printf "%s\n" "## ------------------- ## +## File substitutions. ## +## ------------------- ##" + echo + for ac_var in $ac_subst_files + do + eval ac_val=\$$ac_var + case $ac_val in + *\'\''*) ac_val=`printf "%s\n" "$ac_val" | sed "s/'\''/'\''\\\\\\\\'\'''\''/g"`;; + esac + printf "%s\n" "$ac_var='\''$ac_val'\''" + done | sort + echo + fi + + if test -s confdefs.h; then + printf "%s\n" "## ----------- ## +## confdefs.h. ## +## ----------- ##" + echo + cat confdefs.h + echo + fi + test "$ac_signal" != 0 && + printf "%s\n" "$as_me: caught signal $ac_signal" + printf "%s\n" "$as_me: exit $exit_status" + } >&5 + rm -f core *.core core.conftest.* && + rm -f -r conftest* confdefs* conf$$* $ac_clean_files && + exit $exit_status +' 0 +for ac_signal in 1 2 13 15; do + trap 'ac_signal='$ac_signal'; as_fn_exit 1' $ac_signal +done +ac_signal=0 + +# confdefs.h avoids OS command line length limits that DEFS can exceed. +rm -f -r conftest* confdefs.h + +printf "%s\n" "/* confdefs.h */" > confdefs.h + +# Predefined preprocessor variables. + +printf "%s\n" "#define PACKAGE_NAME \"$PACKAGE_NAME\"" >>confdefs.h + +printf "%s\n" "#define PACKAGE_TARNAME \"$PACKAGE_TARNAME\"" >>confdefs.h + +printf "%s\n" "#define PACKAGE_VERSION \"$PACKAGE_VERSION\"" >>confdefs.h + +printf "%s\n" "#define PACKAGE_STRING \"$PACKAGE_STRING\"" >>confdefs.h + +printf "%s\n" "#define PACKAGE_BUGREPORT \"$PACKAGE_BUGREPORT\"" >>confdefs.h + +printf "%s\n" "#define PACKAGE_URL \"$PACKAGE_URL\"" >>confdefs.h + + +# Let the site file select an alternate cache file if it wants to. +# Prefer an explicitly selected file to automatically selected ones. +if test -n "$CONFIG_SITE"; then + ac_site_files="$CONFIG_SITE" +elif test "x$prefix" != xNONE; then + ac_site_files="$prefix/share/config.site $prefix/etc/config.site" +else + ac_site_files="$ac_default_prefix/share/config.site $ac_default_prefix/etc/config.site" +fi + +for ac_site_file in $ac_site_files +do + case $ac_site_file in #( + */*) : + ;; #( + *) : + ac_site_file=./$ac_site_file ;; +esac + if test -f "$ac_site_file" && test -r "$ac_site_file"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: loading site script $ac_site_file" >&5 +printf "%s\n" "$as_me: loading site script $ac_site_file" >&6;} + sed 's/^/| /' "$ac_site_file" >&5 + . "$ac_site_file" \ + || { { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error $? "failed to load site script $ac_site_file +See 'config.log' for more details" "$LINENO" 5; } + fi +done + +if test -r "$cache_file"; then + # Some versions of bash will fail to source /dev/null (special files + # actually), so we avoid doing that. DJGPP emulates it as a regular file. + if test /dev/null != "$cache_file" && test -f "$cache_file"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: loading cache $cache_file" >&5 +printf "%s\n" "$as_me: loading cache $cache_file" >&6;} + case $cache_file in + [\\/]* | ?:[\\/]* ) . "$cache_file";; + *) . "./$cache_file";; + esac + fi +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: creating cache $cache_file" >&5 +printf "%s\n" "$as_me: creating cache $cache_file" >&6;} + >$cache_file +fi + +# Test code for whether the C++ compiler supports C++98 (global declarations) +ac_cxx_conftest_cxx98_globals=' +// Does the compiler advertise C++98 conformance? +#if !defined __cplusplus || __cplusplus < 199711L +# error "Compiler does not advertise C++98 conformance" +#endif + +// These inclusions are to reject old compilers that +// lack the unsuffixed header files. +#include +#include + +// and are *not* freestanding headers in C++98. +extern void assert (int); +namespace std { + extern int strcmp (const char *, const char *); +} + +// Namespaces, exceptions, and templates were all added after "C++ 2.0". +using std::exception; +using std::strcmp; + +namespace { + +void test_exception_syntax() +{ + try { + throw "test"; + } catch (const char *s) { + // Extra parentheses suppress a warning when building autoconf itself, + // due to lint rules shared with more typical C programs. + assert (!(strcmp) (s, "test")); + } +} + +template struct test_template +{ + T const val; + explicit test_template(T t) : val(t) {} + template T add(U u) { return static_cast(u) + val; } +}; + +} // anonymous namespace +' + +# Test code for whether the C++ compiler supports C++98 (body of main) +ac_cxx_conftest_cxx98_main=' + assert (argc); + assert (! argv[0]); +{ + test_exception_syntax (); + test_template tt (2.0); + assert (tt.add (4) == 6.0); + assert (true && !false); +} +' + +# Test code for whether the C++ compiler supports C++11 (global declarations) +ac_cxx_conftest_cxx11_globals=' +// Does the compiler advertise C++ 2011 conformance? +#if !defined __cplusplus || __cplusplus < 201103L +# error "Compiler does not advertise C++11 conformance" +#endif + +namespace cxx11test +{ + constexpr int get_val() { return 20; } + + struct testinit + { + int i; + double d; + }; + + class delegate + { + public: + delegate(int n) : n(n) {} + delegate(): delegate(2354) {} + + virtual int getval() { return this->n; }; + protected: + int n; + }; + + class overridden : public delegate + { + public: + overridden(int n): delegate(n) {} + virtual int getval() override final { return this->n * 2; } + }; + + class nocopy + { + public: + nocopy(int i): i(i) {} + nocopy() = default; + nocopy(const nocopy&) = delete; + nocopy & operator=(const nocopy&) = delete; + private: + int i; + }; + + // for testing lambda expressions + template Ret eval(Fn f, Ret v) + { + return f(v); + } + + // for testing variadic templates and trailing return types + template auto sum(V first) -> V + { + return first; + } + template auto sum(V first, Args... rest) -> V + { + return first + sum(rest...); + } +} +' + +# Test code for whether the C++ compiler supports C++11 (body of main) +ac_cxx_conftest_cxx11_main=' +{ + // Test auto and decltype + auto a1 = 6538; + auto a2 = 48573953.4; + auto a3 = "String literal"; + + int total = 0; + for (auto i = a3; *i; ++i) { total += *i; } + + decltype(a2) a4 = 34895.034; +} +{ + // Test constexpr + short sa[cxx11test::get_val()] = { 0 }; +} +{ + // Test initializer lists + cxx11test::testinit il = { 4323, 435234.23544 }; +} +{ + // Test range-based for + int array[] = {9, 7, 13, 15, 4, 18, 12, 10, 5, 3, + 14, 19, 17, 8, 6, 20, 16, 2, 11, 1}; + for (auto &x : array) { x += 23; } +} +{ + // Test lambda expressions + using cxx11test::eval; + assert (eval ([](int x) { return x*2; }, 21) == 42); + double d = 2.0; + assert (eval ([&](double x) { return d += x; }, 3.0) == 5.0); + assert (d == 5.0); + assert (eval ([=](double x) mutable { return d += x; }, 4.0) == 9.0); + assert (d == 5.0); +} +{ + // Test use of variadic templates + using cxx11test::sum; + auto a = sum(1); + auto b = sum(1, 2); + auto c = sum(1.0, 2.0, 3.0); +} +{ + // Test constructor delegation + cxx11test::delegate d1; + cxx11test::delegate d2(); + cxx11test::delegate d3(45); +} +{ + // Test override and final + cxx11test::overridden o1(55464); +} +{ + // Test nullptr + char *c = nullptr; +} +{ + // Test template brackets + test_template<::test_template> v(test_template(12)); +} +{ + // Unicode literals + char const *utf8 = u8"UTF-8 string \u2500"; + char16_t const *utf16 = u"UTF-8 string \u2500"; + char32_t const *utf32 = U"UTF-32 string \u2500"; +} +' + +# Test code for whether the C compiler supports C++11 (complete). +ac_cxx_conftest_cxx11_program="${ac_cxx_conftest_cxx98_globals} +${ac_cxx_conftest_cxx11_globals} + +int +main (int argc, char **argv) +{ + int ok = 0; + ${ac_cxx_conftest_cxx98_main} + ${ac_cxx_conftest_cxx11_main} + return ok; +} +" + +# Test code for whether the C compiler supports C++98 (complete). +ac_cxx_conftest_cxx98_program="${ac_cxx_conftest_cxx98_globals} +int +main (int argc, char **argv) +{ + int ok = 0; + ${ac_cxx_conftest_cxx98_main} + return ok; +} +" + +# Check that the precious variables saved in the cache have kept the same +# value. +ac_cache_corrupted=false +for ac_var in $ac_precious_vars; do + eval ac_old_set=\$ac_cv_env_${ac_var}_set + eval ac_new_set=\$ac_env_${ac_var}_set + eval ac_old_val=\$ac_cv_env_${ac_var}_value + eval ac_new_val=\$ac_env_${ac_var}_value + case $ac_old_set,$ac_new_set in + set,) + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: '$ac_var' was set to '$ac_old_val' in the previous run" >&5 +printf "%s\n" "$as_me: error: '$ac_var' was set to '$ac_old_val' in the previous run" >&2;} + ac_cache_corrupted=: ;; + ,set) + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: '$ac_var' was not set in the previous run" >&5 +printf "%s\n" "$as_me: error: '$ac_var' was not set in the previous run" >&2;} + ac_cache_corrupted=: ;; + ,);; + *) + if test "x$ac_old_val" != "x$ac_new_val"; then + # differences in whitespace do not lead to failure. + ac_old_val_w=`echo x $ac_old_val` + ac_new_val_w=`echo x $ac_new_val` + if test "$ac_old_val_w" != "$ac_new_val_w"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: '$ac_var' has changed since the previous run:" >&5 +printf "%s\n" "$as_me: error: '$ac_var' has changed since the previous run:" >&2;} + ac_cache_corrupted=: + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: warning: ignoring whitespace changes in '$ac_var' since the previous run:" >&5 +printf "%s\n" "$as_me: warning: ignoring whitespace changes in '$ac_var' since the previous run:" >&2;} + eval $ac_var=\$ac_old_val + fi + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: former value: '$ac_old_val'" >&5 +printf "%s\n" "$as_me: former value: '$ac_old_val'" >&2;} + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: current value: '$ac_new_val'" >&5 +printf "%s\n" "$as_me: current value: '$ac_new_val'" >&2;} + fi;; + esac + # Pass precious variables to config.status. + if test "$ac_new_set" = set; then + case $ac_new_val in + *\'*) ac_arg=$ac_var=`printf "%s\n" "$ac_new_val" | sed "s/'/'\\\\\\\\''/g"` ;; + *) ac_arg=$ac_var=$ac_new_val ;; + esac + case " $ac_configure_args " in + *" '$ac_arg' "*) ;; # Avoid dups. Use of quotes ensures accuracy. + *) as_fn_append ac_configure_args " '$ac_arg'" ;; + esac + fi +done +if $ac_cache_corrupted; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: changes in the environment can compromise the build" >&5 +printf "%s\n" "$as_me: error: changes in the environment can compromise the build" >&2;} + as_fn_error $? "run '${MAKE-make} distclean' and/or 'rm $cache_file' + and start over" "$LINENO" 5 +fi +## -------------------- ## +## Main body of script. ## +## -------------------- ## + +ac_ext=c +ac_cpp='$CPP $CPPFLAGS' +ac_compile='$CC -c $CFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CC -o conftest$ac_exeext $CFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_c_compiler_gnu + + + +## Set R_HOME, respecting an environment variable if one is set +: ${R_HOME=$(R RHOME)} +if test -z "${R_HOME}"; then + as_fn_error $? "Could not determine R_HOME." "$LINENO" 5 +fi + +## Use R to set CXX and CXXFLAGS +CXX=$(${R_HOME}/bin/R CMD config CXX) +CXXFLAGS=$("${R_HOME}/bin/R" CMD config CXXFLAGS) + +## We are using C++ +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + + + + + + + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu +if test -z "$CXX"; then + if test -n "$CCC"; then + CXX=$CCC + else + if test -n "$ac_tool_prefix"; then + for ac_prog in g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC clang++ + do + # Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args. +set dummy $ac_tool_prefix$ac_prog; ac_word=$2 +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5 +printf %s "checking for $ac_word... " >&6; } +if test ${ac_cv_prog_CXX+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) if test -n "$CXX"; then + ac_cv_prog_CXX="$CXX" # Let the user override the test. +else +as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + for ac_exec_ext in '' $ac_executable_extensions; do + if as_fn_executable_p "$as_dir$ac_word$ac_exec_ext"; then + ac_cv_prog_CXX="$ac_tool_prefix$ac_prog" + printf "%s\n" "$as_me:${as_lineno-$LINENO}: found $as_dir$ac_word$ac_exec_ext" >&5 + break 2 + fi +done + done +IFS=$as_save_IFS + +fi ;; +esac +fi +CXX=$ac_cv_prog_CXX +if test -n "$CXX"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $CXX" >&5 +printf "%s\n" "$CXX" >&6; } +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi + + + test -n "$CXX" && break + done +fi +if test -z "$CXX"; then + ac_ct_CXX=$CXX + for ac_prog in g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC clang++ +do + # Extract the first word of "$ac_prog", so it can be a program name with args. +set dummy $ac_prog; ac_word=$2 +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5 +printf %s "checking for $ac_word... " >&6; } +if test ${ac_cv_prog_ac_ct_CXX+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) if test -n "$ac_ct_CXX"; then + ac_cv_prog_ac_ct_CXX="$ac_ct_CXX" # Let the user override the test. +else +as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + for ac_exec_ext in '' $ac_executable_extensions; do + if as_fn_executable_p "$as_dir$ac_word$ac_exec_ext"; then + ac_cv_prog_ac_ct_CXX="$ac_prog" + printf "%s\n" "$as_me:${as_lineno-$LINENO}: found $as_dir$ac_word$ac_exec_ext" >&5 + break 2 + fi +done + done +IFS=$as_save_IFS + +fi ;; +esac +fi +ac_ct_CXX=$ac_cv_prog_ac_ct_CXX +if test -n "$ac_ct_CXX"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_ct_CXX" >&5 +printf "%s\n" "$ac_ct_CXX" >&6; } +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi + + + test -n "$ac_ct_CXX" && break +done + + if test "x$ac_ct_CXX" = x; then + CXX="g++" + else + case $cross_compiling:$ac_tool_warned in +yes:) +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5 +printf "%s\n" "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;} +ac_tool_warned=yes ;; +esac + CXX=$ac_ct_CXX + fi +fi + + fi +fi +# Provide some information about the compiler. +printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for C++ compiler version" >&5 +set X $ac_compile +ac_compiler=$2 +for ac_option in --version -v -V -qversion; do + { { ac_try="$ac_compiler $ac_option >&5" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_compiler $ac_option >&5") 2>conftest.err + ac_status=$? + if test -s conftest.err; then + sed '10a\ +... rest of stderr output deleted ... + 10q' conftest.err >conftest.er1 + cat conftest.er1 >&5 + fi + rm -f conftest.er1 conftest.err + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } +done + +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +ac_clean_files_save=$ac_clean_files +ac_clean_files="$ac_clean_files a.out a.out.dSYM a.exe b.out" +# Try to create an executable without -o first, disregard a.out. +# It will help us diagnose broken compilers, and finding out an intuition +# of exeext. +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether the C++ compiler works" >&5 +printf %s "checking whether the C++ compiler works... " >&6; } +ac_link_default=`printf "%s\n" "$ac_link" | sed 's/ -o *conftest[^ ]*//'` + +# The possible output files: +ac_files="a.out conftest.exe conftest a.exe a_out.exe b.out conftest.*" + +ac_rmfiles= +for ac_file in $ac_files +do + case $ac_file in + *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.map | *.inf | *.dSYM | *.o | *.obj ) ;; + * ) ac_rmfiles="$ac_rmfiles $ac_file";; + esac +done +rm -f $ac_rmfiles + +if { { ac_try="$ac_link_default" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_link_default") 2>&5 + ac_status=$? + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } +then : + # Autoconf-2.13 could set the ac_cv_exeext variable to 'no'. +# So ignore a value of 'no', otherwise this would lead to 'EXEEXT = no' +# in a Makefile. We should not override ac_cv_exeext if it was cached, +# so that the user can short-circuit this test for compilers unknown to +# Autoconf. +for ac_file in $ac_files '' +do + test -f "$ac_file" || continue + case $ac_file in + *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.map | *.inf | *.dSYM | *.o | *.obj ) + ;; + [ab].out ) + # We found the default executable, but exeext='' is most + # certainly right. + break;; + *.* ) + if test ${ac_cv_exeext+y} && test "$ac_cv_exeext" != no; + then :; else + ac_cv_exeext=`expr "$ac_file" : '[^.]*\(\..*\)'` + fi + # We set ac_cv_exeext here because the later test for it is not + # safe: cross compilers may not add the suffix if given an '-o' + # argument, so we may need to know it at that point already. + # Even if this section looks crufty: it has the advantage of + # actually working. + break;; + * ) + break;; + esac +done +test "$ac_cv_exeext" = no && ac_cv_exeext= + +else case e in #( + e) ac_file='' ;; +esac +fi +if test -z "$ac_file" +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +printf "%s\n" "$as_me: failed program was:" >&5 +sed 's/^/| /' conftest.$ac_ext >&5 + +{ { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error 77 "C++ compiler cannot create executables +See 'config.log' for more details" "$LINENO" 5; } +else case e in #( + e) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for C++ compiler default output file name" >&5 +printf %s "checking for C++ compiler default output file name... " >&6; } +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_file" >&5 +printf "%s\n" "$ac_file" >&6; } +ac_exeext=$ac_cv_exeext + +rm -f -r a.out a.out.dSYM a.exe conftest$ac_cv_exeext b.out +ac_clean_files=$ac_clean_files_save +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for suffix of executables" >&5 +printf %s "checking for suffix of executables... " >&6; } +if { { ac_try="$ac_link" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_link") 2>&5 + ac_status=$? + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } +then : + # If both 'conftest.exe' and 'conftest' are 'present' (well, observable) +# catch 'conftest.exe'. For instance with Cygwin, 'ls conftest' will +# work properly (i.e., refer to 'conftest.exe'), while it won't with +# 'rm'. +for ac_file in conftest.exe conftest conftest.*; do + test -f "$ac_file" || continue + case $ac_file in + *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.map | *.inf | *.dSYM | *.o | *.obj ) ;; + *.* ) ac_cv_exeext=`expr "$ac_file" : '[^.]*\(\..*\)'` + break;; + * ) break;; + esac +done +else case e in #( + e) { { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error $? "cannot compute suffix of executables: cannot compile and link +See 'config.log' for more details" "$LINENO" 5; } ;; +esac +fi +rm -f conftest conftest$ac_cv_exeext +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_exeext" >&5 +printf "%s\n" "$ac_cv_exeext" >&6; } + +rm -f conftest.$ac_ext +EXEEXT=$ac_cv_exeext +ac_exeext=$EXEEXT +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +#include +int +main (void) +{ +FILE *f = fopen ("conftest.out", "w"); + if (!f) + return 1; + return ferror (f) || fclose (f) != 0; + + ; + return 0; +} +_ACEOF +ac_clean_files="$ac_clean_files conftest.out" +# Check that the compiler produces executables we can run. If not, either +# the compiler is broken, or we cross compile. +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether we are cross compiling" >&5 +printf %s "checking whether we are cross compiling... " >&6; } +if test "$cross_compiling" != yes; then + { { ac_try="$ac_link" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_link") 2>&5 + ac_status=$? + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } + if { ac_try='./conftest$ac_cv_exeext' + { { case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_try") 2>&5 + ac_status=$? + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; }; }; then + cross_compiling=no + else + if test "$cross_compiling" = maybe; then + cross_compiling=yes + else + { { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error 77 "cannot run C++ compiled programs. +If you meant to cross compile, use '--host'. +See 'config.log' for more details" "$LINENO" 5; } + fi + fi +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $cross_compiling" >&5 +printf "%s\n" "$cross_compiling" >&6; } + +rm -f conftest.$ac_ext conftest$ac_cv_exeext \ + conftest.o conftest.obj conftest.out +ac_clean_files=$ac_clean_files_save +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for suffix of object files" >&5 +printf %s "checking for suffix of object files... " >&6; } +if test ${ac_cv_objext+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +rm -f conftest.o conftest.obj +if { { ac_try="$ac_compile" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_compile") 2>&5 + ac_status=$? + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } +then : + for ac_file in conftest.o conftest.obj conftest.*; do + test -f "$ac_file" || continue; + case $ac_file in + *.$ac_ext | *.xcoff | *.tds | *.d | *.pdb | *.xSYM | *.bb | *.bbg | *.map | *.inf | *.dSYM ) ;; + *) ac_cv_objext=`expr "$ac_file" : '.*\.\(.*\)'` + break;; + esac +done +else case e in #( + e) printf "%s\n" "$as_me: failed program was:" >&5 +sed 's/^/| /' conftest.$ac_ext >&5 + +{ { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error $? "cannot compute suffix of object files: cannot compile +See 'config.log' for more details" "$LINENO" 5; } ;; +esac +fi +rm -f conftest.$ac_cv_objext conftest.$ac_ext ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_objext" >&5 +printf "%s\n" "$ac_cv_objext" >&6; } +OBJEXT=$ac_cv_objext +ac_objext=$OBJEXT +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether the compiler supports GNU C++" >&5 +printf %s "checking whether the compiler supports GNU C++... " >&6; } +if test ${ac_cv_cxx_compiler_gnu+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ +#ifndef __GNUC__ + choke me +#endif + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_compiler_gnu=yes +else case e in #( + e) ac_compiler_gnu=no ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext +ac_cv_cxx_compiler_gnu=$ac_compiler_gnu + ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_cxx_compiler_gnu" >&5 +printf "%s\n" "$ac_cv_cxx_compiler_gnu" >&6; } +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + +if test $ac_compiler_gnu = yes; then + GXX=yes +else + GXX= +fi +ac_test_CXXFLAGS=${CXXFLAGS+y} +ac_save_CXXFLAGS=$CXXFLAGS +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether $CXX accepts -g" >&5 +printf %s "checking whether $CXX accepts -g... " >&6; } +if test ${ac_cv_prog_cxx_g+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_save_cxx_werror_flag=$ac_cxx_werror_flag + ac_cxx_werror_flag=yes + ac_cv_prog_cxx_g=no + CXXFLAGS="-g" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_g=yes +else case e in #( + e) CXXFLAGS="" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + +else case e in #( + e) ac_cxx_werror_flag=$ac_save_cxx_werror_flag + CXXFLAGS="-g" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_g=yes +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext + ac_cxx_werror_flag=$ac_save_cxx_werror_flag ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_g" >&5 +printf "%s\n" "$ac_cv_prog_cxx_g" >&6; } +if test $ac_test_CXXFLAGS; then + CXXFLAGS=$ac_save_CXXFLAGS +elif test $ac_cv_prog_cxx_g = yes; then + if test "$GXX" = yes; then + CXXFLAGS="-g -O2" + else + CXXFLAGS="-g" + fi +else + if test "$GXX" = yes; then + CXXFLAGS="-O2" + else + CXXFLAGS= + fi +fi +ac_prog_cxx_stdcxx=no +if test x$ac_prog_cxx_stdcxx = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $CXX option to enable C++11 features" >&5 +printf %s "checking for $CXX option to enable C++11 features... " >&6; } +if test ${ac_cv_prog_cxx_cxx11+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_cv_prog_cxx_cxx11=no +ac_save_CXX=$CXX +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +$ac_cxx_conftest_cxx11_program +_ACEOF +for ac_arg in '' -std=gnu++11 -std=gnu++0x -std=c++11 -std=c++0x -qlanglvl=extended0x -AA +do + CXX="$ac_save_CXX $ac_arg" + if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_cxx11=$ac_arg +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam + test "x$ac_cv_prog_cxx_cxx11" != "xno" && break +done +rm -f conftest.$ac_ext +CXX=$ac_save_CXX ;; +esac +fi + +if test "x$ac_cv_prog_cxx_cxx11" = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: unsupported" >&5 +printf "%s\n" "unsupported" >&6; } +else case e in #( + e) if test "x$ac_cv_prog_cxx_cxx11" = x +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: none needed" >&5 +printf "%s\n" "none needed" >&6; } +else case e in #( + e) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_cxx11" >&5 +printf "%s\n" "$ac_cv_prog_cxx_cxx11" >&6; } + CXX="$CXX $ac_cv_prog_cxx_cxx11" ;; +esac +fi + ac_cv_prog_cxx_stdcxx=$ac_cv_prog_cxx_cxx11 + ac_prog_cxx_stdcxx=cxx11 ;; +esac +fi +fi +if test x$ac_prog_cxx_stdcxx = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $CXX option to enable C++98 features" >&5 +printf %s "checking for $CXX option to enable C++98 features... " >&6; } +if test ${ac_cv_prog_cxx_cxx98+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_cv_prog_cxx_cxx98=no +ac_save_CXX=$CXX +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +$ac_cxx_conftest_cxx98_program +_ACEOF +for ac_arg in '' -std=gnu++98 -std=c++98 -qlanglvl=extended -AA +do + CXX="$ac_save_CXX $ac_arg" + if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_cxx98=$ac_arg +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam + test "x$ac_cv_prog_cxx_cxx98" != "xno" && break +done +rm -f conftest.$ac_ext +CXX=$ac_save_CXX ;; +esac +fi + +if test "x$ac_cv_prog_cxx_cxx98" = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: unsupported" >&5 +printf "%s\n" "unsupported" >&6; } +else case e in #( + e) if test "x$ac_cv_prog_cxx_cxx98" = x +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: none needed" >&5 +printf "%s\n" "none needed" >&6; } +else case e in #( + e) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_cxx98" >&5 +printf "%s\n" "$ac_cv_prog_cxx_cxx98" >&6; } + CXX="$CXX $ac_cv_prog_cxx_cxx98" ;; +esac +fi + ac_cv_prog_cxx_stdcxx=$ac_cv_prog_cxx_cxx98 + ac_prog_cxx_stdcxx=cxx98 ;; +esac +fi +fi + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking how to run the C++ preprocessor" >&5 +printf %s "checking how to run the C++ preprocessor... " >&6; } +if test -z "$CXXCPP"; then + if test ${ac_cv_prog_CXXCPP+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) # Double quotes because $CXX needs to be expanded + for CXXCPP in "$CXX -E" cpp /lib/cpp + do + ac_preproc_ok=false +for ac_cxx_preproc_warn_flag in '' yes +do + # Use a header file that comes with gcc, so configuring glibc + # with a fresh cross-compiler works. + # On the NeXT, cc -E runs the code through the compiler's parser, + # not just through cpp. "Syntax error" is here to catch this case. + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +#include + Syntax error +_ACEOF +if ac_fn_cxx_try_cpp "$LINENO" +then : + +else case e in #( + e) # Broken: fails on valid input. +continue ;; +esac +fi +rm -f conftest.err conftest.i conftest.$ac_ext + + # OK, works on sane cases. Now check whether nonexistent headers + # can be detected and how. + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +#include +_ACEOF +if ac_fn_cxx_try_cpp "$LINENO" +then : + # Broken: success on invalid input. +continue +else case e in #( + e) # Passes both tests. +ac_preproc_ok=: +break ;; +esac +fi +rm -f conftest.err conftest.i conftest.$ac_ext + +done +# Because of 'break', _AC_PREPROC_IFELSE's cleaning code was skipped. +rm -f conftest.i conftest.err conftest.$ac_ext +if $ac_preproc_ok +then : + break +fi + + done + ac_cv_prog_CXXCPP=$CXXCPP + ;; +esac +fi + CXXCPP=$ac_cv_prog_CXXCPP +else + ac_cv_prog_CXXCPP=$CXXCPP +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $CXXCPP" >&5 +printf "%s\n" "$CXXCPP" >&6; } +ac_preproc_ok=false +for ac_cxx_preproc_warn_flag in '' yes +do + # Use a header file that comes with gcc, so configuring glibc + # with a fresh cross-compiler works. + # On the NeXT, cc -E runs the code through the compiler's parser, + # not just through cpp. "Syntax error" is here to catch this case. + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +#include + Syntax error +_ACEOF +if ac_fn_cxx_try_cpp "$LINENO" +then : + +else case e in #( + e) # Broken: fails on valid input. +continue ;; +esac +fi +rm -f conftest.err conftest.i conftest.$ac_ext + + # OK, works on sane cases. Now check whether nonexistent headers + # can be detected and how. + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +#include +_ACEOF +if ac_fn_cxx_try_cpp "$LINENO" +then : + # Broken: success on invalid input. +continue +else case e in #( + e) # Passes both tests. +ac_preproc_ok=: +break ;; +esac +fi +rm -f conftest.err conftest.i conftest.$ac_ext + +done +# Because of 'break', _AC_PREPROC_IFELSE's cleaning code was skipped. +rm -f conftest.i conftest.err conftest.$ac_ext +if $ac_preproc_ok +then : + +else case e in #( + e) { { printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: in '$ac_pwd':" >&5 +printf "%s\n" "$as_me: error: in '$ac_pwd':" >&2;} +as_fn_error $? "C++ preprocessor \"$CXXCPP\" fails sanity check +See 'config.log' for more details" "$LINENO" 5; } ;; +esac +fi + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + + + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu +if test -z "$CXX"; then + if test -n "$CCC"; then + CXX=$CCC + else + if test -n "$ac_tool_prefix"; then + for ac_prog in g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC clang++ + do + # Extract the first word of "$ac_tool_prefix$ac_prog", so it can be a program name with args. +set dummy $ac_tool_prefix$ac_prog; ac_word=$2 +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5 +printf %s "checking for $ac_word... " >&6; } +if test ${ac_cv_prog_CXX+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) if test -n "$CXX"; then + ac_cv_prog_CXX="$CXX" # Let the user override the test. +else +as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + for ac_exec_ext in '' $ac_executable_extensions; do + if as_fn_executable_p "$as_dir$ac_word$ac_exec_ext"; then + ac_cv_prog_CXX="$ac_tool_prefix$ac_prog" + printf "%s\n" "$as_me:${as_lineno-$LINENO}: found $as_dir$ac_word$ac_exec_ext" >&5 + break 2 + fi +done + done +IFS=$as_save_IFS + +fi ;; +esac +fi +CXX=$ac_cv_prog_CXX +if test -n "$CXX"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $CXX" >&5 +printf "%s\n" "$CXX" >&6; } +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi + + + test -n "$CXX" && break + done +fi +if test -z "$CXX"; then + ac_ct_CXX=$CXX + for ac_prog in g++ c++ gpp aCC CC cxx cc++ cl.exe FCC KCC RCC xlC_r xlC clang++ +do + # Extract the first word of "$ac_prog", so it can be a program name with args. +set dummy $ac_prog; ac_word=$2 +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $ac_word" >&5 +printf %s "checking for $ac_word... " >&6; } +if test ${ac_cv_prog_ac_ct_CXX+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) if test -n "$ac_ct_CXX"; then + ac_cv_prog_ac_ct_CXX="$ac_ct_CXX" # Let the user override the test. +else +as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + for ac_exec_ext in '' $ac_executable_extensions; do + if as_fn_executable_p "$as_dir$ac_word$ac_exec_ext"; then + ac_cv_prog_ac_ct_CXX="$ac_prog" + printf "%s\n" "$as_me:${as_lineno-$LINENO}: found $as_dir$ac_word$ac_exec_ext" >&5 + break 2 + fi +done + done +IFS=$as_save_IFS + +fi ;; +esac +fi +ac_ct_CXX=$ac_cv_prog_ac_ct_CXX +if test -n "$ac_ct_CXX"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_ct_CXX" >&5 +printf "%s\n" "$ac_ct_CXX" >&6; } +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi + + + test -n "$ac_ct_CXX" && break +done + + if test "x$ac_ct_CXX" = x; then + CXX="g++" + else + case $cross_compiling:$ac_tool_warned in +yes:) +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: using cross tools not prefixed with host triplet" >&5 +printf "%s\n" "$as_me: WARNING: using cross tools not prefixed with host triplet" >&2;} +ac_tool_warned=yes ;; +esac + CXX=$ac_ct_CXX + fi +fi + + fi +fi +# Provide some information about the compiler. +printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for C++ compiler version" >&5 +set X $ac_compile +ac_compiler=$2 +for ac_option in --version -v -V -qversion; do + { { ac_try="$ac_compiler $ac_option >&5" +case "(($ac_try" in + *\"* | *\`* | *\\*) ac_try_echo=\$ac_try;; + *) ac_try_echo=$ac_try;; +esac +eval ac_try_echo="\"\$as_me:${as_lineno-$LINENO}: $ac_try_echo\"" +printf "%s\n" "$ac_try_echo"; } >&5 + (eval "$ac_compiler $ac_option >&5") 2>conftest.err + ac_status=$? + if test -s conftest.err; then + sed '10a\ +... rest of stderr output deleted ... + 10q' conftest.err >conftest.er1 + cat conftest.er1 >&5 + fi + rm -f conftest.er1 conftest.err + printf "%s\n" "$as_me:${as_lineno-$LINENO}: \$? = $ac_status" >&5 + test $ac_status = 0; } +done + +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether the compiler supports GNU C++" >&5 +printf %s "checking whether the compiler supports GNU C++... " >&6; } +if test ${ac_cv_cxx_compiler_gnu+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ +#ifndef __GNUC__ + choke me +#endif + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_compiler_gnu=yes +else case e in #( + e) ac_compiler_gnu=no ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext +ac_cv_cxx_compiler_gnu=$ac_compiler_gnu + ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_cxx_compiler_gnu" >&5 +printf "%s\n" "$ac_cv_cxx_compiler_gnu" >&6; } +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + +if test $ac_compiler_gnu = yes; then + GXX=yes +else + GXX= +fi +ac_test_CXXFLAGS=${CXXFLAGS+y} +ac_save_CXXFLAGS=$CXXFLAGS +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether $CXX accepts -g" >&5 +printf %s "checking whether $CXX accepts -g... " >&6; } +if test ${ac_cv_prog_cxx_g+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_save_cxx_werror_flag=$ac_cxx_werror_flag + ac_cxx_werror_flag=yes + ac_cv_prog_cxx_g=no + CXXFLAGS="-g" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_g=yes +else case e in #( + e) CXXFLAGS="" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + +else case e in #( + e) ac_cxx_werror_flag=$ac_save_cxx_werror_flag + CXXFLAGS="-g" + cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ + +int +main (void) +{ + + ; + return 0; +} +_ACEOF +if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_g=yes +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext ;; +esac +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam conftest.$ac_ext + ac_cxx_werror_flag=$ac_save_cxx_werror_flag ;; +esac +fi +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_g" >&5 +printf "%s\n" "$ac_cv_prog_cxx_g" >&6; } +if test $ac_test_CXXFLAGS; then + CXXFLAGS=$ac_save_CXXFLAGS +elif test $ac_cv_prog_cxx_g = yes; then + if test "$GXX" = yes; then + CXXFLAGS="-g -O2" + else + CXXFLAGS="-g" + fi +else + if test "$GXX" = yes; then + CXXFLAGS="-O2" + else + CXXFLAGS= + fi +fi +ac_prog_cxx_stdcxx=no +if test x$ac_prog_cxx_stdcxx = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $CXX option to enable C++11 features" >&5 +printf %s "checking for $CXX option to enable C++11 features... " >&6; } +if test ${ac_cv_prog_cxx_cxx11+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_cv_prog_cxx_cxx11=no +ac_save_CXX=$CXX +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +$ac_cxx_conftest_cxx11_program +_ACEOF +for ac_arg in '' -std=gnu++11 -std=gnu++0x -std=c++11 -std=c++0x -qlanglvl=extended0x -AA +do + CXX="$ac_save_CXX $ac_arg" + if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_cxx11=$ac_arg +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam + test "x$ac_cv_prog_cxx_cxx11" != "xno" && break +done +rm -f conftest.$ac_ext +CXX=$ac_save_CXX ;; +esac +fi + +if test "x$ac_cv_prog_cxx_cxx11" = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: unsupported" >&5 +printf "%s\n" "unsupported" >&6; } +else case e in #( + e) if test "x$ac_cv_prog_cxx_cxx11" = x +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: none needed" >&5 +printf "%s\n" "none needed" >&6; } +else case e in #( + e) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_cxx11" >&5 +printf "%s\n" "$ac_cv_prog_cxx_cxx11" >&6; } + CXX="$CXX $ac_cv_prog_cxx_cxx11" ;; +esac +fi + ac_cv_prog_cxx_stdcxx=$ac_cv_prog_cxx_cxx11 + ac_prog_cxx_stdcxx=cxx11 ;; +esac +fi +fi +if test x$ac_prog_cxx_stdcxx = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for $CXX option to enable C++98 features" >&5 +printf %s "checking for $CXX option to enable C++98 features... " >&6; } +if test ${ac_cv_prog_cxx_cxx98+y} +then : + printf %s "(cached) " >&6 +else case e in #( + e) ac_cv_prog_cxx_cxx98=no +ac_save_CXX=$CXX +cat confdefs.h - <<_ACEOF >conftest.$ac_ext +/* end confdefs.h. */ +$ac_cxx_conftest_cxx98_program +_ACEOF +for ac_arg in '' -std=gnu++98 -std=c++98 -qlanglvl=extended -AA +do + CXX="$ac_save_CXX $ac_arg" + if ac_fn_cxx_try_compile "$LINENO" +then : + ac_cv_prog_cxx_cxx98=$ac_arg +fi +rm -f core conftest.err conftest.$ac_objext conftest.beam + test "x$ac_cv_prog_cxx_cxx98" != "xno" && break +done +rm -f conftest.$ac_ext +CXX=$ac_save_CXX ;; +esac +fi + +if test "x$ac_cv_prog_cxx_cxx98" = xno +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: unsupported" >&5 +printf "%s\n" "unsupported" >&6; } +else case e in #( + e) if test "x$ac_cv_prog_cxx_cxx98" = x +then : + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: none needed" >&5 +printf "%s\n" "none needed" >&6; } +else case e in #( + e) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: $ac_cv_prog_cxx_cxx98" >&5 +printf "%s\n" "$ac_cv_prog_cxx_cxx98" >&6; } + CXX="$CXX $ac_cv_prog_cxx_cxx98" ;; +esac +fi + ac_cv_prog_cxx_stdcxx=$ac_cv_prog_cxx_cxx98 + ac_prog_cxx_stdcxx=cxx98 ;; +esac +fi +fi + +ac_ext=cpp +ac_cpp='$CXXCPP $CPPFLAGS' +ac_compile='$CXX -c $CXXFLAGS $CPPFLAGS conftest.$ac_ext >&5' +ac_link='$CXX -o conftest$ac_exeext $CXXFLAGS $CPPFLAGS $LDFLAGS conftest.$ac_ext $LIBS >&5' +ac_compiler_gnu=$ac_cv_cxx_compiler_gnu + + +## Rely on Sys.info() from R for cross-compilation cases +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking what system we are on" >&5 +printf %s "checking what system we are on... " >&6; } +SYSKERNEL=$("${R_HOME}/bin/Rscript" --vanilla -e 'cat(Sys.info()["sysname"])') +SYSMACHINE=$("${R_HOME}/bin/Rscript" --vanilla -e 'cat(Sys.info()["machine"])') +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: running ${SYSKERNEL} on ${SYSMACHINE}" >&5 +printf "%s\n" "running ${SYSKERNEL} on ${SYSMACHINE}" >&6; } + + +## Default to not assuming OpenMP, but then test a variety of setups +can_use_openmp="no" + +## Ensure TMPDIR is set. +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether we have a suitable tempdir" >&5 +printf %s "checking whether we have a suitable tempdir... " >&6; } +TMPDIR=$("${R_HOME}/bin/R" --vanilla --slave -e "cat(dirname(tempdir()))") +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: ${TMPDIR}" >&5 +printf "%s\n" "${TMPDIR}" >&6; } + +## Create private directory in TMPDIR. +BUILDDIR="${TMPDIR}/rcppeigen-$$-$RANDOM" +mkdir -p "${BUILDDIR}" + +owd=$(pwd) +cd "${BUILDDIR}" + +cat < test-omp.cpp +#include +int main() { + return omp_get_num_threads(); +} +EOF + +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether on Linux" >&5 +printf %s "checking whether on Linux... " >&6; } +if test x"${SYSKERNEL}" = x"Linux"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + + ## Check if R is configured to compile OpenMP programs out-of-the-box. + if test x"${can_use_openmp}" = x"no"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether R CMD SHLIB can already compile OpenMP programs" >&5 +printf %s "checking whether R CMD SHLIB can already compile OpenMP programs... " >&6; } + "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + can_use_openmp="yes" + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } + can_use_openmp="no" + fi + fi + + ## If needed, check if R is configured to compile OpenMP programs using -fopenmp + if test x"${can_use_openmp}" = x"no"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether R CMD SHLIB can compile OpenMP via -fopenmp" >&5 +printf %s "checking whether R CMD SHLIB can compile OpenMP via -fopenmp... " >&6; } + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" PKG_LIBS="${PKG_LIBS} -fopenmp" "${R_HOME}/bin/R" CMD SHLIB -fopenmp test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" + PKG_LIBS="${PKG_LIBS} -fopenmp" + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } + can_use_openmp="no" + fi + fi +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi # if Linux + +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether on macOS" >&5 +printf %s "checking whether on macOS... " >&6; } +if test x"${SYSKERNEL}" = x"Darwin"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + + ## Check if R is configured to compile OpenMP programs using -Xclang -fopenmp + if test x"${can_use_openmp}" = x"no"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether R CMD SHLIB can compile OpenMP programs using '-Xclang -fopenmp'" >&5 +printf %s "checking whether R CMD SHLIB can compile OpenMP programs using '-Xclang -fopenmp'... " >&6; } + PKG_CXXFLAGS="${PKG_CXXFLAGS} -Xclang -fopenmp" PKG_LIBS="${PKG_LIBS} -lomp" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -Xclang -fopenmp" + PKG_LIBS="${PKG_LIBS} -lomp" + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } + can_use_openmp="no" + fi + fi + + ## Check if R is configured to compile OpenMP programs using -fopenmp (cf data.table #6409) + if test x"${can_use_openmp}" = x"no"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether R CMD SHLIB can compile OpenMP programs using '-fopenmp'" >&5 +printf %s "checking whether R CMD SHLIB can compile OpenMP programs using '-fopenmp'... " >&6; } + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" PKG_LIBS="${PKG_LIBS} -fopenmp" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" + PKG_LIBS="${PKG_LIBS} -fopenmp" + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } + can_use_openmp="no" + fi + fi + + if test x"${can_use_openmp}" = x"no"; then + if test x"${SYSMACHINE}" = x"arm64"; then + HOMEBREW_PREFIX=/opt/homebrew + else + HOMEBREW_PREFIX=/usr/local + fi + if test -e "${HOMEBREW_PREFIX}/opt/libomp"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking whether R CMD SHLIB can use libomp at ${HOMEBREW_PREFIX}/opt/libomp" >&5 +printf %s "checking whether R CMD SHLIB can use libomp at ${HOMEBREW_PREFIX}/opt/libomp... " >&6; } + LIBOMP_INCLUDE="-I${HOMEBREW_PREFIX}/opt/libomp/include -Xclang -fopenmp" + LIBOMP_LINK="-L${HOMEBREW_PREFIX}/opt/libomp/lib -lomp" + PKG_CXXFLAGS="${PKG_CXXFLAGS} ${LIBOMP_INCLUDE}" PKG_LIBS="${PKG_LIBS} ${LIBOMP_LINK}" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: yes" >&5 +printf "%s\n" "yes" >&6; } + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} ${LIBOMP_INCLUDE}" + PKG_LIBS="${PKG_LIBS} ${LIBOMP_LINK}" + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } + can_use_openmp="no" + fi + fi + fi +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: no" >&5 +printf "%s\n" "no" >&6; } +fi # if macOS + +## Go back home. +cd "${owd}" +rm -rf "${BUILDDIR}" + +# Overall summary +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: checking for OpenMP" >&5 +printf %s "checking for OpenMP... " >&6; } +if test x"${can_use_openmp}" = x"yes"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: found and suitable" >&5 +printf "%s\n" "found and suitable" >&6; } + openmp_flag='$(SHLIB_OPENMP_CXXFLAGS)' +else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: result: missing so no OpenMP acceleration" >&5 +printf "%s\n" "missing so no OpenMP acceleration" >&6; } + openmp_flag="" +fi + +## Now use all these +OPENMP_FLAG="${openmp_flag}" + +PKG_CXXFLAGS="${PKG_CXXFLAGS}" + +PKG_LIBS="${PKG_LIBS}" + +ac_config_files="$ac_config_files src/Makevars" + +cat >confcache <<\_ACEOF +# This file is a shell script that caches the results of configure +# tests run on this system so they can be shared between configure +# scripts and configure runs, see configure's option --config-cache. +# It is not useful on other systems. If it contains results you don't +# want to keep, you may remove or edit it. +# +# config.status only pays attention to the cache file if you give it +# the --recheck option to rerun configure. +# +# 'ac_cv_env_foo' variables (set or unset) will be overridden when +# loading this file, other *unset* 'ac_cv_foo' will be assigned the +# following values. + +_ACEOF + +# The following way of writing the cache mishandles newlines in values, +# but we know of no workaround that is simple, portable, and efficient. +# So, we kill variables containing newlines. +# Ultrix sh set writes to stderr and can't be redirected directly, +# and sets the high bit in the cache file unless we assign to the vars. +( + for ac_var in `(set) 2>&1 | sed -n 's/^\([a-zA-Z_][a-zA-Z0-9_]*\)=.*/\1/p'`; do + eval ac_val=\$$ac_var + case $ac_val in #( + *${as_nl}*) + case $ac_var in #( + *_cv_*) { printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: cache variable $ac_var contains a newline" >&5 +printf "%s\n" "$as_me: WARNING: cache variable $ac_var contains a newline" >&2;} ;; + esac + case $ac_var in #( + _ | IFS | as_nl) ;; #( + BASH_ARGV | BASH_SOURCE) eval $ac_var= ;; #( + *) { eval $ac_var=; unset $ac_var;} ;; + esac ;; + esac + done + + (set) 2>&1 | + case $as_nl`(ac_space=' '; set) 2>&1` in #( + *${as_nl}ac_space=\ *) + # 'set' does not quote correctly, so add quotes: double-quote + # substitution turns \\\\ into \\, and sed turns \\ into \. + sed -n \ + "s/'/'\\\\''/g; + s/^\\([_$as_cr_alnum]*_cv_[_$as_cr_alnum]*\\)=\\(.*\\)/\\1='\\2'/p" + ;; #( + *) + # 'set' quotes correctly as required by POSIX, so do not add quotes. + sed -n "/^[_$as_cr_alnum]*_cv_[_$as_cr_alnum]*=/p" + ;; + esac | + sort +) | + sed ' + /^ac_cv_env_/b end + t clear + :clear + s/^\([^=]*\)=\(.*[{}].*\)$/test ${\1+y} || &/ + t end + s/^\([^=]*\)=\(.*\)$/\1=${\1=\2}/ + :end' >>confcache +if diff "$cache_file" confcache >/dev/null 2>&1; then :; else + if test -w "$cache_file"; then + if test "x$cache_file" != "x/dev/null"; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: updating cache $cache_file" >&5 +printf "%s\n" "$as_me: updating cache $cache_file" >&6;} + if test ! -f "$cache_file" || test -h "$cache_file"; then + cat confcache >"$cache_file" + else + case $cache_file in #( + */* | ?:*) + mv -f confcache "$cache_file"$$ && + mv -f "$cache_file"$$ "$cache_file" ;; #( + *) + mv -f confcache "$cache_file" ;; + esac + fi + fi + else + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: not updating unwritable cache $cache_file" >&5 +printf "%s\n" "$as_me: not updating unwritable cache $cache_file" >&6;} + fi +fi +rm -f confcache + +test "x$prefix" = xNONE && prefix=$ac_default_prefix +# Let make expand exec_prefix. +test "x$exec_prefix" = xNONE && exec_prefix='${prefix}' + +# Transform confdefs.h into DEFS. +# Protect against shell expansion while executing Makefile rules. +# Protect against Makefile macro expansion. +# +# If the first sed substitution is executed (which looks for macros that +# take arguments), then branch to the quote section. Otherwise, +# look for a macro that doesn't take arguments. +ac_script=' +:mline +/\\$/{ + N + s,\\\n,, + b mline +} +t clear +:clear +s/^[ ]*#[ ]*define[ ][ ]*\([^ (][^ (]*([^)]*)\)[ ]*\(.*\)/-D\1=\2/g +t quote +s/^[ ]*#[ ]*define[ ][ ]*\([^ ][^ ]*\)[ ]*\(.*\)/-D\1=\2/g +t quote +b any +:quote +s/[][ `~#$^&*(){}\\|;'\''"<>?]/\\&/g +s/\$/$$/g +H +:any +${ + g + s/^\n// + s/\n/ /g + p +} +' +DEFS=`sed -n "$ac_script" confdefs.h` + + +ac_libobjs= +ac_ltlibobjs= +U= +for ac_i in : $LIBOBJS; do test "x$ac_i" = x: && continue + # 1. Remove the extension, and $U if already installed. + ac_script='s/\$U\././;s/\.o$//;s/\.obj$//' + ac_i=`printf "%s\n" "$ac_i" | sed "$ac_script"` + # 2. Prepend LIBOBJDIR. When used with automake>=1.10 LIBOBJDIR + # will be set to the directory where LIBOBJS objects are built. + as_fn_append ac_libobjs " \${LIBOBJDIR}$ac_i\$U.$ac_objext" + as_fn_append ac_ltlibobjs " \${LIBOBJDIR}$ac_i"'$U.lo' +done +LIBOBJS=$ac_libobjs + +LTLIBOBJS=$ac_ltlibobjs + + + +: "${CONFIG_STATUS=./config.status}" +ac_write_fail=0 +ac_clean_files_save=$ac_clean_files +ac_clean_files="$ac_clean_files $CONFIG_STATUS" +{ printf "%s\n" "$as_me:${as_lineno-$LINENO}: creating $CONFIG_STATUS" >&5 +printf "%s\n" "$as_me: creating $CONFIG_STATUS" >&6;} +as_write_fail=0 +cat >$CONFIG_STATUS <<_ASEOF || as_write_fail=1 +#! $SHELL +# Generated by $as_me. +# Run this file to recreate the current configuration. +# Compiler output produced by configure, useful for debugging +# configure, is in config.log if it exists. + +debug=false +ac_cs_recheck=false +ac_cs_silent=false + +SHELL=\${CONFIG_SHELL-$SHELL} +export SHELL +_ASEOF +cat >>$CONFIG_STATUS <<\_ASEOF || as_write_fail=1 +## -------------------- ## +## M4sh Initialization. ## +## -------------------- ## + +# Be more Bourne compatible +DUALCASE=1; export DUALCASE # for MKS sh +if test ${ZSH_VERSION+y} && (emulate sh) >/dev/null 2>&1 +then : + emulate sh + NULLCMD=: + # Pre-4.2 versions of Zsh do word splitting on ${1+"$@"}, which + # is contrary to our usage. Disable this feature. + alias -g '${1+"$@"}'='"$@"' + setopt NO_GLOB_SUBST +else case e in #( + e) case `(set -o) 2>/dev/null` in #( + *posix*) : + set -o posix ;; #( + *) : + ;; +esac ;; +esac +fi + + + +# Reset variables that may have inherited troublesome values from +# the environment. + +# IFS needs to be set, to space, tab, and newline, in precisely that order. +# (If _AS_PATH_WALK were called with IFS unset, it would have the +# side effect of setting IFS to empty, thus disabling word splitting.) +# Quoting is to prevent editors from complaining about space-tab. +as_nl=' +' +export as_nl +IFS=" "" $as_nl" + +PS1='$ ' +PS2='> ' +PS4='+ ' + +# Ensure predictable behavior from utilities with locale-dependent output. +LC_ALL=C +export LC_ALL +LANGUAGE=C +export LANGUAGE + +# We cannot yet rely on "unset" to work, but we need these variables +# to be unset--not just set to an empty or harmless value--now, to +# avoid bugs in old shells (e.g. pre-3.0 UWIN ksh). This construct +# also avoids known problems related to "unset" and subshell syntax +# in other old shells (e.g. bash 2.01 and pdksh 5.2.14). +for as_var in BASH_ENV ENV MAIL MAILPATH CDPATH +do eval test \${$as_var+y} \ + && ( (unset $as_var) || exit 1) >/dev/null 2>&1 && unset $as_var || : +done + +# Ensure that fds 0, 1, and 2 are open. +if (exec 3>&0) 2>/dev/null; then :; else exec 0&1) 2>/dev/null; then :; else exec 1>/dev/null; fi +if (exec 3>&2) ; then :; else exec 2>/dev/null; fi + +# The user is always right. +if ${PATH_SEPARATOR+false} :; then + PATH_SEPARATOR=: + (PATH='/bin;/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 && { + (PATH='/bin:/bin'; FPATH=$PATH; sh -c :) >/dev/null 2>&1 || + PATH_SEPARATOR=';' + } +fi + + +# Find who we are. Look in the path if we contain no directory separator. +as_myself= +case $0 in #(( + *[\\/]* ) as_myself=$0 ;; + *) as_save_IFS=$IFS; IFS=$PATH_SEPARATOR +for as_dir in $PATH +do + IFS=$as_save_IFS + case $as_dir in #((( + '') as_dir=./ ;; + */) ;; + *) as_dir=$as_dir/ ;; + esac + test -r "$as_dir$0" && as_myself=$as_dir$0 && break + done +IFS=$as_save_IFS + + ;; +esac +# We did not find ourselves, most probably we were run as 'sh COMMAND' +# in which case we are not to be found in the path. +if test "x$as_myself" = x; then + as_myself=$0 +fi +if test ! -f "$as_myself"; then + printf "%s\n" "$as_myself: error: cannot find myself; rerun with an absolute file name" >&2 + exit 1 +fi + + + +# as_fn_error STATUS ERROR [LINENO LOG_FD] +# ---------------------------------------- +# Output "`basename $0`: error: ERROR" to stderr. If LINENO and LOG_FD are +# provided, also output the error to LOG_FD, referencing LINENO. Then exit the +# script with STATUS, using 1 if that was 0. +as_fn_error () +{ + as_status=$1; test $as_status -eq 0 && as_status=1 + if test "$4"; then + as_lineno=${as_lineno-"$3"} as_lineno_stack=as_lineno_stack=$as_lineno_stack + printf "%s\n" "$as_me:${as_lineno-$LINENO}: error: $2" >&$4 + fi + printf "%s\n" "$as_me: error: $2" >&2 + as_fn_exit $as_status +} # as_fn_error + + +# as_fn_set_status STATUS +# ----------------------- +# Set $? to STATUS, without forking. +as_fn_set_status () +{ + return $1 +} # as_fn_set_status + +# as_fn_exit STATUS +# ----------------- +# Exit the shell with STATUS, even in a "trap 0" or "set -e" context. +as_fn_exit () +{ + set +e + as_fn_set_status $1 + exit $1 +} # as_fn_exit + +# as_fn_unset VAR +# --------------- +# Portably unset VAR. +as_fn_unset () +{ + { eval $1=; unset $1;} +} +as_unset=as_fn_unset + +# as_fn_append VAR VALUE +# ---------------------- +# Append the text in VALUE to the end of the definition contained in VAR. Take +# advantage of any shell optimizations that allow amortized linear growth over +# repeated appends, instead of the typical quadratic growth present in naive +# implementations. +if (eval "as_var=1; as_var+=2; test x\$as_var = x12") 2>/dev/null +then : + eval 'as_fn_append () + { + eval $1+=\$2 + }' +else case e in #( + e) as_fn_append () + { + eval $1=\$$1\$2 + } ;; +esac +fi # as_fn_append + +# as_fn_arith ARG... +# ------------------ +# Perform arithmetic evaluation on the ARGs, and store the result in the +# global $as_val. Take advantage of shells that can avoid forks. The arguments +# must be portable across $(()) and expr. +if (eval "test \$(( 1 + 1 )) = 2") 2>/dev/null +then : + eval 'as_fn_arith () + { + as_val=$(( $* )) + }' +else case e in #( + e) as_fn_arith () + { + as_val=`expr "$@" || test $? -eq 1` + } ;; +esac +fi # as_fn_arith + + +if expr a : '\(a\)' >/dev/null 2>&1 && + test "X`expr 00001 : '.*\(...\)'`" = X001; then + as_expr=expr +else + as_expr=false +fi + +if (basename -- /) >/dev/null 2>&1 && test "X`basename -- / 2>&1`" = "X/"; then + as_basename=basename +else + as_basename=false +fi + +if (as_dir=`dirname -- /` && test "X$as_dir" = X/) >/dev/null 2>&1; then + as_dirname=dirname +else + as_dirname=false +fi + +as_me=`$as_basename -- "$0" || +$as_expr X/"$0" : '.*/\([^/][^/]*\)/*$' \| \ + X"$0" : 'X\(//\)$' \| \ + X"$0" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X/"$0" | + sed '/^.*\/\([^/][^/]*\)\/*$/{ + s//\1/ + q + } + /^X\/\(\/\/\)$/{ + s//\1/ + q + } + /^X\/\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + +# Avoid depending upon Character Ranges. +as_cr_letters='abcdefghijklmnopqrstuvwxyz' +as_cr_LETTERS='ABCDEFGHIJKLMNOPQRSTUVWXYZ' +as_cr_Letters=$as_cr_letters$as_cr_LETTERS +as_cr_digits='0123456789' +as_cr_alnum=$as_cr_Letters$as_cr_digits + + +# Determine whether it's possible to make 'echo' print without a newline. +# These variables are no longer used directly by Autoconf, but are AC_SUBSTed +# for compatibility with existing Makefiles. +ECHO_C= ECHO_N= ECHO_T= +case `echo -n x` in #((((( +-n*) + case `echo 'xy\c'` in + *c*) ECHO_T=' ';; # ECHO_T is single tab character. + xy) ECHO_C='\c';; + *) echo `echo ksh88 bug on AIX 6.1` > /dev/null + ECHO_T=' ';; + esac;; +*) + ECHO_N='-n';; +esac + +# For backward compatibility with old third-party macros, we provide +# the shell variables $as_echo and $as_echo_n. New code should use +# AS_ECHO(["message"]) and AS_ECHO_N(["message"]), respectively. +as_echo='printf %s\n' +as_echo_n='printf %s' + +rm -f conf$$ conf$$.exe conf$$.file +if test -d conf$$.dir; then + rm -f conf$$.dir/conf$$.file +else + rm -f conf$$.dir + mkdir conf$$.dir 2>/dev/null +fi +if (echo >conf$$.file) 2>/dev/null; then + if ln -s conf$$.file conf$$ 2>/dev/null; then + as_ln_s='ln -s' + # ... but there are two gotchas: + # 1) On MSYS, both 'ln -s file dir' and 'ln file dir' fail. + # 2) DJGPP < 2.04 has no symlinks; 'ln -s' creates a wrapper executable. + # In both cases, we have to default to 'cp -pR'. + ln -s conf$$.file conf$$.dir 2>/dev/null && test ! -f conf$$.exe || + as_ln_s='cp -pR' + elif ln conf$$.file conf$$ 2>/dev/null; then + as_ln_s=ln + else + as_ln_s='cp -pR' + fi +else + as_ln_s='cp -pR' +fi +rm -f conf$$ conf$$.exe conf$$.dir/conf$$.file conf$$.file +rmdir conf$$.dir 2>/dev/null + + +# as_fn_mkdir_p +# ------------- +# Create "$as_dir" as a directory, including parents if necessary. +as_fn_mkdir_p () +{ + + case $as_dir in #( + -*) as_dir=./$as_dir;; + esac + test -d "$as_dir" || eval $as_mkdir_p || { + as_dirs= + while :; do + case $as_dir in #( + *\'*) as_qdir=`printf "%s\n" "$as_dir" | sed "s/'/'\\\\\\\\''/g"`;; #'( + *) as_qdir=$as_dir;; + esac + as_dirs="'$as_qdir' $as_dirs" + as_dir=`$as_dirname -- "$as_dir" || +$as_expr X"$as_dir" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \ + X"$as_dir" : 'X\(//\)[^/]' \| \ + X"$as_dir" : 'X\(//\)$' \| \ + X"$as_dir" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X"$as_dir" | + sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{ + s//\1/ + q + } + /^X\(\/\/\)[^/].*/{ + s//\1/ + q + } + /^X\(\/\/\)$/{ + s//\1/ + q + } + /^X\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + test -d "$as_dir" && break + done + test -z "$as_dirs" || eval "mkdir $as_dirs" + } || test -d "$as_dir" || as_fn_error $? "cannot create directory $as_dir" + + +} # as_fn_mkdir_p +if mkdir -p . 2>/dev/null; then + as_mkdir_p='mkdir -p "$as_dir"' +else + test -d ./-p && rmdir ./-p + as_mkdir_p=false +fi + + +# as_fn_executable_p FILE +# ----------------------- +# Test if FILE is an executable regular file. +as_fn_executable_p () +{ + test -f "$1" && test -x "$1" +} # as_fn_executable_p +as_test_x='test -x' +as_executable_p=as_fn_executable_p + +# Sed expression to map a string onto a valid CPP name. +as_sed_cpp="y%*$as_cr_letters%P$as_cr_LETTERS%;s%[^_$as_cr_alnum]%_%g" +as_tr_cpp="eval sed '$as_sed_cpp'" # deprecated + +# Sed expression to map a string onto a valid variable name. +as_sed_sh="y%*+%pp%;s%[^_$as_cr_alnum]%_%g" +as_tr_sh="eval sed '$as_sed_sh'" # deprecated + + +exec 6>&1 +## ----------------------------------- ## +## Main body of $CONFIG_STATUS script. ## +## ----------------------------------- ## +_ASEOF +test $as_write_fail = 0 && chmod +x $CONFIG_STATUS || ac_write_fail=1 + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +# Save the log message, to keep $0 and so on meaningful, and to +# report actual input values of CONFIG_FILES etc. instead of their +# values after options handling. +ac_log=" +This file was extended by RcppEigen $as_me 0.3.4.0.2-1, which was +generated by GNU Autoconf 2.72. Invocation command line was + + CONFIG_FILES = $CONFIG_FILES + CONFIG_HEADERS = $CONFIG_HEADERS + CONFIG_LINKS = $CONFIG_LINKS + CONFIG_COMMANDS = $CONFIG_COMMANDS + $ $0 $@ + +on `(hostname || uname -n) 2>/dev/null | sed 1q` +" + +_ACEOF + +case $ac_config_files in *" +"*) set x $ac_config_files; shift; ac_config_files=$*;; +esac + + + +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +# Files that config.status was made for. +config_files="$ac_config_files" + +_ACEOF + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +ac_cs_usage="\ +'$as_me' instantiates files and other configuration actions +from templates according to the current configuration. Unless the files +and actions are specified as TAGs, all are instantiated by default. + +Usage: $0 [OPTION]... [TAG]... + + -h, --help print this help, then exit + -V, --version print version number and configuration settings, then exit + --config print configuration, then exit + -q, --quiet, --silent + do not print progress messages + -d, --debug don't remove temporary files + --recheck update $as_me by reconfiguring in the same conditions + --file=FILE[:TEMPLATE] + instantiate the configuration file FILE + +Configuration files: +$config_files + +Report bugs to ." + +_ACEOF +ac_cs_config=`printf "%s\n" "$ac_configure_args" | sed "$ac_safe_unquote"` +ac_cs_config_escaped=`printf "%s\n" "$ac_cs_config" | sed "s/^ //; s/'/'\\\\\\\\''/g"` +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +ac_cs_config='$ac_cs_config_escaped' +ac_cs_version="\\ +RcppEigen config.status 0.3.4.0.2-1 +configured by $0, generated by GNU Autoconf 2.72, + with options \\"\$ac_cs_config\\" + +Copyright (C) 2023 Free Software Foundation, Inc. +This config.status script is free software; the Free Software Foundation +gives unlimited permission to copy, distribute and modify it." + +ac_pwd='$ac_pwd' +srcdir='$srcdir' +test -n "\$AWK" || AWK=awk +_ACEOF + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +# The default lists apply if the user does not specify any file. +ac_need_defaults=: +while test $# != 0 +do + case $1 in + --*=?*) + ac_option=`expr "X$1" : 'X\([^=]*\)='` + ac_optarg=`expr "X$1" : 'X[^=]*=\(.*\)'` + ac_shift=: + ;; + --*=) + ac_option=`expr "X$1" : 'X\([^=]*\)='` + ac_optarg= + ac_shift=: + ;; + *) + ac_option=$1 + ac_optarg=$2 + ac_shift=shift + ;; + esac + + case $ac_option in + # Handling of the options. + -recheck | --recheck | --rechec | --reche | --rech | --rec | --re | --r) + ac_cs_recheck=: ;; + --version | --versio | --versi | --vers | --ver | --ve | --v | -V ) + printf "%s\n" "$ac_cs_version"; exit ;; + --config | --confi | --conf | --con | --co | --c ) + printf "%s\n" "$ac_cs_config"; exit ;; + --debug | --debu | --deb | --de | --d | -d ) + debug=: ;; + --file | --fil | --fi | --f ) + $ac_shift + case $ac_optarg in + *\'*) ac_optarg=`printf "%s\n" "$ac_optarg" | sed "s/'/'\\\\\\\\''/g"` ;; + '') as_fn_error $? "missing file argument" ;; + esac + as_fn_append CONFIG_FILES " '$ac_optarg'" + ac_need_defaults=false;; + --he | --h | --help | --hel | -h ) + printf "%s\n" "$ac_cs_usage"; exit ;; + -q | -quiet | --quiet | --quie | --qui | --qu | --q \ + | -silent | --silent | --silen | --sile | --sil | --si | --s) + ac_cs_silent=: ;; + + # This is an error. + -*) as_fn_error $? "unrecognized option: '$1' +Try '$0 --help' for more information." ;; + + *) as_fn_append ac_config_targets " $1" + ac_need_defaults=false ;; + + esac + shift +done + +ac_configure_extra_args= + +if $ac_cs_silent; then + exec 6>/dev/null + ac_configure_extra_args="$ac_configure_extra_args --silent" +fi + +_ACEOF +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +if \$ac_cs_recheck; then + set X $SHELL '$0' $ac_configure_args \$ac_configure_extra_args --no-create --no-recursion + shift + \printf "%s\n" "running CONFIG_SHELL=$SHELL \$*" >&6 + CONFIG_SHELL='$SHELL' + export CONFIG_SHELL + exec "\$@" +fi + +_ACEOF +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +exec 5>>config.log +{ + echo + sed 'h;s/./-/g;s/^.../## /;s/...$/ ##/;p;x;p;x' <<_ASBOX +## Running $as_me. ## +_ASBOX + printf "%s\n" "$ac_log" +} >&5 + +_ACEOF +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +_ACEOF + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 + +# Handling of arguments. +for ac_config_target in $ac_config_targets +do + case $ac_config_target in + "src/Makevars") CONFIG_FILES="$CONFIG_FILES src/Makevars" ;; + + *) as_fn_error $? "invalid argument: '$ac_config_target'" "$LINENO" 5;; + esac +done + + +# If the user did not use the arguments to specify the items to instantiate, +# then the envvar interface is used. Set only those that are not. +# We use the long form for the default assignment because of an extremely +# bizarre bug on SunOS 4.1.3. +if $ac_need_defaults; then + test ${CONFIG_FILES+y} || CONFIG_FILES=$config_files +fi + +# Have a temporary directory for convenience. Make it in the build tree +# simply because there is no reason against having it here, and in addition, +# creating and moving files from /tmp can sometimes cause problems. +# Hook for its removal unless debugging. +# Note that there is a small window in which the directory will not be cleaned: +# after its creation but before its name has been assigned to '$tmp'. +$debug || +{ + tmp= ac_tmp= + trap 'exit_status=$? + : "${ac_tmp:=$tmp}" + { test ! -d "$ac_tmp" || rm -fr "$ac_tmp"; } && exit $exit_status +' 0 + trap 'as_fn_exit 1' 1 2 13 15 +} +# Create a (secure) tmp directory for tmp files. + +{ + tmp=`(umask 077 && mktemp -d "./confXXXXXX") 2>/dev/null` && + test -d "$tmp" +} || +{ + tmp=./conf$$-$RANDOM + (umask 077 && mkdir "$tmp") +} || as_fn_error $? "cannot create a temporary directory in ." "$LINENO" 5 +ac_tmp=$tmp + +# Set up the scripts for CONFIG_FILES section. +# No need to generate them if there are no CONFIG_FILES. +# This happens for instance with './config.status config.h'. +if test -n "$CONFIG_FILES"; then + + +ac_cr=`echo X | tr X '\015'` +# On cygwin, bash can eat \r inside `` if the user requested igncr. +# But we know of no other shell where ac_cr would be empty at this +# point, so we can use a bashism as a fallback. +if test "x$ac_cr" = x; then + eval ac_cr=\$\'\\r\' +fi +ac_cs_awk_cr=`$AWK 'BEGIN { print "a\rb" }' /dev/null` +if test "$ac_cs_awk_cr" = "a${ac_cr}b"; then + ac_cs_awk_cr='\\r' +else + ac_cs_awk_cr=$ac_cr +fi + +echo 'BEGIN {' >"$ac_tmp/subs1.awk" && +_ACEOF + + +{ + echo "cat >conf$$subs.awk <<_ACEOF" && + echo "$ac_subst_vars" | sed 's/.*/&!$&$ac_delim/' && + echo "_ACEOF" +} >conf$$subs.sh || + as_fn_error $? "could not make $CONFIG_STATUS" "$LINENO" 5 +ac_delim_num=`echo "$ac_subst_vars" | grep -c '^'` +ac_delim='%!_!# ' +for ac_last_try in false false false false false :; do + . ./conf$$subs.sh || + as_fn_error $? "could not make $CONFIG_STATUS" "$LINENO" 5 + + ac_delim_n=`sed -n "s/.*$ac_delim\$/X/p" conf$$subs.awk | grep -c X` + if test $ac_delim_n = $ac_delim_num; then + break + elif $ac_last_try; then + as_fn_error $? "could not make $CONFIG_STATUS" "$LINENO" 5 + else + ac_delim="$ac_delim!$ac_delim _$ac_delim!! " + fi +done +rm -f conf$$subs.sh + +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +cat >>"\$ac_tmp/subs1.awk" <<\\_ACAWK && +_ACEOF +sed -n ' +h +s/^/S["/; s/!.*/"]=/ +p +g +s/^[^!]*!// +:repl +t repl +s/'"$ac_delim"'$// +t delim +:nl +h +s/\(.\{148\}\)..*/\1/ +t more1 +s/["\\]/\\&/g; s/^/"/; s/$/\\n"\\/ +p +n +b repl +:more1 +s/["\\]/\\&/g; s/^/"/; s/$/"\\/ +p +g +s/.\{148\}// +t nl +:delim +h +s/\(.\{148\}\)..*/\1/ +t more2 +s/["\\]/\\&/g; s/^/"/; s/$/"/ +p +b +:more2 +s/["\\]/\\&/g; s/^/"/; s/$/"\\/ +p +g +s/.\{148\}// +t delim +' >$CONFIG_STATUS || ac_write_fail=1 +rm -f conf$$subs.awk +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +_ACAWK +cat >>"\$ac_tmp/subs1.awk" <<_ACAWK && + for (key in S) S_is_set[key] = 1 + FS = "" + +} +{ + line = $ 0 + nfields = split(line, field, "@") + substed = 0 + len = length(field[1]) + for (i = 2; i < nfields; i++) { + key = field[i] + keylen = length(key) + if (S_is_set[key]) { + value = S[key] + line = substr(line, 1, len) "" value "" substr(line, len + keylen + 3) + len += length(value) + length(field[++i]) + substed = 1 + } else + len += 1 + keylen + } + + print line +} + +_ACAWK +_ACEOF +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +if sed "s/$ac_cr//" < /dev/null > /dev/null 2>&1; then + sed "s/$ac_cr\$//; s/$ac_cr/$ac_cs_awk_cr/g" +else + cat +fi < "$ac_tmp/subs1.awk" > "$ac_tmp/subs.awk" \ + || as_fn_error $? "could not setup config files machinery" "$LINENO" 5 +_ACEOF + +# VPATH may cause trouble with some makes, so we remove sole $(srcdir), +# ${srcdir} and @srcdir@ entries from VPATH if srcdir is ".", strip leading and +# trailing colons and then remove the whole line if VPATH becomes empty +# (actually we leave an empty line to preserve line numbers). +if test "x$srcdir" = x.; then + ac_vpsub='/^[ ]*VPATH[ ]*=[ ]*/{ +h +s/// +s/^/:/ +s/[ ]*$/:/ +s/:\$(srcdir):/:/g +s/:\${srcdir}:/:/g +s/:@srcdir@:/:/g +s/^:*// +s/:*$// +x +s/\(=[ ]*\).*/\1/ +G +s/\n// +s/^[^=]*=[ ]*$// +}' +fi + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +fi # test -n "$CONFIG_FILES" + + +eval set X " :F $CONFIG_FILES " +shift +for ac_tag +do + case $ac_tag in + :[FHLC]) ac_mode=$ac_tag; continue;; + esac + case $ac_mode$ac_tag in + :[FHL]*:*);; + :L* | :C*:*) as_fn_error $? "invalid tag '$ac_tag'" "$LINENO" 5;; + :[FH]-) ac_tag=-:-;; + :[FH]*) ac_tag=$ac_tag:$ac_tag.in;; + esac + ac_save_IFS=$IFS + IFS=: + set x $ac_tag + IFS=$ac_save_IFS + shift + ac_file=$1 + shift + + case $ac_mode in + :L) ac_source=$1;; + :[FH]) + ac_file_inputs= + for ac_f + do + case $ac_f in + -) ac_f="$ac_tmp/stdin";; + *) # Look for the file first in the build tree, then in the source tree + # (if the path is not absolute). The absolute path cannot be DOS-style, + # because $ac_f cannot contain ':'. + test -f "$ac_f" || + case $ac_f in + [\\/$]*) false;; + *) test -f "$srcdir/$ac_f" && ac_f="$srcdir/$ac_f";; + esac || + as_fn_error 1 "cannot find input file: '$ac_f'" "$LINENO" 5;; + esac + case $ac_f in *\'*) ac_f=`printf "%s\n" "$ac_f" | sed "s/'/'\\\\\\\\''/g"`;; esac + as_fn_append ac_file_inputs " '$ac_f'" + done + + # Let's still pretend it is 'configure' which instantiates (i.e., don't + # use $as_me), people would be surprised to read: + # /* config.h. Generated by config.status. */ + configure_input='Generated from '` + printf "%s\n" "$*" | sed 's|^[^:]*/||;s|:[^:]*/|, |g' + `' by configure.' + if test x"$ac_file" != x-; then + configure_input="$ac_file. $configure_input" + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: creating $ac_file" >&5 +printf "%s\n" "$as_me: creating $ac_file" >&6;} + fi + # Neutralize special characters interpreted by sed in replacement strings. + case $configure_input in #( + *\&* | *\|* | *\\* ) + ac_sed_conf_input=`printf "%s\n" "$configure_input" | + sed 's/[\\\\&|]/\\\\&/g'`;; #( + *) ac_sed_conf_input=$configure_input;; + esac + + case $ac_tag in + *:-:* | *:-) cat >"$ac_tmp/stdin" \ + || as_fn_error $? "could not create $ac_file" "$LINENO" 5 ;; + esac + ;; + esac + + ac_dir=`$as_dirname -- "$ac_file" || +$as_expr X"$ac_file" : 'X\(.*[^/]\)//*[^/][^/]*/*$' \| \ + X"$ac_file" : 'X\(//\)[^/]' \| \ + X"$ac_file" : 'X\(//\)$' \| \ + X"$ac_file" : 'X\(/\)' \| . 2>/dev/null || +printf "%s\n" X"$ac_file" | + sed '/^X\(.*[^/]\)\/\/*[^/][^/]*\/*$/{ + s//\1/ + q + } + /^X\(\/\/\)[^/].*/{ + s//\1/ + q + } + /^X\(\/\/\)$/{ + s//\1/ + q + } + /^X\(\/\).*/{ + s//\1/ + q + } + s/.*/./; q'` + as_dir="$ac_dir"; as_fn_mkdir_p + ac_builddir=. + +case "$ac_dir" in +.) ac_dir_suffix= ac_top_builddir_sub=. ac_top_build_prefix= ;; +*) + ac_dir_suffix=/`printf "%s\n" "$ac_dir" | sed 's|^\.[\\/]||'` + # A ".." for each directory in $ac_dir_suffix. + ac_top_builddir_sub=`printf "%s\n" "$ac_dir_suffix" | sed 's|/[^\\/]*|/..|g;s|/||'` + case $ac_top_builddir_sub in + "") ac_top_builddir_sub=. ac_top_build_prefix= ;; + *) ac_top_build_prefix=$ac_top_builddir_sub/ ;; + esac ;; +esac +ac_abs_top_builddir=$ac_pwd +ac_abs_builddir=$ac_pwd$ac_dir_suffix +# for backward compatibility: +ac_top_builddir=$ac_top_build_prefix + +case $srcdir in + .) # We are building in place. + ac_srcdir=. + ac_top_srcdir=$ac_top_builddir_sub + ac_abs_top_srcdir=$ac_pwd ;; + [\\/]* | ?:[\\/]* ) # Absolute name. + ac_srcdir=$srcdir$ac_dir_suffix; + ac_top_srcdir=$srcdir + ac_abs_top_srcdir=$srcdir ;; + *) # Relative name. + ac_srcdir=$ac_top_build_prefix$srcdir$ac_dir_suffix + ac_top_srcdir=$ac_top_build_prefix$srcdir + ac_abs_top_srcdir=$ac_pwd/$srcdir ;; +esac +ac_abs_srcdir=$ac_abs_top_srcdir$ac_dir_suffix + + + case $ac_mode in + :F) + # + # CONFIG_FILE + # + +_ACEOF + +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +# If the template does not know about datarootdir, expand it. +# FIXME: This hack should be removed a few years after 2.60. +ac_datarootdir_hack=; ac_datarootdir_seen= +ac_sed_dataroot=' +/datarootdir/ { + p + q +} +/@datadir@/p +/@docdir@/p +/@infodir@/p +/@localedir@/p +/@mandir@/p' +case `eval "sed -n \"\$ac_sed_dataroot\" $ac_file_inputs"` in +*datarootdir*) ac_datarootdir_seen=yes;; +*@datadir@*|*@docdir@*|*@infodir@*|*@localedir@*|*@mandir@*) + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: $ac_file_inputs seems to ignore the --datarootdir setting" >&5 +printf "%s\n" "$as_me: WARNING: $ac_file_inputs seems to ignore the --datarootdir setting" >&2;} +_ACEOF +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 + ac_datarootdir_hack=' + s&@datadir@&$datadir&g + s&@docdir@&$docdir&g + s&@infodir@&$infodir&g + s&@localedir@&$localedir&g + s&@mandir@&$mandir&g + s&\\\${datarootdir}&$datarootdir&g' ;; +esac +_ACEOF + +# Neutralize VPATH when '$srcdir' = '.'. +# Shell code in configure.ac might set extrasub. +# FIXME: do we really want to maintain this feature? +cat >>$CONFIG_STATUS <<_ACEOF || ac_write_fail=1 +ac_sed_extra="$ac_vpsub +$extrasub +_ACEOF +cat >>$CONFIG_STATUS <<\_ACEOF || ac_write_fail=1 +:t +/@[a-zA-Z_][a-zA-Z_0-9]*@/!b +s|@configure_input@|$ac_sed_conf_input|;t t +s&@top_builddir@&$ac_top_builddir_sub&;t t +s&@top_build_prefix@&$ac_top_build_prefix&;t t +s&@srcdir@&$ac_srcdir&;t t +s&@abs_srcdir@&$ac_abs_srcdir&;t t +s&@top_srcdir@&$ac_top_srcdir&;t t +s&@abs_top_srcdir@&$ac_abs_top_srcdir&;t t +s&@builddir@&$ac_builddir&;t t +s&@abs_builddir@&$ac_abs_builddir&;t t +s&@abs_top_builddir@&$ac_abs_top_builddir&;t t +$ac_datarootdir_hack +" +eval sed \"\$ac_sed_extra\" "$ac_file_inputs" | $AWK -f "$ac_tmp/subs.awk" \ + >$ac_tmp/out || as_fn_error $? "could not create $ac_file" "$LINENO" 5 + +test -z "$ac_datarootdir_hack$ac_datarootdir_seen" && + { ac_out=`sed -n '/\${datarootdir}/p' "$ac_tmp/out"`; test -n "$ac_out"; } && + { ac_out=`sed -n '/^[ ]*datarootdir[ ]*:*=/p' \ + "$ac_tmp/out"`; test -z "$ac_out"; } && + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: $ac_file contains a reference to the variable 'datarootdir' +which seems to be undefined. Please make sure it is defined" >&5 +printf "%s\n" "$as_me: WARNING: $ac_file contains a reference to the variable 'datarootdir' +which seems to be undefined. Please make sure it is defined" >&2;} + + rm -f "$ac_tmp/stdin" + case $ac_file in + -) cat "$ac_tmp/out" && rm -f "$ac_tmp/out";; + *) rm -f "$ac_file" && mv "$ac_tmp/out" "$ac_file";; + esac \ + || as_fn_error $? "could not create $ac_file" "$LINENO" 5 + ;; + + + + esac + +done # for ac_tag + + +as_fn_exit 0 +_ACEOF +ac_clean_files=$ac_clean_files_save + +test $ac_write_fail = 0 || + as_fn_error $? "write failure creating $CONFIG_STATUS" "$LINENO" 5 + + +# configure is writing to config.log, and then calls config.status. +# config.status does its own redirection, appending to config.log. +# Unfortunately, on DOS this fails, as config.log is still kept open +# by configure, so config.status won't be able to write to it; its +# output is simply discarded. So we exec the FD to /dev/null, +# effectively closing config.log, so it can be properly (re)opened and +# appended to by config.status. When coming back to configure, we +# need to make the FD available again. +if test "$no_create" != yes; then + ac_cs_success=: + ac_config_status_args= + test "$silent" = yes && + ac_config_status_args="$ac_config_status_args --quiet" + exec 5>/dev/null + $SHELL $CONFIG_STATUS $ac_config_status_args || ac_cs_success=false + exec 5>>config.log + # Use ||, not &&, to avoid exiting from the if with $? = 1, which + # would make configure fail if this is the last instruction. + $ac_cs_success || as_fn_exit 1 +fi +if test -n "$ac_unrecognized_opts" && test "$enable_option_checking" != no; then + { printf "%s\n" "$as_me:${as_lineno-$LINENO}: WARNING: unrecognized options: $ac_unrecognized_opts" >&5 +printf "%s\n" "$as_me: WARNING: unrecognized options: $ac_unrecognized_opts" >&2;} +fi + + diff --git a/configure.ac b/configure.ac new file mode 100644 index 00000000..af1d0238 --- /dev/null +++ b/configure.ac @@ -0,0 +1,182 @@ + +## RcppEigen configure.ac +## +## 'Rcpp' Integration for the 'Eigen' Templated Linear Algebra Library +## +## Copyright (C) 2025 Dirk Eddelbuettel +## +## Licensed under GPL-2 or later + +## This is borrowed with love from RcppArmadillo, which itself drew a lot +## of inspiration from the data.table configuration. We have it a little +## bit more easy here as all actual OpenMP-using code is inside Eigen. + +## require at least autoconf 2.69 +AC_PREREQ([2.69]) + +## Process this file with autoconf to produce a configure script. +AC_INIT([RcppEigen],[0.3.4.0.2-1],[edd@debian.org]) + +## Set R_HOME, respecting an environment variable if one is set +: ${R_HOME=$(R RHOME)} +if test -z "${R_HOME}"; then + AC_MSG_ERROR([Could not determine R_HOME.]) +fi + +## Use R to set CXX and CXXFLAGS +CXX=$(${R_HOME}/bin/R CMD config CXX) +CXXFLAGS=$("${R_HOME}/bin/R" CMD config CXXFLAGS) + +## We are using C++ +AC_LANG(C++) +AC_REQUIRE_CPP +AC_PROG_CXX + +## Rely on Sys.info() from R for cross-compilation cases +AC_MSG_CHECKING([what system we are on]) +SYSKERNEL=$("${R_HOME}/bin/Rscript" --vanilla -e 'cat(Sys.info()[["sysname"]])') +SYSMACHINE=$("${R_HOME}/bin/Rscript" --vanilla -e 'cat(Sys.info()[["machine"]])') +AC_MSG_RESULT([running ${SYSKERNEL} on ${SYSMACHINE}]) + + +## Default to not assuming OpenMP, but then test a variety of setups +can_use_openmp="no" + +## Ensure TMPDIR is set. +AC_MSG_CHECKING([whether we have a suitable tempdir]) +TMPDIR=$("${R_HOME}/bin/R" --vanilla --slave -e "cat(dirname(tempdir()))") +AC_MSG_RESULT([${TMPDIR}]) + +## Create private directory in TMPDIR. +BUILDDIR="${TMPDIR}/rcppeigen-$$-$RANDOM" +mkdir -p "${BUILDDIR}" + +owd=$(pwd) +cd "${BUILDDIR}" + +cat < test-omp.cpp +#include +int main() { + return omp_get_num_threads(); +} +EOF + +AC_MSG_CHECKING([whether on Linux]) +if test x"${SYSKERNEL}" = x"Linux"; then + AC_MSG_RESULT([yes]) + + ## Check if R is configured to compile OpenMP programs out-of-the-box. + if test x"${can_use_openmp}" = x"no"; then + AC_MSG_CHECKING([whether R CMD SHLIB can already compile OpenMP programs]) + "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + AC_MSG_RESULT([yes]) + can_use_openmp="yes" + else + AC_MSG_RESULT([no]) + can_use_openmp="no" + fi + fi + + ## If needed, check if R is configured to compile OpenMP programs using -fopenmp + if test x"${can_use_openmp}" = x"no"; then + AC_MSG_CHECKING([whether R CMD SHLIB can compile OpenMP via -fopenmp]) + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" PKG_LIBS="${PKG_LIBS} -fopenmp" "${R_HOME}/bin/R" CMD SHLIB -fopenmp test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + AC_MSG_RESULT([yes]) + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" + PKG_LIBS="${PKG_LIBS} -fopenmp" + else + AC_MSG_RESULT([no]) + can_use_openmp="no" + fi + fi +else + AC_MSG_RESULT([no]) +fi # if Linux + +AC_MSG_CHECKING([whether on macOS]) +if test x"${SYSKERNEL}" = x"Darwin"; then + AC_MSG_RESULT([yes]) + + ## Check if R is configured to compile OpenMP programs using -Xclang -fopenmp + if test x"${can_use_openmp}" = x"no"; then + AC_MSG_CHECKING([whether R CMD SHLIB can compile OpenMP programs using '-Xclang -fopenmp']) + PKG_CXXFLAGS="${PKG_CXXFLAGS} -Xclang -fopenmp" PKG_LIBS="${PKG_LIBS} -lomp" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + AC_MSG_RESULT([yes]) + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -Xclang -fopenmp" + PKG_LIBS="${PKG_LIBS} -lomp" + else + AC_MSG_RESULT([no]) + can_use_openmp="no" + fi + fi + + ## Check if R is configured to compile OpenMP programs using -fopenmp (cf data.table #6409) + if test x"${can_use_openmp}" = x"no"; then + AC_MSG_CHECKING([whether R CMD SHLIB can compile OpenMP programs using '-fopenmp']) + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" PKG_LIBS="${PKG_LIBS} -fopenmp" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + AC_MSG_RESULT([yes]) + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} -fopenmp" + PKG_LIBS="${PKG_LIBS} -fopenmp" + else + AC_MSG_RESULT([no]) + can_use_openmp="no" + fi + fi + + if test x"${can_use_openmp}" = x"no"; then + if test x"${SYSMACHINE}" = x"arm64"; then + HOMEBREW_PREFIX=/opt/homebrew + else + HOMEBREW_PREFIX=/usr/local + fi + if test -e "${HOMEBREW_PREFIX}/opt/libomp"; then + AC_MSG_CHECKING([whether R CMD SHLIB can use libomp at ${HOMEBREW_PREFIX}/opt/libomp]) + LIBOMP_INCLUDE="-I${HOMEBREW_PREFIX}/opt/libomp/include -Xclang -fopenmp" + LIBOMP_LINK="-L${HOMEBREW_PREFIX}/opt/libomp/lib -lomp" + PKG_CXXFLAGS="${PKG_CXXFLAGS} ${LIBOMP_INCLUDE}" PKG_LIBS="${PKG_LIBS} ${LIBOMP_LINK}" "${R_HOME}/bin/R" CMD SHLIB test-omp.cpp >/dev/null 2>&1 + if test x"$?" = x"0"; then + AC_MSG_RESULT([yes]) + can_use_openmp="yes" + # keep any entries user may have set + PKG_CXXFLAGS="${PKG_CXXFLAGS} ${LIBOMP_INCLUDE}" + PKG_LIBS="${PKG_LIBS} ${LIBOMP_LINK}" + else + AC_MSG_RESULT([no]) + can_use_openmp="no" + fi + fi + fi +else + AC_MSG_RESULT([no]) +fi # if macOS + +## Go back home. +cd "${owd}" +rm -rf "${BUILDDIR}" + +# Overall summary +AC_MSG_CHECKING([for OpenMP]) +if test x"${can_use_openmp}" = x"yes"; then + AC_MSG_RESULT([found and suitable]) + openmp_flag='$(SHLIB_OPENMP_CXXFLAGS)' +else + AC_MSG_RESULT([missing so no OpenMP acceleration]) + openmp_flag="" +fi + +## Now use all these +AC_SUBST([OPENMP_FLAG], ["${openmp_flag}"]) +AC_SUBST([PKG_CXXFLAGS], ["${PKG_CXXFLAGS}"]) +AC_SUBST([PKG_LIBS], ["${PKG_LIBS}"]) +AC_CONFIG_FILES([src/Makevars]) +AC_OUTPUT diff --git a/debian/changelog b/debian/changelog deleted file mode 100644 index 86640a6e..00000000 --- a/debian/changelog +++ /dev/null @@ -1,120 +0,0 @@ -r-cran-rcppeigen (0.3.2.7.0-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Tue, 19 Jan 2016 20:35:19 -0600 - -r-cran-rcppeigen (0.3.2.5.1-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Wed, 23 Sep 2015 06:15:08 -0500 - -r-cran-rcppeigen (0.3.2.5.0-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Tue, 14 Jul 2015 17:57:58 -0500 - -r-cran-rcppeigen (0.3.2.4.0-1) unstable; urgency=low - - * New upstream release - - * debian/control: Add r-cran-pkgkitten to (Build-)Depends - - -- Dirk Eddelbuettel Thu, 26 Feb 2015 14:12:35 -0600 - -r-cran-rcppeigen (0.3.2.3.0-1) unstable; urgency=low - - * New upstream release - - * debian/control: Set Build-Depends: to current R version - * debian/control: Set Standards-Version: to current version - - -- Dirk Eddelbuettel Tue, 23 Dec 2014 14:46:16 -0600 - -r-cran-rcppeigen (0.3.2.2.0-1) unstable; urgency=low - - * New upstream release - - * debian/control: Set Build-Depends: to current R version - - -- Dirk Eddelbuettel Thu, 21 Aug 2014 07:10:31 -0500 - -r-cran-rcppeigen (0.3.2.1.2-1) unstable; urgency=low - - * New upstream release - - * debian/control: Set Build-Depends: to current R version - - -- Dirk Eddelbuettel Tue, 06 May 2014 18:08:48 -0500 - -r-cran-rcppeigen (0.3.2.1.1-1) unstable; urgency=low - - * New upstream release - - * debian/control: Set Build-Depends: to current R version - - -- Dirk Eddelbuettel Sat, 08 Mar 2014 08:10:32 -0600 - -r-cran-rcppeigen (0.3.2.1.0-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Mon, 03 Mar 2014 19:37:28 -0600 - -r-cran-rcppeigen (0.3.2.0.3-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Sat, 01 Mar 2014 19:09:07 -0600 - -r-cran-rcppeigen (0.3.2.0.2-2) unstable; urgency=low - - * Rebuilt as required for Rcpp 0.11.0 - * debian/control: Added (Build-)Depends: on r-cran-rcpp (>= 0.11.0-1) - - -- Dirk Eddelbuettel Mon, 03 Feb 2014 20:27:49 -0600 - -r-cran-rcppeigen (0.3.2.0.2-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Sun, 26 Jan 2014 11:43:41 -0600 - -r-cran-rcppeigen (0.3.2.0.1-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Thu, 19 Dec 2013 19:35:07 -0600 - -r-cran-rcppeigen (0.3.2.0-1) unstable; urgency=low - - * New upstream release - - -- Dirk Eddelbuettel Wed, 13 Nov 2013 15:06:56 -0600 - -r-cran-rcppeigen (0.3.1.2.3-2) unstable; urgency=low - - * debian/control: Correcting Depends: on r-cran-rcppeigen - - -- Dirk Eddelbuettel Tue, 29 Oct 2013 16:43:18 -0500 - -r-cran-rcppeigen (0.3.1.2.3-1) unstable; urgency=low - - * New upstream release - - * debian/control: Set Build-Depends: to current R version - * debian/control: Set Standards-Version: to current version - - * debian/control: Update Build-Depends: to r-cran-matrix (>= 1.1-0) - - -- Dirk Eddelbuettel Tue, 29 Oct 2013 06:30:00 -0500 - -r-cran-rcppeigen (0.3.1.2.1-1) unstable; urgency=low - - * Initial Debian release (Closes: #722652) - - -- Dirk Eddelbuettel Thu, 12 Sep 2013 20:59:34 -0500 - - diff --git a/debian/compat b/debian/compat deleted file mode 100644 index 7f8f011e..00000000 --- a/debian/compat +++ /dev/null @@ -1 +0,0 @@ -7 diff --git a/debian/control b/debian/control deleted file mode 100644 index 53d0d062..00000000 --- a/debian/control +++ /dev/null @@ -1,22 +0,0 @@ -Source: r-cran-rcppeigen -Section: gnu-r -Priority: optional -Maintainer: Dirk Eddelbuettel -Build-Depends: debhelper (>= 7.0.0), r-base-dev (>= 3.2.3), cdbs, r-cran-rcpp (>= 0.11.0), r-cran-matrix (>= 1.1-0), r-cran-pkgkitten -Standards-Version: 3.9.6 - -Package: r-cran-rcppeigen -Architecture: any -Depends: ${shlibs:Depends}, ${misc:Depends}, ${R:Depends}, r-cran-rcpp (>= 0.11.0-1), r-cran-matrix (>= 1.1-0), r-cran-pkgkitten -Description: GNU R package for Eigen templated linear algebra - Eigen is a C++ template library for linear algebra: matrices, vectors, - numerical solvers and related algorithms. It supports dense - and sparse matrices on integer, floating point and complex - numbers, decompositions of such matrices, and solutions of - linear systems. Its performance on many algorithms is - comparable with some of the best implementations based on - Lapack and level-3 BLAS. - . - The RcppEigen package includes the header files from the Eigen C++ - template library. Thus users do not need to install Eigen itself in - order to use RcppEigen. diff --git a/debian/copyright b/debian/copyright deleted file mode 100644 index 70f072d6..00000000 --- a/debian/copyright +++ /dev/null @@ -1,581 +0,0 @@ -This is the Debian GNU/Linux r-cran-rcppeigen package of RcppEigen. -The RcppEigen package provides GNU R integration of the Eigen -templated linear algebra library by using Rcpp and was written by -Douglas Bates, Romain Francois and Dirk Eddelbuettel. - -This package was created by Dirk Eddelbuettel . -The sources were downloaded from the main CRAN site - http://cran.r-project.org/src/contrib/ -and are also available from all CRAN mirrors as e.g. - http://cran.us.r-project.org/src/contrib/ - -The package was renamed from its upstream name 'RcppEigen' to -'r-cran-rcppeigen' to fit the pattern of CRAN (and non-CRAN) packages -for R. - - - -Files: inst/include/Eigen/* inst/include/unsupported/Eigen/* -Copyright: 2006 - 2012 Gael Guennebaud, Benoit Jacob -License: MPL-2 - -Files: unsupported/Eigen/FFT unsupported/Eigen/src/FFT/ei_fftw_impl.h unsupported/Eigen/src/FFT/ei_kissfft_impl.h -Copyright: 2003 - 2009 Mark Borgerding -License: MPL-2 - -Files: inst/include/Eigen/src/SuperLUSupport/SuperLUSupport.h -Copyright: 1994 Xerox Corporation -License: - THIS MATERIAL IS PROVIDED AS IS, WITH ABSOLUTELY NO WARRANTY - EXPRESSED OR IMPLIED. ANY USE IS AT YOUR OWN RISK. - -Files: inst/include/unsupported/Eigen/src/IterativeSolvers/IterationController.h -Copyright: 1997 - 2001 Andrew Lumsdaine and Lie-Quan Lee -License: - This file is part of the Iterative Template Library - - You should have received a copy of the License Agreement for the - Iterative Template Library along with the software; see the - file LICENSE. - - Permission to modify the code and to distribute modified code is - granted, provided the text of this NOTICE is retained, a notice that - the code was modified is included with the above COPYRIGHT NOTICE and - with the COPYRIGHT NOTICE in the LICENSE file, and that the LICENSE - file is distributed with the modified code. - - LICENSOR MAKES NO REPRESENTATIONS OR WARRANTIES, EXPRESS OR IMPLIED. - By way of example, but not limitation, Licensor MAKES NO - REPRESENTATIONS OR WARRANTIES OF MERCHANTABILITY OR FITNESS FOR ANY - PARTICULAR PURPOSE OR THAT THE USE OF THE LICENSED SOFTWARE COMPONENTS - OR DOCUMENTATION WILL NOT INFRINGE ANY PATENTS, COPYRIGHTS, TRADEMARKS - OR OTHER RIGHTS. - -Files: inst/include/unsupported/Eigen/Splines inst/include/unsupported/Eigen/src/Splines/SplineFitting.h inst/include/unsupported/Eigen/src/Splines/SplineFwd.h inst/include/unsupported/Eigen/src/Splines/Spline.h inst/include/Eigen/src/Geometry/Umeyama.h inst/include/Eigen/src/StlSupport/details.h inst/include/Eigen/src/StlSupport/StdDeque.h inst/include/Eigen/src/StlSupport/StdList.h inst/include/Eigen/src/StlSupport/StdVector.h inst/include/Eigen/StdDeque inst/include/Eigen/StdList inst/include/Eigen/StdVector inst/include/Eigen/src/Core/DenseStorage.h inst/include/Eigen/src/Core/util/Memory.h inst/include/Eigen/src/Geometry/Transform.h -Copyright: 2009 - 2011 Hauke Heibel -License: MPL-2 - -Files: inst/include/Eigen/src/LU/arch/Inverse_SSE.h inst/include/Eigen/src/Cholesky/LLT_MKL.h inst/include/Eigen/src/Core/Assign_MKL.h inst/include/Eigen/src/Core/products/GeneralMatrixMatrix_MKL.h inst/include/Eigen/src/Core/products/GeneralMatrixMatrixTriangular_MKL.h inst/include/Eigen/src/Core/products/GeneralMatrixVector_MKL.h inst/include/Eigen/src/Core/products/SelfadjointMatrixMatrix_MKL.h inst/include/Eigen/src/Core/products/SelfadjointMatrixVector_MKL.h inst/include/Eigen/src/Core/products/TriangularMatrixMatrix_MKL.h inst/include/Eigen/src/Core/products/TriangularMatrixVector_MKL.h inst/include/Eigen/src/Core/products/TriangularSolverMatrix_MKL.h inst/include/Eigen/src/Core/util/MKL_support.h inst/include/Eigen/src/Eigenvalues/ComplexSchur_MKL.h inst/include/Eigen/src/Eigenvalues/RealSchur_MKL.h inst/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver_MKL.h inst/include/Eigen/src/LU/PartialPivLU_MKL.h inst/include/Eigen/src/PardisoSupport/PardisoSupport.h inst/include/Eigen/src/QR/ColPivHouseholderQR_MKL.h inst/include/Eigen/src/QR/HouseholderQR_MKL.h inst/include/Eigen/src/SVD/JacobiSVD_MKL.h -Copyright: 2001 Intel Corporation -License: - Permition is granted to use, copy, distribute and prepare derivative works - of this library for any purpose and without fee, provided, that the above - copyright notice and this statement appear in all copies. - Intel makes no representations about the suitability of this software for - any purpose, and specifically disclaims all warranties. - -Files: inst/include/unsupported/Eigen/src/IterativeSolvers/ConstrainedConjGrad.h -Copyright: 2002 - 2007 Yves Renard -License: LPGL-2.1 - -Files: inst/include/Eigen/src/OrderingMethods/Amd.h -Copyright: 2006 Timothy A. Davis -License: LGPL-2.1 - -Files: inst/include/Eigen/src/Core/arch/SSE/MathFunctions.h -Copyright: 2007 Julien Pommier -License: MPL-2 - -Files: inst/include/Eigen/src/Core/Assign.h -Copyright: 2007 Michael Olbrich -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/Skyline/SkylineMatrixBase.h inst/include/unsupported/Eigen/src/Skyline/SkylineMatrix.h inst/include/unsupported/Eigen/src/Skyline/SkylineProduct.h inst/include/unsupported/Eigen/src/Skyline/SkylineStorage.h inst/include/unsupported/Eigen/src/Skyline/SkylineInplaceLU.h inst/include/unsupported/Eigen/src/Skyline/SkylineUtil.h -Copyright: 2008 - 2009 Guillaume Saupin ; -License: MPL-2 - -Files: inst/include/Eigen/src/Core/arch/AltiVec/PacketMath.h inst/include/Eigen/src/Core/arch/NEON/PacketMath.h -Copyright: 2008 Konstantinos Margaritis -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h inst/include/unsupported/Eigen/src/MatrixFunction.h inst/include/unsupported/Eigen/MatrixFunctions inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixFunctionAtomic.h inst/include/Eigen/src/Eigenvalues/ComplexEigenSolver.h inst/include/Eigen/src/Eigenvalues/ComplexSchur.h inst/include/Eigen/src/Eigenvalues/EigenSolver.h inst/include/Eigen/src/Eigenvalues/GeneralizedSelfAdjointEigenSolver.h inst/include/Eigen/src/Eigenvalues/HessenbergDecomposition.h inst/include/Eigen/src/Eigenvalues/MatrixBaseEigenvalues.h inst/include/Eigen/src/Eigenvalues/RealSchur.h inst/include/Eigen/src/Eigenvalues/SelfAdjointEigenSolver.h inst/include/Eigen/src/Eigenvalues/Tridiagonalization.h inst/include/unsupported/Eigen/src/MatrixFunctions/StemFunction.h inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixSquareRoot.h -Copyright: 2009 - 2010 Jitse Niesen -License: MPL-2 - -Files: inst/include/Eigen/src/Eigenvalues/ComplexEigenSolver.h inst/include/Eigen/src/Eigenvalues/ComplexSchur.h -Copyright: 2009 Claire Maurice -License: MPL-2 - -Files: inst/include/unsupported/Eigen/BVH inst/include/unsupported/Eigen/src/BVH/BVAlgorithms.h inst/include/unsupported/Eigen/src/BVH/KdBVH.h -Copyright: 2009 Ilya Baran -License: MPL-2 - -Files: inst/include/Eigen/src/Cholesky/LDLT.h -Copyright: 2009 Keir Mierle -License: MPL-2 - -Files: inst/include/Eigen/src/Geometry/Quaternion.h -Copyright: 2009 Mathieu Gautier -License: MPL-2 - -Files: inst/include/Eigen/src/Geometry/arch/Geometry_SSE.h inst/include/unsupported/Eigen/src/MoreVectorization/MathFunctions.h -Copyright: 2009 Rohit Garg -License: MPL-2 - -Files: inst/include/unsupported/Eigen/NonLinearOptimization inst/include/unsupported/Eigen/NumericalDiff inst/include/unsupported/Eigen/src/NonLinearOptimization/HybridNonLinearSolver.h inst/include/unsupported/Eigen/src/NonLinearOptimization/LevenbergMarquardt.h inst/include/unsupported/Eigen/src/NumericalDiff/NumericalDiff.h inst/include/Eigen/src/Core/util/Memory.h -Copyright: 2009 - 2010 Thomas Capricelli -License: MPL-2 - -Files: inst/include/Eigen/src/SparseCore/SparseView.h inst/include/Eigen/src/Sparse/SparseView.h -Copyright: 2010 Daniel Lowengrub -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/Polynomials/Companion.h inst/include/unsupported/Eigen/src/Polynomials/PolynomialSolver.h inst/include/unsupported/Eigen/src/Polynomials/PolynomialUtils.h -Copyright: 2010 Manuel Yguel -License: MPL-2 - -Files: inst/include/Eigen/src/Householder/BlockHouseholder.h inst/include/Eigen/src/QR/HouseholderQR.h -Copyright: 2010 Vincent Lejeune -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h -Copyright: 2011 Andreas Platen -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixExponential.h inst/include/unsupported/Eigen/src/MatrixFunctions/MatrixLogarithm.h -Copyright: 2011 Chen-Pang He -License: MPL-2 - -Files: inst/include/unsupported/Eigen/src/KroneckerProduct/KroneckerTensorProduct.h inst/include/unsupported/Eigen/src/IterativeSolvers/GMRES.h -Copyright: 2012 Kolja Brix -License: MPL-2 - -Files: inst/include/Eigen/src/Cholesky/LDLT.h -Copyright: 2011 Timothy E. Holy -License: MPL-2 - -Files: inst/include/Eigen/src/IterativeLinearSolvers/BiCGSTAB.h inst/include/Eigen/src/IterativeLinearSolvers/IncompleteLUT.h inst/include/Eigen/src/PaStiXSupport/PaStiXSupport.h inst/include/unsupported/Eigen/src/IterativeSolvers/Scaling.h inst/include/unsupported/Eigen/src/SparseExtra/MarketIO.h inst/include/unsupported/Eigen/src/SparseExtra/MatrixMarketIterator.h -Copyright: 2012 Désiré Nuentsa-Wakam -License: MPL-2 - -Files: * -Copyright: 2011 - 2013 Douglas Bates, Romain Francois and Dirk Eddelbuettel -License: GPL-2 - -Files: debian/* -Copyright: 2013 Dirk Eddelbuettel -License: GPL-2 - - -On a Debian GNU/Linux system, the GPL license (version 2) is included -in the file /usr/share/common-licenses/GPL-2. - -On a Debian GNU/Linux system, the LPGL license (version 2.1) is included -in the file /usr/share/common-licenses/LGPL-2.1. - -License: MPL-2 - Mozilla Public License Version 2.0 - ================================== - . - 1. Definitions - -------------- - . - 1.1. "Contributor" - means each individual or legal entity that creates, contributes to - the creation of, or owns Covered Software. - . - 1.2. "Contributor Version" - means the combination of the Contributions of others (if any) used - by a Contributor and that particular Contributor's Contribution. - . - 1.3. "Contribution" - means Covered Software of a particular Contributor. - . - 1.4. "Covered Software" - means Source Code Form to which the initial Contributor has attached - the notice in Exhibit A, the Executable Form of such Source Code - Form, and Modifications of such Source Code Form, in each case - including portions thereof. - . - 1.5. "Incompatible With Secondary Licenses" - means - . - (a) that the initial Contributor has attached the notice described - in Exhibit B to the Covered Software; or - . - (b) that the Covered Software was made available under the terms of - version 1.1 or earlier of the License, but not also under the - terms of a Secondary License. - . - 1.6. "Executable Form" - means any form of the work other than Source Code Form. - . - 1.7. "Larger Work" - means a work that combines Covered Software with other material, in - a separate file or files, that is not Covered Software. - . - 1.8. "License" - means this document. - . - 1.9. "Licensable" - means having the right to grant, to the maximum extent possible, - whether at the time of the initial grant or subsequently, any and - all of the rights conveyed by this License. - . - 1.10. "Modifications" - means any of the following: - . - (a) any file in Source Code Form that results from an addition to, - deletion from, or modification of the contents of Covered - Software; or - . - (b) any new file in Source Code Form that contains any Covered - Software. - . - 1.11. "Patent Claims" of a Contributor - means any patent claim(s), including without limitation, method, - process, and apparatus claims, in any patent Licensable by such - Contributor that would be infringed, but for the grant of the - License, by the making, using, selling, offering for sale, having - made, import, or transfer of either its Contributions or its - Contributor Version. - . - 1.12. "Secondary License" - means either the GNU General Public License, Version 2.0, the GNU - Lesser General Public License, Version 2.1, the GNU Affero General - Public License, Version 3.0, or any later versions of those - licenses. - . - 1.13. "Source Code Form" - means the form of the work preferred for making modifications. - . - 1.14. "You" (or "Your") - means an individual or a legal entity exercising rights under this - License. For legal entities, "You" includes any entity that - controls, is controlled by, or is under common control with You. For - purposes of this definition, "control" means (a) the power, direct - or indirect, to cause the direction or management of such entity, - whether by contract or otherwise, or (b) ownership of more than - fifty percent (50%) of the outstanding shares or beneficial - ownership of such entity. - . - 2. License Grants and Conditions - -------------------------------- - . - 2.1. Grants - . - Each Contributor hereby grants You a world-wide, royalty-free, - non-exclusive license: - . - (a) under intellectual property rights (other than patent or trademark) - Licensable by such Contributor to use, reproduce, make available, - modify, display, perform, distribute, and otherwise exploit its - Contributions, either on an unmodified basis, with Modifications, or - as part of a Larger Work; and - . - (b) under Patent Claims of such Contributor to make, use, sell, offer - for sale, have made, import, and otherwise transfer either its - Contributions or its Contributor Version. - . - 2.2. Effective Date - . - The licenses granted in Section 2.1 with respect to any Contribution - become effective for each Contribution on the date the Contributor first - distributes such Contribution. - . - 2.3. Limitations on Grant Scope - . - The licenses granted in this Section 2 are the only rights granted under - this License. No additional rights or licenses will be implied from the - distribution or licensing of Covered Software under this License. - Notwithstanding Section 2.1(b) above, no patent license is granted by a - Contributor: - . - (a) for any code that a Contributor has removed from Covered Software; - or - . - (b) for infringements caused by: (i) Your and any other third party's - modifications of Covered Software, or (ii) the combination of its - Contributions with other software (except as part of its Contributor - Version); or - . - (c) under Patent Claims infringed by Covered Software in the absence of - its Contributions. - . - This License does not grant any rights in the trademarks, service marks, - or logos of any Contributor (except as may be necessary to comply with - the notice requirements in Section 3.4). - . - 2.4. Subsequent Licenses - . - No Contributor makes additional grants as a result of Your choice to - distribute the Covered Software under a subsequent version of this - License (see Section 10.2) or under the terms of a Secondary License (if - permitted under the terms of Section 3.3). - . - 2.5. Representation - . - Each Contributor represents that the Contributor believes its - Contributions are its original creation(s) or it has sufficient rights - to grant the rights to its Contributions conveyed by this License. - . - 2.6. Fair Use - . - This License is not intended to limit any rights You have under - applicable copyright doctrines of fair use, fair dealing, or other - equivalents. - . - 2.7. Conditions - . - Sections 3.1, 3.2, 3.3, and 3.4 are conditions of the licenses granted - in Section 2.1. - . - 3. Responsibilities - ------------------- - . - 3.1. Distribution of Source Form - . - All distribution of Covered Software in Source Code Form, including any - Modifications that You create or to which You contribute, must be under - the terms of this License. You must inform recipients that the Source - Code Form of the Covered Software is governed by the terms of this - License, and how they can obtain a copy of this License. You may not - attempt to alter or restrict the recipients' rights in the Source Code - Form. - . - 3.2. Distribution of Executable Form - . - If You distribute Covered Software in Executable Form then: - . - (a) such Covered Software must also be made available in Source Code - Form, as described in Section 3.1, and You must inform recipients of - the Executable Form how they can obtain a copy of such Source Code - Form by reasonable means in a timely manner, at a charge no more - than the cost of distribution to the recipient; and - . - (b) You may distribute such Executable Form under the terms of this - License, or sublicense it under different terms, provided that the - license for the Executable Form does not attempt to limit or alter - the recipients' rights in the Source Code Form under this License. - . - 3.3. Distribution of a Larger Work - . - You may create and distribute a Larger Work under terms of Your choice, - provided that You also comply with the requirements of this License for - the Covered Software. If the Larger Work is a combination of Covered - Software with a work governed by one or more Secondary Licenses, and the - Covered Software is not Incompatible With Secondary Licenses, this - License permits You to additionally distribute such Covered Software - under the terms of such Secondary License(s), so that the recipient of - the Larger Work may, at their option, further distribute the Covered - Software under the terms of either this License or such Secondary - License(s). - . - 3.4. Notices - . - You may not remove or alter the substance of any license notices - (including copyright notices, patent notices, disclaimers of warranty, - or limitations of liability) contained within the Source Code Form of - the Covered Software, except that You may alter any license notices to - the extent required to remedy known factual inaccuracies. - . - 3.5. Application of Additional Terms - . - You may choose to offer, and to charge a fee for, warranty, support, - indemnity or liability obligations to one or more recipients of Covered - Software. However, You may do so only on Your own behalf, and not on - behalf of any Contributor. You must make it absolutely clear that any - such warranty, support, indemnity, or liability obligation is offered by - You alone, and You hereby agree to indemnify every Contributor for any - liability incurred by such Contributor as a result of warranty, support, - indemnity or liability terms You offer. You may include additional - disclaimers of warranty and limitations of liability specific to any - jurisdiction. - . - 4. Inability to Comply Due to Statute or Regulation - --------------------------------------------------- - . - If it is impossible for You to comply with any of the terms of this - License with respect to some or all of the Covered Software due to - statute, judicial order, or regulation then You must: (a) comply with - the terms of this License to the maximum extent possible; and (b) - describe the limitations and the code they affect. Such description must - be placed in a text file included with all distributions of the Covered - Software under this License. Except to the extent prohibited by statute - or regulation, such description must be sufficiently detailed for a - recipient of ordinary skill to be able to understand it. - . - 5. Termination - -------------- - . - 5.1. The rights granted under this License will terminate automatically - if You fail to comply with any of its terms. However, if You become - compliant, then the rights granted under this License from a particular - Contributor are reinstated (a) provisionally, unless and until such - Contributor explicitly and finally terminates Your grants, and (b) on an - ongoing basis, if such Contributor fails to notify You of the - non-compliance by some reasonable means prior to 60 days after You have - come back into compliance. Moreover, Your grants from a particular - Contributor are reinstated on an ongoing basis if such Contributor - notifies You of the non-compliance by some reasonable means, this is the - first time You have received notice of non-compliance with this License - from such Contributor, and You become compliant prior to 30 days after - Your receipt of the notice. - . - 5.2. If You initiate litigation against any entity by asserting a patent - infringement claim (excluding declaratory judgment actions, - counter-claims, and cross-claims) alleging that a Contributor Version - directly or indirectly infringes any patent, then the rights granted to - You by any and all Contributors for the Covered Software under Section - 2.1 of this License shall terminate. - . - 5.3. In the event of termination under Sections 5.1 or 5.2 above, all - end user license agreements (excluding distributors and resellers) which - have been validly granted by You or Your distributors under this License - prior to termination shall survive termination. - . - ************************************************************************ - * * - * 6. Disclaimer of Warranty * - * ------------------------- * - * * - * Covered Software is provided under this License on an "as is" * - * basis, without warranty of any kind, either expressed, implied, or * - * statutory, including, without limitation, warranties that the * - * Covered Software is free of defects, merchantable, fit for a * - * particular purpose or non-infringing. The entire risk as to the * - * quality and performance of the Covered Software is with You. * - * Should any Covered Software prove defective in any respect, You * - * (not any Contributor) assume the cost of any necessary servicing, * - * repair, or correction. This disclaimer of warranty constitutes an * - * essential part of this License. No use of any Covered Software is * - * authorized under this License except under this disclaimer. * - * * - ************************************************************************ - . - ************************************************************************ - * * - * 7. Limitation of Liability * - * -------------------------- * - * * - * Under no circumstances and under no legal theory, whether tort * - * (including negligence), contract, or otherwise, shall any * - * Contributor, or anyone who distributes Covered Software as * - * permitted above, be liable to You for any direct, indirect, * - * special, incidental, or consequential damages of any character * - * including, without limitation, damages for lost profits, loss of * - * goodwill, work stoppage, computer failure or malfunction, or any * - * and all other commercial damages or losses, even if such party * - * shall have been informed of the possibility of such damages. This * - * limitation of liability shall not apply to liability for death or * - * personal injury resulting from such party's negligence to the * - * extent applicable law prohibits such limitation. Some * - * jurisdictions do not allow the exclusion or limitation of * - * incidental or consequential damages, so this exclusion and * - * limitation may not apply to You. * - * * - ************************************************************************ - . - 8. Litigation - ------------- - . - Any litigation relating to this License may be brought only in the - courts of a jurisdiction where the defendant maintains its principal - place of business and such litigation shall be governed by laws of that - jurisdiction, without reference to its conflict-of-law provisions. - Nothing in this Section shall prevent a party's ability to bring - cross-claims or counter-claims. - . - 9. Miscellaneous - ---------------- - . - This License represents the complete agreement concerning the subject - matter hereof. If any provision of this License is held to be - unenforceable, such provision shall be reformed only to the extent - necessary to make it enforceable. Any law or regulation which provides - that the language of a contract shall be construed against the drafter - shall not be used to construe this License against a Contributor. - . - 10. Versions of the License - --------------------------- - . - 10.1. New Versions - . - Mozilla Foundation is the license steward. Except as provided in Section - 10.3, no one other than the license steward has the right to modify or - publish new versions of this License. Each version will be given a - distinguishing version number. - . - 10.2. Effect of New Versions - . - You may distribute the Covered Software under the terms of the version - of the License under which You originally received the Covered Software, - or under the terms of any subsequent version published by the license - steward. - . - 10.3. Modified Versions - . - If you create software not governed by this License, and you want to - create a new license for such software, you may create and use a - modified version of this License if you rename the license and remove - any references to the name of the license steward (except to note that - such modified license differs from this License). - . - 10.4. Distributing Source Code Form that is Incompatible With Secondary - Licenses - . - If You choose to distribute Source Code Form that is Incompatible With - Secondary Licenses under the terms of this version of the License, the - notice described in Exhibit B of this License must be attached. - . - Exhibit A - Source Code Form License Notice - ------------------------------------------- - . - This Source Code Form is subject to the terms of the Mozilla Public - License, v. 2.0. If a copy of the MPL was not distributed with this - file, You can obtain one at http://mozilla.org/MPL/2.0/. - . - If it is not possible or desirable to put the notice in a particular - file, then You may include the notice in a location (such as a LICENSE - file in a relevant directory) where a recipient would be likely to look - for such a notice. - . - You may add additional accurate notices of copyright ownership. - . - Exhibit B - "Incompatible With Secondary Licenses" Notice - --------------------------------------------------------- - . - This Source Code Form is "Incompatible With Secondary Licenses", as - defined by the Mozilla Public License, v. 2.0. - - - - -For reference, the upstream DESCRIPTION file is included below: - - Package: RcppEigen - Type: Package - Title: Rcpp integration for the Eigen templated linear algebra library. - Version: 0.3.1.2.1 - Date: 2013-01-14 - Author: Douglas Bates, Romain Francois and Dirk Eddelbuettel - Maintainer: Douglas Bates - Description: R and Eigen integration using Rcpp. - . - Eigen is a C++ template library for linear algebra: matrices, vectors, - numerical solvers and related algorithms. It supports dense - and sparse matrices on integer, floating point and complex - numbers, decompositions of such matrices, and solutions of - linear systems. Its performance on many algorithms is - comparable with some of the best implementations based on - Lapack and level-3 BLAS. - . - The RcppEigen package includes the header files from the Eigen C++ - template library (currently version 3.1.0). Thus users do not - need to install Eigen itself in order to use RcppEigen. - . - Eigen is licensed under the GNU LGPL version 3 or later, and also under - the GNU GPL version 2 or later. RcppEigen (the Rcpp - bindings/bridge to Eigen) is licensed under the GNU GPL version - 2 or later, as is the rest of Rcpp. - License: GPL (>= 2) - Depends: Rcpp (>= 0.10.1), Matrix (>= 1.0-1), R(>= 2.14.0) - LazyLoad: yes - LinkingTo: Rcpp - Imports: Matrix - Suggests: inline, RUnit, testthat - URL: http://eigen.tuxfamily.org - Packaged: 2013-02-03 19:51:07 UTC; bates - Repository: CRAN - Date/Publication: 2013-02-04 08:02:53 - diff --git a/debian/r-cran-rcppeigen.lintian-overrides b/debian/r-cran-rcppeigen.lintian-overrides deleted file mode 100644 index 84af5289..00000000 --- a/debian/r-cran-rcppeigen.lintian-overrides +++ /dev/null @@ -1,7 +0,0 @@ -r-cran-rcppeigen: binary-or-shlib-defines-rpath usr/lib/R/site-library/RcppEigen/libs/RcppEigen.so /usr/lib/R/site-library/Rcpp/lib -r-cran-rcppeigen: hardening-no-relro usr/lib/R/site-library/RcppEigen/libs/RcppEigen.so -r-cran-rcppeigen: hardening-no-fortify-functions usr/lib/R/site-library/RcppEigen/libs/RcppEigen.so -r-cran-rcppeigen: script-not-executable usr/lib/R/site-library/RcppEigen/unitTests/runit.RcppEigen.R -r-cran-rcppeigen: script-not-executable usr/lib/R/site-library/RcppEigen/unitTests/runit.fastLm.R -r-cran-rcppeigen: script-not-executable usr/lib/R/site-library/RcppEigen/unitTests/runit.sparse.R -r-cran-rcppeigen: extra-license-file usr/lib/R/site-library/RcppEigen/LICENSE diff --git a/debian/rules b/debian/rules deleted file mode 100755 index 1c53bdcf..00000000 --- a/debian/rules +++ /dev/null @@ -1,6 +0,0 @@ -#!/usr/bin/make -f -# -*- makefile -*- -# debian/rules file for the Debian/GNU Linux r-cran-rcppeigen package -# Copyright 2003-2013 by Dirk Eddelbuettel - -include /usr/share/R/debian/r-cran.mk diff --git a/debian/source/format b/debian/source/format deleted file mode 100644 index d3827e75..00000000 --- a/debian/source/format +++ /dev/null @@ -1 +0,0 @@ -1.0 diff --git a/debian/watch b/debian/watch deleted file mode 100644 index 897d3d46..00000000 --- a/debian/watch +++ /dev/null @@ -1,2 +0,0 @@ -version=3 -http://cran.r-project.org/src/contrib/RcppEigen_([-\d\.]*)\.tar.gz diff --git a/inst/CITATION b/inst/CITATION index ab5ecbce..ed8410b6 100644 --- a/inst/CITATION +++ b/inst/CITATION @@ -1,19 +1,13 @@ -citHeader("To cite RcppEigen in publications use:") - -citEntry(entry = "Article", - title = "Fast and Elegant Numerical Linear Algebra Using the {RcppEigen} Package", - author = personList(as.person("Douglas Bates"), - as.person("Dirk Eddelbuettel")), - journal = "Journal of Statistical Software", - year = "2013", - volume = "52", - number = "5", - pages = "1--24", - url = "http://www.jstatsoft.org/v52/i05/", - - textVersion = - paste("Douglas Bates, Dirk Eddelbuettel (2013).", - "Fast and Elegant Numerical Linear Algebra Using the RcppEigen Package.", - "Journal of Statistical Software, 52(5), 1-24.", - "URL http://www.jstatsoft.org/v52/i05/.") -) +bibentry("Article", + title = "Fast and Elegant Numerical Linear Algebra Using the {RcppEigen} Package", + author = c(person("Douglas", "Bates", + comment = c(ORCID = "0000-0001-8316-9503")), + person("Dirk", "Eddelbuettel", + email = "edd@debian.org", + comment = c(ORCID = "0000-0001-6419-907X"))), + journal = "Journal of Statistical Software", + year = "2013", + volume = "52", + number = "5", + pages = "1--24", + doi = "10.18637/jss.v052.i05") diff --git a/inst/NEWS.Rd b/inst/NEWS.Rd index 7da2ea1f..3c15d3f1 100644 --- a/inst/NEWS.Rd +++ b/inst/NEWS.Rd @@ -1,11 +1,177 @@ \name{NEWS} -\title{News for Package 'RcppEigen'} +\title{News for Package \pkg{RcppEigen}} \newcommand{\ghpr}{\href{https://github.com/RcppCore/RcppEigen/pull/#1}{##1}} \newcommand{\ghit}{\href{https://github.com/RcppCore/RcppEigen/issues/#1}{##1}} +\section{Changes in RcppEigen version 0.3.4.0.2 (2024-08-23)}{ + \itemize{ + \item Correct two typos in the ORCID tag + } +} + +\section{Changes in RcppEigen version 0.3.4.0.1 (2024-08-14)}{ + \itemize{ + \item Conditionally comment-out \code{xerbla} in \code{blas.h} as it is + now providedd by R-devel albeit with \code{FC_LEN_T} (per a CRAN request) + \item Minor package updates (continuous integration, badges) + } +} + +\section{Changes in RcppEigen version 0.3.4.0.0 (2024-02-28)}{ + \itemize{ + \item The Eigen version has been upgrade to release 3.4.0 (Yixuan) + \item Extensive reverse-dependency checks ensure only three out of over + 400 packages at CRAN are affected; PRs and patches helped other packages + \item The long-running branch also contains substantial contributions + from Mikael Jagan (for the lme4 interface) and Andrew Johnson (revdep PRs) + } +} + +\section{Changes in RcppEigen version 0.3.3.9.4 (2023-11-01)}{ + \itemize{ + \item The CITATION file has been updated for the new \code{bibentry} + style. + \item The package skeleton generator has been updated and no longer sets + an Imports:. + \item Some README.md URLs and badged have been updated. + \item The use of \code{-fopenmp} has been documented in \code{Makevars}, + and a simple thread-count reporting function has been added. + \item The old manual \code{src/init.c} has been replaced by an + autogenerated version, the \code{RcppExports} file have regenerated + \item The interface to package \pkg{Matrix} has been updated and + simplified thanks to an excllent patch by Mikael Jagan. + \item The new upload is coordinated with packages \pkg{lme4} and \pkg{OpenMx}. + } +} + +\section{Changes in RcppEigen version 0.3.3.9.3 (2022-11-04)}{ + \itemize{ + \item The dependency on R is now versioned to 3.6.0 or later for + support for \code{USE_FC_LEN_T} from Fortran. + \item An old example typo was corrected (Jonah Gabry in \ghpr{114}). + \item The \code{fastLm} methods now reference \code{df.residual} by + its full name (Closes \ghit{115}). + \item A function prototype was updated for \code{clang-15}. + \item GitHub Actions were updated to checkout version 3. + } +} + +\section{Changes in RcppEigen version 0.3.3.9.2 (2022-04-05)}{ + \itemize{ + \item Added test coverage in continuous integration + \item Added new tests to increase test coverage + \item Small improvement to the RcppEigen.package.skeleton() code + \item Small updates and edits to README.md and inst/CITATION + \item Use R_xlen_t for vector rows and columns (by Mikael Jagan) + \item Support USE_FC_LEN_T by adding FCONE to two dgesdd + } +} + +\section{Changes in RcppEigen version 0.3.3.9.1 (2020-12-17)}{ + \itemize{ + \item Upgraded to Eigen 3.3.9 (Dirk in \ghpr{92} fixing \ghit{91}). + \item Added GitHub Actions CI using \code{run.sh} from r-ci (Dirk) + } +} + +\section{Changes in RcppEigen version 0.3.3.7.0 (2019-11-16)}{ + \itemize{ + \item Fixed skeleton package creation listing RcppEigen under Imports + (James Balamuta in \ghpr{68} addressing \ghit{16}). + \item Small RNG use update to first example in skeleton package used + by package creation helper (Dirk addressing \ghit{69}). + \item Update vignette example to use RcppEigen:::eigen_version() (Dirk + addressing \ghit{71}). + \item Correct one RcppEigen.package.skeleton() corner case (Dirk in + \ghpr{77} fixing \ghit{75}). + \item Correct one usage case with \pkg{pkgKitten} (Dirk in \ghpr{78}). + \item The package now uses \pkg{tinytest} for unit tests (Dirk in + \ghpr{81}). + \item Upgraded to Eigen 3.3.7 (Dirk in \ghpr{82} fixing \ghit{80}). + } +} + +\section{Changes in RcppEigen version 0.3.3.5.0 (2018-11-24)}{ + \itemize{ + \item Updated to version 3.3.5 of Eigen (Dirk in \ghpr{65}) + \item Long vectors are now supported via \code{R_xlen_t} (Ralf + Stubner in \ghpr{55} fixing \ghit{54}). + \item The benchmarking example was updated in its use of + RcppArmadillo (Michael Weylandt in \ghpr{56}). + } +} + +\section{Changes in RcppEigen version 0.3.3.4.0 (2018-02-05)}{ + \itemize{ + \item Updated to version 3.3.4 of Eigen (Yixuan in \ghpr{49}) + \item Also carried over on new upstream (Yixuan, addressing + \ghit{48}) + \item As before, condition \code{long long} use on C++11. + \item Pragmas for g++ & clang to suppress diagnostics messages are + disabled per CRAN Policy; use \code{-Wno-ignored-attributes} to quieten. + } +} + +\section{Changes in RcppEigen version 0.3.3.3.1 (2017-11-19)}{ + \itemize{ + \item Compilation under Haiku-OS is now supported (Yu Gong in + \ghpr{45}). + \item The \code{Rcpp.plugin.maker} helper function is called via + \code{::} as it is in fact exported (yet we had old code using + \code{:::}). + \item A spurious argument was removed from an example call. + \item Travis CI now uses https to fetch the test runner script. + } +} + +\section{Changes in RcppEigen version 0.3.3.3.0 (2017-04-29)}{ + \itemize{ + \item Updated to version 3.3.3 of Eigen + \item Fixed incorrect function names in the examples, thanks to + ChingChuan Chen + \item The class \code{MappedSparseMatrix} has been deprecated since + Eigen 3.3.0. The new structure \code{Map >} should be used + instead + \item Exporters for the new type \code{Map >} were added + \item Travis CI is now driven via \code{run.sh} from our forked r-travis + } +} + +\section{Changes in RcppEigen version 0.3.2.9.1 (2017-03-14)}{ + \itemize{ + \item Synchronize CholMod header file with Matrix package to ensure + binary compatibility on all platforms (Martin Maechler in \ghpr{42}) + \item Added file \code{init.c} with calls to \code{R_registerRoutines()} + \code{and R_useDynamicSymbols()}; also use \code{.registration=TRUE} + in \code{useDynLib} in \code{NAMESPACE} + } +} + +\section{Changes in RcppEigen version 0.3.2.9.0 (2016-08-20)}{ + \itemize{ + \item Updated to version 3.2.9 of Eigen (PR \ghpr{37} by Yixuan + closing \ghit{36} from Bob Carpenter of the Stan team) + \item An exporter for \code{RowVectorX} was added (thanks to PR \ghpr{32} + by James Balamuta) + } +} + +\section{Changes in RcppEigen version 0.3.2.8.1 (2016-02-29)}{ + \itemize{ + \item Applied another upstream UBSAN fix (PR \ghpr{30} by Yixuan) + } +} + +\section{Changes in RcppEigen version 0.3.2.8.0 (2016-02-23)}{ + \itemize{ + \item Updated to version 3.2.8 of Eigen (PR \ghpr{29} by Yixuan) + } +} + \section{Changes in RcppEigen version 0.3.2.7.0 (2016-01-18)}{ \itemize{ \item Updated to version 3.2.7 of Eigen + \item One unit test file tightened to please R-devel CMD check \item The fastLm example will not include the Lapack header if MKL is defined (thanks to PR \ghpr{25} by Alexey Stukalow) } @@ -34,7 +200,7 @@ \CRANpkg{pkgKitten} if available } } - + \section{Changes in RcppEigen version 0.3.2.3.0 (2014-12-22)}{ \itemize{ \item Updated to version 3.2.3 of Eigen @@ -65,7 +231,7 @@ the cpu id comparison, with thanks to Gael Guennebaud for the patch } } - + \section{Changes in RcppEigen version 0.3.2.1.1 (2014-03-06)}{ \itemize{ \item Better \code{ifdef} on one directory entry feature, with @@ -83,7 +249,7 @@ \itemize{ \item Updated and extended \code{RcppEigen.package.skeleton()} to use several examples via \CRANpkg{Rcpp} Attributes; also removed the - deprecated \code{namespace} argument + deprecated \code{namespace} argument \item Updated skeleton package example for \CRANpkg{Rcpp} 0.11.0 or later by removing needed for linking with user library \item Updated files \code{DESCRIPTION}, \code{NAMESPACE}, @@ -108,7 +274,7 @@ \item Applied two small patches to deal with non-g++ compilrs \item Clarifications concerning license and authorship of Eigen (as opposed to RcppEigen) code added to \code{DESCRIPTION} at - the request of CRAN + the request of CRAN } } @@ -137,7 +303,7 @@ which cannot be changed to a ColMajor form. \item Because of changes in R, -DNDEBUG is automatic. One must override it with -UNDEBUG in the local ~/.R/Makevars to activate the - debugging code. + debugging code. \item New (unexported) functions CxxFlags() and RcppEigenCxxFlags() for use in Makefiles \item Fixes related to Rcpp 0.10.* @@ -190,5 +356,3 @@ some difficulty with combining testthat, inline and R CMD check. } } - - diff --git a/inst/doc/code.R b/inst/doc/code.R deleted file mode 100644 index 634ebb91..00000000 --- a/inst/doc/code.R +++ /dev/null @@ -1,237 +0,0 @@ -library(inline) -library(RcppEigen) - -incl <- ' -using Eigen::LLT; -using Eigen::Lower; -using Eigen::Map; -using Eigen::MatrixXd; -using Eigen::MatrixXi; -using Eigen::Upper; -using Eigen::VectorXd; -typedef Map MapMatd; -typedef Map MapMati; -typedef Map MapVecd; -inline MatrixXd AtA(const MatrixXd& A) { - int n(A.cols()); - return MatrixXd(n,n).setZero().selfadjointView() - .rankUpdate(A.adjoint()); -} -inline MatrixXd AAt(const MatrixXd& A) { - int n(A.cols()); - return MatrixXd(n,n).setZero().selfadjointView() - .rankUpdate(A); -} -' - - -## section 3.1 -(A <- matrix(1:6, ncol=2)) -str(A) - -transCpp <-' -using Eigen::Map; -using Eigen::MatrixXi; - // Map the integer matrix AA from R -const Map A(as >(AA)); - // evaluate and return the transpose of A -const MatrixXi At(A.transpose()); -return wrap(At); -' - -ftrans <- cxxfunction(signature(AA="matrix"), transCpp, plugin="RcppEigen") -(At <- ftrans(A)) -stopifnot(all.equal(At, t(A))) - - - -## section 3.2 -prodCpp <- ' -typedef Eigen::Map MapMati; -const MapMati B(as(BB)); -const MapMati C(as(CC)); -return List::create(Named("B %*% C") = B * C, - Named("crossprod(B, C)") = B.adjoint() * C); -' - -fprod <- cxxfunction(signature(BB = "matrix", CC = "matrix"), prodCpp, "RcppEigen") -B <- matrix(1:4, ncol=2) -C <- matrix(6:1, nrow=2) -str(fp <- fprod(B, C)) -stopifnot(all.equal(fp[[1]], B %*% C), all.equal(fp[[2]], crossprod(B, C))) - - - -## section 3.3 - -crossprodCpp <- ' -using Eigen::Map; -using Eigen::MatrixXi; -using Eigen::Lower; - -const Map A(as >(AA)); -const int m(A.rows()), n(A.cols()); -MatrixXi AtA(MatrixXi(n, n).setZero(). - selfadjointView().rankUpdate(A.adjoint())); -MatrixXi AAt(MatrixXi(m, m).setZero(). - selfadjointView().rankUpdate(A)); - -return List::create(Named("crossprod(A)") = AtA, - Named("tcrossprod(A)") = AAt); -' -fcprd <- cxxfunction(signature(AA = "matrix"), crossprodCpp, "RcppEigen") -str(crp <- fcprd(A)) -stopifnot(all.equal(crp[[1]], crossprod(A)), - all.equal(crp[[2]], tcrossprod(A))) - - - -## section 3.4 - -storage.mode(A) <- "double" - -cholCpp <- ' -const LLT llt(AtA(as(AA))); -return List::create(Named("L") = MatrixXd(llt.matrixL()), - Named("R") = MatrixXd(llt.matrixU())); -' - -fchol <- cxxfunction(signature(AA = "matrix"), cholCpp, "RcppEigen", incl) -(ll <- fchol(A)) -stopifnot(all.equal(ll[[2]], chol(crossprod(A)))) - - -# section 3.5 - -cholDetCpp <- ' -const MatrixXd ata(AtA(as(AA))); -const double detL(MatrixXd(ata.llt().matrixL()).diagonal().prod()); -const VectorXd Dvec(ata.ldlt().vectorD()); -return List::create(Named("d1") = detL * detL, - Named("d2") = Dvec.prod(), - Named("ld") = Dvec.array().log().sum()); -' - -fdet <- cxxfunction(signature(AA = "matrix"), cholDetCpp, "RcppEigen", incl) -unlist(ll <- fdet(A)) - - -## section 4.1 -lltLSCpp <- ' -const MapMatd X(as(XX)); -const MapVecd y(as(yy)); -const int n(X.rows()), p(X.cols()); -const LLT llt(AtA(X)); -const VectorXd betahat(llt.solve(X.adjoint() * y)); -const VectorXd fitted(X * betahat); -const VectorXd resid(y - fitted); -const int df(n - p); -const double ssq(resid.squaredNorm() / double(df)); -const MatrixXd vcov(ssq * llt.solve(MatrixXd::Identity(p, p))); -return List::create(Named("coefficients") = betahat, - Named("fitted.values") = fitted, - Named("residuals") = resid, - Named("s") = sqrt(ssq), - Named("df.residual") = df, - Named("rank") = p, - Named("vcov") = vcov); -' - -lltLS <- cxxfunction(signature(XX = "matrix", yy = "numeric"), - lltLSCpp, "RcppEigen", incl) -data(trees, package="datasets") -str(lltFit <- with(trees, lltLS(cbind(1, log(Girth)), log(Volume)))) -str(lmFit <- with(trees, lm.fit(cbind(1, log(Girth)), log(Volume)))) -for (nm in c("coefficients", "residuals", "fitted.values", "rank")) - stopifnot(all.equal(lltFit[[nm]], unname(lmFit[[nm]]))) -stopifnot(all.equal(unname(vcov(lm(log(Volume) ~ log(Girth), trees))), - lltFit$vcov)) - -## section 4.3 - -dd <- data.frame(f1 = gl(4, 6, labels = LETTERS[1:4]), - f2 = gl(3, 2, labels = letters[1:3]))[-(7:8), ] -xtabs(~ f2 + f1, dd) # one missing cell -mm <- model.matrix(~ f1 * f2, dd) -kappa(mm) # large condition number, indicating rank deficiency -rcond(mm) # alternative evaluation, the reciprocal condition number -(c(rank=qr(mm)$rank, p=ncol(mm))) # rank as computed in R's qr function -set.seed(1) -dd$y <- mm %*% seq_len(ncol(mm)) + rnorm(nrow(mm), sd = 0.1) - # lm detects the rank deficiency -fm1 <- lm(y ~ f1 * f2, dd) -writeLines(capture.output(print(summary(fm1), signif.stars=FALSE))[9:22]) - - -## section 4.6 -print(summary(fmPQR <- fastLm(y ~ f1 * f2, dd)), signif.stars=FALSE) -all.equal(coef(fm1), coef(fmPQR)) -all.equal(unname(fitted(fm1)), fitted(fmPQR)) -all.equal(unname(residuals(fm1)), residuals(fmPQR)) - - -print(summary(fmSVD <- fastLm(y ~ f1 * f2, dd, method=4L)), signif.stars=FALSE) -all.equal(coef(fm1), coef(fmSVD)) -all.equal(unname(fitted(fm1)), fitted(fmSVD)) -all.equal(unname(residuals(fm1)), residuals(fmSVD)) - - -fmVLV <- fastLm(y ~ f1 * f2, dd, method=5L) -all.equal(coef(fmSVD), coef(fmVLV)) - - -## section 5 - -badtransCpp <- ' -const MapMati A(as(AA)); -return wrap(A.transpose()); -' - -Ai <- matrix(1:6, ncol=2L) -ftrans2 <- cxxfunction(signature(AA = "matrix"), badtransCpp, "RcppEigen", incl) -(At <- ftrans2(Ai)) -all.equal(At, t(Ai)) - - - -## section 6 -sparseProdCpp <- ' -using Eigen::MappedSparseMatrix; -using Eigen::SparseMatrix; - -const MappedSparseMatrix A(as >(AA)); -const MapVecd y(as(yy)); -const SparseMatrix At(A.adjoint()); -return List::create(Named("At") = At, - Named("Aty") = At * y); -' - -sparse1 <- cxxfunction(signature(AA = "dgCMatrix", yy = "numeric"), - sparseProdCpp, "RcppEigen", incl) -data(KNex, package="Matrix") -rr <- sparse1(KNex$mm, KNex$y) -stopifnot(all.equal(rr$At, t(KNex$mm)), - all.equal(rr$Aty, as.vector(crossprod(KNex$mm, KNex$y)))) - - -sparseLSCpp <- ' -typedef Eigen::MappedSparseMatrix MSpMat; -typedef Eigen::SparseMatrix SpMat; -typedef Eigen::SimplicialLDLT SpChol; - -const SpMat At(as(AA).adjoint()); -const VectorXd Aty(At * as(yy)); -const SpChol Ch(At * At.adjoint()); -if (Ch.info() != Eigen::Success) return R_NilValue; -return List::create(Named("betahat") = Ch.solve(Aty), - Named("perm") = Ch.permutationP().indices()); -' - -sparse2 <- cxxfunction(signature(AA = "dgCMatrix", yy = "numeric"), - sparseLSCpp, "RcppEigen", incl) -str(rr <- sparse2(KNex$mm, KNex$y)) -res <- as.vector(solve(Ch <- Cholesky(crossprod(KNex$mm)), - crossprod(KNex$mm, KNex$y))) -stopifnot(all.equal(rr$betahat, res)) - -all(rr$perm == Ch@perm) # fill-reducing permutations are different diff --git a/inst/doc/unitTests/RcppEigen-unitTests.R b/inst/doc/unitTests/RcppEigen-unitTests.R deleted file mode 100644 index 06bfdb40..00000000 --- a/inst/doc/unitTests/RcppEigen-unitTests.R +++ /dev/null @@ -1,20 +0,0 @@ -pkg <- "RcppEigen" - -# load this package -require( pkg, character.only = TRUE ) - -#load RUnit -runit <- "RUnit" ; require( runit, character.only = TRUE ) -if( file.exists( "unitTests-results" ) ){ unlink("unitTests-results", recursive = TRUE ) } -dir.create( "unitTests-results" ) - -path <- system.file("unitTests", package = pkg) -testSuite <- defineTestSuite(name=paste(pkg, "unit testing"), dirs = path) -tests <- runTestSuite(testSuite) -printHTMLProtocol(tests, fileName= sprintf( "unitTests-results/%s-unitTests.html" , pkg ) ) -printTextProtocol(tests, fileName= sprintf( "unitTests-results/%s-unitTests.txt" , pkg ) ) -if( file.exists( "/tmp" ) ){ - file.copy( sprintf( "unitTests-results/%s-unitTests.txt" , pkg ) , "/tmp", overwrite = TRUE ) - file.copy( sprintf( "unitTests-results/%s-unitTests.html", pkg ) , "/tmp", overwrite = TRUE ) -} - diff --git a/inst/doc/unitTests/RcppEigen-unitTests.Rnw b/inst/doc/unitTests/RcppEigen-unitTests.Rnw deleted file mode 100644 index e69de29b..00000000 diff --git a/inst/examples/lmBenchmark.R b/inst/examples/lmBenchmark.R index dd493756..1c07303b 100644 --- a/inst/examples/lmBenchmark.R +++ b/inst/examples/lmBenchmark.R @@ -1,65 +1,82 @@ ## lmBenchmark.R: Benchmark different implementations of linear model solutions ## -## Copyright (C) 2011 Douglas Bates, Dirk Eddelbuettel and Romain Francois +## Copyright (C) 2011 - 2017 Douglas Bates, Dirk Eddelbuettel and Romain Francois ## ## This file is part of RcppEigen. require("stats", character=TRUE, quietly=TRUE) -require("rbenchmark", character=TRUE, quietly=TRUE) require("RcppEigen", character=TRUE, quietly=TRUE) -## define different versions of lm -exprs <- list() - -## These versions use rank-revealing decompositions and thus can -## handle rank-deficient cases. - - # default version used in lm() -exprs$lm.fit <- expression(stats::lm.fit(mm, y)) - # versions from RcppEigen -## column-pivoted QR decomposition - similar to lm.fit -exprs$PivQR <- expression(.Call("fastLm", mm, y, 0L, PACKAGE="RcppEigen")) -## LDLt Cholesky decomposition with rank detection -exprs$LDLt <- expression(.Call("fastLm", mm, y, 2L, PACKAGE="RcppEigen")) -## SVD using the Lapack subroutine dgesdd and Eigen support -exprs$GESDD <- expression(.Call("fastLm", mm, y, 6L, PACKAGE="RcppEigen")) -## SVD (the JacobiSVD class from Eigen) -exprs$SVD <- expression(.Call("fastLm", mm, y, 4L, PACKAGE="RcppEigen")) -## eigenvalues and eigenvectors of X'X -exprs$SymmEig <- expression(.Call("fastLm", mm, y, 5L, PACKAGE="RcppEigen")) - -## Non-rank-revealing decompositions. These work fine except when -## they don't. - -## Unpivoted QR decomposition -exprs$QR <- expression(.Call("fastLm", mm, y, 1L, PACKAGE="RcppEigen")) -## LLt Cholesky decomposition -exprs$LLt <- expression(.Call("fastLm", mm, y, 3L, PACKAGE="RcppEigen")) - -if (suppressMessages(require("RcppArmadillo", character=TRUE, quietly=TRUE))) { - exprs$arma <- expression(.Call("RcppArmadillo_fastLm", mm, y, PACKAGE="RcppArmadillo")) -} +if(require("microbenchmark", character=TRUE, quietly=TRUE)){ -if (suppressMessages(require("RcppGSL", character=TRUE, quietly=TRUE))) { - exprs$GSL <- expression(.Call("fastLm", mm, y, PACKAGE="RcppGSL")) -} + ## define different versions of lm + exprs <- list() -do_bench <- function(n=100000L, p=40L, nrep=20L, suppressSVD=(n > 100000L)) { - mm <- cbind(1, matrix(rnorm(n * (p - 1L)), nc=p-1L)) - y <- rnorm(n) - if (suppressSVD) exprs <- exprs[!names(exprs) %in% c("SVD", "GSL")] - cat("lm benchmark for n = ", n, " and p = ", p, ": nrep = ", nrep, "\n", sep='') - do.call(benchmark, c(exprs, - list(order="relative", - columns = c("test", "relative", - "elapsed", "user.self", "sys.self"), - replications = nrep))) -} + ## These versions use rank-revealing decompositions and thus can + ## handle rank-deficient cases. + + # default version used in lm() + exprs["lm.fit"] <- alist(stats::lm.fit(mm, y)) + + # versions from RcppEigen + ## column-pivoted QR decomposition - similar to lm.fit + exprs["PivQR"] <- alist(RcppEigen::fastLmPure(mm, y, 0L)) + ## LDLt Cholesky decomposition with rank detection + exprs["LDLt"] <- alist(RcppEigen::fastLmPure(mm, y, 2L)) + ## SVD using the Lapack subroutine dgesdd and Eigen support + exprs["GESDD"] <- alist(RcppEigen::fastLmPure(mm, y, 6L)) + ## SVD (the JacobiSVD class from Eigen) + exprs["SVD"] <- alist(RcppEigen::fastLmPure(mm, y, 4L)) + ## eigenvalues and eigenvectors of X'X + exprs["SymmEig"] <- alist(RcppEigen::fastLmPure(mm, y, 5L)) + + ## Non-rank-revealing decompositions. These work fine except when + ## they don't. + + ## Unpivoted QR decomposition + exprs["QR"] <- alist(RcppEigen::fastLmPure(mm, y, 1L)) + ## LLt Cholesky decomposition + exprs["LLt"] <- alist(RcppEigen::fastLmPure(mm, y, 3L)) + + if (suppressMessages(require("RcppArmadillo", character=TRUE, quietly=TRUE))) { + exprs["arma"] <- alist(RcppArmadillo::fastLmPure(mm, y)) + } -print(do_bench()) + if (suppressMessages(require("RcppGSL", character=TRUE, quietly=TRUE))) { + exprs["GSL"] <- alist(RcppGSL::fastLmPure(mm, y)) + } -sessionInfo() + do_bench <- function(n=100000L, p=40L, nrep=20L, suppressSVD=(n > 100000L)) { + mm <- cbind(1, matrix(rnorm(n * (p - 1L)), nc=p-1L)) + y <- rnorm(n) + if (suppressSVD) exprs <- exprs[!names(exprs) %in% c("SVD", "GSL")] -.Call("eigen_version", FALSE, PACKAGE="RcppEigen") + cat("lm benchmark for n = ", n, " and p = ", p, ": nrep = ", nrep, "\n", sep='') + cat("RcppEigen: Included Eigen version", paste(RcppEigen:::eigen_version(FALSE), collapse="."), "\n") + cat("RcppEigen: Eigen SSE support", RcppEigen:::Eigen_SSE(), "\n") -.Call("Eigen_SSE", FALSE, PACKAGE="RcppEigen") + mb <- microbenchmark(list=exprs, times = nrep) + + op <- options(microbenchmark.unit="relative") + on.exit(options(op)) + + mb_relative <- summary(mb) + levels(mb_relative$expr) <- names(exprs) + + options(microbenchmark.unit=NULL) + mb_absolute <- summary(mb) + levels(mb_absolute$expr) <- names(exprs) + + mb_combined <- merge(mb_relative[, c("expr", "median")], + mb_absolute[, c("expr", "median")], + by="expr") + + colnames(mb_combined) <- c("Method", + "Relative", + paste0("Elapsed (", attr(mb_absolute, "unit"), ")")) + + mb_combined[order(mb_combined$Relative),] + } + + print(do_bench()) +} diff --git a/inst/include/Eigen/AccelerateSupport b/inst/include/Eigen/AccelerateSupport new file mode 100644 index 00000000..533be688 --- /dev/null +++ b/inst/include/Eigen/AccelerateSupport @@ -0,0 +1,52 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_ACCELERATESUPPORT_MODULE_H +#define EIGEN_ACCELERATESUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +/** \ingroup Support_modules + * \defgroup AccelerateSupport_Module AccelerateSupport module + * + * This module provides an interface to the Apple Accelerate library. + * It provides the seven following main factorization classes: + * - class AccelerateLLT: a Cholesky (LL^T) factorization. + * - class AccelerateLDLT: the default LDL^T factorization. + * - class AccelerateLDLTUnpivoted: a Cholesky-like LDL^T factorization with only 1x1 pivots and no pivoting + * - class AccelerateLDLTSBK: an LDL^T factorization with Supernode Bunch-Kaufman and static pivoting + * - class AccelerateLDLTTPP: an LDL^T factorization with full threshold partial pivoting + * - class AccelerateQR: a QR factorization + * - class AccelerateCholeskyAtA: a QR factorization without storing Q (equivalent to A^TA = R^T R) + * + * \code + * #include + * \endcode + * + * In order to use this module, the Accelerate headers must be accessible from + * the include paths, and your binary must be linked to the Accelerate framework. + * The Accelerate library is only available on Apple hardware. + * + * Note that many of the algorithms can be influenced by the UpLo template + * argument. All matrices are assumed to be symmetric. For example, the following + * creates an LDLT factorization where your matrix is symmetric (implicit) and + * uses the lower triangle: + * + * \code + * AccelerateLDLT, Lower> ldlt; + * \endcode + */ + +// IWYU pragma: begin_exports +#include "src/AccelerateSupport/AccelerateSupport.h" +// IWYU pragma: end_exports + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_ACCELERATESUPPORT_MODULE_H diff --git a/inst/include/Eigen/Array b/inst/include/Eigen/Array deleted file mode 100644 index 3d004fb6..00000000 --- a/inst/include/Eigen/Array +++ /dev/null @@ -1,11 +0,0 @@ -#ifndef EIGEN_ARRAY_MODULE_H -#define EIGEN_ARRAY_MODULE_H - -// include Core first to handle Eigen2 support macros -#include "Core" - -#ifndef EIGEN2_SUPPORT - #error The Eigen/Array header does no longer exist in Eigen3. All that functionality has moved to Eigen/Core. -#endif - -#endif // EIGEN_ARRAY_MODULE_H diff --git a/inst/include/Eigen/Cholesky b/inst/include/Eigen/Cholesky index f727f5d8..b05ed827 100644 --- a/inst/include/Eigen/Cholesky +++ b/inst/include/Eigen/Cholesky @@ -1,32 +1,43 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_CHOLESKY_MODULE_H #define EIGEN_CHOLESKY_MODULE_H #include "Core" +#include "Jacobi" #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup Cholesky_Module Cholesky module - * - * - * - * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices. - * Those decompositions are accessible via the following MatrixBase methods: - * - MatrixBase::llt(), - * - MatrixBase::ldlt() - * - * \code - * #include - * \endcode - */ + * + * + * + * This module provides two variants of the Cholesky decomposition for selfadjoint (hermitian) matrices. + * Those decompositions are also accessible via the following methods: + * - MatrixBase::llt() + * - MatrixBase::ldlt() + * - SelfAdjointView::llt() + * - SelfAdjointView::ldlt() + * + * \code + * #include + * \endcode + */ -#include "src/misc/Solve.h" +// IWYU pragma: begin_exports #include "src/Cholesky/LLT.h" #include "src/Cholesky/LDLT.h" #ifdef EIGEN_USE_LAPACKE -#include "src/Cholesky/LLT_MKL.h" +#include "src/misc/lapacke_helpers.h" +#include "src/Cholesky/LLT_LAPACKE.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_CHOLESKY_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_CHOLESKY_MODULE_H diff --git a/inst/include/Eigen/CholmodSupport b/inst/include/Eigen/CholmodSupport index be327fa2..bff39e6d 100644 --- a/inst/include/Eigen/CholmodSupport +++ b/inst/include/Eigen/CholmodSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_CHOLMODSUPPORT_MODULE_H #define EIGEN_CHOLMODSUPPORT_MODULE_H @@ -5,41 +12,37 @@ #include "src/Core/util/DisableStupidWarnings.h" -extern "C" { - #include -} +#include /** \ingroup Support_modules - * \defgroup CholmodSupport_Module CholmodSupport module - * - * This module provides an interface to the Cholmod library which is part of the suitesparse package. - * It provides the two following main factorization classes: - * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization. - * - class CholmodDecomposiiton: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of the underlying factorization method (supernodal or simplicial). - * - * For the sake of completeness, this module also propose the two following classes: - * - class CholmodSimplicialLLT - * - class CholmodSimplicialLDLT - * Note that these classes does not bring any particular advantage compared to the built-in - * SimplicialLLT and SimplicialLDLT factorization classes. - * - * \code - * #include - * \endcode - * - * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be linked to the cholmod library and its dependencies. - * The dependencies depend on how cholmod has been compiled. - * For a cmake based project, you can use our FindCholmod.cmake module to help you in this task. - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" - + * \defgroup CholmodSupport_Module CholmodSupport module + * + * This module provides an interface to the Cholmod library which is part of the suitesparse package. It provides the two following main factorization classes: + * - class CholmodSupernodalLLT: a supernodal LLT Cholesky factorization. + * - class CholmodDecomposition: a general L(D)LT Cholesky factorization with automatic or explicit runtime selection of + * the underlying factorization method (supernodal or simplicial). + * + * For the sake of completeness, this module also propose the two following classes: + * - class CholmodSimplicialLLT + * - class CholmodSimplicialLDLT + * Note that these classes does not bring any particular advantage compared to the built-in + * SimplicialLLT and SimplicialLDLT factorization classes. + * + * \code + * #include + * \endcode + * + * In order to use this module, the cholmod headers must be accessible from the include paths, and your binary must be + * linked to the cholmod library and its dependencies. The dependencies depend on how cholmod has been compiled. For a + * cmake based project, you can use our FindCholmod.cmake module to help you in this task. + * + */ + +// IWYU pragma: begin_exports #include "src/CholmodSupport/CholmodSupport.h" - +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_CHOLMODSUPPORT_MODULE_H - +#endif // EIGEN_CHOLMODSUPPORT_MODULE_H diff --git a/inst/include/Eigen/Core b/inst/include/Eigen/Core index 509c529e..34838f5d 100644 --- a/inst/include/Eigen/Core +++ b/inst/include/Eigen/Core @@ -8,138 +8,71 @@ // Public License v. 2.0. If a copy of the MPL was not distributed // with this file, You can obtain one at http://mozilla.org/MPL/2.0/. -#ifndef EIGEN_CORE_H -#define EIGEN_CORE_H +#ifndef EIGEN_CORE_MODULE_H +#define EIGEN_CORE_MODULE_H -// first thing Eigen does: stop the compiler from committing suicide +// Eigen version information. +#include "Version" + +// first thing Eigen does: stop the compiler from reporting useless warnings. #include "src/Core/util/DisableStupidWarnings.h" // then include this file where all our macros are defined. It's really important to do it first because -// it's where we do all the alignment settings (platform detection and honoring the user's will if he -// defined e.g. EIGEN_DONT_ALIGN) so it needs to be done before we do anything with vectorization. +// it's where we do all the compiler/OS/arch detections and define most defaults. #include "src/Core/util/Macros.h" -// Disable the ipa-cp-clone optimization flag with MinGW 6.x or newer (enabled by default with -O3) +// This detects SSE/AVX/NEON/etc. and configure alignment settings +#include "src/Core/util/ConfigureVectorization.h" + +// We need cuda_runtime.h/hip_runtime.h to ensure that +// the EIGEN_USING_STD macro works properly on the device side +#if defined(EIGEN_CUDACC) +#include +#elif defined(EIGEN_HIPCC) +#include +#endif + +#ifdef EIGEN_EXCEPTIONS +#include +#endif + +// Disable the ipa-cp-clone optimization flag with MinGW 6.x or older (enabled by default with -O3) // See http://eigen.tuxfamily.org/bz/show_bug.cgi?id=556 for details. -#if defined(__MINGW32__) && EIGEN_GNUC_AT_LEAST(4,6) - #pragma GCC optimize ("-fno-ipa-cp-clone") +#if EIGEN_COMP_MINGW && EIGEN_GNUC_STRICT_LESS_THAN(6, 0, 0) +#pragma GCC optimize("-fno-ipa-cp-clone") #endif +// Prevent ICC from specializing std::complex operators that silently fail +// on device. This allows us to use our own device-compatible specializations +// instead. +#if EIGEN_COMP_ICC && defined(EIGEN_GPU_COMPILE_PHASE) && !defined(_OVERRIDE_COMPLEX_SPECIALIZATION_) +#define _OVERRIDE_COMPLEX_SPECIALIZATION_ 1 +#endif #include // this include file manages BLAS and MKL related macros // and inclusion of their respective header files #include "src/Core/util/MKL_support.h" -// if alignment is disabled, then disable vectorization. Note: EIGEN_ALIGN is the proper check, it takes into -// account both the user's will (EIGEN_DONT_ALIGN) and our own platform checks -#if !EIGEN_ALIGN - #ifndef EIGEN_DONT_VECTORIZE - #define EIGEN_DONT_VECTORIZE - #endif -#endif - -#ifdef _MSC_VER - #include // for _aligned_malloc -- need it regardless of whether vectorization is enabled - #if (_MSC_VER >= 1500) // 2008 or later - // Remember that usage of defined() in a #define is undefined by the standard. - // a user reported that in 64-bit mode, MSVC doesn't care to define _M_IX86_FP. - #if (defined(_M_IX86_FP) && (_M_IX86_FP >= 2)) || defined(_M_X64) - #define EIGEN_SSE2_ON_MSVC_2008_OR_LATER - #endif - #endif -#else - // Remember that usage of defined() in a #define is undefined by the standard - #if (defined __SSE2__) && ( (!defined __GNUC__) || (defined __INTEL_COMPILER) || EIGEN_GNUC_AT_LEAST(4,2) ) - #define EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC - #endif -#endif - -#ifndef EIGEN_DONT_VECTORIZE - - #if defined (EIGEN_SSE2_ON_NON_MSVC_BUT_NOT_OLD_GCC) || defined(EIGEN_SSE2_ON_MSVC_2008_OR_LATER) - - // Defines symbols for compile-time detection of which instructions are - // used. - // EIGEN_VECTORIZE_YY is defined if and only if the instruction set YY is used - #define EIGEN_VECTORIZE - #define EIGEN_VECTORIZE_SSE - #define EIGEN_VECTORIZE_SSE2 - - // Detect sse3/ssse3/sse4: - // gcc and icc defines __SSE3__, ... - // there is no way to know about this on msvc. You can define EIGEN_VECTORIZE_SSE* if you - // want to force the use of those instructions with msvc. - #ifdef __SSE3__ - #define EIGEN_VECTORIZE_SSE3 - #endif - #ifdef __SSSE3__ - #define EIGEN_VECTORIZE_SSSE3 - #endif - #ifdef __SSE4_1__ - #define EIGEN_VECTORIZE_SSE4_1 - #endif - #ifdef __SSE4_2__ - #define EIGEN_VECTORIZE_SSE4_2 - #endif - - // include files - - // This extern "C" works around a MINGW-w64 compilation issue - // https://sourceforge.net/tracker/index.php?func=detail&aid=3018394&group_id=202880&atid=983354 - // In essence, intrin.h is included by windows.h and also declares intrinsics (just as emmintrin.h etc. below do). - // However, intrin.h uses an extern "C" declaration, and g++ thus complains of duplicate declarations - // with conflicting linkage. The linkage for intrinsics doesn't matter, but at that stage the compiler doesn't know; - // so, to avoid compile errors when windows.h is included after Eigen/Core, ensure intrinsics are extern "C" here too. - // notice that since these are C headers, the extern "C" is theoretically needed anyways. - extern "C" { - // In theory we should only include immintrin.h and not the other *mmintrin.h header files directly. - // Doing so triggers some issues with ICC. However old gcc versions seems to not have this file, thus: - #if defined(__INTEL_COMPILER) && __INTEL_COMPILER >= 1110 - #include - #else - #include - #include - #ifdef EIGEN_VECTORIZE_SSE3 - #include - #endif - #ifdef EIGEN_VECTORIZE_SSSE3 - #include - #endif - #ifdef EIGEN_VECTORIZE_SSE4_1 - #include - #endif - #ifdef EIGEN_VECTORIZE_SSE4_2 - #include - #endif - #endif - } // end extern "C" - #elif defined __ALTIVEC__ - #define EIGEN_VECTORIZE - #define EIGEN_VECTORIZE_ALTIVEC - #include - // We need to #undef all these ugly tokens defined in - // => use __vector instead of vector - #undef bool - #undef vector - #undef pixel - #elif defined __ARM_NEON - #define EIGEN_VECTORIZE - #define EIGEN_VECTORIZE_NEON - #include - #endif +#if defined(EIGEN_HAS_CUDA_FP16) || defined(EIGEN_HAS_HIP_FP16) +#define EIGEN_HAS_GPU_FP16 +#endif + +#if defined(EIGEN_HAS_CUDA_BF16) || defined(EIGEN_HAS_HIP_BF16) +#define EIGEN_HAS_GPU_BF16 #endif #if (defined _OPENMP) && (!defined EIGEN_DONT_PARALLELIZE) - #define EIGEN_HAS_OPENMP +#define EIGEN_HAS_OPENMP #endif #ifdef EIGEN_HAS_OPENMP +#include #include #endif // MSVC for windows mobile does not have the errno.h file -#if !(defined(_MSC_VER) && defined(_WIN32_WCE)) && !defined(__ARMCC_VERSION) +#if !(EIGEN_COMP_MSVC && EIGEN_OS_WINCE) && !EIGEN_COMP_ARM #define EIGEN_HAS_ERRNO #endif @@ -149,183 +82,315 @@ #include #include #include -#include #include +#ifndef EIGEN_NO_IO +#include #include +#endif #include #include #include -#include // for CHAR_BIT +#include // for CHAR_BIT // for min/max: #include +#include +#include +#include + +// for std::is_nothrow_move_assignable +#include + +// for std::this_thread::yield(). +#if !defined(EIGEN_USE_BLAS) && (defined(EIGEN_HAS_OPENMP) || defined(EIGEN_GEMM_THREADPOOL)) +#include +#endif + +// for __cpp_lib feature test macros +#if defined(__has_include) && __has_include() +#include +#endif + +// for std::bit_cast() +#if defined(__cpp_lib_bit_cast) && __cpp_lib_bit_cast >= 201806L +#include +#endif + // for outputting debug info #ifdef EIGEN_DEBUG_ASSIGN #include #endif // required for __cpuid, needs to be included after cmath -#if defined(_MSC_VER) && (defined(_M_IX86)||defined(_M_X64)) && (!defined(_WIN32_WCE)) - #include +// also required for _BitScanReverse on Windows on ARM +#if EIGEN_COMP_MSVC && (EIGEN_ARCH_i386_OR_x86_64 || EIGEN_ARCH_ARM64) && !EIGEN_OS_WINCE +#include #endif -#if defined(_CPPUNWIND) || defined(__EXCEPTIONS) - #define EIGEN_EXCEPTIONS +#if defined(EIGEN_USE_SYCL) +#undef min +#undef max +#undef isnan +#undef isinf +#undef isfinite +#include +#include +#include +#include +#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM0 +#define EIGEN_SYCL_LOCAL_THREAD_DIM0 16 #endif - -#ifdef EIGEN_EXCEPTIONS - #include +#ifndef EIGEN_SYCL_LOCAL_THREAD_DIM1 +#define EIGEN_SYCL_LOCAL_THREAD_DIM1 16 #endif - -/** \brief Namespace containing all symbols from the %Eigen library. */ -namespace Eigen { - -inline static const char *SimdInstructionSetsInUse(void) { -#if defined(EIGEN_VECTORIZE_SSE4_2) - return "SSE, SSE2, SSE3, SSSE3, SSE4.1, SSE4.2"; -#elif defined(EIGEN_VECTORIZE_SSE4_1) - return "SSE, SSE2, SSE3, SSSE3, SSE4.1"; -#elif defined(EIGEN_VECTORIZE_SSSE3) - return "SSE, SSE2, SSE3, SSSE3"; -#elif defined(EIGEN_VECTORIZE_SSE3) - return "SSE, SSE2, SSE3"; -#elif defined(EIGEN_VECTORIZE_SSE2) - return "SSE, SSE2"; -#elif defined(EIGEN_VECTORIZE_ALTIVEC) - return "AltiVec"; -#elif defined(EIGEN_VECTORIZE_NEON) - return "ARM NEON"; -#else - return "None"; -#endif -} - -} // end namespace Eigen - -#define STAGE10_FULL_EIGEN2_API 10 -#define STAGE20_RESOLVE_API_CONFLICTS 20 -#define STAGE30_FULL_EIGEN3_API 30 -#define STAGE40_FULL_EIGEN3_STRICTNESS 40 -#define STAGE99_NO_EIGEN2_SUPPORT 99 - -#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS - #define EIGEN2_SUPPORT - #define EIGEN2_SUPPORT_STAGE STAGE40_FULL_EIGEN3_STRICTNESS -#elif defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API - #define EIGEN2_SUPPORT - #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API -#elif defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS - #define EIGEN2_SUPPORT - #define EIGEN2_SUPPORT_STAGE STAGE20_RESOLVE_API_CONFLICTS -#elif defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API - #define EIGEN2_SUPPORT - #define EIGEN2_SUPPORT_STAGE STAGE10_FULL_EIGEN2_API -#elif defined EIGEN2_SUPPORT - // default to stage 3, that's what it's always meant - #define EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API - #define EIGEN2_SUPPORT_STAGE STAGE30_FULL_EIGEN3_API -#else - #define EIGEN2_SUPPORT_STAGE STAGE99_NO_EIGEN2_SUPPORT #endif -#ifdef EIGEN2_SUPPORT -#undef minor +#if defined EIGEN2_SUPPORT_STAGE40_FULL_EIGEN3_STRICTNESS || defined EIGEN2_SUPPORT_STAGE30_FULL_EIGEN3_API || \ + defined EIGEN2_SUPPORT_STAGE20_RESOLVE_API_CONFLICTS || defined EIGEN2_SUPPORT_STAGE10_FULL_EIGEN2_API || \ + defined EIGEN2_SUPPORT +// This will generate an error message: +#error Eigen2-support is only available up to version 3.2. Please go to "http://eigen.tuxfamily.org/index.php?title=Eigen2" for further information #endif -// we use size_t frequently and we'll never remember to prepend it with std:: everytime just to +namespace Eigen { + +// we use size_t frequently and we'll never remember to prepend it with std:: every time just to // ensure QNX/QCC support using std::size_t; -// gcc 4.6.0 wants std:: for ptrdiff_t +// gcc 4.6.0 wants std:: for ptrdiff_t using std::ptrdiff_t; +} // namespace Eigen + /** \defgroup Core_Module Core module - * This is the main module of Eigen providing dense matrix and vector support - * (both fixed and dynamic size) with all the features corresponding to a BLAS library - * and much more... - * - * \code - * #include - * \endcode - */ + * This is the main module of Eigen providing dense matrix and vector support + * (both fixed and dynamic size) with all the features corresponding to a BLAS library + * and much more... + * + * \code + * #include + * \endcode + */ + +#ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else +#include "src/misc/lapacke.h" +#endif +#endif +// IWYU pragma: begin_exports #include "src/Core/util/Constants.h" -#include "src/Core/util/ForwardDeclarations.h" #include "src/Core/util/Meta.h" +#include "src/Core/util/Assert.h" +#include "src/Core/util/ForwardDeclarations.h" #include "src/Core/util/StaticAssert.h" #include "src/Core/util/XprHelper.h" #include "src/Core/util/Memory.h" +#include "src/Core/util/IntegralConstant.h" +#include "src/Core/util/Serializer.h" +#include "src/Core/util/SymbolicIndex.h" +#include "src/Core/util/EmulateArray.h" +#include "src/Core/util/MoreMeta.h" #include "src/Core/NumTraits.h" #include "src/Core/MathFunctions.h" +#include "src/Core/RandomImpl.h" #include "src/Core/GenericPacketMath.h" +#include "src/Core/MathFunctionsImpl.h" +#include "src/Core/arch/Default/ConjHelper.h" +// Generic half float support +#include "src/Core/arch/Default/Half.h" +#include "src/Core/arch/Default/BFloat16.h" +#include "src/Core/arch/Default/GenericPacketMathFunctionsFwd.h" + +#if defined EIGEN_VECTORIZE_AVX512 +#include "src/Core/arch/SSE/PacketMath.h" +#include "src/Core/arch/SSE/Reductions.h" +#include "src/Core/arch/AVX/PacketMath.h" +#include "src/Core/arch/AVX/Reductions.h" +#include "src/Core/arch/AVX512/PacketMath.h" +#include "src/Core/arch/AVX512/Reductions.h" +#if defined EIGEN_VECTORIZE_AVX512FP16 +#include "src/Core/arch/AVX512/PacketMathFP16.h" +#endif +#include "src/Core/arch/SSE/TypeCasting.h" +#include "src/Core/arch/AVX/TypeCasting.h" +#include "src/Core/arch/AVX512/TypeCasting.h" +#if defined EIGEN_VECTORIZE_AVX512FP16 +#include "src/Core/arch/AVX512/TypeCastingFP16.h" +#endif +#include "src/Core/arch/SSE/Complex.h" +#include "src/Core/arch/AVX/Complex.h" +#include "src/Core/arch/AVX512/Complex.h" +#include "src/Core/arch/SSE/MathFunctions.h" +#include "src/Core/arch/AVX/MathFunctions.h" +#include "src/Core/arch/AVX512/MathFunctions.h" +#if defined EIGEN_VECTORIZE_AVX512FP16 +#include "src/Core/arch/AVX512/MathFunctionsFP16.h" +#endif +#include "src/Core/arch/AVX512/TrsmKernel.h" +#elif defined EIGEN_VECTORIZE_AVX +// Use AVX for floats and doubles, SSE for integers +#include "src/Core/arch/SSE/PacketMath.h" +#include "src/Core/arch/SSE/Reductions.h" +#include "src/Core/arch/SSE/TypeCasting.h" +#include "src/Core/arch/SSE/Complex.h" +#include "src/Core/arch/AVX/PacketMath.h" +#include "src/Core/arch/AVX/Reductions.h" +#include "src/Core/arch/AVX/TypeCasting.h" +#include "src/Core/arch/AVX/Complex.h" +#include "src/Core/arch/SSE/MathFunctions.h" +#include "src/Core/arch/AVX/MathFunctions.h" +#elif defined EIGEN_VECTORIZE_SSE +#include "src/Core/arch/SSE/PacketMath.h" +#include "src/Core/arch/SSE/Reductions.h" +#include "src/Core/arch/SSE/TypeCasting.h" +#include "src/Core/arch/SSE/MathFunctions.h" +#include "src/Core/arch/SSE/Complex.h" +#endif -#if defined EIGEN_VECTORIZE_SSE - #include "src/Core/arch/SSE/PacketMath.h" - #include "src/Core/arch/SSE/MathFunctions.h" - #include "src/Core/arch/SSE/Complex.h" -#elif defined EIGEN_VECTORIZE_ALTIVEC - #include "src/Core/arch/AltiVec/PacketMath.h" - #include "src/Core/arch/AltiVec/Complex.h" +#if defined(EIGEN_VECTORIZE_ALTIVEC) || defined(EIGEN_VECTORIZE_VSX) +#include "src/Core/arch/AltiVec/PacketMath.h" +#include "src/Core/arch/AltiVec/TypeCasting.h" +#include "src/Core/arch/AltiVec/MathFunctions.h" +#include "src/Core/arch/AltiVec/Complex.h" #elif defined EIGEN_VECTORIZE_NEON - #include "src/Core/arch/NEON/PacketMath.h" - #include "src/Core/arch/NEON/Complex.h" +#include "src/Core/arch/NEON/PacketMath.h" +#include "src/Core/arch/NEON/TypeCasting.h" +#include "src/Core/arch/NEON/MathFunctions.h" +#include "src/Core/arch/NEON/Complex.h" +#elif defined EIGEN_VECTORIZE_LSX +#include "src/Core/arch/LSX/PacketMath.h" +#include "src/Core/arch/LSX/TypeCasting.h" +#include "src/Core/arch/LSX/MathFunctions.h" +#include "src/Core/arch/LSX/Complex.h" +#elif defined EIGEN_VECTORIZE_SVE +#include "src/Core/arch/SVE/PacketMath.h" +#include "src/Core/arch/SVE/TypeCasting.h" +#include "src/Core/arch/SVE/MathFunctions.h" +#elif defined EIGEN_VECTORIZE_ZVECTOR +#include "src/Core/arch/ZVector/PacketMath.h" +#include "src/Core/arch/ZVector/MathFunctions.h" +#include "src/Core/arch/ZVector/Complex.h" +#elif defined EIGEN_VECTORIZE_MSA +#include "src/Core/arch/MSA/PacketMath.h" +#include "src/Core/arch/MSA/MathFunctions.h" +#include "src/Core/arch/MSA/Complex.h" +#elif defined EIGEN_VECTORIZE_HVX +#include "src/Core/arch/HVX/PacketMath.h" +#endif + +#if defined EIGEN_VECTORIZE_GPU +#include "src/Core/arch/GPU/PacketMath.h" +#include "src/Core/arch/GPU/MathFunctions.h" +#include "src/Core/arch/GPU/TypeCasting.h" +#endif + +#if defined(EIGEN_USE_SYCL) +#include "src/Core/arch/SYCL/InteropHeaders.h" +#if !defined(EIGEN_DONT_VECTORIZE_SYCL) +#include "src/Core/arch/SYCL/PacketMath.h" +#include "src/Core/arch/SYCL/MathFunctions.h" +#include "src/Core/arch/SYCL/TypeCasting.h" +#endif #endif #include "src/Core/arch/Default/Settings.h" +// This file provides generic implementations valid for scalar as well +#include "src/Core/arch/Default/GenericPacketMathFunctions.h" + +#include "src/Core/functors/TernaryFunctors.h" +#include "src/Core/functors/BinaryFunctors.h" +#include "src/Core/functors/UnaryFunctors.h" +#include "src/Core/functors/NullaryFunctors.h" +#include "src/Core/functors/StlFunctors.h" +#include "src/Core/functors/AssignmentFunctors.h" + +// Specialized functors for GPU. +#ifdef EIGEN_GPUCC +#include "src/Core/arch/GPU/Complex.h" +#endif -#include "src/Core/Functors.h" +// Specializations of vectorized activation functions for NEON. +#ifdef EIGEN_VECTORIZE_NEON +#include "src/Core/arch/NEON/UnaryFunctors.h" +#endif + +#include "src/Core/util/IndexedViewHelper.h" +#include "src/Core/util/ReshapedHelper.h" +#include "src/Core/ArithmeticSequence.h" +#ifndef EIGEN_NO_IO +#include "src/Core/IO.h" +#endif #include "src/Core/DenseCoeffsBase.h" #include "src/Core/DenseBase.h" #include "src/Core/MatrixBase.h" #include "src/Core/EigenBase.h" -#ifndef EIGEN_PARSED_BY_DOXYGEN // work around Doxygen bug triggered by Assign.h r814874 - // at least confirmed with Doxygen 1.5.5 and 1.5.6 - #include "src/Core/Assign.h" -#endif +#include "src/Core/Product.h" +#include "src/Core/CoreEvaluators.h" +#include "src/Core/AssignEvaluator.h" +#include "src/Core/RealView.h" +#include "src/Core/Assign.h" +#include "src/Core/ArrayBase.h" #include "src/Core/util/BlasUtil.h" #include "src/Core/DenseStorage.h" #include "src/Core/NestByValue.h" -#include "src/Core/ForceAlignedAccess.h" + +// #include "src/Core/ForceAlignedAccess.h" + #include "src/Core/ReturnByValue.h" #include "src/Core/NoAlias.h" #include "src/Core/PlainObjectBase.h" #include "src/Core/Matrix.h" #include "src/Core/Array.h" +#include "src/Core/Fill.h" +#include "src/Core/CwiseTernaryOp.h" #include "src/Core/CwiseBinaryOp.h" #include "src/Core/CwiseUnaryOp.h" #include "src/Core/CwiseNullaryOp.h" #include "src/Core/CwiseUnaryView.h" #include "src/Core/SelfCwiseBinaryOp.h" +#include "src/Core/InnerProduct.h" #include "src/Core/Dot.h" #include "src/Core/StableNorm.h" -#include "src/Core/MapBase.h" #include "src/Core/Stride.h" +#include "src/Core/MapBase.h" #include "src/Core/Map.h" +#include "src/Core/Ref.h" #include "src/Core/Block.h" #include "src/Core/VectorBlock.h" -#include "src/Core/Ref.h" +#include "src/Core/IndexedView.h" +#include "src/Core/Reshaped.h" #include "src/Core/Transpose.h" #include "src/Core/DiagonalMatrix.h" #include "src/Core/Diagonal.h" #include "src/Core/DiagonalProduct.h" -#include "src/Core/PermutationMatrix.h" -#include "src/Core/Transpositions.h" +#include "src/Core/SkewSymmetricMatrix3.h" #include "src/Core/Redux.h" #include "src/Core/Visitor.h" +#include "src/Core/FindCoeff.h" #include "src/Core/Fuzzy.h" -#include "src/Core/IO.h" #include "src/Core/Swap.h" #include "src/Core/CommaInitializer.h" -#include "src/Core/Flagged.h" -#include "src/Core/ProductBase.h" #include "src/Core/GeneralProduct.h" +#include "src/Core/Solve.h" +#include "src/Core/Inverse.h" +#include "src/Core/SolverBase.h" +#include "src/Core/PermutationMatrix.h" +#include "src/Core/Transpositions.h" #include "src/Core/TriangularMatrix.h" #include "src/Core/SelfAdjointView.h" #include "src/Core/products/GeneralBlockPanelKernel.h" +#include "src/Core/DeviceWrapper.h" +#ifdef EIGEN_GEMM_THREADPOOL +#include "ThreadPool" +#endif #include "src/Core/products/Parallelizer.h" -#include "src/Core/products/CoeffBasedProduct.h" +#include "src/Core/ProductEvaluators.h" #include "src/Core/products/GeneralMatrixVector.h" #include "src/Core/products/GeneralMatrixMatrix.h" #include "src/Core/SolveTriangular.h" @@ -340,37 +405,47 @@ using std::ptrdiff_t; #include "src/Core/products/TriangularSolverVector.h" #include "src/Core/BandMatrix.h" #include "src/Core/CoreIterators.h" +#include "src/Core/ConditionEstimator.h" + +#if defined(EIGEN_VECTORIZE_VSX) +#include "src/Core/arch/AltiVec/MatrixProduct.h" +#elif defined EIGEN_VECTORIZE_NEON +#include "src/Core/arch/NEON/GeneralBlockPanelKernel.h" +#elif defined EIGEN_VECTORIZE_LSX +#include "src/Core/arch/LSX/GeneralBlockPanelKernel.h" +#endif + +#if defined(EIGEN_VECTORIZE_AVX512) +#include "src/Core/arch/AVX512/GemmKernel.h" +#endif -#include "src/Core/BooleanRedux.h" #include "src/Core/Select.h" #include "src/Core/VectorwiseOp.h" +#include "src/Core/PartialReduxEvaluator.h" #include "src/Core/Random.h" #include "src/Core/Replicate.h" #include "src/Core/Reverse.h" -#include "src/Core/ArrayBase.h" #include "src/Core/ArrayWrapper.h" +#include "src/Core/StlIterators.h" #ifdef EIGEN_USE_BLAS -#include "src/Core/products/GeneralMatrixMatrix_MKL.h" -#include "src/Core/products/GeneralMatrixVector_MKL.h" -#include "src/Core/products/GeneralMatrixMatrixTriangular_MKL.h" -#include "src/Core/products/SelfadjointMatrixMatrix_MKL.h" -#include "src/Core/products/SelfadjointMatrixVector_MKL.h" -#include "src/Core/products/TriangularMatrixMatrix_MKL.h" -#include "src/Core/products/TriangularMatrixVector_MKL.h" -#include "src/Core/products/TriangularSolverMatrix_MKL.h" -#endif // EIGEN_USE_BLAS +#include "src/Core/products/GeneralMatrixMatrix_BLAS.h" +#include "src/Core/products/GeneralMatrixVector_BLAS.h" +#include "src/Core/products/GeneralMatrixMatrixTriangular_BLAS.h" +#include "src/Core/products/SelfadjointMatrixMatrix_BLAS.h" +#include "src/Core/products/SelfadjointMatrixVector_BLAS.h" +#include "src/Core/products/TriangularMatrixMatrix_BLAS.h" +#include "src/Core/products/TriangularMatrixVector_BLAS.h" +#include "src/Core/products/TriangularSolverMatrix_BLAS.h" +#endif // EIGEN_USE_BLAS #ifdef EIGEN_USE_MKL_VML #include "src/Core/Assign_MKL.h" #endif #include "src/Core/GlobalFunctions.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#ifdef EIGEN2_SUPPORT -#include "Eigen2Support" -#endif - -#endif // EIGEN_CORE_H +#endif // EIGEN_CORE_MODULE_H diff --git a/inst/include/Eigen/Eigen b/inst/include/Eigen/Eigen index 19b40ea4..654c8dc6 100644 --- a/inst/include/Eigen/Eigen +++ b/inst/include/Eigen/Eigen @@ -1,2 +1,2 @@ #include "Dense" -//#include "Sparse" +#include "Sparse" diff --git a/inst/include/Eigen/Eigen2Support b/inst/include/Eigen/Eigen2Support deleted file mode 100644 index 6aa009d2..00000000 --- a/inst/include/Eigen/Eigen2Support +++ /dev/null @@ -1,95 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2009 Gael Guennebaud -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#ifndef EIGEN2SUPPORT_H -#define EIGEN2SUPPORT_H - -#if (!defined(EIGEN2_SUPPORT)) || (!defined(EIGEN_CORE_H)) -#error Eigen2 support must be enabled by defining EIGEN2_SUPPORT before including any Eigen header -#endif - -#ifndef EIGEN_NO_EIGEN2_DEPRECATED_WARNING - -#if defined(__GNUC__) || defined(__INTEL_COMPILER) || defined(__clang__) -#warning "Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)" -#else -#pragma message ("Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. (Define EIGEN_NO_EIGEN2_DEPRECATED_WARNING to disable this warning)") -#endif - -#endif // EIGEN_NO_EIGEN2_DEPRECATED_WARNING - -#include "src/Core/util/DisableStupidWarnings.h" - -/** \ingroup Support_modules - * \defgroup Eigen2Support_Module Eigen2 support module - * - * \warning Eigen2 support is deprecated in Eigen 3.2.x and it will be removed in Eigen 3.3. - * - * This module provides a couple of deprecated functions improving the compatibility with Eigen2. - * - * To use it, define EIGEN2_SUPPORT before including any Eigen header - * \code - * #define EIGEN2_SUPPORT - * \endcode - * - */ - -#include "src/Eigen2Support/Macros.h" -#include "src/Eigen2Support/Memory.h" -#include "src/Eigen2Support/Meta.h" -#include "src/Eigen2Support/Lazy.h" -#include "src/Eigen2Support/Cwise.h" -#include "src/Eigen2Support/CwiseOperators.h" -#include "src/Eigen2Support/TriangularSolver.h" -#include "src/Eigen2Support/Block.h" -#include "src/Eigen2Support/VectorBlock.h" -#include "src/Eigen2Support/Minor.h" -#include "src/Eigen2Support/MathFunctions.h" - - -#include "src/Core/util/ReenableStupidWarnings.h" - -// Eigen2 used to include iostream -#include - -#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \ -using Eigen::Matrix##SizeSuffix##TypeSuffix; \ -using Eigen::Vector##SizeSuffix##TypeSuffix; \ -using Eigen::RowVector##SizeSuffix##TypeSuffix; - -#define EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(TypeSuffix) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \ - -#define EIGEN_USING_MATRIX_TYPEDEFS \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(i) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(f) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(d) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cf) \ -EIGEN_USING_MATRIX_TYPEDEFS_FOR_TYPE(cd) - -#define USING_PART_OF_NAMESPACE_EIGEN \ -EIGEN_USING_MATRIX_TYPEDEFS \ -using Eigen::Matrix; \ -using Eigen::MatrixBase; \ -using Eigen::ei_random; \ -using Eigen::ei_real; \ -using Eigen::ei_imag; \ -using Eigen::ei_conj; \ -using Eigen::ei_abs; \ -using Eigen::ei_abs2; \ -using Eigen::ei_sqrt; \ -using Eigen::ei_exp; \ -using Eigen::ei_log; \ -using Eigen::ei_sin; \ -using Eigen::ei_cos; - -#endif // EIGEN2SUPPORT_H diff --git a/inst/include/Eigen/Eigenvalues b/inst/include/Eigen/Eigenvalues index 53c5a73a..3b0bdee1 100644 --- a/inst/include/Eigen/Eigenvalues +++ b/inst/include/Eigen/Eigenvalues @@ -1,30 +1,40 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_EIGENVALUES_MODULE_H #define EIGEN_EIGENVALUES_MODULE_H #include "Core" -#include "src/Core/util/DisableStupidWarnings.h" - #include "Cholesky" #include "Jacobi" #include "Householder" #include "LU" #include "Geometry" +#include "src/Core/util/DisableStupidWarnings.h" + /** \defgroup Eigenvalues_Module Eigenvalues module - * - * - * - * This module mainly provides various eigenvalue solvers. - * This module also provides some MatrixBase methods, including: - * - MatrixBase::eigenvalues(), - * - MatrixBase::operatorNorm() - * - * \code - * #include - * \endcode - */ + * + * + * + * This module mainly provides various eigenvalue solvers. + * This module also provides some MatrixBase methods, including: + * - MatrixBase::eigenvalues(), + * - MatrixBase::operatorNorm() + * + * \code + * #include + * \endcode + */ + +#include "src/misc/RealSvd2x2.h" +// IWYU pragma: begin_exports #include "src/Eigenvalues/Tridiagonalization.h" #include "src/Eigenvalues/RealSchur.h" #include "src/Eigenvalues/EigenSolver.h" @@ -37,12 +47,17 @@ #include "src/Eigenvalues/GeneralizedEigenSolver.h" #include "src/Eigenvalues/MatrixBaseEigenvalues.h" #ifdef EIGEN_USE_LAPACKE -#include "src/Eigenvalues/RealSchur_MKL.h" -#include "src/Eigenvalues/ComplexSchur_MKL.h" -#include "src/Eigenvalues/SelfAdjointEigenSolver_MKL.h" +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else +#include "src/misc/lapacke.h" +#endif +#include "src/Eigenvalues/RealSchur_LAPACKE.h" +#include "src/Eigenvalues/ComplexSchur_LAPACKE.h" +#include "src/Eigenvalues/SelfAdjointEigenSolver_LAPACKE.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_EIGENVALUES_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_EIGENVALUES_MODULE_H diff --git a/inst/include/Eigen/Geometry b/inst/include/Eigen/Geometry index efd9d450..efe3e1fa 100644 --- a/inst/include/Eigen/Geometry +++ b/inst/include/Eigen/Geometry @@ -1,63 +1,59 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_GEOMETRY_MODULE_H #define EIGEN_GEOMETRY_MODULE_H #include "Core" -#include "src/Core/util/DisableStupidWarnings.h" - #include "SVD" #include "LU" #include -#ifndef M_PI -#define M_PI 3.14159265358979323846 -#endif +#include "src/Core/util/DisableStupidWarnings.h" /** \defgroup Geometry_Module Geometry module - * - * - * - * This module provides support for: - * - fixed-size homogeneous transformations - * - translation, scaling, 2D and 3D rotations - * - quaternions - * - \ref MatrixBase::cross() "cross product" - * - \ref MatrixBase::unitOrthogonal() "orthognal vector generation" - * - some linear components: parametrized-lines and hyperplanes - * - * \code - * #include - * \endcode - */ - + * + * This module provides support for: + * - fixed-size homogeneous transformations + * - translation, scaling, 2D and 3D rotations + * - \link Quaternion quaternions \endlink + * - cross products (\ref MatrixBase::cross(), \ref MatrixBase::cross3()) + * - orthogonal vector generation (MatrixBase::unitOrthogonal) + * - some linear components: \link ParametrizedLine parametrized-lines \endlink and \link Hyperplane hyperplanes \endlink + * - \link AlignedBox axis aligned bounding boxes \endlink + * - \link umeyama() least-square transformation fitting \endlink + * \code + * #include + * \endcode + */ + +// IWYU pragma: begin_exports #include "src/Geometry/OrthoMethods.h" #include "src/Geometry/EulerAngles.h" - -#if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS - #include "src/Geometry/Homogeneous.h" - #include "src/Geometry/RotationBase.h" - #include "src/Geometry/Rotation2D.h" - #include "src/Geometry/Quaternion.h" - #include "src/Geometry/AngleAxis.h" - #include "src/Geometry/Transform.h" - #include "src/Geometry/Translation.h" - #include "src/Geometry/Scaling.h" - #include "src/Geometry/Hyperplane.h" - #include "src/Geometry/ParametrizedLine.h" - #include "src/Geometry/AlignedBox.h" - #include "src/Geometry/Umeyama.h" - - #if defined EIGEN_VECTORIZE_SSE - #include "src/Geometry/arch/Geometry_SSE.h" - #endif -#endif - -#ifdef EIGEN2_SUPPORT -#include "src/Eigen2Support/Geometry/All.h" +#include "src/Geometry/Homogeneous.h" +#include "src/Geometry/RotationBase.h" +#include "src/Geometry/Rotation2D.h" +#include "src/Geometry/Quaternion.h" +#include "src/Geometry/AngleAxis.h" +#include "src/Geometry/Transform.h" +#include "src/Geometry/Translation.h" +#include "src/Geometry/Scaling.h" +#include "src/Geometry/Hyperplane.h" +#include "src/Geometry/ParametrizedLine.h" +#include "src/Geometry/AlignedBox.h" +#include "src/Geometry/Umeyama.h" + +// Use the SSE optimized version whenever possible. +#if (defined EIGEN_VECTORIZE_SSE) || (defined EIGEN_VECTORIZE_NEON) +#include "src/Geometry/arch/Geometry_SIMD.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_GEOMETRY_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ - +#endif // EIGEN_GEOMETRY_MODULE_H diff --git a/inst/include/Eigen/Householder b/inst/include/Eigen/Householder index 6e348db5..5070e070 100644 --- a/inst/include/Eigen/Householder +++ b/inst/include/Eigen/Householder @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_HOUSEHOLDER_MODULE_H #define EIGEN_HOUSEHOLDER_MODULE_H @@ -6,18 +13,19 @@ #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup Householder_Module Householder module - * This module provides Householder transformations. - * - * \code - * #include - * \endcode - */ + * This module provides Householder transformations. + * + * \code + * #include + * \endcode + */ +// IWYU pragma: begin_exports #include "src/Householder/Householder.h" #include "src/Householder/HouseholderSequence.h" #include "src/Householder/BlockHouseholder.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_HOUSEHOLDER_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_HOUSEHOLDER_MODULE_H diff --git a/inst/include/Eigen/IterativeLinearSolvers b/inst/include/Eigen/IterativeLinearSolvers index 0f4159dc..fe5159e9 100644 --- a/inst/include/Eigen/IterativeLinearSolvers +++ b/inst/include/Eigen/IterativeLinearSolvers @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_ITERATIVELINEARSOLVERS_MODULE_H #define EIGEN_ITERATIVELINEARSOLVERS_MODULE_H @@ -6,35 +13,40 @@ #include "src/Core/util/DisableStupidWarnings.h" -/** +/** * \defgroup IterativeLinearSolvers_Module IterativeLinearSolvers module * - * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a squared matrix, usually very large and sparse. + * This module currently provides iterative methods to solve problems of the form \c A \c x = \c b, where \c A is a + squared matrix, usually very large and sparse. * Those solvers are accessible via the following classes: * - ConjugateGradient for selfadjoint (hermitian) matrices, + * - LeastSquaresConjugateGradient for rectangular least-square problems, * - BiCGSTAB for general square matrices. * * These iterative solvers are associated with some preconditioners: * - IdentityPreconditioner - not really useful - * - DiagonalPreconditioner - also called JAcobi preconditioner, work very well on diagonal dominant matrices. - * - IncompleteILUT - incomplete LU factorization with dual thresholding + * - DiagonalPreconditioner - also called Jacobi preconditioner, work very well on diagonal dominant matrices. + * - IncompleteLUT - incomplete LU factorization with dual thresholding * - * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, UmfPackSupport, SuperLUSupport. + * Such problems can also be solved using the direct sparse decomposition modules: SparseCholesky, CholmodSupport, + UmfPackSupport, SuperLUSupport, AccelerateSupport. * - * \code - * #include - * \endcode + \code + #include + \endcode */ -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" - +// IWYU pragma: begin_exports +#include "src/IterativeLinearSolvers/SolveWithGuess.h" #include "src/IterativeLinearSolvers/IterativeSolverBase.h" #include "src/IterativeLinearSolvers/BasicPreconditioners.h" #include "src/IterativeLinearSolvers/ConjugateGradient.h" +#include "src/IterativeLinearSolvers/LeastSquareConjugateGradient.h" #include "src/IterativeLinearSolvers/BiCGSTAB.h" #include "src/IterativeLinearSolvers/IncompleteLUT.h" +#include "src/IterativeLinearSolvers/IncompleteCholesky.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H +#endif // EIGEN_ITERATIVELINEARSOLVERS_MODULE_H diff --git a/inst/include/Eigen/Jacobi b/inst/include/Eigen/Jacobi index ba8a4dc3..31eb36a7 100644 --- a/inst/include/Eigen/Jacobi +++ b/inst/include/Eigen/Jacobi @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_JACOBI_MODULE_H #define EIGEN_JACOBI_MODULE_H @@ -6,21 +13,21 @@ #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup Jacobi_Module Jacobi module - * This module provides Jacobi and Givens rotations. - * - * \code - * #include - * \endcode - * - * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation: - * - MatrixBase::applyOnTheLeft() - * - MatrixBase::applyOnTheRight(). - */ + * This module provides Jacobi and Givens rotations. + * + * \code + * #include + * \endcode + * + * In addition to listed classes, it defines the two following MatrixBase methods to apply a Jacobi or Givens rotation: + * - MatrixBase::applyOnTheLeft() + * - MatrixBase::applyOnTheRight(). + */ +// IWYU pragma: begin_exports #include "src/Jacobi/Jacobi.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_JACOBI_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ - +#endif // EIGEN_JACOBI_MODULE_H diff --git a/inst/include/Eigen/KLUSupport b/inst/include/Eigen/KLUSupport new file mode 100644 index 00000000..13959a3c --- /dev/null +++ b/inst/include/Eigen/KLUSupport @@ -0,0 +1,43 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_KLUSUPPORT_MODULE_H +#define EIGEN_KLUSUPPORT_MODULE_H + +#include "SparseCore" + +#include "src/Core/util/DisableStupidWarnings.h" + +extern "C" { +#include +#include +} + +/** \ingroup Support_modules + * \defgroup KLUSupport_Module KLUSupport module + * + * This module provides an interface to the KLU library which is part of the suitesparse package. It provides the following factorization class: + * - class KLU: a sparse LU factorization, well-suited for circuit simulation. + * + * \code + * #include + * \endcode + * + * In order to use this module, the klu and btf headers must be accessible from the include paths, and your binary must + * be linked to the klu library and its dependencies. The dependencies depend on how umfpack has been compiled. For a + * cmake based project, you can use our FindKLU.cmake module to help you in this task. + * + */ + +// IWYU pragma: begin_exports +#include "src/KLUSupport/KLUSupport.h" +// IWYU pragma: end_exports + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_KLUSUPPORT_MODULE_H diff --git a/inst/include/Eigen/LU b/inst/include/Eigen/LU index db579550..d8044803 100644 --- a/inst/include/Eigen/LU +++ b/inst/include/Eigen/LU @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_LU_MODULE_H #define EIGEN_LU_MODULE_H @@ -6,36 +13,34 @@ #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup LU_Module LU module - * This module includes %LU decomposition and related notions such as matrix inversion and determinant. - * This module defines the following MatrixBase methods: - * - MatrixBase::inverse() - * - MatrixBase::determinant() - * - * \code - * #include - * \endcode - */ - -#include "src/misc/Solve.h" + * This module includes %LU decomposition and related notions such as matrix inversion and determinant. + * This module defines the following MatrixBase methods: + * - MatrixBase::inverse() + * - MatrixBase::determinant() + * + * \code + * #include + * \endcode + */ + #include "src/misc/Kernel.h" #include "src/misc/Image.h" + +// IWYU pragma: begin_exports #include "src/LU/FullPivLU.h" #include "src/LU/PartialPivLU.h" #ifdef EIGEN_USE_LAPACKE -#include "src/LU/PartialPivLU_MKL.h" +#include "src/misc/lapacke_helpers.h" +#include "src/LU/PartialPivLU_LAPACKE.h" #endif #include "src/LU/Determinant.h" -#include "src/LU/Inverse.h" - -#if defined EIGEN_VECTORIZE_SSE - #include "src/LU/arch/Inverse_SSE.h" -#endif +#include "src/LU/InverseImpl.h" -#ifdef EIGEN2_SUPPORT - #include "src/Eigen2Support/LU.h" +#if defined EIGEN_VECTORIZE_SSE || defined EIGEN_VECTORIZE_NEON +#include "src/LU/arch/InverseSize4.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_LU_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_LU_MODULE_H diff --git a/inst/include/Eigen/LeastSquares b/inst/include/Eigen/LeastSquares deleted file mode 100644 index 35137c25..00000000 --- a/inst/include/Eigen/LeastSquares +++ /dev/null @@ -1,32 +0,0 @@ -#ifndef EIGEN_REGRESSION_MODULE_H -#define EIGEN_REGRESSION_MODULE_H - -#ifndef EIGEN2_SUPPORT -#error LeastSquares is only available in Eigen2 support mode (define EIGEN2_SUPPORT) -#endif - -// exclude from normal eigen3-only documentation -#ifdef EIGEN2_SUPPORT - -#include "Core" - -#include "src/Core/util/DisableStupidWarnings.h" - -#include "Eigenvalues" -#include "Geometry" - -/** \defgroup LeastSquares_Module LeastSquares module - * This module provides linear regression and related features. - * - * \code - * #include - * \endcode - */ - -#include "src/Eigen2Support/LeastSquares.h" - -#include "src/Core/util/ReenableStupidWarnings.h" - -#endif // EIGEN2_SUPPORT - -#endif // EIGEN_REGRESSION_MODULE_H diff --git a/inst/include/Eigen/MetisSupport b/inst/include/Eigen/MetisSupport index 6a113f7a..3636d3a0 100644 --- a/inst/include/Eigen/MetisSupport +++ b/inst/include/Eigen/MetisSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_METISSUPPORT_MODULE_H #define EIGEN_METISSUPPORT_MODULE_H @@ -9,20 +16,20 @@ extern "C" { #include } - /** \ingroup Support_modules - * \defgroup MetisSupport_Module MetisSupport module - * - * \code - * #include - * \endcode - * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis). - * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink - */ - - + * \defgroup MetisSupport_Module MetisSupport module + * + * \code + * #include + * \endcode + * This module defines an interface to the METIS reordering package (http://glaros.dtc.umn.edu/gkhome/views/metis). + * It can be used just as any other built-in method as explained in \link OrderingMethods_Module here. \endlink + */ + +// IWYU pragma: begin_exports #include "src/MetisSupport/MetisSupport.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_METISSUPPORT_MODULE_H +#endif // EIGEN_METISSUPPORT_MODULE_H diff --git a/inst/include/Eigen/OrderingMethods b/inst/include/Eigen/OrderingMethods index 7c0f1fff..01674194 100644 --- a/inst/include/Eigen/OrderingMethods +++ b/inst/include/Eigen/OrderingMethods @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_ORDERINGMETHODS_MODULE_H #define EIGEN_ORDERINGMETHODS_MODULE_H @@ -5,62 +12,62 @@ #include "src/Core/util/DisableStupidWarnings.h" -/** - * \defgroup OrderingMethods_Module OrderingMethods module - * - * This module is currently for internal use only - * - * It defines various built-in and external ordering methods for sparse matrices. - * They are typically used to reduce the number of elements during - * the sparse matrix decomposition (LLT, LU, QR). - * Precisely, in a preprocessing step, a permutation matrix P is computed using - * those ordering methods and applied to the columns of the matrix. - * Using for instance the sparse Cholesky decomposition, it is expected that - * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A). - * - * - * Usage : - * \code - * #include - * \endcode - * - * A simple usage is as a template parameter in the sparse decomposition classes : - * - * \code - * SparseLU > solver; - * \endcode - * - * \code - * SparseQR > solver; - * \endcode - * - * It is possible as well to call directly a particular ordering method for your own purpose, - * \code - * AMDOrdering ordering; - * PermutationMatrix perm; - * SparseMatrix A; - * //Fill the matrix ... - * - * ordering(A, perm); // Call AMD - * \endcode - * - * \note Some of these methods (like AMD or METIS), need the sparsity pattern - * of the input matrix to be symmetric. When the matrix is structurally unsymmetric, - * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method. - * If your matrix is already symmetric (at leat in structure), you can avoid that - * by calling the method with a SelfAdjointView type. - * - * \code - * // Call the ordering on the pattern of the lower triangular matrix A - * ordering(A.selfadjointView(), perm); - * \endcode - */ +/** + * \defgroup OrderingMethods_Module OrderingMethods module + * + * This module is currently for internal use only + * + * It defines various built-in and external ordering methods for sparse matrices. + * They are typically used to reduce the number of elements during + * the sparse matrix decomposition (LLT, LU, QR). + * Precisely, in a preprocessing step, a permutation matrix P is computed using + * those ordering methods and applied to the columns of the matrix. + * Using for instance the sparse Cholesky decomposition, it is expected that + * the nonzeros elements in LLT(A*P) will be much smaller than that in LLT(A). + * + * + * Usage : + * \code + * #include + * \endcode + * + * A simple usage is as a template parameter in the sparse decomposition classes : + * + * \code + * SparseLU > solver; + * \endcode + * + * \code + * SparseQR > solver; + * \endcode + * + * It is possible as well to call directly a particular ordering method for your own purpose, + * \code + * AMDOrdering ordering; + * PermutationMatrix perm; + * SparseMatrix A; + * //Fill the matrix ... + * + * ordering(A, perm); // Call AMD + * \endcode + * + * \note Some of these methods (like AMD or METIS), need the sparsity pattern + * of the input matrix to be symmetric. When the matrix is structurally unsymmetric, + * Eigen computes internally the pattern of \f$A^T*A\f$ before calling the method. + * If your matrix is already symmetric (at least in structure), you can avoid that + * by calling the method with a SelfAdjointView type. + * + * \code + * // Call the ordering on the pattern of the lower triangular matrix A + * ordering(A.selfadjointView(), perm); + * \endcode + */ -#ifndef EIGEN_MPL2_ONLY +// IWYU pragma: begin_exports #include "src/OrderingMethods/Amd.h" -#endif - #include "src/OrderingMethods/Ordering.h" +// IWYU pragma: end_exports + #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_ORDERINGMETHODS_MODULE_H +#endif // EIGEN_ORDERINGMETHODS_MODULE_H diff --git a/inst/include/Eigen/PaStiXSupport b/inst/include/Eigen/PaStiXSupport index 7c616ee5..dd1cfcb1 100644 --- a/inst/include/Eigen/PaStiXSupport +++ b/inst/include/Eigen/PaStiXSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_PASTIXSUPPORT_MODULE_H #define EIGEN_PASTIXSUPPORT_MODULE_H @@ -5,7 +12,6 @@ #include "src/Core/util/DisableStupidWarnings.h" -#include extern "C" { #include #include @@ -16,31 +22,30 @@ extern "C" { #endif /** \ingroup Support_modules - * \defgroup PaStiXSupport_Module PaStiXSupport module - * - * This module provides an interface to the PaSTiX library. - * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver. - * It provides the two following main factorization classes: - * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization. - * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization. - * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern). - * - * \code - * #include - * \endcode - * - * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be linked to the PaSTiX library and its dependencies. - * The dependencies depend on how PaSTiX has been compiled. - * For a cmake based project, you can use our FindPaSTiX.cmake module to help you in this task. - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" - + * \defgroup PaStiXSupport_Module PaStiXSupport module + * + * This module provides an interface to the PaSTiX library. + * PaSTiX is a general \b supernodal, \b parallel and \b opensource sparse solver. + * It provides the two following main factorization classes: + * - class PastixLLT : a supernodal, parallel LLt Cholesky factorization. + * - class PastixLDLT: a supernodal, parallel LDLt Cholesky factorization. + * - class PastixLU : a supernodal, parallel LU factorization (optimized for a symmetric pattern). + * + * \code + * #include + * \endcode + * + * In order to use this module, the PaSTiX headers must be accessible from the include paths, and your binary must be + * linked to the PaSTiX library and its dependencies. This wrapper resuires PaStiX version 5.x compiled without MPI + * support. The dependencies depend on how PaSTiX has been compiled. For a cmake based project, you can use our + * FindPaSTiX.cmake module to help you in this task. + * + */ + +// IWYU pragma: begin_exports #include "src/PaStiXSupport/PaStiXSupport.h" - +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_PASTIXSUPPORT_MODULE_H +#endif // EIGEN_PASTIXSUPPORT_MODULE_H diff --git a/inst/include/Eigen/PardisoSupport b/inst/include/Eigen/PardisoSupport index 99330ce7..4aef5fb3 100644 --- a/inst/include/Eigen/PardisoSupport +++ b/inst/include/Eigen/PardisoSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_PARDISOSUPPORT_MODULE_H #define EIGEN_PARDISOSUPPORT_MODULE_H @@ -7,24 +14,25 @@ #include -#include - /** \ingroup Support_modules - * \defgroup PardisoSupport_Module PardisoSupport module - * - * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers. - * - * \code - * #include - * \endcode - * - * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be linked to the MKL library and its dependencies. - * See this \ref TopicUsingIntelMKL "page" for more information on MKL-Eigen integration. - * - */ - + * \defgroup PardisoSupport_Module PardisoSupport module + * + * This module brings support for the Intel(R) MKL PARDISO direct sparse solvers. + * + * \code + * #include + * \endcode + * + * In order to use this module, the MKL headers must be accessible from the include paths, and your binary must be + * linked to the MKL library and its dependencies. See this \ref TopicUsingIntelMKL "page" for more information on + * MKL-Eigen integration. + * + */ + +// IWYU pragma: begin_exports #include "src/PardisoSupport/PardisoSupport.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_PARDISOSUPPORT_MODULE_H +#endif // EIGEN_PARDISOSUPPORT_MODULE_H diff --git a/inst/include/Eigen/QR b/inst/include/Eigen/QR index ac5b0269..c38b453b 100644 --- a/inst/include/Eigen/QR +++ b/inst/include/Eigen/QR @@ -1,45 +1,48 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_QR_MODULE_H #define EIGEN_QR_MODULE_H #include "Core" -#include "src/Core/util/DisableStupidWarnings.h" - #include "Cholesky" #include "Jacobi" #include "Householder" +#include "src/Core/util/DisableStupidWarnings.h" + /** \defgroup QR_Module QR module - * - * - * - * This module provides various QR decompositions - * This module also provides some MatrixBase methods, including: - * - MatrixBase::qr(), - * - * \code - * #include - * \endcode - */ - -#include "src/misc/Solve.h" + * + * + * + * This module provides various QR decompositions + * This module also provides some MatrixBase methods, including: + * - MatrixBase::householderQr() + * - MatrixBase::colPivHouseholderQr() + * - MatrixBase::fullPivHouseholderQr() + * + * \code + * #include + * \endcode + */ + +// IWYU pragma: begin_exports #include "src/QR/HouseholderQR.h" #include "src/QR/FullPivHouseholderQR.h" #include "src/QR/ColPivHouseholderQR.h" +#include "src/QR/CompleteOrthogonalDecomposition.h" #ifdef EIGEN_USE_LAPACKE -#include "src/QR/HouseholderQR_MKL.h" -#include "src/QR/ColPivHouseholderQR_MKL.h" -#endif - -#ifdef EIGEN2_SUPPORT -#include "src/Eigen2Support/QR.h" +#include "src/misc/lapacke_helpers.h" +#include "src/QR/HouseholderQR_LAPACKE.h" +#include "src/QR/ColPivHouseholderQR_LAPACKE.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#ifdef EIGEN2_SUPPORT -#include "Eigenvalues" -#endif - -#endif // EIGEN_QR_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_QR_MODULE_H diff --git a/inst/include/Eigen/QtAlignedMalloc b/inst/include/Eigen/QtAlignedMalloc index 46f7d83b..585f8e81 100644 --- a/inst/include/Eigen/QtAlignedMalloc +++ b/inst/include/Eigen/QtAlignedMalloc @@ -1,3 +1,9 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. #ifndef EIGEN_QTMALLOC_MODULE_H #define EIGEN_QTMALLOC_MODULE_H @@ -8,20 +14,13 @@ #include "src/Core/util/DisableStupidWarnings.h" -void *qMalloc(size_t size) -{ - return Eigen::internal::aligned_malloc(size); -} +void *qMalloc(std::size_t size) { return Eigen::internal::aligned_malloc(size); } -void qFree(void *ptr) -{ - Eigen::internal::aligned_free(ptr); -} +void qFree(void *ptr) { Eigen::internal::aligned_free(ptr); } -void *qRealloc(void *ptr, size_t size) -{ - void* newPtr = Eigen::internal::aligned_malloc(size); - memcpy(newPtr, ptr, size); +void *qRealloc(void *ptr, std::size_t size) { + void *newPtr = Eigen::internal::aligned_malloc(size); + std::memcpy(newPtr, ptr, size); Eigen::internal::aligned_free(ptr); return newPtr; } @@ -30,5 +29,4 @@ void *qRealloc(void *ptr, size_t size) #endif -#endif // EIGEN_QTMALLOC_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_QTMALLOC_MODULE_H diff --git a/inst/include/Eigen/SPQRSupport b/inst/include/Eigen/SPQRSupport index 77016442..c01dbe00 100644 --- a/inst/include/Eigen/SPQRSupport +++ b/inst/include/Eigen/SPQRSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SPQRSUPPORT_MODULE_H #define EIGEN_SPQRSUPPORT_MODULE_H @@ -8,22 +15,27 @@ #include "SuiteSparseQR.hpp" /** \ingroup Support_modules - * \defgroup SPQRSupport_Module SuiteSparseQR module - * - * This module provides an interface to the SPQR library, which is part of the suitesparse package. - * - * \code - * #include - * \endcode - * - * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...). - * For a cmake based project, you can use our FindSPQR.cmake and FindCholmod.Cmake modules - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" -#include "src/CholmodSupport/CholmodSupport.h" + * \defgroup SPQRSupport_Module SuiteSparseQR module + * + * This module provides an interface to the SPQR library, which is part of the suitesparse package. + * + * \code + * #include + * \endcode + * + * In order to use this module, the SPQR headers must be accessible from the include paths, and your binary must be + * linked to the SPQR library and its dependencies (Cholmod, AMD, COLAMD,...). For a cmake based project, you can use + * our FindSPQR.cmake and FindCholmod.Cmake modules + * + */ + +#include "CholmodSupport" + +// IWYU pragma: begin_exports #include "src/SPQRSupport/SuiteSparseQRSupport.h" +// IWYU pragma: end_exports + +#include "src/Core/util/ReenableStupidWarnings.h" #endif diff --git a/inst/include/Eigen/SVD b/inst/include/Eigen/SVD index fd310017..2a013f82 100644 --- a/inst/include/Eigen/SVD +++ b/inst/include/Eigen/SVD @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SVD_MODULE_H #define EIGEN_SVD_MODULE_H @@ -8,30 +15,42 @@ #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup SVD_Module SVD module - * - * - * - * This module provides SVD decomposition for matrices (both real and complex). - * This decomposition is accessible via the following MatrixBase method: - * - MatrixBase::jacobiSvd() - * - * \code - * #include - * \endcode - */ + * + * + * + * This module provides SVD decomposition for matrices (both real and complex). + * Two decomposition algorithms are provided: + * - JacobiSVD implementing two-sided Jacobi iterations is numerically very accurate, fast for small matrices, but very + * slow for larger ones. + * - BDCSVD implementing a recursive divide & conquer strategy on top of an upper-bidiagonalization which remains fast + * for large problems. These decompositions are accessible via the respective classes and following MatrixBase methods: + * - MatrixBase::jacobiSvd() + * - MatrixBase::bdcSvd() + * + * \code + * #include + * \endcode + */ -#include "src/misc/Solve.h" +// IWYU pragma: begin_exports +#include "src/misc/RealSvd2x2.h" +#include "src/SVD/UpperBidiagonalization.h" +#include "src/SVD/SVDBase.h" #include "src/SVD/JacobiSVD.h" -#if defined(EIGEN_USE_LAPACKE) && !defined(EIGEN_USE_LAPACKE_STRICT) -#include "src/SVD/JacobiSVD_MKL.h" +#include "src/SVD/BDCSVD.h" +#ifdef EIGEN_USE_LAPACKE +#ifdef EIGEN_USE_MKL +#include "mkl_lapacke.h" +#else +#include "src/misc/lapacke.h" #endif -#include "src/SVD/UpperBidiagonalization.h" - -#ifdef EIGEN2_SUPPORT -#include "src/Eigen2Support/SVD.h" +#ifndef EIGEN_USE_LAPACKE_STRICT +#include "src/SVD/JacobiSVD_LAPACKE.h" +#endif +#include "src/SVD/BDCSVD_LAPACKE.h" #endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_SVD_MODULE_H -/* vim: set filetype=cpp et sw=2 ts=2 ai: */ +#endif // EIGEN_SVD_MODULE_H diff --git a/inst/include/Eigen/Sparse b/inst/include/Eigen/Sparse index 7cc9c091..4d0ee8bc 100644 --- a/inst/include/Eigen/Sparse +++ b/inst/include/Eigen/Sparse @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SPARSE_MODULE_H #define EIGEN_SPARSE_MODULE_H @@ -11,9 +18,9 @@ * - \ref SparseQR_Module * - \ref IterativeLinearSolvers_Module * - * \code - * #include - * \endcode + \code + #include + \endcode */ #include "SparseCore" @@ -23,5 +30,4 @@ #include "SparseQR" #include "IterativeLinearSolvers" -#endif // EIGEN_SPARSE_MODULE_H - +#endif // EIGEN_SPARSE_MODULE_H diff --git a/inst/include/Eigen/SparseCholesky b/inst/include/Eigen/SparseCholesky index 9f5056aa..6abdcd66 100644 --- a/inst/include/Eigen/SparseCholesky +++ b/inst/include/Eigen/SparseCholesky @@ -15,33 +15,26 @@ #include "src/Core/util/DisableStupidWarnings.h" -/** - * \defgroup SparseCholesky_Module SparseCholesky module - * - * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) matrices. - * Those decompositions are accessible via the following classes: - * - SimplicialLLt, - * - SimplicialLDLt - * - * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module. - * - * \code - * #include - * \endcode - */ - -#ifdef EIGEN_MPL2_ONLY -#error The SparseCholesky module has nothing to offer in MPL2 only mode -#endif - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" +/** + * \defgroup SparseCholesky_Module SparseCholesky module + * + * This module currently provides two variants of the direct sparse Cholesky decomposition for selfadjoint (hermitian) + * matrices. Those decompositions are accessible via the following classes: + * - SimplicialLLt, + * - SimplicialLDLt + * + * Such problems can also be solved using the ConjugateGradient solver from the IterativeLinearSolvers module. + * + * \code + * #include + * \endcode + */ + +// IWYU pragma: begin_exports #include "src/SparseCholesky/SimplicialCholesky.h" - -#ifndef EIGEN_MPL2_ONLY #include "src/SparseCholesky/SimplicialCholesky_impl.h" -#endif +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_SPARSECHOLESKY_MODULE_H +#endif // EIGEN_SPARSECHOLESKY_MODULE_H diff --git a/inst/include/Eigen/SparseCore b/inst/include/Eigen/SparseCore index 24bcf015..56a9401a 100644 --- a/inst/include/Eigen/SparseCore +++ b/inst/include/Eigen/SparseCore @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SPARSECORE_MODULE_H #define EIGEN_SPARSECORE_MODULE_H @@ -10,55 +17,54 @@ #include #include #include +#include -/** - * \defgroup SparseCore_Module SparseCore module - * - * This module provides a sparse matrix representation, and basic associated matrix manipulations - * and operations. - * - * See the \ref TutorialSparse "Sparse tutorial" - * - * \code - * #include - * \endcode - * - * This module depends on: Core. - */ - -namespace Eigen { - -/** The type used to identify a general sparse storage. */ -struct Sparse {}; - -} +/** + * \defgroup SparseCore_Module SparseCore module + * + * This module provides a sparse matrix representation, and basic associated matrix manipulations + * and operations. + * + * See the \ref TutorialSparse "Sparse tutorial" + * + * \code + * #include + * \endcode + * + * This module depends on: Core. + */ +// IWYU pragma: begin_exports #include "src/SparseCore/SparseUtil.h" #include "src/SparseCore/SparseMatrixBase.h" +#include "src/SparseCore/SparseAssign.h" #include "src/SparseCore/CompressedStorage.h" #include "src/SparseCore/AmbiVector.h" +#include "src/SparseCore/SparseCompressedBase.h" #include "src/SparseCore/SparseMatrix.h" -#include "src/SparseCore/MappedSparseMatrix.h" +#include "src/SparseCore/SparseMap.h" #include "src/SparseCore/SparseVector.h" -#include "src/SparseCore/SparseBlock.h" -#include "src/SparseCore/SparseTranspose.h" +#include "src/SparseCore/SparseRef.h" #include "src/SparseCore/SparseCwiseUnaryOp.h" #include "src/SparseCore/SparseCwiseBinaryOp.h" +#include "src/SparseCore/SparseTranspose.h" +#include "src/SparseCore/SparseBlock.h" #include "src/SparseCore/SparseDot.h" -#include "src/SparseCore/SparsePermutation.h" #include "src/SparseCore/SparseRedux.h" -#include "src/SparseCore/SparseFuzzy.h" +#include "src/SparseCore/SparseView.h" +#include "src/SparseCore/SparseDiagonalProduct.h" #include "src/SparseCore/ConservativeSparseSparseProduct.h" #include "src/SparseCore/SparseSparseProductWithPruning.h" #include "src/SparseCore/SparseProduct.h" #include "src/SparseCore/SparseDenseProduct.h" -#include "src/SparseCore/SparseDiagonalProduct.h" -#include "src/SparseCore/SparseTriangularView.h" #include "src/SparseCore/SparseSelfAdjointView.h" +#include "src/SparseCore/SparseTriangularView.h" #include "src/SparseCore/TriangularSolver.h" -#include "src/SparseCore/SparseView.h" +#include "src/SparseCore/SparsePermutation.h" +#include "src/SparseCore/SparseFuzzy.h" +#include "src/SparseCore/SparseSolverBase.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_SPARSECORE_MODULE_H - +#endif // EIGEN_SPARSECORE_MODULE_H diff --git a/inst/include/Eigen/SparseLU b/inst/include/Eigen/SparseLU index 8527a49b..6faf1306 100644 --- a/inst/include/Eigen/SparseLU +++ b/inst/include/Eigen/SparseLU @@ -13,21 +13,19 @@ #include "SparseCore" -/** - * \defgroup SparseLU_Module SparseLU module - * This module defines a supernodal factorization of general sparse matrices. - * The code is fully optimized for supernode-panel updates with specialized kernels. - * Please, see the documentation of the SparseLU class for more details. - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" +/** + * \defgroup SparseLU_Module SparseLU module + * This module defines a supernodal factorization of general sparse matrices. + * The code is fully optimized for supernode-panel updates with specialized kernels. + * Please, see the documentation of the SparseLU class for more details. + */ // Ordering interface #include "OrderingMethods" -#include "src/SparseLU/SparseLU_gemm_kernel.h" +#include "src/Core/util/DisableStupidWarnings.h" +// IWYU pragma: begin_exports #include "src/SparseLU/SparseLU_Structs.h" #include "src/SparseLU/SparseLU_SupernodalMatrix.h" #include "src/SparseLU/SparseLUImpl.h" @@ -45,5 +43,8 @@ #include "src/SparseLU/SparseLU_pruneL.h" #include "src/SparseLU/SparseLU_Utils.h" #include "src/SparseLU/SparseLU.h" +// IWYU pragma: end_exports + +#include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_SPARSELU_MODULE_H +#endif // EIGEN_SPARSELU_MODULE_H diff --git a/inst/include/Eigen/SparseQR b/inst/include/Eigen/SparseQR index 4ee42065..b4f1cad6 100644 --- a/inst/include/Eigen/SparseQR +++ b/inst/include/Eigen/SparseQR @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SPARSEQR_MODULE_H #define EIGEN_SPARSEQR_MODULE_H @@ -6,27 +13,25 @@ #include "src/Core/util/DisableStupidWarnings.h" /** \defgroup SparseQR_Module SparseQR module - * \brief Provides QR decomposition for sparse matrices - * - * This module provides a simplicial version of the left-looking Sparse QR decomposition. - * The columns of the input matrix should be reordered to limit the fill-in during the - * decomposition. Built-in methods (COLAMD, AMD) or external methods (METIS) can be used to this end. - * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list - * of built-in and external ordering methods. - * - * \code - * #include - * \endcode - * - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" + * \brief Provides QR decomposition for sparse matrices + * + * This module provides a simplicial version of the left-looking Sparse QR decomposition. + * The columns of the input matrix should be reordered to limit the fill-in during the + * decomposition. Built-in methods (COLAMD, AMD) or external methods (METIS) can be used to this end. + * See the \link OrderingMethods_Module OrderingMethods\endlink module for the list + * of built-in and external ordering methods. + * + * \code + * #include + * \endcode + * + * + */ -#include "OrderingMethods" +// IWYU pragma: begin_exports #include "src/SparseCore/SparseColEtree.h" #include "src/SparseQR/SparseQR.h" +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" diff --git a/inst/include/Eigen/StdDeque b/inst/include/Eigen/StdDeque index f2723477..01e1d76f 100644 --- a/inst/include/Eigen/StdDeque +++ b/inst/include/Eigen/StdDeque @@ -14,14 +14,17 @@ #include "Core" #include -#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */ +#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \ + (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */ #define EIGEN_DEFINE_STL_DEQUE_SPECIALIZATION(...) #else +// IWYU pragma: begin_exports #include "src/StlSupport/StdDeque.h" +// IWYU pragma: end_exports #endif -#endif // EIGEN_STDDEQUE_MODULE_H +#endif // EIGEN_STDDEQUE_MODULE_H diff --git a/inst/include/Eigen/StdList b/inst/include/Eigen/StdList index 225c1e18..1453c9f5 100644 --- a/inst/include/Eigen/StdList +++ b/inst/include/Eigen/StdList @@ -13,14 +13,17 @@ #include "Core" #include -#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */ +#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \ + (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */ #define EIGEN_DEFINE_STL_LIST_SPECIALIZATION(...) #else +// IWYU pragma: begin_exports #include "src/StlSupport/StdList.h" +// IWYU pragma: end_exports #endif -#endif // EIGEN_STDLIST_MODULE_H +#endif // EIGEN_STDLIST_MODULE_H diff --git a/inst/include/Eigen/StdVector b/inst/include/Eigen/StdVector index 6b22627f..711a654e 100644 --- a/inst/include/Eigen/StdVector +++ b/inst/include/Eigen/StdVector @@ -14,14 +14,17 @@ #include "Core" #include -#if (defined(_MSC_VER) && defined(_WIN64)) /* MSVC auto aligns in 64 bit builds */ +#if EIGEN_COMP_MSVC && EIGEN_OS_WIN64 && \ + (EIGEN_MAX_STATIC_ALIGN_BYTES <= 16) /* MSVC auto aligns up to 16 bytes in 64 bit builds */ #define EIGEN_DEFINE_STL_VECTOR_SPECIALIZATION(...) #else +// IWYU pragma: begin_exports #include "src/StlSupport/StdVector.h" +// IWYU pragma: end_exports #endif -#endif // EIGEN_STDVECTOR_MODULE_H +#endif // EIGEN_STDVECTOR_MODULE_H diff --git a/inst/include/Eigen/SuperLUSupport b/inst/include/Eigen/SuperLUSupport index 575e14fb..79e2222f 100644 --- a/inst/include/Eigen/SuperLUSupport +++ b/inst/include/Eigen/SuperLUSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_SUPERLUSUPPORT_MODULE_H #define EIGEN_SUPERLUSUPPORT_MODULE_H @@ -19,41 +26,45 @@ typedef int int_t; // If EMPTY was already defined then we don't undef it. #if defined(EIGEN_EMPTY_WAS_ALREADY_DEFINED) -# undef EIGEN_EMPTY_WAS_ALREADY_DEFINED +#undef EIGEN_EMPTY_WAS_ALREADY_DEFINED #elif defined(EMPTY) -# undef EMPTY +#undef EMPTY #endif #define SUPERLU_EMPTY (-1) -namespace Eigen { struct SluMatrix; } +namespace Eigen { +struct SluMatrix; +} /** \ingroup Support_modules - * \defgroup SuperLUSupport_Module SuperLUSupport module - * - * This module provides an interface to the SuperLU library. - * It provides the following factorization class: - * - class SuperLU: a supernodal sequential LU factorization. - * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative methods). - * - * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined because it is too polluting. - * - * \code - * #include - * \endcode - * - * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be linked to the superlu library and its dependencies. - * The dependencies depend on how superlu has been compiled. - * For a cmake based project, you can use our FindSuperLU.cmake module to help you in this task. - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" + * \defgroup SuperLUSupport_Module SuperLUSupport module + * + * This module provides an interface to the SuperLU library. + * It provides the following factorization class: + * - class SuperLU: a supernodal sequential LU factorization. + * - class SuperILU: a supernodal sequential incomplete LU factorization (to be used as a preconditioner for iterative + * methods). + * + * \warning This wrapper requires at least versions 4.0 of SuperLU. The 3.x versions are not supported. + * + * \warning When including this module, you have to use SUPERLU_EMPTY instead of EMPTY which is no longer defined + * because it is too polluting. + * + * \code + * #include + * \endcode + * + * In order to use this module, the superlu headers must be accessible from the include paths, and your binary must be + * linked to the superlu library and its dependencies. The dependencies depend on how superlu has been compiled. For a + * cmake based project, you can use our FindSuperLU.cmake module to help you in this task. + * + */ +// IWYU pragma: begin_exports #include "src/SuperLUSupport/SuperLUSupport.h" - +// IWYU pragma: end_exports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_SUPERLUSUPPORT_MODULE_H +#endif // EIGEN_SUPERLUSUPPORT_MODULE_H diff --git a/inst/include/Eigen/ThreadPool b/inst/include/Eigen/ThreadPool new file mode 100644 index 00000000..39e5d1ee --- /dev/null +++ b/inst/include/Eigen/ThreadPool @@ -0,0 +1,80 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2016 Benoit Steiner +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_THREADPOOL_MODULE_H +#define EIGEN_THREADPOOL_MODULE_H + +#include "Core" + +#include "src/Core/util/DisableStupidWarnings.h" + +/** \defgroup ThreadPool_Module ThreadPool Module + * + * This module provides 2 threadpool implementations + * - a simple reference implementation + * - a faster non blocking implementation + * + * \code + * #include + * \endcode + */ + +#include +#include +#include + +#include +#include +#include +#include +#include +#include +#include +#include +#include + +// There are non-parenthesized calls to "max" in the header, +// which trigger a check in test/main.h causing compilation to fail. +// We work around the check here by removing the check for max in +// the case where we have to emulate thread_local. +#ifdef max +#undef max +#endif +#include + +#include "src/Core/util/Meta.h" +#include "src/Core/util/MaxSizeVector.h" + +#ifndef EIGEN_MUTEX +#define EIGEN_MUTEX std::mutex +#endif +#ifndef EIGEN_MUTEX_LOCK +#define EIGEN_MUTEX_LOCK std::unique_lock +#endif +#ifndef EIGEN_CONDVAR +#define EIGEN_CONDVAR std::condition_variable +#endif + +// IWYU pragma: begin_exports +#include "src/ThreadPool/ThreadLocal.h" +#include "src/ThreadPool/ThreadYield.h" +#include "src/ThreadPool/ThreadCancel.h" +#include "src/ThreadPool/EventCount.h" +#include "src/ThreadPool/RunQueue.h" +#include "src/ThreadPool/ThreadPoolInterface.h" +#include "src/ThreadPool/ThreadEnvironment.h" +#include "src/ThreadPool/Barrier.h" +#include "src/ThreadPool/NonBlockingThreadPool.h" +#include "src/ThreadPool/CoreThreadPoolDevice.h" +#include "src/ThreadPool/ForkJoin.h" +// IWYU pragma: end_exports + +#include "src/Core/util/ReenableStupidWarnings.h" + +#endif // EIGEN_CXX11_THREADPOOL_MODULE_H diff --git a/inst/include/Eigen/UmfPackSupport b/inst/include/Eigen/UmfPackSupport index 984f64a8..126344cb 100644 --- a/inst/include/Eigen/UmfPackSupport +++ b/inst/include/Eigen/UmfPackSupport @@ -1,3 +1,10 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + #ifndef EIGEN_UMFPACKSUPPORT_MODULE_H #define EIGEN_UMFPACKSUPPORT_MODULE_H @@ -10,27 +17,26 @@ extern "C" { } /** \ingroup Support_modules - * \defgroup UmfPackSupport_Module UmfPackSupport module - * - * This module provides an interface to the UmfPack library which is part of the suitesparse package. - * It provides the following factorization class: - * - class UmfPackLU: a multifrontal sequential LU factorization. - * - * \code - * #include - * \endcode - * - * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be linked to the umfpack library and its dependencies. - * The dependencies depend on how umfpack has been compiled. - * For a cmake based project, you can use our FindUmfPack.cmake module to help you in this task. - * - */ - -#include "src/misc/Solve.h" -#include "src/misc/SparseSolve.h" - + * \defgroup UmfPackSupport_Module UmfPackSupport module + * + * This module provides an interface to the UmfPack library which is part of the suitesparse package. It provides the following factorization class: + * - class UmfPackLU: a multifrontal sequential LU factorization. + * + * \code + * #include + * \endcode + * + * In order to use this module, the umfpack headers must be accessible from the include paths, and your binary must be + * linked to the umfpack library and its dependencies. The dependencies depend on how umfpack has been compiled. For a + * cmake based project, you can use our FindUmfPack.cmake module to help you in this task. + * + */ + +// IWYU pragma: begin_exports #include "src/UmfPackSupport/UmfPackSupport.h" +// IWYU pragma: endexports #include "src/Core/util/ReenableStupidWarnings.h" -#endif // EIGEN_UMFPACKSUPPORT_MODULE_H +#endif // EIGEN_UMFPACKSUPPORT_MODULE_H diff --git a/inst/include/Eigen/Version b/inst/include/Eigen/Version new file mode 100644 index 00000000..9cfd71ff --- /dev/null +++ b/inst/include/Eigen/Version @@ -0,0 +1,14 @@ +#ifndef EIGEN_VERSION_H +#define EIGEN_VERSION_H + +// The "WORLD" version will forever remain "3" for the "Eigen3" library. +#define EIGEN_WORLD_VERSION 3 +// As of Eigen3 5.0.0, we have moved to Semantic Versioning (semver.org). +#define EIGEN_MAJOR_VERSION 5 +#define EIGEN_MINOR_VERSION 0 +#define EIGEN_PATCH_VERSION 1 +#define EIGEN_PRERELEASE_VERSION "" +#define EIGEN_BUILD_VERSION "" +#define EIGEN_VERSION_STRING "5.0.1" + +#endif // EIGEN_VERSION_H diff --git a/inst/include/Eigen/src/AccelerateSupport/AccelerateSupport.h b/inst/include/Eigen/src/AccelerateSupport/AccelerateSupport.h new file mode 100644 index 00000000..13a26dfb --- /dev/null +++ b/inst/include/Eigen/src/AccelerateSupport/AccelerateSupport.h @@ -0,0 +1,423 @@ +#ifndef EIGEN_ACCELERATESUPPORT_H +#define EIGEN_ACCELERATESUPPORT_H + +#include + +#include + +namespace Eigen { + +template +class AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateLLT + * \brief A direct Cholesky (LLT) factorization and solver based on Accelerate + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ additional information about the matrix structure. Default is Lower. + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateLLT + */ +template +using AccelerateLLT = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateLDLT + * \brief The default Cholesky (LDLT) factorization and solver based on Accelerate + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ additional information about the matrix structure. Default is Lower. + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLT + */ +template +using AccelerateLDLT = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateLDLTUnpivoted + * \brief A direct Cholesky-like LDL^T factorization and solver based on Accelerate with only 1x1 pivots and no pivoting + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ additional information about the matrix structure. Default is Lower. + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTUnpivoted + */ +template +using AccelerateLDLTUnpivoted = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateLDLTSBK + * \brief A direct Cholesky (LDLT) factorization and solver based on Accelerate with Supernode Bunch-Kaufman and static + * pivoting + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ additional information about the matrix structure. Default is Lower. + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTSBK + */ +template +using AccelerateLDLTSBK = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateLDLTTPP + * \brief A direct Cholesky (LDLT) factorization and solver based on Accelerate with full threshold partial pivoting + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ additional information about the matrix structure. Default is Lower. + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateLDLTTPP + */ +template +using AccelerateLDLTTPP = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateQR + * \brief A QR factorization and solver based on Accelerate + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateQR + */ +template +using AccelerateQR = AccelerateImpl; + +/** \ingroup AccelerateSupport_Module + * \typedef AccelerateCholeskyAtA + * \brief A QR factorization and solver based on Accelerate without storing Q (equivalent to A^TA = R^T R) + * + * \warning Only single and double precision real scalar types are supported by Accelerate + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * + * \sa \ref TutorialSparseSolverConcept, class AccelerateCholeskyAtA + */ +template +using AccelerateCholeskyAtA = AccelerateImpl; + +namespace internal { +template +struct AccelFactorizationDeleter { + void operator()(T* sym) { + if (sym) { + SparseCleanup(*sym); + delete sym; + sym = nullptr; + } + } +}; + +template +struct SparseTypesTraitBase { + typedef DenseVecT AccelDenseVector; + typedef DenseMatT AccelDenseMatrix; + typedef SparseMatT AccelSparseMatrix; + + typedef SparseOpaqueSymbolicFactorization SymbolicFactorization; + typedef NumFactT NumericFactorization; + + typedef AccelFactorizationDeleter SymbolicFactorizationDeleter; + typedef AccelFactorizationDeleter NumericFactorizationDeleter; +}; + +template +struct SparseTypesTrait {}; + +template <> +struct SparseTypesTrait : SparseTypesTraitBase {}; + +template <> +struct SparseTypesTrait + : SparseTypesTraitBase { +}; + +} // end namespace internal + +template +class AccelerateImpl : public SparseSolverBase > { + protected: + using Base = SparseSolverBase; + using Base::derived; + using Base::m_isInitialized; + + public: + using Base::_solve_impl; + + typedef MatrixType_ MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::StorageIndex StorageIndex; + enum { ColsAtCompileTime = Dynamic, MaxColsAtCompileTime = Dynamic }; + enum { UpLo = UpLo_ }; + + using AccelDenseVector = typename internal::SparseTypesTrait::AccelDenseVector; + using AccelDenseMatrix = typename internal::SparseTypesTrait::AccelDenseMatrix; + using AccelSparseMatrix = typename internal::SparseTypesTrait::AccelSparseMatrix; + using SymbolicFactorization = typename internal::SparseTypesTrait::SymbolicFactorization; + using NumericFactorization = typename internal::SparseTypesTrait::NumericFactorization; + using SymbolicFactorizationDeleter = typename internal::SparseTypesTrait::SymbolicFactorizationDeleter; + using NumericFactorizationDeleter = typename internal::SparseTypesTrait::NumericFactorizationDeleter; + + AccelerateImpl() { + m_isInitialized = false; + + auto check_flag_set = [](int value, int flag) { return ((value & flag) == flag); }; + + if (check_flag_set(UpLo_, Symmetric)) { + m_sparseKind = SparseSymmetric; + m_triType = (UpLo_ & Lower) ? SparseLowerTriangle : SparseUpperTriangle; + } else if (check_flag_set(UpLo_, UnitLower)) { + m_sparseKind = SparseUnitTriangular; + m_triType = SparseLowerTriangle; + } else if (check_flag_set(UpLo_, UnitUpper)) { + m_sparseKind = SparseUnitTriangular; + m_triType = SparseUpperTriangle; + } else if (check_flag_set(UpLo_, StrictlyLower)) { + m_sparseKind = SparseTriangular; + m_triType = SparseLowerTriangle; + } else if (check_flag_set(UpLo_, StrictlyUpper)) { + m_sparseKind = SparseTriangular; + m_triType = SparseUpperTriangle; + } else if (check_flag_set(UpLo_, Lower)) { + m_sparseKind = SparseTriangular; + m_triType = SparseLowerTriangle; + } else if (check_flag_set(UpLo_, Upper)) { + m_sparseKind = SparseTriangular; + m_triType = SparseUpperTriangle; + } else { + m_sparseKind = SparseOrdinary; + m_triType = (UpLo_ & Lower) ? SparseLowerTriangle : SparseUpperTriangle; + } + + m_order = SparseOrderDefault; + } + + explicit AccelerateImpl(const MatrixType& matrix) : AccelerateImpl() { compute(matrix); } + + ~AccelerateImpl() {} + + inline Index cols() const { return m_nCols; } + inline Index rows() const { return m_nRows; } + + ComputationInfo info() const { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + void analyzePattern(const MatrixType& matrix); + + void factorize(const MatrixType& matrix); + + void compute(const MatrixType& matrix); + + template + void _solve_impl(const MatrixBase& b, MatrixBase& dest) const; + + /** Sets the ordering algorithm to use. */ + void setOrder(SparseOrder_t order) { m_order = order; } + + private: + template + void buildAccelSparseMatrix(const SparseMatrix& a, AccelSparseMatrix& A, std::vector& columnStarts) { + const Index nColumnsStarts = a.cols() + 1; + + columnStarts.resize(nColumnsStarts); + + for (Index i = 0; i < nColumnsStarts; i++) columnStarts[i] = a.outerIndexPtr()[i]; + + SparseAttributes_t attributes{}; + attributes.transpose = false; + attributes.triangle = m_triType; + attributes.kind = m_sparseKind; + + SparseMatrixStructure structure{}; + structure.attributes = attributes; + structure.rowCount = static_cast(a.rows()); + structure.columnCount = static_cast(a.cols()); + structure.blockSize = 1; + structure.columnStarts = columnStarts.data(); + structure.rowIndices = const_cast(a.innerIndexPtr()); + + A.structure = structure; + A.data = const_cast(a.valuePtr()); + } + + void doAnalysis(AccelSparseMatrix& A) { + m_numericFactorization.reset(nullptr); + + SparseSymbolicFactorOptions opts{}; + opts.control = SparseDefaultControl; + opts.orderMethod = m_order; + opts.order = nullptr; + opts.ignoreRowsAndColumns = nullptr; + opts.malloc = malloc; + opts.free = free; + opts.reportError = nullptr; + + m_symbolicFactorization.reset(new SymbolicFactorization(SparseFactor(Solver_, A.structure, opts))); + + SparseStatus_t status = m_symbolicFactorization->status; + + updateInfoStatus(status); + + if (status != SparseStatusOK) m_symbolicFactorization.reset(nullptr); + } + + void doFactorization(AccelSparseMatrix& A) { + SparseStatus_t status = SparseStatusReleased; + + if (m_symbolicFactorization) { + m_numericFactorization.reset(new NumericFactorization(SparseFactor(*m_symbolicFactorization, A))); + + status = m_numericFactorization->status; + + if (status != SparseStatusOK) m_numericFactorization.reset(nullptr); + } + + updateInfoStatus(status); + } + + protected: + void updateInfoStatus(SparseStatus_t status) const { + switch (status) { + case SparseStatusOK: + m_info = Success; + break; + case SparseFactorizationFailed: + case SparseMatrixIsSingular: + m_info = NumericalIssue; + break; + case SparseInternalError: + case SparseParameterError: + case SparseStatusReleased: + default: + m_info = InvalidInput; + break; + } + } + + mutable ComputationInfo m_info; + Index m_nRows, m_nCols; + std::unique_ptr m_symbolicFactorization; + std::unique_ptr m_numericFactorization; + SparseKind_t m_sparseKind; + SparseTriangle_t m_triType; + SparseOrder_t m_order; +}; + +/** Computes the symbolic and numeric decomposition of matrix \a a */ +template +void AccelerateImpl::compute(const MatrixType& a) { + if (EnforceSquare_) eigen_assert(a.rows() == a.cols()); + + m_nRows = a.rows(); + m_nCols = a.cols(); + + AccelSparseMatrix A{}; + std::vector columnStarts; + + buildAccelSparseMatrix(a, A, columnStarts); + + doAnalysis(A); + + if (m_symbolicFactorization) doFactorization(A); + + m_isInitialized = true; +} + +/** Performs a symbolic decomposition on the sparsity pattern of matrix \a a. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ +template +void AccelerateImpl::analyzePattern(const MatrixType& a) { + if (EnforceSquare_) eigen_assert(a.rows() == a.cols()); + + m_nRows = a.rows(); + m_nCols = a.cols(); + + AccelSparseMatrix A{}; + std::vector columnStarts; + + buildAccelSparseMatrix(a, A, columnStarts); + + doAnalysis(A); + + m_isInitialized = true; +} + +/** Performs a numeric decomposition of matrix \a a. + * + * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been + * performed. + * + * \sa analyzePattern() + */ +template +void AccelerateImpl::factorize(const MatrixType& a) { + eigen_assert(m_symbolicFactorization && "You must first call analyzePattern()"); + eigen_assert(m_nRows == a.rows() && m_nCols == a.cols()); + + if (EnforceSquare_) eigen_assert(a.rows() == a.cols()); + + AccelSparseMatrix A{}; + std::vector columnStarts; + + buildAccelSparseMatrix(a, A, columnStarts); + + doFactorization(A); +} + +template +template +void AccelerateImpl::_solve_impl(const MatrixBase& b, + MatrixBase& x) const { + if (!m_numericFactorization) { + m_info = InvalidInput; + return; + } + + eigen_assert(m_nRows == b.rows()); + eigen_assert(((b.cols() == 1) || b.outerStride() == b.rows())); + + SparseStatus_t status = SparseStatusOK; + + Scalar* b_ptr = const_cast(b.derived().data()); + Scalar* x_ptr = const_cast(x.derived().data()); + + AccelDenseMatrix xmat{}; + xmat.attributes = SparseAttributes_t(); + xmat.columnCount = static_cast(x.cols()); + xmat.rowCount = static_cast(x.rows()); + xmat.columnStride = xmat.rowCount; + xmat.data = x_ptr; + + AccelDenseMatrix bmat{}; + bmat.attributes = SparseAttributes_t(); + bmat.columnCount = static_cast(b.cols()); + bmat.rowCount = static_cast(b.rows()); + bmat.columnStride = bmat.rowCount; + bmat.data = b_ptr; + + SparseSolve(*m_numericFactorization, bmat, xmat); + + updateInfoStatus(status); +} + +} // end namespace Eigen + +#endif // EIGEN_ACCELERATESUPPORT_H diff --git a/inst/include/Eigen/src/AccelerateSupport/InternalHeaderCheck.h b/inst/include/Eigen/src/AccelerateSupport/InternalHeaderCheck.h new file mode 100644 index 00000000..69bcff50 --- /dev/null +++ b/inst/include/Eigen/src/AccelerateSupport/InternalHeaderCheck.h @@ -0,0 +1,3 @@ +#ifndef EIGEN_ACCELERATESUPPORT_MODULE_H +#error "Please include Eigen/AccelerateSupport instead of including headers inside the src directory directly." +#endif diff --git a/inst/include/Eigen/src/Cholesky/InternalHeaderCheck.h b/inst/include/Eigen/src/Cholesky/InternalHeaderCheck.h new file mode 100644 index 00000000..5de2b219 --- /dev/null +++ b/inst/include/Eigen/src/Cholesky/InternalHeaderCheck.h @@ -0,0 +1,3 @@ +#ifndef EIGEN_CHOLESKY_MODULE_H +#error "Please include Eigen/Cholesky instead of including headers inside the src directory directly." +#endif diff --git a/inst/include/Eigen/src/Cholesky/LDLT.h b/inst/include/Eigen/src/Cholesky/LDLT.h index abd30bd9..b1d801d3 100644 --- a/inst/include/Eigen/src/Cholesky/LDLT.h +++ b/inst/include/Eigen/src/Cholesky/LDLT.h @@ -13,296 +13,314 @@ #ifndef EIGEN_LDLT_H #define EIGEN_LDLT_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { namespace internal { - template struct LDLT_Traits; +template +struct traits > : traits { + typedef MatrixXpr XprKind; + typedef SolverStorage StorageKind; + typedef int StorageIndex; + enum { Flags = 0 }; +}; - // PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef - enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite }; -} +template +struct LDLT_Traits; + +// PositiveSemiDef means positive semi-definite and non-zero; same for NegativeSemiDef +enum SignMatrix { PositiveSemiDef, NegativeSemiDef, ZeroSign, Indefinite }; +} // namespace internal /** \ingroup Cholesky_Module - * - * \class LDLT - * - * \brief Robust Cholesky decomposition of a matrix with pivoting - * - * \param MatrixType the type of the matrix of which to compute the LDL^T Cholesky decomposition - * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper. - * The other triangular part won't be read. - * - * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite - * matrix \f$ A \f$ such that \f$ A = P^TLDL^*P \f$, where P is a permutation matrix, L - * is lower triangular with a unit diagonal and D is a diagonal matrix. - * - * The decomposition uses pivoting to ensure stability, so that L will have - * zeros in the bottom right rank(A) - n submatrix. Avoiding the square root - * on D also stabilizes the computation. - * - * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky - * decomposition to determine whether a system of equations has a solution. - * - * \sa MatrixBase::ldlt(), class LLT - */ -template class LDLT -{ - public: - typedef _MatrixType MatrixType; - enum { - RowsAtCompileTime = MatrixType::RowsAtCompileTime, - ColsAtCompileTime = MatrixType::ColsAtCompileTime, - Options = MatrixType::Options & ~RowMajorBit, // these are the options for the TmpMatrixType, we need a ColMajor matrix here! - MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, - MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, - UpLo = _UpLo - }; - typedef typename MatrixType::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - typedef typename MatrixType::Index Index; - typedef Matrix TmpMatrixType; - - typedef Transpositions TranspositionType; - typedef PermutationMatrix PermutationType; - - typedef internal::LDLT_Traits Traits; - - /** \brief Default Constructor. - * - * The default constructor is useful in cases in which the user intends to - * perform decompositions via LDLT::compute(const MatrixType&). - */ - LDLT() - : m_matrix(), - m_transpositions(), - m_sign(internal::ZeroSign), - m_isInitialized(false) - {} - - /** \brief Default Constructor with memory preallocation - * - * Like the default constructor but with preallocation of the internal data - * according to the specified problem \a size. - * \sa LDLT() - */ - LDLT(Index size) + * + * \class LDLT + * + * \brief Robust Cholesky decomposition of a matrix with pivoting + * + * \tparam MatrixType_ the type of the matrix of which to compute the LDL^T Cholesky decomposition + * \tparam UpLo_ the triangular part that will be used for the decomposition: Lower (default) or Upper. + * The other triangular part won't be read. + * + * Perform a robust Cholesky decomposition of a positive semidefinite or negative semidefinite + * matrix \f$ A \f$ such that \f$ A = P^TLDL^*P \f$, where P is a permutation matrix, L + * is lower triangular with a unit diagonal and D is a diagonal matrix. + * + * The decomposition uses pivoting to ensure stability, so that D will have + * zeros in the bottom right rank(A) - n submatrix. Avoiding the square root + * on D also stabilizes the computation. + * + * Remember that Cholesky decompositions are not rank-revealing. Also, do not use a Cholesky + * decomposition to determine whether a system of equations has a solution. + * + * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism. + * + * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt(), class LLT + */ +template +class LDLT : public SolverBase > { + public: + typedef MatrixType_ MatrixType; + typedef SolverBase Base; + friend class SolverBase; + + EIGEN_GENERIC_PUBLIC_INTERFACE(LDLT) + enum { + MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, + UpLo = UpLo_ + }; + typedef Matrix TmpMatrixType; + + typedef Transpositions TranspositionType; + typedef PermutationMatrix PermutationType; + + typedef internal::LDLT_Traits Traits; + + /** \brief Default Constructor. + * + * The default constructor is useful in cases in which the user intends to + * perform decompositions via LDLT::compute(const MatrixType&). + */ + LDLT() : m_matrix(), m_transpositions(), m_sign(internal::ZeroSign), m_isInitialized(false) {} + + /** \brief Default Constructor with memory preallocation + * + * Like the default constructor but with preallocation of the internal data + * according to the specified problem \a size. + * \sa LDLT() + */ + explicit LDLT(Index size) : m_matrix(size, size), m_transpositions(size), m_temporary(size), m_sign(internal::ZeroSign), - m_isInitialized(false) - {} - - /** \brief Constructor with decomposition - * - * This calculates the decomposition for the input \a matrix. - * \sa LDLT(Index size) - */ - LDLT(const MatrixType& matrix) + m_isInitialized(false) {} + + /** \brief Constructor with decomposition + * + * This calculates the decomposition for the input \a matrix. + * + * \sa LDLT(Index size) + */ + template + explicit LDLT(const EigenBase& matrix) : m_matrix(matrix.rows(), matrix.cols()), m_transpositions(matrix.rows()), m_temporary(matrix.rows()), m_sign(internal::ZeroSign), - m_isInitialized(false) - { - compute(matrix); - } - - /** Clear any existing decomposition - * \sa rankUpdate(w,sigma) - */ - void setZero() - { - m_isInitialized = false; - } - - /** \returns a view of the upper triangular matrix U */ - inline typename Traits::MatrixU matrixU() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return Traits::getU(m_matrix); - } - - /** \returns a view of the lower triangular matrix L */ - inline typename Traits::MatrixL matrixL() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return Traits::getL(m_matrix); - } - - /** \returns the permutation matrix P as a transposition sequence. - */ - inline const TranspositionType& transpositionsP() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_transpositions; - } - - /** \returns the coefficients of the diagonal matrix D */ - inline Diagonal vectorD() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_matrix.diagonal(); - } + m_isInitialized(false) { + compute(matrix.derived()); + } - /** \returns true if the matrix is positive (semidefinite) */ - inline bool isPositive() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign; - } - - #ifdef EIGEN2_SUPPORT - inline bool isPositiveDefinite() const - { - return isPositive(); - } - #endif + /** \brief Constructs a LDLT factorization from a given matrix + * + * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when \c + * MatrixType is a Eigen::Ref. + * + * \sa LDLT(const EigenBase&) + */ + template + explicit LDLT(EigenBase& matrix) + : m_matrix(matrix.derived()), + m_transpositions(matrix.rows()), + m_temporary(matrix.rows()), + m_sign(internal::ZeroSign), + m_isInitialized(false) { + compute(matrix.derived()); + } - /** \returns true if the matrix is negative (semidefinite) */ - inline bool isNegative(void) const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign; - } + /** Clear any existing decomposition + * \sa rankUpdate(w,sigma) + */ + void setZero() { m_isInitialized = false; } - /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * This function also supports in-place solves using the syntax x = decompositionObject.solve(x) . - * - * \note_about_checking_solutions - * - * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$ - * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$, - * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then - * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the - * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function - * computes the least-square solution of \f$ A x = b \f$ is \f$ A \f$ is singular. - * - * \sa MatrixBase::ldlt() - */ - template - inline const internal::solve_retval - solve(const MatrixBase& b) const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - eigen_assert(m_matrix.rows()==b.rows() - && "LDLT::solve(): invalid number of rows of the right hand side matrix b"); - return internal::solve_retval(*this, b.derived()); - } + /** \returns a view of the upper triangular matrix U */ + inline typename Traits::MatrixU matrixU() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return Traits::getU(m_matrix); + } - #ifdef EIGEN2_SUPPORT - template - bool solve(const MatrixBase& b, ResultType *result) const - { - *result = this->solve(b); - return true; - } - #endif + /** \returns a view of the lower triangular matrix L */ + inline typename Traits::MatrixL matrixL() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return Traits::getL(m_matrix); + } - template - bool solveInPlace(MatrixBase &bAndX) const; + /** \returns the permutation matrix P as a transposition sequence. + */ + inline const TranspositionType& transpositionsP() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_transpositions; + } - LDLT& compute(const MatrixType& matrix); + /** \returns the coefficients of the diagonal matrix D */ + inline Diagonal vectorD() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_matrix.diagonal(); + } - template - LDLT& rankUpdate(const MatrixBase& w, const RealScalar& alpha=1); + /** \returns true if the matrix is positive (semidefinite) */ + inline bool isPositive() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_sign == internal::PositiveSemiDef || m_sign == internal::ZeroSign; + } - /** \returns the internal LDLT decomposition matrix - * - * TODO: document the storage layout - */ - inline const MatrixType& matrixLDLT() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return m_matrix; - } + /** \returns true if the matrix is negative (semidefinite) */ + inline bool isNegative(void) const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_sign == internal::NegativeSemiDef || m_sign == internal::ZeroSign; + } - MatrixType reconstructedMatrix() const; +#ifdef EIGEN_PARSED_BY_DOXYGEN + /** \returns a solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * This function also supports in-place solves using the syntax x = decompositionObject.solve(x) . + * + * \note_about_checking_solutions + * + * More precisely, this method solves \f$ A x = b \f$ using the decomposition \f$ A = P^T L D L^* P \f$ + * by solving the systems \f$ P^T y_1 = b \f$, \f$ L y_2 = y_1 \f$, \f$ D y_3 = y_2 \f$, + * \f$ L^* y_4 = y_3 \f$ and \f$ P x = y_4 \f$ in succession. If the matrix \f$ A \f$ is singular, then + * \f$ D \f$ will also be singular (all the other matrices are invertible). In that case, the + * least-square solution of \f$ D y_3 = y_2 \f$ is computed. This does not mean that this function + * computes the least-square solution of \f$ A x = b \f$ if \f$ A \f$ is singular. + * + * \sa MatrixBase::ldlt(), SelfAdjointView::ldlt() + */ + template + inline const Solve solve(const MatrixBase& b) const; +#endif + + template + bool solveInPlace(MatrixBase& bAndX) const; + + template + LDLT& compute(const EigenBase& matrix); + + /** \returns an estimate of the reciprocal condition number of the matrix of + * which \c *this is the LDLT decomposition. + */ + RealScalar rcond() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return internal::rcond_estimate_helper(m_l1_norm, *this); + } - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } + template + LDLT& rankUpdate(const MatrixBase& w, const RealScalar& alpha = 1); - /** \brief Reports whether previous computation was successful. - * - * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. - */ - ComputationInfo info() const - { - eigen_assert(m_isInitialized && "LDLT is not initialized."); - return Success; - } + /** \returns the internal LDLT decomposition matrix + * + * TODO: document the storage layout + */ + inline const MatrixType& matrixLDLT() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_matrix; + } - protected: - - static void check_template_parameters() - { - EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar); - } + MatrixType reconstructedMatrix() const; + + /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix + * is self-adjoint. + * + * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as: + * \code x = decomposition.adjoint().solve(b) \endcode + */ + const LDLT& adjoint() const { return *this; } + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_matrix.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_matrix.cols(); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was successful, + * \c NumericalIssue if the factorization failed because of a zero pivot. + */ + ComputationInfo info() const { + eigen_assert(m_isInitialized && "LDLT is not initialized."); + return m_info; + } - /** \internal - * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U. - * The strict upper part is used during the decomposition, the strict lower - * part correspond to the coefficients of L (its diagonal is equal to 1 and - * is not stored), and the diagonal entries correspond to D. - */ - MatrixType m_matrix; - TranspositionType m_transpositions; - TmpMatrixType m_temporary; - internal::SignMatrix m_sign; - bool m_isInitialized; +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + void _solve_impl(const RhsType& rhs, DstType& dst) const; + + template + void _solve_impl_transposed(const RhsType& rhs, DstType& dst) const; +#endif + + protected: + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) + + /** \internal + * Used to compute and store the Cholesky decomposition A = L D L^* = U^* D U. + * The strict upper part is used during the decomposition, the strict lower + * part correspond to the coefficients of L (its diagonal is equal to 1 and + * is not stored), and the diagonal entries correspond to D. + */ + MatrixType m_matrix; + RealScalar m_l1_norm; + TranspositionType m_transpositions; + TmpMatrixType m_temporary; + internal::SignMatrix m_sign; + bool m_isInitialized; + ComputationInfo m_info; }; namespace internal { -template struct ldlt_inplace; +template +struct ldlt_inplace; -template<> struct ldlt_inplace -{ - template - static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) - { +template <> +struct ldlt_inplace { + template + static bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) { using std::abs; typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; - typedef typename MatrixType::Index Index; - eigen_assert(mat.rows()==mat.cols()); + typedef typename TranspositionType::StorageIndex IndexType; + eigen_assert(mat.rows() == mat.cols()); const Index size = mat.rows(); + bool found_zero_pivot = false; + bool ret = true; - if (size <= 1) - { + if (size <= 1) { transpositions.setIdentity(); - if (numext::real(mat.coeff(0,0)) > 0) sign = PositiveSemiDef; - else if (numext::real(mat.coeff(0,0)) < 0) sign = NegativeSemiDef; - else sign = ZeroSign; + if (size == 0) + sign = ZeroSign; + else if (numext::real(mat.coeff(0, 0)) > static_cast(0)) + sign = PositiveSemiDef; + else if (numext::real(mat.coeff(0, 0)) < static_cast(0)) + sign = NegativeSemiDef; + else + sign = ZeroSign; return true; } - for (Index k = 0; k < size; ++k) - { + for (Index k = 0; k < size; ++k) { // Find largest diagonal element Index index_of_biggest_in_corner; - mat.diagonal().tail(size-k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); + mat.diagonal().tail(size - k).cwiseAbs().maxCoeff(&index_of_biggest_in_corner); index_of_biggest_in_corner += k; - transpositions.coeffRef(k) = index_of_biggest_in_corner; - if(k != index_of_biggest_in_corner) - { + transpositions.coeffRef(k) = IndexType(index_of_biggest_in_corner); + if (k != index_of_biggest_in_corner) { // apply the transposition while taking care to consider only // the lower triangular part - Index s = size-index_of_biggest_in_corner-1; // trailing size after the biggest element + Index s = size - index_of_biggest_in_corner - 1; // trailing size after the biggest element mat.row(k).head(k).swap(mat.row(index_of_biggest_in_corner).head(k)); mat.col(k).tail(s).swap(mat.col(index_of_biggest_in_corner).tail(s)); - std::swap(mat.coeffRef(k,k),mat.coeffRef(index_of_biggest_in_corner,index_of_biggest_in_corner)); - for(int i=k+1;i::IsComplex) - mat.coeffRef(index_of_biggest_in_corner,k) = numext::conj(mat.coeff(index_of_biggest_in_corner,k)); + if (NumTraits::IsComplex) + mat.coeffRef(index_of_biggest_in_corner, k) = numext::conj(mat.coeff(index_of_biggest_in_corner, k)); } // partition the matrix: @@ -310,37 +328,57 @@ template<> struct ldlt_inplace // lu = A10 | A11 | - // A20 | A21 | A22 Index rs = size - k - 1; - Block A21(mat,k+1,k,rs,1); - Block A10(mat,k,0,1,k); - Block A20(mat,k+1,0,rs,k); + Block A21(mat, k + 1, k, rs, 1); + Block A10(mat, k, 0, 1, k); + Block A20(mat, k + 1, 0, rs, k); - if(k>0) - { + if (k > 0) { temp.head(k) = mat.diagonal().real().head(k).asDiagonal() * A10.adjoint(); - mat.coeffRef(k,k) -= (A10 * temp.head(k)).value(); - if(rs>0) - A21.noalias() -= A20 * temp.head(k); + mat.coeffRef(k, k) -= (A10 * temp.head(k)).value(); + if (rs > 0) A21.noalias() -= A20 * temp.head(k); } - + // In some previous versions of Eigen (e.g., 3.2.1), the scaling was omitted if the pivot - // was smaller than the cutoff value. However, soince LDLT is not rank-revealing - // we should only make sure we do not introduce INF or NaN values. - // LAPACK also uses 0 as the cutoff value. - RealScalar realAkk = numext::real(mat.coeffRef(k,k)); - if((rs>0) && (abs(realAkk) > RealScalar(0))) + // was smaller than the cutoff value. However, since LDLT is not rank-revealing + // we should only make sure that we do not introduce INF or NaN values. + // Remark that LAPACK also uses 0 as the cutoff value. + RealScalar realAkk = numext::real(mat.coeffRef(k, k)); + bool pivot_is_valid = (abs(realAkk) > RealScalar(0)); + + if (k == 0 && !pivot_is_valid) { + // The entire diagonal is zero, there is nothing more to do + // except filling the transpositions, and checking whether the matrix is zero. + sign = ZeroSign; + for (Index j = 0; j < size; ++j) { + transpositions.coeffRef(j) = IndexType(j); + ret = ret && (mat.col(j).tail(size - j - 1).array() == Scalar(0)).all(); + } + return ret; + } + + if ((rs > 0) && pivot_is_valid) A21 /= realAkk; + else if (rs > 0) + ret = ret && (A21.array() == Scalar(0)).all(); + + if (found_zero_pivot && pivot_is_valid) + ret = false; // factorization failed + else if (!pivot_is_valid) + found_zero_pivot = true; if (sign == PositiveSemiDef) { - if (realAkk < 0) sign = Indefinite; + if (realAkk < static_cast(0)) sign = Indefinite; } else if (sign == NegativeSemiDef) { - if (realAkk > 0) sign = Indefinite; + if (realAkk > static_cast(0)) sign = Indefinite; } else if (sign == ZeroSign) { - if (realAkk > 0) sign = PositiveSemiDef; - else if (realAkk < 0) sign = NegativeSemiDef; + if (realAkk > static_cast(0)) + sign = PositiveSemiDef; + else if (realAkk < static_cast(0)) + sign = NegativeSemiDef; } } - return true; + return ret; } // Reference for the algorithm: Davis and Hager, "Multiple Rank @@ -350,108 +388,116 @@ template<> struct ldlt_inplace // original matrix is not of full rank. // Here only rank-1 updates are implemented, to reduce the // requirement for intermediate storage and improve accuracy - template - static bool updateInPlace(MatrixType& mat, MatrixBase& w, const typename MatrixType::RealScalar& sigma=1) - { + template + static bool updateInPlace(MatrixType& mat, MatrixBase& w, + const typename MatrixType::RealScalar& sigma = 1) { using numext::isfinite; typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; - typedef typename MatrixType::Index Index; const Index size = mat.rows(); - eigen_assert(mat.cols() == size && w.size()==size); + eigen_assert(mat.cols() == size && w.size() == size); RealScalar alpha = 1; // Apply the update - for (Index j = 0; j < size; j++) - { + for (Index j = 0; j < size; j++) { // Check for termination due to an original decomposition of low-rank - if (!(isfinite)(alpha)) - break; + if (!(isfinite)(alpha)) break; // Update the diagonal terms - RealScalar dj = numext::real(mat.coeff(j,j)); + RealScalar dj = numext::real(mat.coeff(j, j)); Scalar wj = w.coeff(j); - RealScalar swj2 = sigma*numext::abs2(wj); - RealScalar gamma = dj*alpha + swj2; - - mat.coeffRef(j,j) += swj2/alpha; - alpha += swj2/dj; + RealScalar swj2 = sigma * numext::abs2(wj); + RealScalar gamma = dj * alpha + swj2; + mat.coeffRef(j, j) += swj2 / alpha; + alpha += swj2 / dj; // Update the terms of L - Index rs = size-j-1; + Index rs = size - j - 1; w.tail(rs) -= wj * mat.col(j).tail(rs); - if(gamma != 0) - mat.col(j).tail(rs) += (sigma*numext::conj(wj)/gamma)*w.tail(rs); + if (!numext::is_exactly_zero(gamma)) mat.col(j).tail(rs) += (sigma * numext::conj(wj) / gamma) * w.tail(rs); } return true; } - template - static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, const typename MatrixType::RealScalar& sigma=1) - { + template + static bool update(MatrixType& mat, const TranspositionType& transpositions, Workspace& tmp, const WType& w, + const typename MatrixType::RealScalar& sigma = 1) { // Apply the permutation to the input w tmp = transpositions * w; - return ldlt_inplace::updateInPlace(mat,tmp,sigma); + return ldlt_inplace::updateInPlace(mat, tmp, sigma); } }; -template<> struct ldlt_inplace -{ - template - static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, SignMatrix& sign) - { +template <> +struct ldlt_inplace { + template + static EIGEN_STRONG_INLINE bool unblocked(MatrixType& mat, TranspositionType& transpositions, Workspace& temp, + SignMatrix& sign) { Transpose matt(mat); return ldlt_inplace::unblocked(matt, transpositions, temp, sign); } - template - static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, const typename MatrixType::RealScalar& sigma=1) - { + template + static EIGEN_STRONG_INLINE bool update(MatrixType& mat, TranspositionType& transpositions, Workspace& tmp, WType& w, + const typename MatrixType::RealScalar& sigma = 1) { Transpose matt(mat); return ldlt_inplace::update(matt, transpositions, tmp, w.conjugate(), sigma); } }; -template struct LDLT_Traits -{ +template +struct LDLT_Traits { typedef const TriangularView MatrixL; typedef const TriangularView MatrixU; - static inline MatrixL getL(const MatrixType& m) { return m; } - static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } + static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); } + static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); } }; -template struct LDLT_Traits -{ +template +struct LDLT_Traits { typedef const TriangularView MatrixL; typedef const TriangularView MatrixU; - static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); } - static inline MatrixU getU(const MatrixType& m) { return m; } + static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); } + static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); } }; -} // end namespace internal +} // end namespace internal /** Compute / recompute the LDLT decomposition A = L D L^* = U^* D U of \a matrix - */ -template -LDLT& LDLT::compute(const MatrixType& a) -{ - check_template_parameters(); - - eigen_assert(a.rows()==a.cols()); + */ +template +template +LDLT& LDLT::compute(const EigenBase& a) { + eigen_assert(a.rows() == a.cols()); const Index size = a.rows(); - m_matrix = a; + m_matrix = a.derived(); + + // Compute matrix L1 norm = max abs column sum. + m_l1_norm = RealScalar(0); + // TODO move this code to SelfAdjointView + for (Index col = 0; col < size; ++col) { + RealScalar abs_col_sum; + if (UpLo_ == Lower) + abs_col_sum = + m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); + else + abs_col_sum = + m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>(); + if (abs_col_sum > m_l1_norm) m_l1_norm = abs_col_sum; + } m_transpositions.resize(size); m_isInitialized = false; m_temporary.resize(size); m_sign = internal::ZeroSign; - internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign); + m_info = internal::ldlt_inplace::unblocked(m_matrix, m_transpositions, m_temporary, m_sign) ? Success + : NumericalIssue; m_isInitialized = true; return *this; @@ -459,27 +505,24 @@ LDLT& LDLT::compute(const MatrixType& a) /** Update the LDLT decomposition: given A = L D L^T, efficiently compute the decomposition of A + sigma w w^T. * \param w a vector to be incorporated into the decomposition. - * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column vectors. Optional; default value is +1. - * \sa setZero() - */ -template -template -LDLT& LDLT::rankUpdate(const MatrixBase& w, const typename LDLT::RealScalar& sigma) -{ + * \param sigma a scalar, +1 for updates and -1 for "downdates," which correspond to removing previously-added column + * vectors. Optional; default value is +1. \sa setZero() + */ +template +template +LDLT& LDLT::rankUpdate( + const MatrixBase& w, const typename LDLT::RealScalar& sigma) { + typedef typename TranspositionType::StorageIndex IndexType; const Index size = w.rows(); - if (m_isInitialized) - { - eigen_assert(m_matrix.rows()==size); - } - else - { - m_matrix.resize(size,size); + if (m_isInitialized) { + eigen_assert(m_matrix.rows() == size); + } else { + m_matrix.resize(size, size); m_matrix.setZero(); m_transpositions.resize(size); - for (Index i = 0; i < size; i++) - m_transpositions.coeffRef(i) = i; + for (Index i = 0; i < size; i++) m_transpositions.coeffRef(i) = IndexType(i); m_temporary.resize(size); - m_sign = sigma>=0 ? internal::PositiveSemiDef : internal::NegativeSemiDef; + m_sign = sigma >= 0 ? internal::PositiveSemiDef : internal::NegativeSemiDef; m_isInitialized = true; } @@ -488,71 +531,68 @@ LDLT& LDLT::rankUpdate(const MatrixBase -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef LDLT<_MatrixType,_UpLo> LDLTType; - EIGEN_MAKE_SOLVE_HELPERS(LDLTType,Rhs) - - template void evalTo(Dest& dst) const - { - eigen_assert(rhs().rows() == dec().matrixLDLT().rows()); - // dst = P b - dst = dec().transpositionsP() * rhs(); - - // dst = L^-1 (P b) - dec().matrixL().solveInPlace(dst); - - // dst = D^-1 (L^-1 P b) - // more precisely, use pseudo-inverse of D (see bug 241) - using std::abs; - using std::max; - typedef typename LDLTType::MatrixType MatrixType; - typedef typename LDLTType::RealScalar RealScalar; - const typename Diagonal::RealReturnType vectorD(dec().vectorD()); - // In some previous versions, tolerance was set to the max of 1/highest and the maximal diagonal entry * epsilon - // as motivated by LAPACK's xGELSS: - // RealScalar tolerance = (max)(vectorD.array().abs().maxCoeff() *NumTraits::epsilon(),RealScalar(1) / NumTraits::highest()); - // However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the highest - // diagonal element is not well justified and to numerical issues in some cases. - // Moreover, Lapack's xSYTRS routines use 0 for the tolerance. - RealScalar tolerance = RealScalar(1) / NumTraits::highest(); - - for (Index i = 0; i < vectorD.size(); ++i) { - if(abs(vectorD(i)) > tolerance) - dst.row(i) /= vectorD(i); - else - dst.row(i).setZero(); - } - - // dst = L^-T (D^-1 L^-1 P b) - dec().matrixU().solveInPlace(dst); +#ifndef EIGEN_PARSED_BY_DOXYGEN +template +template +void LDLT::_solve_impl(const RhsType& rhs, DstType& dst) const { + _solve_impl_transposed(rhs, dst); +} - // dst = P^-1 (L^-T D^-1 L^-1 P b) = A^-1 b - dst = dec().transpositionsP().transpose() * dst; +template +template +void LDLT::_solve_impl_transposed(const RhsType& rhs, DstType& dst) const { + // dst = P b + dst = m_transpositions * rhs; + + // dst = L^-1 (P b) + // dst = L^-*T (P b) + matrixL().template conjugateIf().solveInPlace(dst); + + // dst = D^-* (L^-1 P b) + // dst = D^-1 (L^-*T P b) + // more precisely, use pseudo-inverse of D (see bug 241) + using std::abs; + const typename Diagonal::RealReturnType vecD(vectorD()); + // In some previous versions, tolerance was set to the max of 1/highest (or rather numeric_limits::min()) + // and the maximal diagonal entry * epsilon as motivated by LAPACK's xGELSS: + // RealScalar tolerance = numext::maxi(vecD.array().abs().maxCoeff() * NumTraits::epsilon(),RealScalar(1) + // / NumTraits::highest()); However, LDLT is not rank revealing, and so adjusting the tolerance wrt to the + // highest diagonal element is not well justified and leads to numerical issues in some cases. Moreover, Lapack's + // xSYTRS routines use 0 for the tolerance. Using numeric_limits::min() gives us more robustness to denormals. + RealScalar tolerance = (std::numeric_limits::min)(); + for (Index i = 0; i < vecD.size(); ++i) { + if (abs(vecD(i)) > tolerance) + dst.row(i) /= vecD(i); + else + dst.row(i).setZero(); } -}; + + // dst = L^-* (D^-* L^-1 P b) + // dst = L^-T (D^-1 L^-*T P b) + matrixL().transpose().template conjugateIf().solveInPlace(dst); + + // dst = P^T (L^-* D^-* L^-1 P b) = A^-1 b + // dst = P^-T (L^-T D^-1 L^-*T P b) = A^-1 b + dst = m_transpositions.transpose() * dst; } +#endif /** \internal use x = ldlt_object.solve(x); - * - * This is the \em in-place version of solve(). - * - * \param bAndX represents both the right-hand side matrix b and result x. - * - * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD. - * - * This version avoids a copy when the right hand side matrix b is not - * needed anymore. - * - * \sa LDLT::solve(), MatrixBase::ldlt() - */ -template -template -bool LDLT::solveInPlace(MatrixBase &bAndX) const -{ + * + * This is the \em in-place version of solve(). + * + * \param bAndX represents both the right-hand side matrix b and result x. + * + * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD. + * + * This version avoids a copy when the right hand side matrix b is not + * needed anymore. + * + * \sa LDLT::solve(), MatrixBase::ldlt() + */ +template +template +bool LDLT::solveInPlace(MatrixBase& bAndX) const { eigen_assert(m_isInitialized && "LDLT is not initialized."); eigen_assert(m_matrix.rows() == bAndX.rows()); @@ -564,12 +604,11 @@ bool LDLT::solveInPlace(MatrixBase &bAndX) const /** \returns the matrix represented by the decomposition, * i.e., it returns the product: P^T L D L^* P. * This function is provided for debug purpose. */ -template -MatrixType LDLT::reconstructedMatrix() const -{ +template +MatrixType LDLT::reconstructedMatrix() const { eigen_assert(m_isInitialized && "LDLT is not initialized."); const Index size = m_matrix.rows(); - MatrixType res(size,size); + MatrixType res(size, size); // P res.setIdentity(); @@ -587,25 +626,24 @@ MatrixType LDLT::reconstructedMatrix() const } /** \cholesky_module - * \returns the Cholesky decomposition with full pivoting without square root of \c *this - */ -template + * \returns the Cholesky decomposition with full pivoting without square root of \c *this + * \sa MatrixBase::ldlt() + */ +template inline const LDLT::PlainObject, UpLo> -SelfAdjointView::ldlt() const -{ - return LDLT(m_matrix); +SelfAdjointView::ldlt() const { + return LDLT(m_matrix); } /** \cholesky_module - * \returns the Cholesky decomposition with full pivoting without square root of \c *this - */ -template -inline const LDLT::PlainObject> -MatrixBase::ldlt() const -{ + * \returns the Cholesky decomposition with full pivoting without square root of \c *this + * \sa SelfAdjointView::ldlt() + */ +template +inline const LDLT::PlainObject> MatrixBase::ldlt() const { return LDLT(derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_LDLT_H +#endif // EIGEN_LDLT_H diff --git a/inst/include/Eigen/src/Cholesky/LLT.h b/inst/include/Eigen/src/Cholesky/LLT.h index 7c11a2dc..7fa4fa2a 100644 --- a/inst/include/Eigen/src/Cholesky/LLT.h +++ b/inst/include/Eigen/src/Cholesky/LLT.h @@ -10,392 +10,411 @@ #ifndef EIGEN_LLT_H #define EIGEN_LLT_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -namespace internal{ -template struct LLT_Traits; -} +namespace Eigen { -/** \ingroup Cholesky_Module - * - * \class LLT - * - * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features - * - * \param MatrixType the type of the matrix of which we are computing the LL^T Cholesky decomposition - * \param UpLo the triangular part that will be used for the decompositon: Lower (default) or Upper. - * The other triangular part won't be read. - * - * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite - * matrix A such that A = LL^* = U^*U, where L is lower triangular. - * - * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like D^*D x = b, - * for that purpose, we recommend the Cholesky decomposition without square root which is more stable - * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other - * situations like generalised eigen problems with hermitian matrices. - * - * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive definite matrices, - * use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine whether a system of equations - * has a solution. - * - * Example: \include LLT_example.cpp - * Output: \verbinclude LLT_example.out - * - * \sa MatrixBase::llt(), class LDLT - */ - /* HEY THIS DOX IS DISABLED BECAUSE THERE's A BUG EITHER HERE OR IN LDLT ABOUT THAT (OR BOTH) - * Note that during the decomposition, only the upper triangular part of A is considered. Therefore, - * the strict lower part does not have to store correct values. - */ -template class LLT -{ - public: - typedef _MatrixType MatrixType; - enum { - RowsAtCompileTime = MatrixType::RowsAtCompileTime, - ColsAtCompileTime = MatrixType::ColsAtCompileTime, - Options = MatrixType::Options, - MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime - }; - typedef typename MatrixType::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - typedef typename MatrixType::Index Index; - - enum { - PacketSize = internal::packet_traits::size, - AlignmentMask = int(PacketSize)-1, - UpLo = _UpLo - }; - - typedef internal::LLT_Traits Traits; - - /** - * \brief Default Constructor. - * - * The default constructor is useful in cases in which the user intends to - * perform decompositions via LLT::compute(const MatrixType&). - */ - LLT() : m_matrix(), m_isInitialized(false) {} - - /** \brief Default Constructor with memory preallocation - * - * Like the default constructor but with preallocation of the internal data - * according to the specified problem \a size. - * \sa LLT() - */ - LLT(Index size) : m_matrix(size, size), - m_isInitialized(false) {} - - LLT(const MatrixType& matrix) - : m_matrix(matrix.rows(), matrix.cols()), - m_isInitialized(false) - { - compute(matrix); - } +namespace internal { - /** \returns a view of the upper triangular matrix U */ - inline typename Traits::MatrixU matrixU() const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - return Traits::getU(m_matrix); - } +template +struct traits > : traits { + typedef MatrixXpr XprKind; + typedef SolverStorage StorageKind; + typedef int StorageIndex; + enum { Flags = 0 }; +}; - /** \returns a view of the lower triangular matrix L */ - inline typename Traits::MatrixL matrixL() const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - return Traits::getL(m_matrix); - } +template +struct LLT_Traits; +} // namespace internal - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * Since this LLT class assumes anyway that the matrix A is invertible, the solution - * theoretically exists and is unique regardless of b. - * - * Example: \include LLT_solve.cpp - * Output: \verbinclude LLT_solve.out - * - * \sa solveInPlace(), MatrixBase::llt() - */ - template - inline const internal::solve_retval - solve(const MatrixBase& b) const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - eigen_assert(m_matrix.rows()==b.rows() - && "LLT::solve(): invalid number of rows of the right hand side matrix b"); - return internal::solve_retval(*this, b.derived()); - } +/** \ingroup Cholesky_Module + * + * \class LLT + * + * \brief Standard Cholesky decomposition (LL^T) of a matrix and associated features + * + * \tparam MatrixType_ the type of the matrix of which we are computing the LL^T Cholesky decomposition + * \tparam UpLo_ the triangular part that will be used for the decomposition: Lower (default) or Upper. + * The other triangular part won't be read. + * + * This class performs a LL^T Cholesky decomposition of a symmetric, positive definite + * matrix A such that A = LL^* = U^*U, where L is lower triangular. + * + * While the Cholesky decomposition is particularly useful to solve selfadjoint problems like D^*D x = b, + * for that purpose, we recommend the Cholesky decomposition without square root which is more stable + * and even faster. Nevertheless, this standard Cholesky decomposition remains useful in many other + * situations like generalised eigen problems with hermitian matrices. + * + * Remember that Cholesky decompositions are not rank-revealing. This LLT decomposition is only stable on positive + * definite matrices, use LDLT instead for the semidefinite case. Also, do not use a Cholesky decomposition to determine + * whether a system of equations has a solution. + * + * Example: \include LLT_example.cpp + * Output: \verbinclude LLT_example.out + * + * \b Performance: for best performance, it is recommended to use a column-major storage format + * with the Lower triangular part (the default), or, equivalently, a row-major storage format + * with the Upper triangular part. Otherwise, you might get a 20% slowdown for the full factorization + * step, and rank-updates can be up to 3 times slower. + * + * This class supports the \link InplaceDecomposition inplace decomposition \endlink mechanism. + * + * Note that during the decomposition, only the lower (or upper, as defined by UpLo_) triangular part of A is + * considered. Therefore, the strict lower part does not have to store correct values. + * + * \sa MatrixBase::llt(), SelfAdjointView::llt(), class LDLT + */ +template +class LLT : public SolverBase > { + public: + typedef MatrixType_ MatrixType; + typedef SolverBase Base; + friend class SolverBase; + + EIGEN_GENERIC_PUBLIC_INTERFACE(LLT) + enum { MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime }; + + enum { PacketSize = internal::packet_traits::size, AlignmentMask = int(PacketSize) - 1, UpLo = UpLo_ }; + + typedef internal::LLT_Traits Traits; + + /** + * \brief Default Constructor. + * + * The default constructor is useful in cases in which the user intends to + * perform decompositions via LLT::compute(const MatrixType&). + */ + LLT() : m_matrix(), m_isInitialized(false) {} + + /** \brief Default Constructor with memory preallocation + * + * Like the default constructor but with preallocation of the internal data + * according to the specified problem \a size. + * \sa LLT() + */ + explicit LLT(Index size) : m_matrix(size, size), m_isInitialized(false) {} + + template + explicit LLT(const EigenBase& matrix) : m_matrix(matrix.rows(), matrix.cols()), m_isInitialized(false) { + compute(matrix.derived()); + } - #ifdef EIGEN2_SUPPORT - template - bool solve(const MatrixBase& b, ResultType *result) const - { - *result = this->solve(b); - return true; - } - - bool isPositiveDefinite() const { return true; } - #endif - - template - void solveInPlace(MatrixBase &bAndX) const; - - LLT& compute(const MatrixType& matrix); - - /** \returns the LLT decomposition matrix - * - * TODO: document the storage layout - */ - inline const MatrixType& matrixLLT() const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - return m_matrix; - } + /** \brief Constructs a LLT factorization from a given matrix + * + * This overloaded constructor is provided for \link InplaceDecomposition inplace decomposition \endlink when + * \c MatrixType is a Eigen::Ref. + * + * \sa LLT(const EigenBase&) + */ + template + explicit LLT(EigenBase& matrix) : m_matrix(matrix.derived()), m_isInitialized(false) { + compute(matrix.derived()); + } - MatrixType reconstructedMatrix() const; + /** \returns a view of the upper triangular matrix U */ + inline typename Traits::MatrixU matrixU() const { + eigen_assert(m_isInitialized && "LLT is not initialized."); + return Traits::getU(m_matrix); + } + /** \returns a view of the lower triangular matrix L */ + inline typename Traits::MatrixL matrixL() const { + eigen_assert(m_isInitialized && "LLT is not initialized."); + return Traits::getL(m_matrix); + } - /** \brief Reports whether previous computation was successful. - * - * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. - */ - ComputationInfo info() const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - return m_info; - } +#ifdef EIGEN_PARSED_BY_DOXYGEN + /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. + * + * Since this LLT class assumes anyway that the matrix A is invertible, the solution + * theoretically exists and is unique regardless of b. + * + * Example: \include LLT_solve.cpp + * Output: \verbinclude LLT_solve.out + * + * \sa solveInPlace(), MatrixBase::llt(), SelfAdjointView::llt() + */ + template + inline const Solve solve(const MatrixBase& b) const; +#endif + + template + void solveInPlace(const MatrixBase& bAndX) const; + + template + LLT& compute(const EigenBase& matrix); + + /** \returns an estimate of the reciprocal condition number of the matrix of + * which \c *this is the Cholesky decomposition. + */ + RealScalar rcond() const { + eigen_assert(m_isInitialized && "LLT is not initialized."); + eigen_assert(m_info == Success && "LLT failed because matrix appears to be negative"); + return internal::rcond_estimate_helper(m_l1_norm, *this); + } - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } + /** \returns the LLT decomposition matrix + * + * TODO: document the storage layout + */ + inline const MatrixType& matrixLLT() const { + eigen_assert(m_isInitialized && "LLT is not initialized."); + return m_matrix; + } - template - LLT rankUpdate(const VectorType& vec, const RealScalar& sigma = 1); + MatrixType reconstructedMatrix() const; - protected: - - static void check_template_parameters() - { - EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar); - } - - /** \internal - * Used to compute and store L - * The strict upper part is not used and even not initialized. - */ - MatrixType m_matrix; - bool m_isInitialized; - ComputationInfo m_info; + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was successful, + * \c NumericalIssue if the matrix.appears not to be positive definite. + */ + ComputationInfo info() const { + eigen_assert(m_isInitialized && "LLT is not initialized."); + return m_info; + } + + /** \returns the adjoint of \c *this, that is, a const reference to the decomposition itself as the underlying matrix + * is self-adjoint. + * + * This method is provided for compatibility with other matrix decompositions, thus enabling generic code such as: + * \code x = decomposition.adjoint().solve(b) \endcode + */ + const LLT& adjoint() const noexcept { return *this; } + + constexpr Index rows() const noexcept { return m_matrix.rows(); } + constexpr Index cols() const noexcept { return m_matrix.cols(); } + + template + LLT& rankUpdate(const VectorType& vec, const RealScalar& sigma = 1); + +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + void _solve_impl(const RhsType& rhs, DstType& dst) const; + + template + void _solve_impl_transposed(const RhsType& rhs, DstType& dst) const; +#endif + + protected: + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) + + /** \internal + * Used to compute and store L + * The strict upper part is not used and even not initialized. + */ + MatrixType m_matrix; + RealScalar m_l1_norm; + bool m_isInitialized; + ComputationInfo m_info; }; namespace internal { -template struct llt_inplace; +template +struct llt_inplace; -template -static typename MatrixType::Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) -{ +template +static Index llt_rank_update_lower(MatrixType& mat, const VectorType& vec, + const typename MatrixType::RealScalar& sigma) { using std::sqrt; typedef typename MatrixType::Scalar Scalar; typedef typename MatrixType::RealScalar RealScalar; - typedef typename MatrixType::Index Index; typedef typename MatrixType::ColXpr ColXpr; - typedef typename internal::remove_all::type ColXprCleaned; + typedef internal::remove_all_t ColXprCleaned; typedef typename ColXprCleaned::SegmentReturnType ColXprSegment; - typedef Matrix TempVectorType; + typedef Matrix TempVectorType; typedef typename TempVectorType::SegmentReturnType TempVecSegment; Index n = mat.cols(); - eigen_assert(mat.rows()==n && vec.size()==n); + eigen_assert(mat.rows() == n && vec.size() == n); TempVectorType temp; - if(sigma>0) - { + if (sigma > 0) { // This version is based on Givens rotations. // It is faster than the other one below, but only works for updates, // i.e., for sigma > 0 temp = sqrt(sigma) * vec; - for(Index i=0; i g; - g.makeGivens(mat(i,i), -temp(i), &mat(i,i)); + g.makeGivens(mat(i, i), -temp(i), &mat(i, i)); - Index rs = n-i-1; - if(rs>0) - { + Index rs = n - i - 1; + if (rs > 0) { ColXprSegment x(mat.col(i).tail(rs)); TempVecSegment y(temp.tail(rs)); apply_rotation_in_the_plane(x, y, g); } } - } - else - { + } else { temp = vec; RealScalar beta = 1; - for(Index j=0; j struct llt_inplace -{ +template +struct llt_inplace { typedef typename NumTraits::Real RealScalar; - template - static typename MatrixType::Index unblocked(MatrixType& mat) - { + template + static Index unblocked(MatrixType& mat) { using std::sqrt; - typedef typename MatrixType::Index Index; - - eigen_assert(mat.rows()==mat.cols()); + + eigen_assert(mat.rows() == mat.cols()); const Index size = mat.rows(); - for(Index k = 0; k < size; ++k) - { - Index rs = size-k-1; // remaining size - - Block A21(mat,k+1,k,rs,1); - Block A10(mat,k,0,1,k); - Block A20(mat,k+1,0,rs,k); - - RealScalar x = numext::real(mat.coeff(k,k)); - if (k>0) x -= A10.squaredNorm(); - if (x<=RealScalar(0)) - return k; - mat.coeffRef(k,k) = x = sqrt(x); - if (k>0 && rs>0) A21.noalias() -= A20 * A10.adjoint(); - if (rs>0) A21 /= x; + for (Index k = 0; k < size; ++k) { + Index rs = size - k - 1; // remaining size + + Block A21(mat, k + 1, k, rs, 1); + Block A10(mat, k, 0, 1, k); + Block A20(mat, k + 1, 0, rs, k); + + RealScalar x = numext::real(mat.coeff(k, k)); + if (k > 0) x -= A10.squaredNorm(); + if (x <= RealScalar(0)) return k; + mat.coeffRef(k, k) = x = sqrt(x); + if (k > 0 && rs > 0) A21.noalias() -= A20 * A10.adjoint(); + if (rs > 0) A21 /= x; } return -1; } - template - static typename MatrixType::Index blocked(MatrixType& m) - { - typedef typename MatrixType::Index Index; - eigen_assert(m.rows()==m.cols()); + template + static Index blocked(MatrixType& m) { + eigen_assert(m.rows() == m.cols()); Index size = m.rows(); - if(size<32) - return unblocked(m); + if (size < 32) return unblocked(m); - Index blockSize = size/8; - blockSize = (blockSize/16)*16; - blockSize = (std::min)((std::max)(blockSize,Index(8)), Index(128)); + Index blockSize = size / 8; + blockSize = (blockSize / 16) * 16; + blockSize = (std::min)((std::max)(blockSize, Index(8)), Index(128)); - for (Index k=0; k A11(m,k, k, bs,bs); - Block A21(m,k+bs,k, rs,bs); - Block A22(m,k+bs,k+bs,rs,rs); + Block A11(m, k, k, bs, bs); + Block A21(m, k + bs, k, rs, bs); + Block A22(m, k + bs, k + bs, rs, rs); Index ret; - if((ret=unblocked(A11))>=0) return k+ret; - if(rs>0) A11.adjoint().template triangularView().template solveInPlace(A21); - if(rs>0) A22.template selfadjointView().rankUpdate(A21,-1); // bottleneck + if ((ret = unblocked(A11)) >= 0) return k + ret; + if (rs > 0) A11.adjoint().template triangularView().template solveInPlace(A21); + if (rs > 0) + A22.template selfadjointView().rankUpdate(A21, + typename NumTraits::Literal(-1)); // bottleneck } return -1; } - template - static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) - { + template + static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } }; - -template struct llt_inplace -{ + +template +struct llt_inplace { typedef typename NumTraits::Real RealScalar; - template - static EIGEN_STRONG_INLINE typename MatrixType::Index unblocked(MatrixType& mat) - { + template + static EIGEN_STRONG_INLINE Index unblocked(MatrixType& mat) { Transpose matt(mat); return llt_inplace::unblocked(matt); } - template - static EIGEN_STRONG_INLINE typename MatrixType::Index blocked(MatrixType& mat) - { + template + static EIGEN_STRONG_INLINE Index blocked(MatrixType& mat) { Transpose matt(mat); return llt_inplace::blocked(matt); } - template - static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) - { + template + static Index rankUpdate(MatrixType& mat, const VectorType& vec, const RealScalar& sigma) { Transpose matt(mat); return llt_inplace::rankUpdate(matt, vec.conjugate(), sigma); } }; -template struct LLT_Traits -{ +template +struct LLT_Traits { typedef const TriangularView MatrixL; typedef const TriangularView MatrixU; - static inline MatrixL getL(const MatrixType& m) { return m; } - static inline MatrixU getU(const MatrixType& m) { return m.adjoint(); } - static bool inplace_decomposition(MatrixType& m) - { return llt_inplace::blocked(m)==-1; } + static inline MatrixL getL(const MatrixType& m) { return MatrixL(m); } + static inline MatrixU getU(const MatrixType& m) { return MatrixU(m.adjoint()); } + static bool inplace_decomposition(MatrixType& m) { + return llt_inplace::blocked(m) == -1; + } }; -template struct LLT_Traits -{ +template +struct LLT_Traits { typedef const TriangularView MatrixL; typedef const TriangularView MatrixU; - static inline MatrixL getL(const MatrixType& m) { return m.adjoint(); } - static inline MatrixU getU(const MatrixType& m) { return m; } - static bool inplace_decomposition(MatrixType& m) - { return llt_inplace::blocked(m)==-1; } + static inline MatrixL getL(const MatrixType& m) { return MatrixL(m.adjoint()); } + static inline MatrixU getU(const MatrixType& m) { return MatrixU(m); } + static bool inplace_decomposition(MatrixType& m) { + return llt_inplace::blocked(m) == -1; + } }; -} // end namespace internal +} // end namespace internal /** Computes / recomputes the Cholesky decomposition A = LL^* = U^*U of \a matrix - * - * \returns a reference to *this - * - * Example: \include TutorialLinAlgComputeTwice.cpp - * Output: \verbinclude TutorialLinAlgComputeTwice.out - */ -template -LLT& LLT::compute(const MatrixType& a) -{ - check_template_parameters(); - - eigen_assert(a.rows()==a.cols()); + * + * \returns a reference to *this + * + * Example: \include TutorialLinAlgComputeTwice.cpp + * Output: \verbinclude TutorialLinAlgComputeTwice.out + */ +template +template +LLT& LLT::compute(const EigenBase& a) { + eigen_assert(a.rows() == a.cols()); const Index size = a.rows(); m_matrix.resize(size, size); - m_matrix = a; + if (!internal::is_same_dense(m_matrix, a.derived())) m_matrix = a.derived(); + + // Compute matrix L1 norm = max abs column sum. + m_l1_norm = RealScalar(0); + // TODO move this code to SelfAdjointView + for (Index col = 0; col < size; ++col) { + RealScalar abs_col_sum; + if (UpLo_ == Lower) + abs_col_sum = + m_matrix.col(col).tail(size - col).template lpNorm<1>() + m_matrix.row(col).head(col).template lpNorm<1>(); + else + abs_col_sum = + m_matrix.col(col).head(col).template lpNorm<1>() + m_matrix.row(col).tail(size - col).template lpNorm<1>(); + if (abs_col_sum > m_l1_norm) m_l1_norm = abs_col_sum; + } m_isInitialized = true; bool ok = Traits::inplace_decomposition(m_matrix); @@ -405,60 +424,59 @@ LLT& LLT::compute(const MatrixType& a) } /** Performs a rank one update (or dowdate) of the current decomposition. - * If A = LL^* before the rank one update, - * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector - * of same dimension. - */ -template -template -LLT<_MatrixType,_UpLo> LLT<_MatrixType,_UpLo>::rankUpdate(const VectorType& v, const RealScalar& sigma) -{ + * If A = LL^* before the rank one update, + * then after it we have LL^* = A + sigma * v v^* where \a v must be a vector + * of same dimension. + */ +template +template +LLT& LLT::rankUpdate(const VectorType& v, const RealScalar& sigma) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(VectorType); - eigen_assert(v.size()==m_matrix.cols()); + eigen_assert(v.size() == m_matrix.cols()); eigen_assert(m_isInitialized); - if(internal::llt_inplace::rankUpdate(m_matrix,v,sigma)>=0) + if (internal::llt_inplace::rankUpdate(m_matrix, v, sigma) >= 0) m_info = NumericalIssue; else m_info = Success; return *this; } - -namespace internal { -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef LLT<_MatrixType,UpLo> LLTType; - EIGEN_MAKE_SOLVE_HELPERS(LLTType,Rhs) - - template void evalTo(Dest& dst) const - { - dst = rhs(); - dec().solveInPlace(dst); - } -}; + +#ifndef EIGEN_PARSED_BY_DOXYGEN +template +template +void LLT::_solve_impl(const RhsType& rhs, DstType& dst) const { + _solve_impl_transposed(rhs, dst); +} + +template +template +void LLT::_solve_impl_transposed(const RhsType& rhs, DstType& dst) const { + dst = rhs; + + matrixL().template conjugateIf().solveInPlace(dst); + matrixU().template conjugateIf().solveInPlace(dst); } +#endif /** \internal use x = llt_object.solve(x); - * - * This is the \em in-place version of solve(). - * - * \param bAndX represents both the right-hand side matrix b and result x. - * - * \returns true always! If you need to check for existence of solutions, use another decomposition like LU, QR, or SVD. - * - * This version avoids a copy when the right hand side matrix b is not - * needed anymore. - * - * \sa LLT::solve(), MatrixBase::llt() - */ -template -template -void LLT::solveInPlace(MatrixBase &bAndX) const -{ + * + * This is the \em in-place version of solve(). + * + * \param bAndX represents both the right-hand side matrix b and result x. + * + * This version avoids a copy when the right hand side matrix b is not needed anymore. + * + * \warning The parameter is only marked 'const' to make the C++ compiler accept a temporary expression here. + * This function will const_cast it, so constness isn't honored here. + * + * \sa LLT::solve(), MatrixBase::llt() + */ +template +template +void LLT::solveInPlace(const MatrixBase& bAndX) const { eigen_assert(m_isInitialized && "LLT is not initialized."); - eigen_assert(m_matrix.rows()==bAndX.rows()); + eigen_assert(m_matrix.rows() == bAndX.rows()); matrixL().solveInPlace(bAndX); matrixU().solveInPlace(bAndX); } @@ -466,33 +484,31 @@ void LLT::solveInPlace(MatrixBase &bAndX) const /** \returns the matrix represented by the decomposition, * i.e., it returns the product: L L^*. * This function is provided for debug purpose. */ -template -MatrixType LLT::reconstructedMatrix() const -{ +template +MatrixType LLT::reconstructedMatrix() const { eigen_assert(m_isInitialized && "LLT is not initialized."); return matrixL() * matrixL().adjoint().toDenseMatrix(); } /** \cholesky_module - * \returns the LLT decomposition of \c *this - */ -template -inline const LLT::PlainObject> -MatrixBase::llt() const -{ + * \returns the LLT decomposition of \c *this + * \sa SelfAdjointView::llt() + */ +template +inline const LLT::PlainObject> MatrixBase::llt() const { return LLT(derived()); } /** \cholesky_module - * \returns the LLT decomposition of \c *this - */ -template -inline const LLT::PlainObject, UpLo> -SelfAdjointView::llt() const -{ - return LLT(m_matrix); + * \returns the LLT decomposition of \c *this + * \sa SelfAdjointView::llt() + */ +template +inline const LLT::PlainObject, UpLo> SelfAdjointView::llt() + const { + return LLT(m_matrix); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_LLT_H +#endif // EIGEN_LLT_H diff --git a/inst/include/Eigen/src/Cholesky/LLT_LAPACKE.h b/inst/include/Eigen/src/Cholesky/LLT_LAPACKE.h new file mode 100644 index 00000000..cb55b156 --- /dev/null +++ b/inst/include/Eigen/src/Cholesky/LLT_LAPACKE.h @@ -0,0 +1,124 @@ +/* + Copyright (c) 2011, Intel Corporation. All rights reserved. + + Redistribution and use in source and binary forms, with or without modification, + are permitted provided that the following conditions are met: + + * Redistributions of source code must retain the above copyright notice, this + list of conditions and the following disclaimer. + * Redistributions in binary form must reproduce the above copyright notice, + this list of conditions and the following disclaimer in the documentation + and/or other materials provided with the distribution. + * Neither the name of Intel Corporation nor the names of its contributors may + be used to endorse or promote products derived from this software without + specific prior written permission. + + THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND + ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED + WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE + DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR + ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES + (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; + LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON + ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT + (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS + SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. + + ******************************************************************************** + * Content : Eigen bindings to LAPACKe + * LLt decomposition based on LAPACKE_?potrf function. + ******************************************************************************** +*/ + +#ifndef EIGEN_LLT_LAPACKE_H +#define EIGEN_LLT_LAPACKE_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +namespace lapacke_helpers { +// ------------------------------------------------------------------------------------------------------------------- +// Dispatch for rank update handling upper and lower parts +// ------------------------------------------------------------------------------------------------------------------- + +template +struct rank_update {}; + +template <> +struct rank_update { + template + static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) { + return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); + } +}; + +template <> +struct rank_update { + template + static Index run(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) { + Transpose matt(mat); + return Eigen::internal::llt_rank_update_lower(matt, vec.conjugate(), sigma); + } +}; + +// ------------------------------------------------------------------------------------------------------------------- +// Generic lapacke llt implementation that hands of to the dispatches +// ------------------------------------------------------------------------------------------------------------------- + +template +struct lapacke_llt { + EIGEN_STATIC_ASSERT(((Mode == Lower) || (Mode == Upper)), MODE_MUST_BE_UPPER_OR_LOWER) + template + static Index blocked(MatrixType &m) { + eigen_assert(m.rows() == m.cols()); + if (m.rows() == 0) { + return -1; + } + /* Set up parameters for ?potrf */ + lapack_int size = to_lapack(m.rows()); + lapack_int matrix_order = lapack_storage_of(m); + constexpr char uplo = Mode == Upper ? 'U' : 'L'; + Scalar *a = &(m.coeffRef(0, 0)); + lapack_int lda = to_lapack(m.outerStride()); + + lapack_int info = potrf(matrix_order, uplo, size, to_lapack(a), lda); + info = (info == 0) ? -1 : info > 0 ? info - 1 : size; + return info; + } + + template + static Index rankUpdate(MatrixType &mat, const VectorType &vec, const typename MatrixType::RealScalar &sigma) { + return rank_update::run(mat, vec, sigma); + } +}; +} // namespace lapacke_helpers +// end namespace lapacke_helpers + +/* + * Here, we just put the generic implementation from lapacke_llt into a full specialization of the llt_inplace + * type. By being a full specialization, the versions defined here thus get precedence over the generic implementation + * in LLT.h for double, float and complex double, complex float types. + */ + +#define EIGEN_LAPACKE_LLT(EIGTYPE) \ + template <> \ + struct llt_inplace : public lapacke_helpers::lapacke_llt {}; \ + template <> \ + struct llt_inplace : public lapacke_helpers::lapacke_llt {}; + +EIGEN_LAPACKE_LLT(double) +EIGEN_LAPACKE_LLT(float) +EIGEN_LAPACKE_LLT(std::complex) +EIGEN_LAPACKE_LLT(std::complex) + +#undef EIGEN_LAPACKE_LLT + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_LLT_LAPACKE_H diff --git a/inst/include/Eigen/src/Cholesky/LLT_MKL.h b/inst/include/Eigen/src/Cholesky/LLT_MKL.h deleted file mode 100644 index 66675d74..00000000 --- a/inst/include/Eigen/src/Cholesky/LLT_MKL.h +++ /dev/null @@ -1,102 +0,0 @@ -/* - Copyright (c) 2011, Intel Corporation. All rights reserved. - - Redistribution and use in source and binary forms, with or without modification, - are permitted provided that the following conditions are met: - - * Redistributions of source code must retain the above copyright notice, this - list of conditions and the following disclaimer. - * Redistributions in binary form must reproduce the above copyright notice, - this list of conditions and the following disclaimer in the documentation - and/or other materials provided with the distribution. - * Neither the name of Intel Corporation nor the names of its contributors may - be used to endorse or promote products derived from this software without - specific prior written permission. - - THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND - ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED - WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE - DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR - ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES - (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; - LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON - ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT - (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS - SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. - - ******************************************************************************** - * Content : Eigen bindings to Intel(R) MKL - * LLt decomposition based on LAPACKE_?potrf function. - ******************************************************************************** -*/ - -#ifndef EIGEN_LLT_MKL_H -#define EIGEN_LLT_MKL_H - -#include "Eigen/src/Core/util/MKL_support.h" -#include - -namespace Eigen { - -namespace internal { - -template struct mkl_llt; - -#define EIGEN_MKL_LLT(EIGTYPE, MKLTYPE, MKLPREFIX) \ -template<> struct mkl_llt \ -{ \ - template \ - static inline typename MatrixType::Index potrf(MatrixType& m, char uplo) \ - { \ - lapack_int matrix_order; \ - lapack_int size, lda, info, StorageOrder; \ - EIGTYPE* a; \ - eigen_assert(m.rows()==m.cols()); \ - /* Set up parameters for ?potrf */ \ - size = m.rows(); \ - StorageOrder = MatrixType::Flags&RowMajorBit?RowMajor:ColMajor; \ - matrix_order = StorageOrder==RowMajor ? LAPACK_ROW_MAJOR : LAPACK_COL_MAJOR; \ - a = &(m.coeffRef(0,0)); \ - lda = m.outerStride(); \ -\ - info = LAPACKE_##MKLPREFIX##potrf( matrix_order, uplo, size, (MKLTYPE*)a, lda ); \ - info = (info==0) ? -1 : info>0 ? info-1 : size; \ - return info; \ - } \ -}; \ -template<> struct llt_inplace \ -{ \ - template \ - static typename MatrixType::Index blocked(MatrixType& m) \ - { \ - return mkl_llt::potrf(m, 'L'); \ - } \ - template \ - static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \ - { return Eigen::internal::llt_rank_update_lower(mat, vec, sigma); } \ -}; \ -template<> struct llt_inplace \ -{ \ - template \ - static typename MatrixType::Index blocked(MatrixType& m) \ - { \ - return mkl_llt::potrf(m, 'U'); \ - } \ - template \ - static typename MatrixType::Index rankUpdate(MatrixType& mat, const VectorType& vec, const typename MatrixType::RealScalar& sigma) \ - { \ - Transpose matt(mat); \ - return llt_inplace::rankUpdate(matt, vec.conjugate(), sigma); \ - } \ -}; - -EIGEN_MKL_LLT(double, double, d) -EIGEN_MKL_LLT(float, float, s) -EIGEN_MKL_LLT(dcomplex, MKL_Complex16, z) -EIGEN_MKL_LLT(scomplex, MKL_Complex8, c) - -} // end namespace internal - -} // end namespace Eigen - -#endif // EIGEN_LLT_MKL_H diff --git a/inst/include/Eigen/src/CholmodSupport/CholmodSupport.h b/inst/include/Eigen/src/CholmodSupport/CholmodSupport.h index 99dbe171..d5c39a63 100644 --- a/inst/include/Eigen/src/CholmodSupport/CholmodSupport.h +++ b/inst/include/Eigen/src/CholmodSupport/CholmodSupport.h @@ -10,598 +10,725 @@ #ifndef EIGEN_CHOLMODSUPPORT_H #define EIGEN_CHOLMODSUPPORT_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +#ifndef R_MATRIX_CHOLMOD +# define R_MATRIX_CHOLMOD(_NAME_) cholmod_ ## _NAME_ +#endif + +namespace Eigen { namespace internal { -template -void cholmod_configure_matrix(CholmodType& mat) -{ - if (internal::is_same::value) - { - mat.xtype = CHOLMOD_REAL; - mat.dtype = CHOLMOD_SINGLE; - } - else if (internal::is_same::value) - { +template +struct cholmod_configure_matrix; + +template <> +struct cholmod_configure_matrix { + template + static void run(CholmodType& mat) { mat.xtype = CHOLMOD_REAL; mat.dtype = CHOLMOD_DOUBLE; } - else if (internal::is_same >::value) - { - mat.xtype = CHOLMOD_COMPLEX; - mat.dtype = CHOLMOD_SINGLE; - } - else if (internal::is_same >::value) - { +}; + +template <> +struct cholmod_configure_matrix > { + template + static void run(CholmodType& mat) { mat.xtype = CHOLMOD_COMPLEX; mat.dtype = CHOLMOD_DOUBLE; } - else - { - eigen_assert(false && "Scalar type not supported by CHOLMOD"); - } -} +}; + +// Other scalar types are not yet supported by Cholmod +// template<> struct cholmod_configure_matrix { +// template +// static void run(CholmodType& mat) { +// mat.xtype = CHOLMOD_REAL; +// mat.dtype = CHOLMOD_SINGLE; +// } +// }; +// +// template<> struct cholmod_configure_matrix > { +// template +// static void run(CholmodType& mat) { +// mat.xtype = CHOLMOD_COMPLEX; +// mat.dtype = CHOLMOD_SINGLE; +// } +// }; -} // namespace internal +} // namespace internal /** Wraps the Eigen sparse matrix \a mat into a Cholmod sparse matrix object. - * Note that the data are shared. - */ -template -cholmod_sparse viewAsCholmod(SparseMatrix<_Scalar,_Options,_Index>& mat) -{ + * Note that the data are shared. + */ +template +cholmod_sparse viewAsCholmod(Ref > mat) { cholmod_sparse res; - res.nzmax = mat.nonZeros(); - res.nrow = mat.rows();; - res.ncol = mat.cols(); - res.p = mat.outerIndexPtr(); - res.i = mat.innerIndexPtr(); - res.x = mat.valuePtr(); - res.z = 0; - res.sorted = 1; - if(mat.isCompressed()) - { - res.packed = 1; + res.nzmax = mat.nonZeros(); + res.nrow = mat.rows(); + res.ncol = mat.cols(); + res.p = mat.outerIndexPtr(); + res.i = mat.innerIndexPtr(); + res.x = mat.valuePtr(); + res.z = 0; + res.sorted = 1; + if (mat.isCompressed()) { + res.packed = 1; res.nz = 0; - } - else - { - res.packed = 0; + } else { + res.packed = 0; res.nz = mat.innerNonZeroPtr(); } - res.dtype = 0; - res.stype = -1; - - if (internal::is_same<_Index,int>::value) - { + res.dtype = 0; + res.stype = -1; + + if (internal::is_same::value) { res.itype = CHOLMOD_INT; - } - else if (internal::is_same<_Index,SuiteSparse_long>::value) - { - res.itype = CHOLMOD_LONG; - } - else - { + // } else if (internal::is_same::value) { + // res.itype = CHOLMOD_LONG; + } else { eigen_assert(false && "Index type not supported yet"); } // setup res.xtype - internal::cholmod_configure_matrix<_Scalar>(res); - + internal::cholmod_configure_matrix::run(res); + res.stype = 0; - + + return res; +} + +template +const cholmod_sparse viewAsCholmod(const SparseMatrix& mat) { + cholmod_sparse res = viewAsCholmod(Ref >(mat.const_cast_derived())); return res; } -template -const cholmod_sparse viewAsCholmod(const SparseMatrix<_Scalar,_Options,_Index>& mat) -{ - cholmod_sparse res = viewAsCholmod(mat.const_cast_derived()); +template +const cholmod_sparse viewAsCholmod(const SparseVector& mat) { + cholmod_sparse res = viewAsCholmod(Ref >(mat.const_cast_derived())); return res; } /** Returns a view of the Eigen sparse matrix \a mat as Cholmod sparse matrix. - * The data are not copied but shared. */ -template -cholmod_sparse viewAsCholmod(const SparseSelfAdjointView, UpLo>& mat) -{ - cholmod_sparse res = viewAsCholmod(mat.matrix().const_cast_derived()); - - if(UpLo==Upper) res.stype = 1; - if(UpLo==Lower) res.stype = -1; + * The data are not copied but shared. */ +template +cholmod_sparse viewAsCholmod(const SparseSelfAdjointView, UpLo>& mat) { + cholmod_sparse res = viewAsCholmod(Ref >(mat.matrix().const_cast_derived())); + + if (UpLo == Upper) res.stype = 1; + if (UpLo == Lower) res.stype = -1; + // swap stype for rowmajor matrices (only works for real matrices) + EIGEN_STATIC_ASSERT((Options_ & RowMajorBit) == 0 || NumTraits::IsComplex == 0, + THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); + if (Options_ & RowMajorBit) res.stype *= -1; return res; } /** Returns a view of the Eigen \b dense matrix \a mat as Cholmod dense matrix. - * The data are not copied but shared. */ -template -cholmod_dense viewAsCholmod(MatrixBase& mat) -{ - EIGEN_STATIC_ASSERT((internal::traits::Flags&RowMajorBit)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); + * The data are not copied but shared. */ +template +cholmod_dense viewAsCholmod(MatrixBase& mat) { + EIGEN_STATIC_ASSERT((internal::traits::Flags & RowMajorBit) == 0, + THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); typedef typename Derived::Scalar Scalar; cholmod_dense res; - res.nrow = mat.rows(); - res.ncol = mat.cols(); - res.nzmax = res.nrow * res.ncol; - res.d = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride(); - res.x = (void*)(mat.derived().data()); - res.z = 0; + res.nrow = mat.rows(); + res.ncol = mat.cols(); + res.nzmax = res.nrow * res.ncol; + res.d = Derived::IsVectorAtCompileTime ? mat.derived().size() : mat.derived().outerStride(); + res.x = (void*)(mat.derived().data()); + res.z = 0; - internal::cholmod_configure_matrix(res); + internal::cholmod_configure_matrix::run(res); return res; } /** Returns a view of the Cholmod sparse matrix \a cm as an Eigen sparse matrix. - * The data are not copied but shared. */ -template -MappedSparseMatrix viewAsEigen(cholmod_sparse& cm) -{ - return MappedSparseMatrix - (cm.nrow, cm.ncol, static_cast(cm.p)[cm.ncol], - static_cast(cm.p), static_cast(cm.i),static_cast(cm.x) ); + * The data are not copied but shared. */ +template +Map > viewAsEigen(cholmod_sparse& cm) { + return Map >( + cm.nrow, cm.ncol, static_cast(cm.p)[cm.ncol], static_cast(cm.p), + static_cast(cm.i), static_cast(cm.x)); } -enum CholmodMode { - CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt -}; +/** Returns a view of the Cholmod sparse matrix factor \a cm as an Eigen sparse matrix. + * The data are not copied but shared. */ +template +Map > viewAsEigen(cholmod_factor& cm) { + return Map >( + cm.n, cm.n, static_cast(cm.p)[cm.n], static_cast(cm.p), + static_cast(cm.i), static_cast(cm.x)); +} +namespace internal { + +// template specializations for int and long that call the correct cholmod method + +#define EIGEN_CHOLMOD_SPECIALIZE0(ret, name) \ + template \ + inline ret cm_##name(cholmod_common& Common) { \ + return R_MATRIX_CHOLMOD(name)(&Common); \ + } + +#define EIGEN_CHOLMOD_SPECIALIZE1(ret, name, t1, a1) \ + template \ + inline ret cm_##name(t1& a1, cholmod_common& Common) { \ + return R_MATRIX_CHOLMOD(name) (&a1, &Common); \ + } + +EIGEN_CHOLMOD_SPECIALIZE0(int, start) +EIGEN_CHOLMOD_SPECIALIZE0(int, finish) + +EIGEN_CHOLMOD_SPECIALIZE1(int, free_factor, cholmod_factor*, L) +EIGEN_CHOLMOD_SPECIALIZE1(int, free_dense, cholmod_dense*, X) +EIGEN_CHOLMOD_SPECIALIZE1(int, free_sparse, cholmod_sparse*, A) + +EIGEN_CHOLMOD_SPECIALIZE1(cholmod_factor*, analyze, cholmod_sparse, A) +EIGEN_CHOLMOD_SPECIALIZE1(cholmod_sparse*, factor_to_sparse, cholmod_factor, L) + +template +inline cholmod_dense* cm_solve(int sys, cholmod_factor& L, cholmod_dense& B, cholmod_common& Common) { + return R_MATRIX_CHOLMOD(solve) (sys, &L, &B, &Common); +} +// template <> +// inline cholmod_dense* cm_solve(int sys, cholmod_factor& L, cholmod_dense& B, cholmod_common& Common) { +// return cholmod_l_solve(sys, &L, &B, &Common); +// } + +template +inline cholmod_sparse* cm_spsolve(int sys, cholmod_factor& L, cholmod_sparse& B, cholmod_common& Common) { + return R_MATRIX_CHOLMOD(spsolve) (sys, &L, &B, &Common); +} +// template <> +// inline cholmod_sparse* cm_spsolve(int sys, cholmod_factor& L, cholmod_sparse& B, +// cholmod_common& Common) { +// return cholmod_l_spsolve(sys, &L, &B, &Common); +// } + +template +inline int cm_factorize_p(cholmod_sparse* A, double beta[2], StorageIndex_* fset, std::size_t fsize, cholmod_factor* L, + cholmod_common& Common) { + return R_MATRIX_CHOLMOD(factorize_p) (A, beta, fset, fsize, L, &Common); +} +// template <> +// inline int cm_factorize_p(cholmod_sparse* A, double beta[2], SuiteSparse_long* fset, +// std::size_t fsize, cholmod_factor* L, cholmod_common& Common) { +// return cholmod_l_factorize_p(A, beta, fset, fsize, L, &Common); +// } + +#undef EIGEN_CHOLMOD_SPECIALIZE0 +#undef EIGEN_CHOLMOD_SPECIALIZE1 + +} // namespace internal + +enum CholmodMode { CholmodAuto, CholmodSimplicialLLt, CholmodSupernodalLLt, CholmodLDLt }; /** \ingroup CholmodSupport_Module - * \class CholmodBase - * \brief The base class for the direct Cholesky factorization of Cholmod - * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT - */ -template -class CholmodBase : internal::noncopyable -{ - public: - typedef _MatrixType MatrixType; - enum { UpLo = _UpLo }; - typedef typename MatrixType::Scalar Scalar; - typedef typename MatrixType::RealScalar RealScalar; - typedef MatrixType CholMatrixType; - typedef typename MatrixType::Index Index; - - public: - - CholmodBase() - : m_cholmodFactor(0), m_info(Success), m_isInitialized(false) - { - m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0); - cholmod_start(&m_cholmod); - } + * \class CholmodBase + * \brief The base class for the direct Cholesky factorization of Cholmod + * \sa class CholmodSupernodalLLT, class CholmodSimplicialLDLT, class CholmodSimplicialLLT + */ +template +class CholmodBase : public SparseSolverBase { + protected: + typedef SparseSolverBase Base; + using Base::derived; + using Base::m_isInitialized; + + public: + typedef MatrixType_ MatrixType; + enum { UpLo = UpLo_ }; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef MatrixType CholMatrixType; + typedef typename MatrixType::StorageIndex StorageIndex; + enum { ColsAtCompileTime = MatrixType::ColsAtCompileTime, MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime }; + + public: + CholmodBase() : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false) { + EIGEN_STATIC_ASSERT((internal::is_same::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY); + m_shiftOffset[0] = m_shiftOffset[1] = 0.0; + internal::cm_start(m_cholmod); + } - CholmodBase(const MatrixType& matrix) - : m_cholmodFactor(0), m_info(Success), m_isInitialized(false) - { - m_shiftOffset[0] = m_shiftOffset[1] = RealScalar(0.0); - cholmod_start(&m_cholmod); - compute(matrix); - } + explicit CholmodBase(const MatrixType& matrix) + : m_cholmodFactor(0), m_info(Success), m_factorizationIsOk(false), m_analysisIsOk(false) { + EIGEN_STATIC_ASSERT((internal::is_same::value), CHOLMOD_SUPPORTS_DOUBLE_PRECISION_ONLY); + m_shiftOffset[0] = m_shiftOffset[1] = 0.0; + internal::cm_start(m_cholmod); + compute(matrix); + } - ~CholmodBase() - { - if(m_cholmodFactor) - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - cholmod_finish(&m_cholmod); - } - - inline Index cols() const { return m_cholmodFactor->n; } - inline Index rows() const { return m_cholmodFactor->n; } - - Derived& derived() { return *static_cast(this); } - const Derived& derived() const { return *static_cast(this); } - - /** \brief Reports whether previous computation was successful. - * - * \returns \c Success if computation was succesful, - * \c NumericalIssue if the matrix.appears to be negative. - */ - ComputationInfo info() const - { - eigen_assert(m_isInitialized && "Decomposition is not initialized."); - return m_info; - } + ~CholmodBase() { + if (m_cholmodFactor) internal::cm_free_factor(m_cholmodFactor, m_cholmod); + internal::cm_finish(m_cholmod); + } - /** Computes the sparse Cholesky decomposition of \a matrix */ - Derived& compute(const MatrixType& matrix) - { - analyzePattern(matrix); - factorize(matrix); - return derived(); - } - - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * \sa compute() - */ - template - inline const internal::solve_retval - solve(const MatrixBase& b) const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - eigen_assert(rows()==b.rows() - && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b"); - return internal::solve_retval(*this, b.derived()); - } - - /** \returns the solution x of \f$ A x = b \f$ using the current decomposition of A. - * - * \sa compute() - */ - template - inline const internal::sparse_solve_retval - solve(const SparseMatrixBase& b) const - { - eigen_assert(m_isInitialized && "LLT is not initialized."); - eigen_assert(rows()==b.rows() - && "CholmodDecomposition::solve(): invalid number of rows of the right hand side matrix b"); - return internal::sparse_solve_retval(*this, b.derived()); - } - - /** Performs a symbolic decomposition on the sparsity pattern of \a matrix. - * - * This function is particularly useful when solving for several problems having the same structure. - * - * \sa factorize() - */ - void analyzePattern(const MatrixType& matrix) - { - if(m_cholmodFactor) - { - cholmod_free_factor(&m_cholmodFactor, &m_cholmod); - m_cholmodFactor = 0; - } - cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView()); - m_cholmodFactor = cholmod_analyze(&A, &m_cholmod); - - this->m_isInitialized = true; - this->m_info = Success; - m_analysisIsOk = true; - m_factorizationIsOk = false; + inline StorageIndex cols() const { return internal::convert_index(m_cholmodFactor->n); } + inline StorageIndex rows() const { return internal::convert_index(m_cholmodFactor->n); } + + /** \brief Reports whether previous computation was successful. + * + * \returns \c Success if computation was successful, + * \c NumericalIssue if the matrix.appears to be negative. + */ + ComputationInfo info() const { + eigen_assert(m_isInitialized && "Decomposition is not initialized."); + return m_info; + } + + /** Computes the sparse Cholesky decomposition of \a matrix */ + Derived& compute(const MatrixType& matrix) { + analyzePattern(matrix); + factorize(matrix); + return derived(); + } + + /** Performs a symbolic decomposition on the sparsity pattern of \a matrix. + * + * This function is particularly useful when solving for several problems having the same structure. + * + * \sa factorize() + */ + void analyzePattern(const MatrixType& matrix) { + if (m_cholmodFactor) { + internal::cm_free_factor(m_cholmodFactor, m_cholmod); + m_cholmodFactor = 0; } - - /** Performs a numeric decomposition of \a matrix - * - * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been performed. - * - * \sa analyzePattern() - */ - void factorize(const MatrixType& matrix) - { - eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); - cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView()); - cholmod_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, &m_cholmod); - - // If the factorization failed, minor is the column at which it did. On success minor == n. - this->m_info = (m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue); - m_factorizationIsOk = true; + cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView()); + m_cholmodFactor = internal::cm_analyze(A, m_cholmod); + + this->m_isInitialized = true; + this->m_info = Success; + m_analysisIsOk = true; + m_factorizationIsOk = false; + } + + /** Performs a numeric decomposition of \a matrix + * + * The given matrix must have the same sparsity pattern as the matrix on which the symbolic decomposition has been + * performed. + * + * \sa analyzePattern() + */ + void factorize(const MatrixType& matrix) { + eigen_assert(m_analysisIsOk && "You must first call analyzePattern()"); + cholmod_sparse A = viewAsCholmod(matrix.template selfadjointView()); + internal::cm_factorize_p(&A, m_shiftOffset, 0, 0, m_cholmodFactor, m_cholmod); + + // If the factorization failed, either the input matrix was zero (so m_cholmodFactor == nullptr), or minor is the + // column at which it failed. On success minor == n. + this->m_info = + (m_cholmodFactor != nullptr && m_cholmodFactor->minor == m_cholmodFactor->n ? Success : NumericalIssue); + m_factorizationIsOk = true; + } + + /** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations. + * See the Cholmod user guide for details. */ + cholmod_common& cholmod() { return m_cholmod; } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal */ + template + void _solve_impl(const MatrixBase& b, MatrixBase& dest) const { + eigen_assert(m_factorizationIsOk && + "The decomposition is not in a valid state for solving, you must first call either compute() or " + "symbolic()/numeric()"); + const Index size = m_cholmodFactor->n; + EIGEN_UNUSED_VARIABLE(size); + eigen_assert(size == b.rows()); + + // Cholmod needs column-major storage without inner-stride, which corresponds to the default behavior of Ref. + Ref > b_ref(b.derived()); + + cholmod_dense b_cd = viewAsCholmod(b_ref); + cholmod_dense* x_cd = internal::cm_solve(CHOLMOD_A, *m_cholmodFactor, b_cd, m_cholmod); + if (!x_cd) { + this->m_info = NumericalIssue; + return; } - - /** Returns a reference to the Cholmod's configuration structure to get a full control over the performed operations. - * See the Cholmod user guide for details. */ - cholmod_common& cholmod() { return m_cholmod; } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** \internal */ - template - void _solve(const MatrixBase &b, MatrixBase &dest) const - { - eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); - const Index size = m_cholmodFactor->n; - EIGEN_UNUSED_VARIABLE(size); - eigen_assert(size==b.rows()); - - // note: cd stands for Cholmod Dense - Rhs& b_ref(b.const_cast_derived()); - cholmod_dense b_cd = viewAsCholmod(b_ref); - cholmod_dense* x_cd = cholmod_solve(CHOLMOD_A, m_cholmodFactor, &b_cd, &m_cholmod); - if(!x_cd) - { - this->m_info = NumericalIssue; - } - // TODO optimize this copy by swapping when possible (be careful with alignment, etc.) - dest = Matrix::Map(reinterpret_cast(x_cd->x),b.rows(),b.cols()); - cholmod_free_dense(&x_cd, &m_cholmod); + // TODO optimize this copy by swapping when possible (be careful with alignment, etc.) + // NOTE Actually, the copy can be avoided by calling cholmod_solve2 instead of cholmod_solve + dest = Matrix::Map(reinterpret_cast(x_cd->x), + b.rows(), b.cols()); + internal::cm_free_dense(x_cd, m_cholmod); + } + + /** \internal */ + template + void _solve_impl(const SparseMatrixBase& b, SparseMatrixBase& dest) const { + eigen_assert(m_factorizationIsOk && + "The decomposition is not in a valid state for solving, you must first call either compute() or " + "symbolic()/numeric()"); + const Index size = m_cholmodFactor->n; + EIGEN_UNUSED_VARIABLE(size); + eigen_assert(size == b.rows()); + + // note: cs stands for Cholmod Sparse + Ref > b_ref( + b.const_cast_derived()); + cholmod_sparse b_cs = viewAsCholmod(b_ref); + cholmod_sparse* x_cs = internal::cm_spsolve(CHOLMOD_A, *m_cholmodFactor, b_cs, m_cholmod); + if (!x_cs) { + this->m_info = NumericalIssue; + return; } - - /** \internal */ - template - void _solve(const SparseMatrix &b, SparseMatrix &dest) const - { - eigen_assert(m_factorizationIsOk && "The decomposition is not in a valid state for solving, you must first call either compute() or symbolic()/numeric()"); - const Index size = m_cholmodFactor->n; - EIGEN_UNUSED_VARIABLE(size); - eigen_assert(size==b.rows()); - - // note: cs stands for Cholmod Sparse - cholmod_sparse b_cs = viewAsCholmod(b); - cholmod_sparse* x_cs = cholmod_spsolve(CHOLMOD_A, m_cholmodFactor, &b_cs, &m_cholmod); - if(!x_cs) - { - this->m_info = NumericalIssue; + // TODO optimize this copy by swapping when possible (be careful with alignment, etc.) + // NOTE cholmod_spsolve in fact just calls the dense solver for blocks of 4 columns at a time (similar to Eigen's + // sparse solver) + dest.derived() = viewAsEigen(*x_cs); + internal::cm_free_sparse(x_cs, m_cholmod); + } +#endif // EIGEN_PARSED_BY_DOXYGEN + + /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization. + * + * During the numerical factorization, an offset term is added to the diagonal coefficients:\n + * \c d_ii = \a offset + \c d_ii + * + * The default is \a offset=0. + * + * \returns a reference to \c *this. + */ + Derived& setShift(const RealScalar& offset) { + m_shiftOffset[0] = double(offset); + return derived(); + } + + /** \returns the determinant of the underlying matrix from the current factorization */ + Scalar determinant() const { + using std::exp; + return exp(logDeterminant()); + } + + /** \returns the log determinant of the underlying matrix from the current factorization */ + Scalar logDeterminant() const { + using numext::real; + using std::log; + eigen_assert(m_factorizationIsOk && + "The decomposition is not in a valid state for solving, you must first call either compute() or " + "symbolic()/numeric()"); + + RealScalar logDet = 0; + Scalar* x = static_cast(m_cholmodFactor->x); + if (m_cholmodFactor->is_super) { + // Supernodal factorization stored as a packed list of dense column-major blocks, + // as described by the following structure: + + // super[k] == index of the first column of the j-th super node + StorageIndex* super = static_cast(m_cholmodFactor->super); + // pi[k] == offset to the description of row indices + StorageIndex* pi = static_cast(m_cholmodFactor->pi); + // px[k] == offset to the respective dense block + StorageIndex* px = static_cast(m_cholmodFactor->px); + + Index nb_super_nodes = m_cholmodFactor->nsuper; + for (Index k = 0; k < nb_super_nodes; ++k) { + StorageIndex ncols = super[k + 1] - super[k]; + StorageIndex nrows = pi[k + 1] - pi[k]; + + Map, 0, InnerStride<> > sk(x + px[k], ncols, InnerStride<>(nrows + 1)); + logDet += sk.real().log().sum(); } - // TODO optimize this copy by swapping when possible (be careful with alignment, etc.) - dest = viewAsEigen(*x_cs); - cholmod_free_sparse(&x_cs, &m_cholmod); + } else { + // Simplicial factorization stored as standard CSC matrix. + StorageIndex* p = static_cast(m_cholmodFactor->p); + Index size = m_cholmodFactor->n; + for (Index k = 0; k < size; ++k) logDet += log(real(x[p[k]])); } - #endif // EIGEN_PARSED_BY_DOXYGEN - - - /** Sets the shift parameter that will be used to adjust the diagonal coefficients during the numerical factorization. - * - * During the numerical factorization, an offset term is added to the diagonal coefficients:\n - * \c d_ii = \a offset + \c d_ii - * - * The default is \a offset=0. - * - * \returns a reference to \c *this. - */ - Derived& setShift(const RealScalar& offset) - { - m_shiftOffset[0] = offset; - return derived(); - } - - template - void dumpMemory(Stream& /*s*/) - {} - - protected: - mutable cholmod_common m_cholmod; - cholmod_factor* m_cholmodFactor; - RealScalar m_shiftOffset[2]; - mutable ComputationInfo m_info; - bool m_isInitialized; - int m_factorizationIsOk; - int m_analysisIsOk; + if (m_cholmodFactor->is_ll) logDet *= 2.0; + return logDet; + } + + template + void dumpMemory(Stream& /*s*/) {} + + protected: + mutable cholmod_common m_cholmod; + cholmod_factor* m_cholmodFactor; + double m_shiftOffset[2]; + mutable ComputationInfo m_info; + int m_factorizationIsOk; + int m_analysisIsOk; }; /** \ingroup CholmodSupport_Module - * \class CholmodSimplicialLLT - * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod - * - * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization - * using the Cholmod library. - * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical interest. - * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * - * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. - * - * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLLT - */ -template -class CholmodSimplicialLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT<_MatrixType, _UpLo> > -{ - typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLLT> Base; - using Base::m_cholmod; - - public: - - typedef _MatrixType MatrixType; - - CholmodSimplicialLLT() : Base() { init(); } - - CholmodSimplicialLLT(const MatrixType& matrix) : Base() - { - init(); - Base::compute(matrix); - } + * \class CholmodSimplicialLLT + * \brief A simplicial direct Cholesky (LLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a simplicial LL^T Cholesky factorization + * using the Cholmod library. + * This simplicial variant is equivalent to Eigen's built-in SimplicialLLT class. Therefore, it has little practical + * interest. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices X and B can be + * either dense or sparse. + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \implsparsesolverconcept + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non + * compressed. + * + * \warning Only double precision real and complex scalar types are supported by Cholmod. + * + * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLLT + */ +template +class CholmodSimplicialLLT : public CholmodBase > { + typedef CholmodBase Base; + using Base::m_cholmod; + + public: + typedef MatrixType_ MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::StorageIndex StorageIndex; + typedef TriangularView MatrixL; + typedef TriangularView MatrixU; + + CholmodSimplicialLLT() : Base() { init(); } + + CholmodSimplicialLLT(const MatrixType& matrix) : Base() { + init(); + this->compute(matrix); + } - ~CholmodSimplicialLLT() {} - protected: - void init() - { - m_cholmod.final_asis = 0; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - m_cholmod.final_ll = 1; - } -}; + ~CholmodSimplicialLLT() {} + /** \returns an expression of the factor L */ + inline MatrixL matrixL() const { return viewAsEigen(*Base::m_cholmodFactor); } -/** \ingroup CholmodSupport_Module - * \class CholmodSimplicialLDLT - * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod - * - * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization - * using the Cholmod library. - * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Therefore, it has little practical interest. - * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * - * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. - * - * \sa \ref TutorialSparseDirectSolvers, class CholmodSupernodalLLT, class SimplicialLDLT - */ -template -class CholmodSimplicialLDLT : public CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT<_MatrixType, _UpLo> > -{ - typedef CholmodBase<_MatrixType, _UpLo, CholmodSimplicialLDLT> Base; - using Base::m_cholmod; - - public: - - typedef _MatrixType MatrixType; - - CholmodSimplicialLDLT() : Base() { init(); } - - CholmodSimplicialLDLT(const MatrixType& matrix) : Base() - { - init(); - Base::compute(matrix); - } + /** \returns an expression of the factor U (= L^*) */ + inline MatrixU matrixU() const { return matrixL().adjoint(); } - ~CholmodSimplicialLDLT() {} - protected: - void init() - { - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - } + protected: + void init() { + m_cholmod.final_asis = 0; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + m_cholmod.final_ll = 1; + } }; /** \ingroup CholmodSupport_Module - * \class CholmodSupernodalLLT - * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod - * - * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization - * using the Cholmod library. - * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM. - * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * - * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. - * - * \sa \ref TutorialSparseDirectSolvers - */ -template -class CholmodSupernodalLLT : public CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT<_MatrixType, _UpLo> > -{ - typedef CholmodBase<_MatrixType, _UpLo, CholmodSupernodalLLT> Base; - using Base::m_cholmod; - - public: - - typedef _MatrixType MatrixType; - - CholmodSupernodalLLT() : Base() { init(); } - - CholmodSupernodalLLT(const MatrixType& matrix) : Base() - { - init(); - Base::compute(matrix); - } + * \class CholmodSimplicialLDLT + * \brief A simplicial direct Cholesky (LDLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a simplicial LDL^T Cholesky factorization + * using the Cholmod library. + * This simplicial variant is equivalent to Eigen's built-in SimplicialLDLT class. Therefore, it has little practical + * interest. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices X and B can be + * either dense or sparse. + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \implsparsesolverconcept + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non + * compressed. + * + * \warning Only double precision real and complex scalar types are supported by Cholmod. + * + * \sa \ref TutorialSparseSolverConcept, class CholmodSupernodalLLT, class SimplicialLDLT + */ +template +class CholmodSimplicialLDLT : public CholmodBase > { + typedef CholmodBase Base; + using Base::m_cholmod; + + public: + typedef MatrixType_ MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::StorageIndex StorageIndex; + typedef Matrix VectorType; + typedef TriangularView MatrixL; + typedef TriangularView MatrixU; + + CholmodSimplicialLDLT() : Base() { init(); } + + CholmodSimplicialLDLT(const MatrixType& matrix) : Base() { + init(); + this->compute(matrix); + } + + ~CholmodSimplicialLDLT() {} + + /** \returns a vector expression of the diagonal D */ + inline VectorType vectorD() const { + auto cholmodL = viewAsEigen(*Base::m_cholmodFactor); + + VectorType D{cholmodL.rows()}; - ~CholmodSupernodalLLT() {} - protected: - void init() - { - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SUPERNODAL; + for (Index k = 0; k < cholmodL.outerSize(); ++k) { + typename decltype(cholmodL)::InnerIterator it{cholmodL, k}; + D(k) = it.value(); } + + return D; + } + + /** \returns an expression of the factor L */ + inline MatrixL matrixL() const { return viewAsEigen(*Base::m_cholmodFactor); } + + /** \returns an expression of the factor U (= L^*) */ + inline MatrixU matrixU() const { return matrixL().adjoint(); } + + protected: + void init() { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + } }; /** \ingroup CholmodSupport_Module - * \class CholmodDecomposition - * \brief A general Cholesky factorization and solver based on Cholmod - * - * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization - * using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices - * X and B can be either dense or sparse. - * - * This variant permits to change the underlying Cholesky method at runtime. - * On the other hand, it does not provide access to the result of the factorization. - * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization. - * - * \tparam _MatrixType the type of the sparse matrix A, it must be a SparseMatrix<> - * \tparam _UpLo the triangular part that will be used for the computations. It can be Lower - * or Upper. Default is Lower. - * - * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non compressed. - * - * \sa \ref TutorialSparseDirectSolvers - */ -template -class CholmodDecomposition : public CholmodBase<_MatrixType, _UpLo, CholmodDecomposition<_MatrixType, _UpLo> > -{ - typedef CholmodBase<_MatrixType, _UpLo, CholmodDecomposition> Base; - using Base::m_cholmod; - - public: - - typedef _MatrixType MatrixType; - - CholmodDecomposition() : Base() { init(); } - - CholmodDecomposition(const MatrixType& matrix) : Base() - { - init(); - Base::compute(matrix); - } + * \class CholmodSupernodalLLT + * \brief A supernodal Cholesky (LLT) factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a supernodal LL^T Cholesky factorization + * using the Cholmod library. + * This supernodal variant performs best on dense enough problems, e.g., 3D FEM, or very high order 2D FEM. + * The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \implsparsesolverconcept + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non + * compressed. + * + * \warning Only double precision real and complex scalar types are supported by Cholmod. + * + * \sa \ref TutorialSparseSolverConcept + */ +template +class CholmodSupernodalLLT : public CholmodBase > { + typedef CholmodBase Base; + using Base::m_cholmod; + + public: + typedef MatrixType_ MatrixType; + typedef typename MatrixType::Scalar Scalar; + typedef typename MatrixType::RealScalar RealScalar; + typedef typename MatrixType::StorageIndex StorageIndex; + + CholmodSupernodalLLT() : Base() { init(); } + + CholmodSupernodalLLT(const MatrixType& matrix) : Base() { + init(); + this->compute(matrix); + } - ~CholmodDecomposition() {} - - void setMode(CholmodMode mode) - { - switch(mode) - { - case CholmodAuto: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_AUTO; - break; - case CholmodSimplicialLLt: - m_cholmod.final_asis = 0; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - m_cholmod.final_ll = 1; - break; - case CholmodSupernodalLLt: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SUPERNODAL; - break; - case CholmodLDLt: - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; - break; - default: - break; - } - } - protected: - void init() - { - m_cholmod.final_asis = 1; - m_cholmod.supernodal = CHOLMOD_AUTO; - } -}; + ~CholmodSupernodalLLT() {} -namespace internal { - -template -struct solve_retval, Rhs> - : solve_retval_base, Rhs> -{ - typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec; - EIGEN_MAKE_SOLVE_HELPERS(Dec,Rhs) - - template void evalTo(Dest& dst) const - { - dec()._solve(rhs(),dst); + /** \returns an expression of the factor L */ + inline MatrixType matrixL() const { + // Convert Cholmod factor's supernodal storage format to Eigen's CSC storage format + cholmod_sparse* cholmodL = internal::cm_factor_to_sparse(*Base::m_cholmodFactor, m_cholmod); + MatrixType L = viewAsEigen(*cholmodL); + internal::cm_free_sparse(cholmodL, m_cholmod); + + return L; } -}; -template -struct sparse_solve_retval, Rhs> - : sparse_solve_retval_base, Rhs> -{ - typedef CholmodBase<_MatrixType,_UpLo,Derived> Dec; - EIGEN_MAKE_SPARSE_SOLVE_HELPERS(Dec,Rhs) + /** \returns an expression of the factor U (= L^*) */ + inline MatrixType matrixU() const { return matrixL().adjoint(); } - template void evalTo(Dest& dst) const - { - dec()._solve(rhs(),dst); + protected: + void init() { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SUPERNODAL; } }; -} // end namespace internal +/** \ingroup CholmodSupport_Module + * \class CholmodDecomposition + * \brief A general Cholesky factorization and solver based on Cholmod + * + * This class allows to solve for A.X = B sparse linear problems via a LL^T or LDL^T Cholesky factorization + * using the Cholmod library. The sparse matrix A must be selfadjoint and positive definite. The vectors or matrices + * X and B can be either dense or sparse. + * + * This variant permits to change the underlying Cholesky method at runtime. + * On the other hand, it does not provide access to the result of the factorization. + * The default is to let Cholmod automatically choose between a simplicial and supernodal factorization. + * + * \tparam MatrixType_ the type of the sparse matrix A, it must be a SparseMatrix<> + * \tparam UpLo_ the triangular part that will be used for the computations. It can be Lower + * or Upper. Default is Lower. + * + * \implsparsesolverconcept + * + * This class supports all kind of SparseMatrix<>: row or column major; upper, lower, or both; compressed or non + * compressed. + * + * \warning Only double precision real and complex scalar types are supported by Cholmod. + * + * \sa \ref TutorialSparseSolverConcept + */ +template +class CholmodDecomposition : public CholmodBase > { + typedef CholmodBase Base; + using Base::m_cholmod; + + public: + typedef MatrixType_ MatrixType; + + CholmodDecomposition() : Base() { init(); } + + CholmodDecomposition(const MatrixType& matrix) : Base() { + init(); + this->compute(matrix); + } + + ~CholmodDecomposition() {} + + void setMode(CholmodMode mode) { + switch (mode) { + case CholmodAuto: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_AUTO; + break; + case CholmodSimplicialLLt: + m_cholmod.final_asis = 0; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + m_cholmod.final_ll = 1; + break; + case CholmodSupernodalLLt: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SUPERNODAL; + break; + case CholmodLDLt: + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_SIMPLICIAL; + break; + default: + break; + } + } + + protected: + void init() { + m_cholmod.final_asis = 1; + m_cholmod.supernodal = CHOLMOD_AUTO; + } +}; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_CHOLMODSUPPORT_H +#endif // EIGEN_CHOLMODSUPPORT_H diff --git a/inst/include/Eigen/src/CholmodSupport/InternalHeaderCheck.h b/inst/include/Eigen/src/CholmodSupport/InternalHeaderCheck.h new file mode 100644 index 00000000..0fb3abc7 --- /dev/null +++ b/inst/include/Eigen/src/CholmodSupport/InternalHeaderCheck.h @@ -0,0 +1,3 @@ +#ifndef EIGEN_CHOLMODSUPPORT_MODULE_H +#error "Please include Eigen/CholmodSupport instead of including headers inside the src directory directly." +#endif diff --git a/inst/include/Eigen/src/Core/ArithmeticSequence.h b/inst/include/Eigen/src/Core/ArithmeticSequence.h new file mode 100644 index 00000000..ae6373dd --- /dev/null +++ b/inst/include/Eigen/src/Core/ArithmeticSequence.h @@ -0,0 +1,239 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2017 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_ARITHMETIC_SEQUENCE_H +#define EIGEN_ARITHMETIC_SEQUENCE_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +// Helper to cleanup the type of the increment: +template +struct cleanup_seq_incr { + typedef typename cleanup_index_type::type type; +}; + +} // namespace internal + +//-------------------------------------------------------------------------------- +// seq(first,last,incr) and seqN(first,size,incr) +//-------------------------------------------------------------------------------- + +template > +class ArithmeticSequence; + +template +ArithmeticSequence::type, + typename internal::cleanup_index_type::type, + typename internal::cleanup_seq_incr::type> +seqN(FirstType first, SizeType size, IncrType incr); + +/** \class ArithmeticSequence + * \ingroup Core_Module + * + * This class represents an arithmetic progression \f$ a_0, a_1, a_2, ..., a_{n-1}\f$ defined by + * its \em first value \f$ a_0 \f$, its \em size (aka length) \em n, and the \em increment (aka stride) + * that is equal to \f$ a_{i+1}-a_{i}\f$ for any \em i. + * + * It is internally used as the return type of the Eigen::seq and Eigen::seqN functions, and as the input arguments + * of DenseBase::operator()(const RowIndices&, const ColIndices&), and most of the time this is the + * only way it is used. + * + * \tparam FirstType type of the first element, usually an Index, + * but internally it can be a symbolic expression + * \tparam SizeType type representing the size of the sequence, usually an Index + * or a compile time integral constant. Internally, it can also be a symbolic expression + * \tparam IncrType type of the increment, can be a runtime Index, or a compile time integral constant (default is + * compile-time 1) + * + * \sa Eigen::seq, Eigen::seqN, DenseBase::operator()(const RowIndices&, const ColIndices&), class IndexedView + */ +template +class ArithmeticSequence { + public: + constexpr ArithmeticSequence() = default; + constexpr ArithmeticSequence(FirstType first, SizeType size) : m_first(first), m_size(size) {} + constexpr ArithmeticSequence(FirstType first, SizeType size, IncrType incr) + : m_first(first), m_size(size), m_incr(incr) {} + + enum { + // SizeAtCompileTime = internal::get_fixed_value::value, + IncrAtCompileTime = internal::get_fixed_value::value + }; + + /** \returns the size, i.e., number of elements, of the sequence */ + constexpr Index size() const { return m_size; } + + /** \returns the first element \f$ a_0 \f$ in the sequence */ + constexpr Index first() const { return m_first; } + + /** \returns the value \f$ a_i \f$ at index \a i in the sequence. */ + constexpr Index operator[](Index i) const { return m_first + i * m_incr; } + + constexpr const FirstType& firstObject() const { return m_first; } + constexpr const SizeType& sizeObject() const { return m_size; } + constexpr const IncrType& incrObject() const { return m_incr; } + + protected: + FirstType m_first; + SizeType m_size; + IncrType m_incr; + + public: + constexpr auto reverse() const -> decltype(Eigen::seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr)) { + return seqN(m_first + (m_size + fix<-1>()) * m_incr, m_size, -m_incr); + } +}; + +/** \returns an ArithmeticSequence starting at \a first, of length \a size, and increment \a incr + * + * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */ +template +ArithmeticSequence::type, + typename internal::cleanup_index_type::type, + typename internal::cleanup_seq_incr::type> +seqN(FirstType first, SizeType size, IncrType incr) { + return ArithmeticSequence::type, + typename internal::cleanup_index_type::type, + typename internal::cleanup_seq_incr::type>(first, size, incr); +} + +/** \returns an ArithmeticSequence starting at \a first, of length \a size, and unit increment + * + * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType) */ +template +ArithmeticSequence::type, + typename internal::cleanup_index_type::type> +seqN(FirstType first, SizeType size) { + return ArithmeticSequence::type, + typename internal::cleanup_index_type::type>(first, size); +} + +#ifdef EIGEN_PARSED_BY_DOXYGEN + +/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and with positive (or negative) increment \a + * incr + * + * It is essentially an alias to: + * \code + * seqN(f, (l-f+incr)/incr, incr); + * \endcode + * + * \sa seqN(FirstType,SizeType,IncrType), seq(FirstType,LastType) + */ +template +auto seq(FirstType f, LastType l, IncrType incr); + +/** \returns an ArithmeticSequence starting at \a f, up (or down) to \a l, and unit increment + * + * It is essentially an alias to: + * \code + * seqN(f,l-f+1); + * \endcode + * + * \sa seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) + */ +template +auto seq(FirstType f, LastType l); + +#else // EIGEN_PARSED_BY_DOXYGEN + +template +auto seq(FirstType f, LastType l) + -> decltype(seqN(typename internal::cleanup_index_type::type(f), + (typename internal::cleanup_index_type::type(l) - + typename internal::cleanup_index_type::type(f) + fix<1>()))) { + return seqN(typename internal::cleanup_index_type::type(f), + (typename internal::cleanup_index_type::type(l) - + typename internal::cleanup_index_type::type(f) + fix<1>())); +} + +template +auto seq(FirstType f, LastType l, IncrType incr) + -> decltype(seqN(typename internal::cleanup_index_type::type(f), + (typename internal::cleanup_index_type::type(l) - + typename internal::cleanup_index_type::type(f) + + typename internal::cleanup_seq_incr::type(incr)) / + typename internal::cleanup_seq_incr::type(incr), + typename internal::cleanup_seq_incr::type(incr))) { + typedef typename internal::cleanup_seq_incr::type CleanedIncrType; + return seqN(typename internal::cleanup_index_type::type(f), + (typename internal::cleanup_index_type::type(l) - + typename internal::cleanup_index_type::type(f) + CleanedIncrType(incr)) / + CleanedIncrType(incr), + CleanedIncrType(incr)); +} + +#endif // EIGEN_PARSED_BY_DOXYGEN + +namespace placeholders { + +/** \cpp11 + * \returns a symbolic ArithmeticSequence representing the last \a size elements with increment \a incr. + * + * It is a shortcut for: \code seqN(last-(size-fix<1>)*incr, size, incr) \endcode + * + * \sa lastN(SizeType), seqN(FirstType,SizeType), seq(FirstType,LastType,IncrType) */ +template +auto lastN(SizeType size, IncrType incr) + -> decltype(seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr)) { + return seqN(Eigen::placeholders::last - (size - fix<1>()) * incr, size, incr); +} + +/** \cpp11 + * \returns a symbolic ArithmeticSequence representing the last \a size elements with a unit increment. + * + * It is a shortcut for: \code seq(last+fix<1>-size, last) \endcode + * + * \sa lastN(SizeType,IncrType, seqN(FirstType,SizeType), seq(FirstType,LastType) */ +template +auto lastN(SizeType size) -> decltype(seqN(Eigen::placeholders::last + fix<1>() - size, size)) { + return seqN(Eigen::placeholders::last + fix<1>() - size, size); +} + +} // namespace placeholders + +/** \namespace Eigen::indexing + * \ingroup Core_Module + * + * The sole purpose of this namespace is to be able to import all functions + * and symbols that are expected to be used within operator() for indexing + * and slicing. If you already imported the whole Eigen namespace: + * \code using namespace Eigen; \endcode + * then you are already all set. Otherwise, if you don't want/cannot import + * the whole Eigen namespace, the following line: + * \code using namespace Eigen::indexing; \endcode + * is equivalent to: + * \code + using Eigen::fix; + using Eigen::seq; + using Eigen::seqN; + using Eigen::placeholders::all; + using Eigen::placeholders::last; + using Eigen::placeholders::lastN; // c++11 only + using Eigen::placeholders::lastp1; + \endcode + */ +namespace indexing { +using Eigen::fix; +using Eigen::seq; +using Eigen::seqN; +using Eigen::placeholders::all; +using Eigen::placeholders::last; +using Eigen::placeholders::lastN; +using Eigen::placeholders::lastp1; +} // namespace indexing + +} // end namespace Eigen + +#endif // EIGEN_ARITHMETIC_SEQUENCE_H diff --git a/inst/include/Eigen/src/Core/Array.h b/inst/include/Eigen/src/Core/Array.h index 0b9c38c8..57f3186b 100644 --- a/inst/include/Eigen/src/Core/Array.h +++ b/inst/include/Eigen/src/Core/Array.h @@ -10,314 +10,367 @@ #ifndef EIGEN_ARRAY_H #define EIGEN_ARRAY_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { -/** \class Array - * \ingroup Core_Module - * - * \brief General-purpose arrays with easy API for coefficient-wise operations - * - * The %Array class is very similar to the Matrix class. It provides - * general-purpose one- and two-dimensional arrays. The difference between the - * %Array and the %Matrix class is primarily in the API: the API for the - * %Array class provides easy access to coefficient-wise operations, while the - * API for the %Matrix class provides easy access to linear-algebra - * operations. - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN. - * - * \sa \ref TutorialArrayClass, \ref TopicClassHierarchy - */ namespace internal { -template -struct traits > : traits > -{ +template +struct traits> + : traits> { typedef ArrayXpr XprKind; - typedef ArrayBase > XprBase; + typedef ArrayBase> XprBase; }; -} - -template -class Array - : public PlainObjectBase > -{ - public: - - typedef PlainObjectBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Array) - - enum { Options = _Options }; - typedef typename Base::PlainObject PlainObject; - - protected: - template - friend struct internal::conservative_resize_like_impl; - - using Base::m_storage; - - public: - - using Base::base; - using Base::coeff; - using Base::coeffRef; - - /** - * The usage of - * using Base::operator=; - * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped - * the usage of 'using'. This should be done only for operator=. - */ - template - EIGEN_STRONG_INLINE Array& operator=(const EigenBase &other) - { - return Base::operator=(other); - } - - /** Copies the value of the expression \a other into \c *this with automatic resizing. - * - * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), - * it will be initialized. - * - * Note that copying a row-vector into a vector (and conversely) is allowed. - * The resizing, if any, is then done in the appropriate way so that row-vectors - * remain row-vectors and vectors remain vectors. - */ - template - EIGEN_STRONG_INLINE Array& operator=(const ArrayBase& other) - { - return Base::_set(other); - } - - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - EIGEN_STRONG_INLINE Array& operator=(const Array& other) - { - return Base::_set(other); - } - - /** Default constructor. - * - * For fixed-size matrices, does nothing. - * - * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix - * is called a null matrix. This constructor is the unique way to create null matrices: resizing - * a matrix to 0 is not supported. - * - * \sa resize(Index,Index) - */ - EIGEN_STRONG_INLINE Array() : Base() - { - Base::_check_template_params(); - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } - -#ifndef EIGEN_PARSED_BY_DOXYGEN - // FIXME is it still needed ?? - /** \internal */ - Array(internal::constructor_without_unaligned_array_assert) - : Base(internal::constructor_without_unaligned_array_assert()) - { - Base::_check_template_params(); - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } +} // namespace internal + +/** \class Array + * \ingroup Core_Module + * + * \brief General-purpose arrays with easy API for coefficient-wise operations + * + * The %Array class is very similar to the Matrix class. It provides + * general-purpose one- and two-dimensional arrays. The difference between the + * %Array and the %Matrix class is primarily in the API: the API for the + * %Array class provides easy access to coefficient-wise operations, while the + * API for the %Matrix class provides easy access to linear-algebra + * operations. + * + * See documentation of class Matrix for detailed information on the template parameters + * storage layout. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAY_PLUGIN. + * + * \sa \blank \ref TutorialArrayClass, \ref TopicClassHierarchy + */ +template +class Array : public PlainObjectBase> { + public: + typedef PlainObjectBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Array) + + enum { Options = Options_ }; + typedef typename Base::PlainObject PlainObject; + + protected: + template + friend struct internal::conservative_resize_like_impl; + + using Base::m_storage; + + public: + using Base::base; + using Base::coeff; + using Base::coeffRef; + + /** + * The usage of + * using Base::operator=; + * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped + * the usage of 'using'. This should be done only for operator=. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const EigenBase& other) { + return Base::operator=(other); + } + + /** Set all the entries to \a value. + * \sa DenseBase::setConstant(), DenseBase::fill() + */ + /* This overload is needed because the usage of + * using Base::operator=; + * fails on MSVC. Since the code below is working with GCC and MSVC, we skipped + * the usage of 'using'. This should be done only for operator=. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const Scalar& value) { + Base::setConstant(value); + return *this; + } + + /** Copies the value of the expression \a other into \c *this with automatic resizing. + * + * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), + * it will be initialized. + * + * Note that copying a row-vector into a vector (and conversely) is allowed. + * The resizing, if any, is then done in the appropriate way so that row-vectors + * remain row-vectors and vectors remain vectors. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const DenseBase& other) { + return Base::_set(other); + } + + /** + * \brief Assigns arrays to each other. + * + * \note This is a special case of the templated operator=. Its purpose is + * to prevent a default operator= from hiding the templated operator=. + * + * \callgraph + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array& operator=(const Array& other) { return Base::_set(other); } + + /** Default constructor. + * + * For fixed-size matrices, does nothing. + * + * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix + * is called a null matrix. This constructor is the unique way to create null matrices: resizing + * a matrix to 0 is not supported. + * + * \sa resize(Index,Index) + */ +#ifdef EIGEN_INITIALIZE_COEFFS + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array() : Base() { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED } +#else + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array() = default; #endif + /** \brief Move constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(Array&&) = default; + EIGEN_DEVICE_FUNC Array& operator=(Array&& other) noexcept(std::is_nothrow_move_assignable::value) { + Base::operator=(std::move(other)); + return *this; + } + + /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients. + * + * \only_for_vectors + * + * This constructor is for 1D array or vectors with more than 4 coefficients. + * + * \warning To construct a column (resp. row) vector of fixed length, the number of values passed to this + * constructor must match the the fixed number of rows (resp. columns) of \c *this. + * + * + * Example: \include Array_variadic_ctor_cxx11.cpp + * Output: \verbinclude Array_variadic_ctor_cxx11.out + * + * \sa Array(const std::initializer_list>&) + * \sa Array(const Scalar&), Array(const Scalar&,const Scalar&) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, + const ArgTypes&... args) + : Base(a0, a1, a2, a3, args...) {} + + /** \brief Constructs an array and initializes it from the coefficients given as initializer-lists grouped by row. + * \cpp11 + * + * In the general case, the constructor takes a list of rows, each row being represented as a list of coefficients: + * + * Example: \include Array_initializer_list_23_cxx11.cpp + * Output: \verbinclude Array_initializer_list_23_cxx11.out + * + * Each of the inner initializer lists must contain the exact same number of elements, otherwise an assertion is + * triggered. + * + * In the case of a compile-time column 1D array, implicit transposition from a single row is allowed. + * Therefore Array{{1,2,3,4,5}} is legal and the more verbose syntax + * Array{{1},{2},{3},{4},{5}} can be avoided: + * + * Example: \include Array_initializer_list_vector_cxx11.cpp + * Output: \verbinclude Array_initializer_list_vector_cxx11.out + * + * In the case of fixed-sized arrays, the initializer list sizes must exactly match the array sizes, + * and implicit transposition is allowed for compile-time 1D arrays only. + * + * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array( + const std::initializer_list>& list) + : Base(list) {} -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - Array(Array&& other) - : Base(std::move(other)) - { - Base::_check_template_params(); - if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic) - Base::_set_noalias(other); - } - Array& operator=(Array&& other) - { - other.swap(*this); - return *this; - } +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(const T& x) { + Base::template _init1(x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1) { + this->template _init2(val0, val1); + } + +#else + /** \brief Constructs a fixed-sized array initialized with coefficients starting at \a data */ + EIGEN_DEVICE_FUNC explicit Array(const Scalar* data); + /** Constructs a vector or row-vector with given dimension. \only_for_vectors + * + * Note that this is only useful for dynamic-size vectors. For fixed-size vectors, + * it is redundant to pass the dimension here, so it makes more sense to use the default + * constructor Array() instead. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Array(Index dim); + /** constructs an initialized 1x1 Array with the given coefficient + * \sa const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args */ + Array(const Scalar& value); + /** constructs an uninitialized array with \a rows rows and \a cols columns. + * + * This is useful for dynamic-size arrays. For fixed-size arrays, + * it is redundant to pass these parameters, so one should use the default constructor + * Array() instead. */ + Array(Index rows, Index cols); + /** constructs an initialized 2D vector with given coefficients + * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) */ + Array(const Scalar& val0, const Scalar& val1); +#endif // end EIGEN_PARSED_BY_DOXYGEN + + /** constructs an initialized 3D vector with given coefficients + * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3) + m_storage.data()[0] = val0; + m_storage.data()[1] = val1; + m_storage.data()[2] = val2; + } + /** constructs an initialized 4D vector with given coefficients + * \sa Array(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, + const Scalar& val3) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4) + m_storage.data()[0] = val0; + m_storage.data()[1] = val1; + m_storage.data()[2] = val2; + m_storage.data()[3] = val3; + } + + /** Copy constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Array(const Array&) = default; + + private: + struct PrivateType {}; + + public: + /** \sa MatrixBase::operator=(const EigenBase&) */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Array( + const EigenBase& other, + std::enable_if_t::value, PrivateType> = + PrivateType()) + : Base(other.derived()) {} + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return 1; } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return this->innerSize(); } + +#ifdef EIGEN_ARRAY_PLUGIN +#include EIGEN_ARRAY_PLUGIN #endif - /** Constructs a vector or row-vector with given dimension. \only_for_vectors - * - * Note that this is only useful for dynamic-size vectors. For fixed-size vectors, - * it is redundant to pass the dimension here, so it makes more sense to use the default - * constructor Matrix() instead. - */ - EIGEN_STRONG_INLINE explicit Array(Index dim) - : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_ONLY(Array) - eigen_assert(dim >= 0); - eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim); - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - EIGEN_STRONG_INLINE Array(const T0& val0, const T1& val1) - { - Base::_check_template_params(); - this->template _init2(val0, val1); - } - #else - /** constructs an uninitialized matrix with \a rows rows and \a cols columns. - * - * This is useful for dynamic-size matrices. For fixed-size matrices, - * it is redundant to pass these parameters, so one should use the default constructor - * Matrix() instead. */ - Array(Index rows, Index cols); - /** constructs an initialized 2D vector with given coefficients */ - Array(const Scalar& val0, const Scalar& val1); - #endif - - /** constructs an initialized 3D vector with given coefficients */ - EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 3) - m_storage.data()[0] = val0; - m_storage.data()[1] = val1; - m_storage.data()[2] = val2; - } - /** constructs an initialized 4D vector with given coefficients */ - EIGEN_STRONG_INLINE Array(const Scalar& val0, const Scalar& val1, const Scalar& val2, const Scalar& val3) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Array, 4) - m_storage.data()[0] = val0; - m_storage.data()[1] = val1; - m_storage.data()[2] = val2; - m_storage.data()[3] = val3; - } - - explicit Array(const Scalar *data); - - /** Constructor copying the value of the expression \a other */ - template - EIGEN_STRONG_INLINE Array(const ArrayBase& other) - : Base(other.rows() * other.cols(), other.rows(), other.cols()) - { - Base::_check_template_params(); - Base::_set_noalias(other); - } - /** Copy constructor */ - EIGEN_STRONG_INLINE Array(const Array& other) - : Base(other.rows() * other.cols(), other.rows(), other.cols()) - { - Base::_check_template_params(); - Base::_set_noalias(other); - } - /** Copy constructor with in-place evaluation */ - template - EIGEN_STRONG_INLINE Array(const ReturnByValue& other) - { - Base::_check_template_params(); - Base::resize(other.rows(), other.cols()); - other.evalTo(*this); - } - - /** \sa MatrixBase::operator=(const EigenBase&) */ - template - EIGEN_STRONG_INLINE Array(const EigenBase &other) - : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols()) - { - Base::_check_template_params(); - Base::_resize_to_match(other); - *this = other; - } - - /** Override MatrixBase::swap() since for dynamic-sized matrices of same type it is enough to swap the - * data pointers. - */ - template - void swap(ArrayBase const & other) - { this->_swap(other.derived()); } - - inline Index innerStride() const { return 1; } - inline Index outerStride() const { return this->innerSize(); } - - #ifdef EIGEN_ARRAY_PLUGIN - #include EIGEN_ARRAY_PLUGIN - #endif - - private: - - template - friend struct internal::matrix_swap_impl; + private: + template + friend struct internal::matrix_swap_impl; }; /** \defgroup arraytypedefs Global array typedefs - * \ingroup Core_Module - * - * Eigen defines several typedef shortcuts for most common 1D and 2D array types. - * - * The general patterns are the following: - * - * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size, - * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd - * for complex double. - * - * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of floats. - * - * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is - * a fixed-size 1D array of 4 complex floats. - * - * \sa class Array - */ - -#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ -/** \ingroup arraytypedefs */ \ -typedef Array Array##SizeSuffix##SizeSuffix##TypeSuffix; \ -/** \ingroup arraytypedefs */ \ -typedef Array Array##SizeSuffix##TypeSuffix; - -#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \ -/** \ingroup arraytypedefs */ \ -typedef Array Array##Size##X##TypeSuffix; \ -/** \ingroup arraytypedefs */ \ -typedef Array Array##X##Size##TypeSuffix; + * \ingroup Core_Module + * + * %Eigen defines several typedef shortcuts for most common 1D and 2D array types. + * + * The general patterns are the following: + * + * \c ArrayRowsColsType where \c Rows and \c Cols can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for + * dynamic size, and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c + * cd for complex double. + * + * For example, \c Array33d is a fixed-size 3x3 array type of doubles, and \c ArrayXXf is a dynamic-size matrix of + * floats. + * + * There are also \c ArraySizeType which are self-explanatory. For example, \c Array4cf is + * a fixed-size 1D array of 4 complex floats. + * + * With \cpp11, template alias are also defined for common sizes. + * They follow the same pattern as above except that the scalar type suffix is replaced by a + * template parameter, i.e.: + * - `ArrayRowsCols` where `Rows` and `Cols` can be \c 2,\c 3,\c 4, or \c X for fixed or dynamic size. + * - `ArraySize` where `Size` can be \c 2,\c 3,\c 4 or \c X for fixed or dynamic size 1D arrays. + * + * \sa class Array + */ + +#define EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ + /** \ingroup arraytypedefs */ \ + typedef Array Array##SizeSuffix##SizeSuffix##TypeSuffix; \ + /** \ingroup arraytypedefs */ \ + typedef Array Array##SizeSuffix##TypeSuffix; + +#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \ + /** \ingroup arraytypedefs */ \ + typedef Array Array##Size##X##TypeSuffix; \ + /** \ingroup arraytypedefs */ \ + typedef Array Array##X##Size##TypeSuffix; #define EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \ -EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \ -EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \ -EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \ -EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \ -EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \ -EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \ -EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4) - -EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int, i) -EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float, f) -EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double, d) -EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex, cf) + EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 2, 2) \ + EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 3, 3) \ + EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, 4, 4) \ + EIGEN_MAKE_ARRAY_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \ + EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \ + EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \ + EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Type, TypeSuffix, 4) + +EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(int, i) +EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(float, f) +EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(double, d) +EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex, cf) EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES(std::complex, cd) #undef EIGEN_MAKE_ARRAY_TYPEDEFS_ALL_SIZES #undef EIGEN_MAKE_ARRAY_TYPEDEFS +#undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS + +#define EIGEN_MAKE_ARRAY_TYPEDEFS(Size, SizeSuffix) \ + /** \ingroup arraytypedefs */ \ + /** \brief \cpp11 */ \ + template \ + using Array##SizeSuffix##SizeSuffix = Array; \ + /** \ingroup arraytypedefs */ \ + /** \brief \cpp11 */ \ + template \ + using Array##SizeSuffix = Array; + +#define EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(Size) \ + /** \ingroup arraytypedefs */ \ + /** \brief \cpp11 */ \ + template \ + using Array##Size##X = Array; \ + /** \ingroup arraytypedefs */ \ + /** \brief \cpp11 */ \ + template \ + using Array##X##Size = Array; + +EIGEN_MAKE_ARRAY_TYPEDEFS(2, 2) +EIGEN_MAKE_ARRAY_TYPEDEFS(3, 3) +EIGEN_MAKE_ARRAY_TYPEDEFS(4, 4) +EIGEN_MAKE_ARRAY_TYPEDEFS(Dynamic, X) +EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(2) +EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(3) +EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS(4) -#undef EIGEN_MAKE_ARRAY_TYPEDEFS_LARGE +#undef EIGEN_MAKE_ARRAY_TYPEDEFS +#undef EIGEN_MAKE_ARRAY_FIXED_TYPEDEFS #define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, SizeSuffix) \ -using Eigen::Matrix##SizeSuffix##TypeSuffix; \ -using Eigen::Vector##SizeSuffix##TypeSuffix; \ -using Eigen::RowVector##SizeSuffix##TypeSuffix; - -#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) \ - -#define EIGEN_USING_ARRAY_TYPEDEFS \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \ -EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd) - -} // end namespace Eigen - -#endif // EIGEN_ARRAY_H + using Eigen::Matrix##SizeSuffix##TypeSuffix; \ + using Eigen::Vector##SizeSuffix##TypeSuffix; \ + using Eigen::RowVector##SizeSuffix##TypeSuffix; + +#define EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(TypeSuffix) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 2) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 3) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, 4) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE_AND_SIZE(TypeSuffix, X) + +#define EIGEN_USING_ARRAY_TYPEDEFS \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(i) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(f) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(d) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cf) \ + EIGEN_USING_ARRAY_TYPEDEFS_FOR_TYPE(cd) + +} // end namespace Eigen + +#endif // EIGEN_ARRAY_H diff --git a/inst/include/Eigen/src/Core/ArrayBase.h b/inst/include/Eigen/src/Core/ArrayBase.h index 33ff5537..8465f54f 100644 --- a/inst/include/Eigen/src/Core/ArrayBase.h +++ b/inst/include/Eigen/src/Core/ArrayBase.h @@ -10,217 +10,204 @@ #ifndef EIGEN_ARRAYBASE_H #define EIGEN_ARRAYBASE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -template class MatrixWrapper; +namespace Eigen { -/** \class ArrayBase - * \ingroup Core_Module - * - * \brief Base class for all 1D and 2D array, and related expressions - * - * An array is similar to a dense vector or matrix. While matrices are mathematical - * objects with well defined linear algebra operators, an array is just a collection - * of scalar values arranged in a one or two dimensionnal fashion. As the main consequence, - * all operations applied to an array are performed coefficient wise. Furthermore, - * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient - * constructors allowing to easily write generic code working for both scalar values - * and arrays. - * - * This class is the base that is inherited by all array expression types. - * - * \tparam Derived is the derived type, e.g., an array or an expression type. - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN. - * - * \sa class MatrixBase, \ref TopicClassHierarchy - */ -template class ArrayBase - : public DenseBase -{ - public: -#ifndef EIGEN_PARSED_BY_DOXYGEN - /** The base class for a given storage type. */ - typedef ArrayBase StorageBaseType; - - typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl; - - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - - typedef DenseBase Base; - using Base::operator*; - using Base::RowsAtCompileTime; - using Base::ColsAtCompileTime; - using Base::SizeAtCompileTime; - using Base::MaxRowsAtCompileTime; - using Base::MaxColsAtCompileTime; - using Base::MaxSizeAtCompileTime; - using Base::IsVectorAtCompileTime; - using Base::Flags; - using Base::CoeffReadCost; - - using Base::derived; - using Base::const_cast_derived; - using Base::rows; - using Base::cols; - using Base::size; - using Base::coeff; - using Base::coeffRef; - using Base::lazyAssign; - using Base::operator=; - using Base::operator+=; - using Base::operator-=; - using Base::operator*=; - using Base::operator/=; - - typedef typename Base::CoeffReturnType CoeffReturnType; - -#endif // not EIGEN_PARSED_BY_DOXYGEN +template +class MatrixWrapper; +/** \class ArrayBase + * \ingroup Core_Module + * + * \brief Base class for all 1D and 2D array, and related expressions + * + * An array is similar to a dense vector or matrix. While matrices are mathematical + * objects with well defined linear algebra operators, an array is just a collection + * of scalar values arranged in a one or two dimensional fashion. As the main consequence, + * all operations applied to an array are performed coefficient wise. Furthermore, + * arrays support scalar math functions of the c++ standard library (e.g., std::sin(x)), and convenient + * constructors allowing to easily write generic code working for both scalar values + * and arrays. + * + * This class is the base that is inherited by all array expression types. + * + * \tparam Derived is the derived type, e.g., an array or an expression type. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_ARRAYBASE_PLUGIN. + * + * \sa class MatrixBase, \ref TopicClassHierarchy + */ +template +class ArrayBase : public DenseBase { + public: #ifndef EIGEN_PARSED_BY_DOXYGEN - /** \internal the plain matrix type corresponding to this expression. Note that is not necessarily - * exactly the return type of eval(): in the case of plain matrices, the return type of eval() is a const - * reference to a matrix, not a matrix! It is however guaranteed that the return type of eval() is either - * PlainObject or const PlainObject&. - */ - typedef Array::Scalar, - internal::traits::RowsAtCompileTime, - internal::traits::ColsAtCompileTime, - AutoAlign | (internal::traits::Flags&RowMajorBit ? RowMajor : ColMajor), - internal::traits::MaxRowsAtCompileTime, - internal::traits::MaxColsAtCompileTime - > PlainObject; - - - /** \internal Represents a matrix with all coefficients equal to one another*/ - typedef CwiseNullaryOp,Derived> ConstantReturnType; -#endif // not EIGEN_PARSED_BY_DOXYGEN + /** The base class for a given storage type. */ + typedef ArrayBase StorageBaseType; + + typedef ArrayBase Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl; + + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::packet_traits::type PacketScalar; + typedef typename NumTraits::Real RealScalar; + + typedef DenseBase Base; + using Base::ColsAtCompileTime; + using Base::Flags; + using Base::IsVectorAtCompileTime; + using Base::MaxColsAtCompileTime; + using Base::MaxRowsAtCompileTime; + using Base::MaxSizeAtCompileTime; + using Base::RowsAtCompileTime; + using Base::SizeAtCompileTime; + + using Base::coeff; + using Base::coeffRef; + using Base::cols; + using Base::const_cast_derived; + using Base::derived; + using Base::lazyAssign; + using Base::rows; + using Base::size; + using Base::operator-; + using Base::operator=; + using Base::operator+=; + using Base::operator-=; + using Base::operator*=; + using Base::operator/=; + + typedef typename Base::CoeffReturnType CoeffReturnType; + + typedef typename Base::PlainObject PlainObject; + + /** \internal Represents a matrix with all coefficients equal to one another*/ + typedef CwiseNullaryOp, PlainObject> ConstantReturnType; +#endif // not EIGEN_PARSED_BY_DOXYGEN #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::ArrayBase -# include "../plugins/CommonCwiseUnaryOps.h" -# include "../plugins/MatrixCwiseUnaryOps.h" -# include "../plugins/ArrayCwiseUnaryOps.h" -# include "../plugins/CommonCwiseBinaryOps.h" -# include "../plugins/MatrixCwiseBinaryOps.h" -# include "../plugins/ArrayCwiseBinaryOps.h" -# ifdef EIGEN_ARRAYBASE_PLUGIN -# include EIGEN_ARRAYBASE_PLUGIN -# endif +#define EIGEN_DOC_UNARY_ADDONS(X, Y) +#include "../plugins/MatrixCwiseUnaryOps.inc" +#include "../plugins/ArrayCwiseUnaryOps.inc" +#include "../plugins/CommonCwiseBinaryOps.inc" +#include "../plugins/MatrixCwiseBinaryOps.inc" +#include "../plugins/ArrayCwiseBinaryOps.inc" +#ifdef EIGEN_ARRAYBASE_PLUGIN +#include EIGEN_ARRAYBASE_PLUGIN +#endif #undef EIGEN_CURRENT_STORAGE_BASE_CLASS - - /** Special case of the template operator=, in order to prevent the compiler - * from generating a default operator= (issue hit with g++ 4.1) - */ - Derived& operator=(const ArrayBase& other) - { - return internal::assign_selector::run(derived(), other.derived()); - } - - Derived& operator+=(const Scalar& scalar) - { return *this = derived() + scalar; } - Derived& operator-=(const Scalar& scalar) - { return *this = derived() - scalar; } - - template - Derived& operator+=(const ArrayBase& other); - template - Derived& operator-=(const ArrayBase& other); - - template - Derived& operator*=(const ArrayBase& other); - - template - Derived& operator/=(const ArrayBase& other); - - public: - ArrayBase& array() { return *this; } - const ArrayBase& array() const { return *this; } - - /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array - * \sa MatrixBase::array() */ - MatrixWrapper matrix() { return derived(); } - const MatrixWrapper matrix() const { return derived(); } - -// template -// inline void evalTo(Dest& dst) const { dst = matrix(); } - - protected: - ArrayBase() : Base() {} - - private: - explicit ArrayBase(Index); - ArrayBase(Index,Index); - template explicit ArrayBase(const ArrayBase&); - protected: - // mixing arrays and matrices is not legal - template Derived& operator+=(const MatrixBase& ) - {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} - // mixing arrays and matrices is not legal - template Derived& operator-=(const MatrixBase& ) - {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} +#undef EIGEN_DOC_UNARY_ADDONS + + /** Special case of the template operator=, in order to prevent the compiler + * from generating a default operator= (issue hit with g++ 4.1) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const ArrayBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); + } + + /** Set all the entries to \a value. + * \sa DenseBase::setConstant(), DenseBase::fill() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const Scalar& value) { + Base::setConstant(value); + return derived(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const Scalar& other) { + internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other), + internal::add_assign_op()); + return derived(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const Scalar& other) { + internal::call_assignment(this->derived(), PlainObject::Constant(rows(), cols(), other), + internal::sub_assign_op()); + return derived(); + } + + /** replaces \c *this by \c *this + \a other. + * + * \returns a reference to \c *this + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const ArrayBase& other) { + call_assignment(derived(), other.derived(), internal::add_assign_op()); + return derived(); + } + + /** replaces \c *this by \c *this - \a other. + * + * \returns a reference to \c *this + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const ArrayBase& other) { + call_assignment(derived(), other.derived(), internal::sub_assign_op()); + return derived(); + } + + /** replaces \c *this by \c *this * \a other coefficient wise. + * + * \returns a reference to \c *this + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const ArrayBase& other) { + call_assignment(derived(), other.derived(), internal::mul_assign_op()); + return derived(); + } + + /** replaces \c *this by \c *this / \a other coefficient wise. + * + * \returns a reference to \c *this + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const ArrayBase& other) { + call_assignment(derived(), other.derived(), internal::div_assign_op()); + return derived(); + } + + public: + EIGEN_DEVICE_FUNC ArrayBase& array() { return *this; } + EIGEN_DEVICE_FUNC const ArrayBase& array() const { return *this; } + + /** \returns an \link Eigen::MatrixBase Matrix \endlink expression of this array + * \sa MatrixBase::array() */ + EIGEN_DEVICE_FUNC MatrixWrapper matrix() { return MatrixWrapper(derived()); } + EIGEN_DEVICE_FUNC const MatrixWrapper matrix() const { + return MatrixWrapper(derived()); + } + + // template + // inline void evalTo(Dest& dst) const { dst = matrix(); } + + protected: + EIGEN_DEFAULT_COPY_CONSTRUCTOR(ArrayBase) + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(ArrayBase) + + private: + explicit ArrayBase(Index); + ArrayBase(Index, Index); + template + explicit ArrayBase(const ArrayBase&); + + protected: + // mixing arrays and matrices is not legal + template + Derived& operator+=(const MatrixBase&) { + EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1, + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); + return *this; + } + // mixing arrays and matrices is not legal + template + Derived& operator-=(const MatrixBase&) { + EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1, + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); + return *this; + } }; -/** replaces \c *this by \c *this - \a other. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -ArrayBase::operator-=(const ArrayBase &other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); - return derived(); -} - -/** replaces \c *this by \c *this + \a other. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -ArrayBase::operator+=(const ArrayBase& other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); - return derived(); -} - -/** replaces \c *this by \c *this * \a other coefficient wise. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -ArrayBase::operator*=(const ArrayBase& other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); - return derived(); -} - -/** replaces \c *this by \c *this / \a other coefficient wise. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -ArrayBase::operator/=(const ArrayBase& other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); - return derived(); -} - -} // end namespace Eigen - -#endif // EIGEN_ARRAYBASE_H +} // end namespace Eigen + +#endif // EIGEN_ARRAYBASE_H diff --git a/inst/include/Eigen/src/Core/ArrayWrapper.h b/inst/include/Eigen/src/Core/ArrayWrapper.h index b4641e2a..c9a194e9 100644 --- a/inst/include/Eigen/src/Core/ArrayWrapper.h +++ b/inst/include/Eigen/src/Core/ArrayWrapper.h @@ -10,255 +10,156 @@ #ifndef EIGEN_ARRAYWRAPPER_H #define EIGEN_ARRAYWRAPPER_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { /** \class ArrayWrapper - * \ingroup Core_Module - * - * \brief Expression of a mathematical vector or matrix as an array object - * - * This class is the return type of MatrixBase::array(), and most of the time - * this is the only way it is use. - * - * \sa MatrixBase::array(), class MatrixWrapper - */ + * \ingroup Core_Module + * + * \brief Expression of a mathematical vector or matrix as an array object + * + * This class is the return type of MatrixBase::array(), and most of the time + * this is the only way it is use. + * + * \sa MatrixBase::array(), class MatrixWrapper + */ namespace internal { -template -struct traits > - : public traits::type > -{ +template +struct traits > : public traits > { typedef ArrayXpr XprKind; // Let's remove NestByRefBit enum { - Flags0 = traits::type >::Flags, - Flags = Flags0 & ~NestByRefBit + Flags0 = traits >::Flags, + LvalueBitFlag = is_lvalue::value ? LvalueBit : 0, + Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag }; }; -} - -template -class ArrayWrapper : public ArrayBase > -{ - public: - typedef ArrayBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper) - - typedef typename internal::conditional< - internal::is_lvalue::value, - Scalar, - const Scalar - >::type ScalarWithConstIfNotLvalue; - - typedef typename internal::nested::type NestedExpressionType; - - inline ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {} - - inline Index rows() const { return m_expression.rows(); } - inline Index cols() const { return m_expression.cols(); } - inline Index outerStride() const { return m_expression.outerStride(); } - inline Index innerStride() const { return m_expression.innerStride(); } - - inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); } - inline const Scalar* data() const { return m_expression.data(); } - - inline CoeffReturnType coeff(Index rowId, Index colId) const - { - return m_expression.coeff(rowId, colId); - } - - inline Scalar& coeffRef(Index rowId, Index colId) - { - return m_expression.const_cast_derived().coeffRef(rowId, colId); - } - - inline const Scalar& coeffRef(Index rowId, Index colId) const - { - return m_expression.const_cast_derived().coeffRef(rowId, colId); - } - - inline CoeffReturnType coeff(Index index) const - { - return m_expression.coeff(index); - } - - inline Scalar& coeffRef(Index index) - { - return m_expression.const_cast_derived().coeffRef(index); - } - - inline const Scalar& coeffRef(Index index) const - { - return m_expression.const_cast_derived().coeffRef(index); - } - - template - inline const PacketScalar packet(Index rowId, Index colId) const - { - return m_expression.template packet(rowId, colId); - } - - template - inline void writePacket(Index rowId, Index colId, const PacketScalar& val) - { - m_expression.const_cast_derived().template writePacket(rowId, colId, val); - } - - template - inline const PacketScalar packet(Index index) const - { - return m_expression.template packet(index); - } - - template - inline void writePacket(Index index, const PacketScalar& val) - { - m_expression.const_cast_derived().template writePacket(index, val); - } - - template - inline void evalTo(Dest& dst) const { dst = m_expression; } - - const typename internal::remove_all::type& - nestedExpression() const - { - return m_expression; - } - - /** Forwards the resizing request to the nested expression - * \sa DenseBase::resize(Index) */ - void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); } - /** Forwards the resizing request to the nested expression - * \sa DenseBase::resize(Index,Index)*/ - void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); } - - protected: - NestedExpressionType m_expression; +} // namespace internal + +template +class ArrayWrapper : public ArrayBase > { + public: + typedef ArrayBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(ArrayWrapper) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ArrayWrapper) + typedef internal::remove_all_t NestedExpression; + + typedef std::conditional_t::value, Scalar, const Scalar> + ScalarWithConstIfNotLvalue; + + typedef typename internal::ref_selector::non_const_type NestedExpressionType; + + using Base::coeffRef; + + EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE ArrayWrapper(ExpressionType& matrix) : m_expression(matrix) {} + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); } + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); } + + EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); } + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { + return m_expression.coeffRef(rowId, colId); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); } + + template + EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const { + dst = m_expression; + } + + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { + return m_expression; + } + + /** Forwards the resizing request to the nested expression + * \sa DenseBase::resize(Index) */ + EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); } + /** Forwards the resizing request to the nested expression + * \sa DenseBase::resize(Index,Index)*/ + EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); } + + protected: + NestedExpressionType m_expression; }; /** \class MatrixWrapper - * \ingroup Core_Module - * - * \brief Expression of an array as a mathematical vector or matrix - * - * This class is the return type of ArrayBase::matrix(), and most of the time - * this is the only way it is use. - * - * \sa MatrixBase::matrix(), class ArrayWrapper - */ + * \ingroup Core_Module + * + * \brief Expression of an array as a mathematical vector or matrix + * + * This class is the return type of ArrayBase::matrix(), and most of the time + * this is the only way it is use. + * + * \sa MatrixBase::matrix(), class ArrayWrapper + */ namespace internal { -template -struct traits > - : public traits::type > -{ +template +struct traits > : public traits > { typedef MatrixXpr XprKind; // Let's remove NestByRefBit enum { - Flags0 = traits::type >::Flags, - Flags = Flags0 & ~NestByRefBit + Flags0 = traits >::Flags, + LvalueBitFlag = is_lvalue::value ? LvalueBit : 0, + Flags = (Flags0 & ~(NestByRefBit | LvalueBit)) | LvalueBitFlag }; }; -} - -template -class MatrixWrapper : public MatrixBase > -{ - public: - typedef MatrixBase > Base; - EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper) - - typedef typename internal::conditional< - internal::is_lvalue::value, - Scalar, - const Scalar - >::type ScalarWithConstIfNotLvalue; - - typedef typename internal::nested::type NestedExpressionType; - - inline MatrixWrapper(ExpressionType& a_matrix) : m_expression(a_matrix) {} - - inline Index rows() const { return m_expression.rows(); } - inline Index cols() const { return m_expression.cols(); } - inline Index outerStride() const { return m_expression.outerStride(); } - inline Index innerStride() const { return m_expression.innerStride(); } - - inline ScalarWithConstIfNotLvalue* data() { return m_expression.const_cast_derived().data(); } - inline const Scalar* data() const { return m_expression.data(); } - - inline CoeffReturnType coeff(Index rowId, Index colId) const - { - return m_expression.coeff(rowId, colId); - } - - inline Scalar& coeffRef(Index rowId, Index colId) - { - return m_expression.const_cast_derived().coeffRef(rowId, colId); - } - - inline const Scalar& coeffRef(Index rowId, Index colId) const - { - return m_expression.derived().coeffRef(rowId, colId); - } - - inline CoeffReturnType coeff(Index index) const - { - return m_expression.coeff(index); - } - - inline Scalar& coeffRef(Index index) - { - return m_expression.const_cast_derived().coeffRef(index); - } - - inline const Scalar& coeffRef(Index index) const - { - return m_expression.const_cast_derived().coeffRef(index); - } - - template - inline const PacketScalar packet(Index rowId, Index colId) const - { - return m_expression.template packet(rowId, colId); - } - - template - inline void writePacket(Index rowId, Index colId, const PacketScalar& val) - { - m_expression.const_cast_derived().template writePacket(rowId, colId, val); - } - - template - inline const PacketScalar packet(Index index) const - { - return m_expression.template packet(index); - } - - template - inline void writePacket(Index index, const PacketScalar& val) - { - m_expression.const_cast_derived().template writePacket(index, val); - } - - const typename internal::remove_all::type& - nestedExpression() const - { - return m_expression; - } - - /** Forwards the resizing request to the nested expression - * \sa DenseBase::resize(Index) */ - void resize(Index newSize) { m_expression.const_cast_derived().resize(newSize); } - /** Forwards the resizing request to the nested expression - * \sa DenseBase::resize(Index,Index)*/ - void resize(Index nbRows, Index nbCols) { m_expression.const_cast_derived().resize(nbRows,nbCols); } - - protected: - NestedExpressionType m_expression; +} // namespace internal + +template +class MatrixWrapper : public MatrixBase > { + public: + typedef MatrixBase > Base; + EIGEN_DENSE_PUBLIC_INTERFACE(MatrixWrapper) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(MatrixWrapper) + typedef internal::remove_all_t NestedExpression; + + typedef std::conditional_t::value, Scalar, const Scalar> + ScalarWithConstIfNotLvalue; + + typedef typename internal::ref_selector::non_const_type NestedExpressionType; + + using Base::coeffRef; + + EIGEN_DEVICE_FUNC explicit inline MatrixWrapper(ExpressionType& matrix) : m_expression(matrix) {} + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); } + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); } + + EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { return m_expression.data(); } + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_expression.data(); } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { + return m_expression.derived().coeffRef(rowId, colId); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { return m_expression.coeffRef(index); } + + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { + return m_expression; + } + + /** Forwards the resizing request to the nested expression + * \sa DenseBase::resize(Index) */ + EIGEN_DEVICE_FUNC void resize(Index newSize) { m_expression.resize(newSize); } + /** Forwards the resizing request to the nested expression + * \sa DenseBase::resize(Index,Index)*/ + EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { m_expression.resize(rows, cols); } + + protected: + NestedExpressionType m_expression; }; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_ARRAYWRAPPER_H +#endif // EIGEN_ARRAYWRAPPER_H diff --git a/inst/include/Eigen/src/Core/Assign.h b/inst/include/Eigen/src/Core/Assign.h index f4817317..4b30f7bb 100644 --- a/inst/include/Eigen/src/Core/Assign.h +++ b/inst/include/Eigen/src/Core/Assign.h @@ -12,579 +12,69 @@ #ifndef EIGEN_ASSIGN_H #define EIGEN_ASSIGN_H -namespace Eigen { - -namespace internal { - -/*************************************************************************** -* Part 1 : the logic deciding a strategy for traversal and unrolling * -***************************************************************************/ - -template -struct assign_traits -{ -public: - enum { - DstIsAligned = Derived::Flags & AlignedBit, - DstHasDirectAccess = Derived::Flags & DirectAccessBit, - SrcIsAligned = OtherDerived::Flags & AlignedBit, - JointAlignment = bool(DstIsAligned) && bool(SrcIsAligned) ? Aligned : Unaligned - }; - -private: - enum { - InnerSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::SizeAtCompileTime) - : int(Derived::Flags)&RowMajorBit ? int(Derived::ColsAtCompileTime) - : int(Derived::RowsAtCompileTime), - InnerMaxSize = int(Derived::IsVectorAtCompileTime) ? int(Derived::MaxSizeAtCompileTime) - : int(Derived::Flags)&RowMajorBit ? int(Derived::MaxColsAtCompileTime) - : int(Derived::MaxRowsAtCompileTime), - MaxSizeAtCompileTime = Derived::SizeAtCompileTime, - PacketSize = packet_traits::size - }; - - enum { - StorageOrdersAgree = (int(Derived::IsRowMajor) == int(OtherDerived::IsRowMajor)), - MightVectorize = StorageOrdersAgree - && (int(Derived::Flags) & int(OtherDerived::Flags) & ActualPacketAccessBit), - MayInnerVectorize = MightVectorize && int(InnerSize)!=Dynamic && int(InnerSize)%int(PacketSize)==0 - && int(DstIsAligned) && int(SrcIsAligned), - MayLinearize = StorageOrdersAgree && (int(Derived::Flags) & int(OtherDerived::Flags) & LinearAccessBit), - MayLinearVectorize = MightVectorize && MayLinearize && DstHasDirectAccess - && (DstIsAligned || MaxSizeAtCompileTime == Dynamic), - /* If the destination isn't aligned, we have to do runtime checks and we don't unroll, - so it's only good for large enough sizes. */ - MaySliceVectorize = MightVectorize && DstHasDirectAccess - && (int(InnerMaxSize)==Dynamic || int(InnerMaxSize)>=3*PacketSize) - /* slice vectorization can be slow, so we only want it if the slices are big, which is - indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block - in a fixed-size matrix */ - }; - -public: - enum { - Traversal = int(MayInnerVectorize) ? int(InnerVectorizedTraversal) - : int(MayLinearVectorize) ? int(LinearVectorizedTraversal) - : int(MaySliceVectorize) ? int(SliceVectorizedTraversal) - : int(MayLinearize) ? int(LinearTraversal) - : int(DefaultTraversal), - Vectorized = int(Traversal) == InnerVectorizedTraversal - || int(Traversal) == LinearVectorizedTraversal - || int(Traversal) == SliceVectorizedTraversal - }; - -private: - enum { - UnrollingLimit = EIGEN_UNROLLING_LIMIT * (Vectorized ? int(PacketSize) : 1), - MayUnrollCompletely = int(Derived::SizeAtCompileTime) != Dynamic - && int(OtherDerived::CoeffReadCost) != Dynamic - && int(Derived::SizeAtCompileTime) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit), - MayUnrollInner = int(InnerSize) != Dynamic - && int(OtherDerived::CoeffReadCost) != Dynamic - && int(InnerSize) * int(OtherDerived::CoeffReadCost) <= int(UnrollingLimit) - }; - -public: - enum { - Unrolling = (int(Traversal) == int(InnerVectorizedTraversal) || int(Traversal) == int(DefaultTraversal)) - ? ( - int(MayUnrollCompletely) ? int(CompleteUnrolling) - : int(MayUnrollInner) ? int(InnerUnrolling) - : int(NoUnrolling) - ) - : int(Traversal) == int(LinearVectorizedTraversal) - ? ( bool(MayUnrollCompletely) && bool(DstIsAligned) ? int(CompleteUnrolling) : int(NoUnrolling) ) - : int(Traversal) == int(LinearTraversal) - ? ( bool(MayUnrollCompletely) ? int(CompleteUnrolling) : int(NoUnrolling) ) - : int(NoUnrolling) - }; - -#ifdef EIGEN_DEBUG_ASSIGN - static void debug() - { - EIGEN_DEBUG_VAR(DstIsAligned) - EIGEN_DEBUG_VAR(SrcIsAligned) - EIGEN_DEBUG_VAR(JointAlignment) - EIGEN_DEBUG_VAR(InnerSize) - EIGEN_DEBUG_VAR(InnerMaxSize) - EIGEN_DEBUG_VAR(PacketSize) - EIGEN_DEBUG_VAR(StorageOrdersAgree) - EIGEN_DEBUG_VAR(MightVectorize) - EIGEN_DEBUG_VAR(MayLinearize) - EIGEN_DEBUG_VAR(MayInnerVectorize) - EIGEN_DEBUG_VAR(MayLinearVectorize) - EIGEN_DEBUG_VAR(MaySliceVectorize) - EIGEN_DEBUG_VAR(Traversal) - EIGEN_DEBUG_VAR(UnrollingLimit) - EIGEN_DEBUG_VAR(MayUnrollCompletely) - EIGEN_DEBUG_VAR(MayUnrollInner) - EIGEN_DEBUG_VAR(Unrolling) - } -#endif -}; - -/*************************************************************************** -* Part 2 : meta-unrollers -***************************************************************************/ - -/************************ -*** Default traversal *** -************************/ - -template -struct assign_DefaultTraversal_CompleteUnrolling -{ - enum { - outer = Index / Derived1::InnerSizeAtCompileTime, - inner = Index % Derived1::InnerSizeAtCompileTime - }; - - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - dst.copyCoeffByOuterInner(outer, inner, src); - assign_DefaultTraversal_CompleteUnrolling::run(dst, src); - } -}; - -template -struct assign_DefaultTraversal_CompleteUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} -}; - -template -struct assign_DefaultTraversal_InnerUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer) - { - dst.copyCoeffByOuterInner(outer, Index, src); - assign_DefaultTraversal_InnerUnrolling::run(dst, src, outer); - } -}; - -template -struct assign_DefaultTraversal_InnerUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {} -}; - -/*********************** -*** Linear traversal *** -***********************/ - -template -struct assign_LinearTraversal_CompleteUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - dst.copyCoeff(Index, src); - assign_LinearTraversal_CompleteUnrolling::run(dst, src); - } -}; - -template -struct assign_LinearTraversal_CompleteUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} -}; - -/************************** -*** Inner vectorization *** -**************************/ - -template -struct assign_innervec_CompleteUnrolling -{ - enum { - outer = Index / Derived1::InnerSizeAtCompileTime, - inner = Index % Derived1::InnerSizeAtCompileTime, - JointAlignment = assign_traits::JointAlignment - }; - - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - dst.template copyPacketByOuterInner(outer, inner, src); - assign_innervec_CompleteUnrolling::size, Stop>::run(dst, src); - } -}; - -template -struct assign_innervec_CompleteUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &) {} -}; - -template -struct assign_innervec_InnerUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src, typename Derived1::Index outer) - { - dst.template copyPacketByOuterInner(outer, Index, src); - assign_innervec_InnerUnrolling::size, Stop>::run(dst, src, outer); - } -}; - -template -struct assign_innervec_InnerUnrolling -{ - static EIGEN_STRONG_INLINE void run(Derived1 &, const Derived2 &, typename Derived1::Index) {} -}; - -/*************************************************************************** -* Part 3 : implementation of all cases -***************************************************************************/ - -template::Traversal, - int Unrolling = assign_traits::Unrolling, - int Version = Specialized> -struct assign_impl; - -/************************ -*** Default traversal *** -************************/ - -template -struct assign_impl -{ - static inline void run(Derived1 &, const Derived2 &) { } -}; - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static inline void run(Derived1 &dst, const Derived2 &src) - { - const Index innerSize = dst.innerSize(); - const Index outerSize = dst.outerSize(); - for(Index outer = 0; outer < outerSize; ++outer) - for(Index inner = 0; inner < innerSize; ++inner) - dst.copyCoeffByOuterInner(outer, inner, src); - } -}; - -template -struct assign_impl -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - assign_DefaultTraversal_CompleteUnrolling - ::run(dst, src); - } -}; - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - const Index outerSize = dst.outerSize(); - for(Index outer = 0; outer < outerSize; ++outer) - assign_DefaultTraversal_InnerUnrolling - ::run(dst, src, outer); - } -}; - -/*********************** -*** Linear traversal *** -***********************/ - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static inline void run(Derived1 &dst, const Derived2 &src) - { - const Index size = dst.size(); - for(Index i = 0; i < size; ++i) - dst.copyCoeff(i, src); - } -}; - -template -struct assign_impl -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - assign_LinearTraversal_CompleteUnrolling - ::run(dst, src); - } -}; +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/************************** -*** Inner vectorization *** -**************************/ - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static inline void run(Derived1 &dst, const Derived2 &src) - { - const Index innerSize = dst.innerSize(); - const Index outerSize = dst.outerSize(); - const Index packetSize = packet_traits::size; - for(Index outer = 0; outer < outerSize; ++outer) - for(Index inner = 0; inner < innerSize; inner+=packetSize) - dst.template copyPacketByOuterInner(outer, inner, src); - } -}; - -template -struct assign_impl -{ - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - assign_innervec_CompleteUnrolling - ::run(dst, src); - } -}; - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - const Index outerSize = dst.outerSize(); - for(Index outer = 0; outer < outerSize; ++outer) - assign_innervec_InnerUnrolling - ::run(dst, src, outer); - } -}; - -/*************************** -*** Linear vectorization *** -***************************/ - -template -struct unaligned_assign_impl -{ - template - static EIGEN_STRONG_INLINE void run(const Derived&, OtherDerived&, typename Derived::Index, typename Derived::Index) {} -}; - -template <> -struct unaligned_assign_impl -{ - // MSVC must not inline this functions. If it does, it fails to optimize the - // packet access path. -#ifdef _MSC_VER - template - static EIGEN_DONT_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end) -#else - template - static EIGEN_STRONG_INLINE void run(const Derived& src, OtherDerived& dst, typename Derived::Index start, typename Derived::Index end) -#endif - { - for (typename Derived::Index index = start; index < end; ++index) - dst.copyCoeff(index, src); - } -}; - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - const Index size = dst.size(); - typedef packet_traits PacketTraits; - enum { - packetSize = PacketTraits::size, - dstAlignment = PacketTraits::AlignedOnScalar ? Aligned : int(assign_traits::DstIsAligned) , - srcAlignment = assign_traits::JointAlignment - }; - const Index alignedStart = assign_traits::DstIsAligned ? 0 - : internal::first_aligned(&dst.coeffRef(0), size); - const Index alignedEnd = alignedStart + ((size-alignedStart)/packetSize)*packetSize; - - unaligned_assign_impl::DstIsAligned!=0>::run(src,dst,0,alignedStart); - - for(Index index = alignedStart; index < alignedEnd; index += packetSize) - { - dst.template copyPacket(index, src); - } - - unaligned_assign_impl<>::run(src,dst,alignedEnd,size); - } -}; - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static EIGEN_STRONG_INLINE void run(Derived1 &dst, const Derived2 &src) - { - enum { size = Derived1::SizeAtCompileTime, - packetSize = packet_traits::size, - alignedSize = (size/packetSize)*packetSize }; - - assign_innervec_CompleteUnrolling::run(dst, src); - assign_DefaultTraversal_CompleteUnrolling::run(dst, src); - } -}; - -/************************** -*** Slice vectorization *** -***************************/ - -template -struct assign_impl -{ - typedef typename Derived1::Index Index; - static inline void run(Derived1 &dst, const Derived2 &src) - { - typedef typename Derived1::Scalar Scalar; - typedef packet_traits PacketTraits; - enum { - packetSize = PacketTraits::size, - alignable = PacketTraits::AlignedOnScalar, - dstIsAligned = assign_traits::DstIsAligned, - dstAlignment = alignable ? Aligned : int(dstIsAligned), - srcAlignment = assign_traits::JointAlignment - }; - const Scalar *dst_ptr = &dst.coeffRef(0,0); - if((!bool(dstIsAligned)) && (size_t(dst_ptr) % sizeof(Scalar))>0) - { - // the pointer is not aligend-on scalar, so alignment is not possible - return assign_impl::run(dst, src); - } - const Index packetAlignedMask = packetSize - 1; - const Index innerSize = dst.innerSize(); - const Index outerSize = dst.outerSize(); - const Index alignedStep = alignable ? (packetSize - dst.outerStride() % packetSize) & packetAlignedMask : 0; - Index alignedStart = ((!alignable) || bool(dstIsAligned)) ? 0 : internal::first_aligned(dst_ptr, innerSize); - - for(Index outer = 0; outer < outerSize; ++outer) - { - const Index alignedEnd = alignedStart + ((innerSize-alignedStart) & ~packetAlignedMask); - // do the non-vectorizable part of the assignment - for(Index inner = 0; inner(outer, inner, src); - - // do the non-vectorizable part of the assignment - for(Index inner = alignedEnd; inner((alignedStart+alignedStep)%packetSize, innerSize); - } - } -}; - -} // end namespace internal - -/*************************************************************************** -* Part 4 : implementation of DenseBase methods -***************************************************************************/ +namespace Eigen { -template -template -EIGEN_STRONG_INLINE Derived& DenseBase - ::lazyAssign(const DenseBase& other) -{ - enum{ - SameType = internal::is_same::value - }; +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::lazyAssign(const DenseBase& other) { + enum { SameType = internal::is_same::value }; EIGEN_STATIC_ASSERT_LVALUE(Derived) - EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived,OtherDerived) - EIGEN_STATIC_ASSERT(SameType,YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Derived, OtherDerived) + EIGEN_STATIC_ASSERT( + SameType, + YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) -#ifdef EIGEN_DEBUG_ASSIGN - internal::assign_traits::debug(); -#endif eigen_assert(rows() == other.rows() && cols() == other.cols()); - internal::assign_impl::Traversal) - : int(InvalidTraversal)>::run(derived(),other.derived()); -#ifndef EIGEN_NO_DEBUG - checkTransposeAliasing(other.derived()); -#endif + internal::call_assignment_no_alias(derived(), other.derived()); + return derived(); } -namespace internal { - -template::Flags) & EvalBeforeAssigningBit) != 0, - bool NeedToTranspose = ((int(Derived::RowsAtCompileTime) == 1 && int(OtherDerived::ColsAtCompileTime) == 1) - | // FIXME | instead of || to please GCC 4.4.0 stupid warning "suggest parentheses around &&". - // revert to || as soon as not needed anymore. - (int(Derived::ColsAtCompileTime) == 1 && int(OtherDerived::RowsAtCompileTime) == 1)) - && int(Derived::SizeAtCompileTime) != 1> -struct assign_selector; - -template -struct assign_selector { - static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.derived()); } - template - static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { other.evalTo(dst); return dst; } -}; -template -struct assign_selector { - static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.eval()); } -}; -template -struct assign_selector { - static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose()); } - template - static EIGEN_STRONG_INLINE Derived& evalTo(ActualDerived& dst, const ActualOtherDerived& other) { Transpose dstTrans(dst); other.evalTo(dstTrans); return dst; } -}; -template -struct assign_selector { - static EIGEN_STRONG_INLINE Derived& run(Derived& dst, const OtherDerived& other) { return dst.lazyAssign(other.transpose().eval()); } -}; - -} // end namespace internal - -template -template -EIGEN_STRONG_INLINE Derived& DenseBase::operator=(const DenseBase& other) -{ - return internal::assign_selector::run(derived(), other.derived()); +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::operator=(const DenseBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); } -template -EIGEN_STRONG_INLINE Derived& DenseBase::operator=(const DenseBase& other) -{ - return internal::assign_selector::run(derived(), other.derived()); +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::operator=(const DenseBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); } -template -EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const MatrixBase& other) -{ - return internal::assign_selector::run(derived(), other.derived()); +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const MatrixBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); } -template +template template -EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const DenseBase& other) -{ - return internal::assign_selector::run(derived(), other.derived()); +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const DenseBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); } -template +template template -EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const EigenBase& other) -{ - return internal::assign_selector::evalTo(derived(), other.derived()); +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const EigenBase& other) { + internal::call_assignment(derived(), other.derived()); + return derived(); } -template -template -EIGEN_STRONG_INLINE Derived& MatrixBase::operator=(const ReturnByValue& other) -{ - return internal::assign_selector::evalTo(derived(), other.derived()); +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator=( + const ReturnByValue& other) { + other.derived().evalTo(derived()); + return derived(); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_ASSIGN_H +#endif // EIGEN_ASSIGN_H diff --git a/inst/include/Eigen/src/Core/AssignEvaluator.h b/inst/include/Eigen/src/Core/AssignEvaluator.h new file mode 100644 index 00000000..36f0a9d7 --- /dev/null +++ b/inst/include/Eigen/src/Core/AssignEvaluator.h @@ -0,0 +1,1057 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Benoit Jacob +// Copyright (C) 2011-2014 Gael Guennebaud +// Copyright (C) 2011-2012 Jitse Niesen +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_ASSIGN_EVALUATOR_H +#define EIGEN_ASSIGN_EVALUATOR_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +// This implementation is based on Assign.h + +namespace internal { + +/*************************************************************************** + * Part 1 : the logic deciding a strategy for traversal and unrolling * + ***************************************************************************/ + +// copy_using_evaluator_traits is based on assign_traits + +template +struct copy_using_evaluator_traits { + using Src = typename SrcEvaluator::XprType; + using Dst = typename DstEvaluator::XprType; + using DstScalar = typename Dst::Scalar; + + static constexpr int DstFlags = DstEvaluator::Flags; + static constexpr int SrcFlags = SrcEvaluator::Flags; + + public: + static constexpr int DstAlignment = DstEvaluator::Alignment; + static constexpr int SrcAlignment = SrcEvaluator::Alignment; + static constexpr int JointAlignment = plain_enum_min(DstAlignment, SrcAlignment); + static constexpr bool DstHasDirectAccess = bool(DstFlags & DirectAccessBit); + static constexpr bool SrcIsRowMajor = bool(SrcFlags & RowMajorBit); + static constexpr bool DstIsRowMajor = bool(DstFlags & RowMajorBit); + static constexpr bool IsVectorAtCompileTime = Dst::IsVectorAtCompileTime; + static constexpr int RowsAtCompileTime = size_prefer_fixed(Src::RowsAtCompileTime, Dst::RowsAtCompileTime); + static constexpr int ColsAtCompileTime = size_prefer_fixed(Src::ColsAtCompileTime, Dst::ColsAtCompileTime); + static constexpr int SizeAtCompileTime = size_at_compile_time(RowsAtCompileTime, ColsAtCompileTime); + static constexpr int MaxRowsAtCompileTime = + min_size_prefer_fixed(Src::MaxRowsAtCompileTime, Dst::MaxRowsAtCompileTime); + static constexpr int MaxColsAtCompileTime = + min_size_prefer_fixed(Src::MaxColsAtCompileTime, Dst::MaxColsAtCompileTime); + static constexpr int MaxSizeAtCompileTime = + min_size_prefer_fixed(Src::MaxSizeAtCompileTime, Dst::MaxSizeAtCompileTime); + static constexpr int InnerSizeAtCompileTime = IsVectorAtCompileTime ? SizeAtCompileTime + : DstIsRowMajor ? ColsAtCompileTime + : RowsAtCompileTime; + static constexpr int MaxInnerSizeAtCompileTime = IsVectorAtCompileTime ? MaxSizeAtCompileTime + : DstIsRowMajor ? MaxColsAtCompileTime + : MaxRowsAtCompileTime; + static constexpr int RestrictedInnerSize = min_size_prefer_fixed(MaxInnerSizeAtCompileTime, MaxPacketSize); + static constexpr int RestrictedLinearSize = min_size_prefer_fixed(MaxSizeAtCompileTime, MaxPacketSize); + static constexpr int OuterStride = outer_stride_at_compile_time::ret; + + // TODO distinguish between linear traversal and inner-traversals + using LinearPacketType = typename find_best_packet::type; + using InnerPacketType = typename find_best_packet::type; + + static constexpr int LinearPacketSize = unpacket_traits::size; + static constexpr int InnerPacketSize = unpacket_traits::size; + + public: + static constexpr int LinearRequiredAlignment = unpacket_traits::alignment; + static constexpr int InnerRequiredAlignment = unpacket_traits::alignment; + + private: + static constexpr bool StorageOrdersAgree = DstIsRowMajor == SrcIsRowMajor; + static constexpr bool MightVectorize = StorageOrdersAgree && bool(DstFlags & SrcFlags & ActualPacketAccessBit) && + bool(functor_traits::PacketAccess); + static constexpr bool MayInnerVectorize = MightVectorize && (InnerSizeAtCompileTime != Dynamic) && + (InnerSizeAtCompileTime % InnerPacketSize == 0) && + (OuterStride != Dynamic) && (OuterStride % InnerPacketSize == 0) && + (EIGEN_UNALIGNED_VECTORIZE || JointAlignment >= InnerRequiredAlignment); + static constexpr bool MayLinearize = StorageOrdersAgree && (DstFlags & SrcFlags & LinearAccessBit); + static constexpr bool MayLinearVectorize = + MightVectorize && MayLinearize && DstHasDirectAccess && + (EIGEN_UNALIGNED_VECTORIZE || (DstAlignment >= LinearRequiredAlignment) || MaxSizeAtCompileTime == Dynamic) && + (MaxSizeAtCompileTime == Dynamic || MaxSizeAtCompileTime >= LinearPacketSize); + /* If the destination isn't aligned, we have to do runtime checks and we don't unroll, + so it's only good for large enough sizes. */ + static constexpr int InnerSizeThreshold = (EIGEN_UNALIGNED_VECTORIZE ? 1 : 3) * InnerPacketSize; + static constexpr bool MaySliceVectorize = + MightVectorize && DstHasDirectAccess && + (MaxInnerSizeAtCompileTime == Dynamic || MaxInnerSizeAtCompileTime >= InnerSizeThreshold); + /* slice vectorization can be slow, so we only want it if the slices are big, which is + indicated by InnerMaxSize rather than InnerSize, think of the case of a dynamic block + in a fixed-size matrix + However, with EIGEN_UNALIGNED_VECTORIZE and unrolling, slice vectorization is still worth it */ + + public: + static constexpr int Traversal = SizeAtCompileTime == 0 ? AllAtOnceTraversal + : (MayLinearVectorize && (LinearPacketSize > InnerPacketSize)) + ? LinearVectorizedTraversal + : MayInnerVectorize ? InnerVectorizedTraversal + : MayLinearVectorize ? LinearVectorizedTraversal + : MaySliceVectorize ? SliceVectorizedTraversal + : MayLinearize ? LinearTraversal + : DefaultTraversal; + static constexpr bool Vectorized = Traversal == InnerVectorizedTraversal || Traversal == LinearVectorizedTraversal || + Traversal == SliceVectorizedTraversal; + + using PacketType = std::conditional_t; + + private: + static constexpr int ActualPacketSize = Vectorized ? unpacket_traits::size : 1; + static constexpr int UnrollingLimit = EIGEN_UNROLLING_LIMIT * ActualPacketSize; + static constexpr int CoeffReadCost = int(DstEvaluator::CoeffReadCost) + int(SrcEvaluator::CoeffReadCost); + static constexpr bool MayUnrollCompletely = + (SizeAtCompileTime != Dynamic) && (SizeAtCompileTime * CoeffReadCost <= UnrollingLimit); + static constexpr bool MayUnrollInner = + (InnerSizeAtCompileTime != Dynamic) && (InnerSizeAtCompileTime * CoeffReadCost <= UnrollingLimit); + + public: + static constexpr int Unrolling = + (Traversal == InnerVectorizedTraversal || Traversal == DefaultTraversal) + ? (MayUnrollCompletely ? CompleteUnrolling + : MayUnrollInner ? InnerUnrolling + : NoUnrolling) + : Traversal == LinearVectorizedTraversal + ? (MayUnrollCompletely && (EIGEN_UNALIGNED_VECTORIZE || (DstAlignment >= LinearRequiredAlignment)) + ? CompleteUnrolling + : NoUnrolling) + : Traversal == LinearTraversal ? (MayUnrollCompletely ? CompleteUnrolling : NoUnrolling) +#if EIGEN_UNALIGNED_VECTORIZE + : Traversal == SliceVectorizedTraversal ? (MayUnrollInner ? InnerUnrolling : NoUnrolling) +#endif + : NoUnrolling; + static constexpr bool UsePacketSegment = has_packet_segment::value; + +#ifdef EIGEN_DEBUG_ASSIGN + static void debug() { + std::cerr << "DstXpr: " << typeid(typename DstEvaluator::XprType).name() << std::endl; + std::cerr << "SrcXpr: " << typeid(typename SrcEvaluator::XprType).name() << std::endl; + std::cerr.setf(std::ios::hex, std::ios::basefield); + std::cerr << "DstFlags" + << " = " << DstFlags << " (" << demangle_flags(DstFlags) << " )" << std::endl; + std::cerr << "SrcFlags" + << " = " << SrcFlags << " (" << demangle_flags(SrcFlags) << " )" << std::endl; + std::cerr.unsetf(std::ios::hex); + EIGEN_DEBUG_VAR(DstAlignment) + EIGEN_DEBUG_VAR(SrcAlignment) + EIGEN_DEBUG_VAR(LinearRequiredAlignment) + EIGEN_DEBUG_VAR(InnerRequiredAlignment) + EIGEN_DEBUG_VAR(JointAlignment) + EIGEN_DEBUG_VAR(InnerSizeAtCompileTime) + EIGEN_DEBUG_VAR(MaxInnerSizeAtCompileTime) + EIGEN_DEBUG_VAR(LinearPacketSize) + EIGEN_DEBUG_VAR(InnerPacketSize) + EIGEN_DEBUG_VAR(ActualPacketSize) + EIGEN_DEBUG_VAR(StorageOrdersAgree) + EIGEN_DEBUG_VAR(MightVectorize) + EIGEN_DEBUG_VAR(MayLinearize) + EIGEN_DEBUG_VAR(MayInnerVectorize) + EIGEN_DEBUG_VAR(MayLinearVectorize) + EIGEN_DEBUG_VAR(MaySliceVectorize) + std::cerr << "Traversal" + << " = " << Traversal << " (" << demangle_traversal(Traversal) << ")" << std::endl; + EIGEN_DEBUG_VAR(SrcEvaluator::CoeffReadCost) + EIGEN_DEBUG_VAR(DstEvaluator::CoeffReadCost) + EIGEN_DEBUG_VAR(Dst::SizeAtCompileTime) + EIGEN_DEBUG_VAR(UnrollingLimit) + EIGEN_DEBUG_VAR(MayUnrollCompletely) + EIGEN_DEBUG_VAR(MayUnrollInner) + std::cerr << "Unrolling" + << " = " << Unrolling << " (" << demangle_unrolling(Unrolling) << ")" << std::endl; + std::cerr << std::endl; + } +#endif +}; + +/*************************************************************************** + * Part 2 : meta-unrollers + ***************************************************************************/ + +/************************ +*** Default traversal *** +************************/ + +template +struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling { + static constexpr int Outer = Index_ / Kernel::AssignmentTraits::InnerSizeAtCompileTime; + static constexpr int Inner = Index_ % Kernel::AssignmentTraits::InnerSizeAtCompileTime; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + kernel.assignCoeffByOuterInner(Outer, Inner); + copy_using_evaluator_DefaultTraversal_CompleteUnrolling::run(kernel); + } +}; + +template +struct copy_using_evaluator_DefaultTraversal_CompleteUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +template +struct copy_using_evaluator_DefaultTraversal_InnerUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer) { + kernel.assignCoeffByOuterInner(outer, Index_); + copy_using_evaluator_DefaultTraversal_InnerUnrolling::run(kernel, outer); + } +}; + +template +struct copy_using_evaluator_DefaultTraversal_InnerUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {} +}; + +/*********************** +*** Linear traversal *** +***********************/ + +template +struct copy_using_evaluator_LinearTraversal_CompleteUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + kernel.assignCoeff(Index_); + copy_using_evaluator_LinearTraversal_CompleteUnrolling::run(kernel); + } +}; + +template +struct copy_using_evaluator_LinearTraversal_CompleteUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +/************************** +*** Inner vectorization *** +**************************/ + +template +struct copy_using_evaluator_innervec_CompleteUnrolling { + using PacketType = typename Kernel::PacketType; + static constexpr int Outer = Index_ / Kernel::AssignmentTraits::InnerSizeAtCompileTime; + static constexpr int Inner = Index_ % Kernel::AssignmentTraits::InnerSizeAtCompileTime; + static constexpr int NextIndex = Index_ + unpacket_traits::size; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment; + static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) { + kernel.template assignPacketByOuterInner(Outer, Inner); + copy_using_evaluator_innervec_CompleteUnrolling::run(kernel); + } +}; + +template +struct copy_using_evaluator_innervec_CompleteUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +template +struct copy_using_evaluator_innervec_InnerUnrolling { + using PacketType = typename Kernel::PacketType; + static constexpr int NextIndex = Index_ + unpacket_traits::size; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel, Index outer) { + kernel.template assignPacketByOuterInner(outer, Index_); + copy_using_evaluator_innervec_InnerUnrolling::run(kernel, + outer); + } +}; + +template +struct copy_using_evaluator_innervec_InnerUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {} +}; + +template +struct copy_using_evaluator_innervec_segment { + using PacketType = typename Kernel::PacketType; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel, Index outer) { + kernel.template assignPacketSegmentByOuterInner(outer, Start, 0, + Stop - Start); + } +}; + +template +struct copy_using_evaluator_innervec_segment + : copy_using_evaluator_DefaultTraversal_InnerUnrolling {}; + +template +struct copy_using_evaluator_innervec_segment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {} +}; + +template +struct copy_using_evaluator_innervec_segment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&, Index) {} +}; + +/*************************************************************************** + * Part 3 : implementation of all cases + ***************************************************************************/ + +// dense_assignment_loop is based on assign_impl + +template +struct dense_assignment_loop_impl; + +template +struct dense_assignment_loop { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { +#ifdef __cpp_lib_is_constant_evaluated + if (internal::is_constant_evaluated()) + dense_assignment_loop_impl::run(kernel); + else +#endif + dense_assignment_loop_impl::run(kernel); + } +}; + +/************************ +***** Special Cases ***** +************************/ + +// Zero-sized assignment is a no-op. +template +struct dense_assignment_loop_impl { + static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime; + + EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE constexpr run(Kernel& /*kernel*/) { + EIGEN_STATIC_ASSERT(SizeAtCompileTime == 0, EIGEN_INTERNAL_ERROR_PLEASE_FILE_A_BUG_REPORT) + } +}; + +/************************ +*** Default traversal *** +************************/ + +template +struct dense_assignment_loop_impl { + EIGEN_DEVICE_FUNC static void EIGEN_STRONG_INLINE constexpr run(Kernel& kernel) { + for (Index outer = 0; outer < kernel.outerSize(); ++outer) { + for (Index inner = 0; inner < kernel.innerSize(); ++inner) { + kernel.assignCoeffByOuterInner(outer, inner); + } + } + } +}; + +template +struct dense_assignment_loop_impl { + static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + copy_using_evaluator_DefaultTraversal_CompleteUnrolling::run(kernel); + } +}; + +template +struct dense_assignment_loop_impl { + static constexpr int InnerSizeAtCompileTime = Kernel::AssignmentTraits::InnerSizeAtCompileTime; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + const Index outerSize = kernel.outerSize(); + for (Index outer = 0; outer < outerSize; ++outer) + copy_using_evaluator_DefaultTraversal_InnerUnrolling::run(kernel, outer); + } +}; + +/*************************** +*** Linear vectorization *** +***************************/ + +// The goal of unaligned_dense_assignment_loop is simply to factorize the handling +// of the non vectorizable beginning and ending parts + +template +struct unaligned_dense_assignment_loop { + // if Skip == true, then do nothing + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& /*kernel*/, Index /*start*/, Index /*end*/) {} + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& /*kernel*/, Index /*outer*/, + Index /*innerStart*/, Index /*innerEnd*/) {} +}; + +template +struct unaligned_dense_assignment_loop { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index start, Index end) { + Index count = end - start; + eigen_assert(count <= unpacket_traits::size); + if (count > 0) kernel.template assignPacketSegment(start, 0, count); + } + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer, Index start, Index end) { + Index count = end - start; + eigen_assert(count <= unpacket_traits::size); + if (count > 0) + kernel.template assignPacketSegmentByOuterInner(outer, start, 0, count); + } +}; + +template +struct unaligned_dense_assignment_loop { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index start, Index end) { + for (Index index = start; index < end; ++index) kernel.assignCoeff(index); + } + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Index outer, Index innerStart, + Index innerEnd) { + for (Index inner = innerStart; inner < innerEnd; ++inner) kernel.assignCoeffByOuterInner(outer, inner); + } +}; + +template +struct copy_using_evaluator_linearvec_CompleteUnrolling { + using PacketType = typename Kernel::PacketType; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment; + static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment; + static constexpr int NextIndex = Index_ + unpacket_traits::size; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) { + kernel.template assignPacket(Index_); + copy_using_evaluator_linearvec_CompleteUnrolling::run(kernel); + } +}; + +template +struct copy_using_evaluator_linearvec_CompleteUnrolling { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +template +struct copy_using_evaluator_linearvec_segment { + using PacketType = typename Kernel::PacketType; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment; + static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) { + kernel.template assignPacketSegment(Index_, 0, Stop - Index_); + } +}; + +template +struct copy_using_evaluator_linearvec_segment + : copy_using_evaluator_LinearTraversal_CompleteUnrolling {}; + +template +struct copy_using_evaluator_linearvec_segment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +template +struct copy_using_evaluator_linearvec_segment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel&) {} +}; + +template +struct dense_assignment_loop_impl { + using Scalar = typename Kernel::Scalar; + using PacketType = typename Kernel::PacketType; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment; + static constexpr int DstAlignment = plain_enum_max(Kernel::AssignmentTraits::DstAlignment, alignof(Scalar)); + static constexpr int RequestedAlignment = unpacket_traits::alignment; + static constexpr bool Alignable = + (DstAlignment >= RequestedAlignment) || ((RequestedAlignment - DstAlignment) % sizeof(Scalar) == 0); + static constexpr int Alignment = Alignable ? RequestedAlignment : DstAlignment; + static constexpr bool DstIsAligned = DstAlignment >= Alignment; + static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment; + + using head_loop = + unaligned_dense_assignment_loop; + using tail_loop = unaligned_dense_assignment_loop; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + const Index size = kernel.size(); + const Index alignedStart = DstIsAligned ? 0 : first_aligned(kernel.dstDataPtr(), size); + const Index alignedEnd = alignedStart + numext::round_down(size - alignedStart, PacketSize); + + head_loop::run(kernel, 0, alignedStart); + + for (Index index = alignedStart; index < alignedEnd; index += PacketSize) + kernel.template assignPacket(index); + + tail_loop::run(kernel, alignedEnd, size); + } +}; + +template +struct dense_assignment_loop_impl { + using PacketType = typename Kernel::PacketType; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int Size = Kernel::AssignmentTraits::SizeAtCompileTime; + static constexpr int AlignedSize = numext::round_down(Size, PacketSize); + static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + copy_using_evaluator_linearvec_CompleteUnrolling::run(kernel); + copy_using_evaluator_linearvec_segment::run(kernel); + } +}; + +/************************** +*** Inner vectorization *** +**************************/ + +template +struct dense_assignment_loop_impl { + using PacketType = typename Kernel::PacketType; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment; + static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + const Index innerSize = kernel.innerSize(); + const Index outerSize = kernel.outerSize(); + for (Index outer = 0; outer < outerSize; ++outer) + for (Index inner = 0; inner < innerSize; inner += PacketSize) + kernel.template assignPacketByOuterInner(outer, inner); + } +}; + +template +struct dense_assignment_loop_impl { + static constexpr int SizeAtCompileTime = Kernel::AssignmentTraits::SizeAtCompileTime; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) { + copy_using_evaluator_innervec_CompleteUnrolling::run(kernel); + } +}; + +template +struct dense_assignment_loop_impl { + static constexpr int InnerSize = Kernel::AssignmentTraits::InnerSizeAtCompileTime; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::SrcAlignment; + static constexpr int DstAlignment = Kernel::AssignmentTraits::DstAlignment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(Kernel& kernel) { + const Index outerSize = kernel.outerSize(); + for (Index outer = 0; outer < outerSize; ++outer) + copy_using_evaluator_innervec_InnerUnrolling::run(kernel, + outer); + } +}; + +/*********************** +*** Linear traversal *** +***********************/ + +template +struct dense_assignment_loop_impl { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + const Index size = kernel.size(); + for (Index i = 0; i < size; ++i) kernel.assignCoeff(i); + } +}; + +template +struct dense_assignment_loop_impl { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + copy_using_evaluator_LinearTraversal_CompleteUnrolling::run( + kernel); + } +}; + +/************************** +*** Slice vectorization *** +***************************/ + +template +struct dense_assignment_loop_impl { + using Scalar = typename Kernel::Scalar; + using PacketType = typename Kernel::PacketType; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int SrcAlignment = Kernel::AssignmentTraits::JointAlignment; + static constexpr int DstAlignment = plain_enum_max(Kernel::AssignmentTraits::DstAlignment, alignof(Scalar)); + static constexpr int RequestedAlignment = unpacket_traits::alignment; + static constexpr bool Alignable = + (DstAlignment >= RequestedAlignment) || ((RequestedAlignment - DstAlignment) % sizeof(Scalar) == 0); + static constexpr int Alignment = Alignable ? RequestedAlignment : DstAlignment; + static constexpr bool DstIsAligned = DstAlignment >= Alignment; + static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment; + + using head_loop = unaligned_dense_assignment_loop; + using tail_loop = unaligned_dense_assignment_loop; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + const Scalar* dst_ptr = kernel.dstDataPtr(); + const Index innerSize = kernel.innerSize(); + const Index outerSize = kernel.outerSize(); + const Index alignedStep = Alignable ? (PacketSize - kernel.outerStride() % PacketSize) % PacketSize : 0; + Index alignedStart = ((!Alignable) || DstIsAligned) ? 0 : internal::first_aligned(dst_ptr, innerSize); + + for (Index outer = 0; outer < outerSize; ++outer) { + const Index alignedEnd = alignedStart + numext::round_down(innerSize - alignedStart, PacketSize); + + head_loop::run(kernel, outer, 0, alignedStart); + + // do the vectorizable part of the assignment + for (Index inner = alignedStart; inner < alignedEnd; inner += PacketSize) + kernel.template assignPacketByOuterInner(outer, inner); + + tail_loop::run(kernel, outer, alignedEnd, innerSize); + + alignedStart = numext::mini((alignedStart + alignedStep) % PacketSize, innerSize); + } + } +}; + +#if EIGEN_UNALIGNED_VECTORIZE +template +struct dense_assignment_loop_impl { + using PacketType = typename Kernel::PacketType; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int InnerSize = Kernel::AssignmentTraits::InnerSizeAtCompileTime; + static constexpr int VectorizableSize = numext::round_down(InnerSize, PacketSize); + static constexpr bool UsePacketSegment = Kernel::AssignmentTraits::UsePacketSegment; + + using packet_loop = copy_using_evaluator_innervec_InnerUnrolling; + using packet_segment_loop = copy_using_evaluator_innervec_segment; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel) { + for (Index outer = 0; outer < kernel.outerSize(); ++outer) { + packet_loop::run(kernel, outer); + packet_segment_loop::run(kernel, outer); + } + } +}; +#endif + +/*************************************************************************** + * Part 4 : Generic dense assignment kernel + ***************************************************************************/ + +// This class generalize the assignment of a coefficient (or packet) from one dense evaluator +// to another dense writable evaluator. +// It is parametrized by the two evaluators, and the actual assignment functor. +// This abstraction level permits to keep the evaluation loops as simple and as generic as possible. +// One can customize the assignment using this generic dense_assignment_kernel with different +// functors, or by completely overloading it, by-passing a functor. +template +class generic_dense_assignment_kernel { + protected: + typedef typename DstEvaluatorTypeT::XprType DstXprType; + typedef typename SrcEvaluatorTypeT::XprType SrcXprType; + + public: + typedef DstEvaluatorTypeT DstEvaluatorType; + typedef SrcEvaluatorTypeT SrcEvaluatorType; + typedef typename DstEvaluatorType::Scalar Scalar; + typedef copy_using_evaluator_traits AssignmentTraits; + typedef typename AssignmentTraits::PacketType PacketType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr generic_dense_assignment_kernel(DstEvaluatorType& dst, + const SrcEvaluatorType& src, + const Functor& func, + DstXprType& dstExpr) + : m_dst(dst), m_src(src), m_functor(func), m_dstExpr(dstExpr) { +#ifdef EIGEN_DEBUG_ASSIGN + AssignmentTraits::debug(); +#endif + } + + EIGEN_DEVICE_FUNC constexpr Index size() const noexcept { return m_dstExpr.size(); } + EIGEN_DEVICE_FUNC constexpr Index innerSize() const noexcept { return m_dstExpr.innerSize(); } + EIGEN_DEVICE_FUNC constexpr Index outerSize() const noexcept { return m_dstExpr.outerSize(); } + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_dstExpr.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_dstExpr.cols(); } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_dstExpr.outerStride(); } + + EIGEN_DEVICE_FUNC DstEvaluatorType& dstEvaluator() noexcept { return m_dst; } + EIGEN_DEVICE_FUNC const SrcEvaluatorType& srcEvaluator() const noexcept { return m_src; } + + /// Assign src(row,col) to dst(row,col) through the assignment functor. + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void assignCoeff(Index row, Index col) { + m_functor.assignCoeff(m_dst.coeffRef(row, col), m_src.coeff(row, col)); + } + + /// \sa assignCoeff(Index,Index) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignCoeff(Index index) { + m_functor.assignCoeff(m_dst.coeffRef(index), m_src.coeff(index)); + } + + /// \sa assignCoeff(Index,Index) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void assignCoeffByOuterInner(Index outer, Index inner) { + Index row = rowIndexByOuterInner(outer, inner); + Index col = colIndexByOuterInner(outer, inner); + assignCoeff(row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index row, Index col) { + m_functor.template assignPacket(&m_dst.coeffRef(row, col), + m_src.template packet(row, col)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacket(Index index) { + m_functor.template assignPacket(&m_dst.coeffRef(index), m_src.template packet(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketByOuterInner(Index outer, Index inner) { + Index row = rowIndexByOuterInner(outer, inner); + Index col = colIndexByOuterInner(outer, inner); + assignPacket(row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegment(Index row, Index col, Index begin, Index count) { + m_functor.template assignPacketSegment( + &m_dst.coeffRef(row, col), m_src.template packetSegment(row, col, begin, count), begin, + count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegment(Index index, Index begin, Index count) { + m_functor.template assignPacketSegment( + &m_dst.coeffRef(index), m_src.template packetSegment(index, begin, count), begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void assignPacketSegmentByOuterInner(Index outer, Index inner, Index begin, + Index count) { + Index row = rowIndexByOuterInner(outer, inner); + Index col = colIndexByOuterInner(outer, inner); + assignPacketSegment(row, col, begin, count); + } + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr Index rowIndexByOuterInner(Index outer, Index inner) { + typedef typename DstEvaluatorType::ExpressionTraits Traits; + return int(Traits::RowsAtCompileTime) == 1 ? 0 + : int(Traits::ColsAtCompileTime) == 1 ? inner + : int(DstEvaluatorType::Flags) & RowMajorBit ? outer + : inner; + } + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr Index colIndexByOuterInner(Index outer, Index inner) { + typedef typename DstEvaluatorType::ExpressionTraits Traits; + return int(Traits::ColsAtCompileTime) == 1 ? 0 + : int(Traits::RowsAtCompileTime) == 1 ? inner + : int(DstEvaluatorType::Flags) & RowMajorBit ? inner + : outer; + } + + EIGEN_DEVICE_FUNC const Scalar* dstDataPtr() const { return m_dstExpr.data(); } + + protected: + DstEvaluatorType& m_dst; + const SrcEvaluatorType& m_src; + const Functor& m_functor; + // TODO find a way to avoid the needs of the original expression + DstXprType& m_dstExpr; +}; + +// Special kernel used when computing small products whose operands have dynamic dimensions. It ensures that the +// PacketSize used is no larger than 4, thereby increasing the chance that vectorized instructions will be used +// when computing the product. + +template +class restricted_packet_dense_assignment_kernel + : public generic_dense_assignment_kernel { + protected: + typedef generic_dense_assignment_kernel Base; + + public: + typedef typename Base::Scalar Scalar; + typedef typename Base::DstXprType DstXprType; + typedef copy_using_evaluator_traits AssignmentTraits; + typedef typename AssignmentTraits::PacketType PacketType; + + EIGEN_DEVICE_FUNC restricted_packet_dense_assignment_kernel(DstEvaluatorTypeT& dst, const SrcEvaluatorTypeT& src, + const Functor& func, DstXprType& dstExpr) + : Base(dst, src, func, dstExpr) {} +}; + +/*************************************************************************** + * Part 5 : Entry point for dense rectangular assignment + ***************************************************************************/ + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize_if_allowed(DstXprType& dst, const SrcXprType& src, + const Functor& /*func*/) { + EIGEN_ONLY_USED_FOR_DEBUG(dst); + EIGEN_ONLY_USED_FOR_DEBUG(src); + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize_if_allowed(DstXprType& dst, const SrcXprType& src, + const internal::assign_op& /*func*/) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if (((dst.rows() != dstRows) || (dst.cols() != dstCols))) dst.resize(dstRows, dstCols); + eigen_assert(dst.rows() == dstRows && dst.cols() == dstCols); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, + const Functor& func) { + typedef evaluator DstEvaluatorType; + typedef evaluator SrcEvaluatorType; + + SrcEvaluatorType srcEvaluator(src); + + // NOTE To properly handle A = (A*A.transpose())/s with A rectangular, + // we need to resize the destination after the source evaluator has been created. + resize_if_allowed(dst, src, func); + + DstEvaluatorType dstEvaluator(dst); + + typedef generic_dense_assignment_kernel Kernel; + Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived()); + + dense_assignment_loop::run(kernel); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src) { + call_dense_assignment_loop(dst, src, internal::assign_op()); +} + +/*************************************************************************** + * Part 6 : Generic assignment + ***************************************************************************/ + +// Based on the respective shapes of the destination and source, +// the class AssignmentKind determine the kind of assignment mechanism. +// AssignmentKind must define a Kind typedef. +template +struct AssignmentKind; + +// Assignment kind defined in this file: +struct Dense2Dense {}; +struct EigenBase2EigenBase {}; + +template +struct AssignmentKind { + typedef EigenBase2EigenBase Kind; +}; +template <> +struct AssignmentKind { + typedef Dense2Dense Kind; +}; + +// This is the main assignment class +template ::Shape, + typename evaluator_traits::Shape>::Kind, + typename EnableIf = void> +struct Assignment; + +// The only purpose of this call_assignment() function is to deal with noalias() / "assume-aliasing" and automatic +// transposition. Indeed, I (Gael) think that this concept of "assume-aliasing" was a mistake, and it makes thing quite +// complicated. So this intermediate function removes everything related to "assume-aliasing" such that Assignment does +// not has to bother about these annoying details. + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(Dst& dst, const Src& src) { + call_assignment(dst, src, internal::assign_op()); +} +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_assignment(const Dst& dst, const Src& src) { + call_assignment(dst, src, internal::assign_op()); +} + +// Deal with "assume-aliasing" +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment( + Dst& dst, const Src& src, const Func& func, std::enable_if_t::value, void*> = 0) { + typename plain_matrix_type::type tmp(src); + call_assignment_no_alias(dst, tmp, func); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment( + Dst& dst, const Src& src, const Func& func, std::enable_if_t::value, void*> = 0) { + call_assignment_no_alias(dst, src, func); +} + +// by-pass "assume-aliasing" +// When there is no aliasing, we require that 'dst' has been properly resized +template class StorageBase, typename Src, typename Func> +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment(NoAlias& dst, const Src& src, + const Func& func) { + call_assignment_no_alias(dst.expression(), src, func); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(Dst& dst, const Src& src, + const Func& func) { + enum { + NeedToTranspose = ((int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1) || + (int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)) && + int(Dst::SizeAtCompileTime) != 1 + }; + + typedef std::conditional_t, Dst> ActualDstTypeCleaned; + typedef std::conditional_t, Dst&> ActualDstType; + ActualDstType actualDst(dst); + + // TODO check whether this is the right place to perform these checks: + EIGEN_STATIC_ASSERT_LVALUE(Dst) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned, Src) + EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename ActualDstTypeCleaned::Scalar, typename Src::Scalar); + + Assignment::run(actualDst, src, func); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void call_restricted_packet_assignment_no_alias(Dst& dst, const Src& src, + const Func& func) { + typedef evaluator DstEvaluatorType; + typedef evaluator SrcEvaluatorType; + typedef restricted_packet_dense_assignment_kernel Kernel; + + EIGEN_STATIC_ASSERT_LVALUE(Dst) + EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename Dst::Scalar, typename Src::Scalar); + + SrcEvaluatorType srcEvaluator(src); + resize_if_allowed(dst, src, func); + + DstEvaluatorType dstEvaluator(dst); + Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived()); + + dense_assignment_loop::run(kernel); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(Dst& dst, const Src& src) { + call_assignment_no_alias(dst, src, internal::assign_op()); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src, + const Func& func) { + // TODO check whether this is the right place to perform these checks: + EIGEN_STATIC_ASSERT_LVALUE(Dst) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Dst, Src) + EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename Dst::Scalar, typename Src::Scalar); + + Assignment::run(dst, src, func); +} +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias_no_transpose(Dst& dst, const Src& src) { + call_assignment_no_alias_no_transpose(dst, src, internal::assign_op()); +} + +// forward declaration +template +EIGEN_DEVICE_FUNC void check_for_aliasing(const Dst& dst, const Src& src); + +// Generic Dense to Dense assignment +// Note that the last template argument "Weak" is needed to make it possible to perform +// both partial specialization+SFINAE without ambiguous specialization +template +struct Assignment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE constexpr void run(DstXprType& dst, const SrcXprType& src, + const Functor& func) { +#ifndef EIGEN_NO_DEBUG + if (!internal::is_constant_evaluated()) { + internal::check_for_aliasing(dst, src); + } +#endif + + call_dense_assignment_loop(dst, src, func); + } +}; + +template +struct Assignment, SrcPlainObject>, + assign_op, Dense2Dense, Weak> { + using Scalar = typename DstXprType::Scalar; + using NullaryOp = scalar_constant_op; + using SrcXprType = CwiseNullaryOp; + using Functor = assign_op; + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const Functor& /*func*/) { + eigen_fill_impl::run(dst, src); + } +}; + +template +struct Assignment, SrcPlainObject>, + assign_op, Dense2Dense, Weak> { + using Scalar = typename DstXprType::Scalar; + using NullaryOp = scalar_zero_op; + using SrcXprType = CwiseNullaryOp; + using Functor = assign_op; + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const Functor& /*func*/) { + eigen_zero_impl::run(dst, src); + } +}; + +// Generic assignment through evalTo. +// TODO: not sure we have to keep that one, but it helps porting current code to new evaluator mechanism. +// Note that the last template argument "Weak" is needed to make it possible to perform +// both partial specialization+SFINAE without ambiguous specialization +template +struct Assignment { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run( + DstXprType& dst, const SrcXprType& src, + const internal::assign_op& /*func*/) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); + + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); + src.evalTo(dst); + } + + // NOTE The following two functions are templated to avoid their instantiation if not needed + // This is needed because some expressions supports evalTo only and/or have 'void' as scalar type. + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run( + DstXprType& dst, const SrcXprType& src, + const internal::add_assign_op& /*func*/) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); + + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); + src.addTo(dst); + } + + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run( + DstXprType& dst, const SrcXprType& src, + const internal::sub_assign_op& /*func*/) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); + + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); + src.subTo(dst); + } +}; + +} // namespace internal + +} // end namespace Eigen + +#endif // EIGEN_ASSIGN_EVALUATOR_H diff --git a/inst/include/Eigen/src/Core/Assign_MKL.h b/inst/include/Eigen/src/Core/Assign_MKL.h index 7772951b..7636445c 100644 --- a/inst/include/Eigen/src/Core/Assign_MKL.h +++ b/inst/include/Eigen/src/Core/Assign_MKL.h @@ -1,5 +1,6 @@ /* Copyright (c) 2011, Intel Corporation. All rights reserved. + Copyright (C) 2015 Gael Guennebaud Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: @@ -33,192 +34,150 @@ #ifndef EIGEN_ASSIGN_VML_H #define EIGEN_ASSIGN_VML_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -namespace internal { - -template struct vml_call -{ enum { IsSupported = 0 }; }; - -template -class vml_assign_traits -{ - private: - enum { - DstHasDirectAccess = Dst::Flags & DirectAccessBit, - SrcHasDirectAccess = Src::Flags & DirectAccessBit, - - StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)), - InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime) - : int(Dst::Flags)&RowMajorBit ? int(Dst::ColsAtCompileTime) - : int(Dst::RowsAtCompileTime), - InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime) - : int(Dst::Flags)&RowMajorBit ? int(Dst::MaxColsAtCompileTime) - : int(Dst::MaxRowsAtCompileTime), - MaxSizeAtCompileTime = Dst::SizeAtCompileTime, - - MightEnableVml = vml_call::IsSupported && StorageOrdersAgree && DstHasDirectAccess && SrcHasDirectAccess - && Src::InnerStrideAtCompileTime==1 && Dst::InnerStrideAtCompileTime==1, - MightLinearize = MightEnableVml && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit), - VmlSize = MightLinearize ? MaxSizeAtCompileTime : InnerMaxSize, - LargeEnough = VmlSize==Dynamic || VmlSize>=EIGEN_MKL_VML_THRESHOLD, - MayEnableVml = MightEnableVml && LargeEnough, - MayLinearize = MayEnableVml && MightLinearize - }; - public: - enum { - Traversal = MayLinearize ? LinearVectorizedTraversal - : MayEnableVml ? InnerVectorizedTraversal - : DefaultTraversal - }; -}; +namespace Eigen { -template::Traversal > -struct vml_assign_impl - : assign_impl,Traversal,Unrolling,BuiltIn> -{ -}; +namespace internal { -template -struct vml_assign_impl -{ - typedef typename Derived1::Scalar Scalar; - typedef typename Derived1::Index Index; - static inline void run(Derived1& dst, const CwiseUnaryOp& src) - { - // in case we want to (or have to) skip VML at runtime we can call: - // assign_impl,Traversal,Unrolling,BuiltIn>::run(dst,src); - const Index innerSize = dst.innerSize(); - const Index outerSize = dst.outerSize(); - for(Index outer = 0; outer < outerSize; ++outer) { - const Scalar *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer,0)) : - &(src.nestedExpression().coeffRef(0, outer)); - Scalar *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer,0)) : &(dst.coeffRef(0, outer)); - vml_call::run(src.functor(), innerSize, src_ptr, dst_ptr ); - } - } -}; +template +class vml_assign_traits { + private: + enum { + DstHasDirectAccess = Dst::Flags & DirectAccessBit, + SrcHasDirectAccess = Src::Flags & DirectAccessBit, + StorageOrdersAgree = (int(Dst::IsRowMajor) == int(Src::IsRowMajor)), + InnerSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::SizeAtCompileTime) + : int(Dst::Flags) & RowMajorBit ? int(Dst::ColsAtCompileTime) + : int(Dst::RowsAtCompileTime), + InnerMaxSize = int(Dst::IsVectorAtCompileTime) ? int(Dst::MaxSizeAtCompileTime) + : int(Dst::Flags) & RowMajorBit ? int(Dst::MaxColsAtCompileTime) + : int(Dst::MaxRowsAtCompileTime), + MaxSizeAtCompileTime = Dst::SizeAtCompileTime, + + MightEnableVml = bool(StorageOrdersAgree) && bool(DstHasDirectAccess) && bool(SrcHasDirectAccess) && + Src::InnerStrideAtCompileTime == 1 && Dst::InnerStrideAtCompileTime == 1, + MightLinearize = bool(MightEnableVml) && (int(Dst::Flags) & int(Src::Flags) & LinearAccessBit), + VmlSize = bool(MightLinearize) ? MaxSizeAtCompileTime : InnerMaxSize, + LargeEnough = (VmlSize == Dynamic) || VmlSize >= EIGEN_MKL_VML_THRESHOLD + }; -template -struct vml_assign_impl -{ - static inline void run(Derived1& dst, const CwiseUnaryOp& src) - { - // in case we want to (or have to) skip VML at runtime we can call: - // assign_impl,Traversal,Unrolling,BuiltIn>::run(dst,src); - vml_call::run(src.functor(), dst.size(), src.nestedExpression().data(), dst.data() ); - } + public: + enum { EnableVml = MightEnableVml && LargeEnough, Traversal = MightLinearize ? LinearTraversal : DefaultTraversal }; }; -// Macroses - -#define EIGEN_MKL_VML_SPECIALIZE_ASSIGN(TRAVERSAL,UNROLLING) \ - template \ - struct assign_impl, TRAVERSAL, UNROLLING, Specialized> { \ - static inline void run(Derived1 &dst, const Eigen::CwiseUnaryOp &src) { \ - vml_assign_impl::run(dst, src); \ - } \ - }; - -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,NoUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,CompleteUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(DefaultTraversal,InnerUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,NoUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearTraversal,CompleteUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,NoUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,CompleteUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(InnerVectorizedTraversal,InnerUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,CompleteUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(LinearVectorizedTraversal,NoUnrolling) -EIGEN_MKL_VML_SPECIALIZE_ASSIGN(SliceVectorizedTraversal,NoUnrolling) - - -#if !defined (EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1) -#define EIGEN_MKL_VML_MODE VML_HA +#define EIGEN_PP_EXPAND(ARG) ARG +#if !defined(EIGEN_FAST_MATH) || (EIGEN_FAST_MATH != 1) +#define EIGEN_VMLMODE_EXPAND_xLA , VML_HA #else -#define EIGEN_MKL_VML_MODE VML_LA +#define EIGEN_VMLMODE_EXPAND_xLA , VML_LA #endif -#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ - template<> struct vml_call< scalar_##EIGENOP##_op > { \ - enum { IsSupported = 1 }; \ - static inline void run( const scalar_##EIGENOP##_op& /*func*/, \ - int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ - VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst); \ - } \ - }; - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ - template<> struct vml_call< scalar_##EIGENOP##_op > { \ - enum { IsSupported = 1 }; \ - static inline void run( const scalar_##EIGENOP##_op& /*func*/, \ - int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ - MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \ - VMLOP(size, (const VMLTYPE*)src, (VMLTYPE*)dst, vmlMode); \ - } \ +#define EIGEN_VMLMODE_EXPAND_x_ + +#define EIGEN_VMLMODE_PREFIX_xLA vm +#define EIGEN_VMLMODE_PREFIX_x_ v +#define EIGEN_VMLMODE_PREFIX(VMLMODE) EIGEN_CAT(EIGEN_VMLMODE_PREFIX_x, VMLMODE) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ + template \ + struct Assignment, SrcXprNested>, \ + assign_op, Dense2Dense, \ + std::enable_if_t::EnableVml>> { \ + typedef CwiseUnaryOp, SrcXprNested> SrcXprType; \ + static void run(DstXprType &dst, const SrcXprType &src, const assign_op &func) { \ + resize_if_allowed(dst, src, func); \ + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ + if (vml_assign_traits::Traversal == (int)LinearTraversal) { \ + VMLOP(dst.size(), (const VMLTYPE *)src.nestedExpression().data(), \ + (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ + } else { \ + const Index outerSize = dst.outerSize(); \ + for (Index outer = 0; outer < outerSize; ++outer) { \ + const EIGENTYPE *src_ptr = src.IsRowMajor ? &(src.nestedExpression().coeffRef(outer, 0)) \ + : &(src.nestedExpression().coeffRef(0, outer)); \ + EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \ + VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, \ + (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ + } \ + } \ + } \ }; -#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE) \ - template<> struct vml_call< scalar_##EIGENOP##_op > { \ - enum { IsSupported = 1 }; \ - static inline void run( const scalar_##EIGENOP##_op& func, \ - int size, const EIGENTYPE* src, EIGENTYPE* dst) { \ - EIGENTYPE exponent = func.m_exponent; \ - MKL_INT64 vmlMode = EIGEN_MKL_VML_MODE; \ - VMLOP(&size, (const VMLTYPE*)src, (const VMLTYPE*)&exponent, \ - (VMLTYPE*)dst, &vmlMode); \ - } \ +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), s##VMLOP), float, float, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), d##VMLOP), double, double, VMLMODE) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), c##VMLOP), scomplex, \ + MKL_Complex8, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, EIGEN_CAT(EIGEN_VMLMODE_PREFIX(VMLMODE), z##VMLOP), dcomplex, \ + MKL_Complex16, VMLMODE) + +#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP, VMLMODE) \ + EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(EIGENOP, VMLOP, VMLMODE) + +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sin, Sin, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(asin, Asin, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sinh, Sinh, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cos, Cos, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(acos, Acos, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(cosh, Cosh, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tan, Tan, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(atan, Atan, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(tanh, Tanh, LA) +// EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(exp, Exp, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log, Ln, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(log10, Log10, LA) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS(sqrt, Sqrt, _) + +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_CPLX(arg, Arg, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(round, Round, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(floor, Floor, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(ceil, Ceil, _) +EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(cbrt, Cbrt, _) + +#define EIGEN_MKL_VML_DECLARE_POW_CALL(EIGENOP, VMLOP, EIGENTYPE, VMLTYPE, VMLMODE) \ + template \ + struct Assignment, SrcXprNested, \ + const CwiseNullaryOp, Plain>>, \ + assign_op, Dense2Dense, \ + std::enable_if_t::EnableVml>> { \ + typedef CwiseBinaryOp, SrcXprNested, \ + const CwiseNullaryOp, Plain>> \ + SrcXprType; \ + static void run(DstXprType &dst, const SrcXprType &src, const assign_op &func) { \ + resize_if_allowed(dst, src, func); \ + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); \ + VMLTYPE exponent = reinterpret_cast(src.rhs().functor().m_other); \ + if (vml_assign_traits::Traversal == LinearTraversal) { \ + VMLOP(dst.size(), (const VMLTYPE *)src.lhs().data(), exponent, \ + (VMLTYPE *)dst.data() EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ + } else { \ + const Index outerSize = dst.outerSize(); \ + for (Index outer = 0; outer < outerSize; ++outer) { \ + const EIGENTYPE *src_ptr = \ + src.IsRowMajor ? &(src.lhs().coeffRef(outer, 0)) : &(src.lhs().coeffRef(0, outer)); \ + EIGENTYPE *dst_ptr = dst.IsRowMajor ? &(dst.coeffRef(outer, 0)) : &(dst.coeffRef(0, outer)); \ + VMLOP(dst.innerSize(), (const VMLTYPE *)src_ptr, exponent, \ + (VMLTYPE *)dst_ptr EIGEN_PP_EXPAND(EIGEN_VMLMODE_EXPAND_x##VMLMODE)); \ + } \ + } \ + } \ }; -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vs##VMLOP, float, float) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vd##VMLOP, double, double) - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vc##VMLOP, scomplex, MKL_Complex8) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL(EIGENOP, vz##VMLOP, dcomplex, MKL_Complex16) - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX(EIGENOP, VMLOP) - - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vms##VMLOP, float, float) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmd##VMLOP, double, double) - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmc##VMLOP, scomplex, MKL_Complex8) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALL_LA(EIGENOP, vmz##VMLOP, dcomplex, MKL_Complex16) - -#define EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL_LA(EIGENOP, VMLOP) \ - EIGEN_MKL_VML_DECLARE_UNARY_CALLS_COMPLEX_LA(EIGENOP, VMLOP) - - -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sin, Sin) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(asin, Asin) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(cos, Cos) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(acos, Acos) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(tan, Tan) -//EIGEN_MKL_VML_DECLARE_UNARY_CALLS(abs, Abs) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(exp, Exp) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(log, Ln) -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_LA(sqrt, Sqrt) - -EIGEN_MKL_VML_DECLARE_UNARY_CALLS_REAL(square, Sqr) - -// The vm*powx functions are not avaibale in the windows version of MKL. -#ifndef _WIN32 -EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmspowx_, float, float) -EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdpowx_, double, double) -EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcpowx_, scomplex, MKL_Complex8) -EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzpowx_, dcomplex, MKL_Complex16) -#endif +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmsPowx, float, float, LA) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmdPowx, double, double, LA) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmcPowx, scomplex, MKL_Complex8, LA) +EIGEN_MKL_VML_DECLARE_POW_CALL(pow, vmzPowx, dcomplex, MKL_Complex16, LA) -} // end namespace internal +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_ASSIGN_VML_H +#endif // EIGEN_ASSIGN_VML_H diff --git a/inst/include/Eigen/src/Core/BandMatrix.h b/inst/include/Eigen/src/Core/BandMatrix.h index ffd7fe8b..57b03229 100644 --- a/inst/include/Eigen/src/Core/BandMatrix.h +++ b/inst/include/Eigen/src/Core/BandMatrix.h @@ -10,325 +10,329 @@ #ifndef EIGEN_BANDMATRIX_H #define EIGEN_BANDMATRIX_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { namespace internal { -template -class BandMatrixBase : public EigenBase -{ - public: +template +class BandMatrixBase : public EigenBase { + public: + enum { + Flags = internal::traits::Flags, + CoeffReadCost = internal::traits::CoeffReadCost, + RowsAtCompileTime = internal::traits::RowsAtCompileTime, + ColsAtCompileTime = internal::traits::ColsAtCompileTime, + MaxRowsAtCompileTime = internal::traits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = internal::traits::MaxColsAtCompileTime, + Supers = internal::traits::Supers, + Subs = internal::traits::Subs, + Options = internal::traits::Options + }; + typedef typename internal::traits::Scalar Scalar; + typedef Matrix DenseMatrixType; + typedef typename DenseMatrixType::StorageIndex StorageIndex; + typedef typename internal::traits::CoefficientsType CoefficientsType; + typedef EigenBase Base; - enum { - Flags = internal::traits::Flags, - CoeffReadCost = internal::traits::CoeffReadCost, - RowsAtCompileTime = internal::traits::RowsAtCompileTime, - ColsAtCompileTime = internal::traits::ColsAtCompileTime, - MaxRowsAtCompileTime = internal::traits::MaxRowsAtCompileTime, - MaxColsAtCompileTime = internal::traits::MaxColsAtCompileTime, - Supers = internal::traits::Supers, - Subs = internal::traits::Subs, - Options = internal::traits::Options - }; - typedef typename internal::traits::Scalar Scalar; - typedef Matrix DenseMatrixType; - typedef typename DenseMatrixType::Index Index; - typedef typename internal::traits::CoefficientsType CoefficientsType; - typedef EigenBase Base; + protected: + enum { + DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic, + SizeAtCompileTime = min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime) + }; - protected: + public: + using Base::cols; + using Base::derived; + using Base::rows; + + /** \returns the number of super diagonals */ + inline Index supers() const { return derived().supers(); } + + /** \returns the number of sub diagonals */ + inline Index subs() const { return derived().subs(); } + + /** \returns an expression of the underlying coefficient matrix */ + inline const CoefficientsType& coeffs() const { return derived().coeffs(); } + + /** \returns an expression of the underlying coefficient matrix */ + inline CoefficientsType& coeffs() { return derived().coeffs(); } + + /** \returns a vector expression of the \a i -th column, + * only the meaningful part is returned. + * \warning the internal storage must be column major. */ + inline Block col(Index i) { + EIGEN_STATIC_ASSERT((int(Options) & int(RowMajor)) == 0, THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); + Index start = 0; + Index len = coeffs().rows(); + if (i <= supers()) { + start = supers() - i; + len = (std::min)(rows(), std::max(0, coeffs().rows() - (supers() - i))); + } else if (i >= rows() - subs()) + len = std::max(0, coeffs().rows() - (i + 1 - rows() + subs())); + return Block(coeffs(), start, i, len, 1); + } + + /** \returns a vector expression of the main diagonal */ + inline Block diagonal() { + return Block(coeffs(), supers(), 0, 1, (std::min)(rows(), cols())); + } + + /** \returns a vector expression of the main diagonal (const version) */ + inline const Block diagonal() const { + return Block(coeffs(), supers(), 0, 1, (std::min)(rows(), cols())); + } + + template + struct DiagonalIntReturnType { enum { - DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) - ? 1 + Supers + Subs - : Dynamic, - SizeAtCompileTime = EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime,ColsAtCompileTime) - }; - - public: - - using Base::derived; - using Base::rows; - using Base::cols; - - /** \returns the number of super diagonals */ - inline Index supers() const { return derived().supers(); } - - /** \returns the number of sub diagonals */ - inline Index subs() const { return derived().subs(); } - - /** \returns an expression of the underlying coefficient matrix */ - inline const CoefficientsType& coeffs() const { return derived().coeffs(); } - - /** \returns an expression of the underlying coefficient matrix */ - inline CoefficientsType& coeffs() { return derived().coeffs(); } - - /** \returns a vector expression of the \a i -th column, - * only the meaningful part is returned. - * \warning the internal storage must be column major. */ - inline Block col(Index i) - { - EIGEN_STATIC_ASSERT((Options&RowMajor)==0,THIS_METHOD_IS_ONLY_FOR_COLUMN_MAJOR_MATRICES); - Index start = 0; - Index len = coeffs().rows(); - if (i<=supers()) - { - start = supers()-i; - len = (std::min)(rows(),std::max(0,coeffs().rows() - (supers()-i))); - } - else if (i>=rows()-subs()) - len = std::max(0,coeffs().rows() - (i + 1 - rows() + subs())); - return Block(coeffs(), start, i, len, 1); - } - - /** \returns a vector expression of the main diagonal */ - inline Block diagonal() - { return Block(coeffs(),supers(),0,1,(std::min)(rows(),cols())); } - - /** \returns a vector expression of the main diagonal (const version) */ - inline const Block diagonal() const - { return Block(coeffs(),supers(),0,1,(std::min)(rows(),cols())); } - - template struct DiagonalIntReturnType { - enum { - ReturnOpposite = (Options&SelfAdjoint) && (((Index)>0 && Supers==0) || ((Index)<0 && Subs==0)), - Conjugate = ReturnOpposite && NumTraits::IsComplex, - ActualIndex = ReturnOpposite ? -Index : Index, - DiagonalSize = (RowsAtCompileTime==Dynamic || ColsAtCompileTime==Dynamic) - ? Dynamic - : (ActualIndex<0 - ? EIGEN_SIZE_MIN_PREFER_DYNAMIC(ColsAtCompileTime, RowsAtCompileTime + ActualIndex) - : EIGEN_SIZE_MIN_PREFER_DYNAMIC(RowsAtCompileTime, ColsAtCompileTime - ActualIndex)) - }; - typedef Block BuildType; - typedef typename internal::conditional,BuildType >, - BuildType>::type Type; + ReturnOpposite = + (int(Options) & int(SelfAdjoint)) && (((Index) > 0 && Supers == 0) || ((Index) < 0 && Subs == 0)), + Conjugate = ReturnOpposite && NumTraits::IsComplex, + ActualIndex = ReturnOpposite ? -Index : Index, + DiagonalSize = + (RowsAtCompileTime == Dynamic || ColsAtCompileTime == Dynamic) + ? Dynamic + : (ActualIndex < 0 ? min_size_prefer_dynamic(ColsAtCompileTime, RowsAtCompileTime + ActualIndex) + : min_size_prefer_dynamic(RowsAtCompileTime, ColsAtCompileTime - ActualIndex)) }; + typedef Block BuildType; + typedef std::conditional_t, BuildType>, BuildType> + Type; + }; - /** \returns a vector expression of the \a N -th sub or super diagonal */ - template inline typename DiagonalIntReturnType::Type diagonal() - { - return typename DiagonalIntReturnType::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N)); - } - - /** \returns a vector expression of the \a N -th sub or super diagonal */ - template inline const typename DiagonalIntReturnType::Type diagonal() const - { - return typename DiagonalIntReturnType::BuildType(coeffs(), supers()-N, (std::max)(0,N), 1, diagonalLength(N)); - } - - /** \returns a vector expression of the \a i -th sub or super diagonal */ - inline Block diagonal(Index i) - { - eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers())); - return Block(coeffs(), supers()-i, std::max(0,i), 1, diagonalLength(i)); - } - - /** \returns a vector expression of the \a i -th sub or super diagonal */ - inline const Block diagonal(Index i) const - { - eigen_assert((i<0 && -i<=subs()) || (i>=0 && i<=supers())); - return Block(coeffs(), supers()-i, std::max(0,i), 1, diagonalLength(i)); - } - - template inline void evalTo(Dest& dst) const - { - dst.resize(rows(),cols()); - dst.setZero(); - dst.diagonal() = diagonal(); - for (Index i=1; i<=supers();++i) - dst.diagonal(i) = diagonal(i); - for (Index i=1; i<=subs();++i) - dst.diagonal(-i) = diagonal(-i); - } - - DenseMatrixType toDenseMatrix() const - { - DenseMatrixType res(rows(),cols()); - evalTo(res); - return res; - } - - protected: - - inline Index diagonalLength(Index i) const - { return i<0 ? (std::min)(cols(),rows()+i) : (std::min)(rows(),cols()-i); } + /** \returns a vector expression of the \a N -th sub or super diagonal */ + template + inline typename DiagonalIntReturnType::Type diagonal() { + return typename DiagonalIntReturnType::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N)); + } + + /** \returns a vector expression of the \a N -th sub or super diagonal */ + template + inline const typename DiagonalIntReturnType::Type diagonal() const { + return typename DiagonalIntReturnType::BuildType(coeffs(), supers() - N, (std::max)(0, N), 1, diagonalLength(N)); + } + + /** \returns a vector expression of the \a i -th sub or super diagonal */ + inline Block diagonal(Index i) { + eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers())); + return Block(coeffs(), supers() - i, std::max(0, i), 1, diagonalLength(i)); + } + + /** \returns a vector expression of the \a i -th sub or super diagonal */ + inline const Block diagonal(Index i) const { + eigen_assert((i < 0 && -i <= subs()) || (i >= 0 && i <= supers())); + return Block(coeffs(), supers() - i, std::max(0, i), 1, + diagonalLength(i)); + } + + template + inline void evalTo(Dest& dst) const { + dst.resize(rows(), cols()); + dst.setZero(); + dst.diagonal() = diagonal(); + for (Index i = 1; i <= supers(); ++i) dst.diagonal(i) = diagonal(i); + for (Index i = 1; i <= subs(); ++i) dst.diagonal(-i) = diagonal(-i); + } + + DenseMatrixType toDenseMatrix() const { + DenseMatrixType res(rows(), cols()); + evalTo(res); + return res; + } + + protected: + inline Index diagonalLength(Index i) const { + return i < 0 ? (std::min)(cols(), rows() + i) : (std::min)(rows(), cols() - i); + } }; /** - * \class BandMatrix - * \ingroup Core_Module - * - * \brief Represents a rectangular matrix with a banded storage - * - * \param _Scalar Numeric type, i.e. float, double, int - * \param Rows Number of rows, or \b Dynamic - * \param Cols Number of columns, or \b Dynamic - * \param Supers Number of super diagonal - * \param Subs Number of sub diagonal - * \param _Options A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint - * The former controls \ref TopicStorageOrders "storage order", and defaults to - * column-major. The latter controls whether the matrix represents a selfadjoint - * matrix in which case either Supers of Subs have to be null. - * - * \sa class TridiagonalMatrix - */ - -template -struct traits > -{ - typedef _Scalar Scalar; + * \class BandMatrix + * \ingroup Core_Module + * + * \brief Represents a rectangular matrix with a banded storage + * + * \tparam Scalar_ Numeric type, i.e. float, double, int + * \tparam Rows_ Number of rows, or \b Dynamic + * \tparam Cols_ Number of columns, or \b Dynamic + * \tparam Supers_ Number of super diagonal + * \tparam Subs_ Number of sub diagonal + * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of \b #SelfAdjoint + * The former controls \ref TopicStorageOrders "storage order", and defaults to + * column-major. The latter controls whether the matrix represents a selfadjoint + * matrix in which case either Supers of Subs have to be null. + * + * \sa class TridiagonalMatrix + */ + +template +struct traits > { + typedef Scalar_ Scalar; typedef Dense StorageKind; - typedef DenseIndex Index; + typedef Eigen::Index StorageIndex; enum { CoeffReadCost = NumTraits::ReadCost, - RowsAtCompileTime = _Rows, - ColsAtCompileTime = _Cols, - MaxRowsAtCompileTime = _Rows, - MaxColsAtCompileTime = _Cols, + RowsAtCompileTime = Rows_, + ColsAtCompileTime = Cols_, + MaxRowsAtCompileTime = Rows_, + MaxColsAtCompileTime = Cols_, Flags = LvalueBit, - Supers = _Supers, - Subs = _Subs, - Options = _Options, - DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic + Supers = Supers_, + Subs = Subs_, + Options = Options_, + DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic }; - typedef Matrix CoefficientsType; + typedef Matrix + CoefficientsType; }; -template -class BandMatrix : public BandMatrixBase > -{ - public: +template +class BandMatrix : public BandMatrixBase > { + public: + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::traits::StorageIndex StorageIndex; + typedef typename internal::traits::CoefficientsType CoefficientsType; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::CoefficientsType CoefficientsType; + explicit inline BandMatrix(Index rows = Rows, Index cols = Cols, Index supers = Supers, Index subs = Subs) + : m_coeffs(1 + supers + subs, cols), m_rows(rows), m_supers(supers), m_subs(subs) {} - inline BandMatrix(Index rows=Rows, Index cols=Cols, Index supers=Supers, Index subs=Subs) - : m_coeffs(1+supers+subs,cols), - m_rows(rows), m_supers(supers), m_subs(subs) - { - } + /** \returns the number of columns */ + constexpr Index rows() const { return m_rows.value(); } - /** \returns the number of columns */ - inline Index rows() const { return m_rows.value(); } + /** \returns the number of rows */ + constexpr Index cols() const { return m_coeffs.cols(); } - /** \returns the number of rows */ - inline Index cols() const { return m_coeffs.cols(); } + /** \returns the number of super diagonals */ + constexpr Index supers() const { return m_supers.value(); } - /** \returns the number of super diagonals */ - inline Index supers() const { return m_supers.value(); } + /** \returns the number of sub diagonals */ + constexpr Index subs() const { return m_subs.value(); } - /** \returns the number of sub diagonals */ - inline Index subs() const { return m_subs.value(); } + inline const CoefficientsType& coeffs() const { return m_coeffs; } + inline CoefficientsType& coeffs() { return m_coeffs; } - inline const CoefficientsType& coeffs() const { return m_coeffs; } - inline CoefficientsType& coeffs() { return m_coeffs; } - - protected: - - CoefficientsType m_coeffs; - internal::variable_if_dynamic m_rows; - internal::variable_if_dynamic m_supers; - internal::variable_if_dynamic m_subs; + protected: + CoefficientsType m_coeffs; + internal::variable_if_dynamic m_rows; + internal::variable_if_dynamic m_supers; + internal::variable_if_dynamic m_subs; }; -template +template class BandMatrixWrapper; -template -struct traits > -{ - typedef typename _CoefficientsType::Scalar Scalar; - typedef typename _CoefficientsType::StorageKind StorageKind; - typedef typename _CoefficientsType::Index Index; +template +struct traits > { + typedef typename CoefficientsType_::Scalar Scalar; + typedef typename CoefficientsType_::StorageKind StorageKind; + typedef typename CoefficientsType_::StorageIndex StorageIndex; enum { - CoeffReadCost = internal::traits<_CoefficientsType>::CoeffReadCost, - RowsAtCompileTime = _Rows, - ColsAtCompileTime = _Cols, - MaxRowsAtCompileTime = _Rows, - MaxColsAtCompileTime = _Cols, + CoeffReadCost = internal::traits::CoeffReadCost, + RowsAtCompileTime = Rows_, + ColsAtCompileTime = Cols_, + MaxRowsAtCompileTime = Rows_, + MaxColsAtCompileTime = Cols_, Flags = LvalueBit, - Supers = _Supers, - Subs = _Subs, - Options = _Options, - DataRowsAtCompileTime = ((Supers!=Dynamic) && (Subs!=Dynamic)) ? 1 + Supers + Subs : Dynamic + Supers = Supers_, + Subs = Subs_, + Options = Options_, + DataRowsAtCompileTime = ((Supers != Dynamic) && (Subs != Dynamic)) ? 1 + Supers + Subs : Dynamic }; - typedef _CoefficientsType CoefficientsType; + typedef CoefficientsType_ CoefficientsType; }; -template -class BandMatrixWrapper : public BandMatrixBase > -{ - public: +template +class BandMatrixWrapper + : public BandMatrixBase > { + public: + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::traits::CoefficientsType CoefficientsType; + typedef typename internal::traits::StorageIndex StorageIndex; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::traits::CoefficientsType CoefficientsType; - typedef typename internal::traits::Index Index; + explicit inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows = Rows_, Index cols = Cols_, + Index supers = Supers_, Index subs = Subs_) + : m_coeffs(coeffs), m_rows(rows), m_supers(supers), m_subs(subs) { + EIGEN_UNUSED_VARIABLE(cols); + // eigen_assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows()); + } - inline BandMatrixWrapper(const CoefficientsType& coeffs, Index rows=_Rows, Index cols=_Cols, Index supers=_Supers, Index subs=_Subs) - : m_coeffs(coeffs), - m_rows(rows), m_supers(supers), m_subs(subs) - { - EIGEN_UNUSED_VARIABLE(cols); - //internal::assert(coeffs.cols()==cols() && (supers()+subs()+1)==coeffs.rows()); - } + /** \returns the number of columns */ + constexpr Index rows() const { return m_rows.value(); } - /** \returns the number of columns */ - inline Index rows() const { return m_rows.value(); } + /** \returns the number of rows */ + constexpr Index cols() const { return m_coeffs.cols(); } - /** \returns the number of rows */ - inline Index cols() const { return m_coeffs.cols(); } + /** \returns the number of super diagonals */ + constexpr Index supers() const { return m_supers.value(); } - /** \returns the number of super diagonals */ - inline Index supers() const { return m_supers.value(); } + /** \returns the number of sub diagonals */ + constexpr Index subs() const { return m_subs.value(); } - /** \returns the number of sub diagonals */ - inline Index subs() const { return m_subs.value(); } + inline const CoefficientsType& coeffs() const { return m_coeffs; } - inline const CoefficientsType& coeffs() const { return m_coeffs; } + protected: + const CoefficientsType& m_coeffs; + internal::variable_if_dynamic m_rows; + internal::variable_if_dynamic m_supers; + internal::variable_if_dynamic m_subs; +}; - protected: +/** + * \class TridiagonalMatrix + * \ingroup Core_Module + * + * \brief Represents a tridiagonal matrix with a compact banded storage + * + * \tparam Scalar Numeric type, i.e. float, double, int + * \tparam Size Number of rows and cols, or \b Dynamic + * \tparam Options Can be 0 or \b SelfAdjoint + * + * \sa class BandMatrix + */ +template +class TridiagonalMatrix : public BandMatrix { + typedef BandMatrix Base; + typedef typename Base::StorageIndex StorageIndex; + + public: + explicit TridiagonalMatrix(Index size = Size) : Base(size, size, Options & SelfAdjoint ? 0 : 1, 1) {} + + inline typename Base::template DiagonalIntReturnType<1>::Type super() { return Base::template diagonal<1>(); } + inline const typename Base::template DiagonalIntReturnType<1>::Type super() const { + return Base::template diagonal<1>(); + } + inline typename Base::template DiagonalIntReturnType<-1>::Type sub() { return Base::template diagonal<-1>(); } + inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const { + return Base::template diagonal<-1>(); + } + + protected: +}; - const CoefficientsType& m_coeffs; - internal::variable_if_dynamic m_rows; - internal::variable_if_dynamic m_supers; - internal::variable_if_dynamic m_subs; +struct BandShape {}; + +template +struct evaluator_traits > + : public evaluator_traits_base > { + typedef BandShape Shape; }; -/** - * \class TridiagonalMatrix - * \ingroup Core_Module - * - * \brief Represents a tridiagonal matrix with a compact banded storage - * - * \param _Scalar Numeric type, i.e. float, double, int - * \param Size Number of rows and cols, or \b Dynamic - * \param _Options Can be 0 or \b SelfAdjoint - * - * \sa class BandMatrix - */ -template -class TridiagonalMatrix : public BandMatrix -{ - typedef BandMatrix Base; - typedef typename Base::Index Index; - public: - TridiagonalMatrix(Index size = Size) : Base(size,size,Options&SelfAdjoint?0:1,1) {} - - inline typename Base::template DiagonalIntReturnType<1>::Type super() - { return Base::template diagonal<1>(); } - inline const typename Base::template DiagonalIntReturnType<1>::Type super() const - { return Base::template diagonal<1>(); } - inline typename Base::template DiagonalIntReturnType<-1>::Type sub() - { return Base::template diagonal<-1>(); } - inline const typename Base::template DiagonalIntReturnType<-1>::Type sub() const - { return Base::template diagonal<-1>(); } - protected: +template +struct evaluator_traits > + : public evaluator_traits_base > { + typedef BandShape Shape; +}; + +template <> +struct AssignmentKind { + typedef EigenBase2EigenBase Kind; }; -} // end namespace internal +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_BANDMATRIX_H +#endif // EIGEN_BANDMATRIX_H diff --git a/inst/include/Eigen/src/Core/Block.h b/inst/include/Eigen/src/Core/Block.h index 82789444..39abff71 100644 --- a/inst/include/Eigen/src/Core/Block.h +++ b/inst/include/Eigen/src/Core/Block.h @@ -11,396 +11,419 @@ #ifndef EIGEN_BLOCK_H #define EIGEN_BLOCK_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class Block - * \ingroup Core_Module - * - * \brief Expression of a fixed-size or dynamic-size block - * - * \param XprType the type of the expression in which we are taking a block - * \param BlockRows the number of rows of the block we are taking at compile time (optional) - * \param BlockCols the number of columns of the block we are taking at compile time (optional) - * - * This class represents an expression of either a fixed-size or dynamic-size block. It is the return - * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block(Index,Index) and - * most of the time this is the only way it is used. - * - * However, if you want to directly maniputate block expressions, - * for instance if you want to write a function returning such an expression, you - * will need to use this class. - * - * Here is an example illustrating the dynamic case: - * \include class_Block.cpp - * Output: \verbinclude class_Block.out - * - * \note Even though this expression has dynamic size, in the case where \a XprType - * has fixed size, this expression inherits a fixed maximal size which means that evaluating - * it does not cause a dynamic memory allocation. - * - * Here is an example illustrating the fixed-size case: - * \include class_FixedBlock.cpp - * Output: \verbinclude class_FixedBlock.out - * - * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock - */ +namespace Eigen { namespace internal { -template -struct traits > : traits -{ - typedef typename traits::Scalar Scalar; - typedef typename traits::StorageKind StorageKind; - typedef typename traits::XprKind XprKind; - typedef typename nested::type XprTypeNested; - typedef typename remove_reference::type _XprTypeNested; - enum{ - MatrixRows = traits::RowsAtCompileTime, - MatrixCols = traits::ColsAtCompileTime, +template +struct traits> : traits { + typedef typename traits::Scalar Scalar; + typedef typename traits::StorageKind StorageKind; + typedef typename traits::XprKind XprKind; + typedef typename ref_selector::type XprTypeNested; + typedef std::remove_reference_t XprTypeNested_; + enum { + MatrixRows = traits::RowsAtCompileTime, + MatrixCols = traits::ColsAtCompileTime, RowsAtCompileTime = MatrixRows == 0 ? 0 : BlockRows, ColsAtCompileTime = MatrixCols == 0 ? 0 : BlockCols, - MaxRowsAtCompileTime = BlockRows==0 ? 0 - : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime) - : int(traits::MaxRowsAtCompileTime), - MaxColsAtCompileTime = BlockCols==0 ? 0 - : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime) - : int(traits::MaxColsAtCompileTime), - XprTypeIsRowMajor = (int(traits::Flags)&RowMajorBit) != 0, - IsDense = is_same::value, - IsRowMajor = (IsDense&&MaxRowsAtCompileTime==1&&MaxColsAtCompileTime!=1) ? 1 - : (IsDense&&MaxColsAtCompileTime==1&&MaxRowsAtCompileTime!=1) ? 0 - : XprTypeIsRowMajor, + MaxRowsAtCompileTime = BlockRows == 0 ? 0 + : RowsAtCompileTime != Dynamic ? int(RowsAtCompileTime) + : int(traits::MaxRowsAtCompileTime), + MaxColsAtCompileTime = BlockCols == 0 ? 0 + : ColsAtCompileTime != Dynamic ? int(ColsAtCompileTime) + : int(traits::MaxColsAtCompileTime), + + XprTypeIsRowMajor = (int(traits::Flags) & RowMajorBit) != 0, + IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1 + : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0 + : XprTypeIsRowMajor, HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor), InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime), - InnerStrideAtCompileTime = HasSameStorageOrderAsXprType - ? int(inner_stride_at_compile_time::ret) - : int(outer_stride_at_compile_time::ret), - OuterStrideAtCompileTime = HasSameStorageOrderAsXprType - ? int(outer_stride_at_compile_time::ret) - : int(inner_stride_at_compile_time::ret), - MaskPacketAccessBit = (InnerSize == Dynamic || (InnerSize % packet_traits::size) == 0) - && (InnerStrideAtCompileTime == 1) - ? PacketAccessBit : 0, - MaskAlignedBit = (InnerPanel && (OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) == 0)) ? AlignedBit : 0, - FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || (InnerPanel && (traits::Flags&LinearAccessBit))) ? LinearAccessBit : 0, - FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, + InnerStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(inner_stride_at_compile_time::ret) + : int(outer_stride_at_compile_time::ret), + OuterStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(outer_stride_at_compile_time::ret) + : int(inner_stride_at_compile_time::ret), + + // FIXME, this traits is rather specialized for dense object and it needs to be cleaned further + FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0, - Flags0 = traits::Flags & ( (HereditaryBits & ~RowMajorBit) | - DirectAccessBit | - MaskPacketAccessBit | - MaskAlignedBit), - Flags = Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit + Flags = (traits::Flags & (DirectAccessBit | (InnerPanel_ ? CompressedAccessBit : 0))) | FlagsLvalueBit | + FlagsRowMajorBit, + // FIXME DirectAccessBit should not be handled by expressions + // + // Alignment is needed by MapBase's assertions + // We can sefely set it to false here. Internal alignment errors will be detected by an eigen_internal_assert in the + // respective evaluator + Alignment = 0, + InnerPanel = InnerPanel_ ? 1 : 0 }; }; -template::ret> class BlockImpl_dense; - -} // end namespace internal - -template class BlockImpl; - -template class Block - : public BlockImpl::StorageKind> -{ - typedef BlockImpl::StorageKind> Impl; - public: - //typedef typename Impl::Base Base; - typedef Impl Base; - EIGEN_GENERIC_PUBLIC_INTERFACE(Block) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block) - - /** Column or Row constructor - */ - inline Block(XprType& xpr, Index i) : Impl(xpr,i) - { - eigen_assert( (i>=0) && ( - ((BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) && i= 0 && BlockRows >= 1 && a_startRow + BlockRows <= xpr.rows() - && a_startCol >= 0 && BlockCols >= 1 && a_startCol + BlockCols <= xpr.cols()); - } - - /** Dynamic-size constructor - */ - inline Block(XprType& xpr, - Index a_startRow, Index a_startCol, - Index blockRows, Index blockCols) - : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) - { - eigen_assert((RowsAtCompileTime==Dynamic || RowsAtCompileTime==blockRows) - && (ColsAtCompileTime==Dynamic || ColsAtCompileTime==blockCols)); - eigen_assert(a_startRow >= 0 && blockRows >= 0 && a_startRow <= xpr.rows() - blockRows - && a_startCol >= 0 && blockCols >= 0 && a_startCol <= xpr.cols() - blockCols); - } +template ::ret> +class BlockImpl_dense; + +} // end namespace internal + +template +class BlockImpl; + +/** \class Block + * \ingroup Core_Module + * + * \brief Expression of a fixed-size or dynamic-size block + * + * \tparam XprType the type of the expression in which we are taking a block + * \tparam BlockRows the number of rows of the block we are taking at compile time (optional) + * \tparam BlockCols the number of columns of the block we are taking at compile time (optional) + * \tparam InnerPanel is true, if the block maps to a set of rows of a row major matrix or + * to set of columns of a column major matrix (optional). The parameter allows to determine + * at compile time whether aligned access is possible on the block expression. + * + * This class represents an expression of either a fixed-size or dynamic-size block. It is the return + * type of DenseBase::block(Index,Index,Index,Index) and DenseBase::block(Index,Index) and + * most of the time this is the only way it is used. + * + * However, if you want to directly manipulate block expressions, + * for instance if you want to write a function returning such an expression, you + * will need to use this class. + * + * Here is an example illustrating the dynamic case: + * \include class_Block.cpp + * Output: \verbinclude class_Block.out + * + * \note Even though this expression has dynamic size, in the case where \a XprType + * has fixed size, this expression inherits a fixed maximal size which means that evaluating + * it does not cause a dynamic memory allocation. + * + * Here is an example illustrating the fixed-size case: + * \include class_FixedBlock.cpp + * Output: \verbinclude class_FixedBlock.out + * + * \sa DenseBase::block(Index,Index,Index,Index), DenseBase::block(Index,Index), class VectorBlock + */ +template +class Block + : public BlockImpl::StorageKind> { + typedef BlockImpl::StorageKind> Impl; + using BlockHelper = internal::block_xpr_helper; + + public: + // typedef typename Impl::Base Base; + typedef Impl Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(Block) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Block) + + typedef internal::remove_all_t NestedExpression; + + /** Column or Row constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index i) : Impl(xpr, i) { + eigen_assert((i >= 0) && (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && i < xpr.rows()) || + ((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) && i < xpr.cols()))); + } + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol) + : Impl(xpr, startRow, startCol) { + EIGEN_STATIC_ASSERT(RowsAtCompileTime != Dynamic && ColsAtCompileTime != Dynamic, + THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE) + eigen_assert(startRow >= 0 && BlockRows >= 0 && startRow + BlockRows <= xpr.rows() && startCol >= 0 && + BlockCols >= 0 && startCol + BlockCols <= xpr.cols()); + } + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Block(XprType& xpr, Index startRow, Index startCol, Index blockRows, + Index blockCols) + : Impl(xpr, startRow, startCol, blockRows, blockCols) { + eigen_assert((RowsAtCompileTime == Dynamic || RowsAtCompileTime == blockRows) && + (ColsAtCompileTime == Dynamic || ColsAtCompileTime == blockCols)); + eigen_assert(startRow >= 0 && blockRows >= 0 && startRow <= xpr.rows() - blockRows && startCol >= 0 && + blockCols >= 0 && startCol <= xpr.cols() - blockCols); + } + + // convert nested blocks (e.g. Block>) to a simple block expression (Block) + + using ConstUnwindReturnType = Block; + using UnwindReturnType = Block; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ConstUnwindReturnType unwind() const { + return ConstUnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0), + this->rows(), this->cols()); + } + + template ::value>> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE UnwindReturnType unwind() { + return UnwindReturnType(BlockHelper::base(*this), BlockHelper::row(*this, 0), BlockHelper::col(*this, 0), + this->rows(), this->cols()); + } }; - -// The generic default implementation for dense block simplu forward to the internal::BlockImpl_dense + +// The generic default implementation for dense block simply forward to the internal::BlockImpl_dense // that must be specialized for direct and non-direct access... -template +template class BlockImpl - : public internal::BlockImpl_dense -{ - typedef internal::BlockImpl_dense Impl; - typedef typename XprType::Index Index; - public: - typedef Impl Base; - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl) - inline BlockImpl(XprType& xpr, Index i) : Impl(xpr,i) {} - inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol) : Impl(xpr, a_startRow, a_startCol) {} - inline BlockImpl(XprType& xpr, Index a_startRow, Index a_startCol, Index blockRows, Index blockCols) - : Impl(xpr, a_startRow, a_startCol, blockRows, blockCols) {} + : public internal::BlockImpl_dense { + typedef internal::BlockImpl_dense Impl; + typedef typename XprType::StorageIndex StorageIndex; + + public: + typedef Impl Base; + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index i) : Impl(xpr, i) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol) + : Impl(xpr, startRow, startCol) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl(XprType& xpr, Index startRow, Index startCol, Index blockRows, + Index blockCols) + : Impl(xpr, startRow, startCol, blockRows, blockCols) {} }; namespace internal { /** \internal Internal implementation of dense Blocks in the general case. */ -template class BlockImpl_dense - : public internal::dense_xpr_base >::type -{ - typedef Block BlockType; - public: +template +class BlockImpl_dense : public internal::dense_xpr_base>::type { + typedef Block BlockType; + typedef typename internal::ref_selector::non_const_type XprTypeNested; - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense) + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense) - class InnerIterator; + // class InnerIterator; // FIXME apparently never used - /** Column or Row constructor - */ - inline BlockImpl_dense(XprType& xpr, Index i) + /** Column or Row constructor + */ + EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index i) : m_xpr(xpr), // It is a row if and only if BlockRows==1 and BlockCols==XprType::ColsAtCompileTime, // and it is a column if and only if BlockRows==XprType::RowsAtCompileTime and BlockCols==1, // all other cases are invalid. // The case a 1x1 matrix seems ambiguous, but the result is the same anyway. - m_startRow( (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0), - m_startCol( (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0), - m_blockRows(BlockRows==1 ? 1 : xpr.rows()), - m_blockCols(BlockCols==1 ? 1 : xpr.cols()) - {} - - /** Fixed-size constructor - */ - inline BlockImpl_dense(XprType& xpr, Index a_startRow, Index a_startCol) - : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol), - m_blockRows(BlockRows), m_blockCols(BlockCols) - {} - - /** Dynamic-size constructor - */ - inline BlockImpl_dense(XprType& xpr, - Index a_startRow, Index a_startCol, - Index blockRows, Index blockCols) - : m_xpr(xpr), m_startRow(a_startRow), m_startCol(a_startCol), - m_blockRows(blockRows), m_blockCols(blockCols) - {} - - inline Index rows() const { return m_blockRows.value(); } - inline Index cols() const { return m_blockCols.value(); } - - inline Scalar& coeffRef(Index rowId, Index colId) - { - EIGEN_STATIC_ASSERT_LVALUE(XprType) - return m_xpr.const_cast_derived() - .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); - } - - inline const Scalar& coeffRef(Index rowId, Index colId) const - { - return m_xpr.derived() - .coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); - } - - EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const - { - return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value()); - } - - inline Scalar& coeffRef(Index index) - { - EIGEN_STATIC_ASSERT_LVALUE(XprType) - return m_xpr.const_cast_derived() - .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), - m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); - } - - inline const Scalar& coeffRef(Index index) const - { - return m_xpr.const_cast_derived() - .coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0), + m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0), + m_blockRows(BlockRows == 1 ? 1 : xpr.rows()), + m_blockCols(BlockCols == 1 ? 1 : xpr.cols()) {} + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol) + : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(BlockRows), m_blockCols(BlockCols) {} + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows, + Index blockCols) + : m_xpr(xpr), m_startRow(startRow), m_startCol(startCol), m_blockRows(blockRows), m_blockCols(blockCols) {} + + EIGEN_DEVICE_FUNC inline Index rows() const { return m_blockRows.value(); } + EIGEN_DEVICE_FUNC inline Index cols() const { return m_blockCols.value(); } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index rowId, Index colId) { + EIGEN_STATIC_ASSERT_LVALUE(XprType) + return m_xpr.coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { + return m_xpr.derived().coeffRef(rowId + m_startRow.value(), colId + m_startCol.value()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const { + return m_xpr.coeff(rowId + m_startRow.value(), colId + m_startCol.value()); + } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index) { + EIGEN_STATIC_ASSERT_LVALUE(XprType) + return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { + return m_xpr.coeffRef(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); + } + + EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const { + return m_xpr.coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); - } - - inline const CoeffReturnType coeff(Index index) const - { - return m_xpr - .coeff(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), - m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); - } - - template - inline PacketScalar packet(Index rowId, Index colId) const - { - return m_xpr.template packet - (rowId + m_startRow.value(), colId + m_startCol.value()); - } - - template - inline void writePacket(Index rowId, Index colId, const PacketScalar& val) - { - m_xpr.const_cast_derived().template writePacket - (rowId + m_startRow.value(), colId + m_startCol.value(), val); - } - - template - inline PacketScalar packet(Index index) const - { - return m_xpr.template packet - (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), - m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); - } - - template - inline void writePacket(Index index, const PacketScalar& val) - { - m_xpr.const_cast_derived().template writePacket - (m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), - m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val); - } - - #ifdef EIGEN_PARSED_BY_DOXYGEN - /** \sa MapBase::data() */ - inline const Scalar* data() const; - inline Index innerStride() const; - inline Index outerStride() const; - #endif - - const typename internal::remove_all::type& nestedExpression() const - { - return m_xpr; - } - - Index startRow() const - { - return m_startRow.value(); - } - - Index startCol() const - { - return m_startCol.value(); - } - - protected: - - const typename XprType::Nested m_xpr; - const internal::variable_if_dynamic m_startRow; - const internal::variable_if_dynamic m_startCol; - const internal::variable_if_dynamic m_blockRows; - const internal::variable_if_dynamic m_blockCols; + } + + template + EIGEN_DEVICE_FUNC inline PacketScalar packet(Index rowId, Index colId) const { + return m_xpr.template packet(rowId + m_startRow.value(), colId + m_startCol.value()); + } + + template + EIGEN_DEVICE_FUNC inline void writePacket(Index rowId, Index colId, const PacketScalar& val) { + m_xpr.template writePacket(rowId + m_startRow.value(), colId + m_startCol.value(), val); + } + + template + EIGEN_DEVICE_FUNC inline PacketScalar packet(Index index) const { + return m_xpr.template packet(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0)); + } + + template + EIGEN_DEVICE_FUNC inline void writePacket(Index index, const PacketScalar& val) { + m_xpr.template writePacket(m_startRow.value() + (RowsAtCompileTime == 1 ? 0 : index), + m_startCol.value() + (RowsAtCompileTime == 1 ? index : 0), val); + } + +#ifdef EIGEN_PARSED_BY_DOXYGEN + /** \sa MapBase::data() */ + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const; + EIGEN_DEVICE_FUNC inline Index innerStride() const; + EIGEN_DEVICE_FUNC inline Index outerStride() const; +#endif + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t& nestedExpression() const { + return m_xpr; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); } + + protected: + XprTypeNested m_xpr; + const internal::variable_if_dynamic + m_startRow; + const internal::variable_if_dynamic + m_startCol; + const internal::variable_if_dynamic m_blockRows; + const internal::variable_if_dynamic m_blockCols; }; /** \internal Internal implementation of dense Blocks in the direct access case.*/ -template -class BlockImpl_dense - : public MapBase > -{ - typedef Block BlockType; - public: - - typedef MapBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense) - - /** Column or Row constructor - */ - inline BlockImpl_dense(XprType& xpr, Index i) - : Base(internal::const_cast_ptr(&xpr.coeffRef( - (BlockRows==1) && (BlockCols==XprType::ColsAtCompileTime) ? i : 0, - (BlockRows==XprType::RowsAtCompileTime) && (BlockCols==1) ? i : 0)), - BlockRows==1 ? 1 : xpr.rows(), - BlockCols==1 ? 1 : xpr.cols()), - m_xpr(xpr) - { - init(); - } - - /** Fixed-size constructor - */ - inline BlockImpl_dense(XprType& xpr, Index startRow, Index startCol) - : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol))), m_xpr(xpr) - { - init(); - } - - /** Dynamic-size constructor - */ - inline BlockImpl_dense(XprType& xpr, - Index startRow, Index startCol, - Index blockRows, Index blockCols) - : Base(internal::const_cast_ptr(&xpr.coeffRef(startRow,startCol)), blockRows, blockCols), - m_xpr(xpr) - { - init(); - } - - const typename internal::remove_all::type& nestedExpression() const - { - return m_xpr; - } - - /** \sa MapBase::innerStride() */ - inline Index innerStride() const - { - return internal::traits::HasSameStorageOrderAsXprType - ? m_xpr.innerStride() - : m_xpr.outerStride(); - } - - /** \sa MapBase::outerStride() */ - inline Index outerStride() const - { - return m_outerStride; - } - - #ifndef __SUNPRO_CC +template +class BlockImpl_dense + : public MapBase> { + typedef Block BlockType; + typedef typename internal::ref_selector::non_const_type XprTypeNested; + enum { XprTypeIsRowMajor = (int(traits::Flags) & RowMajorBit) != 0 }; + + /** \internal Returns base+offset (unless base is null, in which case returns null). + * Adding an offset to nullptr is undefined behavior, so we must avoid it. + */ + template + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE static Scalar* add_to_nullable_pointer(Scalar* base, Index offset) { + return base != nullptr ? base + offset : nullptr; + } + + public: + typedef MapBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(BlockType) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(BlockImpl_dense) + + /** Column or Row constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index i) + : Base((BlockRows == 0 || BlockCols == 0) + ? nullptr + : add_to_nullable_pointer( + xpr.data(), + i * (((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) && (!XprTypeIsRowMajor)) || + ((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) && + (XprTypeIsRowMajor)) + ? xpr.innerStride() + : xpr.outerStride())), + BlockRows == 1 ? 1 : xpr.rows(), BlockCols == 1 ? 1 : xpr.cols()), + m_xpr(xpr), + m_startRow((BlockRows == 1) && (BlockCols == XprType::ColsAtCompileTime) ? i : 0), + m_startCol((BlockRows == XprType::RowsAtCompileTime) && (BlockCols == 1) ? i : 0) { + init(); + } + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol) + : Base((BlockRows == 0 || BlockCols == 0) + ? nullptr + : add_to_nullable_pointer(xpr.data(), + xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) + + xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol))), + m_xpr(xpr), + m_startRow(startRow), + m_startCol(startCol) { + init(); + } + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, Index startRow, Index startCol, Index blockRows, + Index blockCols) + : Base((blockRows == 0 || blockCols == 0) + ? nullptr + : add_to_nullable_pointer(xpr.data(), + xpr.innerStride() * (XprTypeIsRowMajor ? startCol : startRow) + + xpr.outerStride() * (XprTypeIsRowMajor ? startRow : startCol)), + blockRows, blockCols), + m_xpr(xpr), + m_startRow(startRow), + m_startCol(startCol) { + init(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t& nestedExpression() const noexcept { + return m_xpr; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE XprType& nestedExpression() { return m_xpr; } + + /** \sa MapBase::innerStride() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index innerStride() const noexcept { + return internal::traits::HasSameStorageOrderAsXprType ? m_xpr.innerStride() : m_xpr.outerStride(); + } + + /** \sa MapBase::outerStride() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const noexcept { + return internal::traits::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startRow() const noexcept { return m_startRow.value(); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr StorageIndex startCol() const noexcept { return m_startCol.value(); } + +#ifndef __SUNPRO_CC // FIXME sunstudio is not friendly with the above friend... // META-FIXME there is no 'friend' keyword around here. Is this obsolete? - protected: - #endif - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** \internal used by allowAligned() */ - inline BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, Index blockCols) - : Base(data, blockRows, blockCols), m_xpr(xpr) - { - init(); - } - #endif - - protected: - void init() - { - m_outerStride = internal::traits::HasSameStorageOrderAsXprType - ? m_xpr.outerStride() - : m_xpr.innerStride(); - } - - typename XprType::Nested m_xpr; - Index m_outerStride; + protected: +#endif + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal used by allowAligned() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE BlockImpl_dense(XprType& xpr, const Scalar* data, Index blockRows, + Index blockCols) + : Base(data, blockRows, blockCols), m_xpr(xpr) { + init(); + } +#endif + + protected: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void init() { + m_outerStride = + internal::traits::HasSameStorageOrderAsXprType ? m_xpr.outerStride() : m_xpr.innerStride(); + } + + XprTypeNested m_xpr; + const internal::variable_if_dynamic + m_startRow; + const internal::variable_if_dynamic + m_startCol; + Index m_outerStride; }; -} // end namespace internal +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_BLOCK_H +#endif // EIGEN_BLOCK_H diff --git a/inst/include/Eigen/src/Core/BooleanRedux.h b/inst/include/Eigen/src/Core/BooleanRedux.h deleted file mode 100644 index be9f48a8..00000000 --- a/inst/include/Eigen/src/Core/BooleanRedux.h +++ /dev/null @@ -1,154 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Gael Guennebaud -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#ifndef EIGEN_ALLANDANY_H -#define EIGEN_ALLANDANY_H - -namespace Eigen { - -namespace internal { - -template -struct all_unroller -{ - enum { - col = (UnrollCount-1) / Derived::RowsAtCompileTime, - row = (UnrollCount-1) % Derived::RowsAtCompileTime - }; - - static inline bool run(const Derived &mat) - { - return all_unroller::run(mat) && mat.coeff(row, col); - } -}; - -template -struct all_unroller -{ - static inline bool run(const Derived &/*mat*/) { return true; } -}; - -template -struct all_unroller -{ - static inline bool run(const Derived &) { return false; } -}; - -template -struct any_unroller -{ - enum { - col = (UnrollCount-1) / Derived::RowsAtCompileTime, - row = (UnrollCount-1) % Derived::RowsAtCompileTime - }; - - static inline bool run(const Derived &mat) - { - return any_unroller::run(mat) || mat.coeff(row, col); - } -}; - -template -struct any_unroller -{ - static inline bool run(const Derived & /*mat*/) { return false; } -}; - -template -struct any_unroller -{ - static inline bool run(const Derived &) { return false; } -}; - -} // end namespace internal - -/** \returns true if all coefficients are true - * - * Example: \include MatrixBase_all.cpp - * Output: \verbinclude MatrixBase_all.out - * - * \sa any(), Cwise::operator<() - */ -template -inline bool DenseBase::all() const -{ - enum { - unroll = SizeAtCompileTime != Dynamic - && CoeffReadCost != Dynamic - && NumTraits::AddCost != Dynamic - && SizeAtCompileTime * (CoeffReadCost + NumTraits::AddCost) <= EIGEN_UNROLLING_LIMIT - }; - if(unroll) - return internal::all_unroller::run(derived()); - else - { - for(Index j = 0; j < cols(); ++j) - for(Index i = 0; i < rows(); ++i) - if (!coeff(i, j)) return false; - return true; - } -} - -/** \returns true if at least one coefficient is true - * - * \sa all() - */ -template -inline bool DenseBase::any() const -{ - enum { - unroll = SizeAtCompileTime != Dynamic - && CoeffReadCost != Dynamic - && NumTraits::AddCost != Dynamic - && SizeAtCompileTime * (CoeffReadCost + NumTraits::AddCost) <= EIGEN_UNROLLING_LIMIT - }; - if(unroll) - return internal::any_unroller::run(derived()); - else - { - for(Index j = 0; j < cols(); ++j) - for(Index i = 0; i < rows(); ++i) - if (coeff(i, j)) return true; - return false; - } -} - -/** \returns the number of coefficients which evaluate to true - * - * \sa all(), any() - */ -template -inline typename DenseBase::Index DenseBase::count() const -{ - return derived().template cast().template cast().sum(); -} - -/** \returns true is \c *this contains at least one Not A Number (NaN). - * - * \sa allFinite() - */ -template -inline bool DenseBase::hasNaN() const -{ - return !((derived().array()==derived().array()).all()); -} - -/** \returns true if \c *this contains only finite numbers, i.e., no NaN and no +/-INF values. - * - * \sa hasNaN() - */ -template -inline bool DenseBase::allFinite() const -{ - return !((derived()-derived()).hasNaN()); -} - -} // end namespace Eigen - -#endif // EIGEN_ALLANDANY_H diff --git a/inst/include/Eigen/src/Core/CommaInitializer.h b/inst/include/Eigen/src/Core/CommaInitializer.h index a036d8c3..c4141179 100644 --- a/inst/include/Eigen/src/Core/CommaInitializer.h +++ b/inst/include/Eigen/src/Core/CommaInitializer.h @@ -11,43 +11,46 @@ #ifndef EIGEN_COMMAINITIALIZER_H #define EIGEN_COMMAINITIALIZER_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { /** \class CommaInitializer - * \ingroup Core_Module - * - * \brief Helper class used by the comma initializer operator - * - * This class is internally used to implement the comma initializer feature. It is - * the return type of MatrixBase::operator<<, and most of the time this is the only - * way it is used. - * - * \sa \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished() - */ -template -struct CommaInitializer -{ + * \ingroup Core_Module + * + * \brief Helper class used by the comma initializer operator + * + * This class is internally used to implement the comma initializer feature. It is + * the return type of MatrixBase::operator<<, and most of the time this is the only + * way it is used. + * + * \sa \blank \ref MatrixBaseCommaInitRef "MatrixBase::operator<<", CommaInitializer::finished() + */ +template +struct CommaInitializer { typedef typename XprType::Scalar Scalar; - typedef typename XprType::Index Index; - inline CommaInitializer(XprType& xpr, const Scalar& s) - : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) - { - m_xpr.coeffRef(0,0) = s; + EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const Scalar& s) + : m_xpr(xpr), m_row(0), m_col(1), m_currentBlockRows(1) { + eigen_assert(m_xpr.rows() > 0 && m_xpr.cols() > 0 && "Cannot comma-initialize a 0x0 matrix (operator<<)"); + m_xpr.coeffRef(0, 0) = s; } - template - inline CommaInitializer(XprType& xpr, const DenseBase& other) - : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) - { - m_xpr.block(0, 0, other.rows(), other.cols()) = other; + template + EIGEN_DEVICE_FUNC inline CommaInitializer(XprType& xpr, const DenseBase& other) + : m_xpr(xpr), m_row(0), m_col(other.cols()), m_currentBlockRows(other.rows()) { + eigen_assert(m_xpr.rows() >= other.rows() && m_xpr.cols() >= other.cols() && + "Cannot comma-initialize a 0x0 matrix (operator<<)"); + m_xpr.template block(0, 0, other.rows(), + other.cols()) = other; } - /* Copy/Move constructor which transfers ownership. This is crucial in + /* Copy/Move constructor which transfers ownership. This is crucial in * absence of return value optimization to avoid assertions during destruction. */ // FIXME in C++11 mode this could be replaced by a proper RValue constructor - inline CommaInitializer(const CommaInitializer& o) - : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) { + EIGEN_DEVICE_FUNC inline CommaInitializer(const CommaInitializer& o) + : m_xpr(o.m_xpr), m_row(o.m_row), m_col(o.m_col), m_currentBlockRows(o.m_currentBlockRows) { // Mark original object as finished. In absence of R-value references we need to const_cast: const_cast(o).m_row = m_xpr.rows(); const_cast(o).m_col = m_xpr.cols(); @@ -55,100 +58,92 @@ struct CommaInitializer } /* inserts a scalar value in the target matrix */ - CommaInitializer& operator,(const Scalar& s) - { - if (m_col==m_xpr.cols()) - { - m_row+=m_currentBlockRows; + EIGEN_DEVICE_FUNC CommaInitializer &operator,(const Scalar& s) { + if (m_col == m_xpr.cols()) { + m_row += m_currentBlockRows; m_col = 0; m_currentBlockRows = 1; - eigen_assert(m_row - CommaInitializer& operator,(const DenseBase& other) - { - if(other.cols()==0 || other.rows()==0) - return *this; - if (m_col==m_xpr.cols()) - { - m_row+=m_currentBlockRows; + template + EIGEN_DEVICE_FUNC CommaInitializer &operator,(const DenseBase& other) { + if (m_col == m_xpr.cols() && (other.cols() != 0 || other.rows() != m_currentBlockRows)) { + m_row += m_currentBlockRows; m_col = 0; m_currentBlockRows = other.rows(); - eigen_assert(m_row+m_currentBlockRows<=m_xpr.rows() - && "Too many rows passed to comma initializer (operator<<)"); + eigen_assert(m_row + m_currentBlockRows <= m_xpr.rows() && + "Too many rows passed to comma initializer (operator<<)"); } - eigen_assert(m_col - (m_row, m_col) = other; - else - m_xpr.block(m_row, m_col, other.rows(), other.cols()) = other; + eigen_assert((m_col + other.cols() <= m_xpr.cols()) && + "Too many coefficients passed to comma initializer (operator<<)"); + eigen_assert(m_currentBlockRows == other.rows()); + m_xpr.template block(m_row, m_col, other.rows(), + other.cols()) = other; m_col += other.cols(); return *this; } - inline ~CommaInitializer() + EIGEN_DEVICE_FUNC inline ~CommaInitializer() +#if defined VERIFY_RAISES_ASSERT && (!defined EIGEN_NO_ASSERTION_CHECKING) && defined EIGEN_EXCEPTIONS + noexcept(false) // Eigen::eigen_assert_exception +#endif { - eigen_assert((m_row+m_currentBlockRows) == m_xpr.rows() - && m_col == m_xpr.cols() - && "Too few coefficients passed to comma initializer (operator<<)"); + finished(); } /** \returns the built matrix once all its coefficients have been set. - * Calling finished is 100% optional. Its purpose is to write expressions - * like this: - * \code - * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished()); - * \endcode - */ - inline XprType& finished() { return m_xpr; } - - XprType& m_xpr; // target expression - Index m_row; // current row id - Index m_col; // current col id - Index m_currentBlockRows; // current block height + * Calling finished is 100% optional. Its purpose is to write expressions + * like this: + * \code + * quaternion.fromRotationMatrix((Matrix3f() << axis0, axis1, axis2).finished()); + * \endcode + */ + EIGEN_DEVICE_FUNC inline XprType& finished() { + eigen_assert(((m_row + m_currentBlockRows) == m_xpr.rows() || m_xpr.cols() == 0) && m_col == m_xpr.cols() && + "Too few coefficients passed to comma initializer (operator<<)"); + return m_xpr; + } + + XprType& m_xpr; // target expression + Index m_row; // current row id + Index m_col; // current col id + Index m_currentBlockRows; // current block height }; /** \anchor MatrixBaseCommaInitRef - * Convenient operator to set the coefficients of a matrix. - * - * The coefficients must be provided in a row major order and exactly match - * the size of the matrix. Otherwise an assertion is raised. - * - * Example: \include MatrixBase_set.cpp - * Output: \verbinclude MatrixBase_set.out - * - * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary order. - * - * \sa CommaInitializer::finished(), class CommaInitializer - */ -template -inline CommaInitializer DenseBase::operator<< (const Scalar& s) -{ + * Convenient operator to set the coefficients of a matrix. + * + * The coefficients must be provided in a row major order and exactly match + * the size of the matrix. Otherwise an assertion is raised. + * + * Example: \include MatrixBase_set.cpp + * Output: \verbinclude MatrixBase_set.out + * + * \note According the c++ standard, the argument expressions of this comma initializer are evaluated in arbitrary + * order. + * + * \sa CommaInitializer::finished(), class CommaInitializer + */ +template +EIGEN_DEVICE_FUNC inline CommaInitializer DenseBase::operator<<(const Scalar& s) { return CommaInitializer(*static_cast(this), s); } /** \sa operator<<(const Scalar&) */ -template -template -inline CommaInitializer -DenseBase::operator<<(const DenseBase& other) -{ - return CommaInitializer(*static_cast(this), other); +template +template +EIGEN_DEVICE_FUNC inline CommaInitializer DenseBase::operator<<( + const DenseBase& other) { + return CommaInitializer(*static_cast(this), other); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_COMMAINITIALIZER_H +#endif // EIGEN_COMMAINITIALIZER_H diff --git a/inst/include/Eigen/src/Core/ConditionEstimator.h b/inst/include/Eigen/src/Core/ConditionEstimator.h new file mode 100644 index 00000000..dd1770b1 --- /dev/null +++ b/inst/include/Eigen/src/Core/ConditionEstimator.h @@ -0,0 +1,173 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2016 Rasmus Munk Larsen (rmlarsen@google.com) +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_CONDITIONESTIMATOR_H +#define EIGEN_CONDITIONESTIMATOR_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +template +struct rcond_compute_sign { + static inline Vector run(const Vector& v) { + const RealVector v_abs = v.cwiseAbs(); + return (v_abs.array() == static_cast(0)) + .select(Vector::Ones(v.size()), v.cwiseQuotient(v_abs)); + } +}; + +// Partial specialization to avoid elementwise division for real vectors. +template +struct rcond_compute_sign { + static inline Vector run(const Vector& v) { + return (v.array() < static_cast(0)) + .select(-Vector::Ones(v.size()), Vector::Ones(v.size())); + } +}; + +/** + * \returns an estimate of ||inv(matrix)||_1 given a decomposition of + * \a matrix that implements .solve() and .adjoint().solve() methods. + * + * This function implements Algorithms 4.1 and 5.1 from + * http://www.maths.manchester.ac.uk/~higham/narep/narep135.pdf + * which also forms the basis for the condition number estimators in + * LAPACK. Since at most 10 calls to the solve method of dec are + * performed, the total cost is O(dims^2), as opposed to O(dims^3) + * needed to compute the inverse matrix explicitly. + * + * The most common usage is in estimating the condition number + * ||matrix||_1 * ||inv(matrix)||_1. The first term ||matrix||_1 can be + * computed directly in O(n^2) operations. + * + * Supports the following decompositions: FullPivLU, PartialPivLU, LDLT, and + * LLT. + * + * \sa FullPivLU, PartialPivLU, LDLT, LLT. + */ +template +typename Decomposition::RealScalar rcond_invmatrix_L1_norm_estimate(const Decomposition& dec) { + typedef typename Decomposition::MatrixType MatrixType; + typedef typename Decomposition::Scalar Scalar; + typedef typename Decomposition::RealScalar RealScalar; + typedef typename internal::plain_col_type::type Vector; + typedef typename internal::plain_col_type::type RealVector; + const bool is_complex = (NumTraits::IsComplex != 0); + + eigen_assert(dec.rows() == dec.cols()); + const Index n = dec.rows(); + if (n == 0) return 0; + + // Disable Index to float conversion warning +#ifdef __INTEL_COMPILER +#pragma warning push +#pragma warning(disable : 2259) +#endif + Vector v = dec.solve(Vector::Ones(n) / Scalar(n)); +#ifdef __INTEL_COMPILER +#pragma warning pop +#endif + + // lower_bound is a lower bound on + // ||inv(matrix)||_1 = sup_v ||inv(matrix) v||_1 / ||v||_1 + // and is the objective maximized by the ("super-") gradient ascent + // algorithm below. + RealScalar lower_bound = v.template lpNorm<1>(); + if (n == 1) return lower_bound; + + // Gradient ascent algorithm follows: We know that the optimum is achieved at + // one of the simplices v = e_i, so in each iteration we follow a + // super-gradient to move towards the optimal one. + RealScalar old_lower_bound = lower_bound; + Vector sign_vector(n); + Vector old_sign_vector; + Index v_max_abs_index = -1; + Index old_v_max_abs_index = v_max_abs_index; + for (int k = 0; k < 4; ++k) { + sign_vector = internal::rcond_compute_sign::run(v); + if (k > 0 && !is_complex && sign_vector == old_sign_vector) { + // Break if the solution stagnated. + break; + } + // v_max_abs_index = argmax |real( inv(matrix)^T * sign_vector )| + v = dec.adjoint().solve(sign_vector); + v.real().cwiseAbs().maxCoeff(&v_max_abs_index); + if (v_max_abs_index == old_v_max_abs_index) { + // Break if the solution stagnated. + break; + } + // Move to the new simplex e_j, where j = v_max_abs_index. + v = dec.solve(Vector::Unit(n, v_max_abs_index)); // v = inv(matrix) * e_j. + lower_bound = v.template lpNorm<1>(); + if (lower_bound <= old_lower_bound) { + // Break if the gradient step did not increase the lower_bound. + break; + } + if (!is_complex) { + old_sign_vector = sign_vector; + } + old_v_max_abs_index = v_max_abs_index; + old_lower_bound = lower_bound; + } + // The following calculates an independent estimate of ||matrix||_1 by + // multiplying matrix by a vector with entries of slowly increasing + // magnitude and alternating sign: + // v_i = (-1)^{i} (1 + (i / (dim-1))), i = 0,...,dim-1. + // This improvement to Hager's algorithm above is due to Higham. It was + // added to make the algorithm more robust in certain corner cases where + // large elements in the matrix might otherwise escape detection due to + // exact cancellation (especially when op and op_adjoint correspond to a + // sequence of backsubstitutions and permutations), which could cause + // Hager's algorithm to vastly underestimate ||matrix||_1. + Scalar alternating_sign(RealScalar(1)); + for (Index i = 0; i < n; ++i) { + // The static_cast is needed when Scalar is a complex and RealScalar implements expression templates + v[i] = alternating_sign * static_cast(RealScalar(1) + (RealScalar(i) / (RealScalar(n - 1)))); + alternating_sign = -alternating_sign; + } + v = dec.solve(v); + const RealScalar alternate_lower_bound = (2 * v.template lpNorm<1>()) / (3 * RealScalar(n)); + return numext::maxi(lower_bound, alternate_lower_bound); +} + +/** \brief Reciprocal condition number estimator. + * + * Computing a decomposition of a dense matrix takes O(n^3) operations, while + * this method estimates the condition number quickly and reliably in O(n^2) + * operations. + * + * \returns an estimate of the reciprocal condition number + * (1 / (||matrix||_1 * ||inv(matrix)||_1)) of matrix, given ||matrix||_1 and + * its decomposition. Supports the following decompositions: FullPivLU, + * PartialPivLU, LDLT, and LLT. + * + * \sa FullPivLU, PartialPivLU, LDLT, LLT. + */ +template +typename Decomposition::RealScalar rcond_estimate_helper(typename Decomposition::RealScalar matrix_norm, + const Decomposition& dec) { + typedef typename Decomposition::RealScalar RealScalar; + eigen_assert(dec.rows() == dec.cols()); + if (dec.rows() == 0) return NumTraits::infinity(); + if (numext::is_exactly_zero(matrix_norm)) return RealScalar(0); + if (dec.rows() == 1) return RealScalar(1); + const RealScalar inverse_matrix_norm = rcond_invmatrix_L1_norm_estimate(dec); + return (numext::is_exactly_zero(inverse_matrix_norm) ? RealScalar(0) + : (RealScalar(1) / inverse_matrix_norm) / matrix_norm); +} + +} // namespace internal + +} // namespace Eigen + +#endif diff --git a/inst/include/Eigen/src/Core/CoreEvaluators.h b/inst/include/Eigen/src/Core/CoreEvaluators.h new file mode 100644 index 00000000..60857e2c --- /dev/null +++ b/inst/include/Eigen/src/Core/CoreEvaluators.h @@ -0,0 +1,2018 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011 Benoit Jacob +// Copyright (C) 2011-2014 Gael Guennebaud +// Copyright (C) 2011-2012 Jitse Niesen +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_COREEVALUATORS_H +#define EIGEN_COREEVALUATORS_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +// This class returns the evaluator kind from the expression storage kind. +// Default assumes index based accessors +template +struct storage_kind_to_evaluator_kind { + typedef IndexBased Kind; +}; + +// This class returns the evaluator shape from the expression storage kind. +// It can be Dense, Sparse, Triangular, Diagonal, SelfAdjoint, Band, etc. +template +struct storage_kind_to_shape; + +template <> +struct storage_kind_to_shape { + typedef DenseShape Shape; +}; +template <> +struct storage_kind_to_shape { + typedef SolverShape Shape; +}; +template <> +struct storage_kind_to_shape { + typedef PermutationShape Shape; +}; +template <> +struct storage_kind_to_shape { + typedef TranspositionsShape Shape; +}; + +// Evaluators have to be specialized with respect to various criteria such as: +// - storage/structure/shape +// - scalar type +// - etc. +// Therefore, we need specialization of evaluator providing additional template arguments for each kind of evaluators. +// We currently distinguish the following kind of evaluators: +// - unary_evaluator for expressions taking only one arguments (CwiseUnaryOp, CwiseUnaryView, Transpose, +// MatrixWrapper, ArrayWrapper, Reverse, Replicate) +// - binary_evaluator for expression taking two arguments (CwiseBinaryOp) +// - ternary_evaluator for expression taking three arguments (CwiseTernaryOp) +// - product_evaluator for linear algebra products (Product); special case of binary_evaluator because it requires +// additional tags for dispatching. +// - mapbase_evaluator for Map, Block, Ref +// - block_evaluator for Block (special dispatching to a mapbase_evaluator or unary_evaluator) + +template ::Kind, + typename Arg2Kind = typename evaluator_traits::Kind, + typename Arg3Kind = typename evaluator_traits::Kind, + typename Arg1Scalar = typename traits::Scalar, + typename Arg2Scalar = typename traits::Scalar, + typename Arg3Scalar = typename traits::Scalar> +struct ternary_evaluator; + +template ::Kind, + typename RhsKind = typename evaluator_traits::Kind, + typename LhsScalar = typename traits::Scalar, + typename RhsScalar = typename traits::Scalar> +struct binary_evaluator; + +template ::Kind, + typename Scalar = typename T::Scalar> +struct unary_evaluator; + +// evaluator_traits contains traits for evaluator + +template +struct evaluator_traits_base { + // by default, get evaluator kind and shape from storage + typedef typename storage_kind_to_evaluator_kind::StorageKind>::Kind Kind; + typedef typename storage_kind_to_shape::StorageKind>::Shape Shape; +}; + +// Default evaluator traits +template +struct evaluator_traits : public evaluator_traits_base {}; + +template ::Shape> +struct evaluator_assume_aliasing { + static const bool value = false; +}; + +// By default, we assume a unary expression: +template +struct evaluator : public unary_evaluator { + typedef unary_evaluator Base; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const T& xpr) : Base(xpr) {} +}; + +// TODO: Think about const-correctness +template +struct evaluator : evaluator { + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const T& xpr) : evaluator(xpr) {} +}; + +// ---------- base class for all evaluators ---------- + +template +struct evaluator_base { + // TODO that's not very nice to have to propagate all these traits. They are currently only needed to handle + // outer,inner indices. + typedef traits ExpressionTraits; + + enum { Alignment = 0 }; + // noncopyable: + // Don't make this class inherit noncopyable as this kills EBO (Empty Base Optimization) + // and make complex evaluator much larger than then should do. + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator_base() = default; + + private: + EIGEN_DEVICE_FUNC evaluator_base(const evaluator_base&); + EIGEN_DEVICE_FUNC const evaluator_base& operator=(const evaluator_base&); +}; + +// -------------------- Matrix and Array -------------------- +// +// evaluator is a common base class for the +// Matrix and Array evaluators. +// Here we directly specialize evaluator. This is not really a unary expression, and it is, by definition, dense, +// so no need for more sophisticated dispatching. + +// this helper permits to completely eliminate m_outerStride if it is known at compiletime. +template +class plainobjectbase_evaluator_data { + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plainobjectbase_evaluator_data(const Scalar* ptr, Index outerStride) + : data(ptr) { +#ifndef EIGEN_INTERNAL_DEBUGGING + EIGEN_UNUSED_VARIABLE(outerStride); +#endif + eigen_internal_assert(outerStride == OuterStride); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const noexcept { return OuterStride; } + const Scalar* data; +}; + +template +class plainobjectbase_evaluator_data { + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plainobjectbase_evaluator_data(const Scalar* ptr, Index outerStride) + : data(ptr), m_outerStride(outerStride) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index outerStride() const { return m_outerStride; } + const Scalar* data; + + protected: + Index m_outerStride; +}; + +template +struct evaluator> : evaluator_base { + typedef PlainObjectBase PlainObjectType; + typedef typename PlainObjectType::Scalar Scalar; + typedef typename PlainObjectType::CoeffReturnType CoeffReturnType; + + enum { + IsRowMajor = PlainObjectType::IsRowMajor, + IsVectorAtCompileTime = PlainObjectType::IsVectorAtCompileTime, + RowsAtCompileTime = PlainObjectType::RowsAtCompileTime, + ColsAtCompileTime = PlainObjectType::ColsAtCompileTime, + + CoeffReadCost = NumTraits::ReadCost, + Flags = traits::EvaluatorFlags, + Alignment = traits::Alignment + }; + enum { + // We do not need to know the outer stride for vectors + OuterStrideAtCompileTime = IsVectorAtCompileTime ? 0 + : int(IsRowMajor) ? ColsAtCompileTime + : RowsAtCompileTime + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() : m_d(0, OuterStrideAtCompileTime) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const PlainObjectType& m) + : m_d(m.data(), IsVectorAtCompileTime ? 0 : m.outerStride()) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index row, Index col) const { + return coeff(getIndex(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index index) const { return m_d.data[index]; } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index row, Index col) { + return coeffRef(getIndex(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) { + return const_cast(m_d.data)[index]; + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return packet(getIndex(row, col)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return ploadt(m_d.data + index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + writePacket(getIndex(row, col), x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + pstoret(const_cast(m_d.data) + index, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return packetSegment(getIndex(row, col), begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return ploadtSegment(m_d.data + index, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + writePacketSegment(getIndex(row, col), x, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + pstoretSegment(const_cast(m_d.data) + index, x, begin, count); + } + + protected: + plainobjectbase_evaluator_data m_d; + + private: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index constexpr getIndex(Index row, Index col) const { + return IsRowMajor ? row * m_d.outerStride() + col : row + col * m_d.outerStride(); + } +}; + +template +struct evaluator> + : evaluator>> { + typedef Matrix XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() = default; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const XprType& m) + : evaluator>(m) {} +}; + +template +struct evaluator> + : evaluator>> { + typedef Array XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr evaluator() = default; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr explicit evaluator(const XprType& m) + : evaluator>(m) {} +}; + +// -------------------- Transpose -------------------- + +template +struct unary_evaluator, IndexBased> : evaluator_base> { + typedef Transpose XprType; + + enum { + CoeffReadCost = evaluator::CoeffReadCost, + Flags = evaluator::Flags ^ RowMajorBit, + Alignment = evaluator::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& t) : m_argImpl(t.nestedExpression()) {} + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_argImpl.coeff(col, row); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_argImpl.coeff(index); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { return m_argImpl.coeffRef(col, row); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename XprType::Scalar& coeffRef(Index index) { + return m_argImpl.coeffRef(index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_argImpl.template packet(col, row); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_argImpl.template packet(index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + m_argImpl.template writePacket(col, row, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + m_argImpl.template writePacket(index, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_argImpl.template packetSegment(col, row, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return m_argImpl.template packetSegment(index, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + m_argImpl.template writePacketSegment(col, row, x, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + m_argImpl.template writePacketSegment(index, x, begin, count); + } + + protected: + evaluator m_argImpl; +}; + +// -------------------- CwiseNullaryOp -------------------- +// Like Matrix and Array, this is not really a unary expression, so we directly specialize evaluator. +// Likewise, there is not need to more sophisticated dispatching here. + +template ::value, + bool has_unary = has_unary_operator::value, + bool has_binary = has_binary_operator::value> +struct nullary_wrapper { + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const { + return op(i, j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const { + return op(i); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const { + return op.template packetOp(i, j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const { + return op.template packetOp(i); + } +}; + +template +struct nullary_wrapper { + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType = 0, IndexType = 0) const { + return op(); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType = 0, IndexType = 0) const { + return op.template packetOp(); + } +}; + +template +struct nullary_wrapper { + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j = 0) const { + return op(i, j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j = 0) const { + return op.template packetOp(i, j); + } +}; + +// We need the following specialization for vector-only functors assigned to a runtime vector, +// for instance, using linspace and assigning a RowVectorXd to a MatrixXd or even a row of a MatrixXd. +// In this case, i==0 and j is used for the actual iteration. +template +struct nullary_wrapper { + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const { + eigen_assert(i == 0 || j == 0); + return op(i + j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const { + eigen_assert(i == 0 || j == 0); + return op.template packetOp(i + j); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const { + return op(i); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const { + return op.template packetOp(i); + } +}; + +template +struct nullary_wrapper {}; + +#if 0 && EIGEN_COMP_MSVC > 0 +// Disable this ugly workaround. This is now handled in traits::match, +// but this piece of code might still become handly if some other weird compilation +// errors pop up again. + +// MSVC exhibits a weird compilation error when +// compiling: +// Eigen::MatrixXf A = MatrixXf::Random(3,3); +// Ref R = 2.f*A; +// and that has_*ary_operator> have not been instantiated yet. +// The "problem" is that evaluator<2.f*A> is instantiated by traits::match<2.f*A> +// and at that time has_*ary_operator returns true regardless of T. +// Then nullary_wrapper is badly instantiated as nullary_wrapper<.,.,true,true,true>. +// The trick is thus to defer the proper instantiation of nullary_wrapper when coeff(), +// and packet() are really instantiated as implemented below: + +// This is a simple wrapper around Index to enforce the re-instantiation of +// has_*ary_operator when needed. +template struct nullary_wrapper_workaround_msvc { + nullary_wrapper_workaround_msvc(const T&); + operator T()const; +}; + +template +struct nullary_wrapper +{ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i, IndexType j) const { + return nullary_wrapper >::value, + has_unary_operator >::value, + has_binary_operator >::value>().operator()(op,i,j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar operator()(const NullaryOp& op, IndexType i) const { + return nullary_wrapper >::value, + has_unary_operator >::value, + has_binary_operator >::value>().operator()(op,i); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i, IndexType j) const { + return nullary_wrapper >::value, + has_unary_operator >::value, + has_binary_operator >::value>().template packetOp(op,i,j); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE T packetOp(const NullaryOp& op, IndexType i) const { + return nullary_wrapper >::value, + has_unary_operator >::value, + has_binary_operator >::value>().template packetOp(op,i); + } +}; +#endif // MSVC workaround + +template +struct evaluator> + : evaluator_base> { + typedef CwiseNullaryOp XprType; + typedef remove_all_t PlainObjectTypeCleaned; + + enum { + CoeffReadCost = functor_traits::Cost, + + Flags = (evaluator::Flags & + (HereditaryBits | (functor_has_linear_access::ret ? LinearAccessBit : 0) | + (functor_traits::PacketAccess ? PacketAccessBit : 0))) | + (functor_traits::IsRepeatable ? 0 : EvalBeforeNestingBit), + Alignment = AlignedMax + }; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& n) : m_functor(n.functor()), m_wrapper() { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(IndexType row, IndexType col) const { + return m_wrapper(m_functor, row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(IndexType index) const { + return m_wrapper(m_functor, index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(IndexType row, IndexType col) const { + return m_wrapper.template packetOp(m_functor, row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(IndexType index) const { + return m_wrapper.template packetOp(m_functor, index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(IndexType row, IndexType col, Index /*begin*/, + Index /*count*/) const { + return packet(row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(IndexType index, Index /*begin*/, + Index /*count*/) const { + return packet(index); + } + + protected: + const NullaryOp m_functor; + const nullary_wrapper m_wrapper; +}; + +// -------------------- CwiseUnaryOp -------------------- + +template +struct unary_evaluator, IndexBased> : evaluator_base> { + typedef CwiseUnaryOp XprType; + + enum { + CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), + + Flags = evaluator::Flags & + (HereditaryBits | LinearAccessBit | (functor_traits::PacketAccess ? PacketAccessBit : 0)), + Alignment = evaluator::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& op) : m_d(op) { + EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits::Cost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_d.func()(m_d.argImpl.coeff(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_d.func()(m_d.argImpl.coeff(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_d.func().packetOp(m_d.argImpl.template packet(row, col)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_d.func().packetOp(m_d.argImpl.template packet(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_d.func().packetOp(m_d.argImpl.template packetSegment(row, col, begin, count)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return m_d.func().packetOp(m_d.argImpl.template packetSegment(index, begin, count)); + } + + protected: + // this helper permits to completely eliminate the functor if it is empty + struct Data { + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr) + : op(xpr.functor()), argImpl(xpr.nestedExpression()) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& func() const { return op; } + UnaryOp op; + evaluator argImpl; + }; + + Data m_d; +}; + +// ----------------------- Casting --------------------- + +template +struct unary_evaluator, ArgType>, IndexBased> { + using CastOp = core_cast_op; + using XprType = CwiseUnaryOp; + + // Use the largest packet type by default + using SrcPacketType = typename packet_traits::type; + static constexpr int SrcPacketSize = unpacket_traits::size; + static constexpr int SrcPacketBytes = SrcPacketSize * sizeof(SrcType); + + enum { + CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), + PacketAccess = functor_traits::PacketAccess, + ActualPacketAccessBit = PacketAccess ? PacketAccessBit : 0, + Flags = evaluator::Flags & (HereditaryBits | LinearAccessBit | ActualPacketAccessBit), + IsRowMajor = (evaluator::Flags & RowMajorBit), + Alignment = evaluator::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& xpr) + : m_argImpl(xpr.nestedExpression()), m_rows(xpr.rows()), m_cols(xpr.cols()) { + EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits::Cost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + template + using AltSrcScalarOp = std::enable_if_t<(unpacket_traits::size < SrcPacketSize && + !find_packet_by_size::size>::value), + bool>; + template + using SrcPacketArgs1 = + std::enable_if_t<(find_packet_by_size::size>::value), bool>; + template + using SrcPacketArgs2 = std::enable_if_t<(unpacket_traits::size) == (2 * SrcPacketSize), bool>; + template + using SrcPacketArgs4 = std::enable_if_t<(unpacket_traits::size) == (4 * SrcPacketSize), bool>; + template + using SrcPacketArgs8 = std::enable_if_t<(unpacket_traits::size) == (8 * SrcPacketSize), bool>; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool check_array_bounds(Index row, Index col, Index begin, Index count) const { + return IsRowMajor ? (col + count + begin <= cols()) : (row + count + begin <= rows()); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool check_array_bounds(Index index, Index begin, Index count) const { + return index + count + begin <= size(); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE SrcType srcCoeff(Index row, Index col, Index offset) const { + Index actualRow = IsRowMajor ? row : row + offset; + Index actualCol = IsRowMajor ? col + offset : col; + return m_argImpl.coeff(actualRow, actualCol); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE SrcType srcCoeff(Index index, Index offset) const { + Index actualIndex = index + offset; + return m_argImpl.coeff(actualIndex); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstType coeff(Index row, Index col) const { + return cast(srcCoeff(row, col, 0)); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstType coeff(Index index) const { + return cast(srcCoeff(index, 0)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacket(Index row, Index col, Index offset) const { + constexpr int PacketSize = unpacket_traits::size; + Index packetOffset = offset * PacketSize; + Index actualRow = IsRowMajor ? row : row + packetOffset; + Index actualCol = IsRowMajor ? col + packetOffset : col; + eigen_assert(check_array_bounds(actualRow, actualCol, 0, PacketSize) && "Array index out of bounds"); + return m_argImpl.template packet(actualRow, actualCol); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacket(Index index, Index offset) const { + constexpr int PacketSize = unpacket_traits::size; + Index packetOffset = offset * PacketSize; + Index actualIndex = index + packetOffset; + eigen_assert(check_array_bounds(actualIndex, 0, PacketSize) && "Array index out of bounds"); + return m_argImpl.template packet(actualIndex); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacketSegment(Index row, Index col, Index begin, Index count, + Index offset) const { + constexpr int PacketSize = unpacket_traits::size; + Index packetOffset = offset * PacketSize; + Index actualRow = IsRowMajor ? row : row + packetOffset; + Index actualCol = IsRowMajor ? col + packetOffset : col; + eigen_assert(check_array_bounds(actualRow, actualCol, begin, count) && "Array index out of bounds"); + return m_argImpl.template packetSegment(actualRow, actualCol, begin, count); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType srcPacketSegment(Index index, Index begin, Index count, + Index offset) const { + constexpr int PacketSize = unpacket_traits::size; + Index packetOffset = offset * PacketSize; + Index actualIndex = index + packetOffset; + eigen_assert(check_array_bounds(actualIndex, begin, count) && "Array index out of bounds"); + return m_argImpl.template packetSegment(actualIndex, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketBlock srcPacketSegmentHelper(Index row, Index col, + Index begin, + Index count) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets; + for (Index i = 0; i < NumPackets; i++) packets.packet[i] = pzero(PacketType()); + Index offset = begin / SrcPacketSize; + Index actualBegin = begin % SrcPacketSize; + for (; offset < NumPackets; offset++) { + Index actualCount = numext::mini(SrcPacketSize - actualBegin, count); + packets.packet[offset] = srcPacketSegment(row, col, actualBegin, actualCount, offset); + if (count == actualCount) break; + actualBegin = 0; + count -= actualCount; + } + return packets; + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketBlock srcPacketSegmentHelper(Index index, + Index begin, + Index count) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets; + for (Index i = 0; i < NumPackets; i++) packets.packet[i] = pzero(PacketType()); + Index offset = begin / SrcPacketSize; + Index actualBegin = begin % SrcPacketSize; + for (; offset < NumPackets; offset++) { + Index actualCount = numext::mini(SrcPacketSize - actualBegin, count); + packets.packet[offset] = srcPacketSegment(index, actualBegin, actualCount, offset); + if (count == actualCount) break; + actualBegin = 0; + count -= actualCount; + } + return packets; + } + + // There is no source packet type with equal or fewer elements than DstPacketType. + // This is problematic as the evaluation loop may attempt to access data outside the bounds of the array. + // For example, consider the cast utilizing pcast with an array of size 4: {0.0f,1.0f,2.0f,3.0f}. + // The first iteration of the evaluation loop will load 16 bytes: {0.0f,1.0f,2.0f,3.0f} and cast to {0.0,1.0}, which + // is acceptable. The second iteration will load 16 bytes: {2.0f,3.0f,?,?}, which is outside the bounds of the array. + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const { + constexpr int DstPacketSize = unpacket_traits::size; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacketSegment(row, col, 0, DstPacketSize, 0)); + } + // Use the source packet type with the same size as DstPacketType, if it exists + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const { + constexpr int DstPacketSize = unpacket_traits::size; + using SizedSrcPacketType = typename find_packet_by_size::type; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacket(row, col, 0)); + } + // unpacket_traits::size == 2 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast(srcPacket(row, col, 0), + srcPacket(row, col, 1)); + } + // unpacket_traits::size == 4 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast(srcPacket(row, col, 0), srcPacket(row, col, 1), + srcPacket(row, col, 2), + srcPacket(row, col, 3)); + } + // unpacket_traits::size == 8 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index row, Index col) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast( + srcPacket(row, col, 0), srcPacket(row, col, 1), srcPacket(row, col, 2), + srcPacket(row, col, 3), srcPacket(row, col, 4), srcPacket(row, col, 5), + srcPacket(row, col, 6), srcPacket(row, col, 7)); + } + + // packetSegment variants + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + constexpr int DstPacketSize = unpacket_traits::size; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacketSegment(row, col, begin, count, 0)); + } + // Use the source packet type with the same size as DstPacketType, if it exists + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + constexpr int DstPacketSize = unpacket_traits::size; + using SizedSrcPacketType = typename find_packet_by_size::type; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast( + srcPacketSegment(row, col, begin, count, 0)); + } + // unpacket_traits::size == 2 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + constexpr int NumPackets = 2; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(row, col, begin, count); + return pcast(packets.packet[0], packets.packet[1]); + } + // unpacket_traits::size == 4 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + constexpr int NumPackets = 4; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(row, col, begin, count); + return pcast(packets.packet[0], packets.packet[1], packets.packet[2], + packets.packet[3]); + } + // unpacket_traits::size == 8 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + constexpr int NumPackets = 8; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(row, col, begin, count); + return pcast(packets.packet[0], packets.packet[1], packets.packet[2], + packets.packet[3], packets.packet[4], packets.packet[5], + packets.packet[6], packets.packet[7]); + } + + // Analogous routines for linear access. + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const { + constexpr int DstPacketSize = unpacket_traits::size; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacketSegment(index, 0, DstPacketSize, 0)); + } + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const { + constexpr int DstPacketSize = unpacket_traits::size; + using SizedSrcPacketType = typename find_packet_by_size::type; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacket(index, 0)); + } + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast(srcPacket(index, 0), srcPacket(index, 1)); + } + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast(srcPacket(index, 0), srcPacket(index, 1), + srcPacket(index, 2), srcPacket(index, 3)); + } + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packet(Index index) const { + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + return pcast(srcPacket(index, 0), srcPacket(index, 1), + srcPacket(index, 2), srcPacket(index, 3), + srcPacket(index, 4), srcPacket(index, 5), + srcPacket(index, 6), srcPacket(index, 7)); + } + + // packetSegment variants + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int DstPacketSize = unpacket_traits::size; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast(srcPacketSegment(index, begin, count, 0)); + } + // Use the source packet type with the same size as DstPacketType, if it exists + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int DstPacketSize = unpacket_traits::size; + using SizedSrcPacketType = typename find_packet_by_size::type; + constexpr int SrcBytesIncrement = DstPacketSize * sizeof(SrcType); + constexpr int SrcLoadMode = plain_enum_min(SrcBytesIncrement, LoadMode); + return pcast( + srcPacketSegment(index, begin, count, 0)); + } + // unpacket_traits::size == 2 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int NumPackets = 2; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(index, begin, count); + return pcast(packets.packet[0], packets.packet[1]); + } + // unpacket_traits::size == 4 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int NumPackets = 4; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(index, begin, count); + return pcast(packets.packet[0], packets.packet[1], packets.packet[2], + packets.packet[3]); + } + // unpacket_traits::size == 8 * SrcPacketSize + template = true> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DstPacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int NumPackets = 8; + constexpr int SrcLoadMode = plain_enum_min(SrcPacketBytes, LoadMode); + PacketBlock packets = + srcPacketSegmentHelper(index, begin, count); + return pcast(packets.packet[0], packets.packet[1], packets.packet[2], + packets.packet[3], packets.packet[4], packets.packet[5], + packets.packet[6], packets.packet[7]); + } + + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { return m_rows; } + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { return m_cols; } + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_rows * m_cols; } + + protected: + const evaluator m_argImpl; + const variable_if_dynamic m_rows; + const variable_if_dynamic m_cols; +}; + +// -------------------- CwiseTernaryOp -------------------- + +// this is a ternary expression +template +struct evaluator> + : public ternary_evaluator> { + typedef CwiseTernaryOp XprType; + typedef ternary_evaluator> Base; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : Base(xpr) {} +}; + +template +struct ternary_evaluator, IndexBased, IndexBased> + : evaluator_base> { + typedef CwiseTernaryOp XprType; + + enum { + CoeffReadCost = int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), + + Arg1Flags = evaluator::Flags, + Arg2Flags = evaluator::Flags, + Arg3Flags = evaluator::Flags, + SameType = is_same::value && + is_same::value, + StorageOrdersAgree = (int(Arg1Flags) & RowMajorBit) == (int(Arg2Flags) & RowMajorBit) && + (int(Arg1Flags) & RowMajorBit) == (int(Arg3Flags) & RowMajorBit), + Flags0 = (int(Arg1Flags) | int(Arg2Flags) | int(Arg3Flags)) & + (HereditaryBits | + (int(Arg1Flags) & int(Arg2Flags) & int(Arg3Flags) & + ((StorageOrdersAgree ? LinearAccessBit : 0) | + (functor_traits::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)))), + Flags = (Flags0 & ~RowMajorBit) | (Arg1Flags & RowMajorBit), + Alignment = plain_enum_min(plain_enum_min(evaluator::Alignment, evaluator::Alignment), + evaluator::Alignment) + }; + + EIGEN_DEVICE_FUNC explicit ternary_evaluator(const XprType& xpr) : m_d(xpr) { + EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits::Cost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_d.func()(m_d.arg1Impl.coeff(row, col), m_d.arg2Impl.coeff(row, col), m_d.arg3Impl.coeff(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_d.func()(m_d.arg1Impl.coeff(index), m_d.arg2Impl.coeff(index), m_d.arg3Impl.coeff(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_d.func().packetOp(m_d.arg1Impl.template packet(row, col), + m_d.arg2Impl.template packet(row, col), + m_d.arg3Impl.template packet(row, col)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_d.func().packetOp(m_d.arg1Impl.template packet(index), + m_d.arg2Impl.template packet(index), + m_d.arg3Impl.template packet(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_d.func().packetOp(m_d.arg1Impl.template packetSegment(row, col, begin, count), + m_d.arg2Impl.template packetSegment(row, col, begin, count), + m_d.arg3Impl.template packetSegment(row, col, begin, count)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return m_d.func().packetOp(m_d.arg1Impl.template packetSegment(index, begin, count), + m_d.arg2Impl.template packetSegment(index, begin, count), + m_d.arg3Impl.template packetSegment(index, begin, count)); + } + + protected: + // this helper permits to completely eliminate the functor if it is empty + struct Data { + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr) + : op(xpr.functor()), arg1Impl(xpr.arg1()), arg2Impl(xpr.arg2()), arg3Impl(xpr.arg3()) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const TernaryOp& func() const { return op; } + TernaryOp op; + evaluator arg1Impl; + evaluator arg2Impl; + evaluator arg3Impl; + }; + + Data m_d; +}; + +template +struct scalar_boolean_select_spec { + using DummyTernaryOp = scalar_boolean_select_op; + using DummyArg3 = CwiseBinaryOp, CmpLhsType, CmpRhsType>; + using DummyXprType = CwiseTernaryOp; + + // only use the typed comparison if it is vectorized + static constexpr bool UseTyped = functor_traits>::PacketAccess; + using CondScalar = std::conditional_t; + + using TernaryOp = scalar_boolean_select_op; + using Arg3 = CwiseBinaryOp, CmpLhsType, CmpRhsType>; + using XprType = CwiseTernaryOp; + + using Base = ternary_evaluator; +}; + +// specialization for expressions like (a < b).select(c, d) to enable full vectorization +template +struct evaluator, Arg1, Arg2, + CwiseBinaryOp, CmpLhsType, CmpRhsType>>> + : public scalar_boolean_select_spec::Base { + using Helper = scalar_boolean_select_spec; + using Base = typename Helper::Base; + using DummyXprType = typename Helper::DummyXprType; + using Arg3 = typename Helper::Arg3; + using XprType = typename Helper::XprType; + + EIGEN_DEVICE_FUNC explicit evaluator(const DummyXprType& xpr) + : Base(XprType(xpr.arg1(), xpr.arg2(), Arg3(xpr.arg3().lhs(), xpr.arg3().rhs()))) {} +}; + +// -------------------- CwiseBinaryOp -------------------- + +// this is a binary expression +template +struct evaluator> : public binary_evaluator> { + typedef CwiseBinaryOp XprType; + typedef binary_evaluator> Base; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} +}; + +template +struct binary_evaluator, IndexBased, IndexBased> + : evaluator_base> { + typedef CwiseBinaryOp XprType; + + enum { + CoeffReadCost = + int(evaluator::CoeffReadCost) + int(evaluator::CoeffReadCost) + int(functor_traits::Cost), + + LhsFlags = evaluator::Flags, + RhsFlags = evaluator::Flags, + SameType = is_same::value, + StorageOrdersAgree = (int(LhsFlags) & RowMajorBit) == (int(RhsFlags) & RowMajorBit), + Flags0 = (int(LhsFlags) | int(RhsFlags)) & + (HereditaryBits | + (int(LhsFlags) & int(RhsFlags) & + ((StorageOrdersAgree ? LinearAccessBit : 0) | + (functor_traits::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0)))), + Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit), + Alignment = plain_enum_min(evaluator::Alignment, evaluator::Alignment) + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit binary_evaluator(const XprType& xpr) : m_d(xpr) { + EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits::Cost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_d.func()(m_d.lhsImpl.coeff(row, col), m_d.rhsImpl.coeff(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_d.func()(m_d.lhsImpl.coeff(index), m_d.rhsImpl.coeff(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_d.func().packetOp(m_d.lhsImpl.template packet(row, col), + m_d.rhsImpl.template packet(row, col)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_d.func().packetOp(m_d.lhsImpl.template packet(index), + m_d.rhsImpl.template packet(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_d.func().packetOp(m_d.lhsImpl.template packetSegment(row, col, begin, count), + m_d.rhsImpl.template packetSegment(row, col, begin, count)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return m_d.func().packetOp(m_d.lhsImpl.template packetSegment(index, begin, count), + m_d.rhsImpl.template packetSegment(index, begin, count)); + } + + protected: + // this helper permits to completely eliminate the functor if it is empty + struct Data { + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr) + : op(xpr.functor()), lhsImpl(xpr.lhs()), rhsImpl(xpr.rhs()) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& func() const { return op; } + BinaryOp op; + evaluator lhsImpl; + evaluator rhsImpl; + }; + + Data m_d; +}; + +// -------------------- CwiseUnaryView -------------------- + +template +struct unary_evaluator, IndexBased> + : evaluator_base> { + typedef CwiseUnaryView XprType; + + enum { + CoeffReadCost = int(evaluator::CoeffReadCost) + int(functor_traits::Cost), + + Flags = (evaluator::Flags & (HereditaryBits | LinearAccessBit | DirectAccessBit)), + + Alignment = 0 // FIXME it is not very clear why alignment is necessarily lost... + }; + + EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& op) : m_d(op) { + EIGEN_INTERNAL_CHECK_COST_VALUE(functor_traits::Cost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_d.func()(m_d.argImpl.coeff(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_d.func()(m_d.argImpl.coeff(index)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + return m_d.func()(m_d.argImpl.coeffRef(row, col)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + return m_d.func()(m_d.argImpl.coeffRef(index)); + } + + protected: + // this helper permits to completely eliminate the functor if it is empty + struct Data { + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Data(const XprType& xpr) + : op(xpr.functor()), argImpl(xpr.nestedExpression()) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& func() const { return op; } + UnaryOp op; + evaluator argImpl; + }; + + Data m_d; +}; + +// -------------------- Map -------------------- + +// FIXME perhaps the PlainObjectType could be provided by Derived::PlainObject ? +// but that might complicate template specialization +template +struct mapbase_evaluator; + +template +struct mapbase_evaluator : evaluator_base { + typedef Derived XprType; + typedef typename XprType::PointerType PointerType; + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + enum { + IsRowMajor = XprType::RowsAtCompileTime, + ColsAtCompileTime = XprType::ColsAtCompileTime, + CoeffReadCost = NumTraits::ReadCost + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit mapbase_evaluator(const XprType& map) + : m_data(const_cast(map.data())), + m_innerStride(map.innerStride()), + m_outerStride(map.outerStride()) { + EIGEN_STATIC_ASSERT(check_implication((evaluator::Flags & PacketAccessBit) != 0, + inner_stride_at_compile_time::ret == 1), + PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_data[col * colStride() + row * rowStride()]; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_data[index * m_innerStride.value()]; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + return m_data[col * colStride() + row * rowStride()]; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_data[index * m_innerStride.value()]; } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + PointerType ptr = m_data + row * rowStride() + col * colStride(); + return ploadt(ptr); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return ploadt(m_data + index * m_innerStride.value()); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + PointerType ptr = m_data + row * rowStride() + col * colStride(); + pstoret(ptr, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + pstoret(m_data + index * m_innerStride.value(), x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + PointerType ptr = m_data + row * rowStride() + col * colStride(); + return ploadtSegment(ptr, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return ploadtSegment(m_data + index * m_innerStride.value(), begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + PointerType ptr = m_data + row * rowStride() + col * colStride(); + pstoretSegment(ptr, x, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + pstoretSegment(m_data + index * m_innerStride.value(), x, begin, count); + } + + protected: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowStride() const noexcept { + return XprType::IsRowMajor ? m_outerStride.value() : m_innerStride.value(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colStride() const noexcept { + return XprType::IsRowMajor ? m_innerStride.value() : m_outerStride.value(); + } + + PointerType m_data; + const variable_if_dynamic m_innerStride; + const variable_if_dynamic m_outerStride; +}; + +template +struct evaluator> + : public mapbase_evaluator, PlainObjectType> { + typedef Map XprType; + typedef typename XprType::Scalar Scalar; + // TODO: should check for smaller packet types once we can handle multi-sized packet types + typedef typename packet_traits::type PacketScalar; + + enum { + InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0 + ? int(PlainObjectType::InnerStrideAtCompileTime) + : int(StrideType::InnerStrideAtCompileTime), + OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0 + ? int(PlainObjectType::OuterStrideAtCompileTime) + : int(StrideType::OuterStrideAtCompileTime), + HasNoInnerStride = InnerStrideAtCompileTime == 1, + HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0, + HasNoStride = HasNoInnerStride && HasNoOuterStride, + IsDynamicSize = PlainObjectType::SizeAtCompileTime == Dynamic, + + PacketAccessMask = bool(HasNoInnerStride) ? ~int(0) : ~int(PacketAccessBit), + LinearAccessMask = + bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime) ? ~int(0) : ~int(LinearAccessBit), + Flags = int(evaluator::Flags) & (LinearAccessMask & PacketAccessMask), + + Alignment = int(MapOptions) & int(AlignedMask) + }; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& map) : mapbase_evaluator(map) {} +}; + +// -------------------- Ref -------------------- + +template +struct evaluator> + : public mapbase_evaluator, PlainObjectType> { + typedef Ref XprType; + + enum { + Flags = evaluator>::Flags, + Alignment = evaluator>::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& ref) + : mapbase_evaluator(ref) {} +}; + +// -------------------- Block -------------------- + +template ::ret> +struct block_evaluator; + +template +struct evaluator> + : block_evaluator { + typedef Block XprType; + typedef typename XprType::Scalar Scalar; + // TODO: should check for smaller packet types once we can handle multi-sized packet types + typedef typename packet_traits::type PacketScalar; + + enum { + CoeffReadCost = evaluator::CoeffReadCost, + + RowsAtCompileTime = traits::RowsAtCompileTime, + ColsAtCompileTime = traits::ColsAtCompileTime, + MaxRowsAtCompileTime = traits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = traits::MaxColsAtCompileTime, + + ArgTypeIsRowMajor = (int(evaluator::Flags) & RowMajorBit) != 0, + IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1 + : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0 + : ArgTypeIsRowMajor, + HasSameStorageOrderAsArgType = (IsRowMajor == ArgTypeIsRowMajor), + InnerSize = IsRowMajor ? int(ColsAtCompileTime) : int(RowsAtCompileTime), + InnerStrideAtCompileTime = HasSameStorageOrderAsArgType ? int(inner_stride_at_compile_time::ret) + : int(outer_stride_at_compile_time::ret), + OuterStrideAtCompileTime = HasSameStorageOrderAsArgType ? int(outer_stride_at_compile_time::ret) + : int(inner_stride_at_compile_time::ret), + MaskPacketAccessBit = (InnerStrideAtCompileTime == 1 || HasSameStorageOrderAsArgType) ? PacketAccessBit : 0, + + FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1 || + (InnerPanel && (evaluator::Flags & LinearAccessBit))) + ? LinearAccessBit + : 0, + FlagsRowMajorBit = XprType::Flags & RowMajorBit, + Flags0 = evaluator::Flags & ((HereditaryBits & ~RowMajorBit) | DirectAccessBit | MaskPacketAccessBit), + Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit, + + PacketAlignment = unpacket_traits::alignment, + Alignment0 = (InnerPanel && (OuterStrideAtCompileTime != Dynamic) && (OuterStrideAtCompileTime != 0) && + (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % int(PacketAlignment)) == 0)) + ? int(PacketAlignment) + : 0, + Alignment = plain_enum_min(evaluator::Alignment, Alignment0) + }; + typedef block_evaluator block_evaluator_type; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& block) : block_evaluator_type(block) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } +}; + +// no direct-access => dispatch to a unary evaluator +template +struct block_evaluator + : unary_evaluator> { + typedef Block XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit block_evaluator(const XprType& block) + : unary_evaluator(block) {} +}; + +template +struct unary_evaluator, IndexBased> + : evaluator_base> { + typedef Block XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& block) + : m_argImpl(block.nestedExpression()), + m_startRow(block.startRow()), + m_startCol(block.startCol()), + m_linear_offset(ForwardLinearAccess + ? (ArgType::IsRowMajor + ? block.startRow() * block.nestedExpression().cols() + block.startCol() + : block.startCol() * block.nestedExpression().rows() + block.startRow()) + : 0) {} + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + enum { + RowsAtCompileTime = XprType::RowsAtCompileTime, + ForwardLinearAccess = (InnerPanel || int(XprType::IsRowMajor) == int(ArgType::IsRowMajor)) && + bool(evaluator::Flags & LinearAccessBit) + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_argImpl.coeff(m_startRow.value() + row, m_startCol.value() + col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return linear_coeff_impl(index, bool_constant()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + return m_argImpl.coeffRef(m_startRow.value() + row, m_startCol.value() + col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + return linear_coeffRef_impl(index, bool_constant()); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_argImpl.template packet(m_startRow.value() + row, m_startCol.value() + col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + if (ForwardLinearAccess) + return m_argImpl.template packet(m_linear_offset.value() + index); + else + return packet(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + return m_argImpl.template writePacket(m_startRow.value() + row, m_startCol.value() + col, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + if (ForwardLinearAccess) + return m_argImpl.template writePacket(m_linear_offset.value() + index, x); + else + return writePacket(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0, + x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_argImpl.template packetSegment(m_startRow.value() + row, m_startCol.value() + col, + begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + if (ForwardLinearAccess) + return m_argImpl.template packetSegment(m_linear_offset.value() + index, begin, count); + else + return packetSegment(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0, + begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + return m_argImpl.template writePacketSegment(m_startRow.value() + row, + m_startCol.value() + col, x, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + if (ForwardLinearAccess) + return m_argImpl.template writePacketSegment(m_linear_offset.value() + index, x, begin, + count); + else + return writePacketSegment(RowsAtCompileTime == 1 ? 0 : index, + RowsAtCompileTime == 1 ? index : 0, x, begin, count); + } + + protected: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType + linear_coeff_impl(Index index, internal::true_type /* ForwardLinearAccess */) const { + return m_argImpl.coeff(m_linear_offset.value() + index); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType + linear_coeff_impl(Index index, internal::false_type /* not ForwardLinearAccess */) const { + return coeff(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& linear_coeffRef_impl(Index index, + internal::true_type /* ForwardLinearAccess */) { + return m_argImpl.coeffRef(m_linear_offset.value() + index); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& linear_coeffRef_impl( + Index index, internal::false_type /* not ForwardLinearAccess */) { + return coeffRef(RowsAtCompileTime == 1 ? 0 : index, RowsAtCompileTime == 1 ? index : 0); + } + + evaluator m_argImpl; + const variable_if_dynamic m_startRow; + const variable_if_dynamic m_startCol; + const variable_if_dynamic m_linear_offset; +}; + +// TODO: This evaluator does not actually use the child evaluator; +// all action is via the data() as returned by the Block expression. + +template +struct block_evaluator + : mapbase_evaluator, + typename Block::PlainObject> { + typedef Block XprType; + typedef typename XprType::Scalar Scalar; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit block_evaluator(const XprType& block) + : mapbase_evaluator(block) { + eigen_internal_assert((internal::is_constant_evaluated() || + (std::uintptr_t(block.data()) % plain_enum_max(1, evaluator::Alignment)) == 0) && + "data is not aligned"); + } +}; + +// -------------------- Replicate -------------------- + +template +struct unary_evaluator> + : evaluator_base> { + typedef Replicate XprType; + typedef typename XprType::CoeffReturnType CoeffReturnType; + enum { Factor = (RowFactor == Dynamic || ColFactor == Dynamic) ? Dynamic : RowFactor * ColFactor }; + typedef typename nested_eval::type ArgTypeNested; + typedef remove_all_t ArgTypeNestedCleaned; + + enum { + CoeffReadCost = evaluator::CoeffReadCost, + LinearAccessMask = XprType::IsVectorAtCompileTime ? LinearAccessBit : 0, + Flags = (evaluator::Flags & (HereditaryBits | LinearAccessMask) & ~RowMajorBit) | + (traits::Flags & RowMajorBit), + + Alignment = evaluator::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& replicate) + : m_arg(replicate.nestedExpression()), + m_argImpl(m_arg), + m_rows(replicate.nestedExpression().rows()), + m_cols(replicate.nestedExpression().cols()) {} + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + // try to avoid using modulo; this is a pure optimization strategy + const Index actual_row = traits::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value(); + const Index actual_col = traits::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value(); + + return m_argImpl.coeff(actual_row, actual_col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + // try to avoid using modulo; this is a pure optimization strategy + const Index actual_index = traits::RowsAtCompileTime == 1 + ? (ColFactor == 1 ? index : index % m_cols.value()) + : (RowFactor == 1 ? index : index % m_rows.value()); + + return m_argImpl.coeff(actual_index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + const Index actual_row = traits::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value(); + const Index actual_col = traits::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value(); + + return m_argImpl.template packet(actual_row, actual_col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + const Index actual_index = traits::RowsAtCompileTime == 1 + ? (ColFactor == 1 ? index : index % m_cols.value()) + : (RowFactor == 1 ? index : index % m_rows.value()); + + return m_argImpl.template packet(actual_index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + const Index actual_row = traits::RowsAtCompileTime == 1 ? 0 : RowFactor == 1 ? row : row % m_rows.value(); + const Index actual_col = traits::ColsAtCompileTime == 1 ? 0 : ColFactor == 1 ? col : col % m_cols.value(); + + return m_argImpl.template packetSegment(actual_row, actual_col, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + const Index actual_index = traits::RowsAtCompileTime == 1 + ? (ColFactor == 1 ? index : index % m_cols.value()) + : (RowFactor == 1 ? index : index % m_rows.value()); + + return m_argImpl.template packetSegment(actual_index, begin, count); + } + + protected: + const ArgTypeNested m_arg; + evaluator m_argImpl; + const variable_if_dynamic m_rows; + const variable_if_dynamic m_cols; +}; + +// -------------------- MatrixWrapper and ArrayWrapper -------------------- +// +// evaluator_wrapper_base is a common base class for the +// MatrixWrapper and ArrayWrapper evaluators. + +template +struct evaluator_wrapper_base : evaluator_base { + typedef remove_all_t ArgType; + enum { + CoeffReadCost = evaluator::CoeffReadCost, + Flags = evaluator::Flags, + Alignment = evaluator::Alignment + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator_wrapper_base(const ArgType& arg) : m_argImpl(arg) {} + + typedef typename ArgType::Scalar Scalar; + typedef typename ArgType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_argImpl.coeff(row, col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { return m_argImpl.coeff(index); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { return m_argImpl.coeffRef(row, col); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { return m_argImpl.coeffRef(index); } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return m_argImpl.template packet(row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_argImpl.template packet(index); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + m_argImpl.template writePacket(row, col, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + m_argImpl.template writePacket(index, x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return m_argImpl.template packetSegment(row, col, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + return m_argImpl.template packetSegment(index, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + m_argImpl.template writePacketSegment(row, col, x, begin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + m_argImpl.template writePacketSegment(index, x, begin, count); + } + + protected: + evaluator m_argImpl; +}; + +template +struct unary_evaluator> : evaluator_wrapper_base> { + typedef MatrixWrapper XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& wrapper) + : evaluator_wrapper_base>(wrapper.nestedExpression()) {} +}; + +template +struct unary_evaluator> : evaluator_wrapper_base> { + typedef ArrayWrapper XprType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& wrapper) + : evaluator_wrapper_base>(wrapper.nestedExpression()) {} +}; + +// -------------------- Reverse -------------------- + +// defined in Reverse.h: +template +struct reverse_packet_cond; + +template +struct unary_evaluator> : evaluator_base> { + typedef Reverse XprType; + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + enum { + IsRowMajor = XprType::IsRowMajor, + IsColMajor = !IsRowMajor, + ReverseRow = (Direction == Vertical) || (Direction == BothDirections), + ReverseCol = (Direction == Horizontal) || (Direction == BothDirections), + ReversePacket = (Direction == BothDirections) || ((Direction == Vertical) && IsColMajor) || + ((Direction == Horizontal) && IsRowMajor), + + CoeffReadCost = evaluator::CoeffReadCost, + + // let's enable LinearAccess only with vectorization because of the product overhead + // FIXME enable DirectAccess with negative strides? + Flags0 = evaluator::Flags, + LinearAccess = + ((Direction == BothDirections) && (int(Flags0) & PacketAccessBit)) || + ((ReverseRow && XprType::ColsAtCompileTime == 1) || (ReverseCol && XprType::RowsAtCompileTime == 1)) + ? LinearAccessBit + : 0, + + Flags = int(Flags0) & (HereditaryBits | PacketAccessBit | LinearAccess), + + Alignment = 0 // FIXME in some rare cases, Alignment could be preserved, like a Vector4f. + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit unary_evaluator(const XprType& reverse) + : m_argImpl(reverse.nestedExpression()), + m_rows(ReverseRow ? reverse.nestedExpression().rows() : 1), + m_cols(ReverseCol ? reverse.nestedExpression().cols() : 1) {} + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + return m_argImpl.coeff(ReverseRow ? m_rows.value() - row - 1 : row, ReverseCol ? m_cols.value() - col - 1 : col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_argImpl.coeff(m_rows.value() * m_cols.value() - index - 1); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + return m_argImpl.coeffRef(ReverseRow ? m_rows.value() - row - 1 : row, ReverseCol ? m_cols.value() - col - 1 : col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + return m_argImpl.coeffRef(m_rows.value() * m_cols.value() - index - 1); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1; + static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1; + using reverse_packet = reverse_packet_cond; + + Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row; + Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col; + + return reverse_packet::run(m_argImpl.template packet(actualRow, actualCol)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + static constexpr int PacketSize = unpacket_traits::size; + + Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize; + + return preverse(m_argImpl.template packet(actualIndex)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index row, Index col, const PacketType& x) { + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1; + static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1; + using reverse_packet = reverse_packet_cond; + + Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row; + Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col; + + m_argImpl.template writePacket(actualRow, actualCol, reverse_packet::run(x)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacket(Index index, const PacketType& x) { + static constexpr int PacketSize = unpacket_traits::size; + + Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize; + + m_argImpl.template writePacket(actualIndex, preverse(x)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1; + static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1; + using reverse_packet = reverse_packet_cond; + + Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row; + Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col; + Index actualBegin = ReversePacket ? (PacketSize - count - begin) : begin; + + return reverse_packet::run( + m_argImpl.template packetSegment(actualRow, actualCol, actualBegin, count)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + static constexpr int PacketSize = unpacket_traits::size; + + Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize; + Index actualBegin = PacketSize - count - begin; + + return preverse(m_argImpl.template packetSegment(actualIndex, actualBegin, count)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index row, Index col, const PacketType& x, Index begin, + Index count) { + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1; + static constexpr int OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1; + using reverse_packet = reverse_packet_cond; + + Index actualRow = ReverseRow ? m_rows.value() - row - OffsetRow : row; + Index actualCol = ReverseCol ? m_cols.value() - col - OffsetCol : col; + Index actualBegin = ReversePacket ? (PacketSize - count - begin) : begin; + + m_argImpl.template writePacketSegment(actualRow, actualCol, reverse_packet::run(x), actualBegin, count); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void writePacketSegment(Index index, const PacketType& x, Index begin, + Index count) { + static constexpr int PacketSize = unpacket_traits::size; + + Index actualIndex = m_rows.value() * m_cols.value() - index - PacketSize; + Index actualBegin = PacketSize - count - begin; + + m_argImpl.template writePacketSegment(actualIndex, preverse(x), actualBegin, count); + } + + protected: + evaluator m_argImpl; + + // If we do not reverse rows, then we do not need to know the number of rows; same for columns + // Nonetheless, in this case it is important to set to 1 such that the coeff(index) method works fine for vectors. + const variable_if_dynamic m_rows; + const variable_if_dynamic m_cols; +}; + +// -------------------- Diagonal -------------------- + +template +struct evaluator> : evaluator_base> { + typedef Diagonal XprType; + + enum { + CoeffReadCost = evaluator::CoeffReadCost, + + Flags = + (unsigned int)(evaluator::Flags & (HereditaryBits | DirectAccessBit) & ~RowMajorBit) | LinearAccessBit, + + Alignment = 0 + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& diagonal) + : m_argImpl(diagonal.nestedExpression()), m_index(diagonal.index()) {} + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index) const { + return m_argImpl.coeff(row + rowOffset(), row + colOffset()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const { + return m_argImpl.coeff(index + rowOffset(), index + colOffset()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index) { + return m_argImpl.coeffRef(row + rowOffset(), row + colOffset()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + return m_argImpl.coeffRef(index + rowOffset(), index + colOffset()); + } + + protected: + evaluator m_argImpl; + const variable_if_dynamicindex m_index; + + private: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowOffset() const { + return m_index.value() > 0 ? 0 : -m_index.value(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colOffset() const { + return m_index.value() > 0 ? m_index.value() : 0; + } +}; + +//---------------------------------------------------------------------- +// deprecated code +//---------------------------------------------------------------------- + +// -------------------- EvalToTemp -------------------- + +// expression class for evaluating nested expression to a temporary + +template +class EvalToTemp; + +template +struct traits> : public traits {}; + +template +class EvalToTemp : public dense_xpr_base>::type { + public: + typedef typename dense_xpr_base::type Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(EvalToTemp) + + explicit EvalToTemp(const ArgType& arg) : m_arg(arg) {} + + const ArgType& arg() const { return m_arg; } + + constexpr Index rows() const noexcept { return m_arg.rows(); } + + constexpr Index cols() const noexcept { return m_arg.cols(); } + + private: + const ArgType& m_arg; +}; + +template +struct evaluator> : public evaluator { + typedef EvalToTemp XprType; + typedef typename ArgType::PlainObject PlainObject; + typedef evaluator Base; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : m_result(xpr.arg()) { + internal::construct_at(this, m_result); + } + + // This constructor is used when nesting an EvalTo evaluator in another evaluator + EIGEN_DEVICE_FUNC evaluator(const ArgType& arg) : m_result(arg) { internal::construct_at(this, m_result); } + + protected: + PlainObject m_result; +}; + +} // namespace internal + +} // end namespace Eigen + +#endif // EIGEN_COREEVALUATORS_H diff --git a/inst/include/Eigen/src/Core/CoreIterators.h b/inst/include/Eigen/src/Core/CoreIterators.h index 6da4683d..f62cf238 100644 --- a/inst/include/Eigen/src/Core/CoreIterators.h +++ b/inst/include/Eigen/src/Core/CoreIterators.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2010 Gael Guennebaud +// Copyright (C) 2008-2014 Gael Guennebaud // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed @@ -10,52 +10,132 @@ #ifndef EIGEN_COREITERATORS_H #define EIGEN_COREITERATORS_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { /* This file contains the respective InnerIterator definition of the expressions defined in Eigen/Core */ -/** \ingroup SparseCore_Module - * \class InnerIterator - * \brief An InnerIterator allows to loop over the element of a sparse (or dense) matrix or expression - * - * todo - */ - -// generic version for dense matrix and expressions -template class DenseBase::InnerIterator -{ - protected: - typedef typename Derived::Scalar Scalar; - typedef typename Derived::Index Index; - - enum { IsRowMajor = (Derived::Flags&RowMajorBit)==RowMajorBit }; - public: - EIGEN_STRONG_INLINE InnerIterator(const Derived& expr, Index outer) - : m_expression(expr), m_inner(0), m_outer(outer), m_end(expr.innerSize()) - {} - - EIGEN_STRONG_INLINE Scalar value() const - { - return (IsRowMajor) ? m_expression.coeff(m_outer, m_inner) - : m_expression.coeff(m_inner, m_outer); - } - - EIGEN_STRONG_INLINE InnerIterator& operator++() { m_inner++; return *this; } - - EIGEN_STRONG_INLINE Index index() const { return m_inner; } - inline Index row() const { return IsRowMajor ? m_outer : index(); } - inline Index col() const { return IsRowMajor ? index() : m_outer; } - - EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner>=0; } - - protected: - const Derived& m_expression; - Index m_inner; - const Index m_outer; - const Index m_end; +namespace internal { + +template +class inner_iterator_selector; + +} + +/** \class InnerIterator + * \brief An InnerIterator allows to loop over the element of any matrix expression. + * + * \warning To be used with care because an evaluator is constructed every time an InnerIterator iterator is + * constructed. + * + * TODO: add a usage example + */ +template +class InnerIterator { + protected: + typedef internal::inner_iterator_selector::Kind> IteratorType; + typedef internal::evaluator EvaluatorType; + typedef typename internal::traits::Scalar Scalar; + + public: + /** Construct an iterator over the \a outerId -th row or column of \a xpr */ + InnerIterator(const XprType &xpr, const Index &outerId) : m_eval(xpr), m_iter(m_eval, outerId, xpr.innerSize()) {} + + /// \returns the value of the current coefficient. + EIGEN_STRONG_INLINE Scalar value() const { return m_iter.value(); } + /** Increment the iterator \c *this to the next non-zero coefficient. + * Explicit zeros are not skipped over. To skip explicit zeros, see class SparseView + */ + EIGEN_STRONG_INLINE InnerIterator &operator++() { + m_iter.operator++(); + return *this; + } + EIGEN_STRONG_INLINE InnerIterator &operator+=(Index i) { + m_iter.operator+=(i); + return *this; + } + EIGEN_STRONG_INLINE InnerIterator operator+(Index i) { + InnerIterator result(*this); + result += i; + return result; + } + + /// \returns the column or row index of the current coefficient. + EIGEN_STRONG_INLINE Index index() const { return m_iter.index(); } + /// \returns the row index of the current coefficient. + EIGEN_STRONG_INLINE Index row() const { return m_iter.row(); } + /// \returns the column index of the current coefficient. + EIGEN_STRONG_INLINE Index col() const { return m_iter.col(); } + /// \returns \c true if the iterator \c *this still references a valid coefficient. + EIGEN_STRONG_INLINE operator bool() const { return m_iter; } + + protected: + EvaluatorType m_eval; + IteratorType m_iter; + + private: + // If you get here, then you're not using the right InnerIterator type, e.g.: + // SparseMatrix A; + // SparseMatrix::InnerIterator it(A,0); + template + InnerIterator(const EigenBase &, Index outer); }; -} // end namespace Eigen +namespace internal { + +// Generic inner iterator implementation for dense objects +template +class inner_iterator_selector { + protected: + typedef evaluator EvaluatorType; + typedef typename traits::Scalar Scalar; + enum { IsRowMajor = (XprType::Flags & RowMajorBit) == RowMajorBit }; + + public: + EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, const Index &innerSize) + : m_eval(eval), m_inner(0), m_outer(outerId), m_end(innerSize) {} + + EIGEN_STRONG_INLINE Scalar value() const { + return (IsRowMajor) ? m_eval.coeff(m_outer, m_inner) : m_eval.coeff(m_inner, m_outer); + } + + EIGEN_STRONG_INLINE inner_iterator_selector &operator++() { + m_inner++; + return *this; + } + + EIGEN_STRONG_INLINE Index index() const { return m_inner; } + inline Index row() const { return IsRowMajor ? m_outer : index(); } + inline Index col() const { return IsRowMajor ? index() : m_outer; } + + EIGEN_STRONG_INLINE operator bool() const { return m_inner < m_end && m_inner >= 0; } + + protected: + const EvaluatorType &m_eval; + Index m_inner; + const Index m_outer; + const Index m_end; +}; + +// For iterator-based evaluator, inner-iterator is already implemented as +// evaluator<>::InnerIterator +template +class inner_iterator_selector : public evaluator::InnerIterator { + protected: + typedef typename evaluator::InnerIterator Base; + typedef evaluator EvaluatorType; + + public: + EIGEN_STRONG_INLINE inner_iterator_selector(const EvaluatorType &eval, const Index &outerId, + const Index & /*innerSize*/) + : Base(eval, outerId) {} +}; + +} // end namespace internal + +} // end namespace Eigen -#endif // EIGEN_COREITERATORS_H +#endif // EIGEN_COREITERATORS_H diff --git a/inst/include/Eigen/src/Core/CwiseBinaryOp.h b/inst/include/Eigen/src/Core/CwiseBinaryOp.h index 519a866e..e2b2da5a 100644 --- a/inst/include/Eigen/src/Core/CwiseBinaryOp.h +++ b/inst/include/Eigen/src/Core/CwiseBinaryOp.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2009 Gael Guennebaud +// Copyright (C) 2008-2014 Gael Guennebaud // Copyright (C) 2006-2008 Benoit Jacob // // This Source Code Form is subject to the terms of the Mozilla @@ -11,35 +11,17 @@ #ifndef EIGEN_CWISE_BINARY_OP_H #define EIGEN_CWISE_BINARY_OP_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class CwiseBinaryOp - * \ingroup Core_Module - * - * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions - * - * \param BinaryOp template functor implementing the operator - * \param Lhs the type of the left-hand side - * \param Rhs the type of the right-hand side - * - * This class represents an expression where a coefficient-wise binary operator is applied to two expressions. - * It is the return type of binary operators, by which we mean only those binary operators where - * both the left-hand side and the right-hand side are Eigen expressions. - * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp. - * - * Most of the time, this is the only way that it is used, so you typically don't have to name - * CwiseBinaryOp types explicitly. - * - * \sa MatrixBase::binaryExpr(const MatrixBase &,const CustomBinaryOp &) const, class CwiseUnaryOp, class CwiseNullaryOp - */ +namespace Eigen { namespace internal { -template -struct traits > -{ +template +struct traits> { // we must not inherit from traits since it has // the potential to cause problems with MSVC - typedef typename remove_all::type Ancestor; + typedef remove_all_t Ancestor; typedef typename traits::XprKind XprKind; enum { RowsAtCompileTime = traits::RowsAtCompileTime, @@ -50,181 +32,135 @@ struct traits > // even though we require Lhs and Rhs to have the same scalar type (see CwiseBinaryOp constructor), // we still want to handle the case when the result type is different. - typedef typename result_of< - BinaryOp( - typename Lhs::Scalar, - typename Rhs::Scalar - ) - >::type Scalar; - typedef typename promote_storage_type::StorageKind, - typename traits::StorageKind>::ret StorageKind; - typedef typename promote_index_type::Index, - typename traits::Index>::type Index; + typedef typename result_of::type Scalar; + typedef typename cwise_promote_storage_type::StorageKind, typename traits::StorageKind, + BinaryOp>::ret StorageKind; + typedef typename promote_index_type::StorageIndex, typename traits::StorageIndex>::type + StorageIndex; typedef typename Lhs::Nested LhsNested; typedef typename Rhs::Nested RhsNested; - typedef typename remove_reference::type _LhsNested; - typedef typename remove_reference::type _RhsNested; + typedef std::remove_reference_t LhsNested_; + typedef std::remove_reference_t RhsNested_; enum { - LhsCoeffReadCost = _LhsNested::CoeffReadCost, - RhsCoeffReadCost = _RhsNested::CoeffReadCost, - LhsFlags = _LhsNested::Flags, - RhsFlags = _RhsNested::Flags, - SameType = is_same::value, - StorageOrdersAgree = (int(Lhs::Flags)&RowMajorBit)==(int(Rhs::Flags)&RowMajorBit), - Flags0 = (int(LhsFlags) | int(RhsFlags)) & ( - HereditaryBits - | (int(LhsFlags) & int(RhsFlags) & - ( AlignedBit - | (StorageOrdersAgree ? LinearAccessBit : 0) - | (functor_traits::PacketAccess && StorageOrdersAgree && SameType ? PacketAccessBit : 0) - ) - ) - ), - Flags = (Flags0 & ~RowMajorBit) | (LhsFlags & RowMajorBit), - Cost0 = EIGEN_ADD_COST(LhsCoeffReadCost,RhsCoeffReadCost), - CoeffReadCost = EIGEN_ADD_COST(Cost0,functor_traits::Cost) + Flags = cwise_promote_storage_order::StorageKind, typename traits::StorageKind, + LhsNested_::Flags & RowMajorBit, RhsNested_::Flags & RowMajorBit>::value }; }; -} // end namespace internal - -// we require Lhs and Rhs to have the same scalar type. Currently there is no example of a binary functor -// that would take two operands of different types. If there were such an example, then this check should be -// moved to the BinaryOp functors, on a per-case basis. This would however require a change in the BinaryOp functors, as -// currently they take only one typename Scalar template parameter. -// It is tempting to always allow mixing different types but remember that this is often impossible in the vectorized paths. -// So allowing mixing different types gives very unexpected errors when enabling vectorization, when the user tries to -// add together a float matrix and a double matrix. -#define EIGEN_CHECK_BINARY_COMPATIBILIY(BINOP,LHS,RHS) \ - EIGEN_STATIC_ASSERT((internal::functor_is_product_like::ret \ - ? int(internal::scalar_product_traits::Defined) \ - : int(internal::is_same::value)), \ - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - -template +} // end namespace internal + +template class CwiseBinaryOpImpl; -template -class CwiseBinaryOp : internal::no_assignment_operator, - public CwiseBinaryOpImpl< - BinaryOp, Lhs, Rhs, - typename internal::promote_storage_type::StorageKind, - typename internal::traits::StorageKind>::ret> -{ - public: - - typedef typename CwiseBinaryOpImpl< - BinaryOp, Lhs, Rhs, - typename internal::promote_storage_type::StorageKind, - typename internal::traits::StorageKind>::ret>::Base Base; - EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp) - - typedef typename internal::nested::type LhsNested; - typedef typename internal::nested::type RhsNested; - typedef typename internal::remove_reference::type _LhsNested; - typedef typename internal::remove_reference::type _RhsNested; - - EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, const BinaryOp& func = BinaryOp()) - : m_lhs(aLhs), m_rhs(aRhs), m_functor(func) - { - EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp,typename Lhs::Scalar,typename Rhs::Scalar); - // require the sizes to match - EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs) - eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols()); - } - - EIGEN_STRONG_INLINE Index rows() const { - // return the fixed size type if available to enable compile time optimizations - if (internal::traits::type>::RowsAtCompileTime==Dynamic) - return m_rhs.rows(); - else - return m_lhs.rows(); - } - EIGEN_STRONG_INLINE Index cols() const { - // return the fixed size type if available to enable compile time optimizations - if (internal::traits::type>::ColsAtCompileTime==Dynamic) - return m_rhs.cols(); - else - return m_lhs.cols(); - } - - /** \returns the left hand side nested expression */ - const _LhsNested& lhs() const { return m_lhs; } - /** \returns the right hand side nested expression */ - const _RhsNested& rhs() const { return m_rhs; } - /** \returns the functor representing the binary operation */ - const BinaryOp& functor() const { return m_functor; } - - protected: - LhsNested m_lhs; - RhsNested m_rhs; - const BinaryOp m_functor; +/** \class CwiseBinaryOp + * \ingroup Core_Module + * + * \brief Generic expression where a coefficient-wise binary operator is applied to two expressions + * + * \tparam BinaryOp template functor implementing the operator + * \tparam LhsType the type of the left-hand side + * \tparam RhsType the type of the right-hand side + * + * This class represents an expression where a coefficient-wise binary operator is applied to two expressions. + * It is the return type of binary operators, by which we mean only those binary operators where + * both the left-hand side and the right-hand side are Eigen expressions. + * For example, the return type of matrix1+matrix2 is a CwiseBinaryOp. + * + * Most of the time, this is the only way that it is used, so you typically don't have to name + * CwiseBinaryOp types explicitly. + * + * \sa MatrixBase::binaryExpr(const MatrixBase &,const CustomBinaryOp &) const, class CwiseUnaryOp, class + * CwiseNullaryOp + */ +template +class CwiseBinaryOp : public CwiseBinaryOpImpl::StorageKind, + typename internal::traits::StorageKind, BinaryOp>::ret>, + internal::no_assignment_operator { + public: + typedef internal::remove_all_t Functor; + typedef internal::remove_all_t Lhs; + typedef internal::remove_all_t Rhs; + + typedef typename CwiseBinaryOpImpl< + BinaryOp, LhsType, RhsType, + typename internal::cwise_promote_storage_type::StorageKind, + typename internal::traits::StorageKind, BinaryOp>::ret>::Base + Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseBinaryOp) + + EIGEN_CHECK_BINARY_COMPATIBILIY(BinaryOp, typename Lhs::Scalar, typename Rhs::Scalar) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Lhs, Rhs) + + typedef typename internal::ref_selector::type LhsNested; + typedef typename internal::ref_selector::type RhsNested; + typedef std::remove_reference_t LhsNested_; + typedef std::remove_reference_t RhsNested_; + +#if EIGEN_COMP_MSVC + // Required for Visual Studio or the Copy constructor will probably not get inlined! + EIGEN_STRONG_INLINE CwiseBinaryOp(const CwiseBinaryOp&) = default; +#endif + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseBinaryOp(const Lhs& aLhs, const Rhs& aRhs, + const BinaryOp& func = BinaryOp()) + : m_lhs(aLhs), m_rhs(aRhs), m_functor(func) { + eigen_assert(aLhs.rows() == aRhs.rows() && aLhs.cols() == aRhs.cols()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { + // return the fixed size type if available to enable compile time optimizations + return internal::traits>::RowsAtCompileTime == Dynamic ? m_rhs.rows() + : m_lhs.rows(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { + // return the fixed size type if available to enable compile time optimizations + return internal::traits>::ColsAtCompileTime == Dynamic ? m_rhs.cols() + : m_lhs.cols(); + } + + /** \returns the left hand side nested expression */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const LhsNested_& lhs() const { return m_lhs; } + /** \returns the right hand side nested expression */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const RhsNested_& rhs() const { return m_rhs; } + /** \returns the functor representing the binary operation */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const BinaryOp& functor() const { return m_functor; } + + protected: + LhsNested m_lhs; + RhsNested m_rhs; + const BinaryOp m_functor; }; -template -class CwiseBinaryOpImpl - : public internal::dense_xpr_base >::type -{ - typedef CwiseBinaryOp Derived; - public: - - typedef typename internal::dense_xpr_base >::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE( Derived ) - - EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const - { - return derived().functor()(derived().lhs().coeff(rowId, colId), - derived().rhs().coeff(rowId, colId)); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const - { - return derived().functor().packetOp(derived().lhs().template packet(rowId, colId), - derived().rhs().template packet(rowId, colId)); - } - - EIGEN_STRONG_INLINE const Scalar coeff(Index index) const - { - return derived().functor()(derived().lhs().coeff(index), - derived().rhs().coeff(index)); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index index) const - { - return derived().functor().packetOp(derived().lhs().template packet(index), - derived().rhs().template packet(index)); - } +// Generic API dispatcher +template +class CwiseBinaryOpImpl : public internal::generic_xpr_base>::type { + public: + typedef typename internal::generic_xpr_base>::type Base; }; /** replaces \c *this by \c *this - \a other. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -MatrixBase::operator-=(const MatrixBase &other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); + * + * \returns a reference to \c *this + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator-=(const MatrixBase& other) { + call_assignment(derived(), other.derived(), internal::sub_assign_op()); return derived(); } /** replaces \c *this by \c *this + \a other. - * - * \returns a reference to \c *this - */ -template -template -EIGEN_STRONG_INLINE Derived & -MatrixBase::operator+=(const MatrixBase& other) -{ - SelfCwiseBinaryOp, Derived, OtherDerived> tmp(derived()); - tmp = other.derived(); + * + * \returns a reference to \c *this + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::operator+=(const MatrixBase& other) { + call_assignment(derived(), other.derived(), internal::add_assign_op()); return derived(); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_CWISE_BINARY_OP_H +#endif // EIGEN_CWISE_BINARY_OP_H diff --git a/inst/include/Eigen/src/Core/CwiseNullaryOp.h b/inst/include/Eigen/src/Core/CwiseNullaryOp.h index a93bab2d..084f503f 100644 --- a/inst/include/Eigen/src/Core/CwiseNullaryOp.h +++ b/inst/include/Eigen/src/Core/CwiseNullaryOp.h @@ -10,15 +10,26 @@ #ifndef EIGEN_CWISE_NULLARY_OP_H #define EIGEN_CWISE_NULLARY_OP_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { +namespace internal { +template +struct traits > : traits { + enum { Flags = traits::Flags & RowMajorBit }; +}; + +} // namespace internal + /** \class CwiseNullaryOp * \ingroup Core_Module * * \brief Generic expression of a matrix where all coefficients are defined by a functor * - * \param NullaryOp template functor implementing the operator - * \param PlainObjectType the underlying plain matrix/array type + * \tparam NullaryOp template functor implementing the operator + * \tparam PlainObjectType the underlying plain matrix/array type * * This class represents an expression of a generic nullary operator. * It is the return type of the Ones(), Zero(), Constant(), Identity() and Random() methods, @@ -27,708 +38,773 @@ namespace Eigen { * However, if you want to write a function returning such an expression, you * will need to use this class. * - * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr() - */ - -namespace internal { -template -struct traits > : traits -{ - enum { - Flags = (traits::Flags - & ( HereditaryBits - | (functor_has_linear_access::ret ? LinearAccessBit : 0) - | (functor_traits::PacketAccess ? PacketAccessBit : 0))) - | (functor_traits::IsRepeatable ? 0 : EvalBeforeNestingBit), - CoeffReadCost = functor_traits::Cost - }; -}; -} - -template -class CwiseNullaryOp : internal::no_assignment_operator, - public internal::dense_xpr_base< CwiseNullaryOp >::type -{ - public: - - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp) - - CwiseNullaryOp(Index nbRows, Index nbCols, const NullaryOp& func = NullaryOp()) - : m_rows(nbRows), m_cols(nbCols), m_functor(func) - { - eigen_assert(nbRows >= 0 - && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows) - && nbCols >= 0 - && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols)); - } - - EIGEN_STRONG_INLINE Index rows() const { return m_rows.value(); } - EIGEN_STRONG_INLINE Index cols() const { return m_cols.value(); } - - EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const - { - return m_functor(rowId, colId); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const - { - return m_functor.packetOp(rowId, colId); - } - - EIGEN_STRONG_INLINE const Scalar coeff(Index index) const - { - return m_functor(index); - } + * The functor NullaryOp must expose one of the following method: + + +
\c operator()() if the procedural generation does not depend on the coefficient entries + (e.g., random numbers)
\c operator()(Index i)if the procedural generation makes + sense for vectors only and that it depends on the coefficient index \c i (e.g., linspace)
\c + operator()(Index i,Index j)if the procedural generation depends on the matrix coordinates \c i, \c j (e.g., + to generate a checkerboard with 0 and 1)
+ * It is also possible to expose the last two operators if the generation makes sense for matrices but can be optimized + for vectors. + * + * See DenseBase::NullaryExpr(Index,const CustomNullaryOp&) for an example binding + * C++11 random number generators. + * + * A nullary expression can also be used to implement custom sophisticated matrix manipulations + * that cannot be covered by the existing set of natively supported matrix manipulations. + * See this \ref TopicCustomizing_NullaryExpr "page" for some examples and additional explanations + * on the behavior of CwiseNullaryOp. + * + * \sa class CwiseUnaryOp, class CwiseBinaryOp, DenseBase::NullaryExpr + */ +template +class CwiseNullaryOp : public internal::dense_xpr_base >::type, + internal::no_assignment_operator { + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(CwiseNullaryOp) + + EIGEN_DEVICE_FUNC CwiseNullaryOp(Index rows, Index cols, const NullaryOp& func = NullaryOp()) + : m_rows(rows), m_cols(cols), m_functor(func) { + eigen_assert(rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && cols >= 0 && + (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols)); + } + EIGEN_DEVICE_FUNC CwiseNullaryOp(Index size, const NullaryOp& func = NullaryOp()) + : CwiseNullaryOp(RowsAtCompileTime == 1 ? 1 : size, RowsAtCompileTime == 1 ? size : 1, func) { + EIGEN_STATIC_ASSERT(CwiseNullaryOp::IsVectorAtCompileTime, YOU_TRIED_CALLING_A_VECTOR_METHOD_ON_A_MATRIX); + } - template - EIGEN_STRONG_INLINE PacketScalar packet(Index index) const - { - return m_functor.packetOp(index); - } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows.value(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols.value(); } - /** \returns the functor representing the nullary operation */ - const NullaryOp& functor() const { return m_functor; } + /** \returns the functor representing the nullary operation */ + EIGEN_DEVICE_FUNC const NullaryOp& functor() const { return m_functor; } - protected: - const internal::variable_if_dynamic m_rows; - const internal::variable_if_dynamic m_cols; - const NullaryOp m_functor; + protected: + const internal::variable_if_dynamic m_rows; + const internal::variable_if_dynamic m_cols; + const NullaryOp m_functor; }; - /** \returns an expression of a matrix defined by a custom functor \a func - * - * The parameters \a rows and \a cols are the number of rows and of columns of - * the returned matrix. Must be compatible with this MatrixBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used - * instead. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -template -EIGEN_STRONG_INLINE const CwiseNullaryOp -DenseBase::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func) -{ - return CwiseNullaryOp(rows, cols, func); + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this MatrixBase type. + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so NullaryExpr(const CustomNullaryOp&) should be used + * instead. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * \sa class CwiseNullaryOp + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE +#ifndef EIGEN_PARSED_BY_DOXYGEN + const CwiseNullaryOp::PlainObject> +#else + const CwiseNullaryOp +#endif + DenseBase::NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func) { + return CwiseNullaryOp(rows, cols, func); } /** \returns an expression of a matrix defined by a custom functor \a func - * - * The parameter \a size is the size of the returned vector. - * Must be compatible with this MatrixBase type. - * - * \only_for_vectors - * - * This variant is meant to be used for dynamic-size vector types. For fixed-size types, - * it is redundant to pass \a size as argument, so Zero() should be used - * instead. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -template -EIGEN_STRONG_INLINE const CwiseNullaryOp -DenseBase::NullaryExpr(Index size, const CustomNullaryOp& func) -{ + * + * The parameter \a size is the size of the returned vector. + * Must be compatible with this MatrixBase type. + * + * \only_for_vectors + * + * This variant is meant to be used for dynamic-size vector types. For fixed-size types, + * it is redundant to pass \a size as argument, so NullaryExpr(const CustomNullaryOp&) should be used + * instead. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * Here is an example with C++11 random generators: \include random_cpp11.cpp + * Output: \verbinclude random_cpp11.out + * + * \sa class CwiseNullaryOp + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE +#ifndef EIGEN_PARSED_BY_DOXYGEN + const CwiseNullaryOp::PlainObject> +#else + const CwiseNullaryOp +#endif + DenseBase::NullaryExpr(Index size, const CustomNullaryOp& func) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - if(RowsAtCompileTime == 1) return CwiseNullaryOp(1, size, func); - else return CwiseNullaryOp(size, 1, func); + if (RowsAtCompileTime == 1) + return CwiseNullaryOp(1, size, func); + else + return CwiseNullaryOp(size, 1, func); } /** \returns an expression of a matrix defined by a custom functor \a func - * - * This variant is only for fixed-size DenseBase types. For dynamic-size types, you - * need to use the variants taking size arguments. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -template -EIGEN_STRONG_INLINE const CwiseNullaryOp -DenseBase::NullaryExpr(const CustomNullaryOp& func) -{ - return CwiseNullaryOp(RowsAtCompileTime, ColsAtCompileTime, func); + * + * This variant is only for fixed-size DenseBase types. For dynamic-size types, you + * need to use the variants taking size arguments. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * \sa class CwiseNullaryOp + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE +#ifndef EIGEN_PARSED_BY_DOXYGEN + const CwiseNullaryOp::PlainObject> +#else + const CwiseNullaryOp +#endif + DenseBase::NullaryExpr(const CustomNullaryOp& func) { + return CwiseNullaryOp(RowsAtCompileTime, ColsAtCompileTime, func); } /** \returns an expression of a constant matrix of value \a value - * - * The parameters \a nbRows and \a nbCols are the number of rows and of columns of - * the returned matrix. Must be compatible with this DenseBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a nbRows and \a nbCols as arguments, so Zero() should be used - * instead. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Constant(Index nbRows, Index nbCols, const Scalar& value) -{ - return DenseBase::NullaryExpr(nbRows, nbCols, internal::scalar_constant_op(value)); + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this DenseBase type. + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so Constant(const Scalar&) should be used + * instead. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * \sa class CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType +DenseBase::Constant(Index rows, Index cols, const Scalar& value) { + return DenseBase::NullaryExpr(rows, cols, internal::scalar_constant_op(value)); } /** \returns an expression of a constant matrix of value \a value - * - * The parameter \a size is the size of the returned vector. - * Must be compatible with this DenseBase type. - * - * \only_for_vectors - * - * This variant is meant to be used for dynamic-size vector types. For fixed-size types, - * it is redundant to pass \a size as argument, so Zero() should be used - * instead. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Constant(Index size, const Scalar& value) -{ + * + * The parameter \a size is the size of the returned vector. + * Must be compatible with this DenseBase type. + * + * \only_for_vectors + * + * This variant is meant to be used for dynamic-size vector types. For fixed-size types, + * it is redundant to pass \a size as argument, so Constant(const Scalar&) should be used + * instead. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * \sa class CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType +DenseBase::Constant(Index size, const Scalar& value) { return DenseBase::NullaryExpr(size, internal::scalar_constant_op(value)); } /** \returns an expression of a constant matrix of value \a value - * - * This variant is only for fixed-size DenseBase types. For dynamic-size types, you - * need to use the variants taking size arguments. - * - * The template parameter \a CustomNullaryOp is the type of the functor. - * - * \sa class CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Constant(const Scalar& value) -{ + * + * This variant is only for fixed-size DenseBase types. For dynamic-size types, you + * need to use the variants taking size arguments. + * + * The template parameter \a CustomNullaryOp is the type of the functor. + * + * \sa class CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType +DenseBase::Constant(const Scalar& value) { EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) - return DenseBase::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_constant_op(value)); + return DenseBase::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, + internal::scalar_constant_op(value)); +} + +/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(Index,const Scalar&,const Scalar&) + * + * \only_for_vectors + * + * Example: \include DenseBase_LinSpaced_seq_deprecated.cpp + * Output: \verbinclude DenseBase_LinSpaced_seq_deprecated.out + * + * \sa LinSpaced(Index,const Scalar&, const Scalar&), setLinSpaced(Index,const Scalar&,const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType +DenseBase::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + return DenseBase::NullaryExpr(size, internal::linspaced_op(low, high, size)); +} + +/** \deprecated because of accuracy loss. In Eigen 3.3, it is an alias for LinSpaced(const Scalar&,const Scalar&) + * + * \sa LinSpaced(const Scalar&, const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType +DenseBase::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) + return DenseBase::NullaryExpr(Derived::SizeAtCompileTime, + internal::linspaced_op(low, high, Derived::SizeAtCompileTime)); } /** - * \brief Sets a linearly space vector. - * - * The function generates 'size' equally spaced values in the closed interval [low,high]. - * This particular version of LinSpaced() uses sequential access, i.e. vector access is - * assumed to be a(0), a(1), ..., a(size). This assumption allows for better vectorization - * and yields faster code than the random access version. - * - * When size is set to 1, a vector of length 1 containing 'high' is returned. - * - * \only_for_vectors - * - * Example: \include DenseBase_LinSpaced_seq.cpp - * Output: \verbinclude DenseBase_LinSpaced_seq.out - * - * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Index,Scalar,Scalar), CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::SequentialLinSpacedReturnType -DenseBase::LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high) -{ + * \brief Sets a linearly spaced vector. + * + * The function generates 'size' equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. + * + * \only_for_vectors + * + * Example: \include DenseBase_LinSpaced.cpp + * Output: \verbinclude DenseBase_LinSpaced.out + * + * For integer scalar types, an even spacing is possible if and only if the length of the range, + * i.e., \c high-low is a scalar multiple of \c size-1, or if \c size is a scalar multiple of the + * number of values \c high-low+1 (meaning each value can be repeated the same number of time). + * If one of these two considions is not satisfied, then \c high is lowered to the largest value + * satisfying one of this constraint. + * Here are some examples: + * + * Example: \include DenseBase_LinSpacedInt.cpp + * Output: \verbinclude DenseBase_LinSpacedInt.out + * + * \sa setLinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType +DenseBase::LinSpaced(Index size, const Scalar& low, const Scalar& high) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - return DenseBase::NullaryExpr(size, internal::linspaced_op(low,high,size)); + return DenseBase::NullaryExpr(size, internal::linspaced_op(low, high, size)); } /** - * \copydoc DenseBase::LinSpaced(Sequential_t, Index, const Scalar&, const Scalar&) - * Special version for fixed size types which does not require the size parameter. - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::SequentialLinSpacedReturnType -DenseBase::LinSpaced(Sequential_t, const Scalar& low, const Scalar& high) -{ + * \copydoc DenseBase::LinSpaced(Index, const DenseBase::Scalar&, const DenseBase::Scalar&) + * Special version for fixed size types which does not require the size parameter. + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType +DenseBase::LinSpaced(const Scalar& low, const Scalar& high) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) - return DenseBase::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op(low,high,Derived::SizeAtCompileTime)); + return DenseBase::NullaryExpr(Derived::SizeAtCompileTime, + internal::linspaced_op(low, high, Derived::SizeAtCompileTime)); } -/** - * \brief Sets a linearly space vector. - * - * The function generates 'size' equally spaced values in the closed interval [low,high]. - * When size is set to 1, a vector of length 1 containing 'high' is returned. - * - * \only_for_vectors - * - * Example: \include DenseBase_LinSpaced.cpp - * Output: \verbinclude DenseBase_LinSpaced.out - * - * \sa setLinSpaced(Index,const Scalar&,const Scalar&), LinSpaced(Sequential_t,Index,const Scalar&,const Scalar&,Index), CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType -DenseBase::LinSpaced(Index size, const Scalar& low, const Scalar& high) -{ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessEqualSpacedReturnType +DenseBase::EqualSpaced(Index size, const Scalar& low, const Scalar& step) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - return DenseBase::NullaryExpr(size, internal::linspaced_op(low,high,size)); + return DenseBase::NullaryExpr(size, internal::equalspaced_op(low, step)); } -/** - * \copydoc DenseBase::LinSpaced(Index, const Scalar&, const Scalar&) - * Special version for fixed size types which does not require the size parameter. - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessLinSpacedReturnType -DenseBase::LinSpaced(const Scalar& low, const Scalar& high) -{ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::RandomAccessEqualSpacedReturnType +DenseBase::EqualSpaced(const Scalar& low, const Scalar& step) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) - return DenseBase::NullaryExpr(Derived::SizeAtCompileTime, internal::linspaced_op(low,high,Derived::SizeAtCompileTime)); + return DenseBase::NullaryExpr(Derived::SizeAtCompileTime, internal::equalspaced_op(low, step)); } /** \returns true if all coefficients in this matrix are approximately equal to \a val, to within precision \a prec */ -template -bool DenseBase::isApproxToConstant -(const Scalar& val, const RealScalar& prec) const -{ - for(Index j = 0; j < cols(); ++j) - for(Index i = 0; i < rows(); ++i) - if(!internal::isApprox(this->coeff(i, j), val, prec)) - return false; +template +EIGEN_DEVICE_FUNC bool DenseBase::isApproxToConstant(const Scalar& val, const RealScalar& prec) const { + typename internal::nested_eval::type self(derived()); + for (Index j = 0; j < cols(); ++j) + for (Index i = 0; i < rows(); ++i) + if (!internal::isApprox(self.coeff(i, j), val, prec)) return false; return true; } /** This is just an alias for isApproxToConstant(). - * - * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */ -template -bool DenseBase::isConstant -(const Scalar& val, const RealScalar& prec) const -{ + * + * \returns true if all coefficients in this matrix are approximately equal to \a value, to within precision \a prec */ +template +EIGEN_DEVICE_FUNC bool DenseBase::isConstant(const Scalar& val, const RealScalar& prec) const { return isApproxToConstant(val, prec); } /** Alias for setConstant(): sets all coefficients in this expression to \a val. - * - * \sa setConstant(), Constant(), class CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE void DenseBase::fill(const Scalar& val) -{ + * + * \sa setConstant(), Constant(), class CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void DenseBase::fill(const Scalar& val) { setConstant(val); } -/** Sets all coefficients in this expression to \a value. - * - * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), Constant(), class CwiseNullaryOp, setZero(), setOnes() - */ -template -EIGEN_STRONG_INLINE Derived& DenseBase::setConstant(const Scalar& val) -{ - return derived() = Constant(rows(), cols(), val); -} - -/** Resizes to the given \a size, and sets all coefficients in this expression to the given \a value. - * - * \only_for_vectors - * - * Example: \include Matrix_setConstant_int.cpp - * Output: \verbinclude Matrix_setConstant_int.out - * - * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&) - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setConstant(Index size, const Scalar& val) -{ +/** Sets all coefficients in this expression to value \a val. + * + * \sa fill(), setConstant(Index,const Scalar&), setConstant(Index,Index,const Scalar&), setZero(), setOnes(), + * Constant(), class CwiseNullaryOp, setZero(), setOnes() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setConstant(const Scalar& val) { + internal::eigen_fill_impl::run(derived(), val); + return derived(); +} + +/** Resizes to the given \a size, and sets all coefficients in this expression to the given value \a val. + * + * \only_for_vectors + * + * Example: \include Matrix_setConstant_int.cpp + * Output: \verbinclude Matrix_setConstant_int.out + * + * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,Index,const Scalar&), class CwiseNullaryOp, + * MatrixBase::Constant(const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setConstant(Index size, const Scalar& val) { resize(size); return setConstant(val); } -/** Resizes to the given size, and sets all coefficients in this expression to the given \a value. - * - * \param nbRows the new number of rows - * \param nbCols the new number of columns - * \param val the value to which all coefficients are set - * - * Example: \include Matrix_setConstant_int_int.cpp - * Output: \verbinclude Matrix_setConstant_int_int.out - * - * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, MatrixBase::Constant(const Scalar&) - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setConstant(Index nbRows, Index nbCols, const Scalar& val) -{ - resize(nbRows, nbCols); +/** Resizes to the given size, and sets all coefficients in this expression to the given value \a val. + * + * \param rows the new number of rows + * \param cols the new number of columns + * \param val the value to which all coefficients are set + * + * Example: \include Matrix_setConstant_int_int.cpp + * Output: \verbinclude Matrix_setConstant_int_int.out + * + * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, + * MatrixBase::Constant(const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setConstant(Index rows, Index cols, + const Scalar& val) { + resize(rows, cols); return setConstant(val); } +/** Resizes to the given size, changing only the number of columns, and sets all + * coefficients in this expression to the given value \a val. For the parameter + * of type NoChange_t, just pass the special value \c NoChange. + * + * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, + * MatrixBase::Constant(const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setConstant(NoChange_t, Index cols, + const Scalar& val) { + return setConstant(rows(), cols, val); +} + +/** Resizes to the given size, changing only the number of rows, and sets all + * coefficients in this expression to the given value \a val. For the parameter + * of type NoChange_t, just pass the special value \c NoChange. + * + * \sa MatrixBase::setConstant(const Scalar&), setConstant(Index,const Scalar&), class CwiseNullaryOp, + * MatrixBase::Constant(const Scalar&) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setConstant(Index rows, NoChange_t, + const Scalar& val) { + return setConstant(rows, cols(), val); +} + /** - * \brief Sets a linearly space vector. - * - * The function generates 'size' equally spaced values in the closed interval [low,high]. - * When size is set to 1, a vector of length 1 containing 'high' is returned. - * - * \only_for_vectors - * - * Example: \include DenseBase_setLinSpaced.cpp - * Output: \verbinclude DenseBase_setLinSpaced.out - * - * \sa CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(Index newSize, const Scalar& low, const Scalar& high) -{ + * \brief Sets a linearly spaced vector. + * + * The function generates 'size' equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. + * + * \only_for_vectors + * + * Example: \include DenseBase_setLinSpaced.cpp + * Output: \verbinclude DenseBase_setLinSpaced.out + * + * For integer scalar types, do not miss the explanations on the definition + * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink. + * + * \sa LinSpaced(Index,const Scalar&,const Scalar&), CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(Index newSize, const Scalar& low, + const Scalar& high) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op(low,high,newSize)); + return derived() = Derived::NullaryExpr(newSize, internal::linspaced_op(low, high, newSize)); } /** - * \brief Sets a linearly space vector. - * - * The function fill *this with equally spaced values in the closed interval [low,high]. - * When size is set to 1, a vector of length 1 containing 'high' is returned. - * - * \only_for_vectors - * - * \sa setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp - */ -template -EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(const Scalar& low, const Scalar& high) -{ + * \brief Sets a linearly spaced vector. + * + * The function fills \c *this with equally spaced values in the closed interval [low,high]. + * When size is set to 1, a vector of length 1 containing 'high' is returned. + * + * \only_for_vectors + * + * For integer scalar types, do not miss the explanations on the definition + * of \link LinSpaced(Index,const Scalar&,const Scalar&) even spacing \endlink. + * + * \sa LinSpaced(Index,const Scalar&,const Scalar&), setLinSpaced(Index, const Scalar&, const Scalar&), CwiseNullaryOp + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setLinSpaced(const Scalar& low, const Scalar& high) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) return setLinSpaced(size(), low, high); } +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setEqualSpaced(Index newSize, const Scalar& low, + const Scalar& step) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + return derived() = Derived::NullaryExpr(newSize, internal::equalspaced_op(low, step)); +} +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setEqualSpaced(const Scalar& low, + const Scalar& step) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + return setEqualSpaced(size(), low, step); +} + // zero: /** \returns an expression of a zero matrix. - * - * The parameters \a rows and \a cols are the number of rows and of columns of - * the returned matrix. Must be compatible with this MatrixBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used - * instead. - * - * Example: \include MatrixBase_zero_int_int.cpp - * Output: \verbinclude MatrixBase_zero_int_int.out - * - * \sa Zero(), Zero(Index) - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Zero(Index nbRows, Index nbCols) -{ - return Constant(nbRows, nbCols, Scalar(0)); + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this MatrixBase type. + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so Zero() should be used + * instead. + * + * Example: \include MatrixBase_zero_int_int.cpp + * Output: \verbinclude MatrixBase_zero_int_int.out + * + * \sa Zero(), Zero(Index) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ZeroReturnType DenseBase::Zero( + Index rows, Index cols) { + return ZeroReturnType(rows, cols); } /** \returns an expression of a zero vector. - * - * The parameter \a size is the size of the returned vector. - * Must be compatible with this MatrixBase type. - * - * \only_for_vectors - * - * This variant is meant to be used for dynamic-size vector types. For fixed-size types, - * it is redundant to pass \a size as argument, so Zero() should be used - * instead. - * - * Example: \include MatrixBase_zero_int.cpp - * Output: \verbinclude MatrixBase_zero_int.out - * - * \sa Zero(), Zero(Index,Index) - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Zero(Index size) -{ - return Constant(size, Scalar(0)); + * + * The parameter \a size is the size of the returned vector. + * Must be compatible with this MatrixBase type. + * + * \only_for_vectors + * + * This variant is meant to be used for dynamic-size vector types. For fixed-size types, + * it is redundant to pass \a size as argument, so Zero() should be used + * instead. + * + * Example: \include MatrixBase_zero_int.cpp + * Output: \verbinclude MatrixBase_zero_int.out + * + * \sa Zero(), Zero(Index,Index) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ZeroReturnType DenseBase::Zero( + Index size) { + return ZeroReturnType(size); } /** \returns an expression of a fixed-size zero matrix or vector. - * - * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you - * need to use the variants taking size arguments. - * - * Example: \include MatrixBase_zero.cpp - * Output: \verbinclude MatrixBase_zero.out - * - * \sa Zero(Index), Zero(Index,Index) - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Zero() -{ - return Constant(Scalar(0)); + * + * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you + * need to use the variants taking size arguments. + * + * Example: \include MatrixBase_zero.cpp + * Output: \verbinclude MatrixBase_zero.out + * + * \sa Zero(Index), Zero(Index,Index) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ZeroReturnType DenseBase::Zero() { + return ZeroReturnType(RowsAtCompileTime, ColsAtCompileTime); } /** \returns true if *this is approximately equal to the zero matrix, - * within the precision given by \a prec. - * - * Example: \include MatrixBase_isZero.cpp - * Output: \verbinclude MatrixBase_isZero.out - * - * \sa class CwiseNullaryOp, Zero() - */ -template -bool DenseBase::isZero(const RealScalar& prec) const -{ - for(Index j = 0; j < cols(); ++j) - for(Index i = 0; i < rows(); ++i) - if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast(1), prec)) - return false; + * within the precision given by \a prec. + * + * Example: \include MatrixBase_isZero.cpp + * Output: \verbinclude MatrixBase_isZero.out + * + * \sa class CwiseNullaryOp, Zero() + */ +template +EIGEN_DEVICE_FUNC bool DenseBase::isZero(const RealScalar& prec) const { + typename internal::nested_eval::type self(derived()); + for (Index j = 0; j < cols(); ++j) + for (Index i = 0; i < rows(); ++i) + if (!internal::isMuchSmallerThan(self.coeff(i, j), static_cast(1), prec)) return false; return true; } /** Sets all coefficients in this expression to zero. - * - * Example: \include MatrixBase_setZero.cpp - * Output: \verbinclude MatrixBase_setZero.out - * - * \sa class CwiseNullaryOp, Zero() - */ -template -EIGEN_STRONG_INLINE Derived& DenseBase::setZero() -{ - return setConstant(Scalar(0)); + * + * Example: \include MatrixBase_setZero.cpp + * Output: \verbinclude MatrixBase_setZero.out + * + * \sa class CwiseNullaryOp, Zero() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setZero() { + internal::eigen_zero_impl::run(derived()); + return derived(); } /** Resizes to the given \a size, and sets all coefficients in this expression to zero. - * - * \only_for_vectors - * - * Example: \include Matrix_setZero_int.cpp - * Output: \verbinclude Matrix_setZero_int.out - * - * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setZero(Index newSize) -{ + * + * \only_for_vectors + * + * Example: \include Matrix_setZero_int.cpp + * Output: \verbinclude Matrix_setZero_int.out + * + * \sa DenseBase::setZero(), setZero(Index,Index), class CwiseNullaryOp, DenseBase::Zero() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setZero(Index newSize) { resize(newSize); - return setConstant(Scalar(0)); + return setZero(); } /** Resizes to the given size, and sets all coefficients in this expression to zero. - * - * \param nbRows the new number of rows - * \param nbCols the new number of columns - * - * Example: \include Matrix_setZero_int_int.cpp - * Output: \verbinclude Matrix_setZero_int_int.out - * - * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setZero(Index nbRows, Index nbCols) -{ - resize(nbRows, nbCols); - return setConstant(Scalar(0)); + * + * \param rows the new number of rows + * \param cols the new number of columns + * + * Example: \include Matrix_setZero_int_int.cpp + * Output: \verbinclude Matrix_setZero_int_int.out + * + * \sa DenseBase::setZero(), setZero(Index), class CwiseNullaryOp, DenseBase::Zero() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setZero(Index rows, Index cols) { + resize(rows, cols); + return setZero(); +} + +/** Resizes to the given size, changing only the number of columns, and sets all + * coefficients in this expression to zero. For the parameter of type NoChange_t, + * just pass the special value \c NoChange. + * + * \sa DenseBase::setZero(), setZero(Index), setZero(Index, Index), setZero(Index, NoChange_t), class CwiseNullaryOp, + * DenseBase::Zero() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setZero(NoChange_t, Index cols) { + return setZero(rows(), cols); +} + +/** Resizes to the given size, changing only the number of rows, and sets all + * coefficients in this expression to zero. For the parameter of type NoChange_t, + * just pass the special value \c NoChange. + * + * \sa DenseBase::setZero(), setZero(Index), setZero(Index, Index), setZero(NoChange_t, Index), class CwiseNullaryOp, + * DenseBase::Zero() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setZero(Index rows, NoChange_t) { + return setZero(rows, cols()); } // ones: /** \returns an expression of a matrix where all coefficients equal one. - * - * The parameters \a nbRows and \a nbCols are the number of rows and of columns of - * the returned matrix. Must be compatible with this MatrixBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used - * instead. - * - * Example: \include MatrixBase_ones_int_int.cpp - * Output: \verbinclude MatrixBase_ones_int_int.out - * - * \sa Ones(), Ones(Index), isOnes(), class Ones - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Ones(Index nbRows, Index nbCols) -{ - return Constant(nbRows, nbCols, Scalar(1)); + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this MatrixBase type. + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so Ones() should be used + * instead. + * + * Example: \include MatrixBase_ones_int_int.cpp + * Output: \verbinclude MatrixBase_ones_int_int.out + * + * \sa Ones(), Ones(Index), isOnes(), class Ones + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType DenseBase::Ones( + Index rows, Index cols) { + return Constant(rows, cols, Scalar(1)); } /** \returns an expression of a vector where all coefficients equal one. - * - * The parameter \a newSize is the size of the returned vector. - * Must be compatible with this MatrixBase type. - * - * \only_for_vectors - * - * This variant is meant to be used for dynamic-size vector types. For fixed-size types, - * it is redundant to pass \a size as argument, so Ones() should be used - * instead. - * - * Example: \include MatrixBase_ones_int.cpp - * Output: \verbinclude MatrixBase_ones_int.out - * - * \sa Ones(), Ones(Index,Index), isOnes(), class Ones - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Ones(Index newSize) -{ + * + * The parameter \a newSize is the size of the returned vector. + * Must be compatible with this MatrixBase type. + * + * \only_for_vectors + * + * This variant is meant to be used for dynamic-size vector types. For fixed-size types, + * it is redundant to pass \a size as argument, so Ones() should be used + * instead. + * + * Example: \include MatrixBase_ones_int.cpp + * Output: \verbinclude MatrixBase_ones_int.out + * + * \sa Ones(), Ones(Index,Index), isOnes(), class Ones + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType DenseBase::Ones( + Index newSize) { return Constant(newSize, Scalar(1)); } /** \returns an expression of a fixed-size matrix or vector where all coefficients equal one. - * - * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you - * need to use the variants taking size arguments. - * - * Example: \include MatrixBase_ones.cpp - * Output: \verbinclude MatrixBase_ones.out - * - * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones - */ -template -EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType -DenseBase::Ones() -{ + * + * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you + * need to use the variants taking size arguments. + * + * Example: \include MatrixBase_ones.cpp + * Output: \verbinclude MatrixBase_ones.out + * + * \sa Ones(Index), Ones(Index,Index), isOnes(), class Ones + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename DenseBase::ConstantReturnType DenseBase::Ones() { return Constant(Scalar(1)); } /** \returns true if *this is approximately equal to the matrix where all coefficients - * are equal to 1, within the precision given by \a prec. - * - * Example: \include MatrixBase_isOnes.cpp - * Output: \verbinclude MatrixBase_isOnes.out - * - * \sa class CwiseNullaryOp, Ones() - */ -template -bool DenseBase::isOnes -(const RealScalar& prec) const -{ + * are equal to 1, within the precision given by \a prec. + * + * Example: \include MatrixBase_isOnes.cpp + * Output: \verbinclude MatrixBase_isOnes.out + * + * \sa class CwiseNullaryOp, Ones() + */ +template +EIGEN_DEVICE_FUNC bool DenseBase::isOnes(const RealScalar& prec) const { return isApproxToConstant(Scalar(1), prec); } /** Sets all coefficients in this expression to one. - * - * Example: \include MatrixBase_setOnes.cpp - * Output: \verbinclude MatrixBase_setOnes.out - * - * \sa class CwiseNullaryOp, Ones() - */ -template -EIGEN_STRONG_INLINE Derived& DenseBase::setOnes() -{ + * + * Example: \include MatrixBase_setOnes.cpp + * Output: \verbinclude MatrixBase_setOnes.out + * + * \sa class CwiseNullaryOp, Ones() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& DenseBase::setOnes() { return setConstant(Scalar(1)); } /** Resizes to the given \a newSize, and sets all coefficients in this expression to one. - * - * \only_for_vectors - * - * Example: \include Matrix_setOnes_int.cpp - * Output: \verbinclude Matrix_setOnes_int.out - * - * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setOnes(Index newSize) -{ + * + * \only_for_vectors + * + * Example: \include Matrix_setOnes_int.cpp + * Output: \verbinclude Matrix_setOnes_int.out + * + * \sa MatrixBase::setOnes(), setOnes(Index,Index), class CwiseNullaryOp, MatrixBase::Ones() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setOnes(Index newSize) { resize(newSize); return setConstant(Scalar(1)); } /** Resizes to the given size, and sets all coefficients in this expression to one. - * - * \param nbRows the new number of rows - * \param nbCols the new number of columns - * - * Example: \include Matrix_setOnes_int_int.cpp - * Output: \verbinclude Matrix_setOnes_int_int.out - * - * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setOnes(Index nbRows, Index nbCols) -{ - resize(nbRows, nbCols); + * + * \param rows the new number of rows + * \param cols the new number of columns + * + * Example: \include Matrix_setOnes_int_int.cpp + * Output: \verbinclude Matrix_setOnes_int_int.out + * + * \sa MatrixBase::setOnes(), setOnes(Index), class CwiseNullaryOp, MatrixBase::Ones() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setOnes(Index rows, Index cols) { + resize(rows, cols); return setConstant(Scalar(1)); } +/** Resizes to the given size, changing only the number of rows, and sets all + * coefficients in this expression to one. For the parameter of type NoChange_t, + * just pass the special value \c NoChange. + * + * \sa MatrixBase::setOnes(), setOnes(Index), setOnes(Index, Index), setOnes(NoChange_t, Index), class CwiseNullaryOp, + * MatrixBase::Ones() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setOnes(Index rows, NoChange_t) { + return setOnes(rows, cols()); +} + +/** Resizes to the given size, changing only the number of columns, and sets all + * coefficients in this expression to one. For the parameter of type NoChange_t, + * just pass the special value \c NoChange. + * + * \sa MatrixBase::setOnes(), setOnes(Index), setOnes(Index, Index), setOnes(Index, NoChange_t) class CwiseNullaryOp, + * MatrixBase::Ones() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& PlainObjectBase::setOnes(NoChange_t, Index cols) { + return setOnes(rows(), cols); +} + // Identity: /** \returns an expression of the identity matrix (not necessarily square). - * - * The parameters \a nbRows and \a nbCols are the number of rows and of columns of - * the returned matrix. Must be compatible with this MatrixBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used - * instead. - * - * Example: \include MatrixBase_identity_int_int.cpp - * Output: \verbinclude MatrixBase_identity_int_int.out - * - * \sa Identity(), setIdentity(), isIdentity() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::IdentityReturnType -MatrixBase::Identity(Index nbRows, Index nbCols) -{ - return DenseBase::NullaryExpr(nbRows, nbCols, internal::scalar_identity_op()); + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this MatrixBase type. + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so Identity() should be used + * instead. + * + * Example: \include MatrixBase_identity_int_int.cpp + * Output: \verbinclude MatrixBase_identity_int_int.out + * + * \sa Identity(), setIdentity(), isIdentity() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::IdentityReturnType +MatrixBase::Identity(Index rows, Index cols) { + return DenseBase::NullaryExpr(rows, cols, internal::scalar_identity_op()); } /** \returns an expression of the identity matrix (not necessarily square). - * - * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you - * need to use the variant taking size arguments. - * - * Example: \include MatrixBase_identity.cpp - * Output: \verbinclude MatrixBase_identity.out - * - * \sa Identity(Index,Index), setIdentity(), isIdentity() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::IdentityReturnType -MatrixBase::Identity() -{ + * + * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you + * need to use the variant taking size arguments. + * + * Example: \include MatrixBase_identity.cpp + * Output: \verbinclude MatrixBase_identity.out + * + * \sa Identity(Index,Index), setIdentity(), isIdentity() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::IdentityReturnType +MatrixBase::Identity() { EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) return MatrixBase::NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_identity_op()); } /** \returns true if *this is approximately equal to the identity matrix - * (not necessarily square), - * within the precision given by \a prec. - * - * Example: \include MatrixBase_isIdentity.cpp - * Output: \verbinclude MatrixBase_isIdentity.out - * - * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity() - */ -template -bool MatrixBase::isIdentity -(const RealScalar& prec) const -{ - for(Index j = 0; j < cols(); ++j) - { - for(Index i = 0; i < rows(); ++i) - { - if(i == j) - { - if(!internal::isApprox(this->coeff(i, j), static_cast(1), prec)) - return false; - } - else - { - if(!internal::isMuchSmallerThan(this->coeff(i, j), static_cast(1), prec)) - return false; + * (not necessarily square), + * within the precision given by \a prec. + * + * Example: \include MatrixBase_isIdentity.cpp + * Output: \verbinclude MatrixBase_isIdentity.out + * + * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), setIdentity() + */ +template +bool MatrixBase::isIdentity(const RealScalar& prec) const { + typename internal::nested_eval::type self(derived()); + for (Index j = 0; j < cols(); ++j) { + for (Index i = 0; i < rows(); ++i) { + if (i == j) { + if (!internal::isApprox(self.coeff(i, j), static_cast(1), prec)) return false; + } else { + if (!internal::isMuchSmallerThan(self.coeff(i, j), static_cast(1), prec)) return false; } } } @@ -737,128 +813,163 @@ bool MatrixBase::isIdentity namespace internal { -template=16)> -struct setIdentity_impl -{ - static EIGEN_STRONG_INLINE Derived& run(Derived& m) - { +template = 16)> +struct setIdentity_impl { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Derived& run(Derived& m) { return m = Derived::Identity(m.rows(), m.cols()); } }; -template -struct setIdentity_impl -{ - typedef typename Derived::Index Index; - static EIGEN_STRONG_INLINE Derived& run(Derived& m) - { +template +struct setIdentity_impl { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Derived& run(Derived& m) { m.setZero(); - const Index size = (std::min)(m.rows(), m.cols()); - for(Index i = 0; i < size; ++i) m.coeffRef(i,i) = typename Derived::Scalar(1); + const Index size = numext::mini(m.rows(), m.cols()); + for (Index i = 0; i < size; ++i) m.coeffRef(i, i) = typename Derived::Scalar(1); return m; } }; -} // end namespace internal +} // end namespace internal /** Writes the identity expression (not necessarily square) into *this. - * - * Example: \include MatrixBase_setIdentity.cpp - * Output: \verbinclude MatrixBase_setIdentity.out - * - * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity() - */ -template -EIGEN_STRONG_INLINE Derived& MatrixBase::setIdentity() -{ + * + * Example: \include MatrixBase_setIdentity.cpp + * Output: \verbinclude MatrixBase_setIdentity.out + * + * \sa class CwiseNullaryOp, Identity(), Identity(Index,Index), isIdentity() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::setIdentity() { return internal::setIdentity_impl::run(derived()); } /** \brief Resizes to the given size, and writes the identity expression (not necessarily square) into *this. - * - * \param nbRows the new number of rows - * \param nbCols the new number of columns - * - * Example: \include Matrix_setIdentity_int_int.cpp - * Output: \verbinclude Matrix_setIdentity_int_int.out - * - * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity() - */ -template -EIGEN_STRONG_INLINE Derived& MatrixBase::setIdentity(Index nbRows, Index nbCols) -{ - derived().resize(nbRows, nbCols); + * + * \param rows the new number of rows + * \param cols the new number of columns + * + * Example: \include Matrix_setIdentity_int_int.cpp + * Output: \verbinclude Matrix_setIdentity_int_int.out + * + * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Identity() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::setIdentity(Index rows, Index cols) { + derived().resize(rows, cols); return setIdentity(); } /** \returns an expression of the i-th unit (basis) vector. - * - * \only_for_vectors - * - * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::Unit(Index newSize, Index i) -{ + * + * \only_for_vectors + * + * \sa MatrixBase::Unit(Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::Unit( + Index newSize, Index i) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - return BasisReturnType(SquareMatrixType::Identity(newSize,newSize), i); + return BasisReturnType(SquareMatrixType::Identity(newSize, newSize), i); } /** \returns an expression of the i-th unit (basis) vector. - * - * \only_for_vectors - * - * This variant is for fixed-size vector only. - * - * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::Unit(Index i) -{ + * + * \only_for_vectors + * + * This variant is for fixed-size vector only. + * + * \sa MatrixBase::Unit(Index,Index), MatrixBase::UnitX(), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::Unit( + Index i) { EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - return BasisReturnType(SquareMatrixType::Identity(),i); + return BasisReturnType(SquareMatrixType::Identity(), i); } /** \returns an expression of the X axis unit vector (1{,0}^*) - * - * \only_for_vectors - * - * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitX() -{ return Derived::Unit(0); } + * + * \only_for_vectors + * + * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), + * MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitX() { + return Derived::Unit(0); +} /** \returns an expression of the Y axis unit vector (0,1{,0}^*) - * - * \only_for_vectors - * - * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitY() -{ return Derived::Unit(1); } + * + * \only_for_vectors + * + * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), + * MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitY() { + return Derived::Unit(1); +} /** \returns an expression of the Z axis unit vector (0,0,1{,0}^*) - * - * \only_for_vectors - * - * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitZ() -{ return Derived::Unit(2); } + * + * \only_for_vectors + * + * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), + * MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitZ() { + return Derived::Unit(2); +} /** \returns an expression of the W axis unit vector (0,0,0,1) - * - * \only_for_vectors - * - * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), MatrixBase::UnitW() - */ -template -EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitW() -{ return Derived::Unit(3); } - -} // end namespace Eigen - -#endif // EIGEN_CWISE_NULLARY_OP_H + * + * \only_for_vectors + * + * \sa MatrixBase::Unit(Index,Index), MatrixBase::Unit(Index), MatrixBase::UnitY(), MatrixBase::UnitZ(), + * MatrixBase::UnitW() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::BasisReturnType MatrixBase::UnitW() { + return Derived::Unit(3); +} + +/** \brief Set the coefficients of \c *this to the i-th unit (basis) vector + * + * \param i index of the unique coefficient to be set to 1 + * + * \only_for_vectors + * + * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Unit(Index,Index) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::setUnit(Index i) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived); + eigen_assert(i < size()); + derived().setZero(); + derived().coeffRef(i) = Scalar(1); + return derived(); +} + +/** \brief Resizes to the given \a newSize, and writes the i-th unit (basis) vector into *this. + * + * \param newSize the new size of the vector + * \param i index of the unique coefficient to be set to 1 + * + * \only_for_vectors + * + * \sa MatrixBase::setIdentity(), class CwiseNullaryOp, MatrixBase::Unit(Index,Index) + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& MatrixBase::setUnit(Index newSize, Index i) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived); + eigen_assert(i < newSize); + derived().resize(newSize); + return setUnit(i); +} + +} // end namespace Eigen + +#endif // EIGEN_CWISE_NULLARY_OP_H diff --git a/inst/include/Eigen/src/Core/CwiseTernaryOp.h b/inst/include/Eigen/src/Core/CwiseTernaryOp.h new file mode 100644 index 00000000..9bb0d407 --- /dev/null +++ b/inst/include/Eigen/src/Core/CwiseTernaryOp.h @@ -0,0 +1,171 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2014 Gael Guennebaud +// Copyright (C) 2006-2008 Benoit Jacob +// Copyright (C) 2016 Eugene Brevdo +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_CWISE_TERNARY_OP_H +#define EIGEN_CWISE_TERNARY_OP_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { +template +struct traits> { + // we must not inherit from traits since it has + // the potential to cause problems with MSVC + typedef remove_all_t Ancestor; + typedef typename traits::XprKind XprKind; + enum { + RowsAtCompileTime = traits::RowsAtCompileTime, + ColsAtCompileTime = traits::ColsAtCompileTime, + MaxRowsAtCompileTime = traits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = traits::MaxColsAtCompileTime + }; + + // even though we require Arg1, Arg2, and Arg3 to have the same scalar type + // (see CwiseTernaryOp constructor), + // we still want to handle the case when the result type is different. + typedef typename result_of::type Scalar; + + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::StorageIndex StorageIndex; + + typedef typename Arg1::Nested Arg1Nested; + typedef typename Arg2::Nested Arg2Nested; + typedef typename Arg3::Nested Arg3Nested; + typedef std::remove_reference_t Arg1Nested_; + typedef std::remove_reference_t Arg2Nested_; + typedef std::remove_reference_t Arg3Nested_; + enum { Flags = Arg1Nested_::Flags & RowMajorBit }; +}; +} // end namespace internal + +template +class CwiseTernaryOpImpl; + +/** \class CwiseTernaryOp + * \ingroup Core_Module + * + * \brief Generic expression where a coefficient-wise ternary operator is + * applied to two expressions + * + * \tparam TernaryOp template functor implementing the operator + * \tparam Arg1Type the type of the first argument + * \tparam Arg2Type the type of the second argument + * \tparam Arg3Type the type of the third argument + * + * This class represents an expression where a coefficient-wise ternary + * operator is applied to three expressions. + * It is the return type of ternary operators, by which we mean only those + * ternary operators where + * all three arguments are Eigen expressions. + * For example, the return type of betainc(matrix1, matrix2, matrix3) is a + * CwiseTernaryOp. + * + * Most of the time, this is the only way that it is used, so you typically + * don't have to name + * CwiseTernaryOp types explicitly. + * + * \sa MatrixBase::ternaryExpr(const MatrixBase &, const + * MatrixBase &, const CustomTernaryOp &) const, class CwiseBinaryOp, + * class CwiseUnaryOp, class CwiseNullaryOp + */ +template +class CwiseTernaryOp : public CwiseTernaryOpImpl::StorageKind>, + internal::no_assignment_operator { + public: + typedef internal::remove_all_t Arg1; + typedef internal::remove_all_t Arg2; + typedef internal::remove_all_t Arg3; + + // require the sizes to match + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg2) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(Arg1, Arg3) + + // The index types should match + EIGEN_STATIC_ASSERT((internal::is_same::StorageKind, + typename internal::traits::StorageKind>::value), + STORAGE_KIND_MUST_MATCH) + EIGEN_STATIC_ASSERT((internal::is_same::StorageKind, + typename internal::traits::StorageKind>::value), + STORAGE_KIND_MUST_MATCH) + + typedef typename CwiseTernaryOpImpl::StorageKind>::Base Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseTernaryOp) + + typedef typename internal::ref_selector::type Arg1Nested; + typedef typename internal::ref_selector::type Arg2Nested; + typedef typename internal::ref_selector::type Arg3Nested; + typedef std::remove_reference_t Arg1Nested_; + typedef std::remove_reference_t Arg2Nested_; + typedef std::remove_reference_t Arg3Nested_; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CwiseTernaryOp(const Arg1& a1, const Arg2& a2, const Arg3& a3, + const TernaryOp& func = TernaryOp()) + : m_arg1(a1), m_arg2(a2), m_arg3(a3), m_functor(func) { + eigen_assert(a1.rows() == a2.rows() && a1.cols() == a2.cols() && a1.rows() == a3.rows() && a1.cols() == a3.cols()); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rows() const { + // return the fixed size type if available to enable compile time + // optimizations + if (internal::traits>::RowsAtCompileTime == Dynamic && + internal::traits>::RowsAtCompileTime == Dynamic) + return m_arg3.rows(); + else if (internal::traits>::RowsAtCompileTime == Dynamic && + internal::traits>::RowsAtCompileTime == Dynamic) + return m_arg2.rows(); + else + return m_arg1.rows(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index cols() const { + // return the fixed size type if available to enable compile time + // optimizations + if (internal::traits>::ColsAtCompileTime == Dynamic && + internal::traits>::ColsAtCompileTime == Dynamic) + return m_arg3.cols(); + else if (internal::traits>::ColsAtCompileTime == Dynamic && + internal::traits>::ColsAtCompileTime == Dynamic) + return m_arg2.cols(); + else + return m_arg1.cols(); + } + + /** \returns the first argument nested expression */ + EIGEN_DEVICE_FUNC const Arg1Nested_& arg1() const { return m_arg1; } + /** \returns the first argument nested expression */ + EIGEN_DEVICE_FUNC const Arg2Nested_& arg2() const { return m_arg2; } + /** \returns the third argument nested expression */ + EIGEN_DEVICE_FUNC const Arg3Nested_& arg3() const { return m_arg3; } + /** \returns the functor representing the ternary operation */ + EIGEN_DEVICE_FUNC const TernaryOp& functor() const { return m_functor; } + + protected: + Arg1Nested m_arg1; + Arg2Nested m_arg2; + Arg3Nested m_arg3; + const TernaryOp m_functor; +}; + +// Generic API dispatcher +template +class CwiseTernaryOpImpl : public internal::generic_xpr_base>::type { + public: + typedef typename internal::generic_xpr_base>::type Base; +}; + +} // end namespace Eigen + +#endif // EIGEN_CWISE_TERNARY_OP_H diff --git a/inst/include/Eigen/src/Core/CwiseUnaryOp.h b/inst/include/Eigen/src/Core/CwiseUnaryOp.h index f7ee60e9..94ec1a0f 100644 --- a/inst/include/Eigen/src/Core/CwiseUnaryOp.h +++ b/inst/include/Eigen/src/Core/CwiseUnaryOp.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2008-2010 Gael Guennebaud +// Copyright (C) 2008-2014 Gael Guennebaud // Copyright (C) 2006-2008 Benoit Jacob // // This Source Code Form is subject to the terms of the Mozilla @@ -11,116 +11,81 @@ #ifndef EIGEN_CWISE_UNARY_OP_H #define EIGEN_CWISE_UNARY_OP_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class CwiseUnaryOp - * \ingroup Core_Module - * - * \brief Generic expression where a coefficient-wise unary operator is applied to an expression - * - * \param UnaryOp template functor implementing the operator - * \param XprType the type of the expression to which we are applying the unary operator - * - * This class represents an expression where a unary operator is applied to an expression. - * It is the return type of all operations taking exactly 1 input expression, regardless of the - * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix - * is considered unary, because only the right-hand side is an expression, and its - * return type is a specialization of CwiseUnaryOp. - * - * Most of the time, this is the only way that it is used, so you typically don't have to name - * CwiseUnaryOp types explicitly. - * - * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp - */ +namespace Eigen { namespace internal { -template -struct traits > - : traits -{ - typedef typename result_of< - UnaryOp(typename XprType::Scalar) - >::type Scalar; +template +struct traits > : traits { + typedef typename result_of::type Scalar; typedef typename XprType::Nested XprTypeNested; - typedef typename remove_reference::type _XprTypeNested; - enum { - Flags = _XprTypeNested::Flags & ( - HereditaryBits | LinearAccessBit | AlignedBit - | (functor_traits::PacketAccess ? PacketAccessBit : 0)), - CoeffReadCost = EIGEN_ADD_COST(_XprTypeNested::CoeffReadCost, functor_traits::Cost) - }; + typedef std::remove_reference_t XprTypeNested_; + enum { Flags = XprTypeNested_::Flags & RowMajorBit }; }; -} +} // namespace internal -template +template class CwiseUnaryOpImpl; -template -class CwiseUnaryOp : internal::no_assignment_operator, - public CwiseUnaryOpImpl::StorageKind> -{ - public: - - typedef typename CwiseUnaryOpImpl::StorageKind>::Base Base; - EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp) - - inline CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp()) +/** \class CwiseUnaryOp + * \ingroup Core_Module + * + * \brief Generic expression where a coefficient-wise unary operator is applied to an expression + * + * \tparam UnaryOp template functor implementing the operator + * \tparam XprType the type of the expression to which we are applying the unary operator + * + * This class represents an expression where a unary operator is applied to an expression. + * It is the return type of all operations taking exactly 1 input expression, regardless of the + * presence of other inputs such as scalars. For example, the operator* in the expression 3*matrix + * is considered unary, because only the right-hand side is an expression, and its + * return type is a specialization of CwiseUnaryOp. + * + * Most of the time, this is the only way that it is used, so you typically don't have to name + * CwiseUnaryOp types explicitly. + * + * \sa MatrixBase::unaryExpr(const CustomUnaryOp &) const, class CwiseBinaryOp, class CwiseNullaryOp + */ +template +class CwiseUnaryOp : public CwiseUnaryOpImpl::StorageKind>, + internal::no_assignment_operator { + public: + typedef typename CwiseUnaryOpImpl::StorageKind>::Base Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryOp) + typedef typename internal::ref_selector::type XprTypeNested; + typedef internal::remove_all_t NestedExpression; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit CwiseUnaryOp(const XprType& xpr, const UnaryOp& func = UnaryOp()) : m_xpr(xpr), m_functor(func) {} - EIGEN_STRONG_INLINE Index rows() const { return m_xpr.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return m_xpr.cols(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_xpr.rows(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_xpr.cols(); } - /** \returns the functor representing the unary operation */ - const UnaryOp& functor() const { return m_functor; } + /** \returns the functor representing the unary operation */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const UnaryOp& functor() const { return m_functor; } - /** \returns the nested expression */ - const typename internal::remove_all::type& - nestedExpression() const { return m_xpr; } + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const internal::remove_all_t& nestedExpression() const { + return m_xpr; + } - /** \returns the nested expression */ - typename internal::remove_all::type& - nestedExpression() { return m_xpr.const_cast_derived(); } + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE internal::remove_all_t& nestedExpression() { return m_xpr; } - protected: - typename XprType::Nested m_xpr; - const UnaryOp m_functor; + protected: + XprTypeNested m_xpr; + const UnaryOp m_functor; }; -// This is the generic implementation for dense storage. -// It can be used for any expression types implementing the dense concept. -template -class CwiseUnaryOpImpl - : public internal::dense_xpr_base >::type -{ - public: - - typedef CwiseUnaryOp Derived; - typedef typename internal::dense_xpr_base >::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Derived) - - EIGEN_STRONG_INLINE const Scalar coeff(Index rowId, Index colId) const - { - return derived().functor()(derived().nestedExpression().coeff(rowId, colId)); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const - { - return derived().functor().packetOp(derived().nestedExpression().template packet(rowId, colId)); - } - - EIGEN_STRONG_INLINE const Scalar coeff(Index index) const - { - return derived().functor()(derived().nestedExpression().coeff(index)); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index index) const - { - return derived().functor().packetOp(derived().nestedExpression().template packet(index)); - } +// Generic API dispatcher +template +class CwiseUnaryOpImpl : public internal::generic_xpr_base >::type { + public: + typedef typename internal::generic_xpr_base >::type Base; }; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_CWISE_UNARY_OP_H +#endif // EIGEN_CWISE_UNARY_OP_H diff --git a/inst/include/Eigen/src/Core/CwiseUnaryView.h b/inst/include/Eigen/src/Core/CwiseUnaryView.h index b2638d32..7dd7623f 100644 --- a/inst/include/Eigen/src/Core/CwiseUnaryView.h +++ b/inst/include/Eigen/src/Core/CwiseUnaryView.h @@ -10,130 +10,158 @@ #ifndef EIGEN_CWISE_UNARY_VIEW_H #define EIGEN_CWISE_UNARY_VIEW_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class CwiseUnaryView - * \ingroup Core_Module - * - * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector - * - * \param ViewOp template functor implementing the view - * \param MatrixType the type of the matrix we are applying the unary operator - * - * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector. - * It is the return type of real() and imag(), and most of the time this is the only way it is used. - * - * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp - */ +namespace Eigen { namespace internal { -template -struct traits > - : traits -{ - typedef typename result_of< - ViewOp(typename traits::Scalar) - >::type Scalar; +template +struct traits > : traits { + typedef typename result_of::Scalar&)>::type1 ScalarRef; + static_assert(std::is_reference::value, "Views must return a reference type."); + typedef remove_all_t Scalar; typedef typename MatrixType::Nested MatrixTypeNested; - typedef typename remove_all::type _MatrixTypeNested; + typedef remove_all_t MatrixTypeNested_; enum { - Flags = (traits<_MatrixTypeNested>::Flags & (HereditaryBits | LvalueBit | LinearAccessBit | DirectAccessBit)), - CoeffReadCost = traits<_MatrixTypeNested>::CoeffReadCost + functor_traits::Cost, - MatrixTypeInnerStride = inner_stride_at_compile_time::ret, + FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, + Flags = + traits::Flags & + (RowMajorBit | FlagsLvalueBit | DirectAccessBit), // FIXME DirectAccessBit should not be handled by expressions + MatrixTypeInnerStride = inner_stride_at_compile_time::ret, // need to cast the sizeof's from size_t to int explicitly, otherwise: // "error: no integral type can represent all of the enumerator values - InnerStrideAtCompileTime = MatrixTypeInnerStride == Dynamic - ? int(Dynamic) - : int(MatrixTypeInnerStride) * int(sizeof(typename traits::Scalar) / sizeof(Scalar)), - OuterStrideAtCompileTime = outer_stride_at_compile_time::ret == Dynamic - ? int(Dynamic) - : outer_stride_at_compile_time::ret * int(sizeof(typename traits::Scalar) / sizeof(Scalar)) + InnerStrideAtCompileTime = + StrideType::InnerStrideAtCompileTime == 0 + ? (MatrixTypeInnerStride == Dynamic + ? int(Dynamic) + : int(MatrixTypeInnerStride) * int(sizeof(typename traits::Scalar) / sizeof(Scalar))) + : int(StrideType::InnerStrideAtCompileTime), + + OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0 + ? (outer_stride_at_compile_time::ret == Dynamic + ? int(Dynamic) + : outer_stride_at_compile_time::ret * + int(sizeof(typename traits::Scalar) / sizeof(Scalar))) + : int(StrideType::OuterStrideAtCompileTime) }; }; -} -template -class CwiseUnaryViewImpl; +// Generic API dispatcher +template ::value> +class CwiseUnaryViewImpl : public generic_xpr_base >::type { + public: + typedef typename generic_xpr_base >::type Base; +}; -template -class CwiseUnaryView : public CwiseUnaryViewImpl::StorageKind> -{ - public: +template +class CwiseUnaryViewImpl + : public dense_xpr_base >::type { + public: + typedef CwiseUnaryView Derived; + typedef typename dense_xpr_base >::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Derived) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl) + + EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(this->coeffRef(0)); } + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const { + return StrideType::InnerStrideAtCompileTime != 0 ? int(StrideType::InnerStrideAtCompileTime) + : derived().nestedExpression().innerStride() * + sizeof(typename traits::Scalar) / sizeof(Scalar); + } + + EIGEN_DEVICE_FUNC constexpr Index outerStride() const { + return StrideType::OuterStrideAtCompileTime != 0 ? int(StrideType::OuterStrideAtCompileTime) + : derived().nestedExpression().outerStride() * + sizeof(typename traits::Scalar) / sizeof(Scalar); + } + + protected: + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl) + + // Allow const access to coeffRef for the case of direct access being enabled. + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { + return internal::evaluator(derived()).coeffRef(index); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index col) const { + return internal::evaluator(derived()).coeffRef(row, col); + } +}; - typedef typename CwiseUnaryViewImpl::StorageKind>::Base Base; - EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView) +template +class CwiseUnaryViewImpl + : public CwiseUnaryViewImpl { + public: + typedef CwiseUnaryViewImpl Base; + typedef CwiseUnaryView Derived; + EIGEN_DENSE_PUBLIC_INTERFACE(Derived) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl) - inline CwiseUnaryView(const MatrixType& mat, const ViewOp& func = ViewOp()) - : m_matrix(mat), m_functor(func) {} + using Base::data; + EIGEN_DEVICE_FUNC inline Scalar* data() { return &(this->coeffRef(0)); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + return internal::evaluator(derived()).coeffRef(row, col); + } - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + return internal::evaluator(derived()).coeffRef(index); + } - EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); } + protected: + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(CwiseUnaryViewImpl) +}; - /** \returns the functor representing unary operation */ - const ViewOp& functor() const { return m_functor; } +} // namespace internal - /** \returns the nested expression */ - const typename internal::remove_all::type& - nestedExpression() const { return m_matrix; } +/** \class CwiseUnaryView + * \ingroup Core_Module + * + * \brief Generic lvalue expression of a coefficient-wise unary operator of a matrix or a vector + * + * \tparam ViewOp template functor implementing the view + * \tparam MatrixType the type of the matrix we are applying the unary operator + * + * This class represents a lvalue expression of a generic unary view operator of a matrix or a vector. + * It is the return type of real() and imag(), and most of the time this is the only way it is used. + * + * \sa MatrixBase::unaryViewExpr(const CustomUnaryOp &) const, class CwiseUnaryOp + */ +template +class CwiseUnaryView : public internal::CwiseUnaryViewImpl::StorageKind> { + public: + typedef typename internal::CwiseUnaryViewImpl::StorageKind>::Base Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(CwiseUnaryView) + typedef typename internal::ref_selector::non_const_type MatrixTypeNested; + typedef internal::remove_all_t NestedExpression; + + explicit EIGEN_DEVICE_FUNC inline CwiseUnaryView(MatrixType& mat, const ViewOp& func = ViewOp()) + : m_matrix(mat), m_functor(func) {} - /** \returns the nested expression */ - typename internal::remove_all::type& - nestedExpression() { return m_matrix.const_cast_derived(); } + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryView) - protected: - // FIXME changed from MatrixType::Nested because of a weird compilation error with sun CC - typename internal::nested::type m_matrix; - ViewOp m_functor; -}; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_matrix.rows(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_matrix.cols(); } + + /** \returns the functor representing unary operation */ + EIGEN_DEVICE_FUNC const ViewOp& functor() const { return m_functor; } + + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { return m_matrix; } + + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC std::remove_reference_t& nestedExpression() { return m_matrix; } -template -class CwiseUnaryViewImpl - : public internal::dense_xpr_base< CwiseUnaryView >::type -{ - public: - - typedef CwiseUnaryView Derived; - typedef typename internal::dense_xpr_base< CwiseUnaryView >::type Base; - - EIGEN_DENSE_PUBLIC_INTERFACE(Derived) - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(CwiseUnaryViewImpl) - - inline Scalar* data() { return &coeffRef(0); } - inline const Scalar* data() const { return &coeff(0); } - - inline Index innerStride() const - { - return derived().nestedExpression().innerStride() * sizeof(typename internal::traits::Scalar) / sizeof(Scalar); - } - - inline Index outerStride() const - { - return derived().nestedExpression().outerStride() * sizeof(typename internal::traits::Scalar) / sizeof(Scalar); - } - - EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const - { - return derived().functor()(derived().nestedExpression().coeff(row, col)); - } - - EIGEN_STRONG_INLINE CoeffReturnType coeff(Index index) const - { - return derived().functor()(derived().nestedExpression().coeff(index)); - } - - EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) - { - return derived().functor()(const_cast_derived().nestedExpression().coeffRef(row, col)); - } - - EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) - { - return derived().functor()(const_cast_derived().nestedExpression().coeffRef(index)); - } + protected: + MatrixTypeNested m_matrix; + ViewOp m_functor; }; -} // end namespace Eigen +} // namespace Eigen -#endif // EIGEN_CWISE_UNARY_VIEW_H +#endif // EIGEN_CWISE_UNARY_VIEW_H diff --git a/inst/include/Eigen/src/Core/DenseBase.h b/inst/include/Eigen/src/Core/DenseBase.h index 4b371b07..c81e1d10 100644 --- a/inst/include/Eigen/src/Core/DenseBase.h +++ b/inst/include/Eigen/src/Core/DenseBase.h @@ -11,511 +11,663 @@ #ifndef EIGEN_DENSEBASE_H #define EIGEN_DENSEBASE_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { -namespace internal { - // The index type defined by EIGEN_DEFAULT_DENSE_INDEX_TYPE must be a signed type. -// This dummy function simply aims at checking that at compile time. -static inline void check_DenseIndex_is_signed() { - EIGEN_STATIC_ASSERT(NumTraits::IsSigned,THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE); -} +EIGEN_STATIC_ASSERT(NumTraits::IsSigned, THE_INDEX_TYPE_MUST_BE_A_SIGNED_TYPE) -} // end namespace internal - /** \class DenseBase - * \ingroup Core_Module - * - * \brief Base class for all dense matrices, vectors, and arrays - * - * This class is the base that is inherited by all dense objects (matrix, vector, arrays, - * and related expression types). The common Eigen API for dense objects is contained in this class. - * - * \tparam Derived is the derived type, e.g., a matrix type or an expression. - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN. - * - * \sa \ref TopicClassHierarchy - */ -template class DenseBase + * \ingroup Core_Module + * + * \brief Base class for all dense matrices, vectors, and arrays + * + * This class is the base that is inherited by all dense objects (matrix, vector, arrays, + * and related expression types). The common Eigen API for dense objects is contained in this class. + * + * \tparam Derived is the derived type, e.g., a matrix type or an expression. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_DENSEBASE_PLUGIN. + * + * \sa \blank \ref TopicClassHierarchy + */ +template +class DenseBase #ifndef EIGEN_PARSED_BY_DOXYGEN - : public internal::special_scalar_op_base::Scalar, - typename NumTraits::Scalar>::Real, - DenseCoeffsBase > + : public DenseCoeffsBase::value> #else - : public DenseCoeffsBase -#endif // not EIGEN_PARSED_BY_DOXYGEN + : public DenseCoeffsBase +#endif // not EIGEN_PARSED_BY_DOXYGEN { - public: - - class InnerIterator; - - typedef typename internal::traits::StorageKind StorageKind; - - /** \brief The type of indices - * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE. - * \sa \ref TopicPreprocessorDirectives. - */ - typedef typename internal::traits::Index Index; - - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - typedef internal::special_scalar_op_base > Base; - - using Base::operator*; - using Base::derived; - using Base::const_cast_derived; - using Base::rows; - using Base::cols; - using Base::size; - using Base::rowIndexByOuterInner; - using Base::colIndexByOuterInner; - using Base::coeff; - using Base::coeffByOuterInner; - using Base::packet; - using Base::packetByOuterInner; - using Base::writePacket; - using Base::writePacketByOuterInner; - using Base::coeffRef; - using Base::coeffRefByOuterInner; - using Base::copyCoeff; - using Base::copyCoeffByOuterInner; - using Base::copyPacket; - using Base::copyPacketByOuterInner; - using Base::operator(); - using Base::operator[]; - using Base::x; - using Base::y; - using Base::z; - using Base::w; - using Base::stride; - using Base::innerStride; - using Base::outerStride; - using Base::rowStride; - using Base::colStride; - typedef typename Base::CoeffReturnType CoeffReturnType; - - enum { - - RowsAtCompileTime = internal::traits::RowsAtCompileTime, - /**< The number of rows at compile-time. This is just a copy of the value provided - * by the \a Derived type. If a value is not known at compile-time, - * it is set to the \a Dynamic constant. - * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */ - - ColsAtCompileTime = internal::traits::ColsAtCompileTime, - /**< The number of columns at compile-time. This is just a copy of the value provided - * by the \a Derived type. If a value is not known at compile-time, - * it is set to the \a Dynamic constant. - * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */ - - - SizeAtCompileTime = (internal::size_at_compile_time::RowsAtCompileTime, - internal::traits::ColsAtCompileTime>::ret), - /**< This is equal to the number of coefficients, i.e. the number of - * rows times the number of columns, or to \a Dynamic if this is not - * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */ - - MaxRowsAtCompileTime = internal::traits::MaxRowsAtCompileTime, - /**< This value is equal to the maximum possible number of rows that this expression - * might have. If this expression might have an arbitrarily high number of rows, - * this value is set to \a Dynamic. - * - * This value is useful to know when evaluating an expression, in order to determine - * whether it is possible to avoid doing a dynamic memory allocation. - * - * \sa RowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime - */ - - MaxColsAtCompileTime = internal::traits::MaxColsAtCompileTime, - /**< This value is equal to the maximum possible number of columns that this expression - * might have. If this expression might have an arbitrarily high number of columns, - * this value is set to \a Dynamic. - * - * This value is useful to know when evaluating an expression, in order to determine - * whether it is possible to avoid doing a dynamic memory allocation. - * - * \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime - */ - - MaxSizeAtCompileTime = (internal::size_at_compile_time::MaxRowsAtCompileTime, - internal::traits::MaxColsAtCompileTime>::ret), - /**< This value is equal to the maximum possible number of coefficients that this expression - * might have. If this expression might have an arbitrarily high number of coefficients, - * this value is set to \a Dynamic. - * - * This value is useful to know when evaluating an expression, in order to determine - * whether it is possible to avoid doing a dynamic memory allocation. - * - * \sa SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime - */ - - IsVectorAtCompileTime = internal::traits::MaxRowsAtCompileTime == 1 - || internal::traits::MaxColsAtCompileTime == 1, - /**< This is set to true if either the number of rows or the number of - * columns is known at compile-time to be equal to 1. Indeed, in that case, - * we are dealing with a column-vector (if there is only one column) or with - * a row-vector (if there is only one row). */ - - Flags = internal::traits::Flags, - /**< This stores expression \ref flags flags which may or may not be inherited by new expressions - * constructed from this one. See the \ref flags "list of flags". - */ - - IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */ - - InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) - : int(IsRowMajor) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), - - CoeffReadCost = internal::traits::CoeffReadCost, - /**< This is a rough measure of how expensive it is to read one coefficient from - * this expression. - */ - - InnerStrideAtCompileTime = internal::inner_stride_at_compile_time::ret, - OuterStrideAtCompileTime = internal::outer_stride_at_compile_time::ret - }; - - enum { ThisConstantIsPrivateInPlainObjectBase }; - - /** \returns the number of nonzero coefficients which is in practice the number - * of stored coefficients. */ - inline Index nonZeros() const { return size(); } - - /** \returns the outer size. - * - * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension - * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a - * column-major matrix, and the number of rows for a row-major matrix. */ - Index outerSize() const - { - return IsVectorAtCompileTime ? 1 - : int(IsRowMajor) ? this->rows() : this->cols(); - } - - /** \returns the inner size. - * - * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension - * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a - * column-major matrix, and the number of columns for a row-major matrix. */ - Index innerSize() const - { - return IsVectorAtCompileTime ? this->size() - : int(IsRowMajor) ? this->cols() : this->rows(); - } - - /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are - * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does - * nothing else. - */ - void resize(Index newSize) - { - EIGEN_ONLY_USED_FOR_DEBUG(newSize); - eigen_assert(newSize == this->size() - && "DenseBase::resize() does not actually allow to resize."); - } - /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are - * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and does - * nothing else. - */ - void resize(Index nbRows, Index nbCols) - { - EIGEN_ONLY_USED_FOR_DEBUG(nbRows); - EIGEN_ONLY_USED_FOR_DEBUG(nbCols); - eigen_assert(nbRows == this->rows() && nbCols == this->cols() - && "DenseBase::resize() does not actually allow to resize."); - } + public: + /** Inner iterator type to iterate over the coefficients of a row or column. + * \sa class InnerIterator + */ + typedef Eigen::InnerIterator InnerIterator; + + typedef typename internal::traits::StorageKind StorageKind; + + /** + * \brief The type used to store indices + * \details This typedef is relevant for types that store multiple indices such as + * PermutationMatrix or Transpositions, otherwise it defaults to Eigen::Index + * \sa \blank \ref TopicPreprocessorDirectives, Eigen::Index, SparseMatrixBase. + */ + typedef typename internal::traits::StorageIndex StorageIndex; + + /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex, etc. */ + typedef typename internal::traits::Scalar Scalar; + + /** The numeric type of the expression' coefficients, e.g. float, double, int or std::complex, etc. + * + * It is an alias for the Scalar type */ + typedef Scalar value_type; + + typedef typename NumTraits::Real RealScalar; + typedef DenseCoeffsBase::value> Base; + + using Base::coeff; + using Base::coeffByOuterInner; + using Base::colIndexByOuterInner; + using Base::cols; + using Base::const_cast_derived; + using Base::derived; + using Base::rowIndexByOuterInner; + using Base::rows; + using Base::size; + using Base::operator(); + using Base::operator[]; + using Base::colStride; + using Base::innerStride; + using Base::outerStride; + using Base::rowStride; + using Base::stride; + using Base::w; + using Base::x; + using Base::y; + using Base::z; + typedef typename Base::CoeffReturnType CoeffReturnType; + + enum { + + RowsAtCompileTime = internal::traits::RowsAtCompileTime, + /**< The number of rows at compile-time. This is just a copy of the value provided + * by the \a Derived type. If a value is not known at compile-time, + * it is set to the \a Dynamic constant. + * \sa MatrixBase::rows(), MatrixBase::cols(), ColsAtCompileTime, SizeAtCompileTime */ + + ColsAtCompileTime = internal::traits::ColsAtCompileTime, + /**< The number of columns at compile-time. This is just a copy of the value provided + * by the \a Derived type. If a value is not known at compile-time, + * it is set to the \a Dynamic constant. + * \sa MatrixBase::rows(), MatrixBase::cols(), RowsAtCompileTime, SizeAtCompileTime */ + + SizeAtCompileTime = (internal::size_of_xpr_at_compile_time::ret), + /**< This is equal to the number of coefficients, i.e. the number of + * rows times the number of columns, or to \a Dynamic if this is not + * known at compile-time. \sa RowsAtCompileTime, ColsAtCompileTime */ + + MaxRowsAtCompileTime = internal::traits::MaxRowsAtCompileTime, + /**< This value is equal to the maximum possible number of rows that this expression + * might have. If this expression might have an arbitrarily high number of rows, + * this value is set to \a Dynamic. + * + * This value is useful to know when evaluating an expression, in order to determine + * whether it is possible to avoid doing a dynamic memory allocation. + * + * \sa RowsAtCompileTime, MaxColsAtCompileTime, MaxSizeAtCompileTime + */ + + MaxColsAtCompileTime = internal::traits::MaxColsAtCompileTime, + /**< This value is equal to the maximum possible number of columns that this expression + * might have. If this expression might have an arbitrarily high number of columns, + * this value is set to \a Dynamic. + * + * This value is useful to know when evaluating an expression, in order to determine + * whether it is possible to avoid doing a dynamic memory allocation. + * + * \sa ColsAtCompileTime, MaxRowsAtCompileTime, MaxSizeAtCompileTime + */ + + MaxSizeAtCompileTime = internal::size_at_compile_time(internal::traits::MaxRowsAtCompileTime, + internal::traits::MaxColsAtCompileTime), + /**< This value is equal to the maximum possible number of coefficients that this expression + * might have. If this expression might have an arbitrarily high number of coefficients, + * this value is set to \a Dynamic. + * + * This value is useful to know when evaluating an expression, in order to determine + * whether it is possible to avoid doing a dynamic memory allocation. + * + * \sa SizeAtCompileTime, MaxRowsAtCompileTime, MaxColsAtCompileTime + */ + + IsVectorAtCompileTime = + internal::traits::RowsAtCompileTime == 1 || internal::traits::ColsAtCompileTime == 1, + /**< This is set to true if either the number of rows or the number of + * columns is known at compile-time to be equal to 1. Indeed, in that case, + * we are dealing with a column-vector (if there is only one column) or with + * a row-vector (if there is only one row). */ + + NumDimensions = int(MaxSizeAtCompileTime) == 1 ? 0 + : bool(IsVectorAtCompileTime) ? 1 + : 2, + /**< This value is equal to Tensor::NumDimensions, i.e. 0 for scalars, 1 for vectors, + * and 2 for matrices. + */ + + Flags = internal::traits::Flags, + /**< This stores expression \ref flags flags which may or may not be inherited by new expressions + * constructed from this one. See the \ref flags "list of flags". + */ + + IsRowMajor = int(Flags) & RowMajorBit, /**< True if this expression has row-major storage order. */ + + InnerSizeAtCompileTime = int(IsVectorAtCompileTime) ? int(SizeAtCompileTime) + : int(IsRowMajor) ? int(ColsAtCompileTime) + : int(RowsAtCompileTime), + + InnerStrideAtCompileTime = internal::inner_stride_at_compile_time::ret, + OuterStrideAtCompileTime = internal::outer_stride_at_compile_time::ret + }; + + typedef typename internal::find_best_packet::type PacketScalar; + + enum { IsPlainObjectBase = 0 }; + + /** The plain matrix type corresponding to this expression. + * \sa PlainObject */ + typedef Matrix::Scalar, internal::traits::RowsAtCompileTime, + internal::traits::ColsAtCompileTime, + AutoAlign | (internal::traits::Flags & RowMajorBit ? RowMajor : ColMajor), + internal::traits::MaxRowsAtCompileTime, internal::traits::MaxColsAtCompileTime> + PlainMatrix; + + /** The plain array type corresponding to this expression. + * \sa PlainObject */ + typedef Array::Scalar, internal::traits::RowsAtCompileTime, + internal::traits::ColsAtCompileTime, + AutoAlign | (internal::traits::Flags & RowMajorBit ? RowMajor : ColMajor), + internal::traits::MaxRowsAtCompileTime, internal::traits::MaxColsAtCompileTime> + PlainArray; + + /** \brief The plain matrix or array type corresponding to this expression. + * + * This is not necessarily exactly the return type of eval(). In the case of plain matrices, + * the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed + * that the return type of eval() is either PlainObject or const PlainObject&. + */ + typedef std::conditional_t::XprKind, MatrixXpr>::value, + PlainMatrix, PlainArray> + PlainObject; + + /** \returns the outer size. + * + * \note For a vector, this returns just 1. For a matrix (non-vector), this is the major dimension + * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of columns for a + * column-major matrix, and the number of rows for a row-major matrix. */ + EIGEN_DEVICE_FUNC constexpr Index outerSize() const { + return IsVectorAtCompileTime ? 1 : int(IsRowMajor) ? this->rows() : this->cols(); + } + + /** \returns the inner size. + * + * \note For a vector, this is just the size. For a matrix (non-vector), this is the minor dimension + * with respect to the \ref TopicStorageOrders "storage order", i.e., the number of rows for a + * column-major matrix, and the number of columns for a row-major matrix. */ + EIGEN_DEVICE_FUNC constexpr Index innerSize() const { + return IsVectorAtCompileTime ? this->size() : int(IsRowMajor) ? this->cols() : this->rows(); + } + + /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are + * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and + * does nothing else. + */ + EIGEN_DEVICE_FUNC void resize(Index newSize) { + EIGEN_ONLY_USED_FOR_DEBUG(newSize); + eigen_assert(newSize == this->size() && "DenseBase::resize() does not actually allow to resize."); + } + /** Only plain matrices/arrays, not expressions, may be resized; therefore the only useful resize methods are + * Matrix::resize() and Array::resize(). The present method only asserts that the new size equals the old size, and + * does nothing else. + */ + EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { + EIGEN_ONLY_USED_FOR_DEBUG(rows); + EIGEN_ONLY_USED_FOR_DEBUG(cols); + eigen_assert(rows == this->rows() && cols == this->cols() && + "DenseBase::resize() does not actually allow to resize."); + } #ifndef EIGEN_PARSED_BY_DOXYGEN + /** \internal Represents a matrix with all coefficients equal to one another*/ + typedef CwiseNullaryOp, PlainObject> ConstantReturnType; + /** \internal Represents a matrix with all coefficients equal to zero*/ + typedef CwiseNullaryOp, PlainObject> ZeroReturnType; + /** \internal \deprecated Represents a vector with linearly spaced coefficients that allows sequential access only. */ + EIGEN_DEPRECATED typedef CwiseNullaryOp, PlainObject> SequentialLinSpacedReturnType; + /** \internal Represents a vector with linearly spaced coefficients that allows random access. */ + typedef CwiseNullaryOp, PlainObject> RandomAccessLinSpacedReturnType; + /** \internal Represents a vector with equally spaced coefficients that allows random access. */ + typedef CwiseNullaryOp, PlainObject> RandomAccessEqualSpacedReturnType; + /** \internal the return type of MatrixBase::eigenvalues() */ + typedef Matrix::Scalar>::Real, + internal::traits::ColsAtCompileTime, 1> + EigenvaluesReturnType; + +#endif // not EIGEN_PARSED_BY_DOXYGEN + + /** Copies \a other into *this. \returns a reference to *this. */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase& other); + + /** Special case of the template operator=, in order to prevent the compiler + * from generating a default operator= (issue hit with g++ 4.1) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator=(const EigenBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator+=(const EigenBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator-=(const EigenBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator=(const ReturnByValue& func); + + /** \internal + * Copies \a other into *this without evaluating other. \returns a reference to *this. */ + template + /** \deprecated */ + EIGEN_DEPRECATED EIGEN_DEVICE_FUNC Derived& lazyAssign(const DenseBase& other); + + EIGEN_DEVICE_FUNC CommaInitializer operator<<(const Scalar& s); + + template + /** \deprecated it now returns \c *this */ + EIGEN_DEPRECATED const Derived& flagged() const { + return derived(); + } + + template + EIGEN_DEVICE_FUNC CommaInitializer operator<<(const DenseBase& other); + + typedef Transpose TransposeReturnType; + EIGEN_DEVICE_FUNC TransposeReturnType transpose(); + typedef Transpose ConstTransposeReturnType; + EIGEN_DEVICE_FUNC const ConstTransposeReturnType transpose() const; + EIGEN_DEVICE_FUNC void transposeInPlace(); + + EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index rows, Index cols, const Scalar& value); + EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(Index size, const Scalar& value); + EIGEN_DEVICE_FUNC static const ConstantReturnType Constant(const Scalar& value); + + EIGEN_DEPRECATED_WITH_REASON("The method may result in accuracy loss. Use .EqualSpaced() instead.") + EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, Index size, const Scalar& low, + const Scalar& high); + EIGEN_DEPRECATED_WITH_REASON("The method may result in accuracy loss. Use .EqualSpaced() instead.") + EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Sequential_t, const Scalar& low, + const Scalar& high); + + EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(Index size, const Scalar& low, + const Scalar& high); + EIGEN_DEVICE_FUNC static const RandomAccessLinSpacedReturnType LinSpaced(const Scalar& low, const Scalar& high); + + EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(Index size, const Scalar& low, + const Scalar& step); + EIGEN_DEVICE_FUNC static const RandomAccessEqualSpacedReturnType EqualSpaced(const Scalar& low, const Scalar& step); + + template + EIGEN_DEVICE_FUNC static const CwiseNullaryOp NullaryExpr(Index rows, Index cols, + const CustomNullaryOp& func); + template + EIGEN_DEVICE_FUNC static const CwiseNullaryOp NullaryExpr(Index size, + const CustomNullaryOp& func); + template + EIGEN_DEVICE_FUNC static const CwiseNullaryOp NullaryExpr(const CustomNullaryOp& func); + + EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index rows, Index cols); + EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(Index size); + EIGEN_DEVICE_FUNC static const ZeroReturnType Zero(); + EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index rows, Index cols); + EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(Index size); + EIGEN_DEVICE_FUNC static const ConstantReturnType Ones(); + + EIGEN_DEVICE_FUNC void fill(const Scalar& value); + EIGEN_DEVICE_FUNC Derived& setConstant(const Scalar& value); + EIGEN_DEVICE_FUNC Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high); + EIGEN_DEVICE_FUNC Derived& setLinSpaced(const Scalar& low, const Scalar& high); + EIGEN_DEVICE_FUNC Derived& setEqualSpaced(Index size, const Scalar& low, const Scalar& step); + EIGEN_DEVICE_FUNC Derived& setEqualSpaced(const Scalar& low, const Scalar& step); + EIGEN_DEVICE_FUNC Derived& setZero(); + EIGEN_DEVICE_FUNC Derived& setOnes(); + EIGEN_DEVICE_FUNC Derived& setRandom(); + + template + EIGEN_DEVICE_FUNC bool isApprox(const DenseBase& other, + const RealScalar& prec = NumTraits::dummy_precision()) const; + EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const RealScalar& other, + const RealScalar& prec = NumTraits::dummy_precision()) const; + template + EIGEN_DEVICE_FUNC bool isMuchSmallerThan(const DenseBase& other, + const RealScalar& prec = NumTraits::dummy_precision()) const; + + EIGEN_DEVICE_FUNC bool isApproxToConstant(const Scalar& value, + const RealScalar& prec = NumTraits::dummy_precision()) const; + EIGEN_DEVICE_FUNC bool isConstant(const Scalar& value, + const RealScalar& prec = NumTraits::dummy_precision()) const; + EIGEN_DEVICE_FUNC bool isZero(const RealScalar& prec = NumTraits::dummy_precision()) const; + EIGEN_DEVICE_FUNC bool isOnes(const RealScalar& prec = NumTraits::dummy_precision()) const; + + EIGEN_DEVICE_FUNC inline bool hasNaN() const; + EIGEN_DEVICE_FUNC inline bool allFinite() const; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const Scalar& other); + template ::value, typename = std::enable_if_t> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator*=(const RealScalar& other); + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const Scalar& other); + template ::value, typename = std::enable_if_t> + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator/=(const RealScalar& other); + + typedef internal::add_const_on_value_type_t::type> EvalReturnType; + /** \returns the matrix or vector obtained by evaluating this expression. + * + * Notice that in the case of a plain matrix or vector (not an expression) this function just returns + * a const reference, in order to avoid a useless copy. + * + * \warning Be careful with eval() and the auto C++ keyword, as detailed in this \link TopicPitfalls_auto_keyword page + * \endlink. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE EvalReturnType eval() const { + // Even though MSVC does not honor strong inlining when the return type + // is a dynamic matrix, we desperately need strong inlining for fixed + // size types on MSVC. + return typename internal::eval::type(derived()); + } + + /** swaps *this with the expression \a other. + * + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(const DenseBase& other) { + EIGEN_STATIC_ASSERT(!OtherDerived::IsPlainObjectBase, THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY); + eigen_assert(rows() == other.rows() && cols() == other.cols()); + call_assignment(derived(), other.const_cast_derived(), internal::swap_assign_op()); + } + + /** swaps *this with the matrix or array \a other. + * + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(PlainObjectBase& other) { + eigen_assert(rows() == other.rows() && cols() == other.cols()); + call_assignment(derived(), other.derived(), internal::swap_assign_op()); + } + + EIGEN_DEVICE_FUNC inline const NestByValue nestByValue() const; + EIGEN_DEVICE_FUNC inline const ForceAlignedAccess forceAlignedAccess() const; + EIGEN_DEVICE_FUNC inline ForceAlignedAccess forceAlignedAccess(); + template + EIGEN_DEVICE_FUNC inline const std::conditional_t, Derived&> + forceAlignedAccessIf() const; + template + EIGEN_DEVICE_FUNC inline std::conditional_t, Derived&> forceAlignedAccessIf(); + + EIGEN_DEVICE_FUNC Scalar sum() const; + EIGEN_DEVICE_FUNC Scalar mean() const; + EIGEN_DEVICE_FUNC Scalar trace() const; + + EIGEN_DEVICE_FUNC Scalar prod() const; + + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar minCoeff() const; + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar maxCoeff() const; + + // By default, the fastest version with undefined NaN propagation semantics is + // used. + // TODO(rmlarsen): Replace with default template argument when we move to + // c++11 or beyond. + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar minCoeff() const { + return minCoeff(); + } + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar maxCoeff() const { + return maxCoeff(); + } + + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar minCoeff(IndexType* row, IndexType* col) const; + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar maxCoeff(IndexType* row, IndexType* col) const; + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar minCoeff(IndexType* index) const; + template + EIGEN_DEVICE_FUNC typename internal::traits::Scalar maxCoeff(IndexType* index) const; + + // TODO(rmlarsen): Replace these methods with a default template argument. + template + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar minCoeff(IndexType* row, IndexType* col) const { + return minCoeff(row, col); + } + template + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar maxCoeff(IndexType* row, IndexType* col) const { + return maxCoeff(row, col); + } + template + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar minCoeff(IndexType* index) const { + return minCoeff(index); + } + template + EIGEN_DEVICE_FUNC inline typename internal::traits::Scalar maxCoeff(IndexType* index) const { + return maxCoeff(index); + } + + template + EIGEN_DEVICE_FUNC Scalar redux(const BinaryOp& func) const; + + template + EIGEN_DEVICE_FUNC void visit(Visitor& func) const; + + /** \returns a WithFormat proxy object allowing to print a matrix the with given + * format \a fmt. + * + * See class IOFormat for some examples. + * + * \sa class IOFormat, class WithFormat + */ + inline const WithFormat format(const IOFormat& fmt) const { return WithFormat(derived(), fmt); } + + /** \returns the unique coefficient of a 1x1 expression */ + EIGEN_DEVICE_FUNC CoeffReturnType value() const { + EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) eigen_assert(this->rows() == 1 && this->cols() == 1); + return derived().coeff(0, 0); + } + + EIGEN_DEVICE_FUNC bool all() const; + EIGEN_DEVICE_FUNC bool any() const; + EIGEN_DEVICE_FUNC Index count() const; + + typedef VectorwiseOp RowwiseReturnType; + typedef const VectorwiseOp ConstRowwiseReturnType; + typedef VectorwiseOp ColwiseReturnType; + typedef const VectorwiseOp ConstColwiseReturnType; + + /** \returns a VectorwiseOp wrapper of *this for broadcasting and partial reductions + * + * Example: \include MatrixBase_rowwise.cpp + * Output: \verbinclude MatrixBase_rowwise.out + * + * \sa colwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting + */ + // Code moved here due to a CUDA compiler bug + EIGEN_DEVICE_FUNC inline ConstRowwiseReturnType rowwise() const { return ConstRowwiseReturnType(derived()); } + EIGEN_DEVICE_FUNC RowwiseReturnType rowwise(); + + /** \returns a VectorwiseOp wrapper of *this broadcasting and partial reductions + * + * Example: \include MatrixBase_colwise.cpp + * Output: \verbinclude MatrixBase_colwise.out + * + * \sa rowwise(), class VectorwiseOp, \ref TutorialReductionsVisitorsBroadcasting + */ + EIGEN_DEVICE_FUNC inline ConstColwiseReturnType colwise() const { return ConstColwiseReturnType(derived()); } + EIGEN_DEVICE_FUNC ColwiseReturnType colwise(); + + typedef CwiseNullaryOp, PlainObject> RandomReturnType; + static const RandomReturnType Random(Index rows, Index cols); + static const RandomReturnType Random(Index size); + static const RandomReturnType Random(); + + template + inline EIGEN_DEVICE_FUNC + CwiseTernaryOp::Scalar, + typename DenseBase::Scalar, Scalar>, + ThenDerived, ElseDerived, Derived> + select(const DenseBase& thenMatrix, const DenseBase& elseMatrix) const; + + template + inline EIGEN_DEVICE_FUNC + CwiseTernaryOp::Scalar, + typename DenseBase::Scalar, Scalar>, + ThenDerived, typename DenseBase::ConstantReturnType, Derived> + select(const DenseBase& thenMatrix, const typename DenseBase::Scalar& elseScalar) const; + + template + inline EIGEN_DEVICE_FUNC + CwiseTernaryOp::Scalar, + typename DenseBase::Scalar, Scalar>, + typename DenseBase::ConstantReturnType, ElseDerived, Derived> + select(const typename DenseBase::Scalar& thenScalar, const DenseBase& elseMatrix) const; + + template + RealScalar lpNorm() const; + + template + EIGEN_DEVICE_FUNC const Replicate replicate() const; + /** + * \return an expression of the replication of \c *this + * + * Example: \include MatrixBase_replicate_int_int.cpp + * Output: \verbinclude MatrixBase_replicate_int_int.out + * + * \sa VectorwiseOp::replicate(), DenseBase::replicate(), class Replicate + */ + // Code moved here due to a CUDA compiler bug + EIGEN_DEVICE_FUNC const Replicate replicate(Index rowFactor, Index colFactor) const { + return Replicate(derived(), rowFactor, colFactor); + } + + typedef Reverse ReverseReturnType; + typedef const Reverse ConstReverseReturnType; + EIGEN_DEVICE_FUNC ReverseReturnType reverse(); + /** This is the const version of reverse(). */ + // Code moved here due to a CUDA compiler bug + EIGEN_DEVICE_FUNC ConstReverseReturnType reverse() const { return ConstReverseReturnType(derived()); } + EIGEN_DEVICE_FUNC void reverseInPlace(); + +#ifdef EIGEN_PARSED_BY_DOXYGEN + /** STL-like RandomAccessIterator + * iterator type as returned by the begin() and end() methods. + */ + typedef random_access_iterator_type iterator; + /** This is the const version of iterator (aka read-only) */ + typedef random_access_iterator_type const_iterator; +#else + typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit, + internal::pointer_based_stl_iterator, + internal::generic_randaccess_stl_iterator > + iterator_type; - /** \internal Represents a matrix with all coefficients equal to one another*/ - typedef CwiseNullaryOp,Derived> ConstantReturnType; - /** \internal Represents a vector with linearly spaced coefficients that allows sequential access only. */ - typedef CwiseNullaryOp,Derived> SequentialLinSpacedReturnType; - /** \internal Represents a vector with linearly spaced coefficients that allows random access. */ - typedef CwiseNullaryOp,Derived> RandomAccessLinSpacedReturnType; - /** \internal the return type of MatrixBase::eigenvalues() */ - typedef Matrix::Scalar>::Real, internal::traits::ColsAtCompileTime, 1> EigenvaluesReturnType; - -#endif // not EIGEN_PARSED_BY_DOXYGEN - - /** Copies \a other into *this. \returns a reference to *this. */ - template - Derived& operator=(const DenseBase& other); - - /** Special case of the template operator=, in order to prevent the compiler - * from generating a default operator= (issue hit with g++ 4.1) - */ - Derived& operator=(const DenseBase& other); - - template - Derived& operator=(const EigenBase &other); - - template - Derived& operator+=(const EigenBase &other); - - template - Derived& operator-=(const EigenBase &other); - - template - Derived& operator=(const ReturnByValue& func); - - /** \internal Copies \a other into *this without evaluating other. \returns a reference to *this. */ - template - Derived& lazyAssign(const DenseBase& other); - - /** \internal Evaluates \a other into *this. \returns a reference to *this. */ - template - Derived& lazyAssign(const ReturnByValue& other); - - CommaInitializer operator<< (const Scalar& s); + typedef std::conditional_t<(Flags & DirectAccessBit) == DirectAccessBit, + internal::pointer_based_stl_iterator, + internal::generic_randaccess_stl_iterator > + const_iterator_type; - template - const Flagged flagged() const; + // Stl-style iterators are supported only for vectors. - template - CommaInitializer operator<< (const DenseBase& other); + typedef std::conditional_t iterator; - Eigen::Transpose transpose(); - typedef typename internal::add_const >::type ConstTransposeReturnType; - ConstTransposeReturnType transpose() const; - void transposeInPlace(); -#ifndef EIGEN_NO_DEBUG - protected: - template - void checkTransposeAliasing(const OtherDerived& other) const; - public: + typedef std::conditional_t const_iterator; #endif + inline iterator begin(); + inline const_iterator begin() const; + inline const_iterator cbegin() const; + inline iterator end(); + inline const_iterator end() const; + inline const_iterator cend() const; + + using RealViewReturnType = std::conditional_t::IsComplex, RealView, Derived&>; + using ConstRealViewReturnType = + std::conditional_t::IsComplex, RealView, const Derived&>; - static const ConstantReturnType - Constant(Index rows, Index cols, const Scalar& value); - static const ConstantReturnType - Constant(Index size, const Scalar& value); - static const ConstantReturnType - Constant(const Scalar& value); - - static const SequentialLinSpacedReturnType - LinSpaced(Sequential_t, Index size, const Scalar& low, const Scalar& high); - static const RandomAccessLinSpacedReturnType - LinSpaced(Index size, const Scalar& low, const Scalar& high); - static const SequentialLinSpacedReturnType - LinSpaced(Sequential_t, const Scalar& low, const Scalar& high); - static const RandomAccessLinSpacedReturnType - LinSpaced(const Scalar& low, const Scalar& high); - - template - static const CwiseNullaryOp - NullaryExpr(Index rows, Index cols, const CustomNullaryOp& func); - template - static const CwiseNullaryOp - NullaryExpr(Index size, const CustomNullaryOp& func); - template - static const CwiseNullaryOp - NullaryExpr(const CustomNullaryOp& func); - - static const ConstantReturnType Zero(Index rows, Index cols); - static const ConstantReturnType Zero(Index size); - static const ConstantReturnType Zero(); - static const ConstantReturnType Ones(Index rows, Index cols); - static const ConstantReturnType Ones(Index size); - static const ConstantReturnType Ones(); - - void fill(const Scalar& value); - Derived& setConstant(const Scalar& value); - Derived& setLinSpaced(Index size, const Scalar& low, const Scalar& high); - Derived& setLinSpaced(const Scalar& low, const Scalar& high); - Derived& setZero(); - Derived& setOnes(); - Derived& setRandom(); - - template - bool isApprox(const DenseBase& other, - const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isMuchSmallerThan(const RealScalar& other, - const RealScalar& prec = NumTraits::dummy_precision()) const; - template - bool isMuchSmallerThan(const DenseBase& other, - const RealScalar& prec = NumTraits::dummy_precision()) const; - - bool isApproxToConstant(const Scalar& value, const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isConstant(const Scalar& value, const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isZero(const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isOnes(const RealScalar& prec = NumTraits::dummy_precision()) const; - - inline bool hasNaN() const; - inline bool allFinite() const; - - inline Derived& operator*=(const Scalar& other); - inline Derived& operator/=(const Scalar& other); - - typedef typename internal::add_const_on_value_type::type>::type EvalReturnType; - /** \returns the matrix or vector obtained by evaluating this expression. - * - * Notice that in the case of a plain matrix or vector (not an expression) this function just returns - * a const reference, in order to avoid a useless copy. - */ - EIGEN_STRONG_INLINE EvalReturnType eval() const - { - // Even though MSVC does not honor strong inlining when the return type - // is a dynamic matrix, we desperately need strong inlining for fixed - // size types on MSVC. - return typename internal::eval::type(derived()); - } - - /** swaps *this with the expression \a other. - * - */ - template - void swap(const DenseBase& other, - int = OtherDerived::ThisConstantIsPrivateInPlainObjectBase) - { - SwapWrapper(derived()).lazyAssign(other.derived()); - } - - /** swaps *this with the matrix or array \a other. - * - */ - template - void swap(PlainObjectBase& other) - { - SwapWrapper(derived()).lazyAssign(other.derived()); - } - - - inline const NestByValue nestByValue() const; - inline const ForceAlignedAccess forceAlignedAccess() const; - inline ForceAlignedAccess forceAlignedAccess(); - template inline const typename internal::conditional,Derived&>::type forceAlignedAccessIf() const; - template inline typename internal::conditional,Derived&>::type forceAlignedAccessIf(); - - Scalar sum() const; - Scalar mean() const; - Scalar trace() const; - - Scalar prod() const; - - typename internal::traits::Scalar minCoeff() const; - typename internal::traits::Scalar maxCoeff() const; - - template - typename internal::traits::Scalar minCoeff(IndexType* row, IndexType* col) const; - template - typename internal::traits::Scalar maxCoeff(IndexType* row, IndexType* col) const; - template - typename internal::traits::Scalar minCoeff(IndexType* index) const; - template - typename internal::traits::Scalar maxCoeff(IndexType* index) const; - - template - typename internal::result_of::Scalar)>::type - redux(const BinaryOp& func) const; - - template - void visit(Visitor& func) const; - - inline const WithFormat format(const IOFormat& fmt) const; - - /** \returns the unique coefficient of a 1x1 expression */ - CoeffReturnType value() const - { - EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) - eigen_assert(this->rows() == 1 && this->cols() == 1); - return derived().coeff(0,0); - } - - bool all(void) const; - bool any(void) const; - Index count() const; - - typedef VectorwiseOp RowwiseReturnType; - typedef const VectorwiseOp ConstRowwiseReturnType; - typedef VectorwiseOp ColwiseReturnType; - typedef const VectorwiseOp ConstColwiseReturnType; - - ConstRowwiseReturnType rowwise() const; - RowwiseReturnType rowwise(); - ConstColwiseReturnType colwise() const; - ColwiseReturnType colwise(); - - static const CwiseNullaryOp,Derived> Random(Index rows, Index cols); - static const CwiseNullaryOp,Derived> Random(Index size); - static const CwiseNullaryOp,Derived> Random(); - - template - const Select - select(const DenseBase& thenMatrix, - const DenseBase& elseMatrix) const; - - template - inline const Select - select(const DenseBase& thenMatrix, const typename ThenDerived::Scalar& elseScalar) const; - - template - inline const Select - select(const typename ElseDerived::Scalar& thenScalar, const DenseBase& elseMatrix) const; - - template RealScalar lpNorm() const; - - template - inline const Replicate replicate() const; - - typedef Replicate ReplicateReturnType; - inline const ReplicateReturnType replicate(Index rowFacor,Index colFactor) const; - - typedef Reverse ReverseReturnType; - typedef const Reverse ConstReverseReturnType; - ReverseReturnType reverse(); - ConstReverseReturnType reverse() const; - void reverseInPlace(); + EIGEN_DEVICE_FUNC RealViewReturnType realView(); + EIGEN_DEVICE_FUNC ConstRealViewReturnType realView() const; #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::DenseBase -# include "../plugins/BlockMethods.h" -# ifdef EIGEN_DENSEBASE_PLUGIN -# include EIGEN_DENSEBASE_PLUGIN -# endif +#define EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL +#define EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF(COND) +#define EIGEN_DOC_UNARY_ADDONS(X, Y) +#include "../plugins/CommonCwiseUnaryOps.inc" +#include "../plugins/BlockMethods.inc" +#include "../plugins/IndexedViewMethods.inc" +#include "../plugins/ReshapedMethods.inc" +#ifdef EIGEN_DENSEBASE_PLUGIN +#include EIGEN_DENSEBASE_PLUGIN +#endif #undef EIGEN_CURRENT_STORAGE_BASE_CLASS - -#ifdef EIGEN2_SUPPORT - - Block corner(CornerType type, Index cRows, Index cCols); - const Block corner(CornerType type, Index cRows, Index cCols) const; - template - Block corner(CornerType type); - template - const Block corner(CornerType type) const; - -#endif // EIGEN2_SUPPORT - - - // disable the use of evalTo for dense objects with a nice compilation error - template inline void evalTo(Dest& ) const - { - EIGEN_STATIC_ASSERT((internal::is_same::value),THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS); - } - - protected: - /** Default constructor. Do nothing. */ - DenseBase() - { - /* Just checks for self-consistency of the flags. - * Only do it when debugging Eigen, as this borders on paranoiac and could slow compilation down - */ +#undef EIGEN_DOC_BLOCK_ADDONS_NOT_INNER_PANEL +#undef EIGEN_DOC_BLOCK_ADDONS_INNER_PANEL_IF +#undef EIGEN_DOC_UNARY_ADDONS + + // disable the use of evalTo for dense objects with a nice compilation error + template + EIGEN_DEVICE_FUNC inline void evalTo(Dest&) const { + EIGEN_STATIC_ASSERT((internal::is_same::value), + THE_EVAL_EVALTO_FUNCTION_SHOULD_NEVER_BE_CALLED_FOR_DENSE_OBJECTS); + } + + protected: + EIGEN_DEFAULT_COPY_CONSTRUCTOR(DenseBase) + /** Default constructor. Do nothing. */ #ifdef EIGEN_INTERNAL_DEBUGGING - EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, int(IsRowMajor)) - && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, int(!IsRowMajor))), - INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION) + EIGEN_DEVICE_FUNC constexpr DenseBase() { + /* Just checks for self-consistency of the flags. + * Only do it when debugging Eigen, as this borders on paranoia and could slow compilation down + */ + EIGEN_STATIC_ASSERT( + (internal::check_implication(MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1, int(IsRowMajor)) && + internal::check_implication(MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1, int(!IsRowMajor))), + INVALID_STORAGE_ORDER_FOR_THIS_VECTOR_EXPRESSION) + } +#else + EIGEN_DEVICE_FUNC constexpr DenseBase() = default; #endif - } - private: - explicit DenseBase(int); - DenseBase(int,int); - template explicit DenseBase(const DenseBase&); + private: + EIGEN_DEVICE_FUNC explicit DenseBase(int); + EIGEN_DEVICE_FUNC DenseBase(int, int); + template + EIGEN_DEVICE_FUNC explicit DenseBase(const DenseBase&); }; -} // end namespace Eigen +/** Free-function swap. + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE + // Use forwarding references to capture all combinations of cv-qualified l+r-value cases. + std::enable_if_t>, std::decay_t>::value && + std::is_base_of>, std::decay_t>::value, + void> + swap(DerivedA&& a, DerivedB&& b) { + a.swap(b); +} + +} // end namespace Eigen -#endif // EIGEN_DENSEBASE_H +#endif // EIGEN_DENSEBASE_H diff --git a/inst/include/Eigen/src/Core/DenseCoeffsBase.h b/inst/include/Eigen/src/Core/DenseCoeffsBase.h index 3c890f21..377df574 100644 --- a/inst/include/Eigen/src/Core/DenseCoeffsBase.h +++ b/inst/include/Eigen/src/Core/DenseCoeffsBase.h @@ -10,745 +10,559 @@ #ifndef EIGEN_DENSECOEFFSBASE_H #define EIGEN_DENSECOEFFSBASE_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { namespace internal { -template struct add_const_on_value_type_if_arithmetic -{ - typedef typename conditional::value, T, typename add_const_on_value_type::type>::type type; +template +struct add_const_on_value_type_if_arithmetic { + typedef std::conditional_t::value, T, add_const_on_value_type_t> type; }; -} +} // namespace internal /** \brief Base class providing read-only coefficient access to matrices and arrays. - * \ingroup Core_Module - * \tparam Derived Type of the derived class - * \tparam #ReadOnlyAccessors Constant indicating read-only access - * - * This class defines the \c operator() \c const function and friends, which can be used to read specific - * entries of a matrix or array. - * - * \sa DenseCoeffsBase, DenseCoeffsBase, - * \ref TopicClassHierarchy - */ -template -class DenseCoeffsBase : public EigenBase -{ - public: - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - - // Explanation for this CoeffReturnType typedef. - // - This is the return type of the coeff() method. - // - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references - // to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value). - // - The is_artihmetic check is required since "const int", "const double", etc. will cause warnings on some systems - // while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is - // not possible, since the underlying expressions might not offer a valid address the reference could be referring to. - typedef typename internal::conditional::Flags&LvalueBit), - const Scalar&, - typename internal::conditional::value, Scalar, const Scalar>::type - >::type CoeffReturnType; - - typedef typename internal::add_const_on_value_type_if_arithmetic< - typename internal::packet_traits::type - >::type PacketReturnType; - - typedef EigenBase Base; - using Base::rows; - using Base::cols; - using Base::size; - using Base::derived; - - EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const - { - return int(Derived::RowsAtCompileTime) == 1 ? 0 - : int(Derived::ColsAtCompileTime) == 1 ? inner - : int(Derived::Flags)&RowMajorBit ? outer - : inner; - } - - EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const - { - return int(Derived::ColsAtCompileTime) == 1 ? 0 - : int(Derived::RowsAtCompileTime) == 1 ? inner - : int(Derived::Flags)&RowMajorBit ? inner - : outer; - } - - /** Short version: don't use this function, use - * \link operator()(Index,Index) const \endlink instead. - * - * Long version: this function is similar to - * \link operator()(Index,Index) const \endlink, but without the assertion. - * Use this for limiting the performance cost of debugging code when doing - * repeated coefficient access. Only use this when it is guaranteed that the - * parameters \a row and \a col are in range. - * - * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this - * function equivalent to \link operator()(Index,Index) const \endlink. - * - * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const - */ - EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - return derived().coeff(row, col); - } - - EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const - { - return coeff(rowIndexByOuterInner(outer, inner), - colIndexByOuterInner(outer, inner)); - } - - /** \returns the coefficient at given the given row and column. - * - * \sa operator()(Index,Index), operator[](Index) - */ - EIGEN_STRONG_INLINE CoeffReturnType operator()(Index row, Index col) const - { - eigen_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - return derived().coeff(row, col); - } - - /** Short version: don't use this function, use - * \link operator[](Index) const \endlink instead. - * - * Long version: this function is similar to - * \link operator[](Index) const \endlink, but without the assertion. - * Use this for limiting the performance cost of debugging code when doing - * repeated coefficient access. Only use this when it is guaranteed that the - * parameter \a index is in range. - * - * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this - * function equivalent to \link operator[](Index) const \endlink. - * - * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const - */ - - EIGEN_STRONG_INLINE CoeffReturnType - coeff(Index index) const - { - eigen_internal_assert(index >= 0 && index < size()); - return derived().coeff(index); - } - - - /** \returns the coefficient at given index. - * - * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. - * - * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const, - * z() const, w() const - */ - - EIGEN_STRONG_INLINE CoeffReturnType - operator[](Index index) const - { - #ifndef EIGEN2_SUPPORT - EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, - THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) - #endif - eigen_assert(index >= 0 && index < size()); - return derived().coeff(index); - } - - /** \returns the coefficient at given index. - * - * This is synonymous to operator[](Index) const. - * - * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. - * - * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const, - * z() const, w() const - */ - - EIGEN_STRONG_INLINE CoeffReturnType - operator()(Index index) const - { - eigen_assert(index >= 0 && index < size()); - return derived().coeff(index); - } - - /** equivalent to operator[](0). */ - - EIGEN_STRONG_INLINE CoeffReturnType - x() const { return (*this)[0]; } - - /** equivalent to operator[](1). */ - - EIGEN_STRONG_INLINE CoeffReturnType - y() const { return (*this)[1]; } - - /** equivalent to operator[](2). */ - - EIGEN_STRONG_INLINE CoeffReturnType - z() const { return (*this)[2]; } - - /** equivalent to operator[](3). */ - - EIGEN_STRONG_INLINE CoeffReturnType - w() const { return (*this)[3]; } - - /** \internal - * \returns the packet of coefficients starting at the given row and column. It is your responsibility - * to ensure that a packet really starts there. This method is only available on expressions having the - * PacketAccessBit. - * - * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select - * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets - * starting at an address which is a multiple of the packet size. - */ - - template - EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - return derived().template packet(row,col); - } - - - /** \internal */ - template - EIGEN_STRONG_INLINE PacketReturnType packetByOuterInner(Index outer, Index inner) const - { - return packet(rowIndexByOuterInner(outer, inner), - colIndexByOuterInner(outer, inner)); - } - - /** \internal - * \returns the packet of coefficients starting at the given index. It is your responsibility - * to ensure that a packet really starts there. This method is only available on expressions having the - * PacketAccessBit and the LinearAccessBit. - * - * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select - * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets - * starting at an address which is a multiple of the packet size. - */ - - template - EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const - { - eigen_internal_assert(index >= 0 && index < size()); - return derived().template packet(index); - } - - protected: - // explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase. - // But some methods are only available in the DirectAccess case. - // So we add dummy methods here with these names, so that "using... " doesn't fail. - // It's not private so that the child class DenseBase can access them, and it's not public - // either since it's an implementation detail, so has to be protected. - void coeffRef(); - void coeffRefByOuterInner(); - void writePacket(); - void writePacketByOuterInner(); - void copyCoeff(); - void copyCoeffByOuterInner(); - void copyPacket(); - void copyPacketByOuterInner(); - void stride(); - void innerStride(); - void outerStride(); - void rowStride(); - void colStride(); + * \ingroup Core_Module + * \tparam Derived Type of the derived class + * + * \note #ReadOnlyAccessors Constant indicating read-only access + * + * This class defines the \c operator() \c const function and friends, which can be used to read specific + * entries of a matrix or array. + * + * \sa DenseCoeffsBase, DenseCoeffsBase, + * \ref TopicClassHierarchy + */ +template +class DenseCoeffsBase : public EigenBase { + public: + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::packet_traits::type PacketScalar; + + // Explanation for this CoeffReturnType typedef. + // - This is the return type of the coeff() method. + // - The LvalueBit means exactly that we can offer a coeffRef() method, which means exactly that we can get references + // to coeffs, which means exactly that we can have coeff() return a const reference (as opposed to returning a value). + // - The DirectAccessBit means exactly that the underlying data of coefficients can be directly accessed as a plain + // strided array, which means exactly that the underlying data of coefficients does exist in memory, which means + // exactly that the coefficients is const-referencable, which means exactly that we can have coeff() return a const + // reference. For example, Map have DirectAccessBit but not LvalueBit, so that Map.coeff() + // does points to a const Scalar& which exists in memory, while does not allow coeffRef() as it would not provide a + // lvalue. Notice that DirectAccessBit and LvalueBit are mutually orthogonal. + // - The is_arithmetic check is required since "const int", "const double", etc. will cause warnings on some systems + // while the declaration of "const T", where T is a non arithmetic type does not. Always returning "const Scalar&" is + // not possible, since the underlying expressions might not offer a valid address the reference could be referring to. + typedef std::conditional_t::Flags&(LvalueBit | DirectAccessBit)), const Scalar&, + std::conditional_t::value, Scalar, const Scalar>> + CoeffReturnType; + + typedef typename internal::add_const_on_value_type_if_arithmetic::type>::type + PacketReturnType; + + typedef EigenBase Base; + using Base::cols; + using Base::derived; + using Base::rows; + using Base::size; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index rowIndexByOuterInner(Index outer, Index inner) const { + return int(Derived::RowsAtCompileTime) == 1 ? 0 + : int(Derived::ColsAtCompileTime) == 1 ? inner + : int(Derived::Flags) & RowMajorBit ? outer + : inner; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index colIndexByOuterInner(Index outer, Index inner) const { + return int(Derived::ColsAtCompileTime) == 1 ? 0 + : int(Derived::RowsAtCompileTime) == 1 ? inner + : int(Derived::Flags) & RowMajorBit ? inner + : outer; + } + + /** Short version: don't use this function, use + * \link operator()(Index,Index) const \endlink instead. + * + * Long version: this function is similar to + * \link operator()(Index,Index) const \endlink, but without the assertion. + * Use this for limiting the performance cost of debugging code when doing + * repeated coefficient access. Only use this when it is guaranteed that the + * parameters \a row and \a col are in range. + * + * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this + * function equivalent to \link operator()(Index,Index) const \endlink. + * + * \sa operator()(Index,Index) const, coeffRef(Index,Index), coeff(Index) const + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index row, Index col) const { + eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); + return internal::evaluator(derived()).coeff(row, col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeffByOuterInner(Index outer, Index inner) const { + return coeff(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner)); + } + + /** \returns the coefficient at given the given row and column. + * + * \sa operator()(Index,Index), operator[](Index) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator()(Index row, Index col) const { + eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); + return coeff(row, col); + } + + /** Short version: don't use this function, use + * \link operator[](Index) const \endlink instead. + * + * Long version: this function is similar to + * \link operator[](Index) const \endlink, but without the assertion. + * Use this for limiting the performance cost of debugging code when doing + * repeated coefficient access. Only use this when it is guaranteed that the + * parameter \a index is in range. + * + * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this + * function equivalent to \link operator[](Index) const \endlink. + * + * \sa operator[](Index) const, coeffRef(Index), coeff(Index,Index) const + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType coeff(Index index) const { + EIGEN_STATIC_ASSERT(internal::evaluator::Flags & LinearAccessBit, + THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS) + eigen_internal_assert(index >= 0 && index < size()); + return internal::evaluator(derived()).coeff(index); + } + + /** \returns the coefficient at given index. + * + * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. + * + * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const, + * z() const, w() const + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator[](Index index) const { + EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, + THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) + eigen_assert(index >= 0 && index < size()); + return coeff(index); + } + + /** \returns the coefficient at given index. + * + * This is synonymous to operator[](Index) const. + * + * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. + * + * \sa operator[](Index), operator()(Index,Index) const, x() const, y() const, + * z() const, w() const + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType operator()(Index index) const { + eigen_assert(index >= 0 && index < size()); + return coeff(index); + } + + /** equivalent to operator[](0). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType x() const { return (*this)[0]; } + + /** equivalent to operator[](1). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType y() const { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 2, OUT_OF_RANGE_ACCESS); + return (*this)[1]; + } + + /** equivalent to operator[](2). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType z() const { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 3, OUT_OF_RANGE_ACCESS); + return (*this)[2]; + } + + /** equivalent to operator[](3). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr CoeffReturnType w() const { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 4, OUT_OF_RANGE_ACCESS); + return (*this)[3]; + } + + /** \internal + * \returns the packet of coefficients starting at the given row and column. It is your responsibility + * to ensure that a packet really starts there. This method is only available on expressions having the + * PacketAccessBit. + * + * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select + * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets + * starting at an address which is a multiple of the packet size. + */ + + template + EIGEN_STRONG_INLINE PacketReturnType packet(Index row, Index col) const { + typedef typename internal::packet_traits::type DefaultPacketType; + eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); + return internal::evaluator(derived()).template packet(row, col); + } + + /** \internal */ + template + EIGEN_STRONG_INLINE PacketReturnType packetByOuterInner(Index outer, Index inner) const { + return packet(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner)); + } + + /** \internal + * \returns the packet of coefficients starting at the given index. It is your responsibility + * to ensure that a packet really starts there. This method is only available on expressions having the + * PacketAccessBit and the LinearAccessBit. + * + * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select + * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets + * starting at an address which is a multiple of the packet size. + */ + + template + EIGEN_STRONG_INLINE PacketReturnType packet(Index index) const { + EIGEN_STATIC_ASSERT(internal::evaluator::Flags & LinearAccessBit, + THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS) + typedef typename internal::packet_traits::type DefaultPacketType; + eigen_internal_assert(index >= 0 && index < size()); + return internal::evaluator(derived()).template packet(index); + } + + protected: + // explanation: DenseBase is doing "using ..." on the methods from DenseCoeffsBase. + // But some methods are only available in the DirectAccess case. + // So we add dummy methods here with these names, so that "using... " doesn't fail. + // It's not private so that the child class DenseBase can access them, and it's not public + // either since it's an implementation detail, so has to be protected. + void coeffRef(); + void coeffRefByOuterInner(); + void writePacket(); + void writePacketByOuterInner(); + void copyCoeff(); + void copyCoeffByOuterInner(); + void copyPacket(); + void copyPacketByOuterInner(); + void stride(); + void innerStride(); + void outerStride(); + void rowStride(); + void colStride(); }; /** \brief Base class providing read/write coefficient access to matrices and arrays. - * \ingroup Core_Module - * \tparam Derived Type of the derived class - * \tparam #WriteAccessors Constant indicating read/write access - * - * This class defines the non-const \c operator() function and friends, which can be used to write specific - * entries of a matrix or array. This class inherits DenseCoeffsBase which - * defines the const variant for reading specific entries. - * - * \sa DenseCoeffsBase, \ref TopicClassHierarchy - */ -template -class DenseCoeffsBase : public DenseCoeffsBase -{ - public: - - typedef DenseCoeffsBase Base; - - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - - using Base::coeff; - using Base::rows; - using Base::cols; - using Base::size; - using Base::derived; - using Base::rowIndexByOuterInner; - using Base::colIndexByOuterInner; - using Base::operator[]; - using Base::operator(); - using Base::x; - using Base::y; - using Base::z; - using Base::w; - - /** Short version: don't use this function, use - * \link operator()(Index,Index) \endlink instead. - * - * Long version: this function is similar to - * \link operator()(Index,Index) \endlink, but without the assertion. - * Use this for limiting the performance cost of debugging code when doing - * repeated coefficient access. Only use this when it is guaranteed that the - * parameters \a row and \a col are in range. - * - * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this - * function equivalent to \link operator()(Index,Index) \endlink. - * - * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index) - */ - EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - return derived().coeffRef(row, col); - } - - EIGEN_STRONG_INLINE Scalar& - coeffRefByOuterInner(Index outer, Index inner) - { - return coeffRef(rowIndexByOuterInner(outer, inner), - colIndexByOuterInner(outer, inner)); - } - - /** \returns a reference to the coefficient at given the given row and column. - * - * \sa operator[](Index) - */ - - EIGEN_STRONG_INLINE Scalar& - operator()(Index row, Index col) - { - eigen_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - return derived().coeffRef(row, col); - } - - - /** Short version: don't use this function, use - * \link operator[](Index) \endlink instead. - * - * Long version: this function is similar to - * \link operator[](Index) \endlink, but without the assertion. - * Use this for limiting the performance cost of debugging code when doing - * repeated coefficient access. Only use this when it is guaranteed that the - * parameters \a row and \a col are in range. - * - * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this - * function equivalent to \link operator[](Index) \endlink. - * - * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index) - */ - - EIGEN_STRONG_INLINE Scalar& - coeffRef(Index index) - { - eigen_internal_assert(index >= 0 && index < size()); - return derived().coeffRef(index); - } - - /** \returns a reference to the coefficient at given index. - * - * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. - * - * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() - */ - - EIGEN_STRONG_INLINE Scalar& - operator[](Index index) - { - #ifndef EIGEN2_SUPPORT - EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, - THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) - #endif - eigen_assert(index >= 0 && index < size()); - return derived().coeffRef(index); - } - - /** \returns a reference to the coefficient at given index. - * - * This is synonymous to operator[](Index). - * - * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. - * - * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() - */ - - EIGEN_STRONG_INLINE Scalar& - operator()(Index index) - { - eigen_assert(index >= 0 && index < size()); - return derived().coeffRef(index); - } - - /** equivalent to operator[](0). */ - - EIGEN_STRONG_INLINE Scalar& - x() { return (*this)[0]; } - - /** equivalent to operator[](1). */ - - EIGEN_STRONG_INLINE Scalar& - y() { return (*this)[1]; } - - /** equivalent to operator[](2). */ - - EIGEN_STRONG_INLINE Scalar& - z() { return (*this)[2]; } - - /** equivalent to operator[](3). */ - - EIGEN_STRONG_INLINE Scalar& - w() { return (*this)[3]; } - - /** \internal - * Stores the given packet of coefficients, at the given row and column of this expression. It is your responsibility - * to ensure that a packet really starts there. This method is only available on expressions having the - * PacketAccessBit. - * - * The \a LoadMode parameter may have the value \a #Aligned or \a #Unaligned. Its effect is to select - * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets - * starting at an address which is a multiple of the packet size. - */ - - template - EIGEN_STRONG_INLINE void writePacket - (Index row, Index col, const typename internal::packet_traits::type& val) - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - derived().template writePacket(row,col,val); - } - - - /** \internal */ - template - EIGEN_STRONG_INLINE void writePacketByOuterInner - (Index outer, Index inner, const typename internal::packet_traits::type& val) - { - writePacket(rowIndexByOuterInner(outer, inner), - colIndexByOuterInner(outer, inner), - val); - } - - /** \internal - * Stores the given packet of coefficients, at the given index in this expression. It is your responsibility - * to ensure that a packet really starts there. This method is only available on expressions having the - * PacketAccessBit and the LinearAccessBit. - * - * The \a LoadMode parameter may have the value \a Aligned or \a Unaligned. Its effect is to select - * the appropriate vectorization instruction. Aligned access is faster, but is only possible for packets - * starting at an address which is a multiple of the packet size. - */ - template - EIGEN_STRONG_INLINE void writePacket - (Index index, const typename internal::packet_traits::type& val) - { - eigen_internal_assert(index >= 0 && index < size()); - derived().template writePacket(index,val); - } - -#ifndef EIGEN_PARSED_BY_DOXYGEN - - /** \internal Copies the coefficient at position (row,col) of other into *this. - * - * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code - * with usual assignments. - * - * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox. - */ - - template - EIGEN_STRONG_INLINE void copyCoeff(Index row, Index col, const DenseBase& other) - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - derived().coeffRef(row, col) = other.derived().coeff(row, col); - } - - /** \internal Copies the coefficient at the given index of other into *this. - * - * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code - * with usual assignments. - * - * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox. - */ - - template - EIGEN_STRONG_INLINE void copyCoeff(Index index, const DenseBase& other) - { - eigen_internal_assert(index >= 0 && index < size()); - derived().coeffRef(index) = other.derived().coeff(index); - } - - - template - EIGEN_STRONG_INLINE void copyCoeffByOuterInner(Index outer, Index inner, const DenseBase& other) - { - const Index row = rowIndexByOuterInner(outer,inner); - const Index col = colIndexByOuterInner(outer,inner); - // derived() is important here: copyCoeff() may be reimplemented in Derived! - derived().copyCoeff(row, col, other); - } - - /** \internal Copies the packet at position (row,col) of other into *this. - * - * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code - * with usual assignments. - * - * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox. - */ - - template - EIGEN_STRONG_INLINE void copyPacket(Index row, Index col, const DenseBase& other) - { - eigen_internal_assert(row >= 0 && row < rows() - && col >= 0 && col < cols()); - derived().template writePacket(row, col, - other.derived().template packet(row, col)); - } - - /** \internal Copies the packet at the given index of other into *this. - * - * This method is overridden in SwapWrapper, allowing swap() assignments to share 99% of their code - * with usual assignments. - * - * Outside of this internal usage, this method has probably no usefulness. It is hidden in the public API dox. - */ - - template - EIGEN_STRONG_INLINE void copyPacket(Index index, const DenseBase& other) - { - eigen_internal_assert(index >= 0 && index < size()); - derived().template writePacket(index, - other.derived().template packet(index)); - } - - /** \internal */ - template - EIGEN_STRONG_INLINE void copyPacketByOuterInner(Index outer, Index inner, const DenseBase& other) - { - const Index row = rowIndexByOuterInner(outer,inner); - const Index col = colIndexByOuterInner(outer,inner); - // derived() is important here: copyCoeff() may be reimplemented in Derived! - derived().template copyPacket< OtherDerived, StoreMode, LoadMode>(row, col, other); - } -#endif + * \ingroup Core_Module + * \tparam Derived Type of the derived class + * + * \note #WriteAccessors Constant indicating read/write access + * + * This class defines the non-const \c operator() function and friends, which can be used to write specific + * entries of a matrix or array. This class inherits DenseCoeffsBase which + * defines the const variant for reading specific entries. + * + * \sa DenseCoeffsBase, \ref TopicClassHierarchy + */ +template +class DenseCoeffsBase : public DenseCoeffsBase { + public: + typedef DenseCoeffsBase Base; + + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::packet_traits::type PacketScalar; + typedef typename NumTraits::Real RealScalar; + + using Base::coeff; + using Base::colIndexByOuterInner; + using Base::cols; + using Base::derived; + using Base::rowIndexByOuterInner; + using Base::rows; + using Base::size; + using Base::operator[]; + using Base::operator(); + using Base::w; + using Base::x; + using Base::y; + using Base::z; + + /** Short version: don't use this function, use + * \link operator()(Index,Index) \endlink instead. + * + * Long version: this function is similar to + * \link operator()(Index,Index) \endlink, but without the assertion. + * Use this for limiting the performance cost of debugging code when doing + * repeated coefficient access. Only use this when it is guaranteed that the + * parameters \a row and \a col are in range. + * + * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this + * function equivalent to \link operator()(Index,Index) \endlink. + * + * \sa operator()(Index,Index), coeff(Index, Index) const, coeffRef(Index) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index row, Index col) { + eigen_internal_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); + return internal::evaluator(derived()).coeffRef(row, col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRefByOuterInner(Index outer, Index inner) { + return coeffRef(rowIndexByOuterInner(outer, inner), colIndexByOuterInner(outer, inner)); + } + + /** \returns a reference to the coefficient at given the given row and column. + * + * \sa operator[](Index) + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator()(Index row, Index col) { + eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); + return coeffRef(row, col); + } + + /** Short version: don't use this function, use + * \link operator[](Index) \endlink instead. + * + * Long version: this function is similar to + * \link operator[](Index) \endlink, but without the assertion. + * Use this for limiting the performance cost of debugging code when doing + * repeated coefficient access. Only use this when it is guaranteed that the + * parameters \a row and \a col are in range. + * + * If EIGEN_INTERNAL_DEBUGGING is defined, an assertion will be made, making this + * function equivalent to \link operator[](Index) \endlink. + * + * \sa operator[](Index), coeff(Index) const, coeffRef(Index,Index) + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) { + EIGEN_STATIC_ASSERT(internal::evaluator::Flags & LinearAccessBit, + THIS_COEFFICIENT_ACCESSOR_TAKING_ONE_ACCESS_IS_ONLY_FOR_EXPRESSIONS_ALLOWING_LINEAR_ACCESS) + eigen_internal_assert(index >= 0 && index < size()); + return internal::evaluator(derived()).coeffRef(index); + } + + /** \returns a reference to the coefficient at given index. + * + * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. + * + * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator[](Index index) { + EIGEN_STATIC_ASSERT(Derived::IsVectorAtCompileTime, + THE_BRACKET_OPERATOR_IS_ONLY_FOR_VECTORS__USE_THE_PARENTHESIS_OPERATOR_INSTEAD) + eigen_assert(index >= 0 && index < size()); + return coeffRef(index); + } + + /** \returns a reference to the coefficient at given index. + * + * This is synonymous to operator[](Index). + * + * This method is allowed only for vector expressions, and for matrix expressions having the LinearAccessBit. + * + * \sa operator[](Index) const, operator()(Index,Index), x(), y(), z(), w() + */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& operator()(Index index) { + eigen_assert(index >= 0 && index < size()); + return coeffRef(index); + } + + /** equivalent to operator[](0). */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& x() { return (*this)[0]; } + + /** equivalent to operator[](1). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& y() { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 2, OUT_OF_RANGE_ACCESS); + return (*this)[1]; + } + + /** equivalent to operator[](2). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& z() { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 3, OUT_OF_RANGE_ACCESS); + return (*this)[2]; + } + + /** equivalent to operator[](3). */ + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& w() { + EIGEN_STATIC_ASSERT(Derived::SizeAtCompileTime == -1 || Derived::SizeAtCompileTime >= 4, OUT_OF_RANGE_ACCESS); + return (*this)[3]; + } }; /** \brief Base class providing direct read-only coefficient access to matrices and arrays. - * \ingroup Core_Module - * \tparam Derived Type of the derived class - * \tparam #DirectAccessors Constant indicating direct access - * - * This class defines functions to work with strides which can be used to access entries directly. This class - * inherits DenseCoeffsBase which defines functions to access entries read-only using - * \c operator() . - * - * \sa \ref TopicClassHierarchy - */ -template -class DenseCoeffsBase : public DenseCoeffsBase -{ - public: - - typedef DenseCoeffsBase Base; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - - using Base::rows; - using Base::cols; - using Base::size; - using Base::derived; - - /** \returns the pointer increment between two consecutive elements within a slice in the inner direction. - * - * \sa outerStride(), rowStride(), colStride() - */ - inline Index innerStride() const - { - return derived().innerStride(); - } - - /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns - * in a column-major matrix). - * - * \sa innerStride(), rowStride(), colStride() - */ - inline Index outerStride() const - { - return derived().outerStride(); - } - - // FIXME shall we remove it ? - inline Index stride() const - { - return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); - } - - /** \returns the pointer increment between two consecutive rows. - * - * \sa innerStride(), outerStride(), colStride() - */ - inline Index rowStride() const - { - return Derived::IsRowMajor ? outerStride() : innerStride(); - } - - /** \returns the pointer increment between two consecutive columns. - * - * \sa innerStride(), outerStride(), rowStride() - */ - inline Index colStride() const - { - return Derived::IsRowMajor ? innerStride() : outerStride(); - } + * \ingroup Core_Module + * \tparam Derived Type of the derived class + * + * \note #DirectAccessors Constant indicating direct access + * + * This class defines functions to work with strides which can be used to access entries directly. This class + * inherits DenseCoeffsBase which defines functions to access entries read-only using + * \c operator() . + * + * \sa \blank \ref TopicClassHierarchy + */ +template +class DenseCoeffsBase : public DenseCoeffsBase { + public: + typedef DenseCoeffsBase Base; + typedef typename internal::traits::Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + + using Base::cols; + using Base::derived; + using Base::rows; + using Base::size; + + /** \returns the pointer increment between two consecutive elements within a slice in the inner direction. + * + * \sa outerStride(), rowStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index innerStride() const { return derived().innerStride(); } + + /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns + * in a column-major matrix). + * + * \sa innerStride(), rowStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index outerStride() const { return derived().outerStride(); } + + // FIXME shall we remove it ? + constexpr Index stride() const { return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); } + + /** \returns the pointer increment between two consecutive rows. + * + * \sa innerStride(), outerStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index rowStride() const { return Derived::IsRowMajor ? outerStride() : innerStride(); } + + /** \returns the pointer increment between two consecutive columns. + * + * \sa innerStride(), outerStride(), rowStride() + */ + EIGEN_DEVICE_FUNC constexpr Index colStride() const { return Derived::IsRowMajor ? innerStride() : outerStride(); } }; /** \brief Base class providing direct read/write coefficient access to matrices and arrays. - * \ingroup Core_Module - * \tparam Derived Type of the derived class - * \tparam #DirectWriteAccessors Constant indicating direct access - * - * This class defines functions to work with strides which can be used to access entries directly. This class - * inherits DenseCoeffsBase which defines functions to access entries read/write using - * \c operator(). - * - * \sa \ref TopicClassHierarchy - */ -template -class DenseCoeffsBase - : public DenseCoeffsBase -{ - public: - - typedef DenseCoeffsBase Base; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename NumTraits::Real RealScalar; - - using Base::rows; - using Base::cols; - using Base::size; - using Base::derived; - - /** \returns the pointer increment between two consecutive elements within a slice in the inner direction. - * - * \sa outerStride(), rowStride(), colStride() - */ - inline Index innerStride() const - { - return derived().innerStride(); - } - - /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns - * in a column-major matrix). - * - * \sa innerStride(), rowStride(), colStride() - */ - inline Index outerStride() const - { - return derived().outerStride(); - } - - // FIXME shall we remove it ? - inline Index stride() const - { - return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); - } - - /** \returns the pointer increment between two consecutive rows. - * - * \sa innerStride(), outerStride(), colStride() - */ - inline Index rowStride() const - { - return Derived::IsRowMajor ? outerStride() : innerStride(); - } - - /** \returns the pointer increment between two consecutive columns. - * - * \sa innerStride(), outerStride(), rowStride() - */ - inline Index colStride() const - { - return Derived::IsRowMajor ? innerStride() : outerStride(); - } + * \ingroup Core_Module + * \tparam Derived Type of the derived class + * + * \note #DirectWriteAccessors Constant indicating direct access + * + * This class defines functions to work with strides which can be used to access entries directly. This class + * inherits DenseCoeffsBase which defines functions to access entries read/write using + * \c operator(). + * + * \sa \blank \ref TopicClassHierarchy + */ +template +class DenseCoeffsBase : public DenseCoeffsBase { + public: + typedef DenseCoeffsBase Base; + typedef typename internal::traits::Scalar Scalar; + typedef typename NumTraits::Real RealScalar; + + using Base::cols; + using Base::derived; + using Base::rows; + using Base::size; + + /** \returns the pointer increment between two consecutive elements within a slice in the inner direction. + * + * \sa outerStride(), rowStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return derived().innerStride(); } + + /** \returns the pointer increment between two consecutive inner slices (for example, between two consecutive columns + * in a column-major matrix). + * + * \sa innerStride(), rowStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return derived().outerStride(); } + + // FIXME shall we remove it ? + constexpr Index stride() const noexcept { return Derived::IsVectorAtCompileTime ? innerStride() : outerStride(); } + + /** \returns the pointer increment between two consecutive rows. + * + * \sa innerStride(), outerStride(), colStride() + */ + EIGEN_DEVICE_FUNC constexpr Index rowStride() const noexcept { + return Derived::IsRowMajor ? outerStride() : innerStride(); + } + + /** \returns the pointer increment between two consecutive columns. + * + * \sa innerStride(), outerStride(), rowStride() + */ + EIGEN_DEVICE_FUNC constexpr Index colStride() const noexcept { + return Derived::IsRowMajor ? innerStride() : outerStride(); + } }; namespace internal { -template -struct first_aligned_impl -{ - static inline typename Derived::Index run(const Derived&) - { return 0; } +template +struct first_aligned_impl { + static constexpr Index run(const Derived&) noexcept { return 0; } }; -template -struct first_aligned_impl -{ - static inline typename Derived::Index run(const Derived& m) - { - return internal::first_aligned(&m.const_cast_derived().coeffRef(0,0), m.size()); - } +template +struct first_aligned_impl { + static inline Index run(const Derived& m) { return internal::first_aligned(m.data(), m.size()); } }; -/** \internal \returns the index of the first element of the array that is well aligned for vectorization. - * - * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more - * documentation. - */ -template -static inline typename Derived::Index first_aligned(const Derived& m) -{ - return first_aligned_impl - - ::run(m); +/** \internal \returns the index of the first element of the array stored by \a m that is properly aligned with respect + * to \a Alignment for vectorization. + * + * \tparam Alignment requested alignment in Bytes. + * + * There is also the variant first_aligned(const Scalar*, Integer) defined in Memory.h. See it for more + * documentation. + */ +template +static inline Index first_aligned(const DenseBase& m) { + enum { ReturnZero = (int(evaluator::Alignment) >= Alignment) || !(Derived::Flags & DirectAccessBit) }; + return first_aligned_impl::run(m.derived()); +} + +template +static inline Index first_default_aligned(const DenseBase& m) { + typedef typename Derived::Scalar Scalar; + typedef typename packet_traits::type DefaultPacketType; + return internal::first_aligned::alignment), Derived>(m); } -template::ret> -struct inner_stride_at_compile_time -{ +template ::ret> +struct inner_stride_at_compile_time { enum { ret = traits::InnerStrideAtCompileTime }; }; -template -struct inner_stride_at_compile_time -{ +template +struct inner_stride_at_compile_time { enum { ret = 0 }; }; -template::ret> -struct outer_stride_at_compile_time -{ +template ::ret> +struct outer_stride_at_compile_time { enum { ret = traits::OuterStrideAtCompileTime }; }; -template -struct outer_stride_at_compile_time -{ +template +struct outer_stride_at_compile_time { enum { ret = 0 }; }; -} // end namespace internal +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_DENSECOEFFSBASE_H +#endif // EIGEN_DENSECOEFFSBASE_H diff --git a/inst/include/Eigen/src/Core/DenseStorage.h b/inst/include/Eigen/src/Core/DenseStorage.h index 568493cb..45c8779a 100644 --- a/inst/include/Eigen/src/Core/DenseStorage.h +++ b/inst/include/Eigen/src/Core/DenseStorage.h @@ -3,7 +3,7 @@ // // Copyright (C) 2008 Gael Guennebaud // Copyright (C) 2006-2009 Benoit Jacob -// Copyright (C) 2010 Hauke Heibel +// Copyright (C) 2010-2013 Hauke Heibel // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed @@ -13,422 +13,561 @@ #define EIGEN_MATRIXSTORAGE_H #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN - #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN EIGEN_DENSE_STORAGE_CTOR_PLUGIN; +#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) \ + X; \ + EIGEN_DENSE_STORAGE_CTOR_PLUGIN; #else - #define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN +#define EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(X) #endif +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { namespace internal { -struct constructor_without_unaligned_array_assert {}; +#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT) +#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment) +#else +#define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment) \ + eigen_assert((is_constant_evaluated() || (std::uintptr_t(array) % Alignment == 0)) && \ + "this assertion is explained here: " \ + "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \ + " **** READ THIS WEB PAGE !!! ****"); +#endif -template void check_static_allocation_size() -{ - // if EIGEN_STACK_ALLOCATION_LIMIT is defined to 0, then no limit - #if EIGEN_STACK_ALLOCATION_LIMIT - EIGEN_STATIC_ASSERT(Size * sizeof(T) <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG); - #endif -} +#if EIGEN_STACK_ALLOCATION_LIMIT +#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X) \ + EIGEN_STATIC_ASSERT(X <= EIGEN_STACK_ALLOCATION_LIMIT, OBJECT_ALLOCATED_ON_STACK_IS_TOO_BIG) +#else +#define EIGEN_MAKE_STACK_ALLOCATION_ASSERT(X) +#endif /** \internal - * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned: - * to 16 bytes boundary if the total size is a multiple of 16 bytes. - */ -template -struct plain_array -{ - T array[Size]; - - plain_array() - { - check_static_allocation_size(); - } + * Static array. If the MatrixOrArrayOptions require auto-alignment, the array will be automatically aligned: + * to 16 bytes boundary if the total size is a multiple of 16 bytes. + */ - plain_array(constructor_without_unaligned_array_assert) - { - check_static_allocation_size(); +template ::value> +struct plain_array { + EIGEN_ALIGN_TO_BOUNDARY(Alignment) T array[Size]; +#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() = default; +#else + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() { + EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(Alignment) + EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T)) } +#endif }; -#if defined(EIGEN_DISABLE_UNALIGNED_ARRAY_ASSERT) - #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) -#elif EIGEN_GNUC_AT_LEAST(4,7) - // GCC 4.7 is too aggressive in its optimizations and remove the alignement test based on the fact the array is declared to be aligned. - // See this bug report: http://gcc.gnu.org/bugzilla/show_bug.cgi?id=53900 - // Hiding the origin of the array pointer behind a function argument seems to do the trick even if the function is inlined: - template - EIGEN_ALWAYS_INLINE PtrType eigen_unaligned_array_assert_workaround_gcc47(PtrType array) { return array; } - #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \ - eigen_assert((reinterpret_cast(eigen_unaligned_array_assert_workaround_gcc47(array)) & sizemask) == 0 \ - && "this assertion is explained here: " \ - "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \ - " **** READ THIS WEB PAGE !!! ****"); +template +struct plain_array { + // on some 32-bit platforms, stack-allocated arrays are aligned to 4 bytes, not the preferred alignment of T + EIGEN_ALIGN_TO_BOUNDARY(alignof(T)) T array[Size]; +#if defined(EIGEN_NO_DEBUG) || defined(EIGEN_TESTING_PLAINOBJECT_CTOR) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() = default; #else - #define EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(sizemask) \ - eigen_assert((reinterpret_cast(array) & sizemask) == 0 \ - && "this assertion is explained here: " \ - "http://eigen.tuxfamily.org/dox-devel/group__TopicUnalignedArrayAssert.html" \ - " **** READ THIS WEB PAGE !!! ****"); + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr plain_array() { EIGEN_MAKE_STACK_ALLOCATION_ASSERT(Size * sizeof(T)) } #endif +}; -template -struct plain_array -{ - EIGEN_USER_ALIGN16 T array[Size]; +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap_plain_array(plain_array& a, + plain_array& b, + Index a_size, Index b_size) { + Index common_size = numext::mini(a_size, b_size); + std::swap_ranges(a.array, a.array + common_size, b.array); + if (a_size > b_size) + smart_copy(a.array + common_size, a.array + a_size, b.array + common_size); + else if (b_size > a_size) + smart_copy(b.array + common_size, b.array + b_size, a.array + common_size); +} - plain_array() - { - EIGEN_MAKE_UNALIGNED_ARRAY_ASSERT(0xf); - check_static_allocation_size(); - } +template +class DenseStorage_impl { + plain_array m_data; - plain_array(constructor_without_unaligned_array_assert) - { - check_static_allocation_size(); + public: +#ifndef EIGEN_DENSE_STORAGE_CTOR_PLUGIN + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default; +#else + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size) } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = Size) + smart_copy(other.m_data.array, other.m_data.array + Size, m_data.array); + } +#endif + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) { + numext::swap(m_data, other.m_data); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, + Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; } }; +template +class DenseStorage_impl { + plain_array m_data; + Index m_rows = 0; -template -struct plain_array -{ - EIGEN_USER_ALIGN16 T array[1]; - plain_array() {} - plain_array(constructor_without_unaligned_array_assert) {} + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_rows(other.m_rows) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/) + : m_rows(rows) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + EIGEN_UNUSED_VARIABLE(size) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + m_rows = other.m_rows; + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) { + swap_plain_array(m_data, other.m_data, size(), other.size()); + numext::swap(m_rows, other.m_rows); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) { + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) { + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; } }; +template +class DenseStorage_impl { + plain_array m_data; + Index m_cols = 0; -} // end namespace internal - -/** \internal - * - * \class DenseStorage - * \ingroup Core_Module - * - * \brief Stores the data of a matrix - * - * This class stores the data of fixed-size, dynamic-size or mixed matrices - * in a way as compact as possible. - * - * \sa Matrix - */ -template class DenseStorage; - -// purely fixed-size matrix -template class DenseStorage -{ - internal::plain_array m_data; - public: - DenseStorage() {} - DenseStorage(internal::constructor_without_unaligned_array_assert) - : m_data(internal::constructor_without_unaligned_array_assert()) {} - DenseStorage(const DenseStorage& other) : m_data(other.m_data) {} - DenseStorage& operator=(const DenseStorage& other) - { - if (this != &other) m_data = other.m_data; - return *this; - } - DenseStorage(DenseIndex,DenseIndex,DenseIndex) {} - void swap(DenseStorage& other) { std::swap(m_data,other.m_data); } - static DenseIndex rows(void) {return _Rows;} - static DenseIndex cols(void) {return _Cols;} - void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {} - void resize(DenseIndex,DenseIndex,DenseIndex) {} - const T *data() const { return m_data.array; } - T *data() { return m_data.array; } + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_cols(other.m_cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols) + : m_cols(cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + EIGEN_UNUSED_VARIABLE(size) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + m_cols = other.m_cols; + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) { + swap_plain_array(m_data, other.m_data, size(), other.size()); + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) { + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) { + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; } }; +template +class DenseStorage_impl { + plain_array m_data; + Index m_rows = 0; + Index m_cols = 0; -// null matrix -template class DenseStorage -{ - public: - DenseStorage() {} - DenseStorage(internal::constructor_without_unaligned_array_assert) {} - DenseStorage(const DenseStorage&) {} - DenseStorage& operator=(const DenseStorage&) { return *this; } - DenseStorage(DenseIndex,DenseIndex,DenseIndex) {} - void swap(DenseStorage& ) {} - static DenseIndex rows(void) {return _Rows;} - static DenseIndex cols(void) {return _Cols;} - void conservativeResize(DenseIndex,DenseIndex,DenseIndex) {} - void resize(DenseIndex,DenseIndex,DenseIndex) {} - const T *data() const { return 0; } - T *data() { return 0; } + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_rows(other.m_rows), m_cols(other.m_cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols) + : m_rows(rows), m_cols(cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + EIGEN_UNUSED_VARIABLE(size) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + smart_copy(other.m_data.array, other.m_data.array + other.size(), m_data.array); + m_rows = other.m_rows; + m_cols = other.m_cols; + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) { + swap_plain_array(m_data, other.m_data, size(), other.size()); + numext::swap(m_rows, other.m_rows); + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) { + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) { + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data.array; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data.array; } }; +// null matrix variants +template +class DenseStorage_impl { + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl&) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, + Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index /*cols*/) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; } +}; +template +class DenseStorage_impl { + Index m_rows = 0; -// more specializations for null matrices; these are necessary to resolve ambiguities -template class DenseStorage -: public DenseStorage { }; - -template class DenseStorage -: public DenseStorage { }; + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index /*cols*/) + : m_rows(rows) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_rows, other.m_rows); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index /*cols*/) { + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index /*cols*/) { + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; } +}; +template +class DenseStorage_impl { + Index m_cols = 0; -template class DenseStorage -: public DenseStorage { }; + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index /*rows*/, Index cols) + : m_cols(cols) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index /*rows*/, Index cols) { + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index /*rows*/, Index cols) { + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; } +}; +template +class DenseStorage_impl { + Index m_rows = 0; + Index m_cols = 0; -// dynamic-size matrix with fixed-size storage -template class DenseStorage -{ - internal::plain_array m_data; - DenseIndex m_rows; - DenseIndex m_cols; - public: - DenseStorage() : m_rows(0), m_cols(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) - : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0), m_cols(0) {} - DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) {} - DenseStorage& operator=(const DenseStorage& other) - { - if (this != &other) - { - m_data = other.m_data; - m_rows = other.m_rows; - m_cols = other.m_cols; - } - return *this; - } - DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) : m_rows(nbRows), m_cols(nbCols) {} - void swap(DenseStorage& other) - { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); } - DenseIndex rows() const {return m_rows;} - DenseIndex cols() const {return m_cols;} - void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; } - void resize(DenseIndex, DenseIndex nbRows, DenseIndex nbCols) { m_rows = nbRows; m_cols = nbCols; } - const T *data() const { return m_data.array; } - T *data() { return m_data.array; } + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index /*size*/, Index rows, Index cols) + : m_rows(rows), m_cols(cols) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_rows, other.m_rows); + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index /*size*/, Index rows, Index cols) { + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index /*size*/, Index rows, Index cols) { + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return nullptr; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return nullptr; } }; +// fixed-size matrix with dynamic memory allocation not currently supported +template +class DenseStorage_impl {}; +// dynamic-sized variants +template +class DenseStorage_impl { + static constexpr bool Align = (Options & DontAlign) == 0; + T* m_data = nullptr; + Index m_rows = 0; -// dynamic-size matrix with fixed-size storage and fixed width -template class DenseStorage -{ - internal::plain_array m_data; - DenseIndex m_rows; - public: - DenseStorage() : m_rows(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) - : m_data(internal::constructor_without_unaligned_array_assert()), m_rows(0) {} - DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_rows(other.m_rows) {} - DenseStorage& operator=(const DenseStorage& other) - { - if (this != &other) - { - m_data = other.m_data; - m_rows = other.m_rows; - } - return *this; + public: + static constexpr int Size = Dynamic; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_data(conditional_aligned_new_auto(other.size())), m_rows(other.m_rows) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data, other.m_data + other.size(), m_data); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index /*cols*/) + : m_data(conditional_aligned_new_auto(size)), m_rows(rows) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept + : m_data(other.m_data), m_rows(other.m_rows) { + other.m_data = nullptr; + other.m_rows = 0; + } + EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto(m_data, size()); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + resize(other.size(), other.rows(), other.cols()); + smart_copy(other.m_data, other.m_data + other.size(), m_data); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept { + this->swap(other); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_data, other.m_data); + numext::swap(m_rows, other.m_rows); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index /*cols*/) { + m_data = conditional_aligned_realloc_new_auto(m_data, size, this->size()); + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index /*cols*/) { + Index oldSize = this->size(); + if (oldSize != size) { + conditional_aligned_delete_auto(m_data, oldSize); + m_data = conditional_aligned_new_auto(size); + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) } - DenseStorage(DenseIndex, DenseIndex nbRows, DenseIndex) : m_rows(nbRows) {} - void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); } - DenseIndex rows(void) const {return m_rows;} - DenseIndex cols(void) const {return _Cols;} - void conservativeResize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; } - void resize(DenseIndex, DenseIndex nbRows, DenseIndex) { m_rows = nbRows; } - const T *data() const { return m_data.array; } - T *data() { return m_data.array; } + m_rows = rows; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * Cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; } }; +template +class DenseStorage_impl { + static constexpr bool Align = (Options & DontAlign) == 0; + T* m_data = nullptr; + Index m_cols = 0; -// dynamic-size matrix with fixed-size storage and fixed height -template class DenseStorage -{ - internal::plain_array m_data; - DenseIndex m_cols; - public: - DenseStorage() : m_cols(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) - : m_data(internal::constructor_without_unaligned_array_assert()), m_cols(0) {} - DenseStorage(const DenseStorage& other) : m_data(other.m_data), m_cols(other.m_cols) {} - DenseStorage& operator=(const DenseStorage& other) - { - if (this != &other) - { - m_data = other.m_data; - m_cols = other.m_cols; - } - return *this; + public: + static constexpr int Size = Dynamic; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_data(conditional_aligned_new_auto(other.size())), m_cols(other.m_cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data, other.m_data + other.size(), m_data); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index /*rows*/, Index cols) + : m_data(conditional_aligned_new_auto(size)), m_cols(cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept + : m_data(other.m_data), m_cols(other.m_cols) { + other.m_data = nullptr; + other.m_cols = 0; + } + EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto(m_data, size()); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + resize(other.size(), other.rows(), other.cols()); + smart_copy(other.m_data, other.m_data + other.size(), m_data); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept { + this->swap(other); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_data, other.m_data); + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index /*rows*/, Index cols) { + m_data = conditional_aligned_realloc_new_auto(m_data, size, this->size()); + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index /*rows*/, Index cols) { + Index oldSize = this->size(); + if (oldSize != size) { + conditional_aligned_delete_auto(m_data, oldSize); + m_data = conditional_aligned_new_auto(size); + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) } - DenseStorage(DenseIndex, DenseIndex, DenseIndex nbCols) : m_cols(nbCols) {} - void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); } - DenseIndex rows(void) const {return _Rows;} - DenseIndex cols(void) const {return m_cols;} - void conservativeResize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; } - void resize(DenseIndex, DenseIndex, DenseIndex nbCols) { m_cols = nbCols; } - const T *data() const { return m_data.array; } - T *data() { return m_data.array; } + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return Rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return Rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; } }; +template +class DenseStorage_impl { + static constexpr bool Align = (Options & DontAlign) == 0; + T* m_data = nullptr; + Index m_rows = 0; + Index m_cols = 0; -// purely dynamic matrix. -template class DenseStorage -{ - T *m_data; - DenseIndex m_rows; - DenseIndex m_cols; - public: - DenseStorage() : m_data(0), m_rows(0), m_cols(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) - : m_data(0), m_rows(0), m_cols(0) {} - DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols) - : m_data(internal::conditional_aligned_new_auto(size)), m_rows(nbRows), m_cols(nbCols) - { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN } -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - DenseStorage(DenseStorage&& other) - : m_data(std::move(other.m_data)) - , m_rows(std::move(other.m_rows)) - , m_cols(std::move(other.m_cols)) - { - other.m_data = nullptr; - } - DenseStorage& operator=(DenseStorage&& other) - { - using std::swap; - swap(m_data, other.m_data); - swap(m_rows, other.m_rows); - swap(m_cols, other.m_cols); - return *this; - } -#endif - ~DenseStorage() { internal::conditional_aligned_delete_auto(m_data, m_rows*m_cols); } - void swap(DenseStorage& other) - { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); std::swap(m_cols,other.m_cols); } - DenseIndex rows(void) const {return m_rows;} - DenseIndex cols(void) const {return m_cols;} - void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols) - { - m_data = internal::conditional_aligned_realloc_new_auto(m_data, size, m_rows*m_cols); - m_rows = nbRows; - m_cols = nbCols; - } - void resize(DenseIndex size, DenseIndex nbRows, DenseIndex nbCols) - { - if(size != m_rows*m_cols) - { - internal::conditional_aligned_delete_auto(m_data, m_rows*m_cols); - if (size) - m_data = internal::conditional_aligned_new_auto(size); - else - m_data = 0; - EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN - } - m_rows = nbRows; - m_cols = nbCols; + public: + static constexpr int Size = Dynamic; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(const DenseStorage_impl& other) + : m_data(conditional_aligned_new_auto(other.size())), m_rows(other.m_rows), m_cols(other.m_cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN(Index size = other.size()) + smart_copy(other.m_data, other.m_data + other.size(), m_data); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(Index size, Index rows, Index cols) + : m_data(conditional_aligned_new_auto(size)), m_rows(rows), m_cols(cols) { + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl(DenseStorage_impl&& other) noexcept + : m_data(other.m_data), m_rows(other.m_rows), m_cols(other.m_cols) { + other.m_data = nullptr; + other.m_rows = 0; + other.m_cols = 0; + } + EIGEN_DEVICE_FUNC ~DenseStorage_impl() { conditional_aligned_delete_auto(m_data, size()); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(const DenseStorage_impl& other) { + resize(other.size(), other.rows(), other.cols()); + smart_copy(other.m_data, other.m_data + other.size(), m_data); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage_impl& operator=(DenseStorage_impl&& other) noexcept { + this->swap(other); + return *this; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void swap(DenseStorage_impl& other) noexcept { + numext::swap(m_data, other.m_data); + numext::swap(m_rows, other.m_rows); + numext::swap(m_cols, other.m_cols); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void conservativeResize(Index size, Index rows, Index cols) { + m_data = conditional_aligned_realloc_new_auto(m_data, size, this->size()); + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index size, Index rows, Index cols) { + Index oldSize = this->size(); + if (oldSize != size) { + conditional_aligned_delete_auto(m_data, oldSize); + m_data = conditional_aligned_new_auto(size); + EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN({}) } - const T *data() const { return m_data; } - T *data() { return m_data; } - private: - DenseStorage(const DenseStorage&); - DenseStorage& operator=(const DenseStorage&); + m_rows = rows; + m_cols = cols; + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const { return m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index size() const { return m_rows * m_cols; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr T* data() { return m_data; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const T* data() const { return m_data; } +}; +template +struct use_default_move { + static constexpr bool DynamicObject = Size == Dynamic; + static constexpr bool TrivialObject = + (!NumTraits::RequireInitialization) && (Rows >= 0) && (Cols >= 0) && (Size == Rows * Cols); + static constexpr bool value = DynamicObject || TrivialObject; }; +} // end namespace internal -// matrix with dynamic width and fixed height (so that matrix has dynamic size). -template class DenseStorage -{ - T *m_data; - DenseIndex m_cols; - public: - DenseStorage() : m_data(0), m_cols(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_cols(0) {} - DenseStorage(DenseIndex size, DenseIndex, DenseIndex nbCols) : m_data(internal::conditional_aligned_new_auto(size)), m_cols(nbCols) - { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN } -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - DenseStorage(DenseStorage&& other) - : m_data(std::move(other.m_data)) - , m_cols(std::move(other.m_cols)) - { - other.m_data = nullptr; - } - DenseStorage& operator=(DenseStorage&& other) - { - using std::swap; - swap(m_data, other.m_data); - swap(m_cols, other.m_cols); - return *this; - } -#endif - ~DenseStorage() { internal::conditional_aligned_delete_auto(m_data, _Rows*m_cols); } - void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_cols,other.m_cols); } - static DenseIndex rows(void) {return _Rows;} - DenseIndex cols(void) const {return m_cols;} - void conservativeResize(DenseIndex size, DenseIndex, DenseIndex nbCols) - { - m_data = internal::conditional_aligned_realloc_new_auto(m_data, size, _Rows*m_cols); - m_cols = nbCols; - } - EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex, DenseIndex nbCols) - { - if(size != _Rows*m_cols) - { - internal::conditional_aligned_delete_auto(m_data, _Rows*m_cols); - if (size) - m_data = internal::conditional_aligned_new_auto(size); - else - m_data = 0; - EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN - } - m_cols = nbCols; - } - const T *data() const { return m_data; } - T *data() { return m_data; } - private: - DenseStorage(const DenseStorage&); - DenseStorage& operator=(const DenseStorage&); +/** \internal + * + * \class DenseStorage_impl + * \ingroup Core_Module + * + * \brief Stores the data of a matrix + * + * This class stores the data of fixed-size, dynamic-size or mixed matrices + * in a way as compact as possible. + * + * \sa Matrix + */ +template ::value> +class DenseStorage : public internal::DenseStorage_impl { + using Base = internal::DenseStorage_impl; + + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols) + : Base(size, rows, cols) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(const DenseStorage&) = default; + // if DenseStorage meets the requirements of use_default_move, then use the move construction and move assignment + // operation defined in DenseStorage_impl, or the compiler-generated version if none is defined + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(DenseStorage&&) = default; }; +template +class DenseStorage + : public internal::DenseStorage_impl { + using Base = internal::DenseStorage_impl; -// matrix with dynamic height and fixed width (so that matrix has dynamic size). -template class DenseStorage -{ - T *m_data; - DenseIndex m_rows; - public: - DenseStorage() : m_data(0), m_rows(0) {} - DenseStorage(internal::constructor_without_unaligned_array_assert) : m_data(0), m_rows(0) {} - DenseStorage(DenseIndex size, DenseIndex nbRows, DenseIndex) : m_data(internal::conditional_aligned_new_auto(size)), m_rows(nbRows) - { EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN } -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - DenseStorage(DenseStorage&& other) - : m_data(std::move(other.m_data)) - , m_rows(std::move(other.m_rows)) - { - other.m_data = nullptr; - } - DenseStorage& operator=(DenseStorage&& other) - { - using std::swap; - swap(m_data, other.m_data); - swap(m_rows, other.m_rows); - return *this; - } -#endif - ~DenseStorage() { internal::conditional_aligned_delete_auto(m_data, _Cols*m_rows); } - void swap(DenseStorage& other) { std::swap(m_data,other.m_data); std::swap(m_rows,other.m_rows); } - DenseIndex rows(void) const {return m_rows;} - static DenseIndex cols(void) {return _Cols;} - void conservativeResize(DenseIndex size, DenseIndex nbRows, DenseIndex) - { - m_data = internal::conditional_aligned_realloc_new_auto(m_data, size, m_rows*_Cols); - m_rows = nbRows; - } - EIGEN_STRONG_INLINE void resize(DenseIndex size, DenseIndex nbRows, DenseIndex) - { - if(size != m_rows*_Cols) - { - internal::conditional_aligned_delete_auto(m_data, _Cols*m_rows); - if (size) - m_data = internal::conditional_aligned_new_auto(size); - else - m_data = 0; - EIGEN_INTERNAL_DENSE_STORAGE_CTOR_PLUGIN - } - m_rows = nbRows; - } - const T *data() const { return m_data; } - T *data() { return m_data; } - private: - DenseStorage(const DenseStorage&); - DenseStorage& operator=(const DenseStorage&); + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage() = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(const DenseStorage&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(Index size, Index rows, Index cols) + : Base(size, rows, cols) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(const DenseStorage&) = default; + // if DenseStorage does not meet the requirements of use_default_move, then defer to the copy construction and copy + // assignment behavior + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage(DenseStorage&& other) + : DenseStorage(static_cast(other)) {} + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr DenseStorage& operator=(DenseStorage&& other) { + *this = other; + return *this; + } }; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_MATRIX_H +#endif // EIGEN_MATRIX_H diff --git a/inst/include/Eigen/src/Core/DeviceWrapper.h b/inst/include/Eigen/src/Core/DeviceWrapper.h new file mode 100644 index 00000000..012dce10 --- /dev/null +++ b/inst/include/Eigen/src/Core/DeviceWrapper.h @@ -0,0 +1,153 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2023 Charlie Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_DEVICEWRAPPER_H +#define EIGEN_DEVICEWRAPPER_H + +namespace Eigen { +template +struct DeviceWrapper { + using Base = EigenBase>; + using Scalar = typename Derived::Scalar; + + EIGEN_DEVICE_FUNC DeviceWrapper(Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {} + EIGEN_DEVICE_FUNC DeviceWrapper(const Base& xpr, Device& device) : m_xpr(xpr.derived()), m_device(device) {} + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const EigenBase& other) { + using AssignOp = internal::assign_op; + internal::call_assignment(*this, other.derived(), AssignOp()); + return m_xpr; + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const EigenBase& other) { + using AddAssignOp = internal::add_assign_op; + internal::call_assignment(*this, other.derived(), AddAssignOp()); + return m_xpr; + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const EigenBase& other) { + using SubAssignOp = internal::sub_assign_op; + internal::call_assignment(*this, other.derived(), SubAssignOp()); + return m_xpr; + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& derived() { return m_xpr; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Device& device() { return m_device; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE NoAlias noalias() { + return NoAlias(*this); + } + + Derived& m_xpr; + Device& m_device; +}; + +namespace internal { + +// this is where we differentiate between lazy assignment and specialized kernels (e.g. matrix products) +template ::Shape, + typename evaluator_traits::Shape>::Kind, + typename EnableIf = void> +struct AssignmentWithDevice; + +// unless otherwise specified, use the default product implementation +template +struct AssignmentWithDevice, Functor, Device, Dense2Dense, Weak> { + using SrcXprType = Product; + using Base = Assignment; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func, + Device&) { + Base::run(dst, src, func); + } +}; + +// specialization for coeffcient-wise assignment +template +struct AssignmentWithDevice { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, const Functor& func, + Device& device) { +#ifndef EIGEN_NO_DEBUG + internal::check_for_aliasing(dst, src); +#endif + + call_dense_assignment_loop(dst, src, func, device); + } +}; + +// this allows us to use the default evaluation scheme if it is not specialized for the device +template +struct dense_assignment_loop_with_device { + using Base = dense_assignment_loop; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Kernel& kernel, Device&) { Base::run(kernel); } +}; + +// entry point for a generic expression with device +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_assignment_no_alias(DeviceWrapper dst, + const Src& src, const Func& func) { + enum { + NeedToTranspose = ((int(Dst::RowsAtCompileTime) == 1 && int(Src::ColsAtCompileTime) == 1) || + (int(Dst::ColsAtCompileTime) == 1 && int(Src::RowsAtCompileTime) == 1)) && + int(Dst::SizeAtCompileTime) != 1 + }; + + using ActualDstTypeCleaned = std::conditional_t, Dst>; + using ActualDstType = std::conditional_t, Dst&>; + ActualDstType actualDst(dst.derived()); + + // TODO check whether this is the right place to perform these checks: + EIGEN_STATIC_ASSERT_LVALUE(Dst) + EIGEN_STATIC_ASSERT_SAME_MATRIX_SIZE(ActualDstTypeCleaned, Src) + EIGEN_CHECK_BINARY_COMPATIBILIY(Func, typename ActualDstTypeCleaned::Scalar, typename Src::Scalar); + + // this provides a mechanism for specializing simple assignments, matrix products, etc + AssignmentWithDevice::run(actualDst, src, func, dst.device()); +} + +// copy and pasted from AssignEvaluator except forward device to kernel +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void call_dense_assignment_loop(DstXprType& dst, const SrcXprType& src, + const Functor& func, Device& device) { + using DstEvaluatorType = evaluator; + using SrcEvaluatorType = evaluator; + + SrcEvaluatorType srcEvaluator(src); + + // NOTE To properly handle A = (A*A.transpose())/s with A rectangular, + // we need to resize the destination after the source evaluator has been created. + resize_if_allowed(dst, src, func); + + DstEvaluatorType dstEvaluator(dst); + + using Kernel = generic_dense_assignment_kernel; + + Kernel kernel(dstEvaluator, srcEvaluator, func, dst.const_cast_derived()); + + dense_assignment_loop_with_device::run(kernel, device); +} + +} // namespace internal + +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper EigenBase::device(Device& device) { + return DeviceWrapper(derived(), device); +} + +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper EigenBase::device( + Device& device) const { + return DeviceWrapper(derived(), device); +} +} // namespace Eigen +#endif diff --git a/inst/include/Eigen/src/Core/Diagonal.h b/inst/include/Eigen/src/Core/Diagonal.h index 68cf6d4b..ff8611c6 100644 --- a/inst/include/Eigen/src/Core/Diagonal.h +++ b/inst/include/Eigen/src/Core/Diagonal.h @@ -11,227 +11,209 @@ #ifndef EIGEN_DIAGONAL_H #define EIGEN_DIAGONAL_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { /** \class Diagonal - * \ingroup Core_Module - * - * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix - * - * \param MatrixType the type of the object in which we are taking a sub/main/super diagonal - * \param DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal. - * A positive value means a superdiagonal, a negative value means a subdiagonal. - * You can also use Dynamic so the index can be set at runtime. - * - * The matrix is not required to be square. - * - * This class represents an expression of the main diagonal, or any sub/super diagonal - * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the - * time this is the only way it is used. - * - * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index) - */ + * \ingroup Core_Module + * + * \brief Expression of a diagonal/subdiagonal/superdiagonal in a matrix + * + * \tparam MatrixType the type of the object in which we are taking a sub/main/super diagonal + * \tparam DiagIndex the index of the sub/super diagonal. The default is 0 and it means the main diagonal. + * A positive value means a superdiagonal, a negative value means a subdiagonal. + * You can also use DynamicIndex so the index can be set at runtime. + * + * The matrix is not required to be square. + * + * This class represents an expression of the main diagonal, or any sub/super diagonal + * of a square matrix. It is the return type of MatrixBase::diagonal() and MatrixBase::diagonal(Index) and most of the + * time this is the only way it is used. + * + * \sa MatrixBase::diagonal(), MatrixBase::diagonal(Index) + */ namespace internal { -template -struct traits > - : traits -{ - typedef typename nested::type MatrixTypeNested; - typedef typename remove_reference::type _MatrixTypeNested; +template +struct traits > : traits { + typedef typename ref_selector::type MatrixTypeNested; + typedef std::remove_reference_t MatrixTypeNested_; typedef typename MatrixType::StorageKind StorageKind; enum { - RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) ? Dynamic - : (EIGEN_PLAIN_ENUM_MIN(MatrixType::RowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0), - MatrixType::ColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))), + RowsAtCompileTime = (int(DiagIndex) == DynamicIndex || int(MatrixType::SizeAtCompileTime) == Dynamic) + ? Dynamic + : (plain_enum_min(MatrixType::RowsAtCompileTime - plain_enum_max(-DiagIndex, 0), + MatrixType::ColsAtCompileTime - plain_enum_max(DiagIndex, 0))), ColsAtCompileTime = 1, - MaxRowsAtCompileTime = int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic - : DiagIndex == DynamicIndex ? EIGEN_SIZE_MIN_PREFER_FIXED(MatrixType::MaxRowsAtCompileTime, - MatrixType::MaxColsAtCompileTime) - : (EIGEN_PLAIN_ENUM_MIN(MatrixType::MaxRowsAtCompileTime - EIGEN_PLAIN_ENUM_MAX(-DiagIndex, 0), - MatrixType::MaxColsAtCompileTime - EIGEN_PLAIN_ENUM_MAX( DiagIndex, 0))), + MaxRowsAtCompileTime = + int(MatrixType::MaxSizeAtCompileTime) == Dynamic ? Dynamic + : DiagIndex == DynamicIndex + ? min_size_prefer_fixed(MatrixType::MaxRowsAtCompileTime, MatrixType::MaxColsAtCompileTime) + : (plain_enum_min(MatrixType::MaxRowsAtCompileTime - plain_enum_max(-DiagIndex, 0), + MatrixType::MaxColsAtCompileTime - plain_enum_max(DiagIndex, 0))), MaxColsAtCompileTime = 1, MaskLvalueBit = is_lvalue::value ? LvalueBit : 0, - Flags = (unsigned int)_MatrixTypeNested::Flags & (HereditaryBits | LinearAccessBit | MaskLvalueBit | DirectAccessBit) & ~RowMajorBit, - CoeffReadCost = _MatrixTypeNested::CoeffReadCost, + Flags = (unsigned int)MatrixTypeNested_::Flags & (RowMajorBit | MaskLvalueBit | DirectAccessBit) & + ~RowMajorBit, // FIXME DirectAccessBit should not be handled by expressions MatrixTypeOuterStride = outer_stride_at_compile_time::ret, - InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride+1, + InnerStrideAtCompileTime = MatrixTypeOuterStride == Dynamic ? Dynamic : MatrixTypeOuterStride + 1, OuterStrideAtCompileTime = 0 }; }; -} - -template class Diagonal - : public internal::dense_xpr_base< Diagonal >::type -{ - public: - - enum { DiagIndex = _DiagIndex }; - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal) - - inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) : m_matrix(matrix), m_index(a_index) {} - - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal) - - inline Index rows() const - { return m_index.value()<0 ? (std::min)(m_matrix.cols(),m_matrix.rows()+m_index.value()) : (std::min)(m_matrix.rows(),m_matrix.cols()-m_index.value()); } - - inline Index cols() const { return 1; } - - inline Index innerStride() const - { - return m_matrix.outerStride() + 1; - } - - inline Index outerStride() const - { - return 0; - } - - typedef typename internal::conditional< - internal::is_lvalue::value, - Scalar, - const Scalar - >::type ScalarWithConstIfNotLvalue; - - inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); } - inline const Scalar* data() const { return &(m_matrix.const_cast_derived().coeffRef(rowOffset(), colOffset())); } - - inline Scalar& coeffRef(Index row, Index) - { - EIGEN_STATIC_ASSERT_LVALUE(MatrixType) - return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset()); - } - - inline const Scalar& coeffRef(Index row, Index) const - { - return m_matrix.const_cast_derived().coeffRef(row+rowOffset(), row+colOffset()); - } - - inline CoeffReturnType coeff(Index row, Index) const - { - return m_matrix.coeff(row+rowOffset(), row+colOffset()); - } - - inline Scalar& coeffRef(Index idx) - { - EIGEN_STATIC_ASSERT_LVALUE(MatrixType) - return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset()); - } - - inline const Scalar& coeffRef(Index idx) const - { - return m_matrix.const_cast_derived().coeffRef(idx+rowOffset(), idx+colOffset()); - } - - inline CoeffReturnType coeff(Index idx) const - { - return m_matrix.coeff(idx+rowOffset(), idx+colOffset()); - } - - const typename internal::remove_all::type& - nestedExpression() const - { - return m_matrix; - } - - int index() const - { - return m_index.value(); - } - - protected: - typename MatrixType::Nested m_matrix; - const internal::variable_if_dynamicindex m_index; - - private: - // some compilers may fail to optimize std::max etc in case of compile-time constants... - EIGEN_STRONG_INLINE Index absDiagIndex() const { return m_index.value()>0 ? m_index.value() : -m_index.value(); } - EIGEN_STRONG_INLINE Index rowOffset() const { return m_index.value()>0 ? 0 : -m_index.value(); } - EIGEN_STRONG_INLINE Index colOffset() const { return m_index.value()>0 ? m_index.value() : 0; } - // triger a compile time error is someone try to call packet - template typename MatrixType::PacketReturnType packet(Index) const; - template typename MatrixType::PacketReturnType packet(Index,Index) const; +} // namespace internal + +template +class Diagonal : public internal::dense_xpr_base >::type { + public: + enum { DiagIndex = DiagIndex_ }; + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Diagonal) + + EIGEN_DEVICE_FUNC explicit inline Diagonal(MatrixType& matrix, Index a_index = DiagIndex) + : m_matrix(matrix), m_index(a_index) { + eigen_assert(a_index <= m_matrix.cols() && -a_index <= m_matrix.rows()); + } + + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Diagonal) + + EIGEN_DEVICE_FUNC inline Index rows() const { + return m_index.value() < 0 ? numext::mini(m_matrix.cols(), m_matrix.rows() + m_index.value()) + : numext::mini(m_matrix.rows(), m_matrix.cols() - m_index.value()); + } + + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return 1; } + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_matrix.outerStride() + 1; } + + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return 0; } + + typedef std::conditional_t::value, Scalar, const Scalar> ScalarWithConstIfNotLvalue; + + EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue* data() { return &(m_matrix.coeffRef(rowOffset(), colOffset())); } + EIGEN_DEVICE_FUNC inline const Scalar* data() const { return &(m_matrix.coeffRef(rowOffset(), colOffset())); } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index) { + EIGEN_STATIC_ASSERT_LVALUE(MatrixType) + return m_matrix.coeffRef(row + rowOffset(), row + colOffset()); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index row, Index) const { + return m_matrix.coeffRef(row + rowOffset(), row + colOffset()); + } + + EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index row, Index) const { + return m_matrix.coeff(row + rowOffset(), row + colOffset()); + } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index idx) { + EIGEN_STATIC_ASSERT_LVALUE(MatrixType) + return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset()); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index idx) const { + return m_matrix.coeffRef(idx + rowOffset(), idx + colOffset()); + } + + EIGEN_DEVICE_FUNC inline CoeffReturnType coeff(Index idx) const { + return m_matrix.coeff(idx + rowOffset(), idx + colOffset()); + } + + EIGEN_DEVICE_FUNC inline const internal::remove_all_t& nestedExpression() const { + return m_matrix; + } + + EIGEN_DEVICE_FUNC inline Index index() const { return m_index.value(); } + + protected: + typename internal::ref_selector::non_const_type m_matrix; + const internal::variable_if_dynamicindex m_index; + + private: + // some compilers may fail to optimize std::max etc in case of compile-time constants... + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index absDiagIndex() const noexcept { + return m_index.value() > 0 ? m_index.value() : -m_index.value(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rowOffset() const noexcept { + return m_index.value() > 0 ? 0 : -m_index.value(); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index colOffset() const noexcept { + return m_index.value() > 0 ? m_index.value() : 0; + } + // trigger a compile-time error if someone try to call packet + template + typename MatrixType::PacketReturnType packet(Index) const; + template + typename MatrixType::PacketReturnType packet(Index, Index) const; }; /** \returns an expression of the main diagonal of the matrix \c *this - * - * \c *this is not required to be square. - * - * Example: \include MatrixBase_diagonal.cpp - * Output: \verbinclude MatrixBase_diagonal.out - * - * \sa class Diagonal */ -template -inline typename MatrixBase::DiagonalReturnType -MatrixBase::diagonal() -{ - return derived(); + * + * \c *this is not required to be square. + * + * Example: \include MatrixBase_diagonal.cpp + * Output: \verbinclude MatrixBase_diagonal.out + * + * \sa class Diagonal */ +template +EIGEN_DEVICE_FUNC inline typename MatrixBase::DiagonalReturnType MatrixBase::diagonal() { + return DiagonalReturnType(derived()); } /** This is the const version of diagonal(). */ -template -inline typename MatrixBase::ConstDiagonalReturnType -MatrixBase::diagonal() const -{ +template +EIGEN_DEVICE_FUNC inline const typename MatrixBase::ConstDiagonalReturnType MatrixBase::diagonal() + const { return ConstDiagonalReturnType(derived()); } /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this - * - * \c *this is not required to be square. - * - * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0 - * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal. - * - * Example: \include MatrixBase_diagonal_int.cpp - * Output: \verbinclude MatrixBase_diagonal_int.out - * - * \sa MatrixBase::diagonal(), class Diagonal */ -template -inline typename MatrixBase::DiagonalDynamicIndexReturnType -MatrixBase::diagonal(Index index) -{ - return DiagonalDynamicIndexReturnType(derived(), index); + * + * \c *this is not required to be square. + * + * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0 + * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal. + * + * Example: \include MatrixBase_diagonal_int.cpp + * Output: \verbinclude MatrixBase_diagonal_int.out + * + * \sa MatrixBase::diagonal(), class Diagonal */ +template +EIGEN_DEVICE_FUNC inline Diagonal MatrixBase::diagonal(Index index) { + return Diagonal(derived(), index); } /** This is the const version of diagonal(Index). */ -template -inline typename MatrixBase::ConstDiagonalDynamicIndexReturnType -MatrixBase::diagonal(Index index) const -{ - return ConstDiagonalDynamicIndexReturnType(derived(), index); +template +EIGEN_DEVICE_FUNC inline const Diagonal MatrixBase::diagonal(Index index) const { + return Diagonal(derived(), index); } /** \returns an expression of the \a DiagIndex-th sub or super diagonal of the matrix \c *this - * - * \c *this is not required to be square. - * - * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0 - * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal. - * - * Example: \include MatrixBase_diagonal_template_int.cpp - * Output: \verbinclude MatrixBase_diagonal_template_int.out - * - * \sa MatrixBase::diagonal(), class Diagonal */ -template -template -inline typename MatrixBase::template DiagonalIndexReturnType::Type -MatrixBase::diagonal() -{ - return derived(); + * + * \c *this is not required to be square. + * + * The template parameter \a DiagIndex represent a super diagonal if \a DiagIndex > 0 + * and a sub diagonal otherwise. \a DiagIndex == 0 is equivalent to the main diagonal. + * + * Example: \include MatrixBase_diagonal_template_int.cpp + * Output: \verbinclude MatrixBase_diagonal_template_int.out + * + * \sa MatrixBase::diagonal(), class Diagonal */ +template +template +EIGEN_DEVICE_FUNC inline Diagonal MatrixBase::diagonal() { + return Diagonal(derived()); } /** This is the const version of diagonal(). */ -template -template -inline typename MatrixBase::template ConstDiagonalIndexReturnType::Type -MatrixBase::diagonal() const -{ - return derived(); +template +template +EIGEN_DEVICE_FUNC inline const Diagonal MatrixBase::diagonal() const { + return Diagonal(derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_DIAGONAL_H +#endif // EIGEN_DIAGONAL_H diff --git a/inst/include/Eigen/src/Core/DiagonalMatrix.h b/inst/include/Eigen/src/Core/DiagonalMatrix.h index e6c220f4..52630d92 100644 --- a/inst/include/Eigen/src/Core/DiagonalMatrix.h +++ b/inst/include/Eigen/src/Core/DiagonalMatrix.h @@ -11,303 +11,410 @@ #ifndef EIGEN_DIAGONALMATRIX_H #define EIGEN_DIAGONALMATRIX_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +/** \class DiagonalBase + * \ingroup Core_Module + * + * \brief Base class for diagonal matrices and expressions + * + * This is the base class that is inherited by diagonal matrix and related expression + * types, which internally use a vector for storing the diagonal entries. Diagonal + * types always represent square matrices. + * + * \tparam Derived is the derived type, a DiagonalMatrix or DiagonalWrapper. + * + * \sa class DiagonalMatrix, class DiagonalWrapper + */ +template +class DiagonalBase : public EigenBase { + public: + typedef typename internal::traits::DiagonalVectorType DiagonalVectorType; + typedef typename DiagonalVectorType::Scalar Scalar; + typedef typename DiagonalVectorType::RealScalar RealScalar; + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::StorageIndex StorageIndex; -#ifndef EIGEN_PARSED_BY_DOXYGEN -template -class DiagonalBase : public EigenBase -{ - public: - typedef typename internal::traits::DiagonalVectorType DiagonalVectorType; - typedef typename DiagonalVectorType::Scalar Scalar; - typedef typename DiagonalVectorType::RealScalar RealScalar; - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - - enum { - RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, - ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, - MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, - MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, - IsVectorAtCompileTime = 0, - Flags = 0 - }; - - typedef Matrix DenseMatrixType; - typedef DenseMatrixType DenseType; - typedef DiagonalMatrix PlainObject; - - inline const Derived& derived() const { return *static_cast(this); } - inline Derived& derived() { return *static_cast(this); } - - DenseMatrixType toDenseMatrix() const { return derived(); } - template - void evalTo(MatrixBase &other) const; - template - void addTo(MatrixBase &other) const - { other.diagonal() += diagonal(); } - template - void subTo(MatrixBase &other) const - { other.diagonal() -= diagonal(); } - - inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); } - inline DiagonalVectorType& diagonal() { return derived().diagonal(); } - - inline Index rows() const { return diagonal().size(); } - inline Index cols() const { return diagonal().size(); } - - /** \returns the diagonal matrix product of \c *this by the matrix \a matrix. - */ - template - const DiagonalProduct - operator*(const MatrixBase &matrix) const - { - return DiagonalProduct(matrix.derived(), derived()); - } + enum { + RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, + ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, + MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, + MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, + IsVectorAtCompileTime = 0, + Flags = NoPreferredStorageOrderBit + }; - inline const DiagonalWrapper, const DiagonalVectorType> > - inverse() const - { - return diagonal().cwiseInverse(); - } - - inline const DiagonalWrapper, const DiagonalVectorType> > - operator*(const Scalar& scalar) const - { - return diagonal() * scalar; - } - friend inline const DiagonalWrapper, const DiagonalVectorType> > - operator*(const Scalar& scalar, const DiagonalBase& other) - { - return other.diagonal() * scalar; - } - - #ifdef EIGEN2_SUPPORT - template - bool isApprox(const DiagonalBase& other, typename NumTraits::Real precision = NumTraits::dummy_precision()) const - { - return diagonal().isApprox(other.diagonal(), precision); - } - template - bool isApprox(const MatrixBase& other, typename NumTraits::Real precision = NumTraits::dummy_precision()) const - { - return toDenseMatrix().isApprox(other, precision); - } - #endif -}; + typedef Matrix + DenseMatrixType; + typedef DenseMatrixType DenseType; + typedef DiagonalMatrix + PlainObject; + + /** \returns a reference to the derived object. */ + EIGEN_DEVICE_FUNC inline const Derived& derived() const { return *static_cast(this); } + /** \returns a const reference to the derived object. */ + EIGEN_DEVICE_FUNC inline Derived& derived() { return *static_cast(this); } + + /** + * Constructs a dense matrix from \c *this. Note, this directly returns a dense matrix type, + * not an expression. + * \returns A dense matrix, with its diagonal entries set from the the derived object. */ + EIGEN_DEVICE_FUNC DenseMatrixType toDenseMatrix() const { return derived(); } + + /** \returns a reference to the derived object's vector of diagonal coefficients. */ + EIGEN_DEVICE_FUNC inline const DiagonalVectorType& diagonal() const { return derived().diagonal(); } + /** \returns a const reference to the derived object's vector of diagonal coefficients. */ + EIGEN_DEVICE_FUNC inline DiagonalVectorType& diagonal() { return derived().diagonal(); } + + /** \returns the value of the coefficient as if \c *this was a dense matrix. */ + EIGEN_DEVICE_FUNC inline Scalar coeff(Index row, Index col) const { + eigen_assert(row >= 0 && col >= 0 && row < rows() && col <= cols()); + return row == col ? diagonal().coeff(row) : Scalar(0); + } -template -template -void DiagonalBase::evalTo(MatrixBase &other) const -{ - other.setZero(); - other.diagonal() = diagonal(); -} -#endif + /** \returns the number of rows. */ + EIGEN_DEVICE_FUNC constexpr Index rows() const { return diagonal().size(); } + /** \returns the number of columns. */ + EIGEN_DEVICE_FUNC constexpr Index cols() const { return diagonal().size(); } + + /** \returns the diagonal matrix product of \c *this by the dense matrix, \a matrix */ + template + EIGEN_DEVICE_FUNC const Product operator*( + const MatrixBase& matrix) const { + return Product(derived(), matrix.derived()); + } + + template + using DiagonalProductReturnType = DiagonalWrapper; + + /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a other */ + template + EIGEN_DEVICE_FUNC const DiagonalProductReturnType operator*( + const DiagonalBase& other) const { + return diagonal().cwiseProduct(other.diagonal()).asDiagonal(); + } + + using DiagonalInverseReturnType = + DiagonalWrapper, const DiagonalVectorType>>; + + /** \returns the inverse \c *this. Computed as the coefficient-wise inverse of the diagonal. */ + EIGEN_DEVICE_FUNC inline const DiagonalInverseReturnType inverse() const { + return diagonal().cwiseInverse().asDiagonal(); + } + + using DiagonalScaleReturnType = + DiagonalWrapper; + + /** \returns the product of \c *this by the scalar \a scalar */ + EIGEN_DEVICE_FUNC inline const DiagonalScaleReturnType operator*(const Scalar& scalar) const { + return (diagonal() * scalar).asDiagonal(); + } + + using ScaleDiagonalReturnType = + DiagonalWrapper; + + /** \returns the product of a scalar and the diagonal matrix \a other */ + EIGEN_DEVICE_FUNC friend inline const ScaleDiagonalReturnType operator*(const Scalar& scalar, + const DiagonalBase& other) { + return (scalar * other.diagonal()).asDiagonal(); + } + + template + using DiagonalSumReturnType = DiagonalWrapper; + + /** \returns the sum of \c *this and the diagonal matrix \a other */ + template + EIGEN_DEVICE_FUNC inline const DiagonalSumReturnType operator+( + const DiagonalBase& other) const { + return (diagonal() + other.diagonal()).asDiagonal(); + } + + template + using DiagonalDifferenceReturnType = DiagonalWrapper; + + /** \returns the difference of \c *this and the diagonal matrix \a other */ + template + EIGEN_DEVICE_FUNC inline const DiagonalDifferenceReturnType operator-( + const DiagonalBase& other) const { + return (diagonal() - other.diagonal()).asDiagonal(); + } +}; /** \class DiagonalMatrix - * \ingroup Core_Module - * - * \brief Represents a diagonal matrix with its storage - * - * \param _Scalar the type of coefficients - * \param SizeAtCompileTime the dimension of the matrix, or Dynamic - * \param MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults - * to SizeAtCompileTime. Most of the time, you do not need to specify it. - * - * \sa class DiagonalWrapper - */ + * \ingroup Core_Module + * + * \brief Represents a diagonal matrix with its storage + * + * \tparam Scalar_ the type of coefficients + * \tparam SizeAtCompileTime the dimension of the matrix, or Dynamic + * \tparam MaxSizeAtCompileTime the dimension of the matrix, or Dynamic. This parameter is optional and defaults + * to SizeAtCompileTime. Most of the time, you do not need to specify it. + * + * \sa class DiagonalBase, class DiagonalWrapper + */ namespace internal { -template -struct traits > - : traits > -{ - typedef Matrix<_Scalar,SizeAtCompileTime,1,0,MaxSizeAtCompileTime,1> DiagonalVectorType; - typedef Dense StorageKind; - typedef DenseIndex Index; - enum { - Flags = LvalueBit - }; +template +struct traits> + : traits> { + typedef Matrix DiagonalVectorType; + typedef DiagonalShape StorageKind; + enum { Flags = LvalueBit | NoPreferredStorageOrderBit | NestByRefBit }; }; -} -template -class DiagonalMatrix - : public DiagonalBase > -{ - public: - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef typename internal::traits::DiagonalVectorType DiagonalVectorType; - typedef const DiagonalMatrix& Nested; - typedef _Scalar Scalar; - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - #endif - - protected: - - DiagonalVectorType m_diagonal; - - public: - - /** const version of diagonal(). */ - inline const DiagonalVectorType& diagonal() const { return m_diagonal; } - /** \returns a reference to the stored vector of diagonal coefficients. */ - inline DiagonalVectorType& diagonal() { return m_diagonal; } - - /** Default constructor without initialization */ - inline DiagonalMatrix() {} - - /** Constructs a diagonal matrix with given dimension */ - inline DiagonalMatrix(Index dim) : m_diagonal(dim) {} - - /** 2D constructor. */ - inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x,y) {} - - /** 3D constructor. */ - inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x,y,z) {} - - /** Copy constructor. */ - template - inline DiagonalMatrix(const DiagonalBase& other) : m_diagonal(other.diagonal()) {} - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */ - inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {} - #endif - - /** generic constructor from expression of the diagonal coefficients */ - template - explicit inline DiagonalMatrix(const MatrixBase& other) : m_diagonal(other) - {} - - /** Copy operator. */ - template - DiagonalMatrix& operator=(const DiagonalBase& other) - { - m_diagonal = other.diagonal(); - return *this; - } +} // namespace internal +template +class DiagonalMatrix : public DiagonalBase> { + public: +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef typename internal::traits::DiagonalVectorType DiagonalVectorType; + typedef const DiagonalMatrix& Nested; + typedef Scalar_ Scalar; + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::StorageIndex StorageIndex; +#endif - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - DiagonalMatrix& operator=(const DiagonalMatrix& other) - { - m_diagonal = other.diagonal(); - return *this; - } - #endif - - /** Resizes to given size. */ - inline void resize(Index size) { m_diagonal.resize(size); } - /** Sets all coefficients to zero. */ - inline void setZero() { m_diagonal.setZero(); } - /** Resizes and sets all coefficients to zero. */ - inline void setZero(Index size) { m_diagonal.setZero(size); } - /** Sets this matrix to be the identity matrix of the current size. */ - inline void setIdentity() { m_diagonal.setOnes(); } - /** Sets this matrix to be the identity matrix of the given size. */ - inline void setIdentity(Index size) { m_diagonal.setOnes(size); } + protected: + DiagonalVectorType m_diagonal; + + public: + /** const version of diagonal(). */ + EIGEN_DEVICE_FUNC inline const DiagonalVectorType& diagonal() const { return m_diagonal; } + /** \returns a reference to the stored vector of diagonal coefficients. */ + EIGEN_DEVICE_FUNC inline DiagonalVectorType& diagonal() { return m_diagonal; } + + /** Default constructor without initialization */ + EIGEN_DEVICE_FUNC inline DiagonalMatrix() {} + + /** Constructs a diagonal matrix with given dimension */ + EIGEN_DEVICE_FUNC explicit inline DiagonalMatrix(Index dim) : m_diagonal(dim) {} + + /** 2D constructor. */ + EIGEN_DEVICE_FUNC inline DiagonalMatrix(const Scalar& x, const Scalar& y) : m_diagonal(x, y) {} + + /** 3D constructor. */ + EIGEN_DEVICE_FUNC inline DiagonalMatrix(const Scalar& x, const Scalar& y, const Scalar& z) : m_diagonal(x, y, z) {} + + /** \brief Construct a diagonal matrix with fixed size from an arbitrary number of coefficients. + * + * \warning To construct a diagonal matrix of fixed size, the number of values passed to this + * constructor must match the fixed dimension of \c *this. + * + * \sa DiagonalMatrix(const Scalar&, const Scalar&) + * \sa DiagonalMatrix(const Scalar&, const Scalar&, const Scalar&) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DiagonalMatrix(const Scalar& a0, const Scalar& a1, const Scalar& a2, + const ArgTypes&... args) + : m_diagonal(a0, a1, a2, args...) {} + + /** \brief Constructs a DiagonalMatrix and initializes it by elements given by an initializer list of initializer + * lists \cpp11 + */ + EIGEN_DEVICE_FUNC explicit EIGEN_STRONG_INLINE DiagonalMatrix( + const std::initializer_list>& list) + : m_diagonal(list) {} + + /** \brief Constructs a DiagonalMatrix from an r-value diagonal vector type */ + EIGEN_DEVICE_FUNC explicit inline DiagonalMatrix(DiagonalVectorType&& diag) : m_diagonal(std::move(diag)) {} + + /** Copy constructor. */ + template + EIGEN_DEVICE_FUNC inline DiagonalMatrix(const DiagonalBase& other) : m_diagonal(other.diagonal()) {} + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** copy constructor. prevent a default copy constructor from hiding the other templated constructor */ + inline DiagonalMatrix(const DiagonalMatrix& other) : m_diagonal(other.diagonal()) {} +#endif + + /** generic constructor from expression of the diagonal coefficients */ + template + EIGEN_DEVICE_FUNC explicit inline DiagonalMatrix(const MatrixBase& other) : m_diagonal(other) {} + + /** Copy operator. */ + template + EIGEN_DEVICE_FUNC DiagonalMatrix& operator=(const DiagonalBase& other) { + m_diagonal = other.diagonal(); + return *this; + } + +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** This is a special case of the templated operator=. Its purpose is to + * prevent a default operator= from hiding the templated operator=. + */ + EIGEN_DEVICE_FUNC DiagonalMatrix& operator=(const DiagonalMatrix& other) { + m_diagonal = other.diagonal(); + return *this; + } +#endif + + typedef DiagonalWrapper, DiagonalVectorType>> + InitializeReturnType; + + typedef DiagonalWrapper, DiagonalVectorType>> + ZeroInitializeReturnType; + + /** Initializes a diagonal matrix of size SizeAtCompileTime with coefficients set to zero */ + EIGEN_DEVICE_FUNC static const ZeroInitializeReturnType Zero() { return DiagonalVectorType::Zero().asDiagonal(); } + /** Initializes a diagonal matrix of size dim with coefficients set to zero */ + EIGEN_DEVICE_FUNC static const ZeroInitializeReturnType Zero(Index size) { + return DiagonalVectorType::Zero(size).asDiagonal(); + } + /** Initializes a identity matrix of size SizeAtCompileTime */ + EIGEN_DEVICE_FUNC static const InitializeReturnType Identity() { return DiagonalVectorType::Ones().asDiagonal(); } + /** Initializes a identity matrix of size dim */ + EIGEN_DEVICE_FUNC static const InitializeReturnType Identity(Index size) { + return DiagonalVectorType::Ones(size).asDiagonal(); + } + + /** Resizes to given size. */ + EIGEN_DEVICE_FUNC inline void resize(Index size) { m_diagonal.resize(size); } + /** Sets all coefficients to zero. */ + EIGEN_DEVICE_FUNC inline void setZero() { m_diagonal.setZero(); } + /** Resizes and sets all coefficients to zero. */ + EIGEN_DEVICE_FUNC inline void setZero(Index size) { m_diagonal.setZero(size); } + /** Sets this matrix to be the identity matrix of the current size. */ + EIGEN_DEVICE_FUNC inline void setIdentity() { m_diagonal.setOnes(); } + /** Sets this matrix to be the identity matrix of the given size. */ + EIGEN_DEVICE_FUNC inline void setIdentity(Index size) { m_diagonal.setOnes(size); } }; /** \class DiagonalWrapper - * \ingroup Core_Module - * - * \brief Expression of a diagonal matrix - * - * \param _DiagonalVectorType the type of the vector of diagonal coefficients - * - * This class is an expression of a diagonal matrix, but not storing its own vector of diagonal coefficients, - * instead wrapping an existing vector expression. It is the return type of MatrixBase::asDiagonal() - * and most of the time this is the only way that it is used. - * - * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal() - */ + * \ingroup Core_Module + * + * \brief Expression of a diagonal matrix + * + * \tparam DiagonalVectorType_ the type of the vector of diagonal coefficients + * + * This class is an expression of a diagonal matrix, but not storing its own vector of diagonal coefficients, + * instead wrapping an existing vector expression. It is the return type of MatrixBase::asDiagonal() + * and most of the time this is the only way that it is used. + * + * \sa class DiagonalMatrix, class DiagonalBase, MatrixBase::asDiagonal() + */ namespace internal { -template -struct traits > -{ - typedef _DiagonalVectorType DiagonalVectorType; +template +struct traits> { + typedef DiagonalVectorType_ DiagonalVectorType; typedef typename DiagonalVectorType::Scalar Scalar; - typedef typename DiagonalVectorType::Index Index; - typedef typename DiagonalVectorType::StorageKind StorageKind; + typedef typename DiagonalVectorType::StorageIndex StorageIndex; + typedef DiagonalShape StorageKind; + typedef typename traits::XprKind XprKind; enum { RowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, ColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, - MaxRowsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, - MaxColsAtCompileTime = DiagonalVectorType::SizeAtCompileTime, - Flags = traits::Flags & LvalueBit + MaxRowsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, + MaxColsAtCompileTime = DiagonalVectorType::MaxSizeAtCompileTime, + Flags = (traits::Flags & LvalueBit) | NoPreferredStorageOrderBit }; }; -} +} // namespace internal -template -class DiagonalWrapper - : public DiagonalBase >, internal::no_assignment_operator -{ - public: - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef _DiagonalVectorType DiagonalVectorType; - typedef DiagonalWrapper Nested; - #endif +template +class DiagonalWrapper : public DiagonalBase>, internal::no_assignment_operator { + public: +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef DiagonalVectorType_ DiagonalVectorType; + typedef DiagonalWrapper Nested; +#endif - /** Constructor from expression of diagonal coefficients to wrap. */ - inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {} + /** Constructor from expression of diagonal coefficients to wrap. */ + EIGEN_DEVICE_FUNC explicit inline DiagonalWrapper(DiagonalVectorType& a_diagonal) : m_diagonal(a_diagonal) {} - /** \returns a const reference to the wrapped expression of diagonal coefficients. */ - const DiagonalVectorType& diagonal() const { return m_diagonal; } + /** \returns a const reference to the wrapped expression of diagonal coefficients. */ + EIGEN_DEVICE_FUNC const DiagonalVectorType& diagonal() const { return m_diagonal; } - protected: - typename DiagonalVectorType::Nested m_diagonal; + protected: + typename DiagonalVectorType::Nested m_diagonal; }; /** \returns a pseudo-expression of a diagonal matrix with *this as vector of diagonal coefficients - * - * \only_for_vectors - * - * Example: \include MatrixBase_asDiagonal.cpp - * Output: \verbinclude MatrixBase_asDiagonal.out - * - * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal() - **/ -template -inline const DiagonalWrapper -MatrixBase::asDiagonal() const -{ - return derived(); + * + * \only_for_vectors + * + * Example: \include MatrixBase_asDiagonal.cpp + * Output: \verbinclude MatrixBase_asDiagonal.out + * + * \sa class DiagonalWrapper, class DiagonalMatrix, diagonal(), isDiagonal() + **/ +template +EIGEN_DEVICE_FUNC inline const DiagonalWrapper MatrixBase::asDiagonal() const { + return DiagonalWrapper(derived()); } /** \returns true if *this is approximately equal to a diagonal matrix, - * within the precision given by \a prec. - * - * Example: \include MatrixBase_isDiagonal.cpp - * Output: \verbinclude MatrixBase_isDiagonal.out - * - * \sa asDiagonal() - */ -template -bool MatrixBase::isDiagonal(const RealScalar& prec) const -{ - using std::abs; - if(cols() != rows()) return false; + * within the precision given by \a prec. + * + * Example: \include MatrixBase_isDiagonal.cpp + * Output: \verbinclude MatrixBase_isDiagonal.out + * + * \sa asDiagonal() + */ +template +bool MatrixBase::isDiagonal(const RealScalar& prec) const { + if (cols() != rows()) return false; RealScalar maxAbsOnDiagonal = static_cast(-1); - for(Index j = 0; j < cols(); ++j) - { - RealScalar absOnDiagonal = abs(coeff(j,j)); - if(absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal; + for (Index j = 0; j < cols(); ++j) { + RealScalar absOnDiagonal = numext::abs(coeff(j, j)); + if (absOnDiagonal > maxAbsOnDiagonal) maxAbsOnDiagonal = absOnDiagonal; } - for(Index j = 0; j < cols(); ++j) - for(Index i = 0; i < j; ++i) - { - if(!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false; - if(!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false; + for (Index j = 0; j < cols(); ++j) + for (Index i = 0; i < j; ++i) { + if (!internal::isMuchSmallerThan(coeff(i, j), maxAbsOnDiagonal, prec)) return false; + if (!internal::isMuchSmallerThan(coeff(j, i), maxAbsOnDiagonal, prec)) return false; } return true; } -} // end namespace Eigen +namespace internal { + +template <> +struct storage_kind_to_shape { + typedef DiagonalShape Shape; +}; + +struct Diagonal2Dense {}; + +template <> +struct AssignmentKind { + typedef Diagonal2Dense Kind; +}; + +// Diagonal matrix to Dense assignment +template +struct Assignment { + static EIGEN_DEVICE_FUNC void run( + DstXprType& dst, const SrcXprType& src, + const internal::assign_op& /*func*/) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); + + dst.setZero(); + dst.diagonal() = src.diagonal(); + } + + static EIGEN_DEVICE_FUNC void run( + DstXprType& dst, const SrcXprType& src, + const internal::add_assign_op& /*func*/) { + dst.diagonal() += src.diagonal(); + } + + static EIGEN_DEVICE_FUNC void run( + DstXprType& dst, const SrcXprType& src, + const internal::sub_assign_op& /*func*/) { + dst.diagonal() -= src.diagonal(); + } +}; + +} // namespace internal + +} // end namespace Eigen -#endif // EIGEN_DIAGONALMATRIX_H +#endif // EIGEN_DIAGONALMATRIX_H diff --git a/inst/include/Eigen/src/Core/DiagonalProduct.h b/inst/include/Eigen/src/Core/DiagonalProduct.h index cc6b536e..bd0feeac 100644 --- a/inst/include/Eigen/src/Core/DiagonalProduct.h +++ b/inst/include/Eigen/src/Core/DiagonalProduct.h @@ -11,121 +11,20 @@ #ifndef EIGEN_DIAGONALPRODUCT_H #define EIGEN_DIAGONALPRODUCT_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -namespace internal { -template -struct traits > - : traits -{ - typedef typename scalar_product_traits::ReturnType Scalar; - enum { - RowsAtCompileTime = MatrixType::RowsAtCompileTime, - ColsAtCompileTime = MatrixType::ColsAtCompileTime, - MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, - MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, - - _StorageOrder = MatrixType::Flags & RowMajorBit ? RowMajor : ColMajor, - _ScalarAccessOnDiag = !((int(_StorageOrder) == ColMajor && int(ProductOrder) == OnTheLeft) - ||(int(_StorageOrder) == RowMajor && int(ProductOrder) == OnTheRight)), - _SameTypes = is_same::value, - // FIXME currently we need same types, but in the future the next rule should be the one - //_Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && ((!_PacketOnDiag) || (_SameTypes && bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))), - _Vectorizable = bool(int(MatrixType::Flags)&PacketAccessBit) && _SameTypes && (_ScalarAccessOnDiag || (bool(int(DiagonalType::DiagonalVectorType::Flags)&PacketAccessBit))), - _LinearAccessMask = (RowsAtCompileTime==1 || ColsAtCompileTime==1) ? LinearAccessBit : 0, - - Flags = ((HereditaryBits|_LinearAccessMask|AlignedBit) & (unsigned int)(MatrixType::Flags)) | (_Vectorizable ? PacketAccessBit : 0),//(int(MatrixType::Flags)&int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit), - Cost0 = EIGEN_ADD_COST(NumTraits::MulCost, MatrixType::CoeffReadCost), - CoeffReadCost = EIGEN_ADD_COST(Cost0,DiagonalType::DiagonalVectorType::CoeffReadCost) - }; -}; -} - -template -class DiagonalProduct : internal::no_assignment_operator, - public MatrixBase > -{ - public: - - typedef MatrixBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(DiagonalProduct) - - inline DiagonalProduct(const MatrixType& matrix, const DiagonalType& diagonal) - : m_matrix(matrix), m_diagonal(diagonal) - { - eigen_assert(diagonal.diagonal().size() == (ProductOrder == OnTheLeft ? matrix.rows() : matrix.cols())); - } - - EIGEN_STRONG_INLINE Index rows() const { return m_matrix.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return m_matrix.cols(); } - - EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const - { - return m_diagonal.diagonal().coeff(ProductOrder == OnTheLeft ? row : col) * m_matrix.coeff(row, col); - } - - EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const - { - enum { - StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor - }; - return coeff(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index row, Index col) const - { - enum { - StorageOrder = Flags & RowMajorBit ? RowMajor : ColMajor - }; - const Index indexInDiagonalVector = ProductOrder == OnTheLeft ? row : col; - return packet_impl(row,col,indexInDiagonalVector,typename internal::conditional< - ((int(StorageOrder) == RowMajor && int(ProductOrder) == OnTheLeft) - ||(int(StorageOrder) == ColMajor && int(ProductOrder) == OnTheRight)), internal::true_type, internal::false_type>::type()); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet(Index idx) const - { - enum { - StorageOrder = int(MatrixType::Flags) & RowMajorBit ? RowMajor : ColMajor - }; - return packet(int(StorageOrder)==ColMajor?idx:0,int(StorageOrder)==ColMajor?0:idx); - } - - protected: - template - EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::true_type) const - { - return internal::pmul(m_matrix.template packet(row, col), - internal::pset1(m_diagonal.diagonal().coeff(id))); - } - - template - EIGEN_STRONG_INLINE PacketScalar packet_impl(Index row, Index col, Index id, internal::false_type) const - { - enum { - InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime, - DiagonalVectorPacketLoadMode = (LoadMode == Aligned && (((InnerSize%16) == 0) || (int(DiagonalType::DiagonalVectorType::Flags)&AlignedBit)==AlignedBit) ? Aligned : Unaligned) - }; - return internal::pmul(m_matrix.template packet(row, col), - m_diagonal.diagonal().template packet(id)); - } - - typename MatrixType::Nested m_matrix; - typename DiagonalType::Nested m_diagonal; -}; +namespace Eigen { /** \returns the diagonal matrix product of \c *this by the diagonal matrix \a diagonal. - */ -template -template -inline const DiagonalProduct -MatrixBase::operator*(const DiagonalBase &a_diagonal) const -{ - return DiagonalProduct(derived(), a_diagonal.derived()); + */ +template +template +EIGEN_DEVICE_FUNC inline const Product MatrixBase::operator*( + const DiagonalBase &a_diagonal) const { + return Product(derived(), a_diagonal.derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_DIAGONALPRODUCT_H +#endif // EIGEN_DIAGONALPRODUCT_H diff --git a/inst/include/Eigen/src/Core/Dot.h b/inst/include/Eigen/src/Core/Dot.h index 9d7651f1..059527c8 100644 --- a/inst/include/Eigen/src/Core/Dot.h +++ b/inst/include/Eigen/src/Core/Dot.h @@ -10,254 +10,259 @@ #ifndef EIGEN_DOT_H #define EIGEN_DOT_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { namespace internal { -// helper function for dot(). The problem is that if we put that in the body of dot(), then upon calling dot -// with mismatched types, the compiler emits errors about failing to instantiate cwiseProduct BEFORE -// looking at the static assertions. Thus this is a trick to get better compile errors. -template -struct dot_nocheck -{ - typedef typename scalar_product_traits::Scalar,typename traits::Scalar>::ReturnType ResScalar; - static inline ResScalar run(const MatrixBase& a, const MatrixBase& b) - { - return a.template binaryExpr::Scalar,typename traits::Scalar> >(b).sum(); +template ::Scalar> +struct squared_norm_impl { + using Real = typename NumTraits::Real; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Real run(const Derived& a) { + Scalar result = a.unaryExpr(squared_norm_functor()).sum(); + return numext::real(result) + numext::imag(result); } }; -template -struct dot_nocheck -{ - typedef typename scalar_product_traits::Scalar,typename traits::Scalar>::ReturnType ResScalar; - static inline ResScalar run(const MatrixBase& a, const MatrixBase& b) - { - return a.transpose().template binaryExpr::Scalar,typename traits::Scalar> >(b).sum(); - } +template +struct squared_norm_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE bool run(const Derived& a) { return a.any(); } }; -} // end namespace internal - -/** \returns the dot product of *this with other. - * - * \only_for_vectors - * - * \note If the scalar type is complex numbers, then this function returns the hermitian - * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the - * second variable. - * - * \sa squaredNorm(), norm() - */ -template -template -typename internal::scalar_product_traits::Scalar,typename internal::traits::Scalar>::ReturnType -MatrixBase::dot(const MatrixBase& other) const -{ - EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) - EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived) - typedef internal::scalar_conj_product_op func; - EIGEN_CHECK_BINARY_COMPATIBILIY(func,Scalar,typename OtherDerived::Scalar); - - eigen_assert(size() == other.size()); - - return internal::dot_nocheck::run(*this, other); -} - -#ifdef EIGEN2_SUPPORT -/** \returns the dot product of *this with other, with the Eigen2 convention that the dot product is linear in the first variable - * (conjugating the second variable). Of course this only makes a difference in the complex case. - * - * This method is only available in EIGEN2_SUPPORT mode. - * - * \only_for_vectors - * - * \sa dot() - */ -template -template -typename internal::traits::Scalar -MatrixBase::eigen2_dot(const MatrixBase& other) const -{ - EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - EIGEN_STATIC_ASSERT_VECTOR_ONLY(OtherDerived) - EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Derived,OtherDerived) - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - - eigen_assert(size() == other.size()); +} // end namespace internal - return internal::dot_nocheck::run(other,*this); +/** \fn MatrixBase::dot + * \returns the dot product of *this with other. + * + * \only_for_vectors + * + * \note If the scalar type is complex numbers, then this function returns the hermitian + * (sesquilinear) dot product, conjugate-linear in the first variable and linear in the + * second variable. + * + * \sa squaredNorm(), norm() + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE + typename ScalarBinaryOpTraits::Scalar, + typename internal::traits::Scalar>::ReturnType + MatrixBase::dot(const MatrixBase& other) const { + return internal::dot_impl::run(derived(), other.derived()); } -#endif - //---------- implementation of L2 norm and related functions ---------- -/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the Frobenius norm. - * In both cases, it consists in the sum of the square of all the matrix entries. - * For vectors, this is also equals to the dot product of \c *this with itself. - * - * \sa dot(), norm() - */ -template -EIGEN_STRONG_INLINE typename NumTraits::Scalar>::Real MatrixBase::squaredNorm() const -{ - return numext::real((*this).cwiseAbs2().sum()); +/** \returns, for vectors, the squared \em l2 norm of \c *this, and for matrices the squared Frobenius norm. + * In both cases, it consists in the sum of the square of all the matrix entries. + * For vectors, this is also equals to the dot product of \c *this with itself. + * + * \sa dot(), norm(), lpNorm() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits::Scalar>::Real +MatrixBase::squaredNorm() const { + return internal::squared_norm_impl::run(derived()); } /** \returns, for vectors, the \em l2 norm of \c *this, and for matrices the Frobenius norm. - * In both cases, it consists in the square root of the sum of the square of all the matrix entries. - * For vectors, this is also equals to the square root of the dot product of \c *this with itself. - * - * \sa dot(), squaredNorm() - */ -template -inline typename NumTraits::Scalar>::Real MatrixBase::norm() const -{ - using std::sqrt; - return sqrt(squaredNorm()); + * In both cases, it consists in the square root of the sum of the square of all the matrix entries. + * For vectors, this is also equals to the square root of the dot product of \c *this with itself. + * + * \sa lpNorm(), dot(), squaredNorm() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename NumTraits::Scalar>::Real +MatrixBase::norm() const { + return numext::sqrt(squaredNorm()); } -/** \returns an expression of the quotient of *this by its own norm. - * - * \only_for_vectors - * - * \sa norm(), normalize() - */ -template -inline const typename MatrixBase::PlainObject -MatrixBase::normalized() const -{ - typedef typename internal::nested::type Nested; - typedef typename internal::remove_reference::type _Nested; - _Nested n(derived()); - return n / n.norm(); +/** \returns an expression of the quotient of \c *this by its own norm. + * + * \warning If the input vector is too small (i.e., this->norm()==0), + * then this function returns a copy of the input. + * + * \only_for_vectors + * + * \sa norm(), normalize() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::PlainObject MatrixBase::normalized() + const { + typedef typename internal::nested_eval::type Nested_; + Nested_ n(derived()); + RealScalar z = n.squaredNorm(); + // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU + if (z > RealScalar(0)) + return n / numext::sqrt(z); + else + return n; } /** Normalizes the vector, i.e. divides it by its own norm. - * - * \only_for_vectors - * - * \sa norm(), normalized() - */ -template -inline void MatrixBase::normalize() -{ - *this /= norm(); + * + * \only_for_vectors + * + * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged. + * + * \sa norm(), normalized() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase::normalize() { + RealScalar z = squaredNorm(); + // NOTE: after extensive benchmarking, this conditional does not impact performance, at least on recent x86 CPU + if (z > RealScalar(0)) derived() /= numext::sqrt(z); +} + +/** \returns an expression of the quotient of \c *this by its own norm while avoiding underflow and overflow. + * + * \only_for_vectors + * + * This method is analogue to the normalized() method, but it reduces the risk of + * underflow and overflow when computing the norm. + * + * \warning If the input vector is too small (i.e., this->norm()==0), + * then this function returns a copy of the input. + * + * \sa stableNorm(), stableNormalize(), normalized() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const typename MatrixBase::PlainObject +MatrixBase::stableNormalized() const { + typedef typename internal::nested_eval::type Nested_; + Nested_ n(derived()); + RealScalar w = n.cwiseAbs().maxCoeff(); + RealScalar z = (n / w).squaredNorm(); + if (z > RealScalar(0)) + return n / (numext::sqrt(z) * w); + else + return n; +} + +/** Normalizes the vector while avoid underflow and overflow + * + * \only_for_vectors + * + * This method is analogue to the normalize() method, but it reduces the risk of + * underflow and overflow when computing the norm. + * + * \warning If the input vector is too small (i.e., this->norm()==0), then \c *this is left unchanged. + * + * \sa stableNorm(), stableNormalized(), normalize() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void MatrixBase::stableNormalize() { + RealScalar w = cwiseAbs().maxCoeff(); + RealScalar z = (derived() / w).squaredNorm(); + if (z > RealScalar(0)) derived() /= numext::sqrt(z) * w; } //---------- implementation of other norms ---------- namespace internal { -template -struct lpNorm_selector -{ +template +struct lpNorm_selector { typedef typename NumTraits::Scalar>::Real RealScalar; - static inline RealScalar run(const MatrixBase& m) - { - using std::pow; - return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1)/p); + EIGEN_DEVICE_FUNC static inline RealScalar run(const MatrixBase& m) { + EIGEN_USING_STD(pow) + return pow(m.cwiseAbs().array().pow(p).sum(), RealScalar(1) / p); } }; -template -struct lpNorm_selector -{ - static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) - { +template +struct lpNorm_selector { + EIGEN_DEVICE_FUNC static inline typename NumTraits::Scalar>::Real run( + const MatrixBase& m) { return m.cwiseAbs().sum(); } }; -template -struct lpNorm_selector -{ - static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) - { +template +struct lpNorm_selector { + EIGEN_DEVICE_FUNC static inline typename NumTraits::Scalar>::Real run( + const MatrixBase& m) { return m.norm(); } }; -template -struct lpNorm_selector -{ - static inline typename NumTraits::Scalar>::Real run(const MatrixBase& m) - { +template +struct lpNorm_selector { + typedef typename NumTraits::Scalar>::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const MatrixBase& m) { + if (Derived::SizeAtCompileTime == 0 || (Derived::SizeAtCompileTime == Dynamic && m.size() == 0)) + return RealScalar(0); return m.cwiseAbs().maxCoeff(); } }; -} // end namespace internal +} // end namespace internal -/** \returns the \f$ \ell^p \f$ norm of *this, that is, returns the p-th root of the sum of the p-th powers of the absolute values - * of the coefficients of *this. If \a p is the special value \a Eigen::Infinity, this function returns the \f$ \ell^\infty \f$ - * norm, that is the maximum of the absolute values of the coefficients of *this. - * - * \sa norm() - */ -template -template -inline typename NumTraits::Scalar>::Real -MatrixBase::lpNorm() const -{ +/** \returns the \b coefficient-wise \f$ \ell^p \f$ norm of \c *this, that is, returns the p-th root of the sum of the + * p-th powers of the absolute values of the coefficients of \c *this. If \a p is the special value \a Eigen::Infinity, + * this function returns the \f$ \ell^\infty \f$ norm, that is the maximum of the absolute values of the coefficients of + * \c *this. + * + * In all cases, if \c *this is empty, then the value 0 is returned. + * + * \note For matrices, this function does not compute the operator-norm. That is, if \c *this is a matrix, then its + * coefficients are interpreted as a 1D vector. Nonetheless, you can easily compute the 1-norm and \f$\infty\f$-norm + * matrix operator norms using \link TutorialReductionsVisitorsBroadcastingReductionsNorm partial reductions \endlink. + * + * \sa norm() + */ +template +template +#ifndef EIGEN_PARSED_BY_DOXYGEN +EIGEN_DEVICE_FUNC inline typename NumTraits::Scalar>::Real +#else +EIGEN_DEVICE_FUNC MatrixBase::RealScalar +#endif +MatrixBase::lpNorm() const { return internal::lpNorm_selector::run(*this); } //---------- implementation of isOrthogonal / isUnitary ---------- /** \returns true if *this is approximately orthogonal to \a other, - * within the precision given by \a prec. - * - * Example: \include MatrixBase_isOrthogonal.cpp - * Output: \verbinclude MatrixBase_isOrthogonal.out - */ -template -template -bool MatrixBase::isOrthogonal -(const MatrixBase& other, const RealScalar& prec) const -{ - typename internal::nested::type nested(derived()); - typename internal::nested::type otherNested(other.derived()); + * within the precision given by \a prec. + * + * Example: \include MatrixBase_isOrthogonal.cpp + * Output: \verbinclude MatrixBase_isOrthogonal.out + */ +template +template +bool MatrixBase::isOrthogonal(const MatrixBase& other, const RealScalar& prec) const { + typename internal::nested_eval::type nested(derived()); + typename internal::nested_eval::type otherNested(other.derived()); return numext::abs2(nested.dot(otherNested)) <= prec * prec * nested.squaredNorm() * otherNested.squaredNorm(); } /** \returns true if *this is approximately an unitary matrix, - * within the precision given by \a prec. In the case where the \a Scalar - * type is real numbers, a unitary matrix is an orthogonal matrix, whence the name. - * - * \note This can be used to check whether a family of vectors forms an orthonormal basis. - * Indeed, \c m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an - * orthonormal basis. - * - * Example: \include MatrixBase_isUnitary.cpp - * Output: \verbinclude MatrixBase_isUnitary.out - */ -template -bool MatrixBase::isUnitary(const RealScalar& prec) const -{ - typename Derived::Nested nested(derived()); - for(Index i = 0; i < cols(); ++i) - { - if(!internal::isApprox(nested.col(i).squaredNorm(), static_cast(1), prec)) - return false; - for(Index j = 0; j < i; ++j) - if(!internal::isMuchSmallerThan(nested.col(i).dot(nested.col(j)), static_cast(1), prec)) - return false; + * within the precision given by \a prec. In the case where the \a Scalar + * type is real numbers, a unitary matrix is an orthogonal matrix, whence the name. + * + * \note This can be used to check whether a family of vectors forms an orthonormal basis. + * Indeed, \c m.isUnitary() returns true if and only if the columns (equivalently, the rows) of m form an + * orthonormal basis. + * + * Example: \include MatrixBase_isUnitary.cpp + * Output: \verbinclude MatrixBase_isUnitary.out + */ +template +bool MatrixBase::isUnitary(const RealScalar& prec) const { + typename internal::nested_eval::type self(derived()); + for (Index i = 0; i < cols(); ++i) { + if (!internal::isApprox(self.col(i).squaredNorm(), static_cast(1), prec)) return false; + for (Index j = 0; j < i; ++j) + if (!internal::isMuchSmallerThan(self.col(i).dot(self.col(j)), static_cast(1), prec)) return false; } return true; } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_DOT_H +#endif // EIGEN_DOT_H diff --git a/inst/include/Eigen/src/Core/EigenBase.h b/inst/include/Eigen/src/Core/EigenBase.h index fadb4585..c9a6e88e 100644 --- a/inst/include/Eigen/src/Core/EigenBase.h +++ b/inst/include/Eigen/src/Core/EigenBase.h @@ -11,121 +11,139 @@ #ifndef EIGEN_EIGENBASE_H #define EIGEN_EIGENBASE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T). - * - * In other words, an EigenBase object is an object that can be copied into a MatrixBase. - * - * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc. - * - * Notice that this class is trivial, it is only used to disambiguate overloaded functions. - * - * \sa \ref TopicClassHierarchy - */ -template struct EigenBase -{ -// typedef typename internal::plain_matrix_type::type PlainObject; +namespace Eigen { +/** \class EigenBase + * \ingroup Core_Module + * + * Common base class for all classes T such that MatrixBase has an operator=(T) and a constructor MatrixBase(T). + * + * In other words, an EigenBase object is an object that can be copied into a MatrixBase. + * + * Besides MatrixBase-derived classes, this also includes special matrix classes such as diagonal matrices, etc. + * + * Notice that this class is trivial, it is only used to disambiguate overloaded functions. + * + * \sa \blank \ref TopicClassHierarchy + */ +template +struct EigenBase { + // typedef typename internal::plain_matrix_type::type PlainObject; + + /** \brief The interface type of indices + * \details To change this, \c \#define the preprocessor symbol \c EIGEN_DEFAULT_DENSE_INDEX_TYPE. + * \sa StorageIndex, \ref TopicPreprocessorDirectives. + * DEPRECATED: Since Eigen 3.3, its usage is deprecated. Use Eigen::Index instead. + * Deprecation is not marked with a doxygen comment because there are too many existing usages to add the deprecation + * attribute. + */ + typedef Eigen::Index Index; + + // FIXME is it needed? typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; /** \returns a reference to the derived object */ - Derived& derived() { return *static_cast(this); } + EIGEN_DEVICE_FUNC constexpr Derived& derived() { return *static_cast(this); } /** \returns a const reference to the derived object */ - const Derived& derived() const { return *static_cast(this); } + EIGEN_DEVICE_FUNC constexpr const Derived& derived() const { return *static_cast(this); } - inline Derived& const_cast_derived() const - { return *static_cast(const_cast(this)); } - inline const Derived& const_derived() const - { return *static_cast(this); } + EIGEN_DEVICE_FUNC inline constexpr Derived& const_cast_derived() const { + return *static_cast(const_cast(this)); + } + EIGEN_DEVICE_FUNC inline const Derived& const_derived() const { return *static_cast(this); } /** \returns the number of rows. \sa cols(), RowsAtCompileTime */ - inline Index rows() const { return derived().rows(); } + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return derived().rows(); } /** \returns the number of columns. \sa rows(), ColsAtCompileTime*/ - inline Index cols() const { return derived().cols(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return derived().cols(); } /** \returns the number of coefficients, which is rows()*cols(). - * \sa rows(), cols(), SizeAtCompileTime. */ - inline Index size() const { return rows() * cols(); } + * \sa rows(), cols(), SizeAtCompileTime. */ + EIGEN_DEVICE_FUNC constexpr Index size() const noexcept { return rows() * cols(); } /** \internal Don't use it, but do the equivalent: \code dst = *this; \endcode */ - template inline void evalTo(Dest& dst) const - { derived().evalTo(dst); } + template + EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const { + derived().evalTo(dst); + } /** \internal Don't use it, but do the equivalent: \code dst += *this; \endcode */ - template inline void addTo(Dest& dst) const - { + template + EIGEN_DEVICE_FUNC inline void addTo(Dest& dst) const { // This is the default implementation, // derived class can reimplement it in a more optimized way. - typename Dest::PlainObject res(rows(),cols()); + typename Dest::PlainObject res(rows(), cols()); evalTo(res); dst += res; } /** \internal Don't use it, but do the equivalent: \code dst -= *this; \endcode */ - template inline void subTo(Dest& dst) const - { + template + EIGEN_DEVICE_FUNC inline void subTo(Dest& dst) const { // This is the default implementation, // derived class can reimplement it in a more optimized way. - typename Dest::PlainObject res(rows(),cols()); + typename Dest::PlainObject res(rows(), cols()); evalTo(res); dst -= res; } /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheRight(*this); \endcode */ - template inline void applyThisOnTheRight(Dest& dst) const - { + template + EIGEN_DEVICE_FUNC inline void applyThisOnTheRight(Dest& dst) const { // This is the default implementation, // derived class can reimplement it in a more optimized way. dst = dst * this->derived(); } /** \internal Don't use it, but do the equivalent: \code dst.applyOnTheLeft(*this); \endcode */ - template inline void applyThisOnTheLeft(Dest& dst) const - { + template + EIGEN_DEVICE_FUNC inline void applyThisOnTheLeft(Dest& dst) const { // This is the default implementation, // derived class can reimplement it in a more optimized way. dst = this->derived() * dst; } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper device(Device& device); + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE DeviceWrapper device(Device& device) const; }; /*************************************************************************** -* Implementation of matrix base methods -***************************************************************************/ + * Implementation of matrix base methods + ***************************************************************************/ /** \brief Copies the generic expression \a other into *this. - * - * \details The expression must provide a (templated) evalTo(Derived& dst) const - * function which does the actual job. In practice, this allows any user to write - * its own special matrix without having to modify MatrixBase - * - * \returns a reference to *this. - */ -template -template -Derived& DenseBase::operator=(const EigenBase &other) -{ - other.derived().evalTo(derived()); + * + * \details The expression must provide a (templated) evalTo(Derived& dst) const + * function which does the actual job. In practice, this allows any user to write + * its own special matrix without having to modify MatrixBase + * + * \returns a reference to *this. + */ +template +template +EIGEN_DEVICE_FUNC Derived& DenseBase::operator=(const EigenBase& other) { + call_assignment(derived(), other.derived()); return derived(); } -template -template -Derived& DenseBase::operator+=(const EigenBase &other) -{ - other.derived().addTo(derived()); +template +template +EIGEN_DEVICE_FUNC Derived& DenseBase::operator+=(const EigenBase& other) { + call_assignment(derived(), other.derived(), internal::add_assign_op()); return derived(); } -template -template -Derived& DenseBase::operator-=(const EigenBase &other) -{ - other.derived().subTo(derived()); +template +template +EIGEN_DEVICE_FUNC Derived& DenseBase::operator-=(const EigenBase& other) { + call_assignment(derived(), other.derived(), internal::sub_assign_op()); return derived(); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_EIGENBASE_H +#endif // EIGEN_EIGENBASE_H diff --git a/inst/include/Eigen/src/Core/Fill.h b/inst/include/Eigen/src/Core/Fill.h new file mode 100644 index 00000000..779ef26a --- /dev/null +++ b/inst/include/Eigen/src/Core/Fill.h @@ -0,0 +1,138 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2024 Charles Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_FILL_H +#define EIGEN_FILL_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +template +struct eigen_fill_helper : std::false_type {}; + +template +struct eigen_fill_helper> : std::true_type {}; + +template +struct eigen_fill_helper> : std::true_type {}; + +template +struct eigen_fill_helper> : eigen_fill_helper {}; + +template +struct eigen_fill_helper> + : std::integral_constant::value && + (Xpr::IsRowMajor ? (BlockRows == 1) : (BlockCols == 1))> {}; + +template +struct eigen_fill_helper>> : eigen_fill_helper {}; + +template +struct eigen_fill_helper>> + : std::integral_constant::value && + enum_eq_not_dynamic(OuterStride_, Xpr::InnerSizeAtCompileTime)> {}; + +template +struct eigen_fill_helper>> + : eigen_fill_helper>> {}; + +template +struct eigen_fill_helper>> + : eigen_fill_helper>> {}; + +template +struct eigen_fill_helper>> + : eigen_fill_helper>> {}; + +template +struct eigen_fill_impl { + using Scalar = typename Xpr::Scalar; + using Func = scalar_constant_op; + using PlainObject = typename Xpr::PlainObject; + using Constant = typename PlainObject::ConstantReturnType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const Scalar& val) { + const Constant src(dst.rows(), dst.cols(), val); + run(dst, src); + } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const SrcXpr& src) { + call_dense_assignment_loop(dst, src, assign_op()); + } +}; + +#if EIGEN_COMP_MSVC || defined(EIGEN_GPU_COMPILE_PHASE) +template +struct eigen_fill_impl : eigen_fill_impl {}; +#else +template +struct eigen_fill_impl { + using Scalar = typename Xpr::Scalar; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const Scalar& val) { + const Scalar val_copy = val; + using std::fill_n; + fill_n(dst.data(), dst.size(), val_copy); + } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const SrcXpr& src) { + resize_if_allowed(dst, src, assign_op()); + const Scalar& val = src.functor()(); + run(dst, val); + } +}; +#endif + +template +struct eigen_memset_helper { + static constexpr bool value = + std::is_trivially_copyable::value && eigen_fill_helper::value; +}; + +template +struct eigen_zero_impl { + using Scalar = typename Xpr::Scalar; + using PlainObject = typename Xpr::PlainObject; + using Zero = typename PlainObject::ZeroReturnType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst) { + const Zero src(dst.rows(), dst.cols()); + run(dst, src); + } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void run(Xpr& dst, const SrcXpr& src) { + call_dense_assignment_loop(dst, src, assign_op()); + } +}; + +template +struct eigen_zero_impl { + using Scalar = typename Xpr::Scalar; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst) { + const std::ptrdiff_t num_bytes = dst.size() * static_cast(sizeof(Scalar)); + if (num_bytes <= 0) return; + void* dst_ptr = static_cast(dst.data()); +#ifndef EIGEN_NO_DEBUG + eigen_assert((dst_ptr != nullptr) && "null pointer dereference error!"); +#endif + EIGEN_USING_STD(memset); + memset(dst_ptr, 0, static_cast(num_bytes)); + } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Xpr& dst, const SrcXpr& src) { + resize_if_allowed(dst, src, assign_op()); + run(dst); + } +}; + +} // namespace internal +} // namespace Eigen + +#endif // EIGEN_FILL_H diff --git a/inst/include/Eigen/src/Core/FindCoeff.h b/inst/include/Eigen/src/Core/FindCoeff.h new file mode 100644 index 00000000..0102e8af --- /dev/null +++ b/inst/include/Eigen/src/Core/FindCoeff.h @@ -0,0 +1,464 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2025 Charlie Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_FIND_COEFF_H +#define EIGEN_FIND_COEFF_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +template ::IsInteger> +struct max_coeff_functor { + EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const { + return candidate > incumbent; + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const { + return pcmp_lt(incumbent, candidate); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_max(a); + } +}; + +template +struct max_coeff_functor { + EIGEN_DEVICE_FUNC inline Scalar compareCoeff(const Scalar& incumbent, const Scalar& candidate) { + return (candidate > incumbent) || ((candidate != candidate) && (incumbent == incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) { + return pandnot(pcmp_lt_or_nan(incumbent, candidate), pisnan(incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_max(a); + } +}; + +template +struct max_coeff_functor { + EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const { + return (candidate > incumbent) || ((candidate == candidate) && (incumbent != incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const { + return pandnot(pcmp_lt_or_nan(incumbent, candidate), pisnan(candidate)); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_max(a); + } +}; + +template ::IsInteger> +struct min_coeff_functor { + EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const { + return candidate < incumbent; + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const { + return pcmp_lt(candidate, incumbent); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_min(a); + } +}; + +template +struct min_coeff_functor { + EIGEN_DEVICE_FUNC inline Scalar compareCoeff(const Scalar& incumbent, const Scalar& candidate) { + return (candidate < incumbent) || ((candidate != candidate) && (incumbent == incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) { + return pandnot(pcmp_lt_or_nan(candidate, incumbent), pisnan(incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_min(a); + } +}; + +template +struct min_coeff_functor { + EIGEN_DEVICE_FUNC inline bool compareCoeff(const Scalar& incumbent, const Scalar& candidate) const { + return (candidate < incumbent) || ((candidate == candidate) && (incumbent != incumbent)); + } + template + EIGEN_DEVICE_FUNC inline Packet comparePacket(const Packet& incumbent, const Packet& candidate) const { + return pandnot(pcmp_lt_or_nan(candidate, incumbent), pisnan(candidate)); + } + template + EIGEN_DEVICE_FUNC inline Scalar predux(const Packet& a) const { + return predux_min(a); + } +}; + +template +struct min_max_traits { + static constexpr bool PacketAccess = packet_traits::Vectorizable; +}; +template +struct functor_traits> : min_max_traits {}; +template +struct functor_traits> : min_max_traits {}; + +template +struct find_coeff_loop; +template +struct find_coeff_loop { + using Scalar = typename Evaluator::Scalar; + static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& res, Index& outer, Index& inner) { + Index outerSize = eval.outerSize(); + Index innerSize = eval.innerSize(); + + /* initialization performed in calling function */ + /* result = eval.coeff(0, 0); */ + /* outer = 0; */ + /* inner = 0; */ + + for (Index j = 0; j < outerSize; j++) { + for (Index i = 0; i < innerSize; i++) { + Scalar xprCoeff = eval.coeffByOuterInner(j, i); + bool newRes = func.compareCoeff(res, xprCoeff); + if (newRes) { + outer = j; + inner = i; + res = xprCoeff; + } + } + } + } +}; +template +struct find_coeff_loop { + using Scalar = typename Evaluator::Scalar; + static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& res, Index& index) { + Index size = eval.size(); + + /* initialization performed in calling function */ + /* result = eval.coeff(0); */ + /* index = 0; */ + + for (Index k = 0; k < size; k++) { + Scalar xprCoeff = eval.coeff(k); + bool newRes = func.compareCoeff(res, xprCoeff); + if (newRes) { + index = k; + res = xprCoeff; + } + } + } +}; +template +struct find_coeff_loop { + using ScalarImpl = find_coeff_loop; + using Scalar = typename Evaluator::Scalar; + using Packet = typename Evaluator::Packet; + static constexpr int PacketSize = unpacket_traits::size; + static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& result, Index& outer, + Index& inner) { + Index outerSize = eval.outerSize(); + Index innerSize = eval.innerSize(); + Index packetEnd = numext::round_down(innerSize, PacketSize); + + /* initialization performed in calling function */ + /* result = eval.coeff(0, 0); */ + /* outer = 0; */ + /* inner = 0; */ + + bool checkPacket = false; + + for (Index j = 0; j < outerSize; j++) { + Packet resultPacket = pset1(result); + for (Index i = 0; i < packetEnd; i += PacketSize) { + Packet xprPacket = eval.template packetByOuterInner(j, i); + if (predux_any(func.comparePacket(resultPacket, xprPacket))) { + outer = j; + inner = i; + result = func.predux(xprPacket); + resultPacket = pset1(result); + checkPacket = true; + } + } + + for (Index i = packetEnd; i < innerSize; i++) { + Scalar xprCoeff = eval.coeffByOuterInner(j, i); + if (func.compareCoeff(result, xprCoeff)) { + outer = j; + inner = i; + result = xprCoeff; + checkPacket = false; + } + } + } + + if (checkPacket) { + result = eval.coeffByOuterInner(outer, inner); + Index i_end = inner + PacketSize; + for (Index i = inner; i < i_end; i++) { + Scalar xprCoeff = eval.coeffByOuterInner(outer, i); + if (func.compareCoeff(result, xprCoeff)) { + inner = i; + result = xprCoeff; + } + } + } + } +}; +template +struct find_coeff_loop { + using ScalarImpl = find_coeff_loop; + using Scalar = typename Evaluator::Scalar; + using Packet = typename Evaluator::Packet; + static constexpr int PacketSize = unpacket_traits::size; + static constexpr int Alignment = Evaluator::Alignment; + + static EIGEN_DEVICE_FUNC inline void run(const Evaluator& eval, Func& func, Scalar& result, Index& index) { + Index size = eval.size(); + Index packetEnd = numext::round_down(size, PacketSize); + + /* initialization performed in calling function */ + /* result = eval.coeff(0); */ + /* index = 0; */ + + Packet resultPacket = pset1(result); + bool checkPacket = false; + + for (Index k = 0; k < packetEnd; k += PacketSize) { + Packet xprPacket = eval.template packet(k); + if (predux_any(func.comparePacket(resultPacket, xprPacket))) { + index = k; + result = func.predux(xprPacket); + resultPacket = pset1(result); + checkPacket = true; + } + } + + for (Index k = packetEnd; k < size; k++) { + Scalar xprCoeff = eval.coeff(k); + if (func.compareCoeff(result, xprCoeff)) { + index = k; + result = xprCoeff; + checkPacket = false; + } + } + + if (checkPacket) { + result = eval.coeff(index); + Index k_end = index + PacketSize; + for (Index k = index; k < k_end; k++) { + Scalar xprCoeff = eval.coeff(k); + if (func.compareCoeff(result, xprCoeff)) { + index = k; + result = xprCoeff; + } + } + } + } +}; + +template +struct find_coeff_evaluator : public evaluator { + using Base = evaluator; + using Scalar = typename Derived::Scalar; + using Packet = typename packet_traits::type; + static constexpr int Flags = Base::Flags; + static constexpr bool IsRowMajor = bool(Flags & RowMajorBit); + EIGEN_DEVICE_FUNC inline find_coeff_evaluator(const Derived& xpr) : Base(xpr), m_xpr(xpr) {} + + EIGEN_DEVICE_FUNC inline Scalar coeffByOuterInner(Index outer, Index inner) const { + Index row = IsRowMajor ? outer : inner; + Index col = IsRowMajor ? inner : outer; + return Base::coeff(row, col); + } + template + EIGEN_DEVICE_FUNC inline PacketType packetByOuterInner(Index outer, Index inner) const { + Index row = IsRowMajor ? outer : inner; + Index col = IsRowMajor ? inner : outer; + return Base::template packet(row, col); + } + + EIGEN_DEVICE_FUNC inline Index innerSize() const { return m_xpr.innerSize(); } + EIGEN_DEVICE_FUNC inline Index outerSize() const { return m_xpr.outerSize(); } + EIGEN_DEVICE_FUNC inline Index size() const { return m_xpr.size(); } + + const Derived& m_xpr; +}; + +template +struct find_coeff_impl { + using Evaluator = find_coeff_evaluator; + static constexpr int Flags = Evaluator::Flags; + static constexpr int Alignment = Evaluator::Alignment; + static constexpr bool IsRowMajor = Derived::IsRowMajor; + static constexpr int MaxInnerSizeAtCompileTime = + IsRowMajor ? Derived::MaxColsAtCompileTime : Derived::MaxRowsAtCompileTime; + static constexpr int MaxSizeAtCompileTime = Derived::MaxSizeAtCompileTime; + + using Scalar = typename Derived::Scalar; + using Packet = typename Evaluator::Packet; + + static constexpr int PacketSize = unpacket_traits::size; + static constexpr bool Linearize = bool(Flags & LinearAccessBit); + static constexpr bool DontVectorize = + enum_lt_not_dynamic(Linearize ? MaxSizeAtCompileTime : MaxInnerSizeAtCompileTime, PacketSize); + static constexpr bool Vectorize = + !DontVectorize && bool(Flags & PacketAccessBit) && functor_traits::PacketAccess; + + using Loop = find_coeff_loop; + + template = true> + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& outer, + Index& inner) { + Evaluator eval(xpr); + Loop::run(eval, func, res, outer, inner); + } + template = true> + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& outer, + Index& inner) { + // where possible, use the linear loop and back-calculate the outer and inner indices + Index index = 0; + run(xpr, func, res, index); + outer = index / xpr.innerSize(); + inner = index % xpr.innerSize(); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(const Derived& xpr, Func& func, Scalar& res, Index& index) { + Evaluator eval(xpr); + Loop::run(eval, func, res, index); + } +}; + +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar findCoeff(const DenseBase& mat, Func& func, + IndexType* rowPtr, IndexType* colPtr) { + eigen_assert(mat.rows() > 0 && mat.cols() > 0 && "you are using an empty matrix"); + using Scalar = typename DenseBase::Scalar; + using FindCoeffImpl = internal::find_coeff_impl; + Index outer = 0; + Index inner = 0; + Scalar res = mat.coeff(0, 0); + FindCoeffImpl::run(mat.derived(), func, res, outer, inner); + *rowPtr = internal::convert_index(Derived::IsRowMajor ? outer : inner); + if (colPtr) *colPtr = internal::convert_index(Derived::IsRowMajor ? inner : outer); + return res; +} + +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar findCoeff(const DenseBase& mat, Func& func, + IndexType* indexPtr) { + eigen_assert(mat.size() > 0 && "you are using an empty matrix"); + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + using Scalar = typename DenseBase::Scalar; + using FindCoeffImpl = internal::find_coeff_impl; + Index index = 0; + Scalar res = mat.coeff(0); + FindCoeffImpl::run(mat.derived(), func, res, index); + *indexPtr = internal::convert_index(index); + return res; +} + +} // namespace internal + +/** \fn DenseBase::minCoeff(IndexType* rowId, IndexType* colId) const + * \returns the minimum of all coefficients of *this and puts in *row and *col its location. + * + * If there are multiple coefficients with the same extreme value, the location of the first instance is returned. + * + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + * + * \sa DenseBase::minCoeff(Index*), DenseBase::maxCoeff(Index*,Index*), DenseBase::visit(), DenseBase::minCoeff() + */ +template +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar DenseBase::minCoeff(IndexType* rowPtr, + IndexType* colPtr) const { + using Func = internal::min_coeff_functor; + Func func; + return internal::findCoeff(derived(), func, rowPtr, colPtr); +} + +/** \returns the minimum of all coefficients of *this and puts in *index its location. + * + * If there are multiple coefficients with the same extreme value, the location of the first instance is returned. + * + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + * + * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::visit(), + * DenseBase::minCoeff() + */ +template +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar DenseBase::minCoeff(IndexType* indexPtr) const { + using Func = internal::min_coeff_functor; + Func func; + return internal::findCoeff(derived(), func, indexPtr); +} + +/** \fn DenseBase::maxCoeff(IndexType* rowId, IndexType* colId) const + * \returns the maximum of all coefficients of *this and puts in *row and *col its location. + * + * If there are multiple coefficients with the same extreme value, the location of the first instance is returned. + * + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + * + * \sa DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visit(), DenseBase::maxCoeff() + */ +template +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar DenseBase::maxCoeff(IndexType* rowPtr, + IndexType* colPtr) const { + using Func = internal::max_coeff_functor; + Func func; + return internal::findCoeff(derived(), func, rowPtr, colPtr); +} + +/** \returns the maximum of all coefficients of *this and puts in *index its location. + * + * If there are multiple coefficients with the same extreme value, the location of the first instance is returned. + * + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + * + * \sa DenseBase::maxCoeff(IndexType*,IndexType*), DenseBase::minCoeff(IndexType*,IndexType*), DenseBase::visitor(), + * DenseBase::maxCoeff() + */ +template +template +EIGEN_DEVICE_FUNC typename internal::traits::Scalar DenseBase::maxCoeff(IndexType* indexPtr) const { + using Func = internal::max_coeff_functor; + Func func; + return internal::findCoeff(derived(), func, indexPtr); +} + +} // namespace Eigen + +#endif // EIGEN_FIND_COEFF_H diff --git a/inst/include/Eigen/src/Core/Flagged.h b/inst/include/Eigen/src/Core/Flagged.h deleted file mode 100644 index 1f2955fc..00000000 --- a/inst/include/Eigen/src/Core/Flagged.h +++ /dev/null @@ -1,140 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008 Benoit Jacob -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#ifndef EIGEN_FLAGGED_H -#define EIGEN_FLAGGED_H - -namespace Eigen { - -/** \class Flagged - * \ingroup Core_Module - * - * \brief Expression with modified flags - * - * \param ExpressionType the type of the object of which we are modifying the flags - * \param Added the flags added to the expression - * \param Removed the flags removed from the expression (has priority over Added). - * - * This class represents an expression whose flags have been modified. - * It is the return type of MatrixBase::flagged() - * and most of the time this is the only way it is used. - * - * \sa MatrixBase::flagged() - */ - -namespace internal { -template -struct traits > : traits -{ - enum { Flags = (ExpressionType::Flags | Added) & ~Removed }; -}; -} - -template class Flagged - : public MatrixBase > -{ - public: - - typedef MatrixBase Base; - - EIGEN_DENSE_PUBLIC_INTERFACE(Flagged) - typedef typename internal::conditional::ret, - ExpressionType, const ExpressionType&>::type ExpressionTypeNested; - typedef typename ExpressionType::InnerIterator InnerIterator; - - inline Flagged(const ExpressionType& matrix) : m_matrix(matrix) {} - - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } - inline Index outerStride() const { return m_matrix.outerStride(); } - inline Index innerStride() const { return m_matrix.innerStride(); } - - inline CoeffReturnType coeff(Index row, Index col) const - { - return m_matrix.coeff(row, col); - } - - inline CoeffReturnType coeff(Index index) const - { - return m_matrix.coeff(index); - } - - inline const Scalar& coeffRef(Index row, Index col) const - { - return m_matrix.const_cast_derived().coeffRef(row, col); - } - - inline const Scalar& coeffRef(Index index) const - { - return m_matrix.const_cast_derived().coeffRef(index); - } - - inline Scalar& coeffRef(Index row, Index col) - { - return m_matrix.const_cast_derived().coeffRef(row, col); - } - - inline Scalar& coeffRef(Index index) - { - return m_matrix.const_cast_derived().coeffRef(index); - } - - template - inline const PacketScalar packet(Index row, Index col) const - { - return m_matrix.template packet(row, col); - } - - template - inline void writePacket(Index row, Index col, const PacketScalar& x) - { - m_matrix.const_cast_derived().template writePacket(row, col, x); - } - - template - inline const PacketScalar packet(Index index) const - { - return m_matrix.template packet(index); - } - - template - inline void writePacket(Index index, const PacketScalar& x) - { - m_matrix.const_cast_derived().template writePacket(index, x); - } - - const ExpressionType& _expression() const { return m_matrix; } - - template - typename ExpressionType::PlainObject solveTriangular(const MatrixBase& other) const; - - template - void solveTriangularInPlace(const MatrixBase& other) const; - - protected: - ExpressionTypeNested m_matrix; -}; - -/** \returns an expression of *this with added and removed flags - * - * This is mostly for internal use. - * - * \sa class Flagged - */ -template -template -inline const Flagged -DenseBase::flagged() const -{ - return derived(); -} - -} // end namespace Eigen - -#endif // EIGEN_FLAGGED_H diff --git a/inst/include/Eigen/src/Core/ForceAlignedAccess.h b/inst/include/Eigen/src/Core/ForceAlignedAccess.h index 807c7a29..55beab35 100644 --- a/inst/include/Eigen/src/Core/ForceAlignedAccess.h +++ b/inst/include/Eigen/src/Core/ForceAlignedAccess.h @@ -10,137 +10,118 @@ #ifndef EIGEN_FORCEALIGNEDACCESS_H #define EIGEN_FORCEALIGNEDACCESS_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { /** \class ForceAlignedAccess - * \ingroup Core_Module - * - * \brief Enforce aligned packet loads and stores regardless of what is requested - * - * \param ExpressionType the type of the object of which we are forcing aligned packet access - * - * This class is the return type of MatrixBase::forceAlignedAccess() - * and most of the time this is the only way it is used. - * - * \sa MatrixBase::forceAlignedAccess() - */ + * \ingroup Core_Module + * + * \brief Enforce aligned packet loads and stores regardless of what is requested + * + * \param ExpressionType the type of the object of which we are forcing aligned packet access + * + * This class is the return type of MatrixBase::forceAlignedAccess() + * and most of the time this is the only way it is used. + * + * \sa MatrixBase::forceAlignedAccess() + */ namespace internal { -template -struct traits > : public traits -{}; -} +template +struct traits> : public traits {}; +} // namespace internal + +template +class ForceAlignedAccess : public internal::dense_xpr_base>::type { + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess) + + EIGEN_DEVICE_FUNC explicit inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {} + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return m_expression.outerStride(); } + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_expression.innerStride(); } + + EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index row, Index col) const { + return m_expression.coeff(row, col); + } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index row, Index col) { + return m_expression.const_cast_derived().coeffRef(row, col); + } + + EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const { return m_expression.coeff(index); } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index) { return m_expression.const_cast_derived().coeffRef(index); } + + template + inline const PacketScalar packet(Index row, Index col) const { + return m_expression.template packet(row, col); + } + + template + inline void writePacket(Index row, Index col, const PacketScalar& x) { + m_expression.const_cast_derived().template writePacket(row, col, x); + } + + template + inline const PacketScalar packet(Index index) const { + return m_expression.template packet(index); + } + + template + inline void writePacket(Index index, const PacketScalar& x) { + m_expression.const_cast_derived().template writePacket(index, x); + } + + EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; } + + protected: + const ExpressionType& m_expression; -template class ForceAlignedAccess - : public internal::dense_xpr_base< ForceAlignedAccess >::type -{ - public: - - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(ForceAlignedAccess) - - inline ForceAlignedAccess(const ExpressionType& matrix) : m_expression(matrix) {} - - inline Index rows() const { return m_expression.rows(); } - inline Index cols() const { return m_expression.cols(); } - inline Index outerStride() const { return m_expression.outerStride(); } - inline Index innerStride() const { return m_expression.innerStride(); } - - inline const CoeffReturnType coeff(Index row, Index col) const - { - return m_expression.coeff(row, col); - } - - inline Scalar& coeffRef(Index row, Index col) - { - return m_expression.const_cast_derived().coeffRef(row, col); - } - - inline const CoeffReturnType coeff(Index index) const - { - return m_expression.coeff(index); - } - - inline Scalar& coeffRef(Index index) - { - return m_expression.const_cast_derived().coeffRef(index); - } - - template - inline const PacketScalar packet(Index row, Index col) const - { - return m_expression.template packet(row, col); - } - - template - inline void writePacket(Index row, Index col, const PacketScalar& x) - { - m_expression.const_cast_derived().template writePacket(row, col, x); - } - - template - inline const PacketScalar packet(Index index) const - { - return m_expression.template packet(index); - } - - template - inline void writePacket(Index index, const PacketScalar& x) - { - m_expression.const_cast_derived().template writePacket(index, x); - } - - operator const ExpressionType&() const { return m_expression; } - - protected: - const ExpressionType& m_expression; - - private: - ForceAlignedAccess& operator=(const ForceAlignedAccess&); + private: + ForceAlignedAccess& operator=(const ForceAlignedAccess&); }; /** \returns an expression of *this with forced aligned access - * \sa forceAlignedAccessIf(),class ForceAlignedAccess - */ -template -inline const ForceAlignedAccess -MatrixBase::forceAlignedAccess() const -{ + * \sa forceAlignedAccessIf(),class ForceAlignedAccess + */ +template +inline const ForceAlignedAccess MatrixBase::forceAlignedAccess() const { return ForceAlignedAccess(derived()); } /** \returns an expression of *this with forced aligned access - * \sa forceAlignedAccessIf(), class ForceAlignedAccess - */ -template -inline ForceAlignedAccess -MatrixBase::forceAlignedAccess() -{ + * \sa forceAlignedAccessIf(), class ForceAlignedAccess + */ +template +inline ForceAlignedAccess MatrixBase::forceAlignedAccess() { return ForceAlignedAccess(derived()); } /** \returns an expression of *this with forced aligned access if \a Enable is true. - * \sa forceAlignedAccess(), class ForceAlignedAccess - */ -template -template -inline typename internal::add_const_on_value_type,Derived&>::type>::type -MatrixBase::forceAlignedAccessIf() const -{ - return derived(); + * \sa forceAlignedAccess(), class ForceAlignedAccess + */ +template +template +inline add_const_on_value_type_t, Derived&>> +MatrixBase::forceAlignedAccessIf() const { + return derived(); // FIXME This should not work but apparently is never used } /** \returns an expression of *this with forced aligned access if \a Enable is true. - * \sa forceAlignedAccess(), class ForceAlignedAccess - */ -template -template -inline typename internal::conditional,Derived&>::type -MatrixBase::forceAlignedAccessIf() -{ - return derived(); + * \sa forceAlignedAccess(), class ForceAlignedAccess + */ +template +template +inline std::conditional_t, Derived&> MatrixBase::forceAlignedAccessIf() { + return derived(); // FIXME This should not work but apparently is never used } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_FORCEALIGNEDACCESS_H +#endif // EIGEN_FORCEALIGNEDACCESS_H diff --git a/inst/include/Eigen/src/Core/Functors.h b/inst/include/Eigen/src/Core/Functors.h deleted file mode 100644 index 5f14c658..00000000 --- a/inst/include/Eigen/src/Core/Functors.h +++ /dev/null @@ -1,1026 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2008-2010 Gael Guennebaud -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#ifndef EIGEN_FUNCTORS_H -#define EIGEN_FUNCTORS_H - -namespace Eigen { - -namespace internal { - -// associative functors: - -/** \internal - * \brief Template functor to compute the sum of two scalars - * - * \sa class CwiseBinaryOp, MatrixBase::operator+, class VectorwiseOp, MatrixBase::sum() - */ -template struct scalar_sum_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_sum_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a + b; } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::padd(a,b); } - template - EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const - { return internal::predux(a); } -}; -template -struct functor_traits > { - enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasAdd - }; -}; - -/** \internal - * \brief Template functor to compute the product of two scalars - * - * \sa class CwiseBinaryOp, Cwise::operator*(), class VectorwiseOp, MatrixBase::redux() - */ -template struct scalar_product_op { - enum { - // TODO vectorize mixed product - Vectorizable = is_same::value && packet_traits::HasMul && packet_traits::HasMul - }; - typedef typename scalar_product_traits::ReturnType result_type; - EIGEN_EMPTY_STRUCT_CTOR(scalar_product_op) - EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a * b; } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::pmul(a,b); } - template - EIGEN_STRONG_INLINE const result_type predux(const Packet& a) const - { return internal::predux_mul(a); } -}; -template -struct functor_traits > { - enum { - Cost = (NumTraits::MulCost + NumTraits::MulCost)/2, // rough estimate! - PacketAccess = scalar_product_op::Vectorizable - }; -}; - -/** \internal - * \brief Template functor to compute the conjugate product of two scalars - * - * This is a short cut for conj(x) * y which is needed for optimization purpose; in Eigen2 support mode, this becomes x * conj(y) - */ -template struct scalar_conj_product_op { - - enum { - Conj = NumTraits::IsComplex - }; - - typedef typename scalar_product_traits::ReturnType result_type; - - EIGEN_EMPTY_STRUCT_CTOR(scalar_conj_product_op) - EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const - { return conj_helper().pmul(a,b); } - - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return conj_helper().pmul(a,b); } -}; -template -struct functor_traits > { - enum { - Cost = NumTraits::MulCost, - PacketAccess = internal::is_same::value && packet_traits::HasMul - }; -}; - -/** \internal - * \brief Template functor to compute the min of two scalars - * - * \sa class CwiseBinaryOp, MatrixBase::cwiseMin, class VectorwiseOp, MatrixBase::minCoeff() - */ -template struct scalar_min_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_min_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::min; return (min)(a, b); } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::pmin(a,b); } - template - EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const - { return internal::predux_min(a); } -}; -template -struct functor_traits > { - enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasMin - }; -}; - -/** \internal - * \brief Template functor to compute the max of two scalars - * - * \sa class CwiseBinaryOp, MatrixBase::cwiseMax, class VectorwiseOp, MatrixBase::maxCoeff() - */ -template struct scalar_max_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_max_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { using std::max; return (max)(a, b); } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::pmax(a,b); } - template - EIGEN_STRONG_INLINE const Scalar predux(const Packet& a) const - { return internal::predux_max(a); } -}; -template -struct functor_traits > { - enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasMax - }; -}; - -/** \internal - * \brief Template functor to compute the hypot of two scalars - * - * \sa MatrixBase::stableNorm(), class Redux - */ -template struct scalar_hypot_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_hypot_op) -// typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& _x, const Scalar& _y) const - { - using std::max; - using std::min; - using std::sqrt; - Scalar p = (max)(_x, _y); - Scalar q = (min)(_x, _y); - Scalar qp = q/p; - return p * sqrt(Scalar(1) + qp*qp); - } -}; -template -struct functor_traits > { - enum { Cost = 5 * NumTraits::MulCost, PacketAccess=0 }; -}; - -/** \internal - * \brief Template functor to compute the pow of two scalars - */ -template struct scalar_binary_pow_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_binary_pow_op) - inline Scalar operator() (const Scalar& a, const OtherScalar& b) const { return numext::pow(a, b); } -}; -template -struct functor_traits > { - enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false }; -}; - -// other binary functors: - -/** \internal - * \brief Template functor to compute the difference of two scalars - * - * \sa class CwiseBinaryOp, MatrixBase::operator- - */ -template struct scalar_difference_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_difference_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a, const Scalar& b) const { return a - b; } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::psub(a,b); } -}; -template -struct functor_traits > { - enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasSub - }; -}; - -/** \internal - * \brief Template functor to compute the quotient of two scalars - * - * \sa class CwiseBinaryOp, Cwise::operator/() - */ -template struct scalar_quotient_op { - enum { - // TODO vectorize mixed product - Vectorizable = is_same::value && packet_traits::HasDiv && packet_traits::HasDiv - }; - typedef typename scalar_product_traits::ReturnType result_type; - EIGEN_EMPTY_STRUCT_CTOR(scalar_quotient_op) - EIGEN_STRONG_INLINE const result_type operator() (const LhsScalar& a, const RhsScalar& b) const { return a / b; } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a, const Packet& b) const - { return internal::pdiv(a,b); } -}; -template -struct functor_traits > { - enum { - Cost = (NumTraits::MulCost + NumTraits::MulCost), // rough estimate! - PacketAccess = scalar_quotient_op::Vectorizable - }; -}; - - - -/** \internal - * \brief Template functor to compute the and of two booleans - * - * \sa class CwiseBinaryOp, ArrayBase::operator&& - */ -struct scalar_boolean_and_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_and_op) - EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a && b; } -}; -template<> struct functor_traits { - enum { - Cost = NumTraits::AddCost, - PacketAccess = false - }; -}; - -/** \internal - * \brief Template functor to compute the or of two booleans - * - * \sa class CwiseBinaryOp, ArrayBase::operator|| - */ -struct scalar_boolean_or_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_boolean_or_op) - EIGEN_STRONG_INLINE bool operator() (const bool& a, const bool& b) const { return a || b; } -}; -template<> struct functor_traits { - enum { - Cost = NumTraits::AddCost, - PacketAccess = false - }; -}; - -/** \internal - * \brief Template functors for comparison of two scalars - * \todo Implement packet-comparisons - */ -template struct scalar_cmp_op; - -template -struct functor_traits > { - enum { - Cost = NumTraits::AddCost, - PacketAccess = false - }; -}; - -template -struct result_of(Scalar,Scalar)> { - typedef bool type; -}; - - -template struct scalar_cmp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op) - EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a==b;} -}; -template struct scalar_cmp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op) - EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a struct scalar_cmp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op) - EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a<=b;} -}; -template struct scalar_cmp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op) - EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return !(a<=b || b<=a);} -}; -template struct scalar_cmp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cmp_op) - EIGEN_STRONG_INLINE bool operator()(const Scalar& a, const Scalar& b) const {return a!=b;} -}; - -// unary functors: - -/** \internal - * \brief Template functor to compute the opposite of a scalar - * - * \sa class CwiseUnaryOp, MatrixBase::operator- - */ -template struct scalar_opposite_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_opposite_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { return -a; } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const - { return internal::pnegate(a); } -}; -template -struct functor_traits > -{ enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasNegate }; -}; - -/** \internal - * \brief Template functor to compute the absolute value of a scalar - * - * \sa class CwiseUnaryOp, Cwise::abs - */ -template struct scalar_abs_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_abs_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { using std::abs; return abs(a); } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const - { return internal::pabs(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = NumTraits::AddCost, - PacketAccess = packet_traits::HasAbs - }; -}; - -/** \internal - * \brief Template functor to compute the squared absolute value of a scalar - * - * \sa class CwiseUnaryOp, Cwise::abs2 - */ -template struct scalar_abs2_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_abs2_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE const result_type operator() (const Scalar& a) const { return numext::abs2(a); } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const - { return internal::pmul(a,a); } -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = packet_traits::HasAbs2 }; }; - -/** \internal - * \brief Template functor to compute the conjugate of a complex value - * - * \sa class CwiseUnaryOp, MatrixBase::conjugate() - */ -template struct scalar_conjugate_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_conjugate_op) - EIGEN_STRONG_INLINE const Scalar operator() (const Scalar& a) const { using numext::conj; return conj(a); } - template - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const { return internal::pconj(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = NumTraits::IsComplex ? NumTraits::AddCost : 0, - PacketAccess = packet_traits::HasConj - }; -}; - -/** \internal - * \brief Template functor to cast a scalar to another type - * - * \sa class CwiseUnaryOp, MatrixBase::cast() - */ -template -struct scalar_cast_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cast_op) - typedef NewType result_type; - EIGEN_STRONG_INLINE const NewType operator() (const Scalar& a) const { return cast(a); } -}; -template -struct functor_traits > -{ enum { Cost = is_same::value ? 0 : NumTraits::AddCost, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to extract the real part of a complex - * - * \sa class CwiseUnaryOp, MatrixBase::real() - */ -template -struct scalar_real_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_real_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::real(a); } -}; -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to extract the imaginary part of a complex - * - * \sa class CwiseUnaryOp, MatrixBase::imag() - */ -template -struct scalar_imag_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type operator() (const Scalar& a) const { return numext::imag(a); } -}; -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to extract the real part of a complex as a reference - * - * \sa class CwiseUnaryOp, MatrixBase::real() - */ -template -struct scalar_real_ref_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_real_ref_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::real_ref(*const_cast(&a)); } -}; -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to extract the imaginary part of a complex as a reference - * - * \sa class CwiseUnaryOp, MatrixBase::imag() - */ -template -struct scalar_imag_ref_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_imag_ref_op) - typedef typename NumTraits::Real result_type; - EIGEN_STRONG_INLINE result_type& operator() (const Scalar& a) const { return numext::imag_ref(*const_cast(&a)); } -}; -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -/** \internal - * - * \brief Template functor to compute the exponential of a scalar - * - * \sa class CwiseUnaryOp, Cwise::exp() - */ -template struct scalar_exp_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_exp_op) - inline const Scalar operator() (const Scalar& a) const { using std::exp; return exp(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::pexp(a); } -}; -template -struct functor_traits > -{ enum { Cost = 5 * NumTraits::MulCost, PacketAccess = packet_traits::HasExp }; }; - -/** \internal - * - * \brief Template functor to compute the logarithm of a scalar - * - * \sa class CwiseUnaryOp, Cwise::log() - */ -template struct scalar_log_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_log_op) - inline const Scalar operator() (const Scalar& a) const { using std::log; return log(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::plog(a); } -}; -template -struct functor_traits > -{ enum { Cost = 5 * NumTraits::MulCost, PacketAccess = packet_traits::HasLog }; }; - -/** \internal - * \brief Template functor to multiply a scalar by a fixed other one - * - * \sa class CwiseUnaryOp, MatrixBase::operator*, MatrixBase::operator/ - */ -/* NOTE why doing the pset1() in packetOp *is* an optimization ? - * indeed it seems better to declare m_other as a Packet and do the pset1() once - * in the constructor. However, in practice: - * - GCC does not like m_other as a Packet and generate a load every time it needs it - * - on the other hand GCC is able to moves the pset1() outside the loop :) - * - simpler code ;) - * (ICC and gcc 4.4 seems to perform well in both cases, the issue is visible with y = a*x + b*y) - */ -template -struct scalar_multiple_op { - typedef typename packet_traits::type Packet; - // FIXME default copy constructors seems bugged with std::complex<> - EIGEN_STRONG_INLINE scalar_multiple_op(const scalar_multiple_op& other) : m_other(other.m_other) { } - EIGEN_STRONG_INLINE scalar_multiple_op(const Scalar& other) : m_other(other) { } - EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a * m_other; } - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const - { return internal::pmul(a, pset1(m_other)); } - typename add_const_on_value_type::Nested>::type m_other; -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = packet_traits::HasMul }; }; - -template -struct scalar_multiple2_op { - typedef typename scalar_product_traits::ReturnType result_type; - EIGEN_STRONG_INLINE scalar_multiple2_op(const scalar_multiple2_op& other) : m_other(other.m_other) { } - EIGEN_STRONG_INLINE scalar_multiple2_op(const Scalar2& other) : m_other(other) { } - EIGEN_STRONG_INLINE result_type operator() (const Scalar1& a) const { return a * m_other; } - typename add_const_on_value_type::Nested>::type m_other; -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to divide a scalar by a fixed other one - * - * This functor is used to implement the quotient of a matrix by - * a scalar where the scalar type is not necessarily a floating point type. - * - * \sa class CwiseUnaryOp, MatrixBase::operator/ - */ -template -struct scalar_quotient1_op { - typedef typename packet_traits::type Packet; - // FIXME default copy constructors seems bugged with std::complex<> - EIGEN_STRONG_INLINE scalar_quotient1_op(const scalar_quotient1_op& other) : m_other(other.m_other) { } - EIGEN_STRONG_INLINE scalar_quotient1_op(const Scalar& other) : m_other(other) {} - EIGEN_STRONG_INLINE Scalar operator() (const Scalar& a) const { return a / m_other; } - EIGEN_STRONG_INLINE const Packet packetOp(const Packet& a) const - { return internal::pdiv(a, pset1(m_other)); } - typename add_const_on_value_type::Nested>::type m_other; -}; -template -struct functor_traits > -{ enum { Cost = 2 * NumTraits::MulCost, PacketAccess = packet_traits::HasDiv }; }; - -// nullary functors - -template -struct scalar_constant_op { - typedef typename packet_traits::type Packet; - EIGEN_STRONG_INLINE scalar_constant_op(const scalar_constant_op& other) : m_other(other.m_other) { } - EIGEN_STRONG_INLINE scalar_constant_op(const Scalar& other) : m_other(other) { } - template - EIGEN_STRONG_INLINE const Scalar operator() (Index, Index = 0) const { return m_other; } - template - EIGEN_STRONG_INLINE const Packet packetOp(Index, Index = 0) const { return internal::pset1(m_other); } - const Scalar m_other; -}; -template -struct functor_traits > -// FIXME replace this packet test by a safe one -{ enum { Cost = 1, PacketAccess = packet_traits::Vectorizable, IsRepeatable = true }; }; - -template struct scalar_identity_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_identity_op) - template - EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const { return row==col ? Scalar(1) : Scalar(0); } -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::AddCost, PacketAccess = false, IsRepeatable = true }; }; - -template struct linspaced_op_impl; - -// linear access for packet ops: -// 1) initialization -// base = [low, ..., low] + ([step, ..., step] * [-size, ..., 0]) -// 2) each step (where size is 1 for coeff access or PacketSize for packet access) -// base += [size*step, ..., size*step] -// -// TODO: Perhaps it's better to initialize lazily (so not in the constructor but in packetOp) -// in order to avoid the padd() in operator() ? -template -struct linspaced_op_impl -{ - typedef typename packet_traits::type Packet; - - linspaced_op_impl(const Scalar& low, const Scalar& step) : - m_low(low), m_step(step), - m_packetStep(pset1(packet_traits::size*step)), - m_base(padd(pset1(low), pmul(pset1(step),plset(-packet_traits::size)))) {} - - template - EIGEN_STRONG_INLINE const Scalar operator() (Index i) const - { - m_base = padd(m_base, pset1(m_step)); - return m_low+Scalar(i)*m_step; - } - - template - EIGEN_STRONG_INLINE const Packet packetOp(Index) const { return m_base = padd(m_base,m_packetStep); } - - const Scalar m_low; - const Scalar m_step; - const Packet m_packetStep; - mutable Packet m_base; -}; - -// random access for packet ops: -// 1) each step -// [low, ..., low] + ( [step, ..., step] * ( [i, ..., i] + [0, ..., size] ) ) -template -struct linspaced_op_impl -{ - typedef typename packet_traits::type Packet; - - linspaced_op_impl(const Scalar& low, const Scalar& step) : - m_low(low), m_step(step), - m_lowPacket(pset1(m_low)), m_stepPacket(pset1(m_step)), m_interPacket(plset(0)) {} - - template - EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return m_low+i*m_step; } - - template - EIGEN_STRONG_INLINE const Packet packetOp(Index i) const - { return internal::padd(m_lowPacket, pmul(m_stepPacket, padd(pset1(Scalar(i)),m_interPacket))); } - - const Scalar m_low; - const Scalar m_step; - const Packet m_lowPacket; - const Packet m_stepPacket; - const Packet m_interPacket; -}; - -// ----- Linspace functor ---------------------------------------------------------------- - -// Forward declaration (we default to random access which does not really give -// us a speed gain when using packet access but it allows to use the functor in -// nested expressions). -template struct linspaced_op; -template struct functor_traits< linspaced_op > -{ enum { Cost = 1, PacketAccess = packet_traits::HasSetLinear, IsRepeatable = true }; }; -template struct linspaced_op -{ - typedef typename packet_traits::type Packet; - linspaced_op(const Scalar& low, const Scalar& high, DenseIndex num_steps) : impl((num_steps==1 ? high : low), (num_steps==1 ? Scalar() : (high-low)/Scalar(num_steps-1))) {} - - template - EIGEN_STRONG_INLINE const Scalar operator() (Index i) const { return impl(i); } - - // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since - // there row==0 and col is used for the actual iteration. - template - EIGEN_STRONG_INLINE const Scalar operator() (Index row, Index col) const - { - eigen_assert(col==0 || row==0); - return impl(col + row); - } - - template - EIGEN_STRONG_INLINE const Packet packetOp(Index i) const { return impl.packetOp(i); } - - // We need this function when assigning e.g. a RowVectorXd to a MatrixXd since - // there row==0 and col is used for the actual iteration. - template - EIGEN_STRONG_INLINE const Packet packetOp(Index row, Index col) const - { - eigen_assert(col==0 || row==0); - return impl.packetOp(col + row); - } - - // This proxy object handles the actual required temporaries, the different - // implementations (random vs. sequential access) as well as the - // correct piping to size 2/4 packet operations. - const linspaced_op_impl impl; -}; - -// all functors allow linear access, except scalar_identity_op. So we fix here a quick meta -// to indicate whether a functor allows linear access, just always answering 'yes' except for -// scalar_identity_op. -// FIXME move this to functor_traits adding a functor_default -template struct functor_has_linear_access { enum { ret = 1 }; }; -template struct functor_has_linear_access > { enum { ret = 0 }; }; - -// In Eigen, any binary op (Product, CwiseBinaryOp) require the Lhs and Rhs to have the same scalar type, except for multiplication -// where the mixing of different types is handled by scalar_product_traits -// In particular, real * complex is allowed. -// FIXME move this to functor_traits adding a functor_default -template struct functor_is_product_like { enum { ret = 0 }; }; -template struct functor_is_product_like > { enum { ret = 1 }; }; -template struct functor_is_product_like > { enum { ret = 1 }; }; -template struct functor_is_product_like > { enum { ret = 1 }; }; - - -/** \internal - * \brief Template functor to add a scalar to a fixed other one - * \sa class CwiseUnaryOp, Array::operator+ - */ -/* If you wonder why doing the pset1() in packetOp() is an optimization check scalar_multiple_op */ -template -struct scalar_add_op { - typedef typename packet_traits::type Packet; - // FIXME default copy constructors seems bugged with std::complex<> - inline scalar_add_op(const scalar_add_op& other) : m_other(other.m_other) { } - inline scalar_add_op(const Scalar& other) : m_other(other) { } - inline Scalar operator() (const Scalar& a) const { return a + m_other; } - inline const Packet packetOp(const Packet& a) const - { return internal::padd(a, pset1(m_other)); } - const Scalar m_other; -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::AddCost, PacketAccess = packet_traits::HasAdd }; }; - -/** \internal - * \brief Template functor to compute the square root of a scalar - * \sa class CwiseUnaryOp, Cwise::sqrt() - */ -template struct scalar_sqrt_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_sqrt_op) - inline const Scalar operator() (const Scalar& a) const { using std::sqrt; return sqrt(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::psqrt(a); } -}; -template -struct functor_traits > -{ enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasSqrt - }; -}; - -/** \internal - * \brief Template functor to compute the cosine of a scalar - * \sa class CwiseUnaryOp, ArrayBase::cos() - */ -template struct scalar_cos_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cos_op) - inline Scalar operator() (const Scalar& a) const { using std::cos; return cos(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::pcos(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasCos - }; -}; - -/** \internal - * \brief Template functor to compute the sine of a scalar - * \sa class CwiseUnaryOp, ArrayBase::sin() - */ -template struct scalar_sin_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_sin_op) - inline const Scalar operator() (const Scalar& a) const { using std::sin; return sin(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::psin(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasSin - }; -}; - - -/** \internal - * \brief Template functor to compute the tan of a scalar - * \sa class CwiseUnaryOp, ArrayBase::tan() - */ -template struct scalar_tan_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_tan_op) - inline const Scalar operator() (const Scalar& a) const { using std::tan; return tan(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::ptan(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasTan - }; -}; - -/** \internal - * \brief Template functor to compute the arc cosine of a scalar - * \sa class CwiseUnaryOp, ArrayBase::acos() - */ -template struct scalar_acos_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_acos_op) - inline const Scalar operator() (const Scalar& a) const { using std::acos; return acos(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::pacos(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasACos - }; -}; - -/** \internal - * \brief Template functor to compute the arc sine of a scalar - * \sa class CwiseUnaryOp, ArrayBase::asin() - */ -template struct scalar_asin_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_asin_op) - inline const Scalar operator() (const Scalar& a) const { using std::asin; return asin(a); } - typedef typename packet_traits::type Packet; - inline Packet packetOp(const Packet& a) const { return internal::pasin(a); } -}; -template -struct functor_traits > -{ - enum { - Cost = 5 * NumTraits::MulCost, - PacketAccess = packet_traits::HasASin - }; -}; - -/** \internal - * \brief Template functor to raise a scalar to a power - * \sa class CwiseUnaryOp, Cwise::pow - */ -template -struct scalar_pow_op { - // FIXME default copy constructors seems bugged with std::complex<> - inline scalar_pow_op(const scalar_pow_op& other) : m_exponent(other.m_exponent) { } - inline scalar_pow_op(const Scalar& exponent) : m_exponent(exponent) {} - inline Scalar operator() (const Scalar& a) const { return numext::pow(a, m_exponent); } - const Scalar m_exponent; -}; -template -struct functor_traits > -{ enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false }; }; - -/** \internal - * \brief Template functor to compute the quotient between a scalar and array entries. - * \sa class CwiseUnaryOp, Cwise::inverse() - */ -template -struct scalar_inverse_mult_op { - scalar_inverse_mult_op(const Scalar& other) : m_other(other) {} - inline Scalar operator() (const Scalar& a) const { return m_other / a; } - template - inline const Packet packetOp(const Packet& a) const - { return internal::pdiv(pset1(m_other),a); } - Scalar m_other; -}; - -/** \internal - * \brief Template functor to compute the inverse of a scalar - * \sa class CwiseUnaryOp, Cwise::inverse() - */ -template -struct scalar_inverse_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_inverse_op) - inline Scalar operator() (const Scalar& a) const { return Scalar(1)/a; } - template - inline const Packet packetOp(const Packet& a) const - { return internal::pdiv(pset1(Scalar(1)),a); } -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = packet_traits::HasDiv }; }; - -/** \internal - * \brief Template functor to compute the square of a scalar - * \sa class CwiseUnaryOp, Cwise::square() - */ -template -struct scalar_square_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_square_op) - inline Scalar operator() (const Scalar& a) const { return a*a; } - template - inline const Packet packetOp(const Packet& a) const - { return internal::pmul(a,a); } -}; -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = packet_traits::HasMul }; }; - -/** \internal - * \brief Template functor to compute the cube of a scalar - * \sa class CwiseUnaryOp, Cwise::cube() - */ -template -struct scalar_cube_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_cube_op) - inline Scalar operator() (const Scalar& a) const { return a*a*a; } - template - inline const Packet packetOp(const Packet& a) const - { return internal::pmul(a,pmul(a,a)); } -}; -template -struct functor_traits > -{ enum { Cost = 2*NumTraits::MulCost, PacketAccess = packet_traits::HasMul }; }; - -// default functor traits for STL functors: - -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = NumTraits::MulCost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = NumTraits::AddCost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = NumTraits::AddCost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = NumTraits::AddCost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = functor_traits::Cost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = functor_traits::Cost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1 + functor_traits::Cost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 1 + functor_traits::Cost, PacketAccess = false }; }; - -#ifdef EIGEN_STDEXT_SUPPORT - -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = 0, PacketAccess = false }; }; - -template -struct functor_traits > > -{ enum { Cost = 0, PacketAccess = false }; }; - -template -struct functor_traits > > -{ enum { Cost = 0, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = functor_traits::Cost + functor_traits::Cost, PacketAccess = false }; }; - -template -struct functor_traits > -{ enum { Cost = functor_traits::Cost + functor_traits::Cost + functor_traits::Cost, PacketAccess = false }; }; - -#endif // EIGEN_STDEXT_SUPPORT - -// allow to add new functors and specializations of functor_traits from outside Eigen. -// this macro is really needed because functor_traits must be specialized after it is declared but before it is used... -#ifdef EIGEN_FUNCTORS_PLUGIN -#include EIGEN_FUNCTORS_PLUGIN -#endif - -} // end namespace internal - -} // end namespace Eigen - -#endif // EIGEN_FUNCTORS_H diff --git a/inst/include/Eigen/src/Core/Fuzzy.h b/inst/include/Eigen/src/Core/Fuzzy.h index fe63bd29..ed6b4ffe 100644 --- a/inst/include/Eigen/src/Core/Fuzzy.h +++ b/inst/include/Eigen/src/Core/Fuzzy.h @@ -11,140 +11,122 @@ #ifndef EIGEN_FUZZY_H #define EIGEN_FUZZY_H -namespace Eigen { - -namespace internal -{ - -template::IsInteger> -struct isApprox_selector -{ - static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) - { - using std::min; - typename internal::nested::type nested(x); - typename internal::nested::type otherNested(y); - return (nested - otherNested).cwiseAbs2().sum() <= prec * prec * (min)(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +template ::IsInteger> +struct isApprox_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) { + typename internal::nested_eval::type nested(x); + typename internal::nested_eval::type otherNested(y); + return (nested.matrix() - otherNested.matrix()).cwiseAbs2().sum() <= + prec * prec * numext::mini(nested.cwiseAbs2().sum(), otherNested.cwiseAbs2().sum()); } }; -template -struct isApprox_selector -{ - static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&) - { +template +struct isApprox_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar&) { return x.matrix() == y.matrix(); } }; -template::IsInteger> -struct isMuchSmallerThan_object_selector -{ - static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) - { +template ::IsInteger> +struct isMuchSmallerThan_object_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived& y, const typename Derived::RealScalar& prec) { return x.cwiseAbs2().sum() <= numext::abs2(prec) * y.cwiseAbs2().sum(); } }; -template -struct isMuchSmallerThan_object_selector -{ - static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&) - { +template +struct isMuchSmallerThan_object_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const OtherDerived&, const typename Derived::RealScalar&) { return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); } }; -template::IsInteger> -struct isMuchSmallerThan_scalar_selector -{ - static bool run(const Derived& x, const typename Derived::RealScalar& y, const typename Derived::RealScalar& prec) - { +template ::IsInteger> +struct isMuchSmallerThan_scalar_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const typename Derived::RealScalar& y, + const typename Derived::RealScalar& prec) { return x.cwiseAbs2().sum() <= numext::abs2(prec * y); } }; -template -struct isMuchSmallerThan_scalar_selector -{ - static bool run(const Derived& x, const typename Derived::RealScalar&, const typename Derived::RealScalar&) - { +template +struct isMuchSmallerThan_scalar_selector { + EIGEN_DEVICE_FUNC static bool run(const Derived& x, const typename Derived::RealScalar&, + const typename Derived::RealScalar&) { return x.matrix() == Derived::Zero(x.rows(), x.cols()).matrix(); } }; -} // end namespace internal - +} // end namespace internal /** \returns \c true if \c *this is approximately equal to \a other, within the precision - * determined by \a prec. - * - * \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$ - * are considered to be approximately equal within precision \f$ p \f$ if - * \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f] - * For matrices, the comparison is done using the Hilbert-Schmidt norm (aka Frobenius norm - * L2 norm). - * - * \note Because of the multiplicativeness of this comparison, one can't use this function - * to check whether \c *this is approximately equal to the zero matrix or vector. - * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix - * or vector. If you want to test whether \c *this is zero, use internal::isMuchSmallerThan(const - * RealScalar&, RealScalar) instead. - * - * \sa internal::isMuchSmallerThan(const RealScalar&, RealScalar) const - */ -template -template -bool DenseBase::isApprox( - const DenseBase& other, - const RealScalar& prec -) const -{ + * determined by \a prec. + * + * \note The fuzzy compares are done multiplicatively. Two vectors \f$ v \f$ and \f$ w \f$ + * are considered to be approximately equal within precision \f$ p \f$ if + * \f[ \Vert v - w \Vert \leqslant p\,\min(\Vert v\Vert, \Vert w\Vert). \f] + * For matrices, the comparison is done using the Hilbert-Schmidt norm (aka Frobenius norm + * L2 norm). + * + * \note Because of the multiplicativeness of this comparison, one can't use this function + * to check whether \c *this is approximately equal to the zero matrix or vector. + * Indeed, \c isApprox(zero) returns false unless \c *this itself is exactly the zero matrix + * or vector. If you want to test whether \c *this is zero, use internal::isMuchSmallerThan(const + * RealScalar&, RealScalar) instead. + * + * \sa internal::isMuchSmallerThan(const RealScalar&, RealScalar) const + */ +template +template +EIGEN_DEVICE_FUNC bool DenseBase::isApprox(const DenseBase& other, + const RealScalar& prec) const { return internal::isApprox_selector::run(derived(), other.derived(), prec); } /** \returns \c true if the norm of \c *this is much smaller than \a other, - * within the precision determined by \a prec. - * - * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is - * considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if - * \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f] - * - * For matrices, the comparison is done using the Hilbert-Schmidt norm. For this reason, - * the value of the reference scalar \a other should come from the Hilbert-Schmidt norm - * of a reference matrix of same dimensions. - * - * \sa isApprox(), isMuchSmallerThan(const DenseBase&, RealScalar) const - */ -template -bool DenseBase::isMuchSmallerThan( - const typename NumTraits::Real& other, - const RealScalar& prec -) const -{ + * within the precision determined by \a prec. + * + * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is + * considered to be much smaller than \f$ x \f$ within precision \f$ p \f$ if + * \f[ \Vert v \Vert \leqslant p\,\vert x\vert. \f] + * + * For matrices, the comparison is done using the Hilbert-Schmidt norm. For this reason, + * the value of the reference scalar \a other should come from the Hilbert-Schmidt norm + * of a reference matrix of same dimensions. + * + * \sa isApprox(), isMuchSmallerThan(const DenseBase&, RealScalar) const + */ +template +EIGEN_DEVICE_FUNC bool DenseBase::isMuchSmallerThan(const typename NumTraits::Real& other, + const RealScalar& prec) const { return internal::isMuchSmallerThan_scalar_selector::run(derived(), other, prec); } /** \returns \c true if the norm of \c *this is much smaller than the norm of \a other, - * within the precision determined by \a prec. - * - * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is - * considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if - * \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f] - * For matrices, the comparison is done using the Hilbert-Schmidt norm. - * - * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const - */ -template -template -bool DenseBase::isMuchSmallerThan( - const DenseBase& other, - const RealScalar& prec -) const -{ + * within the precision determined by \a prec. + * + * \note The fuzzy compares are done multiplicatively. A vector \f$ v \f$ is + * considered to be much smaller than a vector \f$ w \f$ within precision \f$ p \f$ if + * \f[ \Vert v \Vert \leqslant p\,\Vert w\Vert. \f] + * For matrices, the comparison is done using the Hilbert-Schmidt norm. + * + * \sa isApprox(), isMuchSmallerThan(const RealScalar&, RealScalar) const + */ +template +template +EIGEN_DEVICE_FUNC bool DenseBase::isMuchSmallerThan(const DenseBase& other, + const RealScalar& prec) const { return internal::isMuchSmallerThan_object_selector::run(derived(), other.derived(), prec); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_FUZZY_H +#endif // EIGEN_FUZZY_H diff --git a/inst/include/Eigen/src/Core/GeneralProduct.h b/inst/include/Eigen/src/Core/GeneralProduct.h index 0eae5299..e4c51d2a 100644 --- a/inst/include/Eigen/src/Core/GeneralProduct.h +++ b/inst/include/Eigen/src/Core/GeneralProduct.h @@ -11,174 +11,187 @@ #ifndef EIGEN_GENERAL_PRODUCT_H #define EIGEN_GENERAL_PRODUCT_H -namespace Eigen { - -/** \class GeneralProduct - * \ingroup Core_Module - * - * \brief Expression of the product of two general matrices or vectors - * - * \param LhsNested the type used to store the left-hand side - * \param RhsNested the type used to store the right-hand side - * \param ProductMode the type of the product - * - * This class represents an expression of the product of two general matrices. - * We call a general matrix, a dense matrix with full storage. For instance, - * This excludes triangular, selfadjoint, and sparse matrices. - * It is the return type of the operator* between general matrices. Its template - * arguments are determined automatically by ProductReturnType. Therefore, - * GeneralProduct should never be used direclty. To determine the result type of a - * function which involves a matrix product, use ProductReturnType::Type. - * - * \sa ProductReturnType, MatrixBase::operator*(const MatrixBase&) - */ -template::value> -class GeneralProduct; - -enum { - Large = 2, - Small = 3 -}; +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +enum { Large = 2, Small = 3 }; + +// Define the threshold value to fallback from the generic matrix-matrix product +// implementation (heavy) to the lightweight coeff-based product one. +// See generic_product_impl +// in products/GeneralMatrixMatrix.h for more details. +// TODO This threshold should also be used in the compile-time selector below. +#ifndef EIGEN_GEMM_TO_COEFFBASED_THRESHOLD +// This default value has been obtained on a Haswell architecture. +#define EIGEN_GEMM_TO_COEFFBASED_THRESHOLD 20 +#endif namespace internal { -template struct product_type_selector; +template +struct product_type_selector; -template struct product_size_category -{ - enum { is_large = MaxSize == Dynamic || - Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD, - value = is_large ? Large - : Size == 1 ? 1 - : Small +template +struct product_size_category { + enum { +#ifndef EIGEN_GPU_COMPILE_PHASE + is_large = MaxSize == Dynamic || Size >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD || + (Size == Dynamic && MaxSize >= EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD), +#else + is_large = 0, +#endif + value = is_large ? Large + : Size == 1 ? 1 + : Small }; }; -template struct product_type -{ - typedef typename remove_all::type _Lhs; - typedef typename remove_all::type _Rhs; +template +struct product_type { + typedef remove_all_t Lhs_; + typedef remove_all_t Rhs_; enum { - MaxRows = _Lhs::MaxRowsAtCompileTime, - Rows = _Lhs::RowsAtCompileTime, - MaxCols = _Rhs::MaxColsAtCompileTime, - Cols = _Rhs::ColsAtCompileTime, - MaxDepth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::MaxColsAtCompileTime, - _Rhs::MaxRowsAtCompileTime), - Depth = EIGEN_SIZE_MIN_PREFER_FIXED(_Lhs::ColsAtCompileTime, - _Rhs::RowsAtCompileTime), - LargeThreshold = EIGEN_CACHEFRIENDLY_PRODUCT_THRESHOLD + MaxRows = traits::MaxRowsAtCompileTime, + Rows = traits::RowsAtCompileTime, + MaxCols = traits::MaxColsAtCompileTime, + Cols = traits::ColsAtCompileTime, + MaxDepth = min_size_prefer_fixed(traits::MaxColsAtCompileTime, traits::MaxRowsAtCompileTime), + Depth = min_size_prefer_fixed(traits::ColsAtCompileTime, traits::RowsAtCompileTime) }; // the splitting into different lines of code here, introducing the _select enums and the typedef below, // is to work around an internal compiler error with gcc 4.1 and 4.2. -private: + private: enum { - rows_select = product_size_category::value, - cols_select = product_size_category::value, - depth_select = product_size_category::value + rows_select = product_size_category::value, + cols_select = product_size_category::value, + depth_select = product_size_category::value }; typedef product_type_selector selector; -public: - enum { - value = selector::ret - }; + public: + enum { value = selector::ret, ret = selector::ret }; #ifdef EIGEN_DEBUG_PRODUCT - static void debug() - { - EIGEN_DEBUG_VAR(Rows); - EIGEN_DEBUG_VAR(Cols); - EIGEN_DEBUG_VAR(Depth); - EIGEN_DEBUG_VAR(rows_select); - EIGEN_DEBUG_VAR(cols_select); - EIGEN_DEBUG_VAR(depth_select); - EIGEN_DEBUG_VAR(value); + static void debug() { + EIGEN_DEBUG_VAR(Rows); + EIGEN_DEBUG_VAR(Cols); + EIGEN_DEBUG_VAR(Depth); + EIGEN_DEBUG_VAR(rows_select); + EIGEN_DEBUG_VAR(cols_select); + EIGEN_DEBUG_VAR(depth_select); + EIGEN_DEBUG_VAR(value); } #endif }; - /* The following allows to select the kind of product at compile time * based on the three dimensions of the product. * This is a compile time mapping from {1,Small,Large}^3 -> {product types} */ // FIXME I'm not sure the current mapping is the ideal one. -template struct product_type_selector { enum { ret = OuterProduct }; }; -template struct product_type_selector<1, 1, Depth> { enum { ret = InnerProduct }; }; -template<> struct product_type_selector<1, 1, 1> { enum { ret = InnerProduct }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Small,Small> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = LazyCoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Large,Small> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector<1, Large,Large> { enum { ret = GemvProduct }; }; -template<> struct product_type_selector<1, Small,Large> { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = GemvProduct }; }; -template<> struct product_type_selector { enum { ret = CoeffBasedProductMode }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; -template<> struct product_type_selector { enum { ret = GemmProduct }; }; - -} // end namespace internal - -/** \class ProductReturnType - * \ingroup Core_Module - * - * \brief Helper class to get the correct and optimized returned type of operator* - * - * \param Lhs the type of the left-hand side - * \param Rhs the type of the right-hand side - * \param ProductMode the type of the product (determined automatically by internal::product_mode) - * - * This class defines the typename Type representing the optimized product expression - * between two matrix expressions. In practice, using ProductReturnType::Type - * is the recommended way to define the result type of a function returning an expression - * which involve a matrix product. The class Product should never be - * used directly. - * - * \sa class Product, MatrixBase::operator*(const MatrixBase&) - */ -template -struct ProductReturnType -{ - // TODO use the nested type to reduce instanciations ???? -// typedef typename internal::nested::type LhsNested; -// typedef typename internal::nested::type RhsNested; - - typedef GeneralProduct Type; -}; - -template -struct ProductReturnType -{ - typedef typename internal::nested::type >::type LhsNested; - typedef typename internal::nested::type >::type RhsNested; - typedef CoeffBasedProduct Type; -}; - -template -struct ProductReturnType -{ - typedef typename internal::nested::type >::type LhsNested; - typedef typename internal::nested::type >::type RhsNested; - typedef CoeffBasedProduct Type; -}; - -// this is a workaround for sun CC -template -struct LazyProductReturnType : public ProductReturnType -{}; +template +struct product_type_selector { + enum { ret = OuterProduct }; +}; +template +struct product_type_selector { + enum { ret = LazyCoeffBasedProductMode }; +}; +template +struct product_type_selector<1, N, 1> { + enum { ret = LazyCoeffBasedProductMode }; +}; +template +struct product_type_selector<1, 1, Depth> { + enum { ret = InnerProduct }; +}; +template <> +struct product_type_selector<1, 1, 1> { + enum { ret = InnerProduct }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector<1, Small, Small> { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = LazyCoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = LazyCoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = LazyCoeffBasedProductMode }; +}; +template <> +struct product_type_selector<1, Large, Small> { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector<1, Large, Large> { + enum { ret = GemvProduct }; +}; +template <> +struct product_type_selector<1, Small, Large> { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = GemvProduct }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = GemmProduct }; +}; +template <> +struct product_type_selector { + enum { ret = GemmProduct }; +}; +template <> +struct product_type_selector { + enum { ret = GemmProduct }; +}; +template <> +struct product_type_selector { + enum { ret = GemmProduct }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = CoeffBasedProductMode }; +}; +template <> +struct product_type_selector { + enum { ret = GemmProduct }; +}; + +} // end namespace internal /*********************************************************************** -* Implementation of Inner Vector Vector Product -***********************************************************************/ + * Implementation of Inner Vector Vector Product + ***********************************************************************/ // FIXME : maybe the "inner product" could return a Scalar // instead of a 1x1 matrix ?? @@ -187,122 +200,13 @@ struct LazyProductReturnType : public ProductReturnType with: operator=(Scalar x); -namespace internal { - -template -struct traits > - : traits::ReturnType,1,1> > -{}; - -} - -template -class GeneralProduct - : internal::no_assignment_operator, - public Matrix::ReturnType,1,1> -{ - typedef Matrix::ReturnType,1,1> Base; - public: - GeneralProduct(const Lhs& lhs, const Rhs& rhs) - { - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - - Base::coeffRef(0,0) = (lhs.transpose().cwiseProduct(rhs)).sum(); - } - - /** Convertion to scalar */ - operator const typename Base::Scalar() const { - return Base::coeff(0,0); - } -}; - /*********************************************************************** -* Implementation of Outer Vector Vector Product -***********************************************************************/ - -namespace internal { - -// Column major -template -EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const false_type&) -{ - typedef typename Dest::Index Index; - // FIXME make sure lhs is sequentially stored - // FIXME not very good if rhs is real and lhs complex while alpha is real too - const Index cols = dest.cols(); - for (Index j=0; j -EIGEN_DONT_INLINE void outer_product_selector_run(const ProductType& prod, Dest& dest, const Func& func, const true_type&) { - typedef typename Dest::Index Index; - // FIXME make sure rhs is sequentially stored - // FIXME not very good if lhs is real and rhs complex while alpha is real too - const Index rows = dest.rows(); - for (Index i=0; i -struct traits > - : traits, Lhs, Rhs> > -{}; - -} - -template -class GeneralProduct - : public ProductBase, Lhs, Rhs> -{ - template struct is_row_major : internal::conditional<(int(T::Flags)&RowMajorBit), internal::true_type, internal::false_type>::type {}; - - public: - EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) - - GeneralProduct(const Lhs& lhs, const Rhs& rhs) : Base(lhs,rhs) - { - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - } - - struct set { template void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() = src; } }; - struct add { template void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() += src; } }; - struct sub { template void operator()(const Dst& dst, const Src& src) const { dst.const_cast_derived() -= src; } }; - struct adds { - Scalar m_scale; - adds(const Scalar& s) : m_scale(s) {} - template void operator()(const Dst& dst, const Src& src) const { - dst.const_cast_derived() += m_scale * src; - } - }; - - template - inline void evalTo(Dest& dest) const { - internal::outer_product_selector_run(*this, dest, set(), is_row_major()); - } - - template - inline void addTo(Dest& dest) const { - internal::outer_product_selector_run(*this, dest, add(), is_row_major()); - } - - template - inline void subTo(Dest& dest) const { - internal::outer_product_selector_run(*this, dest, sub(), is_row_major()); - } - - template void scaleAndAddTo(Dest& dest, const Scalar& alpha) const - { - internal::outer_product_selector_run(*this, dest, adds(alpha), is_row_major()); - } -}; + * Implementation of Outer Vector Vector Product + ***********************************************************************/ /*********************************************************************** -* Implementation of General Matrix Vector Product -***********************************************************************/ + * Implementation of General Matrix Vector Product + ***********************************************************************/ /* According to the shape/flags of the matrix we have to distinghish 3 different cases: * 1 - the matrix is col-major, BLAS compatible and M is large => call fast BLAS-like colmajor routine @@ -313,323 +217,303 @@ class GeneralProduct */ namespace internal { -template -struct traits > - : traits, Lhs, Rhs> > -{}; +template +struct gemv_dense_selector; -template -struct gemv_selector; +} // end namespace internal -} // end namespace internal - -template -class GeneralProduct - : public ProductBase, Lhs, Rhs> -{ - public: - EIGEN_PRODUCT_PUBLIC_INTERFACE(GeneralProduct) - - typedef typename Lhs::Scalar LhsScalar; - typedef typename Rhs::Scalar RhsScalar; +namespace internal { - GeneralProduct(const Lhs& a_lhs, const Rhs& a_rhs) : Base(a_lhs,a_rhs) - { -// EIGEN_STATIC_ASSERT((internal::is_same::value), -// YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - } +template +struct gemv_static_vector_if; - enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight }; - typedef typename internal::conditional::type MatrixType; +template +struct gemv_static_vector_if { + EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr Scalar* data() { + eigen_internal_assert(false && "should never be called"); + return 0; + } +}; - template void scaleAndAddTo(Dest& dst, const Scalar& alpha) const - { - eigen_assert(m_lhs.rows() == dst.rows() && m_rhs.cols() == dst.cols()); - internal::gemv_selector::HasUsableDirectAccess)>::run(*this, dst, alpha); - } +template +struct gemv_static_vector_if { + EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr Scalar* data() { return 0; } }; -namespace internal { +template +struct gemv_static_vector_if { +#if EIGEN_MAX_STATIC_ALIGN_BYTES != 0 + internal::plain_array m_data; + EIGEN_STRONG_INLINE constexpr Scalar* data() { return m_data.array; } +#else + // Some architectures cannot align on the stack, + // => let's manually enforce alignment by allocating more data and return the address of the first aligned element. + internal::plain_array m_data; + EIGEN_STRONG_INLINE constexpr Scalar* data() { + return reinterpret_cast((std::uintptr_t(m_data.array) & ~(std::size_t(EIGEN_MAX_ALIGN_BYTES - 1))) + + EIGEN_MAX_ALIGN_BYTES); + } +#endif +}; // The vector is on the left => transposition -template -struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha) - { +template +struct gemv_dense_selector { + template + static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha) { Transpose destT(dest); enum { OtherStorageOrder = StorageOrder == RowMajor ? ColMajor : RowMajor }; - gemv_selector - ::run(GeneralProduct,Transpose, GemvProduct> - (prod.rhs().transpose(), prod.lhs().transpose()), destT, alpha); + gemv_dense_selector::run(rhs.transpose(), lhs.transpose(), destT, + alpha); } }; -template struct gemv_static_vector_if; +template <> +struct gemv_dense_selector { + template + static inline void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha) { + typedef typename Lhs::Scalar LhsScalar; + typedef typename Rhs::Scalar RhsScalar; + typedef typename Dest::Scalar ResScalar; -template -struct gemv_static_vector_if -{ - EIGEN_STRONG_INLINE Scalar* data() { eigen_internal_assert(false && "should never be called"); return 0; } -}; + typedef internal::blas_traits LhsBlasTraits; + typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; + typedef internal::blas_traits RhsBlasTraits; + typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; -template -struct gemv_static_vector_if -{ - EIGEN_STRONG_INLINE Scalar* data() { return 0; } -}; + typedef Map, plain_enum_min(AlignedMax, internal::packet_traits::size)> + MappedDest; -template -struct gemv_static_vector_if -{ - #if EIGEN_ALIGN_STATICALLY - internal::plain_array m_data; - EIGEN_STRONG_INLINE Scalar* data() { return m_data.array; } - #else - // Some architectures cannot align on the stack, - // => let's manually enforce alignment by allocating more data and return the address of the first aligned element. - enum { - ForceAlignment = internal::packet_traits::Vectorizable, - PacketSize = internal::packet_traits::size - }; - internal::plain_array m_data; - EIGEN_STRONG_INLINE Scalar* data() { - return ForceAlignment - ? reinterpret_cast((reinterpret_cast(m_data.array) & ~(size_t(15))) + 16) - : m_data.array; - } - #endif -}; - -template<> struct gemv_selector -{ - template - static inline void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha) - { - typedef typename ProductType::Index Index; - typedef typename ProductType::LhsScalar LhsScalar; - typedef typename ProductType::RhsScalar RhsScalar; - typedef typename ProductType::Scalar ResScalar; - typedef typename ProductType::RealScalar RealScalar; - typedef typename ProductType::ActualLhsType ActualLhsType; - typedef typename ProductType::ActualRhsType ActualRhsType; - typedef typename ProductType::LhsBlasTraits LhsBlasTraits; - typedef typename ProductType::RhsBlasTraits RhsBlasTraits; - typedef Map, Aligned> MappedDest; - - ActualLhsType actualLhs = LhsBlasTraits::extract(prod.lhs()); - ActualRhsType actualRhs = RhsBlasTraits::extract(prod.rhs()); - - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) - * RhsBlasTraits::extractScalarFactor(prod.rhs()); + ActualLhsType actualLhs = LhsBlasTraits::extract(lhs); + ActualRhsType actualRhs = RhsBlasTraits::extract(rhs); + + ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs); + + // make sure Dest is a compile-time vector type (bug 1166) + typedef std::conditional_t ActualDest; enum { // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 // on, the other hand it is good for the cache to pack the vector anyways... - EvalToDestAtCompileTime = Dest::InnerStrideAtCompileTime==1, + EvalToDestAtCompileTime = (ActualDest::InnerStrideAtCompileTime == 1), ComplexByReal = (NumTraits::IsComplex) && (!NumTraits::IsComplex), - MightCannotUseDest = (Dest::InnerStrideAtCompileTime!=1) || ComplexByReal + MightCannotUseDest = ((!EvalToDestAtCompileTime) || ComplexByReal) && (ActualDest::MaxSizeAtCompileTime != 0) }; - gemv_static_vector_if static_dest; - - bool alphaIsCompatible = (!ComplexByReal) || (numext::imag(actualAlpha)==RealScalar(0)); - bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; - - RhsScalar compatibleAlpha = get_factor::run(actualAlpha); - - ei_declare_aligned_stack_constructed_variable(ResScalar,actualDestPtr,dest.size(), - evalToDest ? dest.data() : static_dest.data()); - - if(!evalToDest) - { - #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN - int size = dest.size(); - EIGEN_DENSE_STORAGE_CTOR_PLUGIN - #endif - if(!alphaIsCompatible) - { - MappedDest(actualDestPtr, dest.size()).setZero(); - compatibleAlpha = RhsScalar(1); + typedef const_blas_data_mapper LhsMapper; + typedef const_blas_data_mapper RhsMapper; + RhsScalar compatibleAlpha = get_factor::run(actualAlpha); + + if (!MightCannotUseDest) { + // shortcut if we are sure to be able to use dest directly, + // this ease the compiler to generate cleaner and more optimzized code for most common cases + general_matrix_vector_product::run(actualLhs.rows(), actualLhs.cols(), + LhsMapper(actualLhs.data(), + actualLhs.outerStride()), + RhsMapper(actualRhs.data(), + actualRhs.innerStride()), + dest.data(), 1, compatibleAlpha); + } else { + gemv_static_vector_if + static_dest; + + const bool alphaIsCompatible = (!ComplexByReal) || (numext::is_exactly_zero(numext::imag(actualAlpha))); + const bool evalToDest = EvalToDestAtCompileTime && alphaIsCompatible; + + ei_declare_aligned_stack_constructed_variable(ResScalar, actualDestPtr, dest.size(), + evalToDest ? dest.data() : static_dest.data()); + + if (!evalToDest) { +#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN + constexpr int Size = Dest::SizeAtCompileTime; + Index size = dest.size(); + EIGEN_DENSE_STORAGE_CTOR_PLUGIN +#endif + if (!alphaIsCompatible) { + MappedDest(actualDestPtr, dest.size()).setZero(); + compatibleAlpha = RhsScalar(1); + } else + MappedDest(actualDestPtr, dest.size()) = dest; } - else - MappedDest(actualDestPtr, dest.size()) = dest; - } - general_matrix_vector_product - ::run( - actualLhs.rows(), actualLhs.cols(), - actualLhs.data(), actualLhs.outerStride(), - actualRhs.data(), actualRhs.innerStride(), - actualDestPtr, 1, - compatibleAlpha); - - if (!evalToDest) - { - if(!alphaIsCompatible) - dest += actualAlpha * MappedDest(actualDestPtr, dest.size()); - else - dest = MappedDest(actualDestPtr, dest.size()); + general_matrix_vector_product::run(actualLhs.rows(), actualLhs.cols(), + LhsMapper(actualLhs.data(), + actualLhs.outerStride()), + RhsMapper(actualRhs.data(), + actualRhs.innerStride()), + actualDestPtr, 1, compatibleAlpha); + + if (!evalToDest) { + if (!alphaIsCompatible) + dest.matrix() += actualAlpha * MappedDest(actualDestPtr, dest.size()); + else + dest = MappedDest(actualDestPtr, dest.size()); + } } } }; -template<> struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha) - { - typedef typename ProductType::LhsScalar LhsScalar; - typedef typename ProductType::RhsScalar RhsScalar; - typedef typename ProductType::Scalar ResScalar; - typedef typename ProductType::Index Index; - typedef typename ProductType::ActualLhsType ActualLhsType; - typedef typename ProductType::ActualRhsType ActualRhsType; - typedef typename ProductType::_ActualRhsType _ActualRhsType; - typedef typename ProductType::LhsBlasTraits LhsBlasTraits; - typedef typename ProductType::RhsBlasTraits RhsBlasTraits; +template <> +struct gemv_dense_selector { + template + static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha) { + typedef typename Lhs::Scalar LhsScalar; + typedef typename Rhs::Scalar RhsScalar; + typedef typename Dest::Scalar ResScalar; + + typedef internal::blas_traits LhsBlasTraits; + typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; + typedef internal::blas_traits RhsBlasTraits; + typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; + typedef internal::remove_all_t ActualRhsTypeCleaned; - typename add_const::type actualLhs = LhsBlasTraits::extract(prod.lhs()); - typename add_const::type actualRhs = RhsBlasTraits::extract(prod.rhs()); + std::add_const_t actualLhs = LhsBlasTraits::extract(lhs); + std::add_const_t actualRhs = RhsBlasTraits::extract(rhs); - ResScalar actualAlpha = alpha * LhsBlasTraits::extractScalarFactor(prod.lhs()) - * RhsBlasTraits::extractScalarFactor(prod.rhs()); + ResScalar actualAlpha = combine_scalar_factors(alpha, lhs, rhs); enum { // FIXME find a way to allow an inner stride on the result if packet_traits::size==1 // on, the other hand it is good for the cache to pack the vector anyways... - DirectlyUseRhs = _ActualRhsType::InnerStrideAtCompileTime==1 + DirectlyUseRhs = + ActualRhsTypeCleaned::InnerStrideAtCompileTime == 1 || ActualRhsTypeCleaned::MaxSizeAtCompileTime == 0 }; - gemv_static_vector_if static_rhs; + gemv_static_vector_if + static_rhs; - ei_declare_aligned_stack_constructed_variable(RhsScalar,actualRhsPtr,actualRhs.size(), + ei_declare_aligned_stack_constructed_variable( + RhsScalar, actualRhsPtr, actualRhs.size(), DirectlyUseRhs ? const_cast(actualRhs.data()) : static_rhs.data()); - if(!DirectlyUseRhs) - { - #ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN - int size = actualRhs.size(); + if (!DirectlyUseRhs) { +#ifdef EIGEN_DENSE_STORAGE_CTOR_PLUGIN + constexpr int Size = ActualRhsTypeCleaned::SizeAtCompileTime; + Index size = actualRhs.size(); EIGEN_DENSE_STORAGE_CTOR_PLUGIN - #endif - Map(actualRhsPtr, actualRhs.size()) = actualRhs; +#endif + Map(actualRhsPtr, actualRhs.size()) = actualRhs; } - general_matrix_vector_product - ::run( - actualLhs.rows(), actualLhs.cols(), - actualLhs.data(), actualLhs.outerStride(), - actualRhsPtr, 1, - dest.data(), dest.innerStride(), - actualAlpha); + typedef const_blas_data_mapper LhsMapper; + typedef const_blas_data_mapper RhsMapper; + general_matrix_vector_product:: + run(actualLhs.rows(), actualLhs.cols(), LhsMapper(actualLhs.data(), actualLhs.outerStride()), + RhsMapper(actualRhsPtr, 1), dest.data(), + dest.col(0).innerStride(), // NOTE if dest is not a vector at compile-time, then dest.innerStride() might + // be wrong. (bug 1166) + actualAlpha); } }; -template<> struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha) - { - typedef typename Dest::Index Index; - // TODO makes sure dest is sequentially stored in memory, otherwise use a temp - const Index size = prod.rhs().rows(); - for(Index k=0; k +struct gemv_dense_selector { + template + static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha) { + EIGEN_STATIC_ASSERT((!nested_eval::Evaluate), + EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE); + // TODO if rhs is large enough it might be beneficial to make sure that dest is sequentially stored in memory, + // otherwise use a temp + typename nested_eval::type actual_rhs(rhs); + const Index size = rhs.rows(); + for (Index k = 0; k < size; ++k) dest += (alpha * actual_rhs.coeff(k)) * lhs.col(k); } }; -template<> struct gemv_selector -{ - template - static void run(const ProductType& prod, Dest& dest, const typename ProductType::Scalar& alpha) - { - typedef typename Dest::Index Index; - // TODO makes sure rhs is sequentially stored in memory, otherwise use a temp - const Index rows = prod.rows(); - for(Index i=0; i +struct gemv_dense_selector { + template + static void run(const Lhs& lhs, const Rhs& rhs, Dest& dest, const typename Dest::Scalar& alpha) { + EIGEN_STATIC_ASSERT((!nested_eval::Evaluate), + EIGEN_INTERNAL_COMPILATION_ERROR_OR_YOU_MADE_A_PROGRAMMING_MISTAKE); + typename nested_eval::type actual_rhs(rhs); + const Index rows = dest.rows(); + for (Index i = 0; i < rows; ++i) + dest.coeffRef(i) += alpha * (lhs.row(i).cwiseProduct(actual_rhs.transpose())).sum(); } }; -} // end namespace internal +} // end namespace internal /*************************************************************************** -* Implementation of matrix base methods -***************************************************************************/ + * Implementation of matrix base methods + ***************************************************************************/ /** \returns the matrix product of \c *this and \a other. - * - * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*(). - * - * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*() - */ -template -template -inline const typename ProductReturnType::Type -MatrixBase::operator*(const MatrixBase &other) const -{ + * + * \note If instead of the matrix product you want the coefficient-wise product, see Cwise::operator*(). + * + * \sa lazyProduct(), operator*=(const MatrixBase&), Cwise::operator*() + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Product MatrixBase::operator*( + const MatrixBase& other) const { // A note regarding the function declaration: In MSVC, this function will sometimes // not be inlined since DenseStorage is an unwindable object for dynamic // matrices and product types are holding a member to store the result. // Thus it does not help tagging this function with EIGEN_STRONG_INLINE. enum { - ProductIsValid = Derived::ColsAtCompileTime==Dynamic - || OtherDerived::RowsAtCompileTime==Dynamic - || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), + ProductIsValid = Derived::ColsAtCompileTime == Dynamic || OtherDerived::RowsAtCompileTime == Dynamic || + int(Derived::ColsAtCompileTime) == int(OtherDerived::RowsAtCompileTime), AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, - SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) + SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived, OtherDerived) }; // note to the lost user: // * for a dot product use: v1.dot(v2) // * for a coeff-wise product use: v1.cwiseProduct(v2) - EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), - INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) + EIGEN_STATIC_ASSERT( + ProductIsValid || !(AreVectors && SameSizes), + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), - INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) #ifdef EIGEN_DEBUG_PRODUCT - internal::product_type::debug(); + internal::product_type::debug(); #endif - return typename ProductReturnType::Type(derived(), other.derived()); + + return Product(derived(), other.derived()); } /** \returns an expression of the matrix product of \c *this and \a other without implicit evaluation. - * - * The returned product will behave like any other expressions: the coefficients of the product will be - * computed once at a time as requested. This might be useful in some extremely rare cases when only - * a small and no coherent fraction of the result's coefficients have to be computed. - * - * \warning This version of the matrix product can be much much slower. So use it only if you know - * what you are doing and that you measured a true speed improvement. - * - * \sa operator*(const MatrixBase&) - */ -template -template -const typename LazyProductReturnType::Type -MatrixBase::lazyProduct(const MatrixBase &other) const -{ + * + * The returned product will behave like any other expressions: the coefficients of the product will be + * computed once at a time as requested. This might be useful in some extremely rare cases when only + * a small and no coherent fraction of the result's coefficients have to be computed. + * + * \warning This version of the matrix product can be much much slower. So use it only if you know + * what you are doing and that you measured a true speed improvement. + * + * \sa operator*(const MatrixBase&) + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Product +MatrixBase::lazyProduct(const MatrixBase& other) const { enum { - ProductIsValid = Derived::ColsAtCompileTime==Dynamic - || OtherDerived::RowsAtCompileTime==Dynamic - || int(Derived::ColsAtCompileTime)==int(OtherDerived::RowsAtCompileTime), + ProductIsValid = Derived::ColsAtCompileTime == Dynamic || OtherDerived::RowsAtCompileTime == Dynamic || + int(Derived::ColsAtCompileTime) == int(OtherDerived::RowsAtCompileTime), AreVectors = Derived::IsVectorAtCompileTime && OtherDerived::IsVectorAtCompileTime, - SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived,OtherDerived) + SameSizes = EIGEN_PREDICATE_SAME_MATRIX_SIZE(Derived, OtherDerived) }; // note to the lost user: // * for a dot product use: v1.dot(v2) // * for a coeff-wise product use: v1.cwiseProduct(v2) - EIGEN_STATIC_ASSERT(ProductIsValid || !(AreVectors && SameSizes), - INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) + EIGEN_STATIC_ASSERT( + ProductIsValid || !(AreVectors && SameSizes), + INVALID_VECTOR_VECTOR_PRODUCT__IF_YOU_WANTED_A_DOT_OR_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTIONS) EIGEN_STATIC_ASSERT(ProductIsValid || !(SameSizes && !AreVectors), - INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) + INVALID_MATRIX_PRODUCT__IF_YOU_WANTED_A_COEFF_WISE_PRODUCT_YOU_MUST_USE_THE_EXPLICIT_FUNCTION) EIGEN_STATIC_ASSERT(ProductIsValid || SameSizes, INVALID_MATRIX_PRODUCT) - return typename LazyProductReturnType::Type(derived(), other.derived()); + return Product(derived(), other.derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_PRODUCT_H +#endif // EIGEN_PRODUCT_H diff --git a/inst/include/Eigen/src/Core/GenericPacketMath.h b/inst/include/Eigen/src/Core/GenericPacketMath.h index 5f783ebe..64e11231 100644 --- a/inst/include/Eigen/src/Core/GenericPacketMath.h +++ b/inst/include/Eigen/src/Core/GenericPacketMath.h @@ -11,17 +11,20 @@ #ifndef EIGEN_GENERIC_PACKET_MATH_H #define EIGEN_GENERIC_PACKET_MATH_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { namespace internal { /** \internal - * \file GenericPacketMath.h - * - * Default implementation for types not supported by the vectorization. - * In practice these functions are provided to make easier the writing - * of generic vectorized code. - */ + * \file GenericPacketMath.h + * + * Default implementation for types not supported by the vectorization. + * In practice these functions are provided to make easier the writing + * of generic vectorized code. + */ #ifndef EIGEN_DEBUG_ALIGNED_LOAD #define EIGEN_DEBUG_ALIGNED_LOAD @@ -39,312 +42,1661 @@ namespace internal { #define EIGEN_DEBUG_UNALIGNED_STORE #endif -struct default_packet_traits -{ +struct default_packet_traits { enum { - HasAdd = 1, - HasSub = 1, - HasMul = 1, + // Ops that are implemented for most types. + HasAdd = 1, + HasSub = 1, + HasShift = 1, + HasMul = 1, HasNegate = 1, - HasAbs = 1, - HasAbs2 = 1, - HasMin = 1, - HasMax = 1, - HasConj = 1, + HasAbs = 1, + HasAbs2 = 1, + HasMin = 1, + HasMax = 1, + HasConj = 1, HasSetLinear = 1, - - HasDiv = 0, - HasSqrt = 0, - HasExp = 0, - HasLog = 0, - HasPow = 0, - - HasSin = 0, - HasCos = 0, - HasTan = 0, - HasASin = 0, - HasACos = 0, - HasATan = 0 + HasSign = 1, + // By default, the nearest integer functions (rint, round, floor, ceil, trunc) are enabled for all scalar and packet + // types + HasRound = 1, + + HasArg = 0, + HasAbsDiff = 0, + HasBlend = 0, + // This flag is used to indicate whether packet comparison is supported. + // pcmp_eq and pcmp_lt should be defined for it to be true. + HasCmp = 0, + + HasDiv = 0, + HasReciprocal = 0, + HasSqrt = 0, + HasRsqrt = 0, + HasCbrt = 0, + HasExp = 0, + HasExpm1 = 0, + HasLog = 0, + HasLog1p = 0, + HasLog10 = 0, + HasPow = 0, + HasSin = 0, + HasCos = 0, + HasTan = 0, + HasASin = 0, + HasACos = 0, + HasATan = 0, + HasATanh = 0, + HasSinh = 0, + HasCosh = 0, + HasTanh = 0, + HasLGamma = 0, + HasDiGamma = 0, + HasZeta = 0, + HasPolygamma = 0, + HasErf = 0, + HasErfc = 0, + HasNdtri = 0, + HasBessel = 0, + HasIGamma = 0, + HasIGammaDerA = 0, + HasGammaSampleDerAlpha = 0, + HasIGammac = 0, + HasBetaInc = 0 }; }; -template struct packet_traits : default_packet_traits -{ +template +struct packet_traits : default_packet_traits { typedef T type; + typedef T half; enum { Vectorizable = 0, size = 1, - AlignedOnScalar = 0 + AlignedOnScalar = 0, }; enum { - HasAdd = 0, - HasSub = 0, - HasMul = 0, + HasAdd = 0, + HasSub = 0, + HasMul = 0, HasNegate = 0, - HasAbs = 0, - HasAbs2 = 0, - HasMin = 0, - HasMax = 0, - HasConj = 0, + HasAbs = 0, + HasAbs2 = 0, + HasMin = 0, + HasMax = 0, + HasConj = 0, HasSetLinear = 0 }; }; +template +struct packet_traits : packet_traits {}; + +template +struct unpacket_traits { + typedef T type; + typedef T half; + typedef typename numext::get_integer_by_size::signed_type integer_packet; + enum { + size = 1, + alignment = alignof(T), + vectorizable = false, + masked_load_available = false, + masked_store_available = false + }; +}; + +template +struct unpacket_traits : unpacket_traits {}; + +/** \internal A convenience utility for determining if the type is a scalar. + * This is used to enable some generic packet implementations. + */ +template +struct is_scalar { + using Scalar = typename unpacket_traits::type; + enum { value = internal::is_same::value }; +}; + +// automatically and succinctly define combinations of pcast when +// 1) the packets are the same type, or +// 2) the packets differ only in sign. +// In both of these cases, preinterpret (bit_cast) is equivalent to pcast (static_cast) +template ::value && is_scalar::value> +struct is_degenerate_helper : is_same {}; +template <> +struct is_degenerate_helper : std::true_type {}; +template <> +struct is_degenerate_helper : std::true_type {}; +template <> +struct is_degenerate_helper : std::true_type {}; +template <> +struct is_degenerate_helper : std::true_type {}; + +template +struct is_degenerate_helper { + using SrcScalar = typename unpacket_traits::type; + static constexpr int SrcSize = unpacket_traits::size; + using TgtScalar = typename unpacket_traits::type; + static constexpr int TgtSize = unpacket_traits::size; + static constexpr bool value = is_degenerate_helper::value && (SrcSize == TgtSize); +}; + +// is_degenerate::value == is_degenerate::value +template +struct is_degenerate { + static constexpr bool value = + is_degenerate_helper::value || is_degenerate_helper::value; +}; + +template +struct is_half { + using Scalar = typename unpacket_traits::type; + static constexpr int Size = unpacket_traits::size; + using DefaultPacket = typename packet_traits::type; + static constexpr int DefaultSize = unpacket_traits::size; + static constexpr bool value = Size != 1 && Size < DefaultSize; +}; + +template +struct type_casting_traits { + enum { + VectorizedCast = + is_degenerate::value && packet_traits::Vectorizable && packet_traits::Vectorizable, + SrcCoeffRatio = 1, + TgtCoeffRatio = 1 + }; +}; + +// provides a succinct template to define vectorized casting traits with respect to the largest accessible packet types +template +struct vectorized_type_casting_traits { + enum : int { + DefaultSrcPacketSize = packet_traits::size, + DefaultTgtPacketSize = packet_traits::size, + VectorizedCast = 1, + SrcCoeffRatio = plain_enum_max(DefaultTgtPacketSize / DefaultSrcPacketSize, 1), + TgtCoeffRatio = plain_enum_max(DefaultSrcPacketSize / DefaultTgtPacketSize, 1) + }; +}; + +/** \internal Wrapper to ensure that multiple packet types can map to the same + same underlying vector type. */ +template +struct eigen_packet_wrapper { + EIGEN_ALWAYS_INLINE operator T&() { return m_val; } + EIGEN_ALWAYS_INLINE operator const T&() const { return m_val; } + EIGEN_ALWAYS_INLINE eigen_packet_wrapper() = default; + EIGEN_ALWAYS_INLINE eigen_packet_wrapper(const T& v) : m_val(v) {} + EIGEN_ALWAYS_INLINE eigen_packet_wrapper& operator=(const T& v) { + m_val = v; + return *this; + } + + T m_val; +}; + +template ::value> +struct preinterpret_generic; + +template +struct preinterpret_generic { + // the packets are not the same, attempt scalar bit_cast + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Target run(const Packet& a) { + return numext::bit_cast(a); + } +}; + +template +struct preinterpret_generic { + // the packets are the same type: do nothing + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run(const Packet& a) { return a; } +}; + +template +struct preinterpret_generic::as_real, ComplexPacket, false> { + using RealPacket = typename unpacket_traits::as_real; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE RealPacket run(const ComplexPacket& a) { return a.v; } +}; + +/** \internal \returns reinterpret_cast(a) */ +template +EIGEN_DEVICE_FUNC inline Target preinterpret(const Packet& a) { + return preinterpret_generic::run(a); +} + +template ::value, + bool TgtIsHalf = is_half::value> +struct pcast_generic; + +template +struct pcast_generic { + // the packets are not degenerate: attempt scalar static_cast + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket run(const SrcPacket& a) { + return cast_impl::run(a); + } +}; + +template +struct pcast_generic { + // the packets are the same: do nothing + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run(const Packet& a) { return a; } +}; + +template +struct pcast_generic { + // the packets are degenerate: preinterpret is equivalent to pcast + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket run(const SrcPacket& a) { return preinterpret(a); } +}; + +/** \internal \returns static_cast(a) (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline TgtPacket pcast(const SrcPacket& a) { + return pcast_generic::run(a); +} +template +EIGEN_DEVICE_FUNC inline TgtPacket pcast(const SrcPacket& a, const SrcPacket& b) { + return pcast_generic::run(a, b); +} +template +EIGEN_DEVICE_FUNC inline TgtPacket pcast(const SrcPacket& a, const SrcPacket& b, const SrcPacket& c, + const SrcPacket& d) { + return pcast_generic::run(a, b, c, d); +} +template +EIGEN_DEVICE_FUNC inline TgtPacket pcast(const SrcPacket& a, const SrcPacket& b, const SrcPacket& c, const SrcPacket& d, + const SrcPacket& e, const SrcPacket& f, const SrcPacket& g, + const SrcPacket& h) { + return pcast_generic::run(a, b, c, d, e, f, g, h); +} + +template +struct pcast_generic { + // TgtPacket is a half packet of some other type + // perform cast and truncate result + using DefaultTgtPacket = typename is_half::DefaultPacket; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TgtPacket run(const SrcPacket& a) { + return preinterpret(pcast(a)); + } +}; + /** \internal \returns a + b (coeff-wise) */ -template inline Packet -padd(const Packet& a, - const Packet& b) { return a+b; } +template +EIGEN_DEVICE_FUNC inline Packet padd(const Packet& a, const Packet& b) { + return a + b; +} +// Avoid compiler warning for boolean algebra. +template <> +EIGEN_DEVICE_FUNC inline bool padd(const bool& a, const bool& b) { + return a || b; +} + +/** \internal \returns a packet version of \a *from, (un-aligned masked add) + * There is no generic implementation. We only have implementations for specialized + * cases. Generic case should not be called. + */ +template +EIGEN_DEVICE_FUNC inline std::enable_if_t::masked_fpops_available, Packet> padd( + const Packet& a, const Packet& b, typename unpacket_traits::mask_t umask); /** \internal \returns a - b (coeff-wise) */ -template inline Packet -psub(const Packet& a, - const Packet& b) { return a-b; } +template +EIGEN_DEVICE_FUNC inline Packet psub(const Packet& a, const Packet& b) { + return a - b; +} /** \internal \returns -a (coeff-wise) */ -template inline Packet -pnegate(const Packet& a) { return -a; } +template +EIGEN_DEVICE_FUNC inline Packet pnegate(const Packet& a) { + EIGEN_STATIC_ASSERT((!is_same::type, bool>::value), + NEGATE IS NOT DEFINED FOR BOOLEAN TYPES) + return numext::negate(a); +} /** \internal \returns conj(a) (coeff-wise) */ -template inline Packet -pconj(const Packet& a) { return numext::conj(a); } +template +EIGEN_DEVICE_FUNC inline Packet pconj(const Packet& a) { + return numext::conj(a); +} /** \internal \returns a * b (coeff-wise) */ -template inline Packet -pmul(const Packet& a, - const Packet& b) { return a*b; } +template +EIGEN_DEVICE_FUNC inline Packet pmul(const Packet& a, const Packet& b) { + return a * b; +} +// Avoid compiler warning for boolean algebra. +template <> +EIGEN_DEVICE_FUNC inline bool pmul(const bool& a, const bool& b) { + return a && b; +} /** \internal \returns a / b (coeff-wise) */ -template inline Packet -pdiv(const Packet& a, - const Packet& b) { return a/b; } +template +EIGEN_DEVICE_FUNC inline Packet pdiv(const Packet& a, const Packet& b) { + return a / b; +} +// Avoid compiler warning for boolean algebra. +template <> +EIGEN_DEVICE_FUNC inline bool pdiv(const bool& a, const bool& b) { + return a && b; +} -/** \internal \returns the min of \a a and \a b (coeff-wise) */ -template inline Packet -pmin(const Packet& a, - const Packet& b) { using std::min; return (min)(a, b); } +// In the generic packet case, memset to all one bits. +template +struct ptrue_impl { + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& /*a*/) { + Packet b; + memset(static_cast(&b), 0xff, sizeof(Packet)); + return b; + } +}; -/** \internal \returns the max of \a a and \a b (coeff-wise) */ -template inline Packet -pmax(const Packet& a, - const Packet& b) { using std::max; return (max)(a, b); } +// Use a value of one for scalars. +template +struct ptrue_impl::value>> { + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar&) { return Scalar(1); } +}; -/** \internal \returns the absolute value of \a a */ -template inline Packet -pabs(const Packet& a) { using std::abs; return abs(a); } +// For booleans, we can only directly set a valid `bool` value to avoid UB. +template <> +struct ptrue_impl { + static EIGEN_DEVICE_FUNC inline bool run(const bool&) { return true; } +}; + +/** \internal \returns one bits. */ +template +EIGEN_DEVICE_FUNC inline Packet ptrue(const Packet& a) { + return ptrue_impl::run(a); +} + +// In the general packet case, memset to zero. +template +struct pzero_impl { + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& /*a*/) { + Packet b; + memset(static_cast(&b), 0x00, sizeof(Packet)); + return b; + } +}; + +// For scalars, explicitly set to Scalar(0), since the underlying representation +// for zero may not consist of all-zero bits. +template +struct pzero_impl::value>> { + static EIGEN_DEVICE_FUNC inline T run(const T& /*a*/) { return T(0); } +}; + +/** \internal \returns packet of zeros */ +template +EIGEN_DEVICE_FUNC inline Packet pzero(const Packet& a) { + return pzero_impl::run(a); +} + +template +struct bit_and { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE T operator()(const T& a, const T& b) const { return a & b; } +}; + +template +struct bit_or { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE T operator()(const T& a, const T& b) const { return a | b; } +}; + +template +struct bit_xor { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE T operator()(const T& a, const T& b) const { return a ^ b; } +}; + +template +struct bit_not { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE T operator()(const T& a) const { return ~a; } +}; + +template <> +struct bit_and { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE bool operator()(const bool& a, const bool& b) const { return a && b; } +}; + +template <> +struct bit_or { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE bool operator()(const bool& a, const bool& b) const { return a || b; } +}; + +template <> +struct bit_xor { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE bool operator()(const bool& a, const bool& b) const { return a != b; } +}; + +template <> +struct bit_not { + EIGEN_DEVICE_FUNC constexpr EIGEN_ALWAYS_INLINE bool operator()(const bool& a) const { return !a; } +}; + +// Use operators &, |, ^, ~. +template +struct operator_bitwise_helper { + EIGEN_DEVICE_FUNC static inline T bitwise_and(const T& a, const T& b) { return bit_and()(a, b); } + EIGEN_DEVICE_FUNC static inline T bitwise_or(const T& a, const T& b) { return bit_or()(a, b); } + EIGEN_DEVICE_FUNC static inline T bitwise_xor(const T& a, const T& b) { return bit_xor()(a, b); } + EIGEN_DEVICE_FUNC static inline T bitwise_not(const T& a) { return bit_not()(a); } +}; + +// Apply binary operations byte-by-byte +template +struct bytewise_bitwise_helper { + EIGEN_DEVICE_FUNC static inline T bitwise_and(const T& a, const T& b) { + return binary(a, b, bit_and()); + } + EIGEN_DEVICE_FUNC static inline T bitwise_or(const T& a, const T& b) { return binary(a, b, bit_or()); } + EIGEN_DEVICE_FUNC static inline T bitwise_xor(const T& a, const T& b) { + return binary(a, b, bit_xor()); + } + EIGEN_DEVICE_FUNC static inline T bitwise_not(const T& a) { return unary(a, bit_not()); } + + private: + template + EIGEN_DEVICE_FUNC static inline T unary(const T& a, Op op) { + const unsigned char* a_ptr = reinterpret_cast(&a); + T c; + unsigned char* c_ptr = reinterpret_cast(&c); + for (size_t i = 0; i < sizeof(T); ++i) { + *c_ptr++ = op(*a_ptr++); + } + return c; + } + + template + EIGEN_DEVICE_FUNC static inline T binary(const T& a, const T& b, Op op) { + const unsigned char* a_ptr = reinterpret_cast(&a); + const unsigned char* b_ptr = reinterpret_cast(&b); + T c; + unsigned char* c_ptr = reinterpret_cast(&c); + for (size_t i = 0; i < sizeof(T); ++i) { + *c_ptr++ = op(*a_ptr++, *b_ptr++); + } + return c; + } +}; + +// In the general case, use byte-by-byte manipulation. +template +struct bitwise_helper : public bytewise_bitwise_helper {}; + +// For integers or non-trivial scalars, use binary operators. +template +struct bitwise_helper::value && + (NumTraits::IsInteger || NumTraits::RequireInitialization)>> + : public operator_bitwise_helper {}; /** \internal \returns the bitwise and of \a a and \a b */ -template inline Packet -pand(const Packet& a, const Packet& b) { return a & b; } +template +EIGEN_DEVICE_FUNC inline Packet pand(const Packet& a, const Packet& b) { + return bitwise_helper::bitwise_and(a, b); +} /** \internal \returns the bitwise or of \a a and \a b */ -template inline Packet -por(const Packet& a, const Packet& b) { return a | b; } +template +EIGEN_DEVICE_FUNC inline Packet por(const Packet& a, const Packet& b) { + return bitwise_helper::bitwise_or(a, b); +} /** \internal \returns the bitwise xor of \a a and \a b */ -template inline Packet -pxor(const Packet& a, const Packet& b) { return a ^ b; } +template +EIGEN_DEVICE_FUNC inline Packet pxor(const Packet& a, const Packet& b) { + return bitwise_helper::bitwise_xor(a, b); +} + +/** \internal \returns the bitwise not of \a a */ +template +EIGEN_DEVICE_FUNC inline Packet pnot(const Packet& a) { + return bitwise_helper::bitwise_not(a); +} + +/** \internal \returns the bitwise and of \a a and not \a b */ +template +EIGEN_DEVICE_FUNC inline Packet pandnot(const Packet& a, const Packet& b) { + return pand(a, pnot(b)); +} + +/** \internal \returns a < b as a bit mask */ +template +EIGEN_DEVICE_FUNC inline Packet pcmp_lt(const Packet& a, const Packet& b) { + return a < b ? ptrue(a) : pzero(a); +} + +/** \internal \returns a == b as a bit mask */ +template +EIGEN_DEVICE_FUNC inline Packet pcmp_eq(const Packet& a, const Packet& b) { + return a == b ? ptrue(a) : pzero(a); +} + +/** \internal \returns a <= b as a bit mask */ +template +EIGEN_DEVICE_FUNC inline Packet pcmp_le(const Packet& a, const Packet& b) { + return por(pcmp_eq(a, b), pcmp_lt(a, b)); +} + +/** \internal \returns a < b or a==NaN or b==NaN as a bit mask */ +template +EIGEN_DEVICE_FUNC inline Packet pcmp_lt_or_nan(const Packet& a, const Packet& b) { + return a >= b ? pzero(a) : ptrue(a); +} + +// In the general case, use bitwise select. +template ::value> +struct pselect_impl { + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& mask, const Packet& a, const Packet& b) { + return por(pand(a, mask), pandnot(b, mask)); + } +}; + +// For scalars, use ternary select. +template +struct pselect_impl { + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& mask, const Packet& a, const Packet& b) { + return numext::select(mask, a, b); + } +}; + +/** \internal \returns \a or \b for each field in packet according to \mask */ +template +EIGEN_DEVICE_FUNC inline Packet pselect(const Packet& mask, const Packet& a, const Packet& b) { + return pselect_impl::run(mask, a, b); +} + +template <> +EIGEN_DEVICE_FUNC inline bool pselect(const bool& cond, const bool& a, const bool& b) { + return cond ? a : b; +} + +/** \internal \returns the min or of \a a and \a b (coeff-wise) + If either \a a or \a b are NaN, the result is implementation defined. */ +template +struct pminmax_impl { + template + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& a, const Packet& b, Op op) { + return op(a, b); + } +}; -/** \internal \returns the bitwise andnot of \a a and \a b */ -template inline Packet -pandnot(const Packet& a, const Packet& b) { return a & (!b); } +/** \internal \returns the min or max of \a a and \a b (coeff-wise) + If either \a a or \a b are NaN, NaN is returned. */ +template <> +struct pminmax_impl { + template + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& a, const Packet& b, Op op) { + Packet not_nan_mask_a = pcmp_eq(a, a); + Packet not_nan_mask_b = pcmp_eq(b, b); + return pselect(not_nan_mask_a, pselect(not_nan_mask_b, op(a, b), b), a); + } +}; + +/** \internal \returns the min or max of \a a and \a b (coeff-wise) + If both \a a and \a b are NaN, NaN is returned. + Equivalent to std::fmin(a, b). */ +template <> +struct pminmax_impl { + template + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& a, const Packet& b, Op op) { + Packet not_nan_mask_a = pcmp_eq(a, a); + Packet not_nan_mask_b = pcmp_eq(b, b); + return pselect(not_nan_mask_a, pselect(not_nan_mask_b, op(a, b), a), b); + } +}; -/** \internal \returns a packet version of \a *from, from must be 16 bytes aligned */ -template inline Packet -pload(const typename unpacket_traits::type* from) { return *from; } +#define EIGEN_BINARY_OP_NAN_PROPAGATION(Type, Func) [](const Type& aa, const Type& bb) { return Func(aa, bb); } + +/** \internal \returns the min of \a a and \a b (coeff-wise). + If \a a or \b b is NaN, the return value is implementation defined. */ +template +EIGEN_DEVICE_FUNC inline Packet pmin(const Packet& a, const Packet& b) { + return numext::mini(a, b); +} + +/** \internal \returns the min of \a a and \a b (coeff-wise). + NaNPropagation determines the NaN propagation semantics. */ +template +EIGEN_DEVICE_FUNC inline Packet pmin(const Packet& a, const Packet& b) { + constexpr bool IsInteger = NumTraits::type>::IsInteger; + return pminmax_impl::run(a, b, EIGEN_BINARY_OP_NAN_PROPAGATION(Packet, (pmin))); +} + +/** \internal \returns the max of \a a and \a b (coeff-wise) + If \a a or \b b is NaN, the return value is implementation defined. */ +template +EIGEN_DEVICE_FUNC inline Packet pmax(const Packet& a, const Packet& b) { + return numext::maxi(a, b); +} + +/** \internal \returns the max of \a a and \a b (coeff-wise). + NaNPropagation determines the NaN propagation semantics. */ +template +EIGEN_DEVICE_FUNC inline Packet pmax(const Packet& a, const Packet& b) { + constexpr bool IsInteger = NumTraits::type>::IsInteger; + return pminmax_impl::run(a, b, EIGEN_BINARY_OP_NAN_PROPAGATION(Packet, (pmax))); +} + +/** \internal \returns the absolute value of \a a */ +template +EIGEN_DEVICE_FUNC inline Packet pabs(const Packet& a) { + return numext::abs(a); +} +template <> +EIGEN_DEVICE_FUNC inline unsigned int pabs(const unsigned int& a) { + return a; +} +template <> +EIGEN_DEVICE_FUNC inline unsigned long pabs(const unsigned long& a) { + return a; +} +template <> +EIGEN_DEVICE_FUNC inline unsigned long long pabs(const unsigned long long& a) { + return a; +} + +/** \internal \returns the addsub value of \a a,b */ +template +EIGEN_DEVICE_FUNC inline Packet paddsub(const Packet& a, const Packet& b) { + return pselect(peven_mask(a), padd(a, b), psub(a, b)); +} + +/** \internal \returns the phase angle of \a a */ +template +EIGEN_DEVICE_FUNC inline Packet parg(const Packet& a) { + using numext::arg; + return arg(a); +} + +/** \internal \returns \a a arithmetically shifted by N bits to the right */ +template +EIGEN_DEVICE_FUNC inline T parithmetic_shift_right(const T& a) { + return numext::arithmetic_shift_right(a, N); +} + +/** \internal \returns \a a logically shifted by N bits to the right */ +template +EIGEN_DEVICE_FUNC inline T plogical_shift_right(const T& a) { + return numext::logical_shift_right(a, N); +} + +/** \internal \returns \a a shifted by N bits to the left */ +template +EIGEN_DEVICE_FUNC inline T plogical_shift_left(const T& a) { + return numext::logical_shift_left(a, N); +} + +/** \internal \returns the significant and exponent of the underlying floating point numbers + * See https://en.cppreference.com/w/cpp/numeric/math/frexp + */ +template +EIGEN_DEVICE_FUNC inline Packet pfrexp(const Packet& a, Packet& exponent) { + int exp; + EIGEN_USING_STD(frexp); + Packet result = static_cast(frexp(a, &exp)); + exponent = static_cast(exp); + return result; +} + +/** \internal \returns a * 2^((int)exponent) + * See https://en.cppreference.com/w/cpp/numeric/math/ldexp + */ +template +EIGEN_DEVICE_FUNC inline Packet pldexp(const Packet& a, const Packet& exponent) { + EIGEN_USING_STD(ldexp) + return static_cast(ldexp(a, static_cast(exponent))); +} + +/** \internal \returns the min of \a a and \a b (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet pabsdiff(const Packet& a, const Packet& b) { + return pselect(pcmp_lt(a, b), psub(b, a), psub(a, b)); +} + +/** \internal \returns a packet version of \a *from, from must be properly aligned */ +template +EIGEN_DEVICE_FUNC inline Packet pload(const typename unpacket_traits::type* from) { + return *from; +} + +/** \internal \returns n elements of a packet version of \a *from, from must be properly aligned + * offset indicates the starting element in which to load and + * offset + n <= unpacket_traits::size + * All elements before offset and after the last element loaded will initialized with zero */ +template +EIGEN_DEVICE_FUNC inline Packet pload_partial(const typename unpacket_traits::type* from, const Index n, + const Index offset = 0) { + const Index packet_size = unpacket_traits::size; + eigen_assert(n + offset <= packet_size && "number of elements plus offset will read past end of packet"); + typedef typename unpacket_traits::type Scalar; + EIGEN_ALIGN_MAX Scalar elements[packet_size] = {Scalar(0)}; + for (Index i = offset; i < numext::mini(n + offset, packet_size); i++) { + elements[i] = from[i - offset]; + } + return pload(elements); +} /** \internal \returns a packet version of \a *from, (un-aligned load) */ -template inline Packet -ploadu(const typename unpacket_traits::type* from) { return *from; } +template +EIGEN_DEVICE_FUNC inline Packet ploadu(const typename unpacket_traits::type* from) { + return *from; +} -/** \internal \returns a packet with elements of \a *from duplicated. - * For instance, for a packet of 8 elements, 4 scalar will be read from \a *from and - * duplicated to form: {from[0],from[0],from[1],from[1],,from[2],from[2],,from[3],from[3]} - * Currently, this function is only used for scalar * complex products. +/** \internal \returns n elements of a packet version of \a *from, (un-aligned load) + * All elements after the last element loaded will initialized with zero */ +template +EIGEN_DEVICE_FUNC inline Packet ploadu_partial(const typename unpacket_traits::type* from, const Index n, + const Index offset = 0) { + const Index packet_size = unpacket_traits::size; + eigen_assert(n + offset <= packet_size && "number of elements plus offset will read past end of packet"); + typedef typename unpacket_traits::type Scalar; + EIGEN_ALIGN_MAX Scalar elements[packet_size] = {Scalar(0)}; + for (Index i = offset; i < numext::mini(n + offset, packet_size); i++) { + elements[i] = from[i - offset]; + } + return pload(elements); +} + +/** \internal \returns a packet version of \a *from, (un-aligned masked load) + * There is no generic implementation. We only have implementations for specialized + * cases. Generic case should not be called. */ -template inline Packet -ploaddup(const typename unpacket_traits::type* from) { return *from; } +template +EIGEN_DEVICE_FUNC inline std::enable_if_t::masked_load_available, Packet> ploadu( + const typename unpacket_traits::type* from, typename unpacket_traits::mask_t umask); /** \internal \returns a packet with constant coefficients \a a, e.g.: (a,a,a,a) */ -template inline Packet -pset1(const typename unpacket_traits::type& a) { return a; } +template +EIGEN_DEVICE_FUNC inline Packet pset1(const typename unpacket_traits::type& a) { + return a; +} + +/** \internal \returns a packet with constant coefficients set from bits */ +template +EIGEN_DEVICE_FUNC inline Packet pset1frombits(BitsType a); + +/** \internal \returns a packet with constant coefficients \a a[0], e.g.: (a[0],a[0],a[0],a[0]) */ +template +EIGEN_DEVICE_FUNC inline Packet pload1(const typename unpacket_traits::type* a) { + return pset1(*a); +} + +/** \internal \returns a packet with elements of \a *from duplicated. + * For instance, for a packet of 8 elements, 4 scalars will be read from \a *from and + * duplicated to form: {from[0],from[0],from[1],from[1],from[2],from[2],from[3],from[3]} + * Currently, this function is only used for scalar * complex products. + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet ploaddup(const typename unpacket_traits::type* from) { + return *from; +} + +/** \internal \returns a packet with elements of \a *from quadrupled. + * For instance, for a packet of 8 elements, 2 scalars will be read from \a *from and + * replicated to form: {from[0],from[0],from[0],from[0],from[1],from[1],from[1],from[1]} + * Currently, this function is only used in matrix products. + * For packet-size smaller or equal to 4, this function is equivalent to pload1 + */ +template +EIGEN_DEVICE_FUNC inline Packet ploadquad(const typename unpacket_traits::type* from) { + return pload1(from); +} + +/** \internal equivalent to + * \code + * a0 = pload1(a+0); + * a1 = pload1(a+1); + * a2 = pload1(a+2); + * a3 = pload1(a+3); + * \endcode + * \sa pset1, pload1, ploaddup, pbroadcast2 + */ +template +EIGEN_DEVICE_FUNC inline void pbroadcast4(const typename unpacket_traits::type* a, Packet& a0, Packet& a1, + Packet& a2, Packet& a3) { + a0 = pload1(a + 0); + a1 = pload1(a + 1); + a2 = pload1(a + 2); + a3 = pload1(a + 3); +} + +/** \internal equivalent to + * \code + * a0 = pload1(a+0); + * a1 = pload1(a+1); + * \endcode + * \sa pset1, pload1, ploaddup, pbroadcast4 + */ +template +EIGEN_DEVICE_FUNC inline void pbroadcast2(const typename unpacket_traits::type* a, Packet& a0, Packet& a1) { + a0 = pload1(a + 0); + a1 = pload1(a + 1); +} /** \internal \brief Returns a packet with coefficients (a,a+1,...,a+packet_size-1). */ -template inline typename packet_traits::type -plset(const Scalar& a) { return a; } +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet plset(const typename unpacket_traits::type& a) { + return a; +} + +template +struct peven_mask_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run(const Packet&) { + typedef typename unpacket_traits::type Scalar; + const size_t n = unpacket_traits::size; + EIGEN_ALIGN_TO_BOUNDARY(sizeof(Packet)) Scalar elements[n]; + for (size_t i = 0; i < n; ++i) { + memset(elements + i, ((i & 1) == 0 ? 0xff : 0), sizeof(Scalar)); + } + return ploadu(elements); + } +}; + +template +struct peven_mask_impl::value>> { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run(const Scalar&) { return Scalar(1); } +}; + +/** \internal \returns a packet with constant coefficients \a a, e.g.: (x, 0, x, 0), + where x is the value of all 1-bits. */ +template +EIGEN_DEVICE_FUNC inline Packet peven_mask(const Packet& a) { + return peven_mask_impl::run(a); +} -/** \internal copy the packet \a from to \a *to, \a to must be 16 bytes aligned */ -template inline void pstore(Scalar* to, const Packet& from) -{ (*to) = from; } +/** \internal copy the packet \a from to \a *to, \a to must be properly aligned */ +template +EIGEN_DEVICE_FUNC inline void pstore(Scalar* to, const Packet& from) { + (*to) = from; +} + +/** \internal copy n elements of the packet \a from to \a *to, \a to must be properly aligned + * offset indicates the starting element in which to store and + * offset + n <= unpacket_traits::size */ +template +EIGEN_DEVICE_FUNC inline void pstore_partial(Scalar* to, const Packet& from, const Index n, const Index offset = 0) { + const Index packet_size = unpacket_traits::size; + eigen_assert(n + offset <= packet_size && "number of elements plus offset will write past end of packet"); + EIGEN_ALIGN_MAX Scalar elements[packet_size]; + pstore(elements, from); + for (Index i = 0; i < numext::mini(n, packet_size - offset); i++) { + to[i] = elements[i + offset]; + } +} /** \internal copy the packet \a from to \a *to, (un-aligned store) */ -template inline void pstoreu(Scalar* to, const Packet& from) -{ (*to) = from; } +template +EIGEN_DEVICE_FUNC inline void pstoreu(Scalar* to, const Packet& from) { + (*to) = from; +} -/** \internal tries to do cache prefetching of \a addr */ -template inline void prefetch(const Scalar* addr) -{ -#if !defined(_MSC_VER) -__builtin_prefetch(addr); -#endif +/** \internal copy n elements of the packet \a from to \a *to, (un-aligned store) */ +template +EIGEN_DEVICE_FUNC inline void pstoreu_partial(Scalar* to, const Packet& from, const Index n, const Index offset = 0) { + const Index packet_size = unpacket_traits::size; + eigen_assert(n + offset <= packet_size && "number of elements plus offset will write past end of packet"); + EIGEN_ALIGN_MAX Scalar elements[packet_size]; + pstore(elements, from); + for (Index i = 0; i < numext::mini(n, packet_size - offset); i++) { + to[i] = elements[i + offset]; + } } -/** \internal \returns the first element of a packet */ -template inline typename unpacket_traits::type pfirst(const Packet& a) -{ return a; } +/** \internal copy the packet \a from to \a *to, (un-aligned store with a mask) + * There is no generic implementation. We only have implementations for specialized + * cases. Generic case should not be called. + */ +template +EIGEN_DEVICE_FUNC inline std::enable_if_t::masked_store_available, void> pstoreu( + Scalar* to, const Packet& from, typename unpacket_traits::mask_t umask); -/** \internal \returns a packet where the element i contains the sum of the packet of \a vec[i] */ -template inline Packet -preduxp(const Packet* vecs) { return vecs[0]; } +template +EIGEN_DEVICE_FUNC inline Packet pgather(const Scalar* from, Index /*stride*/) { + return ploadu(from); +} -/** \internal \returns the sum of the elements of \a a*/ -template inline typename unpacket_traits::type predux(const Packet& a) -{ return a; } +template +EIGEN_DEVICE_FUNC inline Packet pgather_partial(const Scalar* from, Index stride, const Index n) { + const Index packet_size = unpacket_traits::size; + EIGEN_ALIGN_MAX Scalar elements[packet_size] = {Scalar(0)}; + for (Index i = 0; i < numext::mini(n, packet_size); i++) { + elements[i] = from[i * stride]; + } + return pload(elements); +} -/** \internal \returns the product of the elements of \a a*/ -template inline typename unpacket_traits::type predux_mul(const Packet& a) -{ return a; } +template +EIGEN_DEVICE_FUNC inline void pscatter(Scalar* to, const Packet& from, Index /*stride*/) { + pstore(to, from); +} -/** \internal \returns the min of the elements of \a a*/ -template inline typename unpacket_traits::type predux_min(const Packet& a) -{ return a; } +template +EIGEN_DEVICE_FUNC inline void pscatter_partial(Scalar* to, const Packet& from, Index stride, const Index n) { + const Index packet_size = unpacket_traits::size; + EIGEN_ALIGN_MAX Scalar elements[packet_size]; + pstore(elements, from); + for (Index i = 0; i < numext::mini(n, packet_size); i++) { + to[i * stride] = elements[i]; + } +} -/** \internal \returns the max of the elements of \a a*/ -template inline typename unpacket_traits::type predux_max(const Packet& a) -{ return a; } +/** \internal tries to do cache prefetching of \a addr */ +template +EIGEN_DEVICE_FUNC inline void prefetch(const Scalar* addr) { +#if defined(EIGEN_HIP_DEVICE_COMPILE) + // do nothing +#elif defined(EIGEN_CUDA_ARCH) +#if defined(__LP64__) || EIGEN_OS_WIN64 + // 64-bit pointer operand constraint for inlined asm + asm(" prefetch.L1 [ %1 ];" : "=l"(addr) : "l"(addr)); +#else + // 32-bit pointer operand constraint for inlined asm + asm(" prefetch.L1 [ %1 ];" : "=r"(addr) : "r"(addr)); +#endif +#elif (!EIGEN_COMP_MSVC) && (EIGEN_COMP_GNUC || EIGEN_COMP_CLANG || EIGEN_COMP_ICC) + __builtin_prefetch(addr); +#endif +} /** \internal \returns the reversed elements of \a a*/ -template inline Packet preverse(const Packet& a) -{ return a; } - +template +EIGEN_DEVICE_FUNC inline Packet preverse(const Packet& a) { + return a; +} /** \internal \returns \a a with real and imaginary part flipped (for complex type only) */ -template inline Packet pcplxflip(const Packet& a) -{ - // FIXME: uncomment the following in case we drop the internal imag and real functions. -// using std::imag; -// using std::real; - return Packet(imag(a),real(a)); +template +EIGEN_DEVICE_FUNC inline Packet pcplxflip(const Packet& a) { + return Packet(numext::imag(a), numext::real(a)); } /************************** -* Special math functions -***************************/ + * Special math functions + ***************************/ + +/** \internal \returns isnan(a) */ +template +EIGEN_DEVICE_FUNC inline Packet pisnan(const Packet& a) { + return pandnot(ptrue(a), pcmp_eq(a, a)); +} + +/** \internal \returns isinf(a) */ +template +EIGEN_DEVICE_FUNC inline Packet pisinf(const Packet& a) { + using Scalar = typename unpacket_traits::type; + constexpr Scalar inf = NumTraits::infinity(); + return pcmp_eq(pabs(a), pset1(inf)); +} /** \internal \returns the sine of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet psin(const Packet& a) { using std::sin; return sin(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet psin(const Packet& a) { + EIGEN_USING_STD(sin); + return sin(a); +} /** \internal \returns the cosine of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet pcos(const Packet& a) { using std::cos; return cos(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pcos(const Packet& a) { + EIGEN_USING_STD(cos); + return cos(a); +} /** \internal \returns the tan of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet ptan(const Packet& a) { using std::tan; return tan(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet ptan(const Packet& a) { + EIGEN_USING_STD(tan); + return tan(a); +} /** \internal \returns the arc sine of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet pasin(const Packet& a) { using std::asin; return asin(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pasin(const Packet& a) { + EIGEN_USING_STD(asin); + return asin(a); +} /** \internal \returns the arc cosine of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet pacos(const Packet& a) { using std::acos; return acos(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pacos(const Packet& a) { + EIGEN_USING_STD(acos); + return acos(a); +} + +/** \internal \returns the hyperbolic sine of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet psinh(const Packet& a) { + EIGEN_USING_STD(sinh); + return sinh(a); +} + +/** \internal \returns the hyperbolic cosine of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pcosh(const Packet& a) { + EIGEN_USING_STD(cosh); + return cosh(a); +} + +/** \internal \returns the arc tangent of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet patan(const Packet& a) { + EIGEN_USING_STD(atan); + return atan(a); +} + +/** \internal \returns the hyperbolic tan of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet ptanh(const Packet& a) { + EIGEN_USING_STD(tanh); + return tanh(a); +} + +/** \internal \returns the arc tangent of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet patanh(const Packet& a) { + EIGEN_USING_STD(atanh); + return atanh(a); +} /** \internal \returns the exp of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet pexp(const Packet& a) { using std::exp; return exp(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pexp(const Packet& a) { + return numext::exp(a); +} + +/** \internal \returns the exp2 of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pexp2(const Packet& a) { + return numext::exp2(a); +} + +/** \internal \returns the expm1 of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pexpm1(const Packet& a) { + return numext::expm1(a); +} /** \internal \returns the log of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet plog(const Packet& a) { using std::log; return log(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet plog(const Packet& a) { + EIGEN_USING_STD(log); + return log(a); +} + +/** \internal \returns the log1p of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet plog1p(const Packet& a) { + return numext::log1p(a); +} + +/** \internal \returns the log10 of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet plog10(const Packet& a) { + EIGEN_USING_STD(log10); + return log10(a); +} + +/** \internal \returns the log2 of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet plog2(const Packet& a) { + using Scalar = typename internal::unpacket_traits::type; + using RealScalar = typename NumTraits::Real; + return pmul(pset1(Scalar(RealScalar(EIGEN_LOG2E))), plog(a)); +} /** \internal \returns the square-root of \a a (coeff-wise) */ -template EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS -Packet psqrt(const Packet& a) { using std::sqrt; return sqrt(a); } +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet psqrt(const Packet& a) { + return numext::sqrt(a); +} -/*************************************************************************** -* The following functions might not have to be overwritten for vectorized types -***************************************************************************/ - -/** \internal copy a packet with constant coeficient \a a (e.g., [a,a,a,a]) to \a *to. \a to must be 16 bytes aligned */ -// NOTE: this function must really be templated on the packet type (think about different packet types for the same scalar type) -template -inline void pstore1(typename unpacket_traits::type* to, const typename unpacket_traits::type& a) -{ - pstore(to, pset1(a)); +/** \internal \returns the cube-root of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet pcbrt(const Packet& a) { + return numext::cbrt(a); +} + +template ::value, + bool IsInteger = NumTraits::type>::IsInteger> +struct nearest_integer_packetop_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run_floor(const Packet& x) { return numext::floor(x); } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run_ceil(const Packet& x) { return numext::ceil(x); } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run_rint(const Packet& x) { return numext::rint(x); } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run_round(const Packet& x) { return numext::round(x); } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet run_trunc(const Packet& x) { return numext::trunc(x); } +}; + +/** \internal \returns the rounded value of \a a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet pround(const Packet& a) { + return nearest_integer_packetop_impl::run_round(a); +} + +/** \internal \returns the floor of \a a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet pfloor(const Packet& a) { + return nearest_integer_packetop_impl::run_floor(a); +} + +/** \internal \returns the rounded value of \a a (coeff-wise) with current + * rounding mode */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet print(const Packet& a) { + return nearest_integer_packetop_impl::run_rint(a); +} + +/** \internal \returns the ceil of \a a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet pceil(const Packet& a) { + return nearest_integer_packetop_impl::run_ceil(a); +} + +/** \internal \returns the truncation of \a a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet ptrunc(const Packet& a) { + return nearest_integer_packetop_impl::run_trunc(a); +} + +template +struct psign_impl { + static EIGEN_DEVICE_FUNC inline Packet run(const Packet& a) { return numext::sign(a); } +}; + +/** \internal \returns the sign of \a a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet psign(const Packet& a) { + return psign_impl::run(a); +} + +template <> +EIGEN_DEVICE_FUNC inline bool psign(const bool& a) { + return a; +} + +/** \internal \returns the first element of a packet */ +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type pfirst(const Packet& a) { + return a; +} + +/** \internal \returns the sum of the elements of upper and lower half of \a a if \a a is larger than 4. + * For a packet {a0, a1, a2, a3, a4, a5, a6, a7}, it returns a half packet {a0+a4, a1+a5, a2+a6, a3+a7} + * For packet-size smaller or equal to 4, this boils down to a noop. + */ +template +EIGEN_DEVICE_FUNC inline std::conditional_t<(unpacket_traits::size % 8) == 0, + typename unpacket_traits::half, Packet> +predux_half_dowto4(const Packet& a) { + return a; +} + +// Slow generic implementation of Packet reduction. +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_helper(const Packet& a, Op op) { + typedef typename unpacket_traits::type Scalar; + const size_t n = unpacket_traits::size; + EIGEN_ALIGN_TO_BOUNDARY(sizeof(Packet)) Scalar elements[n]; + pstoreu(elements, a); + for (size_t k = n / 2; k > 0; k /= 2) { + for (size_t i = 0; i < k; ++i) { + elements[i] = op(elements[i], elements[i + k]); + } + } + return elements[0]; +} + +/** \internal \returns the sum of the elements of \a a*/ +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux(const Packet& a) { + return a; } +/** \internal \returns the product of the elements of \a a */ +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_mul(const Packet& a) { + typedef typename unpacket_traits::type Scalar; + return predux_helper(a, EIGEN_BINARY_OP_NAN_PROPAGATION(Scalar, (pmul))); +} + +/** \internal \returns the min of the elements of \a a */ +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_min(const Packet& a) { + typedef typename unpacket_traits::type Scalar; + return predux_helper(a, EIGEN_BINARY_OP_NAN_PROPAGATION(Scalar, (pmin))); +} + +/** \internal \returns the max of the elements of \a a */ +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_max(const Packet& a) { + typedef typename unpacket_traits::type Scalar; + return predux_helper(a, EIGEN_BINARY_OP_NAN_PROPAGATION(Scalar, (pmax))); +} + +template +struct predux_min_max_helper_impl { + using Scalar = typename unpacket_traits::type; + static constexpr bool UsePredux_ = NaNPropagation == PropagateFast || NumTraits::IsInteger; + template = true> + static EIGEN_DEVICE_FUNC inline Scalar run_min(const Packet& a) { + return predux_helper(a, EIGEN_BINARY_OP_NAN_PROPAGATION(Scalar, (pmin))); + } + template = true> + static EIGEN_DEVICE_FUNC inline Scalar run_max(const Packet& a) { + return predux_helper(a, EIGEN_BINARY_OP_NAN_PROPAGATION(Scalar, (pmax))); + } + template = true> + static EIGEN_DEVICE_FUNC inline Scalar run_min(const Packet& a) { + return predux_min(a); + } + template = true> + static EIGEN_DEVICE_FUNC inline Scalar run_max(const Packet& a) { + return predux_max(a); + } +}; + +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_min(const Packet& a) { + return predux_min_max_helper_impl::run_min(a); +} + +template +EIGEN_DEVICE_FUNC inline typename unpacket_traits::type predux_max(const Packet& a) { + return predux_min_max_helper_impl::run_max(a); +} + +#undef EIGEN_BINARY_OP_NAN_PROPAGATION + +/** \internal \returns true if all coeffs of \a a means "true" + * It is supposed to be called on values returned by pcmp_*. + */ +// not needed yet +// template EIGEN_DEVICE_FUNC inline bool predux_all(const Packet& a) +// { return bool(a); } + +/** \internal \returns true if any coeffs of \a a means "true" + * It is supposed to be called on values returned by pcmp_*. + */ +template +EIGEN_DEVICE_FUNC inline bool predux_any(const Packet& a) { + // Dirty but generic implementation where "true" is assumed to be non 0 and all the sames. + // It is expected that "true" is either: + // - Scalar(1) + // - bits full of ones (NaN for floats), + // - or first bit equals to 1 (1 for ints, smallest denormal for floats). + // For all these cases, taking the sum is just fine, and this boils down to a no-op for scalars. + typedef typename unpacket_traits::type Scalar; + return numext::not_equal_strict(predux(a), Scalar(0)); +} + +/*************************************************************************** + * The following functions might not have to be overwritten for vectorized types + ***************************************************************************/ + +template +struct pmadd_impl { + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pmadd(const Packet& a, const Packet& b, const Packet& c) { + return padd(pmul(a, b), c); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pmsub(const Packet& a, const Packet& b, const Packet& c) { + return psub(pmul(a, b), c); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pnmadd(const Packet& a, const Packet& b, const Packet& c) { + return psub(c, pmul(a, b)); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pnmsub(const Packet& a, const Packet& b, const Packet& c) { + return pnegate(pmadd(a, b, c)); + } +}; + +template +struct pmadd_impl::value && NumTraits::IsSigned>> { + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar pmadd(const Scalar& a, const Scalar& b, const Scalar& c) { + return numext::madd(a, b, c); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar pmsub(const Scalar& a, const Scalar& b, const Scalar& c) { + return numext::madd(a, b, Scalar(-c)); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar pnmadd(const Scalar& a, const Scalar& b, const Scalar& c) { + return numext::madd(Scalar(-a), b, c); + } + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar pnmsub(const Scalar& a, const Scalar& b, const Scalar& c) { + return -Scalar(numext::madd(a, b, c)); + } +}; + +// Multiply-add instructions. /** \internal \returns a * b + c (coeff-wise) */ -template inline Packet -pmadd(const Packet& a, - const Packet& b, - const Packet& c) -{ return padd(pmul(a, b),c); } +template +EIGEN_DEVICE_FUNC inline Packet pmadd(const Packet& a, const Packet& b, const Packet& c) { + return pmadd_impl::pmadd(a, b, c); +} + +/** \internal \returns a * b - c (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet pmsub(const Packet& a, const Packet& b, const Packet& c) { + return pmadd_impl::pmsub(a, b, c); +} + +/** \internal \returns -(a * b) + c (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet pnmadd(const Packet& a, const Packet& b, const Packet& c) { + return pmadd_impl::pnmadd(a, b, c); +} + +/** \internal \returns -((a * b + c) (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet pnmsub(const Packet& a, const Packet& b, const Packet& c) { + return pmadd_impl::pnmsub(a, b, c); +} + +/** \internal copy a packet with constant coefficient \a a (e.g., [a,a,a,a]) to \a *to. \a to must be 16 bytes aligned + */ +// NOTE: this function must really be templated on the packet type (think about different packet types for the same +// scalar type) +template +inline void pstore1(typename unpacket_traits::type* to, const typename unpacket_traits::type& a) { + pstore(to, pset1(a)); +} /** \internal \returns a packet version of \a *from. - * If LoadMode equals #Aligned, \a from must be 16 bytes aligned */ -template -inline Packet ploadt(const typename unpacket_traits::type* from) -{ - if(LoadMode == Aligned) + * The pointer \a from must be aligned on a \a Alignment bytes boundary. */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt(const typename unpacket_traits::type* from) { + if (Alignment >= unpacket_traits::alignment) return pload(from); else return ploadu(from); } +/** \internal \returns n elements of a packet version of \a *from. + * The pointer \a from must be aligned on a \a Alignment bytes boundary. */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_partial(const typename unpacket_traits::type* from, + const Index n, const Index offset = 0) { + if (Alignment >= unpacket_traits::alignment) + return pload_partial(from, n, offset); + else + return ploadu_partial(from, n, offset); +} + /** \internal copy the packet \a from to \a *to. - * If StoreMode equals #Aligned, \a to must be 16 bytes aligned */ -template -inline void pstoret(Scalar* to, const Packet& from) -{ - if(LoadMode == Aligned) + * The pointer \a from must be aligned on a \a Alignment bytes boundary. */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret(Scalar* to, const Packet& from) { + if (Alignment >= unpacket_traits::alignment) pstore(to, from); else pstoreu(to, from); } -/** \internal default implementation of palign() allowing partial specialization */ -template -struct palign_impl -{ - // by default data are aligned, so there is nothing to be done :) - static inline void run(PacketType&, const PacketType&) {} -}; - -/** \internal update \a first using the concatenation of the packet_size minus \a Offset last elements - * of \a first and \a Offset first elements of \a second. - * - * This function is currently only used to optimize matrix-vector products on unligned matrices. - * It takes 2 packets that represent a contiguous memory array, and returns a packet starting - * at the position \a Offset. For instance, for packets of 4 elements, we have: - * Input: - * - first = {f0,f1,f2,f3} - * - second = {s0,s1,s2,s3} - * Output: - * - if Offset==0 then {f0,f1,f2,f3} - * - if Offset==1 then {f1,f2,f3,s0} - * - if Offset==2 then {f2,f3,s0,s1} - * - if Offset==3 then {f3,s0,s1,s3} - */ -template -inline void palign(PacketType& first, const PacketType& second) -{ - palign_impl::run(first,second); +/** \internal copy n elements of the packet \a from to \a *to. + * The pointer \a from must be aligned on a \a Alignment bytes boundary. */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE void pstoret_partial(Scalar* to, const Packet& from, const Index n, + const Index offset = 0) { + if (Alignment >= unpacket_traits::alignment) + pstore_partial(to, from, n, offset); + else + pstoreu_partial(to, from, n, offset); +} + +/** \internal \returns a packet version of \a *from. + * Unlike ploadt, ploadt_ro takes advantage of the read-only memory path on the + * hardware if available to speedup the loading of data that won't be modified + * by the current computation. + */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet ploadt_ro(const typename unpacket_traits::type* from) { + return ploadt(from); } /*************************************************************************** -* Fast complex products (GCC generates a function call which is very slow) -***************************************************************************/ + * Fast complex products (GCC generates a function call which is very slow) + ***************************************************************************/ + +// Eigen+CUDA does not support complexes. +#if !defined(EIGEN_GPUCC) -template<> inline std::complex pmul(const std::complex& a, const std::complex& b) -{ return std::complex(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); } +template <> +inline std::complex pmul(const std::complex& a, const std::complex& b) { + return std::complex(a.real() * b.real() - a.imag() * b.imag(), a.imag() * b.real() + a.real() * b.imag()); +} + +template <> +inline std::complex pmul(const std::complex& a, const std::complex& b) { + return std::complex(a.real() * b.real() - a.imag() * b.imag(), a.imag() * b.real() + a.real() * b.imag()); +} -template<> inline std::complex pmul(const std::complex& a, const std::complex& b) -{ return std::complex(real(a)*real(b) - imag(a)*imag(b), imag(a)*real(b) + real(a)*imag(b)); } +#endif + +/*************************************************************************** + * PacketBlock, that is a collection of N packets where the number of words + * in the packet is a multiple of N. + ***************************************************************************/ +template ::size> +struct PacketBlock { + Packet packet[N]; +}; + +template +EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock& /*kernel*/) { + // Nothing to do in the scalar case, i.e. a 1x1 matrix. +} + +/*************************************************************************** + * Selector, i.e. vector of N boolean values used to select (i.e. blend) + * words from 2 packets. + ***************************************************************************/ +template +struct Selector { + bool select[N]; +}; + +template +EIGEN_DEVICE_FUNC inline Packet pblend(const Selector::size>& ifPacket, + const Packet& thenPacket, const Packet& elsePacket) { + return ifPacket.select[0] ? thenPacket : elsePacket; +} + +/** \internal \returns 1 / a (coeff-wise) */ +template +EIGEN_DEVICE_FUNC inline Packet preciprocal(const Packet& a) { + using Scalar = typename unpacket_traits::type; + return pdiv(pset1(Scalar(1)), a); +} + +/** \internal \returns the reciprocal square-root of \a a (coeff-wise) */ +template +EIGEN_DECLARE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS Packet prsqrt(const Packet& a) { + return preciprocal(psqrt(a)); +} + +template ::value, + bool IsInteger = NumTraits::type>::IsInteger> +struct psignbit_impl; +template +struct psignbit_impl { + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Packet run(const Packet& a) { return numext::signbit(a); } +}; +template +struct psignbit_impl { + // generic implementation if not specialized in PacketMath.h + // slower than arithmetic shift + typedef typename unpacket_traits::type Scalar; + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static Packet run(const Packet& a) { + const Packet cst_pos_one = pset1(Scalar(1)); + const Packet cst_neg_one = pset1(Scalar(-1)); + return pcmp_eq(por(pand(a, cst_neg_one), cst_pos_one), cst_neg_one); + } +}; +template +struct psignbit_impl { + // generic implementation for integer packets + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Packet run(const Packet& a) { return pcmp_lt(a, pzero(a)); } +}; +/** \internal \returns the sign bit of \a a as a bitmask*/ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE constexpr Packet psignbit(const Packet& a) { + return psignbit_impl::run(a); +} + +/** \internal \returns the 2-argument arc tangent of \a y and \a x (coeff-wise) */ +template ::value, int> = 0> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet patan2(const Packet& y, const Packet& x) { + return numext::atan2(y, x); +} + +/** \internal \returns the 2-argument arc tangent of \a y and \a x (coeff-wise) */ +template ::value, int> = 0> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet patan2(const Packet& y, const Packet& x) { + typedef typename internal::unpacket_traits::type Scalar; + + // See https://en.cppreference.com/w/cpp/numeric/math/atan2 + // for how corner cases are supposed to be handled according to the + // IEEE floating-point standard (IEC 60559). + const Packet kSignMask = pset1(-Scalar(0)); + const Packet kZero = pzero(x); + const Packet kOne = pset1(Scalar(1)); + const Packet kPi = pset1(Scalar(EIGEN_PI)); + + const Packet x_has_signbit = psignbit(x); + const Packet y_signmask = pand(y, kSignMask); + const Packet x_signmask = pand(x, kSignMask); + const Packet result_signmask = pxor(y_signmask, x_signmask); + const Packet shift = por(pand(x_has_signbit, kPi), y_signmask); + + const Packet x_and_y_are_same = pcmp_eq(pabs(x), pabs(y)); + const Packet x_and_y_are_zero = pcmp_eq(por(x, y), kZero); + + Packet arg = pdiv(y, x); + arg = pselect(x_and_y_are_same, por(kOne, result_signmask), arg); + arg = pselect(x_and_y_are_zero, result_signmask, arg); + + Packet result = patan(arg); + result = padd(result, shift); + return result; +} + +/** \internal \returns the argument of \a a as a complex number */ +template ::value, int> = 0> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pcarg(const Packet& a) { + return Packet(numext::arg(a)); +} + +/** \internal \returns the argument of \a a as a complex number */ +template ::value, int> = 0> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Packet pcarg(const Packet& a) { + EIGEN_STATIC_ASSERT(NumTraits::type>::IsComplex, + THIS METHOD IS FOR COMPLEX TYPES ONLY) + using RealPacket = typename unpacket_traits::as_real; + // a // r i r i ... + RealPacket aflip = pcplxflip(a).v; // i r i r ... + RealPacket result = patan2(aflip, a.v); // atan2 crap atan2 crap ... + return (Packet)pand(result, peven_mask(result)); // atan2 0 atan2 0 ... +} + +/** \internal \returns a packet populated with values in the range [begin, begin + count). Elements + * outside this range are not defined. \a *from does not need to be aligned, and can be null if \a count is zero.*/ +template +EIGEN_DEVICE_FUNC inline Packet ploaduSegment(const typename unpacket_traits::type* from, Index begin, + Index count) { + using Scalar = typename unpacket_traits::type; + constexpr Index PacketSize = unpacket_traits::size; + eigen_assert((begin >= 0 && count >= 0 && begin + count <= PacketSize) && "invalid range"); + Scalar aux[PacketSize] = {}; + for (Index k = begin; k < begin + count; k++) { + aux[k] = from[k]; + } + return ploadu(aux); +} + +/** \internal \returns a packet populated with values in the range [begin, begin + count). Elements + * outside this range are not defined. \a *from must be aligned, and cannot be null.*/ +template +EIGEN_DEVICE_FUNC inline Packet ploadSegment(const typename unpacket_traits::type* from, Index begin, + Index count) { + return ploaduSegment(from, begin, count); +} + +/** \internal copy the packet \a from in the range [begin, begin + count) to \a *to. +Elements outside of the range [begin, begin + count) are not defined. \a *to does not need to be aligned, and can be +null if \a count is zero.*/ +template +EIGEN_DEVICE_FUNC inline void pstoreuSegment(Scalar* to, const Packet& from, Index begin, Index count) { + constexpr Index PacketSize = unpacket_traits::size; + eigen_assert((begin >= 0 && count >= 0 && begin + count <= PacketSize) && "invalid range"); + Scalar aux[PacketSize]; + pstoreu(aux, from); + for (Index k = begin; k < begin + count; k++) { + to[k] = aux[k]; + } +} + +/** \internal copy the packet \a from in the range [begin, begin + count) to \a *to. +Elements outside of the range [begin, begin + count) are not defined. \a *to must be aligned, and cannot be +null.*/ +template +EIGEN_DEVICE_FUNC inline void pstoreSegment(Scalar* to, const Packet& from, Index begin, Index count) { + return pstoreuSegment(to, from, begin, count); +} + +/** \internal \returns a packet populated with values in the range [begin, begin + count). Elements + * outside this range are not defined.*/ +template +EIGEN_DEVICE_FUNC inline Packet ploadtSegment(const typename unpacket_traits::type* from, Index begin, + Index count) { + constexpr int RequiredAlignment = unpacket_traits::alignment; + if (Alignment >= RequiredAlignment) { + return ploadSegment(from, begin, count); + } else { + return ploaduSegment(from, begin, count); + } +} + +/** \internal copy the packet \a from in the range [begin, begin + count) to \a *to. +Elements outside of the range [begin, begin + count) are not defined.*/ +template +EIGEN_DEVICE_FUNC inline void pstoretSegment(Scalar* to, const Packet& from, Index begin, Index count) { + constexpr int RequiredAlignment = unpacket_traits::alignment; + if (Alignment >= RequiredAlignment) { + pstoreSegment(to, from, begin, count); + } else { + pstoreuSegment(to, from, begin, count); + } +} + +#ifndef EIGEN_NO_IO + +template +class StreamablePacket { + public: + using Scalar = typename unpacket_traits::type; + StreamablePacket(const Packet& packet) { pstoreu(v_, packet); } + + friend std::ostream& operator<<(std::ostream& os, const StreamablePacket& packet) { + os << "{" << packet.v_[0]; + for (int i = 1; i < unpacket_traits::size; ++i) { + os << "," << packet.v_[i]; + } + os << "}"; + return os; + } + + private: + Scalar v_[unpacket_traits::size]; +}; + +/** + * \internal \returns an intermediary that can be used to ostream packets, e.g. for debugging. + */ +template +StreamablePacket postream(const Packet& packet) { + return StreamablePacket(packet); +} -} // end namespace internal +#endif // EIGEN_NO_IO -} // end namespace Eigen +} // end namespace internal -#endif // EIGEN_GENERIC_PACKET_MATH_H +} // end namespace Eigen +#endif // EIGEN_GENERIC_PACKET_MATH_H diff --git a/inst/include/Eigen/src/Core/GlobalFunctions.h b/inst/include/Eigen/src/Core/GlobalFunctions.h index 2acf9772..df1098e2 100644 --- a/inst/include/Eigen/src/Core/GlobalFunctions.h +++ b/inst/include/Eigen/src/Core/GlobalFunctions.h @@ -1,7 +1,7 @@ // This file is part of Eigen, a lightweight C++ template library // for linear algebra. // -// Copyright (C) 2010-2012 Gael Guennebaud +// Copyright (C) 2010-2016 Gael Guennebaud // Copyright (C) 2010 Benoit Jacob // // This Source Code Form is subject to the terms of the Mozilla @@ -11,82 +11,220 @@ #ifndef EIGEN_GLOBAL_FUNCTIONS_H #define EIGEN_GLOBAL_FUNCTIONS_H -#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME,FUNCTOR) \ - template \ - inline const Eigen::CwiseUnaryOp, const Derived> \ - NAME(const Eigen::ArrayBase& x) { \ - return x.derived(); \ +#ifdef EIGEN_PARSED_BY_DOXYGEN + +#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME, FUNCTOR, DOC_OP, DOC_DETAILS) \ + /** \returns an expression of the coefficient-wise DOC_OP of \a x \ + \ \ + DOC_DETAILS \ + \ \ + \sa Math functions, class CwiseUnaryOp \ + */ \ + template \ + inline const Eigen::CwiseUnaryOp, const Derived> NAME( \ + const Eigen::ArrayBase& x); + +#else + +#define EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(NAME, FUNCTOR, DOC_OP, DOC_DETAILS) \ + template \ + inline const Eigen::CwiseUnaryOp, const Derived>(NAME)( \ + const Eigen::ArrayBase& x) { \ + return Eigen::CwiseUnaryOp, const Derived>(x.derived()); \ } -#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME,FUNCTOR) \ - \ - template \ - struct NAME##_retval > \ - { \ +#endif // EIGEN_PARSED_BY_DOXYGEN + +#define EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(NAME, FUNCTOR) \ + \ + template \ + struct NAME##_retval > { \ typedef const Eigen::CwiseUnaryOp, const Derived> type; \ - }; \ - template \ - struct NAME##_impl > \ - { \ - static inline typename NAME##_retval >::type run(const Eigen::ArrayBase& x) \ - { \ - return x.derived(); \ - } \ + }; \ + template \ + struct NAME##_impl > { \ + static inline typename NAME##_retval >::type run(const Eigen::ArrayBase& x) { \ + return typename NAME##_retval >::type(x.derived()); \ + } \ }; +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -namespace Eigen -{ - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real,scalar_real_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag,scalar_imag_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj,scalar_conjugate_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin,scalar_sin_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos,scalar_cos_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin,scalar_asin_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos,scalar_acos_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan,scalar_tan_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp,scalar_exp_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log,scalar_log_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs,scalar_abs_op) - EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt,scalar_sqrt_op) - - template - inline const Eigen::CwiseUnaryOp, const Derived> - pow(const Eigen::ArrayBase& x, const typename Derived::Scalar& exponent) { - return x.derived().pow(exponent); - } +namespace Eigen { +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(real, scalar_real_op, real part,\sa ArrayBase::real) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(imag, scalar_imag_op, imaginary part,\sa ArrayBase::imag) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(conj, scalar_conjugate_op, complex conjugate,\sa ArrayBase::conjugate) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(inverse, scalar_inverse_op, inverse,\sa ArrayBase::inverse) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sin, scalar_sin_op, sine,\sa ArrayBase::sin) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cos, scalar_cos_op, cosine,\sa ArrayBase::cos) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tan, scalar_tan_op, tangent,\sa ArrayBase::tan) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atan, scalar_atan_op, arc - tangent,\sa ArrayBase::atan) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asin, scalar_asin_op, arc - sine,\sa ArrayBase::asin) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acos, scalar_acos_op, arc - consine,\sa ArrayBase::acos) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sinh, scalar_sinh_op, hyperbolic sine,\sa ArrayBase::sinh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cosh, scalar_cosh_op, hyperbolic cosine,\sa ArrayBase::cosh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(tanh, scalar_tanh_op, hyperbolic tangent,\sa ArrayBase::tanh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(asinh, scalar_asinh_op, inverse hyperbolic sine,\sa ArrayBase::asinh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(acosh, scalar_acosh_op, inverse hyperbolic cosine,\sa ArrayBase::acosh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(atanh, scalar_atanh_op, inverse hyperbolic tangent,\sa ArrayBase::atanh) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(logistic, scalar_logistic_op, logistic function,\sa ArrayBase::logistic) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(lgamma, scalar_lgamma_op, + natural logarithm of the gamma function,\sa ArrayBase::lgamma) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(digamma, scalar_digamma_op, derivative of lgamma,\sa ArrayBase::digamma) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erf, scalar_erf_op, error function,\sa ArrayBase::erf) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(erfc, scalar_erfc_op, complement error function,\sa ArrayBase::erfc) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(ndtri, scalar_ndtri_op, inverse normal distribution function,\sa ArrayBase::ndtri) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp, scalar_exp_op, exponential,\sa ArrayBase::exp) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(exp2, scalar_exp2_op, exponential,\sa ArrayBase::exp2) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(expm1, scalar_expm1_op, exponential of a value minus 1,\sa ArrayBase::expm1) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log, scalar_log_op, natural logarithm,\sa Eigen::log10 DOXCOMMA ArrayBase::log) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log1p, scalar_log1p_op, natural logarithm of 1 plus the value,\sa ArrayBase::log1p) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log10, scalar_log10_op, base 10 logarithm,\sa Eigen::log DOXCOMMA ArrayBase::log10) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(log2, scalar_log2_op, base 2 logarithm,\sa Eigen::log DOXCOMMA ArrayBase::log2) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs, scalar_abs_op, absolute value,\sa ArrayBase::abs DOXCOMMA MatrixBase::cwiseAbs) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(abs2, scalar_abs2_op, + squared absolute value,\sa ArrayBase::abs2 DOXCOMMA MatrixBase::cwiseAbs2) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(arg, scalar_arg_op, complex argument,\sa ArrayBase::arg DOXCOMMA MatrixBase::cwiseArg) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(carg, scalar_carg_op, + complex argument, \sa ArrayBase::carg DOXCOMMA MatrixBase::cwiseCArg) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sqrt, scalar_sqrt_op, square root,\sa ArrayBase::sqrt DOXCOMMA MatrixBase::cwiseSqrt) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cbrt, scalar_cbrt_op, cube root,\sa ArrayBase::cbrt DOXCOMMA MatrixBase::cwiseCbrt) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(rsqrt, scalar_rsqrt_op, reciprocal square root,\sa ArrayBase::rsqrt) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(square, scalar_square_op, + square(power 2),\sa Eigen::abs2 DOXCOMMA Eigen::pow DOXCOMMA ArrayBase::square) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(cube, scalar_cube_op, cube(power 3),\sa Eigen::pow DOXCOMMA ArrayBase::cube) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(rint, scalar_rint_op, + nearest integer,\sa Eigen::floor DOXCOMMA Eigen::ceil DOXCOMMA ArrayBase::round) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(round, scalar_round_op, + nearest integer,\sa Eigen::floor DOXCOMMA Eigen::ceil DOXCOMMA ArrayBase::round) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY( + floor, scalar_floor_op, nearest integer not greater than the given value,\sa Eigen::ceil DOXCOMMA ArrayBase::floor) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY( + ceil, scalar_ceil_op, nearest integer not less than the given value,\sa Eigen::floor DOXCOMMA ArrayBase::ceil) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(trunc, scalar_trunc_op, + nearest integer not greater in magnitude than the given value,\sa Eigen::trunc DOXCOMMA + ArrayBase::trunc) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY( + isnan, scalar_isnan_op, not -a - number test,\sa Eigen::isinf DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isnan) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY( + isinf, scalar_isinf_op, infinite value test,\sa Eigen::isnan DOXCOMMA Eigen::isfinite DOXCOMMA ArrayBase::isinf) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(isfinite, scalar_isfinite_op, + finite value test,\sa Eigen::isinf DOXCOMMA Eigen::isnan DOXCOMMA ArrayBase::isfinite) +EIGEN_ARRAY_DECLARE_GLOBAL_UNARY(sign, scalar_sign_op, sign(or 0),\sa ArrayBase::sign) - template - inline const Eigen::CwiseBinaryOp, const Derived, const Derived> - pow(const Eigen::ArrayBase& x, const Eigen::ArrayBase& exponents) - { - return Eigen::CwiseBinaryOp, const Derived, const Derived>( - x.derived(), - exponents.derived() - ); - } - - /** - * \brief Component-wise division of a scalar by array elements. - **/ - template - inline const Eigen::CwiseUnaryOp, const Derived> - operator/(const typename Derived::Scalar& s, const Eigen::ArrayBase& a) - { - return Eigen::CwiseUnaryOp, const Derived>( - a.derived(), - Eigen::internal::scalar_inverse_mult_op(s) - ); - } +template +using GlobalUnaryPowReturnType = std::enable_if_t< + !internal::is_arithmetic::Real>::value && + internal::is_arithmetic::Real>::value, + CwiseUnaryOp, const Derived> >; - namespace internal - { - EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real,scalar_real_op) - EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag,scalar_imag_op) - EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2,scalar_abs2_op) - } +/** \returns an expression of the coefficient-wise power of \a x to the given constant \a exponent. + * + * \tparam ScalarExponent is the scalar type of \a exponent. It must be compatible with the scalar type of the given + * expression (\c Derived::Scalar). + * + * \sa ArrayBase::pow() + * + * \relates ArrayBase + */ +#ifdef EIGEN_PARSED_BY_DOXYGEN +template +EIGEN_DEVICE_FUNC inline const GlobalUnaryPowReturnType pow(const Eigen::ArrayBase& x, + const ScalarExponent& exponent); +#else +template +EIGEN_DEVICE_FUNC inline const GlobalUnaryPowReturnType pow(const Eigen::ArrayBase& x, + const ScalarExponent& exponent) { + return GlobalUnaryPowReturnType( + x.derived(), internal::scalar_unary_pow_op(exponent)); } +#endif + +/** \returns an expression of the coefficient-wise power of \a x to the given array of \a exponents. + * + * This function computes the coefficient-wise power. + * + * Example: \include Cwise_array_power_array.cpp + * Output: \verbinclude Cwise_array_power_array.out + * + * \sa ArrayBase::pow() + * + * \relates ArrayBase + */ +template +inline const Eigen::CwiseBinaryOp< + Eigen::internal::scalar_pow_op, const Derived, + const ExponentDerived> +pow(const Eigen::ArrayBase& x, const Eigen::ArrayBase& exponents) { + return Eigen::CwiseBinaryOp< + Eigen::internal::scalar_pow_op, const Derived, + const ExponentDerived>(x.derived(), exponents.derived()); +} + +/** \returns an expression of the coefficient-wise power of the scalar \a x to the given array of \a exponents. + * + * This function computes the coefficient-wise power between a scalar and an array of exponents. + * + * \tparam Scalar is the scalar type of \a x. It must be compatible with the scalar type of the given array expression + * (\c Derived::Scalar). + * + * Example: \include Cwise_scalar_power_array.cpp + * Output: \verbinclude Cwise_scalar_power_array.out + * + * \sa ArrayBase::pow() + * + * \relates ArrayBase + */ +#ifdef EIGEN_PARSED_BY_DOXYGEN +template +inline const CwiseBinaryOp, Constant, Derived> pow( + const Scalar& x, const Eigen::ArrayBase& x); +#else +template +EIGEN_DEVICE_FUNC inline const EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE( + typename internal::promote_scalar_arg::type, + Derived, pow) pow(const Scalar& x, const Eigen::ArrayBase& exponents) { + typedef + typename internal::promote_scalar_arg::type + PromotedScalar; + return EIGEN_SCALAR_BINARYOP_EXPR_RETURN_TYPE(PromotedScalar, Derived, pow)( + typename internal::plain_constant_type::type( + exponents.derived().rows(), exponents.derived().cols(), internal::scalar_constant_op(x)), + exponents.derived()); +} +#endif + +/** \returns an expression of the coefficient-wise atan2(\a x, \a y). \a x and \a y must be of the same type. + * + * This function computes the coefficient-wise atan2(). + * + * \sa ArrayBase::atan2() + * + * \relates ArrayBase + */ +template +inline const std::enable_if_t< + std::is_same::value, + Eigen::CwiseBinaryOp, + const LhsDerived, const RhsDerived> > +atan2(const Eigen::ArrayBase& x, const Eigen::ArrayBase& exponents) { + return Eigen::CwiseBinaryOp< + Eigen::internal::scalar_atan2_op, const LhsDerived, + const RhsDerived>(x.derived(), exponents.derived()); +} + +namespace internal { +EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(real, scalar_real_op) +EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(imag, scalar_imag_op) +EIGEN_ARRAY_DECLARE_GLOBAL_EIGEN_UNARY(abs2, scalar_abs2_op) +} // namespace internal +} // namespace Eigen -// TODO: cleanly disable those functions that are not supported on Array (numext::real_ref, internal::random, internal::isApprox...) +// TODO: cleanly disable those functions that are not supported on Array (numext::real_ref, internal::random, +// internal::isApprox...) -#endif // EIGEN_GLOBAL_FUNCTIONS_H +#endif // EIGEN_GLOBAL_FUNCTIONS_H diff --git a/inst/include/Eigen/src/Core/IO.h b/inst/include/Eigen/src/Core/IO.h index 8d4bc59e..0a1b583d 100644 --- a/inst/include/Eigen/src/Core/IO.h +++ b/inst/include/Eigen/src/Core/IO.h @@ -11,55 +11,65 @@ #ifndef EIGEN_IO_H #define EIGEN_IO_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { enum { DontAlignCols = 1 }; -enum { StreamPrecision = -1, - FullPrecision = -2 }; +enum { StreamPrecision = -1, FullPrecision = -2 }; namespace internal { -template -std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt); +template +std::ostream& print_matrix(std::ostream& s, const Derived& _m, const IOFormat& fmt); } /** \class IOFormat - * \ingroup Core_Module - * - * \brief Stores a set of parameters controlling the way matrices are printed - * - * List of available parameters: - * - \b precision number of digits for floating point values, or one of the special constants \c StreamPrecision and \c FullPrecision. - * The default is the special value \c StreamPrecision which means to use the - * stream's own precision setting, as set for instance using \c cout.precision(3). The other special value - * \c FullPrecision means that the number of digits will be computed to match the full precision of each floating-point - * type. - * - \b flags an OR-ed combination of flags, the default value is 0, the only currently available flag is \c DontAlignCols which - * allows to disable the alignment of columns, resulting in faster code. - * - \b coeffSeparator string printed between two coefficients of the same row - * - \b rowSeparator string printed between two rows - * - \b rowPrefix string printed at the beginning of each row - * - \b rowSuffix string printed at the end of each row - * - \b matPrefix string printed at the beginning of the matrix - * - \b matSuffix string printed at the end of the matrix - * - * Example: \include IOFormat.cpp - * Output: \verbinclude IOFormat.out - * - * \sa DenseBase::format(), class WithFormat - */ -struct IOFormat -{ - /** Default contructor, see class IOFormat for the meaning of the parameters */ - IOFormat(int _precision = StreamPrecision, int _flags = 0, - const std::string& _coeffSeparator = " ", - const std::string& _rowSeparator = "\n", const std::string& _rowPrefix="", const std::string& _rowSuffix="", - const std::string& _matPrefix="", const std::string& _matSuffix="") - : matPrefix(_matPrefix), matSuffix(_matSuffix), rowPrefix(_rowPrefix), rowSuffix(_rowSuffix), rowSeparator(_rowSeparator), - rowSpacer(""), coeffSeparator(_coeffSeparator), precision(_precision), flags(_flags) - { - int i = int(matSuffix.length())-1; - while (i>=0 && matSuffix[i]!='\n') - { + * \ingroup Core_Module + * + * \brief Stores a set of parameters controlling the way matrices are printed + * + * List of available parameters: + * - \b precision number of digits for floating point values, or one of the special constants \c StreamPrecision and \c + * FullPrecision. The default is the special value \c StreamPrecision which means to use the stream's own precision + * setting, as set for instance using \c cout.precision(3). The other special value \c FullPrecision means that the + * number of digits will be computed to match the full precision of each floating-point type. + * - \b flags an OR-ed combination of flags, the default value is 0, the only currently available flag is \c + * DontAlignCols which allows to disable the alignment of columns, resulting in faster code. + * - \b coeffSeparator string printed between two coefficients of the same row + * - \b rowSeparator string printed between two rows + * - \b rowPrefix string printed at the beginning of each row + * - \b rowSuffix string printed at the end of each row + * - \b matPrefix string printed at the beginning of the matrix + * - \b matSuffix string printed at the end of the matrix + * - \b fill character printed to fill the empty space in aligned columns + * + * Example: \include IOFormat.cpp + * Output: \verbinclude IOFormat.out + * + * \sa DenseBase::format(), class WithFormat + */ +struct IOFormat { + /** Default constructor, see class IOFormat for the meaning of the parameters */ + IOFormat(int _precision = StreamPrecision, int _flags = 0, const std::string& _coeffSeparator = " ", + const std::string& _rowSeparator = "\n", const std::string& _rowPrefix = "", + const std::string& _rowSuffix = "", const std::string& _matPrefix = "", const std::string& _matSuffix = "", + const char _fill = ' ') + : matPrefix(_matPrefix), + matSuffix(_matSuffix), + rowPrefix(_rowPrefix), + rowSuffix(_rowSuffix), + rowSeparator(_rowSeparator), + rowSpacer(""), + coeffSeparator(_coeffSeparator), + fill(_fill), + precision(_precision), + flags(_flags) { + // TODO check if rowPrefix, rowSuffix or rowSeparator contains a newline + // don't add rowSpacer if columns are not to be aligned + if ((flags & DontAlignCols)) return; + int i = int(matPrefix.length()) - 1; + while (i >= 0 && matPrefix[i] != '\n') { rowSpacer += ' '; i--; } @@ -67,184 +77,157 @@ struct IOFormat std::string matPrefix, matSuffix; std::string rowPrefix, rowSuffix, rowSeparator, rowSpacer; std::string coeffSeparator; + char fill; int precision; int flags; }; /** \class WithFormat - * \ingroup Core_Module - * - * \brief Pseudo expression providing matrix output with given format - * - * \param ExpressionType the type of the object on which IO stream operations are performed - * - * This class represents an expression with stream operators controlled by a given IOFormat. - * It is the return type of DenseBase::format() - * and most of the time this is the only way it is used. - * - * See class IOFormat for some examples. - * - * \sa DenseBase::format(), class IOFormat - */ -template -class WithFormat -{ - public: - - WithFormat(const ExpressionType& matrix, const IOFormat& format) - : m_matrix(matrix), m_format(format) - {} - - friend std::ostream & operator << (std::ostream & s, const WithFormat& wf) - { - return internal::print_matrix(s, wf.m_matrix.eval(), wf.m_format); - } + * \ingroup Core_Module + * + * \brief Pseudo expression providing matrix output with given format + * + * \tparam ExpressionType the type of the object on which IO stream operations are performed + * + * This class represents an expression with stream operators controlled by a given IOFormat. + * It is the return type of DenseBase::format() + * and most of the time this is the only way it is used. + * + * See class IOFormat for some examples. + * + * \sa DenseBase::format(), class IOFormat + */ +template +class WithFormat { + public: + WithFormat(const ExpressionType& matrix, const IOFormat& format) : m_matrix(matrix), m_format(format) {} + + friend std::ostream& operator<<(std::ostream& s, const WithFormat& wf) { + return internal::print_matrix(s, wf.m_matrix.eval(), wf.m_format); + } - protected: - const typename ExpressionType::Nested m_matrix; - IOFormat m_format; + protected: + typename ExpressionType::Nested m_matrix; + IOFormat m_format; }; -/** \returns a WithFormat proxy object allowing to print a matrix the with given - * format \a fmt. - * - * See class IOFormat for some examples. - * - * \sa class IOFormat, class WithFormat - */ -template -inline const WithFormat -DenseBase::format(const IOFormat& fmt) const -{ - return WithFormat(derived(), fmt); -} - namespace internal { -template -struct significant_decimals_default_impl -{ - typedef typename NumTraits::Real RealScalar; - static inline int run() - { - using std::ceil; - using std::log; - return cast(ceil(-log(NumTraits::epsilon())/log(RealScalar(10)))); - } +// NOTE: This helper is kept for backward compatibility with previous code specializing +// this internal::significant_decimals_impl structure. In the future we should directly +// call max_digits10(). +template +struct significant_decimals_impl { + static inline int run() { return NumTraits::max_digits10(); } }; -template -struct significant_decimals_default_impl -{ - static inline int run() - { - return 0; - } -}; - -template -struct significant_decimals_impl - : significant_decimals_default_impl::IsInteger> -{}; - /** \internal - * print the matrix \a _m to the output stream \a s using the output format \a fmt */ -template -std::ostream & print_matrix(std::ostream & s, const Derived& _m, const IOFormat& fmt) -{ - if(_m.size() == 0) - { + * print the matrix \a _m to the output stream \a s using the output format \a fmt */ +template +std::ostream& print_matrix(std::ostream& s, const Derived& _m, const IOFormat& fmt) { + using internal::is_same; + + if (_m.size() == 0) { s << fmt.matPrefix << fmt.matSuffix; return s; } - + typename Derived::Nested m = _m; typedef typename Derived::Scalar Scalar; - typedef typename Derived::Index Index; + typedef std::conditional_t::value || is_same::value || + is_same::value || is_same::value, + int, + std::conditional_t >::value || + is_same >::value || + is_same >::value || + is_same >::value, + std::complex, const Scalar&> > + PrintType; Index width = 0; std::streamsize explicit_precision; - if(fmt.precision == StreamPrecision) - { + if (fmt.precision == StreamPrecision) { explicit_precision = 0; - } - else if(fmt.precision == FullPrecision) - { - if (NumTraits::IsInteger) - { + } else if (fmt.precision == FullPrecision) { + if (NumTraits::IsInteger) { explicit_precision = 0; - } - else - { + } else { explicit_precision = significant_decimals_impl::run(); } - } - else - { + } else { explicit_precision = fmt.precision; } std::streamsize old_precision = 0; - if(explicit_precision) old_precision = s.precision(explicit_precision); + if (explicit_precision) old_precision = s.precision(explicit_precision); bool align_cols = !(fmt.flags & DontAlignCols); - if(align_cols) - { + if (align_cols) { // compute the largest width - for(Index j = 0; j < m.cols(); ++j) - for(Index i = 0; i < m.rows(); ++i) - { + for (Index j = 0; j < m.cols(); ++j) + for (Index i = 0; i < m.rows(); ++i) { std::stringstream sstr; sstr.copyfmt(s); - sstr << m.coeff(i,j); + sstr << static_cast(m.coeff(i, j)); width = std::max(width, Index(sstr.str().length())); } } + std::streamsize old_width = s.width(); + char old_fill_character = s.fill(); s << fmt.matPrefix; - for(Index i = 0; i < m.rows(); ++i) - { - if (i) - s << fmt.rowSpacer; + for (Index i = 0; i < m.rows(); ++i) { + if (i) s << fmt.rowSpacer; s << fmt.rowPrefix; - if(width) s.width(width); - s << m.coeff(i, 0); - for(Index j = 1; j < m.cols(); ++j) - { + if (width) { + s.fill(fmt.fill); + s.width(width); + } + s << static_cast(m.coeff(i, 0)); + for (Index j = 1; j < m.cols(); ++j) { s << fmt.coeffSeparator; - if (width) s.width(width); - s << m.coeff(i, j); + if (width) { + s.fill(fmt.fill); + s.width(width); + } + s << static_cast(m.coeff(i, j)); } s << fmt.rowSuffix; - if( i < m.rows() - 1) - s << fmt.rowSeparator; + if (i < m.rows() - 1) s << fmt.rowSeparator; } s << fmt.matSuffix; - if(explicit_precision) s.precision(old_precision); + if (explicit_precision) s.precision(old_precision); + if (width) { + s.fill(old_fill_character); + s.width(old_width); + } return s; } -} // end namespace internal +} // end namespace internal /** \relates DenseBase - * - * Outputs the matrix, to the given stream. - * - * If you wish to print the matrix with a format different than the default, use DenseBase::format(). - * - * It is also possible to change the default format by defining EIGEN_DEFAULT_IO_FORMAT before including Eigen headers. - * If not defined, this will automatically be defined to Eigen::IOFormat(), that is the Eigen::IOFormat with default parameters. - * - * \sa DenseBase::format() - */ -template -std::ostream & operator << -(std::ostream & s, - const DenseBase & m) -{ + * + * Outputs the matrix, to the given stream. + * + * If you wish to print the matrix with a format different than the default, use DenseBase::format(). + * + * It is also possible to change the default format by defining EIGEN_DEFAULT_IO_FORMAT before including Eigen headers. + * If not defined, this will automatically be defined to Eigen::IOFormat(), that is the Eigen::IOFormat with default + * parameters. + * + * \sa DenseBase::format() + */ +template +std::ostream& operator<<(std::ostream& s, const DenseBase& m) { return internal::print_matrix(s, m.eval(), EIGEN_DEFAULT_IO_FORMAT); } -} // end namespace Eigen +template +std::ostream& operator<<(std::ostream& s, const DiagonalBase& m) { + return internal::print_matrix(s, m.derived(), EIGEN_DEFAULT_IO_FORMAT); +} + +} // end namespace Eigen -#endif // EIGEN_IO_H +#endif // EIGEN_IO_H diff --git a/inst/include/Eigen/src/Core/IndexedView.h b/inst/include/Eigen/src/Core/IndexedView.h new file mode 100644 index 00000000..10562c19 --- /dev/null +++ b/inst/include/Eigen/src/Core/IndexedView.h @@ -0,0 +1,321 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2017 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_INDEXED_VIEW_H +#define EIGEN_INDEXED_VIEW_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +template +struct traits> : traits { + enum { + RowsAtCompileTime = int(IndexedViewHelper::SizeAtCompileTime), + ColsAtCompileTime = int(IndexedViewHelper::SizeAtCompileTime), + MaxRowsAtCompileTime = RowsAtCompileTime, + MaxColsAtCompileTime = ColsAtCompileTime, + + XprTypeIsRowMajor = (int(traits::Flags) & RowMajorBit) != 0, + IsRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1 + : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0 + : XprTypeIsRowMajor, + + RowIncr = int(IndexedViewHelper::IncrAtCompileTime), + ColIncr = int(IndexedViewHelper::IncrAtCompileTime), + InnerIncr = IsRowMajor ? ColIncr : RowIncr, + OuterIncr = IsRowMajor ? RowIncr : ColIncr, + + HasSameStorageOrderAsXprType = (IsRowMajor == XprTypeIsRowMajor), + XprInnerStride = HasSameStorageOrderAsXprType ? int(inner_stride_at_compile_time::ret) + : int(outer_stride_at_compile_time::ret), + XprOuterstride = HasSameStorageOrderAsXprType ? int(outer_stride_at_compile_time::ret) + : int(inner_stride_at_compile_time::ret), + + InnerSize = XprTypeIsRowMajor ? ColsAtCompileTime : RowsAtCompileTime, + IsBlockAlike = InnerIncr == 1 && OuterIncr == 1, + IsInnerPannel = HasSameStorageOrderAsXprType && + is_same, std::conditional_t>::value, + + InnerStrideAtCompileTime = + InnerIncr < 0 || InnerIncr == DynamicIndex || XprInnerStride == Dynamic || InnerIncr == Undefined + ? Dynamic + : XprInnerStride * InnerIncr, + OuterStrideAtCompileTime = + OuterIncr < 0 || OuterIncr == DynamicIndex || XprOuterstride == Dynamic || OuterIncr == Undefined + ? Dynamic + : XprOuterstride * OuterIncr, + + ReturnAsScalar = is_single_range::value && is_single_range::value, + ReturnAsBlock = (!ReturnAsScalar) && IsBlockAlike, + ReturnAsIndexedView = (!ReturnAsScalar) && (!ReturnAsBlock), + + // FIXME we deal with compile-time strides if and only if we have DirectAccessBit flag, + // but this is too strict regarding negative strides... + DirectAccessMask = (int(InnerIncr) != Undefined && int(OuterIncr) != Undefined && InnerIncr >= 0 && OuterIncr >= 0) + ? DirectAccessBit + : 0, + FlagsRowMajorBit = IsRowMajor ? RowMajorBit : 0, + FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, + FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0, + Flags = (traits::Flags & (HereditaryBits | DirectAccessMask)) | FlagsLvalueBit | FlagsRowMajorBit | + FlagsLinearAccessBit + }; + + typedef Block BlockType; +}; + +template +class IndexedViewImpl; + +} // namespace internal + +/** \class IndexedView + * \ingroup Core_Module + * + * \brief Expression of a non-sequential sub-matrix defined by arbitrary sequences of row and column indices + * + * \tparam XprType the type of the expression in which we are taking the intersections of sub-rows and sub-columns + * \tparam RowIndices the type of the object defining the sequence of row indices + * \tparam ColIndices the type of the object defining the sequence of column indices + * + * This class represents an expression of a sub-matrix (or sub-vector) defined as the intersection + * of sub-sets of rows and columns, that are themself defined by generic sequences of row indices \f$ + * \{r_0,r_1,..r_{m-1}\} \f$ and column indices \f$ \{c_0,c_1,..c_{n-1} \}\f$. Let \f$ A \f$ be the nested matrix, then + * the resulting matrix \f$ B \f$ has \c m rows and \c n columns, and its entries are given by: \f$ B(i,j) = A(r_i,c_j) + * \f$. + * + * The \c RowIndices and \c ColIndices types must be compatible with the following API: + * \code + * operator[](Index) const; + * Index size() const; + * \endcode + * + * Typical supported types thus include: + * - std::vector + * - std::valarray + * - std::array + * - Eigen::ArrayXi + * - decltype(ArrayXi::LinSpaced(...)) + * - Any view/expressions of the previous types + * - Eigen::ArithmeticSequence + * - Eigen::internal::AllRange (helper for Eigen::placeholders::all) + * - Eigen::internal::SingleRange (helper for single index) + * - etc. + * + * In typical usages of %Eigen, this class should never be used directly. It is the return type of + * DenseBase::operator()(const RowIndices&, const ColIndices&). + * + * \sa class Block + */ +template +class IndexedView + : public internal::IndexedViewImpl::StorageKind, + (internal::traits>::Flags & + DirectAccessBit) != 0> { + public: + typedef typename internal::IndexedViewImpl< + XprType, RowIndices, ColIndices, typename internal::traits::StorageKind, + (internal::traits>::Flags & DirectAccessBit) != 0> + Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(IndexedView) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(IndexedView) + + template + IndexedView(XprType& xpr, const T0& rowIndices, const T1& colIndices) : Base(xpr, rowIndices, colIndices) {} +}; + +namespace internal { + +// Generic API dispatcher +template +class IndexedViewImpl : public internal::generic_xpr_base>::type { + public: + typedef typename internal::generic_xpr_base>::type Base; + typedef typename internal::ref_selector::non_const_type MatrixTypeNested; + typedef internal::remove_all_t NestedExpression; + typedef typename XprType::Scalar Scalar; + + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(IndexedViewImpl) + + template + IndexedViewImpl(XprType& xpr, const T0& rowIndices, const T1& colIndices) + : m_xpr(xpr), m_rowIndices(rowIndices), m_colIndices(colIndices) {} + + /** \returns number of rows */ + Index rows() const { return IndexedViewHelper::size(m_rowIndices); } + + /** \returns number of columns */ + Index cols() const { return IndexedViewHelper::size(m_colIndices); } + + /** \returns the nested expression */ + const internal::remove_all_t& nestedExpression() const { return m_xpr; } + + /** \returns the nested expression */ + std::remove_reference_t& nestedExpression() { return m_xpr; } + + /** \returns a const reference to the object storing/generating the row indices */ + const RowIndices& rowIndices() const { return m_rowIndices; } + + /** \returns a const reference to the object storing/generating the column indices */ + const ColIndices& colIndices() const { return m_colIndices; } + + constexpr Scalar& coeffRef(Index rowId, Index colId) { + return nestedExpression().coeffRef(m_rowIndices[rowId], m_colIndices[colId]); + } + + constexpr const Scalar& coeffRef(Index rowId, Index colId) const { + return nestedExpression().coeffRef(m_rowIndices[rowId], m_colIndices[colId]); + } + + protected: + MatrixTypeNested m_xpr; + RowIndices m_rowIndices; + ColIndices m_colIndices; +}; + +template +class IndexedViewImpl + : public IndexedViewImpl { + public: + using Base = internal::IndexedViewImpl::StorageKind, false>; + using Derived = IndexedView; + + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(IndexedViewImpl) + + template + IndexedViewImpl(XprType& xpr, const T0& rowIndices, const T1& colIndices) : Base(xpr, rowIndices, colIndices) {} + + Index rowIncrement() const { + if (traits::RowIncr != DynamicIndex && traits::RowIncr != Undefined) { + return traits::RowIncr; + } + return IndexedViewHelper::incr(this->rowIndices()); + } + Index colIncrement() const { + if (traits::ColIncr != DynamicIndex && traits::ColIncr != Undefined) { + return traits::ColIncr; + } + return IndexedViewHelper::incr(this->colIndices()); + } + + Index innerIncrement() const { return traits::IsRowMajor ? colIncrement() : rowIncrement(); } + + Index outerIncrement() const { return traits::IsRowMajor ? rowIncrement() : colIncrement(); } + + std::decay_t* data() { + Index row_offset = this->rowIndices()[0] * this->nestedExpression().rowStride(); + Index col_offset = this->colIndices()[0] * this->nestedExpression().colStride(); + return this->nestedExpression().data() + row_offset + col_offset; + } + + const std::decay_t* data() const { + Index row_offset = this->rowIndices()[0] * this->nestedExpression().rowStride(); + Index col_offset = this->colIndices()[0] * this->nestedExpression().colStride(); + return this->nestedExpression().data() + row_offset + col_offset; + } + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { + if (traits::InnerStrideAtCompileTime != Dynamic) { + return traits::InnerStrideAtCompileTime; + } + return innerIncrement() * this->nestedExpression().innerStride(); + } + + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { + if (traits::OuterStrideAtCompileTime != Dynamic) { + return traits::OuterStrideAtCompileTime; + } + return outerIncrement() * this->nestedExpression().outerStride(); + } +}; + +template +struct unary_evaluator, IndexBased> + : evaluator_base> { + typedef IndexedView XprType; + + enum { + CoeffReadCost = evaluator::CoeffReadCost /* TODO + cost of row/col index */, + + FlagsLinearAccessBit = + (traits::RowsAtCompileTime == 1 || traits::ColsAtCompileTime == 1) ? LinearAccessBit : 0, + + FlagsRowMajorBit = traits::FlagsRowMajorBit, + + Flags = (evaluator::Flags & (HereditaryBits & ~RowMajorBit /*| LinearAccessBit | DirectAccessBit*/)) | + FlagsLinearAccessBit | FlagsRowMajorBit, + + Alignment = 0 + }; + + EIGEN_DEVICE_FUNC explicit unary_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_xpr(xpr) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeff(Index row, Index col) const { + eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows() && + m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols()); + return m_argImpl.coeff(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows() && + m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols()); + return m_argImpl.coeffRef(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + EIGEN_STATIC_ASSERT_LVALUE(XprType) + Index row = XprType::RowsAtCompileTime == 1 ? 0 : index; + Index col = XprType::RowsAtCompileTime == 1 ? index : 0; + eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows() && + m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols()); + return m_argImpl.coeffRef(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const { + Index row = XprType::RowsAtCompileTime == 1 ? 0 : index; + Index col = XprType::RowsAtCompileTime == 1 ? index : 0; + eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows() && + m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols()); + return m_argImpl.coeffRef(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index index) const { + Index row = XprType::RowsAtCompileTime == 1 ? 0 : index; + Index col = XprType::RowsAtCompileTime == 1 ? index : 0; + eigen_assert(m_xpr.rowIndices()[row] >= 0 && m_xpr.rowIndices()[row] < m_xpr.nestedExpression().rows() && + m_xpr.colIndices()[col] >= 0 && m_xpr.colIndices()[col] < m_xpr.nestedExpression().cols()); + return m_argImpl.coeff(m_xpr.rowIndices()[row], m_xpr.colIndices()[col]); + } + + protected: + evaluator m_argImpl; + const XprType& m_xpr; +}; + +// Catch assignments to an IndexedView. +template +struct evaluator_assume_aliasing> { + static const bool value = true; +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_INDEXED_VIEW_H diff --git a/inst/include/Eigen/src/Core/InnerProduct.h b/inst/include/Eigen/src/Core/InnerProduct.h new file mode 100644 index 00000000..686ad137 --- /dev/null +++ b/inst/include/Eigen/src/Core/InnerProduct.h @@ -0,0 +1,260 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2024 Charlie Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_INNER_PRODUCT_EVAL_H +#define EIGEN_INNER_PRODUCT_EVAL_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +// recursively searches for the largest simd type that does not exceed Size, or the smallest if no such type exists +template ::type, + bool Stop = + (unpacket_traits::size <= Size) || is_same::half>::value> +struct find_inner_product_packet_helper; + +template +struct find_inner_product_packet_helper { + using type = typename find_inner_product_packet_helper::half>::type; +}; + +template +struct find_inner_product_packet_helper { + using type = Packet; +}; + +template +struct find_inner_product_packet : find_inner_product_packet_helper {}; + +template +struct find_inner_product_packet { + using type = typename packet_traits::type; +}; + +template +struct inner_product_assert { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Lhs) + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Rhs) + EIGEN_STATIC_ASSERT_SAME_VECTOR_SIZE(Lhs, Rhs) +#ifndef EIGEN_NO_DEBUG + static EIGEN_DEVICE_FUNC void run(const Lhs& lhs, const Rhs& rhs) { + eigen_assert((lhs.size() == rhs.size()) && "Inner product: lhs and rhs vectors must have same size"); + } +#else + static EIGEN_DEVICE_FUNC void run(const Lhs&, const Rhs&) {} +#endif +}; + +template +struct inner_product_evaluator { + static constexpr int LhsFlags = evaluator::Flags; + static constexpr int RhsFlags = evaluator::Flags; + static constexpr int SizeAtCompileTime = size_prefer_fixed(Lhs::SizeAtCompileTime, Rhs::SizeAtCompileTime); + static constexpr int MaxSizeAtCompileTime = + min_size_prefer_fixed(Lhs::MaxSizeAtCompileTime, Rhs::MaxSizeAtCompileTime); + static constexpr int LhsAlignment = evaluator::Alignment; + static constexpr int RhsAlignment = evaluator::Alignment; + + using Scalar = typename Func::result_type; + using Packet = typename find_inner_product_packet::type; + + static constexpr bool Vectorize = + bool(LhsFlags & RhsFlags & PacketAccessBit) && Func::PacketAccess && + ((MaxSizeAtCompileTime == Dynamic) || (unpacket_traits::size <= MaxSizeAtCompileTime)); + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit inner_product_evaluator(const Lhs& lhs, const Rhs& rhs, + Func func = Func()) + : m_func(func), m_lhs(lhs), m_rhs(rhs), m_size(lhs.size()) { + inner_product_assert::run(lhs, rhs); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Index size() const { return m_size.value(); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index index) const { + return m_func.coeff(m_lhs.coeff(index), m_rhs.coeff(index)); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(const Scalar& value, Index index) const { + return m_func.coeff(value, m_lhs.coeff(index), m_rhs.coeff(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + return m_func.packet(m_lhs.template packet(index), + m_rhs.template packet(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(const PacketType& value, Index index) const { + return m_func.packet(value, m_lhs.template packet(index), + m_rhs.template packet(index)); + } + + const Func m_func; + const evaluator m_lhs; + const evaluator m_rhs; + const variable_if_dynamic m_size; +}; + +template +struct inner_product_impl; + +// scalar loop +template +struct inner_product_impl { + using Scalar = typename Evaluator::Scalar; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval) { + const Index size = eval.size(); + if (size == 0) return Scalar(0); + + Scalar result = eval.coeff(0); + for (Index k = 1; k < size; k++) { + result = eval.coeff(result, k); + } + + return result; + } +}; + +// vector loop +template +struct inner_product_impl { + using UnsignedIndex = std::make_unsigned_t; + using Scalar = typename Evaluator::Scalar; + using Packet = typename Evaluator::Packet; + static constexpr int PacketSize = unpacket_traits::size; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval) { + const UnsignedIndex size = static_cast(eval.size()); + if (size < PacketSize) return inner_product_impl::run(eval); + + const UnsignedIndex packetEnd = numext::round_down(size, PacketSize); + const UnsignedIndex quadEnd = numext::round_down(size, 4 * PacketSize); + const UnsignedIndex numPackets = size / PacketSize; + const UnsignedIndex numRemPackets = (packetEnd - quadEnd) / PacketSize; + + Packet presult0, presult1, presult2, presult3; + + presult0 = eval.template packet(0 * PacketSize); + if (numPackets >= 2) presult1 = eval.template packet(1 * PacketSize); + if (numPackets >= 3) presult2 = eval.template packet(2 * PacketSize); + if (numPackets >= 4) { + presult3 = eval.template packet(3 * PacketSize); + + for (UnsignedIndex k = 4 * PacketSize; k < quadEnd; k += 4 * PacketSize) { + presult0 = eval.packet(presult0, k + 0 * PacketSize); + presult1 = eval.packet(presult1, k + 1 * PacketSize); + presult2 = eval.packet(presult2, k + 2 * PacketSize); + presult3 = eval.packet(presult3, k + 3 * PacketSize); + } + + if (numRemPackets >= 1) presult0 = eval.packet(presult0, quadEnd + 0 * PacketSize); + if (numRemPackets >= 2) presult1 = eval.packet(presult1, quadEnd + 1 * PacketSize); + if (numRemPackets == 3) presult2 = eval.packet(presult2, quadEnd + 2 * PacketSize); + + presult2 = padd(presult2, presult3); + } + + if (numPackets >= 3) presult1 = padd(presult1, presult2); + if (numPackets >= 2) presult0 = padd(presult0, presult1); + + Scalar result = predux(presult0); + for (UnsignedIndex k = packetEnd; k < size; k++) { + result = eval.coeff(result, k); + } + + return result; + } +}; + +template +struct conditional_conj; + +template +struct conditional_conj { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(const Scalar& a) { return numext::conj(a); } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(const Packet& a) { + return pconj(a); + } +}; + +template +struct conditional_conj { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(const Scalar& a) { return a; } + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(const Packet& a) { + return a; + } +}; + +template +struct scalar_inner_product_op { + using result_type = typename ScalarBinaryOpTraits::ReturnType; + using conj_helper = conditional_conj; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type coeff(const LhsScalar& a, const RhsScalar& b) const { + return (conj_helper::coeff(a) * b); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type coeff(const result_type& accum, const LhsScalar& a, + const RhsScalar& b) const { + return (conj_helper::coeff(a) * b) + accum; + } + static constexpr bool PacketAccess = false; +}; + +// Partial specialization for packet access if and only if +// LhsScalar == RhsScalar == ScalarBinaryOpTraits::ReturnType. +template +struct scalar_inner_product_op< + Scalar, + typename std::enable_if::ReturnType, Scalar>::value, + Scalar>::type, + Conj> { + using result_type = Scalar; + using conj_helper = conditional_conj; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(const Scalar& a, const Scalar& b) const { + return pmul(conj_helper::coeff(a), b); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(const Scalar& accum, const Scalar& a, const Scalar& b) const { + return pmadd(conj_helper::coeff(a), b, accum); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(const Packet& a, const Packet& b) const { + return pmul(conj_helper::packet(a), b); + } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Packet packet(const Packet& accum, const Packet& a, const Packet& b) const { + return pmadd(conj_helper::packet(a), b, accum); + } + static constexpr bool PacketAccess = packet_traits::HasMul && packet_traits::HasAdd; +}; + +template +struct default_inner_product_impl { + using LhsScalar = typename traits::Scalar; + using RhsScalar = typename traits::Scalar; + using Op = scalar_inner_product_op; + using Evaluator = inner_product_evaluator; + using result_type = typename Evaluator::Scalar; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE result_type run(const MatrixBase& a, const MatrixBase& b) { + Evaluator eval(a.derived(), b.derived(), Op()); + return inner_product_impl::run(eval); + } +}; + +template +struct dot_impl : default_inner_product_impl {}; + +} // namespace internal +} // namespace Eigen + +#endif // EIGEN_INNER_PRODUCT_EVAL_H diff --git a/inst/include/Eigen/src/Core/InternalHeaderCheck.h b/inst/include/Eigen/src/Core/InternalHeaderCheck.h new file mode 100644 index 00000000..1cea572d --- /dev/null +++ b/inst/include/Eigen/src/Core/InternalHeaderCheck.h @@ -0,0 +1,3 @@ +#ifndef EIGEN_CORE_MODULE_H +#error "Please include Eigen/Core instead of including headers inside the src directory directly." +#endif diff --git a/inst/include/Eigen/src/Core/Inverse.h b/inst/include/Eigen/src/Core/Inverse.h new file mode 100644 index 00000000..79fc3ab6 --- /dev/null +++ b/inst/include/Eigen/src/Core/Inverse.h @@ -0,0 +1,108 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2014-2019 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_INVERSE_H +#define EIGEN_INVERSE_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +template +class InverseImpl; + +namespace internal { + +template +struct traits > : traits { + typedef typename XprType::PlainObject PlainObject; + typedef traits BaseTraits; + enum { Flags = BaseTraits::Flags & RowMajorBit }; +}; + +} // end namespace internal + +/** \class Inverse + * + * \brief Expression of the inverse of another expression + * + * \tparam XprType the type of the expression we are taking the inverse + * + * This class represents an abstract expression of A.inverse() + * and most of the time this is the only way it is used. + * + */ +template +class Inverse : public InverseImpl::StorageKind> { + public: + typedef typename XprType::StorageIndex StorageIndex; + typedef typename XprType::Scalar Scalar; + typedef typename internal::ref_selector::type XprTypeNested; + typedef internal::remove_all_t XprTypeNestedCleaned; + typedef typename internal::ref_selector::type Nested; + typedef internal::remove_all_t NestedExpression; + + explicit EIGEN_DEVICE_FUNC Inverse(const XprType& xpr) : m_xpr(xpr) {} + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_xpr.cols(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_xpr.rows(); } + + EIGEN_DEVICE_FUNC const XprTypeNestedCleaned& nestedExpression() const { return m_xpr; } + + protected: + XprTypeNested m_xpr; +}; + +// Generic API dispatcher +template +class InverseImpl : public internal::generic_xpr_base >::type { + public: + typedef typename internal::generic_xpr_base >::type Base; + typedef typename XprType::Scalar Scalar; + + private: + Scalar coeff(Index row, Index col) const; + Scalar coeff(Index i) const; +}; + +namespace internal { + +/** \internal + * \brief Default evaluator for Inverse expression. + * + * This default evaluator for Inverse expression simply evaluate the inverse into a temporary + * by a call to internal::call_assignment_no_alias. + * Therefore, inverse implementers only have to specialize Assignment, ...> for + * there own nested expression. + * + * \sa class Inverse + */ +template +struct unary_evaluator > : public evaluator::PlainObject> { + typedef Inverse InverseType; + typedef typename InverseType::PlainObject PlainObject; + typedef evaluator Base; + + enum { Flags = Base::Flags | EvalBeforeNestingBit }; + + EIGEN_DEVICE_FUNC unary_evaluator(const InverseType& inv_xpr) : m_result(inv_xpr.rows(), inv_xpr.cols()) { + internal::construct_at(this, m_result); + internal::call_assignment_no_alias(m_result, inv_xpr); + } + + protected: + PlainObject m_result; +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_INVERSE_H diff --git a/inst/include/Eigen/src/Core/Map.h b/inst/include/Eigen/src/Core/Map.h index f804c89d..c740da72 100644 --- a/inst/include/Eigen/src/Core/Map.h +++ b/inst/include/Eigen/src/Core/Map.h @@ -11,182 +11,143 @@ #ifndef EIGEN_MAP_H #define EIGEN_MAP_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class Map - * \ingroup Core_Module - * - * \brief A matrix or vector expression mapping an existing array of data. - * - * \tparam PlainObjectType the equivalent matrix type of the mapped data - * \tparam MapOptions specifies whether the pointer is \c #Aligned, or \c #Unaligned. - * The default is \c #Unaligned. - * \tparam StrideType optionally specifies strides. By default, Map assumes the memory layout - * of an ordinary, contiguous array. This can be overridden by specifying strides. - * The type passed here must be a specialization of the Stride template, see examples below. - * - * This class represents a matrix or vector expression mapping an existing array of data. - * It can be used to let Eigen interface without any overhead with non-Eigen data structures, - * such as plain C arrays or structures from other libraries. By default, it assumes that the - * data is laid out contiguously in memory. You can however override this by explicitly specifying - * inner and outer strides. - * - * Here's an example of simply mapping a contiguous array as a \ref TopicStorageOrders "column-major" matrix: - * \include Map_simple.cpp - * Output: \verbinclude Map_simple.out - * - * If you need to map non-contiguous arrays, you can do so by specifying strides: - * - * Here's an example of mapping an array as a vector, specifying an inner stride, that is, the pointer - * increment between two consecutive coefficients. Here, we're specifying the inner stride as a compile-time - * fixed value. - * \include Map_inner_stride.cpp - * Output: \verbinclude Map_inner_stride.out - * - * Here's an example of mapping an array while specifying an outer stride. Here, since we're mapping - * as a column-major matrix, 'outer stride' means the pointer increment between two consecutive columns. - * Here, we're specifying the outer stride as a runtime parameter. Note that here \c OuterStride<> is - * a short version of \c OuterStride because the default template parameter of OuterStride - * is \c Dynamic - * \include Map_outer_stride.cpp - * Output: \verbinclude Map_outer_stride.out - * - * For more details and for an example of specifying both an inner and an outer stride, see class Stride. - * - * \b Tip: to change the array of data mapped by a Map object, you can use the C++ - * placement new syntax: - * - * Example: \include Map_placement_new.cpp - * Output: \verbinclude Map_placement_new.out - * - * This class is the return type of PlainObjectBase::Map() but can also be used directly. - * - * \sa PlainObjectBase::Map(), \ref TopicStorageOrders - */ +namespace Eigen { namespace internal { -template -struct traits > - : public traits -{ +template +struct traits > : public traits { typedef traits TraitsBase; - typedef typename PlainObjectType::Index Index; - typedef typename PlainObjectType::Scalar Scalar; enum { + PlainObjectTypeInnerSize = ((traits::Flags & RowMajorBit) == RowMajorBit) + ? PlainObjectType::ColsAtCompileTime + : PlainObjectType::RowsAtCompileTime, + InnerStrideAtCompileTime = StrideType::InnerStrideAtCompileTime == 0 - ? int(PlainObjectType::InnerStrideAtCompileTime) - : int(StrideType::InnerStrideAtCompileTime), + ? int(PlainObjectType::InnerStrideAtCompileTime) + : int(StrideType::InnerStrideAtCompileTime), OuterStrideAtCompileTime = StrideType::OuterStrideAtCompileTime == 0 - ? int(PlainObjectType::OuterStrideAtCompileTime) - : int(StrideType::OuterStrideAtCompileTime), - HasNoInnerStride = InnerStrideAtCompileTime == 1, - HasNoOuterStride = StrideType::OuterStrideAtCompileTime == 0, - HasNoStride = HasNoInnerStride && HasNoOuterStride, - IsAligned = bool(EIGEN_ALIGN) && ((int(MapOptions)&Aligned)==Aligned), - IsDynamicSize = PlainObjectType::SizeAtCompileTime==Dynamic, - KeepsPacketAccess = bool(HasNoInnerStride) - && ( bool(IsDynamicSize) - || HasNoOuterStride - || ( OuterStrideAtCompileTime!=Dynamic - && ((static_cast(sizeof(Scalar))*OuterStrideAtCompileTime)%16)==0 ) ), + ? (InnerStrideAtCompileTime == Dynamic || PlainObjectTypeInnerSize == Dynamic + ? Dynamic + : int(InnerStrideAtCompileTime) * int(PlainObjectTypeInnerSize)) + : int(StrideType::OuterStrideAtCompileTime), + Alignment = int(MapOptions) & int(AlignedMask), Flags0 = TraitsBase::Flags & (~NestByRefBit), - Flags1 = IsAligned ? (int(Flags0) | AlignedBit) : (int(Flags0) & ~AlignedBit), - Flags2 = (bool(HasNoStride) || bool(PlainObjectType::IsVectorAtCompileTime)) - ? int(Flags1) : int(Flags1 & ~LinearAccessBit), - Flags3 = is_lvalue::value ? int(Flags2) : (int(Flags2) & ~LvalueBit), - Flags = KeepsPacketAccess ? int(Flags3) : (int(Flags3) & ~PacketAccessBit) + Flags = is_lvalue::value ? int(Flags0) : (int(Flags0) & ~LvalueBit) }; -private: - enum { Options }; // Expressions don't have Options -}; -} - -template class Map - : public MapBase > -{ - public: - - typedef MapBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Map) - - typedef typename Base::PointerType PointerType; -#if EIGEN2_SUPPORT_STAGE <= STAGE30_FULL_EIGEN3_API - typedef const Scalar* PointerArgType; - inline PointerType cast_to_pointer_type(PointerArgType ptr) { return const_cast(ptr); } -#else - typedef PointerType PointerArgType; - inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; } -#endif - - inline Index innerStride() const - { - return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1; - } - - inline Index outerStride() const - { - return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer() - : IsVectorAtCompileTime ? this->size() - : int(Flags)&RowMajorBit ? this->cols() - : this->rows(); - } - - /** Constructor in the fixed-size case. - * - * \param dataPtr pointer to the array to map - * \param a_stride optional Stride object, passing the strides. - */ - inline Map(PointerArgType dataPtr, const StrideType& a_stride = StrideType()) - : Base(cast_to_pointer_type(dataPtr)), m_stride(a_stride) - { - PlainObjectType::Base::_check_template_params(); - } - - /** Constructor in the dynamic-size vector case. - * - * \param dataPtr pointer to the array to map - * \param a_size the size of the vector expression - * \param a_stride optional Stride object, passing the strides. - */ - inline Map(PointerArgType dataPtr, Index a_size, const StrideType& a_stride = StrideType()) - : Base(cast_to_pointer_type(dataPtr), a_size), m_stride(a_stride) - { - PlainObjectType::Base::_check_template_params(); - } - - /** Constructor in the dynamic-size matrix case. - * - * \param dataPtr pointer to the array to map - * \param nbRows the number of rows of the matrix expression - * \param nbCols the number of columns of the matrix expression - * \param a_stride optional Stride object, passing the strides. - */ - inline Map(PointerArgType dataPtr, Index nbRows, Index nbCols, const StrideType& a_stride = StrideType()) - : Base(cast_to_pointer_type(dataPtr), nbRows, nbCols), m_stride(a_stride) - { - PlainObjectType::Base::_check_template_params(); - } - - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map) - - protected: - StrideType m_stride; -}; -template -inline Array<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> - ::Array(const Scalar *data) -{ - this->_set_noalias(Eigen::Map(data)); -} + private: + enum { Options }; // Expressions don't have Options +}; +} // namespace internal -template -inline Matrix<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols> - ::Matrix(const Scalar *data) -{ - this->_set_noalias(Eigen::Map(data)); -} +/** \class Map + * \ingroup Core_Module + * + * \brief A matrix or vector expression mapping an existing array of data. + * + * \tparam PlainObjectType the equivalent matrix type of the mapped data + * \tparam MapOptions specifies the pointer alignment in bytes. It can be: \c #Aligned128, \c #Aligned64, \c #Aligned32, + * \c #Aligned16, \c #Aligned8 or \c #Unaligned. The default is \c #Unaligned. \tparam StrideType optionally specifies + * strides. By default, Map assumes the memory layout of an ordinary, contiguous array. This can be overridden by + * specifying strides. The type passed here must be a specialization of the Stride template, see examples below. + * + * This class represents a matrix or vector expression mapping an existing array of data. + * It can be used to let Eigen interface without any overhead with non-Eigen data structures, + * such as plain C arrays or structures from other libraries. By default, it assumes that the + * data is laid out contiguously in memory. You can however override this by explicitly specifying + * inner and outer strides. + * + * Here's an example of simply mapping a contiguous array as a \ref TopicStorageOrders "column-major" matrix: + * \include Map_simple.cpp + * Output: \verbinclude Map_simple.out + * + * If you need to map non-contiguous arrays, you can do so by specifying strides: + * + * Here's an example of mapping an array as a vector, specifying an inner stride, that is, the pointer + * increment between two consecutive coefficients. Here, we're specifying the inner stride as a compile-time + * fixed value. + * \include Map_inner_stride.cpp + * Output: \verbinclude Map_inner_stride.out + * + * Here's an example of mapping an array while specifying an outer stride. Here, since we're mapping + * as a column-major matrix, 'outer stride' means the pointer increment between two consecutive columns. + * Here, we're specifying the outer stride as a runtime parameter. Note that here \c OuterStride<> is + * a short version of \c OuterStride because the default template parameter of OuterStride + * is \c Dynamic + * \include Map_outer_stride.cpp + * Output: \verbinclude Map_outer_stride.out + * + * For more details and for an example of specifying both an inner and an outer stride, see class Stride. + * + * \b Tip: to change the array of data mapped by a Map object, you can use the C++ + * placement new syntax: + * + * Example: \include Map_placement_new.cpp + * Output: \verbinclude Map_placement_new.out + * + * This class is the return type of PlainObjectBase::Map() but can also be used directly. + * + * \sa PlainObjectBase::Map(), \ref TopicStorageOrders + */ +template +class Map : public MapBase > { + public: + typedef MapBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Map) + + typedef typename Base::PointerType PointerType; + typedef PointerType PointerArgType; + EIGEN_DEVICE_FUNC inline PointerType cast_to_pointer_type(PointerArgType ptr) { return ptr; } + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const { + return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1; + } + + EIGEN_DEVICE_FUNC constexpr Index outerStride() const { + return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer() + : internal::traits::OuterStrideAtCompileTime != Dynamic + ? Index(internal::traits::OuterStrideAtCompileTime) + : IsVectorAtCompileTime ? (this->size() * innerStride()) + : int(Flags) & RowMajorBit ? (this->cols() * innerStride()) + : (this->rows() * innerStride()); + } + + /** Constructor in the fixed-size case. + * + * \param dataPtr pointer to the array to map + * \param stride optional Stride object, passing the strides. + */ + EIGEN_DEVICE_FUNC explicit inline Map(PointerArgType dataPtr, const StrideType& stride = StrideType()) + : Base(cast_to_pointer_type(dataPtr)), m_stride(stride) {} + + /** Constructor in the dynamic-size vector case. + * + * \param dataPtr pointer to the array to map + * \param size the size of the vector expression + * \param stride optional Stride object, passing the strides. + */ + EIGEN_DEVICE_FUNC inline Map(PointerArgType dataPtr, Index size, const StrideType& stride = StrideType()) + : Base(cast_to_pointer_type(dataPtr), size), m_stride(stride) {} + + /** Constructor in the dynamic-size matrix case. + * + * \param dataPtr pointer to the array to map + * \param rows the number of rows of the matrix expression + * \param cols the number of columns of the matrix expression + * \param stride optional Stride object, passing the strides. + */ + EIGEN_DEVICE_FUNC inline Map(PointerArgType dataPtr, Index rows, Index cols, const StrideType& stride = StrideType()) + : Base(cast_to_pointer_type(dataPtr), rows, cols), m_stride(stride) {} + + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Map) + + protected: + StrideType m_stride; +}; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_MAP_H +#endif // EIGEN_MAP_H diff --git a/inst/include/Eigen/src/Core/MapBase.h b/inst/include/Eigen/src/Core/MapBase.h index a9828f7f..5e3d746b 100644 --- a/inst/include/Eigen/src/Core/MapBase.h +++ b/inst/include/Eigen/src/Core/MapBase.h @@ -11,237 +11,273 @@ #ifndef EIGEN_MAPBASE_H #define EIGEN_MAPBASE_H -#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \ - EIGEN_STATIC_ASSERT((int(internal::traits::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ - YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT) - -namespace Eigen { - -/** \class MapBase - * \ingroup Core_Module - * - * \brief Base class for Map and Block expression with direct access - * - * \sa class Map, class Block - */ -template class MapBase - : public internal::dense_xpr_base::type -{ - public: - - typedef typename internal::dense_xpr_base::type Base; - enum { - RowsAtCompileTime = internal::traits::RowsAtCompileTime, - ColsAtCompileTime = internal::traits::ColsAtCompileTime, - SizeAtCompileTime = Base::SizeAtCompileTime - }; - - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - typedef typename internal::conditional< - bool(internal::is_lvalue::value), - Scalar *, - const Scalar *>::type - PointerType; - - using Base::derived; -// using Base::RowsAtCompileTime; -// using Base::ColsAtCompileTime; -// using Base::SizeAtCompileTime; - using Base::MaxRowsAtCompileTime; - using Base::MaxColsAtCompileTime; - using Base::MaxSizeAtCompileTime; - using Base::IsVectorAtCompileTime; - using Base::Flags; - using Base::IsRowMajor; - - using Base::rows; - using Base::cols; - using Base::size; - using Base::coeff; - using Base::coeffRef; - using Base::lazyAssign; - using Base::eval; - - using Base::innerStride; - using Base::outerStride; - using Base::rowStride; - using Base::colStride; - - // bug 217 - compile error on ICC 11.1 - using Base::operator=; - - typedef typename Base::CoeffReturnType CoeffReturnType; - - inline Index rows() const { return m_rows.value(); } - inline Index cols() const { return m_cols.value(); } - - /** Returns a pointer to the first coefficient of the matrix or vector. - * - * \note When addressing this data, make sure to honor the strides returned by innerStride() and outerStride(). - * - * \sa innerStride(), outerStride() - */ - inline const Scalar* data() const { return m_data; } - - inline const Scalar& coeff(Index rowId, Index colId) const - { - return m_data[colId * colStride() + rowId * rowStride()]; - } - - inline const Scalar& coeff(Index index) const - { - EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) - return m_data[index * innerStride()]; - } - - inline const Scalar& coeffRef(Index rowId, Index colId) const - { - return this->m_data[colId * colStride() + rowId * rowStride()]; - } - - inline const Scalar& coeffRef(Index index) const - { - EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) - return this->m_data[index * innerStride()]; - } - - template - inline PacketScalar packet(Index rowId, Index colId) const - { - return internal::ploadt - (m_data + (colId * colStride() + rowId * rowStride())); - } - - template - inline PacketScalar packet(Index index) const - { - EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) - return internal::ploadt(m_data + index * innerStride()); - } - - explicit inline MapBase(PointerType dataPtr) : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime) - { - EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) - checkSanity(); - } - - inline MapBase(PointerType dataPtr, Index vecSize) - : m_data(dataPtr), - m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)), - m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime)) - { - EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) - eigen_assert(vecSize >= 0); - eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize); - checkSanity(); - } - - inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) - : m_data(dataPtr), m_rows(nbRows), m_cols(nbCols) - { - eigen_assert( (dataPtr == 0) - || ( nbRows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == nbRows) - && nbCols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == nbCols))); - checkSanity(); - } - - protected: - - void checkSanity() const - { - EIGEN_STATIC_ASSERT(EIGEN_IMPLIES(internal::traits::Flags&PacketAccessBit, - internal::inner_stride_at_compile_time::ret==1), - PACKET_ACCESS_REQUIRES_TO_HAVE_INNER_STRIDE_FIXED_TO_1); - eigen_assert(EIGEN_IMPLIES(internal::traits::Flags&AlignedBit, (size_t(m_data) % 16) == 0) - && "input pointer is not aligned on a 16 byte boundary"); - } - - PointerType m_data; - const internal::variable_if_dynamic m_rows; - const internal::variable_if_dynamic m_cols; +#define EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) \ + EIGEN_STATIC_ASSERT((int(internal::evaluator::Flags) & LinearAccessBit) || Derived::IsVectorAtCompileTime, \ + YOU_ARE_TRYING_TO_USE_AN_INDEX_BASED_ACCESSOR_ON_AN_EXPRESSION_THAT_DOES_NOT_SUPPORT_THAT) + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +/** \ingroup Core_Module + * + * \brief Base class for dense Map and Block expression with direct access + * + * This base class provides the const low-level accessors (e.g. coeff, coeffRef) of dense + * Map and Block objects with direct access. + * Typical users do not have to directly deal with this class. + * + * This class can be extended by through the macro plugin \c EIGEN_MAPBASE_PLUGIN. + * See \link TopicCustomizing_Plugins customizing Eigen \endlink for details. + * + * The \c Derived class has to provide the following two methods describing the memory layout: + * \code Index innerStride() const; \endcode + * \code Index outerStride() const; \endcode + * + * \sa class Map, class Block + */ +template +class MapBase : public internal::dense_xpr_base::type { + public: + typedef typename internal::dense_xpr_base::type Base; + enum { + RowsAtCompileTime = internal::traits::RowsAtCompileTime, + ColsAtCompileTime = internal::traits::ColsAtCompileTime, + InnerStrideAtCompileTime = internal::traits::InnerStrideAtCompileTime, + SizeAtCompileTime = Base::SizeAtCompileTime + }; + + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::packet_traits::type PacketScalar; + typedef typename NumTraits::Real RealScalar; + typedef std::conditional_t::value), Scalar*, const Scalar*> PointerType; + + using Base::derived; + // using Base::RowsAtCompileTime; + // using Base::ColsAtCompileTime; + // using Base::SizeAtCompileTime; + using Base::Flags; + using Base::IsRowMajor; + using Base::IsVectorAtCompileTime; + using Base::MaxColsAtCompileTime; + using Base::MaxRowsAtCompileTime; + using Base::MaxSizeAtCompileTime; + + using Base::coeff; + using Base::coeffRef; + using Base::cols; + using Base::eval; + using Base::lazyAssign; + using Base::rows; + using Base::size; + + using Base::colStride; + using Base::innerStride; + using Base::outerStride; + using Base::rowStride; + + // bug 217 - compile error on ICC 11.1 + using Base::operator=; + + typedef typename Base::CoeffReturnType CoeffReturnType; + + /** \copydoc DenseBase::rows() */ + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_rows.value(); } + /** \copydoc DenseBase::cols() */ + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_cols.value(); } + + /** Returns a pointer to the first coefficient of the matrix or vector. + * + * \note When addressing this data, make sure to honor the strides returned by innerStride() and outerStride(). + * + * \sa innerStride(), outerStride() + */ + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_data; } + + /** \copydoc PlainObjectBase::coeff(Index,Index) const */ + EIGEN_DEVICE_FUNC inline const Scalar& coeff(Index rowId, Index colId) const { + return m_data[colId * colStride() + rowId * rowStride()]; + } + + /** \copydoc PlainObjectBase::coeff(Index) const */ + EIGEN_DEVICE_FUNC inline const Scalar& coeff(Index index) const { + EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) + return m_data[index * innerStride()]; + } + + /** \copydoc PlainObjectBase::coeffRef(Index,Index) const */ + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { + return this->m_data[colId * colStride() + rowId * rowStride()]; + } + + /** \copydoc PlainObjectBase::coeffRef(Index) const */ + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { + EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) + return this->m_data[index * innerStride()]; + } + + /** \internal */ + template + inline PacketScalar packet(Index rowId, Index colId) const { + return internal::ploadt(m_data + (colId * colStride() + rowId * rowStride())); + } + + /** \internal */ + template + inline PacketScalar packet(Index index) const { + EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) + return internal::ploadt(m_data + index * innerStride()); + } + + /** \internal Constructor for fixed size matrices or vectors */ + EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) + : m_data(dataPtr), m_rows(RowsAtCompileTime), m_cols(ColsAtCompileTime) { + EIGEN_STATIC_ASSERT_FIXED_SIZE(Derived) + checkSanity(); + } + + /** \internal Constructor for dynamically sized vectors */ + EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) + : m_data(dataPtr), + m_rows(RowsAtCompileTime == Dynamic ? vecSize : Index(RowsAtCompileTime)), + m_cols(ColsAtCompileTime == Dynamic ? vecSize : Index(ColsAtCompileTime)) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(Derived) + eigen_assert(vecSize >= 0); + eigen_assert(dataPtr == 0 || SizeAtCompileTime == Dynamic || SizeAtCompileTime == vecSize); + checkSanity(); + } + + /** \internal Constructor for dynamically sized matrices */ + EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) + : m_data(dataPtr), m_rows(rows), m_cols(cols) { + eigen_assert((dataPtr == 0) || (rows >= 0 && (RowsAtCompileTime == Dynamic || RowsAtCompileTime == rows) && + cols >= 0 && (ColsAtCompileTime == Dynamic || ColsAtCompileTime == cols))); + checkSanity(); + } + +#ifdef EIGEN_MAPBASE_PLUGIN +#include EIGEN_MAPBASE_PLUGIN +#endif + + protected: + EIGEN_DEFAULT_COPY_CONSTRUCTOR(MapBase) + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(MapBase) + + template + EIGEN_DEVICE_FUNC void checkSanity(std::enable_if_t<(internal::traits::Alignment > 0), void*> = 0) const { +// Temporary macro to allow scalars to not be properly aligned. This is while we sort out failures +// in TensorFlow Lite that are currently relying on this UB. +#ifndef EIGEN_ALLOW_UNALIGNED_SCALARS + // Pointer must be aligned to the Scalar type, otherwise we get UB. + eigen_assert((std::uintptr_t(m_data) % alignof(Scalar) == 0) && "data is not scalar-aligned"); +#endif +#if EIGEN_MAX_ALIGN_BYTES > 0 + // innerStride() is not set yet when this function is called, so we optimistically assume the lowest plausible + // value: + const Index minInnerStride = InnerStrideAtCompileTime == Dynamic ? 1 : Index(InnerStrideAtCompileTime); + EIGEN_ONLY_USED_FOR_DEBUG(minInnerStride); + eigen_assert((((std::uintptr_t(m_data) % internal::traits::Alignment) == 0) || + (cols() * rows() * minInnerStride * sizeof(Scalar)) < internal::traits::Alignment) && + "data is not aligned"); +#endif + } + + template + EIGEN_DEVICE_FUNC void checkSanity(std::enable_if_t::Alignment == 0, void*> = 0) const { +#ifndef EIGEN_ALLOW_UNALIGNED_SCALARS + // Pointer must be aligned to the Scalar type, otherwise we get UB. + eigen_assert((std::uintptr_t(m_data) % alignof(Scalar) == 0) && "data is not scalar-aligned"); +#endif + } + + PointerType m_data; + const internal::variable_if_dynamic m_rows; + const internal::variable_if_dynamic m_cols; }; -template class MapBase - : public MapBase -{ - typedef MapBase ReadOnlyMapBase; - public: - - typedef MapBase Base; - - typedef typename Base::Scalar Scalar; - typedef typename Base::PacketScalar PacketScalar; - typedef typename Base::Index Index; - typedef typename Base::PointerType PointerType; - - using Base::derived; - using Base::rows; - using Base::cols; - using Base::size; - using Base::coeff; - using Base::coeffRef; - - using Base::innerStride; - using Base::outerStride; - using Base::rowStride; - using Base::colStride; - - typedef typename internal::conditional< - internal::is_lvalue::value, - Scalar, - const Scalar - >::type ScalarWithConstIfNotLvalue; - - inline const Scalar* data() const { return this->m_data; } - inline ScalarWithConstIfNotLvalue* data() { return this->m_data; } // no const-cast here so non-const-correct code will give a compile error - - inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col) - { - return this->m_data[col * colStride() + row * rowStride()]; - } - - inline ScalarWithConstIfNotLvalue& coeffRef(Index index) - { - EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) - return this->m_data[index * innerStride()]; - } - - template - inline void writePacket(Index row, Index col, const PacketScalar& val) - { - internal::pstoret - (this->m_data + (col * colStride() + row * rowStride()), val); - } - - template - inline void writePacket(Index index, const PacketScalar& val) - { - EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) - internal::pstoret - (this->m_data + index * innerStride(), val); - } - - explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {} - inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {} - inline MapBase(PointerType dataPtr, Index nbRows, Index nbCols) : Base(dataPtr, nbRows, nbCols) {} - - Derived& operator=(const MapBase& other) - { - ReadOnlyMapBase::Base::operator=(other); - return derived(); - } - - // In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base, - // see bugs 821 and 920. - using ReadOnlyMapBase::Base::operator=; +/** \ingroup Core_Module + * + * \brief Base class for non-const dense Map and Block expression with direct access + * + * This base class provides the non-const low-level accessors (e.g. coeff and coeffRef) of + * dense Map and Block objects with direct access. + * It inherits MapBase which defines the const variant for reading specific entries. + * + * \sa class Map, class Block + */ +template +class MapBase : public MapBase { + typedef MapBase ReadOnlyMapBase; + + public: + typedef MapBase Base; + + typedef typename Base::Scalar Scalar; + typedef typename Base::PacketScalar PacketScalar; + typedef typename Base::StorageIndex StorageIndex; + typedef typename Base::PointerType PointerType; + + using Base::coeff; + using Base::coeffRef; + using Base::cols; + using Base::derived; + using Base::rows; + using Base::size; + + using Base::colStride; + using Base::innerStride; + using Base::outerStride; + using Base::rowStride; + + typedef std::conditional_t::value, Scalar, const Scalar> ScalarWithConstIfNotLvalue; + + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return this->m_data; } + EIGEN_DEVICE_FUNC constexpr ScalarWithConstIfNotLvalue* data() { + return this->m_data; + } // no const-cast here so non-const-correct code will give a compile error + + EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue& coeffRef(Index row, Index col) { + return this->m_data[col * colStride() + row * rowStride()]; + } + + EIGEN_DEVICE_FUNC inline ScalarWithConstIfNotLvalue& coeffRef(Index index) { + EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) + return this->m_data[index * innerStride()]; + } + + template + inline void writePacket(Index row, Index col, const PacketScalar& val) { + internal::pstoret(this->m_data + (col * colStride() + row * rowStride()), val); + } + + template + inline void writePacket(Index index, const PacketScalar& val) { + EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS(Derived) + internal::pstoret(this->m_data + index * innerStride(), val); + } + + EIGEN_DEVICE_FUNC explicit inline MapBase(PointerType dataPtr) : Base(dataPtr) {} + EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index vecSize) : Base(dataPtr, vecSize) {} + EIGEN_DEVICE_FUNC inline MapBase(PointerType dataPtr, Index rows, Index cols) : Base(dataPtr, rows, cols) {} + + EIGEN_DEVICE_FUNC Derived& operator=(const MapBase& other) { + ReadOnlyMapBase::Base::operator=(other); + return derived(); + } + + // In theory we could simply refer to Base:Base::operator=, but MSVC does not like Base::Base, + // see bugs 821 and 920. + using ReadOnlyMapBase::Base::operator=; + + protected: + EIGEN_DEFAULT_COPY_CONSTRUCTOR(MapBase) + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(MapBase) }; #undef EIGEN_STATIC_ASSERT_INDEX_BASED_ACCESS -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_MAPBASE_H +#endif // EIGEN_MAPBASE_H diff --git a/inst/include/Eigen/src/Core/MathFunctions.h b/inst/include/Eigen/src/Core/MathFunctions.h index adf2f9c5..5e36ce84 100644 --- a/inst/include/Eigen/src/Core/MathFunctions.h +++ b/inst/include/Eigen/src/Core/MathFunctions.h @@ -2,6 +2,7 @@ // for linear algebra. // // Copyright (C) 2006-2010 Benoit Jacob +// Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed @@ -10,719 +11,2022 @@ #ifndef EIGEN_MATHFUNCTIONS_H #define EIGEN_MATHFUNCTIONS_H +// TODO this should better be moved to NumTraits +// Source: WolframAlpha +#define EIGEN_PI 3.141592653589793238462643383279502884197169399375105820974944592307816406L +#define EIGEN_LOG2E 1.442695040888963407359924681001892137426645954152985934135449406931109219L +#define EIGEN_LN2 0.693147180559945309417232121458176568075500134360255254120680009493393621L + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { namespace internal { -/** \internal \struct global_math_functions_filtering_base - * - * What it does: - * Defines a typedef 'type' as follows: - * - if type T has a member typedef Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl, then - * global_math_functions_filtering_base::type is a typedef for it. - * - otherwise, global_math_functions_filtering_base::type is a typedef for T. - * - * How it's used: - * To allow to defined the global math functions (like sin...) in certain cases, like the Array expressions. - * When you do sin(array1+array2), the object array1+array2 has a complicated expression type, all what you want to know - * is that it inherits ArrayBase. So we implement a partial specialization of sin_impl for ArrayBase. - * So we must make sure to use sin_impl > and not sin_impl, otherwise our partial specialization - * won't be used. How does sin know that? That's exactly what global_math_functions_filtering_base tells it. - * - * How it's implemented: - * SFINAE in the style of enable_if. Highly susceptible of breaking compilers. With GCC, it sure does work, but if you replace - * the typename dummy by an integer template parameter, it doesn't work anymore! - */ - -template -struct global_math_functions_filtering_base -{ +/** \internal \class global_math_functions_filtering_base + * + * What it does: + * Defines a typedef 'type' as follows: + * - if type T has a member typedef Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl, then + * global_math_functions_filtering_base::type is a typedef for it. + * - otherwise, global_math_functions_filtering_base::type is a typedef for T. + * + * How it's used: + * To allow to defined the global math functions (like sin...) in certain cases, like the Array expressions. + * When you do sin(array1+array2), the object array1+array2 has a complicated expression type, all what you want to know + * is that it inherits ArrayBase. So we implement a partial specialization of sin_impl for ArrayBase. + * So we must make sure to use sin_impl > and not sin_impl, otherwise our partial + * specialization won't be used. How does sin know that? That's exactly what global_math_functions_filtering_base tells + * it. + * + * How it's implemented: + * SFINAE in the style of enable_if. Highly susceptible of breaking compilers. With GCC, it sure does work, but if you + * replace the typename dummy by an integer template parameter, it doesn't work anymore! + */ + +template +struct global_math_functions_filtering_base { typedef T type; }; -template struct always_void { typedef void type; }; +template +struct always_void { + typedef void type; +}; -template -struct global_math_functions_filtering_base - ::type - > -{ +template +struct global_math_functions_filtering_base< + T, typename always_void::type> { typedef typename T::Eigen_BaseClassForSpecializationOfGlobalMathFuncImpl type; }; -#define EIGEN_MATHFUNC_IMPL(func, scalar) Eigen::internal::func##_impl::type> -#define EIGEN_MATHFUNC_RETVAL(func, scalar) typename Eigen::internal::func##_retval::type>::type +#define EIGEN_MATHFUNC_IMPL(func, scalar) \ + Eigen::internal::func##_impl::type> +#define EIGEN_MATHFUNC_RETVAL(func, scalar) \ + typename Eigen::internal::func##_retval< \ + typename Eigen::internal::global_math_functions_filtering_base::type>::type /**************************************************************************** -* Implementation of real * -****************************************************************************/ + * Implementation of real * + ****************************************************************************/ -template::IsComplex> -struct real_default_impl -{ +template ::IsComplex> +struct real_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x) - { - return x; - } + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return x; } }; -template -struct real_default_impl -{ +template +struct real_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x) - { + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { using std::real; return real(x); } }; -template struct real_impl : real_default_impl {}; +template +struct real_impl : real_default_impl {}; -template -struct real_retval -{ - typedef typename NumTraits::Real type; +#if defined(EIGEN_GPU_COMPILE_PHASE) +template +struct real_impl> { + typedef T RealScalar; + EIGEN_DEVICE_FUNC static inline T run(const std::complex& x) { return x.real(); } }; +#endif +template +struct real_retval { + typedef typename NumTraits::Real type; +}; /**************************************************************************** -* Implementation of imag * -****************************************************************************/ + * Implementation of imag * + ****************************************************************************/ -template::IsComplex> -struct imag_default_impl -{ +template ::IsComplex> +struct imag_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar&) - { - return RealScalar(0); - } + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar&) { return RealScalar(0); } }; -template -struct imag_default_impl -{ +template +struct imag_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x) - { + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { using std::imag; return imag(x); } }; -template struct imag_impl : imag_default_impl {}; +template +struct imag_impl : imag_default_impl {}; -template -struct imag_retval -{ +#if defined(EIGEN_GPU_COMPILE_PHASE) +template +struct imag_impl> { + typedef T RealScalar; + EIGEN_DEVICE_FUNC static inline T run(const std::complex& x) { return x.imag(); } +}; +#endif + +template +struct imag_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** -* Implementation of real_ref * -****************************************************************************/ + * Implementation of real_ref * + ****************************************************************************/ -template -struct real_ref_impl -{ +template +struct real_ref_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar& run(Scalar& x) - { - return reinterpret_cast(&x)[0]; - } - static inline const RealScalar& run(const Scalar& x) - { + EIGEN_DEVICE_FUNC static inline RealScalar& run(Scalar& x) { return reinterpret_cast(&x)[0]; } + EIGEN_DEVICE_FUNC static inline const RealScalar& run(const Scalar& x) { return reinterpret_cast(&x)[0]; } }; -template -struct real_ref_retval -{ - typedef typename NumTraits::Real & type; +template +struct real_ref_retval { + typedef typename NumTraits::Real& type; }; /**************************************************************************** -* Implementation of imag_ref * -****************************************************************************/ + * Implementation of imag_ref * + ****************************************************************************/ -template -struct imag_ref_default_impl -{ +template +struct imag_ref_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar& run(Scalar& x) - { - return reinterpret_cast(&x)[1]; - } - static inline const RealScalar& run(const Scalar& x) - { - return reinterpret_cast(&x)[1]; + EIGEN_DEVICE_FUNC static inline RealScalar& run(Scalar& x) { return reinterpret_cast(&x)[1]; } + EIGEN_DEVICE_FUNC static inline const RealScalar& run(const Scalar& x) { + return reinterpret_cast(&x)[1]; } }; -template -struct imag_ref_default_impl -{ - static inline Scalar run(Scalar&) - { - return Scalar(0); - } - static inline const Scalar run(const Scalar&) - { - return Scalar(0); - } +template +struct imag_ref_default_impl { + EIGEN_DEVICE_FUNC constexpr static Scalar run(Scalar&) { return Scalar(0); } + EIGEN_DEVICE_FUNC constexpr static const Scalar run(const Scalar&) { return Scalar(0); } }; -template +template struct imag_ref_impl : imag_ref_default_impl::IsComplex> {}; -template -struct imag_ref_retval -{ - typedef typename NumTraits::Real & type; +template +struct imag_ref_retval { + typedef typename NumTraits::Real& type; }; +} // namespace internal + +namespace numext { + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline internal::add_const_on_value_type_t real_ref( + const Scalar& x) { + return internal::real_ref_impl::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) real_ref(Scalar& x) { + return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar select(const Scalar& mask, const Scalar& a, const Scalar& b) { + return numext::is_exactly_zero(mask) ? b : a; +} + +} // namespace numext + +namespace internal { + /**************************************************************************** -* Implementation of conj * -****************************************************************************/ + * Implementation of conj * + ****************************************************************************/ -template::IsComplex> -struct conj_impl -{ - static inline Scalar run(const Scalar& x) - { - return x; - } +template ::IsComplex> +struct conj_default_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { return x; } }; -template -struct conj_impl -{ - static inline Scalar run(const Scalar& x) - { +template +struct conj_default_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { using std::conj; return conj(x); } }; -template -struct conj_retval -{ +template ::IsComplex> +struct conj_impl : conj_default_impl {}; + +template +struct conj_retval { typedef Scalar type; }; /**************************************************************************** -* Implementation of abs2 * -****************************************************************************/ + * Implementation of abs2 * + ****************************************************************************/ -template -struct abs2_impl +template +struct abs2_impl_default { + typedef typename NumTraits::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { return x * x; } +}; + +template +struct abs2_impl_default // IsComplex { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x) - { - return x*x; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + return numext::real(x) * numext::real(x) + numext::imag(x) * numext::imag(x); } }; -template -struct abs2_impl > -{ - static inline RealScalar run(const std::complex& x) - { - return real(x)*real(x) + imag(x)*imag(x); +template +struct abs2_impl { + typedef typename NumTraits::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + return abs2_impl_default::IsComplex>::run(x); } }; -template -struct abs2_retval -{ +template +struct abs2_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** -* Implementation of norm1 * -****************************************************************************/ + * Implementation of sqrt/rsqrt * + ****************************************************************************/ + +template +struct sqrt_impl { + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE Scalar run(const Scalar& x) { + EIGEN_USING_STD(sqrt); + return sqrt(x); + } +}; + +// Complex sqrt defined in MathFunctionsImpl.h. +template +EIGEN_DEVICE_FUNC ComplexT complex_sqrt(const ComplexT& a_x); + +// Custom implementation is faster than `std::sqrt`, works on +// GPU, and correctly handles special cases (unlike MSVC). +template +struct sqrt_impl> { + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE std::complex run(const std::complex& x) { return complex_sqrt(x); } +}; + +template +struct sqrt_retval { + typedef Scalar type; +}; + +// Default implementation relies on numext::sqrt, at bottom of file. +template +struct rsqrt_impl; + +// Complex rsqrt defined in MathFunctionsImpl.h. +template +EIGEN_DEVICE_FUNC ComplexT complex_rsqrt(const ComplexT& a_x); + +template +struct rsqrt_impl> { + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE std::complex run(const std::complex& x) { + return complex_rsqrt(x); + } +}; + +template +struct rsqrt_retval { + typedef Scalar type; +}; + +/**************************************************************************** + * Implementation of norm1 * + ****************************************************************************/ -template -struct norm1_default_impl -{ +template +struct norm1_default_impl; + +template +struct norm1_default_impl { typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x) - { - using std::abs; - return abs(real(x)) + abs(imag(x)); + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + EIGEN_USING_STD(abs); + return abs(numext::real(x)) + abs(numext::imag(x)); } }; -template -struct norm1_default_impl -{ - static inline Scalar run(const Scalar& x) - { - using std::abs; +template +struct norm1_default_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { + EIGEN_USING_STD(abs); return abs(x); } }; -template +template struct norm1_impl : norm1_default_impl::IsComplex> {}; -template -struct norm1_retval -{ +template +struct norm1_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** -* Implementation of hypot * -****************************************************************************/ + * Implementation of hypot * + ****************************************************************************/ -template -struct hypot_impl -{ - typedef typename NumTraits::Real RealScalar; - static inline RealScalar run(const Scalar& x, const Scalar& y) - { - using std::max; - using std::min; - using std::abs; - using std::sqrt; - RealScalar _x = abs(x); - RealScalar _y = abs(y); - RealScalar p = (max)(_x, _y); - if(p==RealScalar(0)) return RealScalar(0); - RealScalar q = (min)(_x, _y); - RealScalar qp = q/p; - return p * sqrt(RealScalar(1) + qp*qp); - } -}; - -template -struct hypot_retval -{ +template +struct hypot_impl; + +template +struct hypot_retval { typedef typename NumTraits::Real type; }; /**************************************************************************** -* Implementation of cast * -****************************************************************************/ + * Implementation of cast * + ****************************************************************************/ -template -struct cast_impl -{ - static inline NewType run(const OldType& x) - { - return static_cast(x); +template +struct cast_impl { + EIGEN_DEVICE_FUNC static inline NewType run(const OldType& x) { return static_cast(x); } +}; + +template +struct cast_impl { + EIGEN_DEVICE_FUNC static inline bool run(const OldType& x) { return x != OldType(0); } +}; + +// Casting from S -> Complex leads to an implicit conversion from S to T, +// generating warnings on clang. Here we explicitly cast the real component. +template +struct cast_impl::IsComplex && NumTraits::IsComplex>> { + EIGEN_DEVICE_FUNC static inline NewType run(const OldType& x) { + typedef typename NumTraits::Real NewReal; + return static_cast(static_cast(x)); } }; // here, for once, we're plainly returning NewType: we don't want cast to do weird things. -template -inline NewType cast(const OldType& x) -{ +template +EIGEN_DEVICE_FUNC inline NewType cast(const OldType& x) { return cast_impl::run(x); } /**************************************************************************** -* Implementation of atanh2 * -****************************************************************************/ - -template -struct atanh2_default_impl -{ - typedef Scalar retval; + * Implementation of arg * + ****************************************************************************/ + +// Visual Studio 2017 has a bug where arg(float) returns 0 for negative inputs. +// This seems to be fixed in VS 2019. +#if (!EIGEN_COMP_MSVC || EIGEN_COMP_MSVC >= 1920) +// std::arg is only defined for types of std::complex, or integer types or float/double/long double +template ::IsComplex || is_integral::value || + is_same::value || is_same::value || + is_same::value> +struct arg_default_impl; + +template +struct arg_default_impl { typedef typename NumTraits::Real RealScalar; - static inline Scalar run(const Scalar& x, const Scalar& y) - { - using std::abs; - using std::log; - using std::sqrt; - Scalar z = x / y; - if (y == Scalar(0) || abs(z) > sqrt(NumTraits::epsilon())) - return RealScalar(0.5) * log((y + x) / (y - x)); - else - return z + z*z*z / RealScalar(3); + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + // There is no official ::arg on device in CUDA/HIP, so we always need to use std::arg. + using std::arg; + return static_cast(arg(x)); } }; -template -struct atanh2_default_impl -{ - static inline Scalar run(const Scalar&, const Scalar&) - { - EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) - return Scalar(0); +// Must be non-complex floating-point type (e.g. half/bfloat16). +template +struct arg_default_impl { + typedef typename NumTraits::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + return (x < Scalar(0)) ? RealScalar(EIGEN_PI) : RealScalar(0); + } +}; +#else +template ::IsComplex> +struct arg_default_impl { + typedef typename NumTraits::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + return (x < RealScalar(0)) ? RealScalar(EIGEN_PI) : RealScalar(0); } }; -template -struct atanh2_impl : atanh2_default_impl::IsInteger> {}; +template +struct arg_default_impl { + typedef typename NumTraits::Real RealScalar; + EIGEN_DEVICE_FUNC static inline RealScalar run(const Scalar& x) { + EIGEN_USING_STD(arg); + return arg(x); + } +}; +#endif +template +struct arg_impl : arg_default_impl {}; -template -struct atanh2_retval -{ - typedef Scalar type; +template +struct arg_retval { + typedef typename NumTraits::Real type; }; /**************************************************************************** -* Implementation of pow * -****************************************************************************/ + * Implementation of expm1 * + ****************************************************************************/ + +// This implementation is based on GSL Math's expm1. +namespace std_fallback { +// fallback expm1 implementation in case there is no expm1(Scalar) function in namespace of Scalar, +// or that there is no suitable std::expm1 function available. Implementation +// attributed to Kahan. See: http://www.plunk.org/~hatch/rightway.php. +template +EIGEN_DEVICE_FUNC inline Scalar expm1(const Scalar& x) { + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) + typedef typename NumTraits::Real RealScalar; -template -struct pow_default_impl -{ - typedef Scalar retval; - static inline Scalar run(const Scalar& x, const Scalar& y) - { - using std::pow; - return pow(x, y); + EIGEN_USING_STD(exp); + Scalar u = exp(x); + if (numext::equal_strict(u, Scalar(1))) { + return x; + } + Scalar um1 = u - RealScalar(1); + if (numext::equal_strict(um1, Scalar(-1))) { + return RealScalar(-1); } -}; -template -struct pow_default_impl -{ - static inline Scalar run(Scalar x, Scalar y) - { - Scalar res(1); - eigen_assert(!NumTraits::IsSigned || y >= 0); - if(y & 1) res *= x; - y >>= 1; - while(y) - { - x *= x; - if(y&1) res *= x; - y >>= 1; - } - return res; + EIGEN_USING_STD(log); + Scalar logu = log(u); + return numext::equal_strict(u, logu) ? u : (u - RealScalar(1)) * x / logu; +} +} // namespace std_fallback + +template +struct expm1_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) + EIGEN_USING_STD(expm1); + return expm1(x); } }; -template -struct pow_impl : pow_default_impl::IsInteger> {}; - -template -struct pow_retval -{ +template +struct expm1_retval { typedef Scalar type; }; /**************************************************************************** -* Implementation of random * -****************************************************************************/ + * Implementation of log * + ****************************************************************************/ + +// Complex log defined in MathFunctionsImpl.h. +template +EIGEN_DEVICE_FUNC ComplexT complex_log(const ComplexT& z); + +template +struct log_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { + EIGEN_USING_STD(log); + return static_cast(log(x)); + } +}; + +template +struct log_impl> { + EIGEN_DEVICE_FUNC static inline std::complex run(const std::complex& z) { return complex_log(z); } +}; -template -struct random_default_impl {}; +/**************************************************************************** + * Implementation of log1p * + ****************************************************************************/ + +namespace std_fallback { +// fallback log1p implementation in case there is no log1p(Scalar) function in namespace of Scalar, +// or that there is no suitable std::log1p function available +template +EIGEN_DEVICE_FUNC inline Scalar log1p(const Scalar& x) { + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) + typedef typename NumTraits::Real RealScalar; + EIGEN_USING_STD(log); + Scalar x1p = RealScalar(1) + x; + Scalar log_1p = log_impl::run(x1p); + const bool is_small = numext::equal_strict(x1p, Scalar(1)); + const bool is_inf = numext::equal_strict(x1p, log_1p); + return (is_small || is_inf) ? x : x * (log_1p / (x1p - RealScalar(1))); +} +} // namespace std_fallback -template -struct random_impl : random_default_impl::IsComplex, NumTraits::IsInteger> {}; +template +struct log1p_impl { + EIGEN_STATIC_ASSERT_NON_INTEGER(Scalar) -template -struct random_retval -{ - typedef Scalar type; + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& x) { + EIGEN_USING_STD(log1p); + return log1p(x); + } }; -template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(const Scalar& x, const Scalar& y); -template inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(); +// Specialization for complex types that are not supported by std::log1p. +template +struct log1p_impl> { + EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar) -template -struct random_default_impl -{ - static inline Scalar run(const Scalar& x, const Scalar& y) - { - return x + (y-x) * Scalar(std::rand()) / Scalar(RAND_MAX); + EIGEN_DEVICE_FUNC static inline std::complex run(const std::complex& x) { + return std_fallback::log1p(x); } - static inline Scalar run() - { - return run(Scalar(NumTraits::IsSigned ? -1 : 0), Scalar(1)); +}; + +template +struct log1p_retval { + typedef Scalar type; +}; + +/**************************************************************************** + * Implementation of pow * + ****************************************************************************/ + +template ::IsInteger && NumTraits::IsInteger> +struct pow_impl { + // typedef Scalar retval; + typedef typename ScalarBinaryOpTraits>::ReturnType + result_type; + static EIGEN_DEVICE_FUNC inline result_type run(const ScalarX& x, const ScalarY& y) { + EIGEN_USING_STD(pow); + return pow(x, y); } }; -enum { - floor_log2_terminate, - floor_log2_move_up, - floor_log2_move_down, - floor_log2_bogus +template +struct pow_impl { + typedef ScalarX result_type; + static EIGEN_DEVICE_FUNC inline ScalarX run(ScalarX x, ScalarY y) { + ScalarX res(1); + eigen_assert(!NumTraits::IsSigned || y >= 0); + if (y & 1) res *= x; + y >>= 1; + while (y) { + x *= x; + if (y & 1) res *= x; + y >>= 1; + } + return res; + } }; -template struct floor_log2_selector -{ - enum { middle = (lower + upper) / 2, - value = (upper <= lower + 1) ? int(floor_log2_terminate) - : (n < (1 << middle)) ? int(floor_log2_move_down) - : (n==0) ? int(floor_log2_bogus) - : int(floor_log2_move_up) +enum { meta_floor_log2_terminate, meta_floor_log2_move_up, meta_floor_log2_move_down, meta_floor_log2_bogus }; + +template +struct meta_floor_log2_selector { + enum { + middle = (lower + upper) / 2, + value = (upper <= lower + 1) ? int(meta_floor_log2_terminate) + : (n < (1 << middle)) ? int(meta_floor_log2_move_down) + : (n == 0) ? int(meta_floor_log2_bogus) + : int(meta_floor_log2_move_up) }; }; -template::value> -struct floor_log2 {}; +template ::value> +struct meta_floor_log2 {}; -template -struct floor_log2 -{ - enum { value = floor_log2::middle>::value }; +template +struct meta_floor_log2 { + enum { value = meta_floor_log2::middle>::value }; }; -template -struct floor_log2 -{ - enum { value = floor_log2::middle, upper>::value }; +template +struct meta_floor_log2 { + enum { value = meta_floor_log2::middle, upper>::value }; }; -template -struct floor_log2 -{ - enum { value = (n >= ((unsigned int)(1) << (lower+1))) ? lower+1 : lower }; +template +struct meta_floor_log2 { + enum { value = (n >= ((unsigned int)(1) << (lower + 1))) ? lower + 1 : lower }; }; -template -struct floor_log2 -{ +template +struct meta_floor_log2 { // no value, error at compile time }; -template -struct random_default_impl -{ - typedef typename NumTraits::NonInteger NonInteger; +template +struct count_bits_impl { + static_assert(std::is_integral::value && std::is_unsigned::value, + "BitsType must be an unsigned integer"); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + int n = CHAR_BIT * sizeof(BitsType); + int shift = n / 2; + while (bits > 0 && shift > 0) { + BitsType y = bits >> shift; + if (y > 0) { + n -= shift; + bits = y; + } + shift /= 2; + } + if (shift == 0) { + --n; + } + return n; + } - static inline Scalar run(const Scalar& x, const Scalar& y) - { - return x + Scalar((NonInteger(y)-x+1) * std::rand() / (RAND_MAX + NonInteger(1))); + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + int n = CHAR_BIT * sizeof(BitsType); + int shift = n / 2; + while (bits > 0 && shift > 0) { + BitsType y = bits << shift; + if (y > 0) { + n -= shift; + bits = y; + } + shift /= 2; + } + if (shift == 0) { + --n; + } + return n; } +}; - static inline Scalar run() - { -#ifdef EIGEN_MAKING_DOCS - return run(Scalar(NumTraits::IsSigned ? -10 : 0), Scalar(10)); -#else - enum { rand_bits = floor_log2<(unsigned int)(RAND_MAX)+1>::value, - scalar_bits = sizeof(Scalar) * CHAR_BIT, - shift = EIGEN_PLAIN_ENUM_MAX(0, int(rand_bits) - int(scalar_bits)), - offset = NumTraits::IsSigned ? (1 << (EIGEN_PLAIN_ENUM_MIN(rand_bits,scalar_bits)-1)) : 0 - }; - return Scalar((std::rand() >> shift) - offset); -#endif +// Count leading zeros. +template +EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + return count_bits_impl::clz(bits); +} + +// Count trailing zeros. +template +EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + return count_bits_impl::ctz(bits); +} + +#if EIGEN_COMP_GNUC || EIGEN_COMP_CLANG + +template +struct count_bits_impl< + BitsType, std::enable_if_t::value && sizeof(BitsType) <= sizeof(unsigned int)>> { + static constexpr int kNumBits = static_cast(sizeof(BitsType) * CHAR_BIT); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + static constexpr int kLeadingBitsOffset = (sizeof(unsigned int) - sizeof(BitsType)) * CHAR_BIT; + return bits == 0 ? kNumBits : __builtin_clz(static_cast(bits)) - kLeadingBitsOffset; + } + + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + return bits == 0 ? kNumBits : __builtin_ctz(static_cast(bits)); } }; -template -struct random_default_impl -{ - static inline Scalar run(const Scalar& x, const Scalar& y) - { - return Scalar(random(real(x), real(y)), - random(imag(x), imag(y))); +template +struct count_bits_impl::value && sizeof(unsigned int) < sizeof(BitsType) && + sizeof(BitsType) <= sizeof(unsigned long)>> { + static constexpr int kNumBits = static_cast(sizeof(BitsType) * CHAR_BIT); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + static constexpr int kLeadingBitsOffset = (sizeof(unsigned long) - sizeof(BitsType)) * CHAR_BIT; + return bits == 0 ? kNumBits : __builtin_clzl(static_cast(bits)) - kLeadingBitsOffset; } - static inline Scalar run() - { - typedef typename NumTraits::Real RealScalar; - return Scalar(random(), random()); + + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + return bits == 0 ? kNumBits : __builtin_ctzl(static_cast(bits)); } }; -template -inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(const Scalar& x, const Scalar& y) -{ - return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(x, y); -} +template +struct count_bits_impl::value && sizeof(unsigned long) < sizeof(BitsType) && + sizeof(BitsType) <= sizeof(unsigned long long)>> { + static constexpr int kNumBits = static_cast(sizeof(BitsType) * CHAR_BIT); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + static constexpr int kLeadingBitsOffset = (sizeof(unsigned long long) - sizeof(BitsType)) * CHAR_BIT; + return bits == 0 ? kNumBits : __builtin_clzll(static_cast(bits)) - kLeadingBitsOffset; + } -template -inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random() -{ - return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(); -} + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + return bits == 0 ? kNumBits : __builtin_ctzll(static_cast(bits)); + } +}; -} // end namespace internal +#elif EIGEN_COMP_MSVC -/**************************************************************************** -* Generic math function * -****************************************************************************/ +template +struct count_bits_impl< + BitsType, std::enable_if_t::value && sizeof(BitsType) <= sizeof(unsigned long)>> { + static constexpr int kNumBits = static_cast(sizeof(BitsType) * CHAR_BIT); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + unsigned long out; + _BitScanReverse(&out, static_cast(bits)); + return bits == 0 ? kNumBits : (kNumBits - 1) - static_cast(out); + } -namespace numext { + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + unsigned long out; + _BitScanForward(&out, static_cast(bits)); + return bits == 0 ? kNumBits : static_cast(out); + } +}; -template -inline EIGEN_MATHFUNC_RETVAL(real, Scalar) real(const Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(real, Scalar)::run(x); -} +#ifdef _WIN64 + +template +struct count_bits_impl::value && sizeof(unsigned long) < sizeof(BitsType) && + sizeof(BitsType) <= sizeof(__int64)>> { + static constexpr int kNumBits = static_cast(sizeof(BitsType) * CHAR_BIT); + static EIGEN_DEVICE_FUNC inline int clz(BitsType bits) { + unsigned long out; + _BitScanReverse64(&out, static_cast(bits)); + return bits == 0 ? kNumBits : (kNumBits - 1) - static_cast(out); + } -template -inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) >::type real_ref(const Scalar& x) -{ - return internal::real_ref_impl::run(x); -} + static EIGEN_DEVICE_FUNC inline int ctz(BitsType bits) { + unsigned long out; + _BitScanForward64(&out, static_cast(bits)); + return bits == 0 ? kNumBits : static_cast(out); + } +}; -template -inline EIGEN_MATHFUNC_RETVAL(real_ref, Scalar) real_ref(Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(real_ref, Scalar)::run(x); -} +#endif // _WIN64 -template -inline EIGEN_MATHFUNC_RETVAL(imag, Scalar) imag(const Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(imag, Scalar)::run(x); -} +#endif // EIGEN_COMP_GNUC || EIGEN_COMP_CLANG -template -inline typename internal::add_const_on_value_type< EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) >::type imag_ref(const Scalar& x) -{ - return internal::imag_ref_impl::run(x); -} +template +struct log_2_impl { + static constexpr int kTotalBits = sizeof(BitsType) * CHAR_BIT; + static EIGEN_DEVICE_FUNC inline int run_ceil(const BitsType& x) { + const int n = kTotalBits - clz(x); + bool power_of_two = (x & (x - 1)) == 0; + return x == 0 ? 0 : power_of_two ? (n - 1) : n; + } + static EIGEN_DEVICE_FUNC inline int run_floor(const BitsType& x) { + const int n = kTotalBits - clz(x); + return x == 0 ? 0 : n - 1; + } +}; -template -inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) imag_ref(Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x); +template +int log2_ceil(const BitsType& x) { + return log_2_impl::run_ceil(x); } -template -inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x); +template +int log2_floor(const BitsType& x) { + return log_2_impl::run_floor(x); } -template -inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(abs2, Scalar)::run(x); -} +// Implementation of is* functions -template -inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar) norm1(const Scalar& x) -{ - return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x); +template +EIGEN_DEVICE_FUNC std::enable_if_t::has_infinity || std::numeric_limits::has_quiet_NaN || + std::numeric_limits::has_signaling_NaN), + bool> +isfinite_impl(const T&) { + return true; } -template -inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar& y) -{ - return EIGEN_MATHFUNC_IMPL(hypot, Scalar)::run(x, y); +template +EIGEN_DEVICE_FUNC std::enable_if_t<(std::numeric_limits::has_infinity || std::numeric_limits::has_quiet_NaN || + std::numeric_limits::has_signaling_NaN) && + (!NumTraits::IsComplex), + bool> +isfinite_impl(const T& x) { + EIGEN_USING_STD(isfinite); + return isfinite EIGEN_NOT_A_MACRO(x); } -template -inline EIGEN_MATHFUNC_RETVAL(atanh2, Scalar) atanh2(const Scalar& x, const Scalar& y) -{ - return EIGEN_MATHFUNC_IMPL(atanh2, Scalar)::run(x, y); +template +EIGEN_DEVICE_FUNC std::enable_if_t::has_infinity, bool> isinf_impl(const T&) { + return false; } -template -inline EIGEN_MATHFUNC_RETVAL(pow, Scalar) pow(const Scalar& x, const Scalar& y) -{ - return EIGEN_MATHFUNC_IMPL(pow, Scalar)::run(x, y); +template +EIGEN_DEVICE_FUNC std::enable_if_t<(std::numeric_limits::has_infinity && !NumTraits::IsComplex), bool> isinf_impl( + const T& x) { + EIGEN_USING_STD(isinf); + return isinf EIGEN_NOT_A_MACRO(x); } -// std::isfinite is non standard, so let's define our own version, -// even though it is not very efficient. -template bool (isfinite)(const T& x) -{ - return x::highest() && x>NumTraits::lowest(); +template +EIGEN_DEVICE_FUNC +std::enable_if_t::has_quiet_NaN || std::numeric_limits::has_signaling_NaN), bool> +isnan_impl(const T&) { + return false; } -} // end namespace numext +template +EIGEN_DEVICE_FUNC std::enable_if_t< + (std::numeric_limits::has_quiet_NaN || std::numeric_limits::has_signaling_NaN) && (!NumTraits::IsComplex), + bool> +isnan_impl(const T& x) { + EIGEN_USING_STD(isnan); + return isnan EIGEN_NOT_A_MACRO(x); +} -namespace internal { +// The following overload are defined at the end of this file +template +EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex& x); +template +EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex& x); +template +EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex& x); +template +EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS T ptanh_float(const T& a_x); /**************************************************************************** -* Implementation of fuzzy comparisons * -****************************************************************************/ + * Implementation of sign * + ****************************************************************************/ +template ::IsComplex != 0), + bool IsInteger = (NumTraits::IsInteger != 0)> +struct sign_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& a) { return Scalar((a > Scalar(0)) - (a < Scalar(0))); } +}; -template -struct scalar_fuzzy_default_impl {}; +template +struct sign_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& a) { + return (isnan_impl)(a) ? a : Scalar((a > Scalar(0)) - (a < Scalar(0))); + } +}; -template -struct scalar_fuzzy_default_impl -{ - typedef typename NumTraits::Real RealScalar; - template - static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec) - { - using std::abs; - return abs(x) <= abs(y) * prec; - } - static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) - { - using std::min; - using std::abs; - return abs(x - y) <= (min)(abs(x), abs(y)) * prec; - } - static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec) - { - return x <= y || isApprox(x, y, prec); +template +struct sign_impl { + EIGEN_DEVICE_FUNC static inline Scalar run(const Scalar& a) { + using real_type = typename NumTraits::Real; + EIGEN_USING_STD(abs); + real_type aa = abs(a); + if (aa == real_type(0)) return Scalar(0); + aa = real_type(1) / aa; + return Scalar(numext::real(a) * aa, numext::imag(a) * aa); } }; -template -struct scalar_fuzzy_default_impl -{ - typedef typename NumTraits::Real RealScalar; - template - static inline bool isMuchSmallerThan(const Scalar& x, const Scalar&, const RealScalar&) - { - return x == Scalar(0); +// The sign function for bool is the identity. +template <> +struct sign_impl { + EIGEN_DEVICE_FUNC static inline bool run(const bool& a) { return a; } +}; + +template +struct sign_retval { + typedef Scalar type; +}; + +// suppress "unary minus operator applied to unsigned type, result still unsigned" warnings on MSVC +// note: `0 - a` is distinct from `-a` when Scalar is a floating point type and `a` is zero + +template ::IsInteger> +struct negate_impl { + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar run(const Scalar& a) { return -a; } +}; + +template +struct negate_impl { + EIGEN_STATIC_ASSERT((!is_same::value), NEGATE IS NOT DEFINED FOR BOOLEAN TYPES) + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE Scalar run(const Scalar& a) { return Scalar(0) - a; } +}; + +template +struct negate_retval { + typedef Scalar type; +}; + +template ::type>::IsInteger> +struct nearest_integer_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_floor(const Scalar& x) { + EIGEN_USING_STD(floor) return floor(x); } - static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar&) - { - return x == y; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_ceil(const Scalar& x) { + EIGEN_USING_STD(ceil) return ceil(x); } - static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar&) - { - return x <= y; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_rint(const Scalar& x) { + EIGEN_USING_STD(rint) return rint(x); } -}; - -template -struct scalar_fuzzy_default_impl -{ - typedef typename NumTraits::Real RealScalar; - template - static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, const RealScalar& prec) - { - return numext::abs2(x) <= numext::abs2(y) * prec * prec; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_round(const Scalar& x) { + EIGEN_USING_STD(round) return round(x); } - static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) - { - using std::min; - return numext::abs2(x - y) <= (min)(numext::abs2(x), numext::abs2(y)) * prec * prec; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_trunc(const Scalar& x) { + EIGEN_USING_STD(trunc) return trunc(x); } }; +template +struct nearest_integer_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_floor(const Scalar& x) { return x; } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_ceil(const Scalar& x) { return x; } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_rint(const Scalar& x) { return x; } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_round(const Scalar& x) { return x; } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run_trunc(const Scalar& x) { return x; } +}; -template -struct scalar_fuzzy_impl : scalar_fuzzy_default_impl::IsComplex, NumTraits::IsInteger> {}; +// Extra namespace to prevent leaking std::fma into Eigen::internal. +namespace has_fma_detail { -template -inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, - typename NumTraits::Real precision = NumTraits::dummy_precision()) -{ - return scalar_fuzzy_impl::template isMuchSmallerThan(x, y, precision); -} +template +struct has_fma_impl : public std::false_type {}; -template -inline bool isApprox(const Scalar& x, const Scalar& y, - typename NumTraits::Real precision = NumTraits::dummy_precision()) -{ +using std::fma; + +template +struct has_fma_impl< + T, std::enable_if_t(), std::declval(), std::declval()))>::value>> + : public std::true_type {}; + +} // namespace has_fma_detail + +template +struct has_fma : public has_fma_detail::has_fma_impl {}; + +// Default implementation. +template +struct fma_impl { + static_assert(has_fma::value, "No function fma(...) for type. Please provide an implementation."); +}; + +// STD or ADL version if it exists. +template +struct fma_impl::value>> { + static EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T run(const T& a, const T& b, const T& c) { + using std::fma; + return fma(a, b, c); + } +}; + +#if defined(EIGEN_GPUCC) +template <> +struct has_fma : public true_type {}; + +template <> +struct fma_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE float run(const float& a, const float& b, const float& c) { + return ::fmaf(a, b, c); + } +}; + +template <> +struct has_fma : public true_type {}; + +template <> +struct fma_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE double run(const double& a, const double& b, const double& c) { + return ::fma(a, b, c); + } +}; +#endif + +// Basic multiply-add. +template +struct madd_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run(const Scalar& x, const Scalar& y, const Scalar& z) { + return x * y + z; + } +}; + +#if EIGEN_SCALAR_MADD_USE_FMA +template +struct madd_impl::value>> { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar run(const Scalar& x, const Scalar& y, const Scalar& z) { + return fma_impl::run(x, y, z); + } +}; +#endif + +} // end namespace internal + +/**************************************************************************** + * Generic math functions * + ****************************************************************************/ + +namespace numext { + +#if (!defined(EIGEN_GPUCC) || defined(EIGEN_CONSTEXPR_ARE_DEVICE_FUNC)) +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y) { + EIGEN_USING_STD(min) + return min EIGEN_NOT_A_MACRO(x, y); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y) { + EIGEN_USING_STD(max) + return max EIGEN_NOT_A_MACRO(x, y); +} +#else +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T mini(const T& x, const T& y) { + return y < x ? y : x; +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float mini(const float& x, const float& y) { + return fminf(x, y); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double mini(const double& x, const double& y) { + return fmin(x, y); +} + +#ifndef EIGEN_GPU_COMPILE_PHASE +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double mini(const long double& x, const long double& y) { +#if defined(EIGEN_HIPCC) + // no "fminl" on HIP yet + return (x < y) ? x : y; +#else + return fminl(x, y); +#endif +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T maxi(const T& x, const T& y) { + return x < y ? y : x; +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float maxi(const float& x, const float& y) { + return fmaxf(x, y); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double maxi(const double& x, const double& y) { + return fmax(x, y); +} +#ifndef EIGEN_GPU_COMPILE_PHASE +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double maxi(const long double& x, const long double& y) { +#if defined(EIGEN_HIPCC) + // no "fmaxl" on HIP yet + return (x > y) ? x : y; +#else + return fmaxl(x, y); +#endif +} +#endif +#endif + +#if defined(SYCL_DEVICE_ONLY) + +#define SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_char) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_short) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_int) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_long) +#define SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_char) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_short) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_int) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_long) +#define SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_uchar) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_ushort) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_uint) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_ulong) +#define SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_uchar) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_ushort) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_uint) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_ulong) +#define SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(NAME, FUNC) \ + SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) \ + SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY(NAME, FUNC) +#define SYCL_SPECIALIZE_INTEGER_TYPES_UNARY(NAME, FUNC) \ + SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) \ + SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY(NAME, FUNC) +#define SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(NAME, FUNC) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_float) \ + SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, cl::sycl::cl_double) +#define SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(NAME, FUNC) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_float) \ + SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, cl::sycl::cl_double) +#define SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(NAME, FUNC, RET_TYPE) \ + SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, cl::sycl::cl_float) \ + SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, cl::sycl::cl_double) + +#define SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE) \ + template <> \ + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE RET_TYPE NAME(const ARG_TYPE& x) { \ + return cl::sycl::FUNC(x); \ + } + +#define SYCL_SPECIALIZE_UNARY_FUNC(NAME, FUNC, TYPE) SYCL_SPECIALIZE_GEN_UNARY_FUNC(NAME, FUNC, TYPE, TYPE) + +#define SYCL_SPECIALIZE_GEN1_BINARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE1, ARG_TYPE2) \ + template <> \ + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE RET_TYPE NAME(const ARG_TYPE1& x, const ARG_TYPE2& y) { \ + return cl::sycl::FUNC(x, y); \ + } + +#define SYCL_SPECIALIZE_GEN2_BINARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE) \ + SYCL_SPECIALIZE_GEN1_BINARY_FUNC(NAME, FUNC, RET_TYPE, ARG_TYPE, ARG_TYPE) + +#define SYCL_SPECIALIZE_BINARY_FUNC(NAME, FUNC, TYPE) SYCL_SPECIALIZE_GEN2_BINARY_FUNC(NAME, FUNC, TYPE, TYPE) + +SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(mini, min) +SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(mini, fmin) +SYCL_SPECIALIZE_INTEGER_TYPES_BINARY(maxi, max) +SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(maxi, fmax) + +#endif + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(arg, Scalar) arg(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(arg, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline internal::add_const_on_value_type_t imag_ref( + const Scalar& x) { + return internal::imag_ref_impl::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(imag_ref, Scalar) imag_ref(Scalar& x) { + return EIGEN_MATHFUNC_IMPL(imag_ref, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(conj, Scalar) conj(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(conj, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(sign, Scalar) sign(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(sign, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(negate, Scalar) negate(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(negate, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(abs2, Scalar) abs2(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(abs2, Scalar)::run(x); +} + +EIGEN_DEVICE_FUNC inline bool abs2(bool x) { return x; } + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T absdiff(const T& x, const T& y) { + return x > y ? x - y : y - x; +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float absdiff(const float& x, const float& y) { + return fabsf(x - y); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double absdiff(const double& x, const double& y) { + return fabs(x - y); +} + +// HIP and CUDA do not support long double. +#ifndef EIGEN_GPU_COMPILE_PHASE +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE long double absdiff(const long double& x, const long double& y) { + return fabsl(x - y); +} +#endif + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(norm1, Scalar) norm1(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(norm1, Scalar)::run(x); +} + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(hypot, Scalar) hypot(const Scalar& x, const Scalar& y) { + return EIGEN_MATHFUNC_IMPL(hypot, Scalar)::run(x, y); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(hypot, hypot) +#endif + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(log1p, Scalar) log1p(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(log1p, Scalar)::run(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(log1p, log1p) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float log1p(const float& x) { + return ::log1pf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double log1p(const double& x) { + return ::log1p(x); +} +#endif + +template +EIGEN_DEVICE_FUNC inline typename internal::pow_impl::result_type pow(const ScalarX& x, + const ScalarY& y) { + return internal::pow_impl::run(x, y); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(pow, pow) +#endif + +template +EIGEN_DEVICE_FUNC bool(isnan)(const T& x) { + return internal::isnan_impl(x); +} +template +EIGEN_DEVICE_FUNC bool(isinf)(const T& x) { + return internal::isinf_impl(x); +} +template +EIGEN_DEVICE_FUNC bool(isfinite)(const T& x) { + return internal::isfinite_impl(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isnan, isnan, bool) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isinf, isinf, bool) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE(isfinite, isfinite, bool) +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar rint(const Scalar& x) { + return internal::nearest_integer_impl::run_rint(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar round(const Scalar& x) { + return internal::nearest_integer_impl::run_round(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar(floor)(const Scalar& x) { + return internal::nearest_integer_impl::run_floor(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar(ceil)(const Scalar& x) { + return internal::nearest_integer_impl::run_ceil(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar(trunc)(const Scalar& x) { + return internal::nearest_integer_impl::run_trunc(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(round, round) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(floor, floor) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(ceil, ceil) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(trunc, trunc) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float floor(const float& x) { + return ::floorf(x); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double floor(const double& x) { + return ::floor(x); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float ceil(const float& x) { + return ::ceilf(x); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double ceil(const double& x) { + return ::ceil(x); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float trunc(const float& x) { + return ::truncf(x); +} +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double trunc(const double& x) { + return ::trunc(x); +} +#endif + +// Integer division with rounding up. +// T is assumed to be an integer type with a>=0, and b>0 +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE constexpr T div_ceil(T a, T b) { + using UnsignedT = typename internal::make_unsigned::type; + EIGEN_STATIC_ASSERT((NumTraits::IsInteger), THIS FUNCTION IS FOR INTEGER TYPES) + // Note: explicitly declaring a and b as non-negative values allows the compiler to use better optimizations + const UnsignedT ua = UnsignedT(a); + const UnsignedT ub = UnsignedT(b); + // Note: This form is used because it cannot overflow. + return ua == 0 ? 0 : (ua - 1) / ub + 1; +} + +// Integer round down to nearest power of b +// T is assumed to be an integer type with a>=0, and b>0 +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE constexpr T round_down(T a, U b) { + using UnsignedT = typename internal::make_unsigned::type; + using UnsignedU = typename internal::make_unsigned::type; + EIGEN_STATIC_ASSERT((NumTraits::IsInteger), THIS FUNCTION IS FOR INTEGER TYPES) + EIGEN_STATIC_ASSERT((NumTraits::IsInteger), THIS FUNCTION IS FOR INTEGER TYPES) + // Note: explicitly declaring a and b as non-negative values allows the compiler to use better optimizations + const UnsignedT ua = UnsignedT(a); + const UnsignedU ub = UnsignedU(b); + return ub * (ua / ub); +} + +/** Log base 2 for 32 bits positive integers. + * Conveniently returns 0 for x==0. */ +constexpr int log2(int x) { + unsigned int v(x); + constexpr int table[32] = {0, 9, 1, 10, 13, 21, 2, 29, 11, 14, 16, 18, 22, 25, 3, 30, + 8, 12, 20, 28, 15, 17, 24, 7, 19, 27, 23, 6, 26, 5, 4, 31}; + v |= v >> 1; + v |= v >> 2; + v |= v >> 4; + v |= v >> 8; + v |= v >> 16; + return table[(v * 0x07C4ACDDU) >> 27]; +} + +/** \returns the square root of \a x. + * + * It is essentially equivalent to + * \code using std::sqrt; return sqrt(x); \endcode + * but slightly faster for float/double and some compilers (e.g., gcc), thanks to + * specializations when SSE is enabled. + * + * It's usage is justified in performance critical functions, like norm/normalize. + */ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE EIGEN_MATHFUNC_RETVAL(sqrt, Scalar) sqrt(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(sqrt, Scalar)::run(x); +} + +// Boolean specialization, avoids implicit float to bool conversion (-Wimplicit-conversion-floating-point-to-bool). +template <> +EIGEN_DEFINE_FUNCTION_ALLOWING_MULTIPLE_DEFINITIONS EIGEN_DEVICE_FUNC bool sqrt(const bool& x) { + return x; +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sqrt, sqrt) +#endif + +/** \returns the cube root of \a x. **/ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::enable_if_t::IsComplex, T> cbrt(const T& x) { + EIGEN_USING_STD(cbrt); + return static_cast(cbrt(x)); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::enable_if_t::IsComplex, T> cbrt(const T& x) { + EIGEN_USING_STD(pow); + return pow(x, typename NumTraits::Real(1.0 / 3.0)); +} + +/** \returns the reciprocal square root of \a x. **/ +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T rsqrt(const T& x) { + return internal::rsqrt_impl::run(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T log(const T& x) { + return internal::log_impl::run(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(log, log) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float log(const float& x) { + return ::logf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double log(const double& x) { + return ::log(x); +} +#endif + +template +EIGEN_DEVICE_FUNC +EIGEN_ALWAYS_INLINE std::enable_if_t::IsSigned || NumTraits::IsComplex, typename NumTraits::Real> +abs(const T& x) { + EIGEN_USING_STD(abs); + return abs(x); +} + +template +EIGEN_DEVICE_FUNC +EIGEN_ALWAYS_INLINE std::enable_if_t::IsSigned || NumTraits::IsComplex), typename NumTraits::Real> +abs(const T& x) { + return x; +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_INTEGER_TYPES_UNARY(abs, abs) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(abs, fabs) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float abs(const float& x) { + return ::fabsf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double abs(const double& x) { + return ::fabs(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float abs(const std::complex& x) { + return ::hypotf(x.real(), x.imag()); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double abs(const std::complex& x) { + return ::hypot(x.real(), x.imag()); +} +#endif + +template ::IsInteger, bool IsSigned = NumTraits::IsSigned> +struct signbit_impl; +template +struct signbit_impl { + static constexpr size_t Size = sizeof(Scalar); + static constexpr size_t Shift = (CHAR_BIT * Size) - 1; + using intSize_t = typename get_integer_by_size::signed_type; + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static Scalar run(const Scalar& x) { + intSize_t a = bit_cast(x); + a = a >> Shift; + Scalar result = bit_cast(a); + return result; + } +}; +template +struct signbit_impl { + static constexpr size_t Size = sizeof(Scalar); + static constexpr size_t Shift = (CHAR_BIT * Size) - 1; + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar run(const Scalar& x) { return x >> Shift; } +}; +template +struct signbit_impl { + EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar run(const Scalar&) { return Scalar(0); } +}; +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE static constexpr Scalar signbit(const Scalar& x) { + return signbit_impl::run(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T exp(const T& x) { + EIGEN_USING_STD(exp); + return exp(x); +} + +// MSVC screws up some edge-cases for std::exp(complex). +#ifdef EIGEN_COMP_MSVC +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp(const std::complex& x) { + EIGEN_USING_STD(exp); + // If z is (x,±∞) (for any finite x), the result is (NaN,NaN) and FE_INVALID is raised. + // If z is (x,NaN) (for any finite x), the result is (NaN,NaN) and FE_INVALID may be raised. + if ((isfinite)(real_ref(x)) && !(isfinite)(imag_ref(x))) { + return std::complex(NumTraits::quiet_NaN(), NumTraits::quiet_NaN()); + } + // If z is (+∞,±∞), the result is (±∞,NaN) and FE_INVALID is raised (the sign of the real part is unspecified) + // If z is (+∞,NaN), the result is (±∞,NaN) (the sign of the real part is unspecified) + if ((real_ref(x) == NumTraits::infinity() && !(isfinite)(imag_ref(x)))) { + return std::complex(NumTraits::infinity(), NumTraits::quiet_NaN()); + } + return exp(x); +} +#endif + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(exp, exp) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float exp(const float& x) { + return ::expf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double exp(const double& x) { + return ::exp(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp(const std::complex& x) { + float com = ::expf(x.real()); + float res_real = com * ::cosf(x.imag()); + float res_imag = com * ::sinf(x.imag()); + return std::complex(res_real, res_imag); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp(const std::complex& x) { + double com = ::exp(x.real()); + double res_real = com * ::cos(x.imag()); + double res_imag = com * ::sin(x.imag()); + return std::complex(res_real, res_imag); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T exp2(const T& x) { + EIGEN_USING_STD(exp2); + return exp2(x); +} + +// MSVC screws up some edge-cases for std::exp2(complex). +#ifdef EIGEN_COMP_MSVC +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp2(const std::complex& x) { + EIGEN_USING_STD(exp); + // If z is (x,±∞) (for any finite x), the result is (NaN,NaN) and FE_INVALID is raised. + // If z is (x,NaN) (for any finite x), the result is (NaN,NaN) and FE_INVALID may be raised. + if ((isfinite)(real_ref(x)) && !(isfinite)(imag_ref(x))) { + return std::complex(NumTraits::quiet_NaN(), NumTraits::quiet_NaN()); + } + // If z is (+∞,±∞), the result is (±∞,NaN) and FE_INVALID is raised (the sign of the real part is unspecified) + // If z is (+∞,NaN), the result is (±∞,NaN) (the sign of the real part is unspecified) + if ((real_ref(x) == NumTraits::infinity() && !(isfinite)(imag_ref(x)))) { + return std::complex(NumTraits::infinity(), NumTraits::quiet_NaN()); + } + return exp2(x); +} +#endif + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(exp2, exp2) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float exp2(const float& x) { + return ::exp2f(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double exp2(const double& x) { + return ::exp2(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp2(const std::complex& x) { + float com = ::exp2f(x.real()); + float res_real = com * ::cosf(static_cast(EIGEN_LN2) * x.imag()); + float res_imag = com * ::sinf(static_cast(EIGEN_LN2) * x.imag()); + return std::complex(res_real, res_imag); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE std::complex exp2(const std::complex& x) { + double com = ::exp2(x.real()); + double res_real = com * ::cos(static_cast(EIGEN_LN2) * x.imag()); + double res_imag = com * ::sin(static_cast(EIGEN_LN2) * x.imag()); + return std::complex(res_real, res_imag); +} +#endif + +template +EIGEN_DEVICE_FUNC inline EIGEN_MATHFUNC_RETVAL(expm1, Scalar) expm1(const Scalar& x) { + return EIGEN_MATHFUNC_IMPL(expm1, Scalar)::run(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(expm1, expm1) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float expm1(const float& x) { + return ::expm1f(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double expm1(const double& x) { + return ::expm1(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T cos(const T& x) { + EIGEN_USING_STD(cos); + return cos(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(cos, cos) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float cos(const float& x) { + return ::cosf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double cos(const double& x) { + return ::cos(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T sin(const T& x) { + EIGEN_USING_STD(sin); + return sin(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sin, sin) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float sin(const float& x) { + return ::sinf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double sin(const double& x) { + return ::sin(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T tan(const T& x) { + EIGEN_USING_STD(tan); + return tan(x); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(tan, tan) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tan(const float& x) { + return ::tanf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double tan(const double& x) { + return ::tan(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T acos(const T& x) { + EIGEN_USING_STD(acos); + return acos(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T acosh(const T& x) { + EIGEN_USING_STD(acosh); + return static_cast(acosh(x)); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(acos, acos) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(acosh, acosh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float acos(const float& x) { + return ::acosf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double acos(const double& x) { + return ::acos(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T asin(const T& x) { + EIGEN_USING_STD(asin); + return asin(x); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T asinh(const T& x) { + EIGEN_USING_STD(asinh); + return static_cast(asinh(x)); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(asin, asin) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(asinh, asinh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float asin(const float& x) { + return ::asinf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double asin(const double& x) { + return ::asin(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T atan(const T& x) { + EIGEN_USING_STD(atan); + return static_cast(atan(x)); +} + +template ::IsComplex, int> = 0> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T atan2(const T& y, const T& x) { + EIGEN_USING_STD(atan2); + return static_cast(atan2(y, x)); +} + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T atanh(const T& x) { + EIGEN_USING_STD(atanh); + return static_cast(atanh(x)); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(atan, atan) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(atanh, atanh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float atan(const float& x) { + return ::atanf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double atan(const double& x) { + return ::atan(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T cosh(const T& x) { + EIGEN_USING_STD(cosh); + return static_cast(cosh(x)); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(cosh, cosh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float cosh(const float& x) { + return ::coshf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double cosh(const double& x) { + return ::cosh(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T sinh(const T& x) { + EIGEN_USING_STD(sinh); + return static_cast(sinh(x)); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(sinh, sinh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float sinh(const float& x) { + return ::sinhf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double sinh(const double& x) { + return ::sinh(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T tanh(const T& x) { + EIGEN_USING_STD(tanh); + return tanh(x); +} + +#if (!defined(EIGEN_GPUCC)) && EIGEN_FAST_MATH && !defined(SYCL_DEVICE_ONLY) +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tanh(float x) { return internal::ptanh_float(x); } +#endif + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_UNARY(tanh, tanh) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float tanh(const float& x) { + return ::tanhf(x); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double tanh(const double& x) { + return ::tanh(x); +} +#endif + +template +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE T fmod(const T& a, const T& b) { + EIGEN_USING_STD(fmod); + return fmod(a, b); +} + +#if defined(SYCL_DEVICE_ONLY) +SYCL_SPECIALIZE_FLOATING_TYPES_BINARY(fmod, fmod) +#endif + +#if defined(EIGEN_GPUCC) +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE float fmod(const float& a, const float& b) { + return ::fmodf(a, b); +} + +template <> +EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE double fmod(const double& a, const double& b) { + return ::fmod(a, b); +} +#endif + +#if defined(SYCL_DEVICE_ONLY) +#undef SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_BINARY +#undef SYCL_SPECIALIZE_SIGNED_INTEGER_TYPES_UNARY +#undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_BINARY +#undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY +#undef SYCL_SPECIALIZE_INTEGER_TYPES_BINARY +#undef SYCL_SPECIALIZE_UNSIGNED_INTEGER_TYPES_UNARY +#undef SYCL_SPECIALIZE_FLOATING_TYPES_BINARY +#undef SYCL_SPECIALIZE_FLOATING_TYPES_UNARY +#undef SYCL_SPECIALIZE_FLOATING_TYPES_UNARY_FUNC_RET_TYPE +#undef SYCL_SPECIALIZE_GEN_UNARY_FUNC +#undef SYCL_SPECIALIZE_UNARY_FUNC +#undef SYCL_SPECIALIZE_GEN1_BINARY_FUNC +#undef SYCL_SPECIALIZE_GEN2_BINARY_FUNC +#undef SYCL_SPECIALIZE_BINARY_FUNC +#endif + +template ::value>> +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar logical_shift_left(const Scalar& a, int n) { + return a << n; +} + +template ::value>> +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar logical_shift_right(const Scalar& a, int n) { + using UnsignedScalar = typename numext::get_integer_by_size::unsigned_type; + return bit_cast(bit_cast(a) >> n); +} + +template ::value>> +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar arithmetic_shift_right(const Scalar& a, int n) { + using SignedScalar = typename numext::get_integer_by_size::signed_type; + return bit_cast(bit_cast(a) >> n); +} + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar fma(const Scalar& x, const Scalar& y, const Scalar& z) { + return internal::fma_impl::run(x, y, z); +} + +// Multiply-add. +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar madd(const Scalar& x, const Scalar& y, const Scalar& z) { + return internal::madd_impl::run(x, y, z); +} + +} // end namespace numext + +namespace internal { + +template +EIGEN_DEVICE_FUNC bool isfinite_impl(const std::complex& x) { + return (numext::isfinite)(numext::real(x)) && (numext::isfinite)(numext::imag(x)); +} + +template +EIGEN_DEVICE_FUNC bool isnan_impl(const std::complex& x) { + return (numext::isnan)(numext::real(x)) || (numext::isnan)(numext::imag(x)); +} + +template +EIGEN_DEVICE_FUNC bool isinf_impl(const std::complex& x) { + return ((numext::isinf)(numext::real(x)) || (numext::isinf)(numext::imag(x))) && (!(numext::isnan)(x)); +} + +/**************************************************************************** + * Implementation of fuzzy comparisons * + ****************************************************************************/ + +template +struct scalar_fuzzy_default_impl {}; + +template +struct scalar_fuzzy_default_impl { + typedef typename NumTraits::Real RealScalar; + template + EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, + const RealScalar& prec) { + return numext::abs(x) <= numext::abs(y) * prec; + } + EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) { + return numext::abs(x - y) <= numext::mini(numext::abs(x), numext::abs(y)) * prec; + } + EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar& prec) { + return x <= y || isApprox(x, y, prec); + } +}; + +template +struct scalar_fuzzy_default_impl { + typedef typename NumTraits::Real RealScalar; + template + EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const Scalar& x, const Scalar&, const RealScalar&) { + return x == Scalar(0); + } + EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar&) { return x == y; } + EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, const RealScalar&) { + return x <= y; + } +}; + +template +struct scalar_fuzzy_default_impl { + typedef typename NumTraits::Real RealScalar; + template + EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const Scalar& x, const OtherScalar& y, + const RealScalar& prec) { + return numext::abs2(x) <= numext::abs2(y) * prec * prec; + } + EIGEN_DEVICE_FUNC static inline bool isApprox(const Scalar& x, const Scalar& y, const RealScalar& prec) { + return numext::abs2(x - y) <= numext::mini(numext::abs2(x), numext::abs2(y)) * prec * prec; + } +}; + +template +struct scalar_fuzzy_impl + : scalar_fuzzy_default_impl::IsComplex, NumTraits::IsInteger> {}; + +template +EIGEN_DEVICE_FUNC inline bool isMuchSmallerThan( + const Scalar& x, const OtherScalar& y, + const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { + return scalar_fuzzy_impl::template isMuchSmallerThan(x, y, precision); +} + +template +EIGEN_DEVICE_FUNC inline bool isApprox( + const Scalar& x, const Scalar& y, + const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { return scalar_fuzzy_impl::isApprox(x, y, precision); } -template -inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, - typename NumTraits::Real precision = NumTraits::dummy_precision()) -{ +template +EIGEN_DEVICE_FUNC inline bool isApproxOrLessThan( + const Scalar& x, const Scalar& y, + const typename NumTraits::Real& precision = NumTraits::dummy_precision()) { return scalar_fuzzy_impl::isApproxOrLessThan(x, y, precision); } @@ -730,39 +2034,70 @@ inline bool isApproxOrLessThan(const Scalar& x, const Scalar& y, *** The special case of the bool type *** ******************************************/ -template<> struct random_impl -{ - static inline bool run() - { - return random(0,1)==0 ? false : true; - } -}; - -template<> struct scalar_fuzzy_impl -{ +template <> +struct scalar_fuzzy_impl { typedef bool RealScalar; - - template - static inline bool isMuchSmallerThan(const bool& x, const bool&, const bool&) - { + + template + EIGEN_DEVICE_FUNC static inline bool isMuchSmallerThan(const bool& x, const bool&, const bool&) { return !x; } - - static inline bool isApprox(bool x, bool y, bool) - { - return x == y; - } - static inline bool isApproxOrLessThan(const bool& x, const bool& y, const bool&) - { + EIGEN_DEVICE_FUNC static inline bool isApprox(bool x, bool y, bool) { return x == y; } + + EIGEN_DEVICE_FUNC static inline bool isApproxOrLessThan(const bool& x, const bool& y, const bool&) { return (!x) || y; } - }; - -} // end namespace internal +} // end namespace internal + +// Default implementations that rely on other numext implementations +namespace internal { + +// Specialization for complex types that are not supported by std::expm1. +template +struct expm1_impl> { + EIGEN_STATIC_ASSERT_NON_INTEGER(RealScalar) + + EIGEN_DEVICE_FUNC static inline std::complex run(const std::complex& x) { + RealScalar xr = x.real(); + RealScalar xi = x.imag(); + // expm1(z) = exp(z) - 1 + // = exp(x + i * y) - 1 + // = exp(x) * (cos(y) + i * sin(y)) - 1 + // = exp(x) * cos(y) - 1 + i * exp(x) * sin(y) + // Imag(expm1(z)) = exp(x) * sin(y) + // Real(expm1(z)) = exp(x) * cos(y) - 1 + // = exp(x) * cos(y) - 1. + // = expm1(x) + exp(x) * (cos(y) - 1) + // = expm1(x) + exp(x) * (2 * sin(y / 2) ** 2) + RealScalar erm1 = numext::expm1(xr); + RealScalar er = erm1 + RealScalar(1.); + RealScalar sin2 = numext::sin(xi / RealScalar(2.)); + sin2 = sin2 * sin2; + RealScalar s = numext::sin(xi); + RealScalar real_part = erm1 - RealScalar(2.) * er * sin2; + return std::complex(real_part, er * s); + } +}; + +template +struct rsqrt_impl { + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE T run(const T& x) { return T(1) / numext::sqrt(x); } +}; + +#if defined(EIGEN_GPU_COMPILE_PHASE) +template +struct conj_impl, true> { + EIGEN_DEVICE_FUNC static inline std::complex run(const std::complex& x) { + return std::complex(numext::real(x), -numext::imag(x)); + } +}; +#endif + +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_MATHFUNCTIONS_H +#endif // EIGEN_MATHFUNCTIONS_H diff --git a/inst/include/Eigen/src/Core/MathFunctionsImpl.h b/inst/include/Eigen/src/Core/MathFunctionsImpl.h new file mode 100644 index 00000000..c4b5da3c --- /dev/null +++ b/inst/include/Eigen/src/Core/MathFunctionsImpl.h @@ -0,0 +1,263 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2014 Pedro Gonnet (pedro.gonnet@gmail.com) +// Copyright (C) 2016 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_MATHFUNCTIONSIMPL_H +#define EIGEN_MATHFUNCTIONSIMPL_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +/** \internal Fast reciprocal using Newton-Raphson's method. + + Preconditions: + 1. The starting guess provided in approx_a_recip must have at least half + the leading mantissa bits in the correct result, such that a single + Newton-Raphson step is sufficient to get within 1-2 ulps of the correct + result. + 2. If a is zero, approx_a_recip must be infinite with the same sign as a. + 3. If a is infinite, approx_a_recip must be zero with the same sign as a. + + If the preconditions are satisfied, which they are for the _*_rcp_ps + instructions on x86, the result has a maximum relative error of 2 ulps, + and correctly handles reciprocals of zero, infinity, and NaN. +*/ +template +struct generic_reciprocal_newton_step { + static_assert(Steps > 0, "Steps must be at least 1."); + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet run(const Packet& a, const Packet& approx_a_recip) { + using Scalar = typename unpacket_traits::type; + const Packet two = pset1(Scalar(2)); + // Refine the approximation using one Newton-Raphson step: + // x_{i} = x_{i-1} * (2 - a * x_{i-1}) + const Packet x = generic_reciprocal_newton_step::run(a, approx_a_recip); + const Packet tmp = pnmadd(a, x, two); + // If tmp is NaN, it means that a is either +/-0 or +/-Inf. + // In this case return the approximation directly. + const Packet is_not_nan = pcmp_eq(tmp, tmp); + return pselect(is_not_nan, pmul(x, tmp), x); + } +}; + +template +struct generic_reciprocal_newton_step { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet run(const Packet& /*unused*/, const Packet& approx_rsqrt) { + return approx_rsqrt; + } +}; + +/** \internal Fast reciprocal sqrt using Newton-Raphson's method. + + Preconditions: + 1. The starting guess provided in approx_a_recip must have at least half + the leading mantissa bits in the correct result, such that a single + Newton-Raphson step is sufficient to get within 1-2 ulps of the correct + result. + 2. If a is zero, approx_a_recip must be infinite with the same sign as a. + 3. If a is infinite, approx_a_recip must be zero with the same sign as a. + + If the preconditions are satisfied, which they are for the _*_rcp_ps + instructions on x86, the result has a maximum relative error of 2 ulps, + and correctly handles zero, infinity, and NaN. Positive denormals are + treated as zero. +*/ +template +struct generic_rsqrt_newton_step { + static_assert(Steps > 0, "Steps must be at least 1."); + using Scalar = typename unpacket_traits::type; + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet run(const Packet& a, const Packet& approx_rsqrt) { + const Scalar kMinusHalf = Scalar(-1) / Scalar(2); + const Packet cst_minus_half = pset1(kMinusHalf); + const Packet cst_minus_one = pset1(Scalar(-1)); + + Packet inv_sqrt = approx_rsqrt; + for (int step = 0; step < Steps; ++step) { + // Refine the approximation using one Newton-Raphson step: + // h_n = (x * inv_sqrt) * inv_sqrt - 1 (so that h_n is nearly 0). + // inv_sqrt = inv_sqrt - 0.5 * inv_sqrt * h_n + Packet r2 = pmul(a, inv_sqrt); + Packet half_r = pmul(inv_sqrt, cst_minus_half); + Packet h_n = pmadd(r2, inv_sqrt, cst_minus_one); + inv_sqrt = pmadd(half_r, h_n, inv_sqrt); + } + + // If x is NaN, then either: + // 1) the input is NaN + // 2) zero and infinity were multiplied + // In either of these cases, return approx_rsqrt + return pselect(pisnan(inv_sqrt), approx_rsqrt, inv_sqrt); + } +}; + +template +struct generic_rsqrt_newton_step { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet run(const Packet& /*unused*/, const Packet& approx_rsqrt) { + return approx_rsqrt; + } +}; + +/** \internal Fast sqrt using Newton-Raphson's method. + + Preconditions: + 1. The starting guess for the reciprocal sqrt provided in approx_rsqrt must + have at least half the leading mantissa bits in the correct result, such + that a single Newton-Raphson step is sufficient to get within 1-2 ulps of + the correct result. + 2. If a is zero, approx_rsqrt must be infinite. + 3. If a is infinite, approx_rsqrt must be zero. + + If the preconditions are satisfied, which they are for the _*_rsqrt_ps + instructions on x86, the result has a maximum relative error of 2 ulps, + and correctly handles zero and infinity, and NaN. Positive denormal inputs + are treated as zero. +*/ +template +struct generic_sqrt_newton_step { + static_assert(Steps > 0, "Steps must be at least 1."); + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Packet run(const Packet& a, const Packet& approx_rsqrt) { + using Scalar = typename unpacket_traits::type; + const Packet one_point_five = pset1(Scalar(1.5)); + const Packet minus_half = pset1(Scalar(-0.5)); + // If a is inf or zero, return a directly. + const Packet inf_mask = pcmp_eq(a, pset1(NumTraits::infinity())); + const Packet return_a = por(pcmp_eq(a, pzero(a)), inf_mask); + // Do a single step of Newton's iteration for reciprocal square root: + // x_{n+1} = x_n * (1.5 + (-0.5 * x_n) * (a * x_n))). + // The Newton's step is computed this way to avoid over/under-flows. + Packet rsqrt = pmul(approx_rsqrt, pmadd(pmul(minus_half, approx_rsqrt), pmul(a, approx_rsqrt), one_point_five)); + for (int step = 1; step < Steps; ++step) { + rsqrt = pmul(rsqrt, pmadd(pmul(minus_half, rsqrt), pmul(a, rsqrt), one_point_five)); + } + + // Return sqrt(x) = x * rsqrt(x) for non-zero finite positive arguments. + // Return a itself for 0 or +inf, NaN for negative arguments. + return pselect(return_a, a, pmul(a, rsqrt)); + } +}; + +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE RealScalar positive_real_hypot(const RealScalar& x, const RealScalar& y) { + // IEEE IEC 6059 special cases. + if ((numext::isinf)(x) || (numext::isinf)(y)) return NumTraits::infinity(); + if ((numext::isnan)(x) || (numext::isnan)(y)) return NumTraits::quiet_NaN(); + + EIGEN_USING_STD(sqrt); + RealScalar p, qp; + p = numext::maxi(x, y); + if (numext::is_exactly_zero(p)) return RealScalar(0); + qp = numext::mini(y, x) / p; + return p * sqrt(RealScalar(1) + qp * qp); +} + +template +struct hypot_impl { + typedef typename NumTraits::Real RealScalar; + static EIGEN_DEVICE_FUNC inline RealScalar run(const Scalar& x, const Scalar& y) { + EIGEN_USING_STD(abs); + return positive_real_hypot(abs(x), abs(y)); + } +}; + +// Generic complex sqrt implementation that correctly handles corner cases +// according to https://en.cppreference.com/w/cpp/numeric/complex/sqrt +template +EIGEN_DEVICE_FUNC ComplexT complex_sqrt(const ComplexT& z) { + // Computes the principal sqrt of the input. + // + // For a complex square root of the number x + i*y. We want to find real + // numbers u and v such that + // (u + i*v)^2 = x + i*y <=> + // u^2 - v^2 + i*2*u*v = x + i*v. + // By equating the real and imaginary parts we get: + // u^2 - v^2 = x + // 2*u*v = y. + // + // For x >= 0, this has the numerically stable solution + // u = sqrt(0.5 * (x + sqrt(x^2 + y^2))) + // v = y / (2 * u) + // and for x < 0, + // v = sign(y) * sqrt(0.5 * (-x + sqrt(x^2 + y^2))) + // u = y / (2 * v) + // + // Letting w = sqrt(0.5 * (|x| + |z|)), + // if x == 0: u = w, v = sign(y) * w + // if x > 0: u = w, v = y / (2 * w) + // if x < 0: u = |y| / (2 * w), v = sign(y) * w + using T = typename NumTraits::Real; + const T x = numext::real(z); + const T y = numext::imag(z); + const T zero = T(0); + const T w = numext::sqrt(T(0.5) * (numext::abs(x) + numext::hypot(x, y))); + + return (numext::isinf)(y) ? ComplexT(NumTraits::infinity(), y) + : numext::is_exactly_zero(x) ? ComplexT(w, y < zero ? -w : w) + : x > zero ? ComplexT(w, y / (2 * w)) + : ComplexT(numext::abs(y) / (2 * w), y < zero ? -w : w); +} + +// Generic complex rsqrt implementation. +template +EIGEN_DEVICE_FUNC ComplexT complex_rsqrt(const ComplexT& z) { + // Computes the principal reciprocal sqrt of the input. + // + // For a complex reciprocal square root of the number z = x + i*y. We want to + // find real numbers u and v such that + // (u + i*v)^2 = 1 / (x + i*y) <=> + // u^2 - v^2 + i*2*u*v = x/|z|^2 - i*v/|z|^2. + // By equating the real and imaginary parts we get: + // u^2 - v^2 = x/|z|^2 + // 2*u*v = y/|z|^2. + // + // For x >= 0, this has the numerically stable solution + // u = sqrt(0.5 * (x + |z|)) / |z| + // v = -y / (2 * u * |z|) + // and for x < 0, + // v = -sign(y) * sqrt(0.5 * (-x + |z|)) / |z| + // u = -y / (2 * v * |z|) + // + // Letting w = sqrt(0.5 * (|x| + |z|)), + // if x == 0: u = w / |z|, v = -sign(y) * w / |z| + // if x > 0: u = w / |z|, v = -y / (2 * w * |z|) + // if x < 0: u = |y| / (2 * w * |z|), v = -sign(y) * w / |z| + using T = typename NumTraits::Real; + const T x = numext::real(z); + const T y = numext::imag(z); + const T zero = T(0); + + const T abs_z = numext::hypot(x, y); + const T w = numext::sqrt(T(0.5) * (numext::abs(x) + abs_z)); + const T woz = w / abs_z; + // Corner cases consistent with 1/sqrt(z) on gcc/clang. + return numext::is_exactly_zero(abs_z) ? ComplexT(NumTraits::infinity(), NumTraits::quiet_NaN()) + : ((numext::isinf)(x) || (numext::isinf)(y)) ? ComplexT(zero, zero) + : numext::is_exactly_zero(x) ? ComplexT(woz, y < zero ? woz : -woz) + : x > zero ? ComplexT(woz, -y / (2 * w * abs_z)) + : ComplexT(numext::abs(y) / (2 * w * abs_z), y < zero ? woz : -woz); +} + +template +EIGEN_DEVICE_FUNC ComplexT complex_log(const ComplexT& z) { + // Computes complex log. + using T = typename NumTraits::Real; + T a = numext::abs(z); + EIGEN_USING_STD(atan2); + T b = atan2(z.imag(), z.real()); + return ComplexT(numext::log(a), b); +} + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_MATHFUNCTIONSIMPL_H diff --git a/inst/include/Eigen/src/Core/Matrix.h b/inst/include/Eigen/src/Core/Matrix.h index 02be142d..a2c8eba5 100644 --- a/inst/include/Eigen/src/Core/Matrix.h +++ b/inst/include/Eigen/src/Core/Matrix.h @@ -11,410 +11,524 @@ #ifndef EIGEN_MATRIX_H #define EIGEN_MATRIX_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class Matrix - * \ingroup Core_Module - * - * \brief The matrix class, also used for vectors and row-vectors - * - * The %Matrix class is the work-horse for all \em dense (\ref dense "note") matrices and vectors within Eigen. - * Vectors are matrices with one column, and row-vectors are matrices with one row. - * - * The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note"). - * - * The first three template parameters are required: - * \tparam _Scalar \anchor matrix_tparam_scalar Numeric type, e.g. float, double, int or std::complex. - * User defined sclar types are supported as well (see \ref user_defined_scalars "here"). - * \tparam _Rows Number of rows, or \b Dynamic - * \tparam _Cols Number of columns, or \b Dynamic - * - * The remaining template parameters are optional -- in most cases you don't have to worry about them. - * \tparam _Options \anchor matrix_tparam_options A combination of either \b #RowMajor or \b #ColMajor, and of either - * \b #AutoAlign or \b #DontAlign. - * The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter controls alignment, which is required - * for vectorization. It defaults to aligning matrices except for fixed sizes that aren't a multiple of the packet size. - * \tparam _MaxRows Maximum number of rows. Defaults to \a _Rows (\ref maxrows "note"). - * \tparam _MaxCols Maximum number of columns. Defaults to \a _Cols (\ref maxrows "note"). - * - * Eigen provides a number of typedefs covering the usual cases. Here are some examples: - * - * \li \c Matrix2d is a 2x2 square matrix of doubles (\c Matrix) - * \li \c Vector4f is a vector of 4 floats (\c Matrix) - * \li \c RowVector3i is a row-vector of 3 ints (\c Matrix) - * - * \li \c MatrixXf is a dynamic-size matrix of floats (\c Matrix) - * \li \c VectorXf is a dynamic-size vector of floats (\c Matrix) - * - * \li \c Matrix2Xf is a partially fixed-size (dynamic-size) matrix of floats (\c Matrix) - * \li \c MatrixX3d is a partially dynamic-size (fixed-size) matrix of double (\c Matrix) - * - * See \link matrixtypedefs this page \endlink for a complete list of predefined \em %Matrix and \em Vector typedefs. - * - * You can access elements of vectors and matrices using normal subscripting: - * - * \code - * Eigen::VectorXd v(10); - * v[0] = 0.1; - * v[1] = 0.2; - * v(0) = 0.3; - * v(1) = 0.4; - * - * Eigen::MatrixXi m(10, 10); - * m(0, 1) = 1; - * m(0, 2) = 2; - * m(0, 3) = 3; - * \endcode - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_MATRIX_PLUGIN. - * - * Some notes: - * - *
- *
\anchor dense Dense versus sparse:
- *
This %Matrix class handles dense, not sparse matrices and vectors. For sparse matrices and vectors, see the Sparse module. - * - * Dense matrices and vectors are plain usual arrays of coefficients. All the coefficients are stored, in an ordinary contiguous array. - * This is unlike Sparse matrices and vectors where the coefficients are stored as a list of nonzero coefficients.
- * - *
\anchor fixedsize Fixed-size versus dynamic-size:
- *
Fixed-size means that the numbers of rows and columns are known are compile-time. In this case, Eigen allocates the array - * of coefficients as a fixed-size array, as a class member. This makes sense for very small matrices, typically up to 4x4, sometimes up - * to 16x16. Larger matrices should be declared as dynamic-size even if one happens to know their size at compile-time. - * - * Dynamic-size means that the numbers of rows or columns are not necessarily known at compile-time. In this case they are runtime - * variables, and the array of coefficients is allocated dynamically on the heap. - * - * Note that \em dense matrices, be they Fixed-size or Dynamic-size, do not expand dynamically in the sense of a std::map. - * If you want this behavior, see the Sparse module.
- * - *
\anchor maxrows _MaxRows and _MaxCols:
- *
In most cases, one just leaves these parameters to the default values. - * These parameters mean the maximum size of rows and columns that the matrix may have. They are useful in cases - * when the exact numbers of rows and columns are not known are compile-time, but it is known at compile-time that they cannot - * exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case _MaxRows and _MaxCols - * are the dimensions of the original matrix, while _Rows and _Cols are Dynamic.
- *
- * - * \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy, - * \ref TopicStorageOrders - */ +namespace Eigen { namespace internal { -template -struct traits > -{ - typedef _Scalar Scalar; +template +struct traits> { + private: + constexpr static int size = internal::size_at_compile_time(Rows_, Cols_); + typedef typename find_best_packet::type PacketScalar; + enum { + row_major_bit = Options_ & RowMajor ? RowMajorBit : 0, + is_dynamic_size_storage = MaxRows_ == Dynamic || MaxCols_ == Dynamic, + max_size = is_dynamic_size_storage ? Dynamic : MaxRows_ * MaxCols_, + default_alignment = compute_default_alignment::value, + actual_alignment = ((Options_ & DontAlign) == 0) ? default_alignment : 0, + required_alignment = unpacket_traits::alignment, + packet_access_bit = (packet_traits::Vectorizable && + (EIGEN_UNALIGNED_VECTORIZE || (int(actual_alignment) >= int(required_alignment)))) + ? PacketAccessBit + : 0 + }; + + public: + typedef Scalar_ Scalar; typedef Dense StorageKind; - typedef DenseIndex Index; + typedef Eigen::Index StorageIndex; typedef MatrixXpr XprKind; enum { - RowsAtCompileTime = _Rows, - ColsAtCompileTime = _Cols, - MaxRowsAtCompileTime = _MaxRows, - MaxColsAtCompileTime = _MaxCols, - Flags = compute_matrix_flags<_Scalar, _Rows, _Cols, _Options, _MaxRows, _MaxCols>::ret, - CoeffReadCost = NumTraits::ReadCost, - Options = _Options, + RowsAtCompileTime = Rows_, + ColsAtCompileTime = Cols_, + MaxRowsAtCompileTime = MaxRows_, + MaxColsAtCompileTime = MaxCols_, + Flags = compute_matrix_flags(Options_), + Options = Options_, InnerStrideAtCompileTime = 1, - OuterStrideAtCompileTime = (Options&RowMajor) ? ColsAtCompileTime : RowsAtCompileTime + OuterStrideAtCompileTime = (int(Options) & int(RowMajor)) ? ColsAtCompileTime : RowsAtCompileTime, + + // FIXME, the following flag in only used to define NeedsToAlign in PlainObjectBase + EvaluatorFlags = LinearAccessBit | DirectAccessBit | packet_access_bit | row_major_bit, + Alignment = actual_alignment }; }; -} - -template -class Matrix - : public PlainObjectBase > -{ - public: - - /** \brief Base class typedef. - * \sa PlainObjectBase - */ - typedef PlainObjectBase Base; - - enum { Options = _Options }; - - EIGEN_DENSE_PUBLIC_INTERFACE(Matrix) - - typedef typename Base::PlainObject PlainObject; - - using Base::base; - using Base::coeffRef; - - /** - * \brief Assigns matrices to each other. - * - * \note This is a special case of the templated operator=. Its purpose is - * to prevent a default operator= from hiding the templated operator=. - * - * \callgraph - */ - EIGEN_STRONG_INLINE Matrix& operator=(const Matrix& other) - { - return Base::_set(other); - } - - /** \internal - * \brief Copies the value of the expression \a other into \c *this with automatic resizing. - * - * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), - * it will be initialized. - * - * Note that copying a row-vector into a vector (and conversely) is allowed. - * The resizing, if any, is then done in the appropriate way so that row-vectors - * remain row-vectors and vectors remain vectors. - */ - template - EIGEN_STRONG_INLINE Matrix& operator=(const MatrixBase& other) - { - return Base::_set(other); - } - - /* Here, doxygen failed to copy the brief information when using \copydoc */ - - /** - * \brief Copies the generic expression \a other into *this. - * \copydetails DenseBase::operator=(const EigenBase &other) - */ - template - EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase &other) - { - return Base::operator=(other); - } - - template - EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue& func) - { - return Base::operator=(func); - } - - /** \brief Default constructor. - * - * For fixed-size matrices, does nothing. - * - * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix - * is called a null matrix. This constructor is the unique way to create null matrices: resizing - * a matrix to 0 is not supported. - * - * \sa resize(Index,Index) - */ - EIGEN_STRONG_INLINE Matrix() : Base() - { - Base::_check_template_params(); - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } - - // FIXME is it still needed - Matrix(internal::constructor_without_unaligned_array_assert) - : Base(internal::constructor_without_unaligned_array_assert()) - { Base::_check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED } - -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - Matrix(Matrix&& other) - : Base(std::move(other)) - { - Base::_check_template_params(); - if (RowsAtCompileTime!=Dynamic && ColsAtCompileTime!=Dynamic) - Base::_set_noalias(other); - } - Matrix& operator=(Matrix&& other) - { - other.swap(*this); - return *this; - } +} // namespace internal + +/** \class Matrix + * \ingroup Core_Module + * + * \brief The matrix class, also used for vectors and row-vectors + * + * The %Matrix class is the work-horse for all \em dense (\ref dense "note") matrices and vectors within Eigen. + * Vectors are matrices with one column, and row-vectors are matrices with one row. + * + * The %Matrix class encompasses \em both fixed-size and dynamic-size objects (\ref fixedsize "note"). + * + * The first three template parameters are required: + * \tparam Scalar_ Numeric type, e.g. float, double, int or std::complex. + * User defined scalar types are supported as well (see \ref user_defined_scalars "here"). + * \tparam Rows_ Number of rows, or \b Dynamic + * \tparam Cols_ Number of columns, or \b Dynamic + * + * The remaining template parameters are optional -- in most cases you don't have to worry about them. + * \tparam Options_ A combination of either \b #RowMajor or \b #ColMajor, and of either + * \b #AutoAlign or \b #DontAlign. + * The former controls \ref TopicStorageOrders "storage order", and defaults to column-major. The latter + * controls alignment, which is required for vectorization. It defaults to aligning matrices except for fixed sizes that + * aren't a multiple of the packet size. \tparam MaxRows_ Maximum number of rows. Defaults to \a Rows_ (\ref maxrows + * "note"). \tparam MaxCols_ Maximum number of columns. Defaults to \a Cols_ (\ref maxrows "note"). + * + * Eigen provides a number of typedefs covering the usual cases. Here are some examples: + * + * \li \c Matrix2d is a 2x2 square matrix of doubles (\c Matrix) + * \li \c Vector4f is a vector of 4 floats (\c Matrix) + * \li \c RowVector3i is a row-vector of 3 ints (\c Matrix) + * + * \li \c MatrixXf is a dynamic-size matrix of floats (\c Matrix) + * \li \c VectorXf is a dynamic-size vector of floats (\c Matrix) + * + * \li \c Matrix2Xf is a partially fixed-size (dynamic-size) matrix of floats (\c Matrix) + * \li \c MatrixX3d is a partially dynamic-size (fixed-size) matrix of double (\c Matrix) + * + * See \link matrixtypedefs this page \endlink for a complete list of predefined \em %Matrix and \em Vector typedefs. + * + * You can access elements of vectors and matrices using normal subscripting: + * + * \code + * Eigen::VectorXd v(10); + * v[0] = 0.1; + * v[1] = 0.2; + * v(0) = 0.3; + * v(1) = 0.4; + * + * Eigen::MatrixXi m(10, 10); + * m(0, 1) = 1; + * m(0, 2) = 2; + * m(0, 3) = 3; + * \endcode + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_MATRIX_PLUGIN. + * + * Some notes: + * + *
+ *
\anchor dense Dense versus sparse:
+ *
This %Matrix class handles dense, not sparse matrices and vectors. For sparse matrices and vectors, see the + * Sparse module. + * + * Dense matrices and vectors are plain usual arrays of coefficients. All the coefficients are stored, in an ordinary + * contiguous array. This is unlike Sparse matrices and vectors where the coefficients are stored as a list of nonzero + * coefficients.
+ * + *
\anchor fixedsize Fixed-size versus dynamic-size:
+ *
Fixed-size means that the numbers of rows and columns are known at compile-time. In this case, Eigen allocates + * the array of coefficients as a fixed-size array, as a class member. This makes sense for very small matrices, + * typically up to 4x4, sometimes up to 16x16. Larger matrices should be declared as dynamic-size even if one happens to + * know their size at compile-time. + * + * Dynamic-size means that the numbers of rows or columns are not necessarily known at compile-time. In this case they + * are runtime variables, and the array of coefficients is allocated dynamically on the heap. + * + * Note that \em dense matrices, be they Fixed-size or Dynamic-size, do not expand dynamically in the sense of + * a std::map. If you want this behavior, see the Sparse module.
+ * + *
\anchor maxrows MaxRows_ and MaxCols_:
+ *
In most cases, one just leaves these parameters to the default values. + * These parameters mean the maximum size of rows and columns that the matrix may have. They are useful in cases + * when the exact numbers of rows and columns are not known at compile-time, but it is known at compile-time that they + * cannot exceed a certain value. This happens when taking dynamic-size blocks inside fixed-size matrices: in this case + * MaxRows_ and MaxCols_ are the dimensions of the original matrix, while Rows_ and Cols_ are Dynamic.
+ *
+ * + * ABI and storage layout + * + * The table below summarizes the ABI of some possible Matrix instances which is fixed thorough the lifetime of Eigen 3. + * + * + * + * + * + * + *
Matrix typeEquivalent C structure
\code Matrix \endcode\code + * struct { + * T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0 + * Eigen::Index rows, cols; + * }; + * \endcode
\code + * Matrix + * Matrix \endcode\code + * struct { + * T *data; // with (size_t(data)%EIGEN_MAX_ALIGN_BYTES)==0 + * Eigen::Index size; + * }; + * \endcode
\code Matrix \endcode\code + * struct { + * T data[Rows*Cols]; // with (size_t(data)%A(Rows*Cols*sizeof(T)))==0 + * }; + * \endcode
\code Matrix \endcode\code + * struct { + * T data[MaxRows*MaxCols]; // with (size_t(data)%A(MaxRows*MaxCols*sizeof(T)))==0 + * Eigen::Index rows, cols; + * }; + * \endcode
+ * Note that in this table Rows, Cols, MaxRows and MaxCols are all positive integers. A(S) is defined to the largest + * possible power-of-two smaller to EIGEN_MAX_STATIC_ALIGN_BYTES. + * + * \see MatrixBase for the majority of the API methods for matrices, \ref TopicClassHierarchy, + * \ref TopicStorageOrders + */ + +template +class Matrix : public PlainObjectBase> { + public: + /** \brief Base class typedef. + * \sa PlainObjectBase + */ + typedef PlainObjectBase Base; + + enum { Options = Options_ }; + + EIGEN_DENSE_PUBLIC_INTERFACE(Matrix) + + typedef typename Base::PlainObject PlainObject; + + using Base::base; + using Base::coeffRef; + + /** + * \brief Assigns matrices to each other. + * + * \note This is a special case of the templated operator=. Its purpose is + * to prevent a default operator= from hiding the templated operator=. + * + * \callgraph + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix& operator=(const Matrix& other) { return Base::_set(other); } + + /** \internal + * \brief Copies the value of the expression \a other into \c *this with automatic resizing. + * + * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), + * it will be initialized. + * + * Note that copying a row-vector into a vector (and conversely) is allowed. + * The resizing, if any, is then done in the appropriate way so that row-vectors + * remain row-vectors and vectors remain vectors. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix& operator=(const DenseBase& other) { + return Base::_set(other); + } + + /** + * \brief Copies the generic expression \a other into *this. + * \copydetails DenseBase::operator=(const EigenBase &other) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix& operator=(const EigenBase& other) { + return Base::operator=(other); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix& operator=(const ReturnByValue& func) { + return Base::operator=(func); + } + + /** \brief Default constructor. + * + * For fixed-size matrices, does nothing. + * + * For dynamic-size matrices, creates an empty matrix of size 0. Does not allocate any array. Such a matrix + * is called a null matrix. This constructor is the unique way to create null matrices: resizing + * a matrix to 0 is not supported. + * + * \sa resize(Index,Index) + */ +#if defined(EIGEN_INITIALIZE_COEFFS) + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix() { EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED } +#else + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix() = default; +#endif + /** \brief Move constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix(Matrix&&) = default; + /** \brief Moves the matrix into the other one. + * + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix& operator=(Matrix&& other) noexcept( + std::is_nothrow_move_assignable::value) { + Base::operator=(std::move(other)); + return *this; + } + + /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients. + * + * \only_for_vectors + * + * This constructor is for 1D array or vectors with more than 4 coefficients. + * + * \warning To construct a column (resp. row) vector of fixed length, the number of values passed to this + * constructor must match the the fixed number of rows (resp. columns) of \c *this. + * + * + * Example: \include Matrix_variadic_ctor_cxx11.cpp + * Output: \verbinclude Matrix_variadic_ctor_cxx11.out + * + * \sa Matrix(const std::initializer_list>&) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, + const ArgTypes&... args) + : Base(a0, a1, a2, a3, args...) {} + + /** \brief Constructs a Matrix and initializes it from the coefficients given as initializer-lists grouped by row. + * \cpp11 + * \anchor matrix_initializer_list + * + * In the general case, the constructor takes a list of rows, each row being represented as a list of coefficients: + * + * Example: \include Matrix_initializer_list_23_cxx11.cpp + * Output: \verbinclude Matrix_initializer_list_23_cxx11.out + * + * Each of the inner initializer lists must contain the exact same number of elements, otherwise an assertion is + * triggered. + * + * In the case of a compile-time column vector, implicit transposition from a single row is allowed. + * Therefore VectorXd{{1,2,3,4,5}} is legal and the more verbose syntax + * RowVectorXd{{1},{2},{3},{4},{5}} can be avoided: + * + * Example: \include Matrix_initializer_list_vector_cxx11.cpp + * Output: \verbinclude Matrix_initializer_list_vector_cxx11.out + * + * In the case of fixed-sized matrices, the initializer list sizes must exactly match the matrix sizes, + * and implicit transposition is allowed for compile-time vectors only. + * + * \sa Matrix(const Scalar& a0, const Scalar& a1, const Scalar& a2, const Scalar& a3, const ArgTypes&... args) + */ + EIGEN_DEVICE_FUNC explicit constexpr EIGEN_STRONG_INLINE Matrix( + const std::initializer_list>& list) + : Base(list) {} + +#ifndef EIGEN_PARSED_BY_DOXYGEN + + // This constructor is for both 1x1 matrices and dynamic vectors + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit Matrix(const T& x) { + Base::template _init1(x); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y) { + Base::template _init2(x, y); + } + +#else + /** \brief Constructs a fixed-sized matrix initialized with coefficients starting at \a data */ + EIGEN_DEVICE_FUNC explicit Matrix(const Scalar* data); + + /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors + * + * This is useful for dynamic-size vectors. For fixed-size vectors, + * it is redundant to pass these parameters, so one should use the default constructor + * Matrix() instead. + * + * \warning This constructor is disabled for fixed-size \c 1x1 matrices. For instance, + * calling Matrix(1) will call the initialization constructor: Matrix(const Scalar&). + * For fixed-size \c 1x1 matrices it is therefore recommended to use the default + * constructor Matrix() instead, especially when using one of the non standard + * \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives). + */ + EIGEN_STRONG_INLINE explicit Matrix(Index dim); + /** \brief Constructs an initialized 1x1 matrix with the given coefficient + * \sa Matrix(const Scalar&, const Scalar&, const Scalar&, const Scalar&, const ArgTypes&...) */ + Matrix(const Scalar& x); + /** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns. + * + * This is useful for dynamic-size matrices. For fixed-size matrices, + * it is redundant to pass these parameters, so one should use the default constructor + * Matrix() instead. + * + * \warning This constructor is disabled for fixed-size \c 1x2 and \c 2x1 vectors. For instance, + * calling Matrix2f(2,1) will call the initialization constructor: Matrix(const Scalar& x, const Scalar& y). + * For fixed-size \c 1x2 or \c 2x1 vectors it is therefore recommended to use the default + * constructor Matrix() instead, especially when using one of the non standard + * \c EIGEN_INITIALIZE_MATRICES_BY_{ZERO,\c NAN} macros (see \ref TopicPreprocessorDirectives). + */ + EIGEN_DEVICE_FUNC Matrix(Index rows, Index cols); + + /** \brief Constructs an initialized 2D vector with given coefficients + * \sa Matrix(const Scalar&, const Scalar&, const Scalar&, const Scalar&, const ArgTypes&...) */ + Matrix(const Scalar& x, const Scalar& y); +#endif // end EIGEN_PARSED_BY_DOXYGEN + + /** \brief Constructs an initialized 3D vector with given coefficients + * \sa Matrix(const Scalar&, const Scalar&, const Scalar&, const Scalar&, const ArgTypes&...) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3) + m_storage.data()[0] = x; + m_storage.data()[1] = y; + m_storage.data()[2] = z; + } + /** \brief Constructs an initialized 4D vector with given coefficients + * \sa Matrix(const Scalar&, const Scalar&, const Scalar&, const Scalar&, const ArgTypes&...) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4) + m_storage.data()[0] = x; + m_storage.data()[1] = y; + m_storage.data()[2] = z; + m_storage.data()[3] = w; + } + + /** \brief Copy constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Matrix(const Matrix&) = default; + + /** \brief Copy constructor for generic expressions. + * \sa MatrixBase::operator=(const EigenBase&) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Matrix(const EigenBase& other) : Base(other.derived()) {} + + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return 1; } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return this->innerSize(); } + + /////////// Geometry module /////////// + + template + EIGEN_DEVICE_FUNC explicit Matrix(const RotationBase& r); + template + EIGEN_DEVICE_FUNC Matrix& operator=(const RotationBase& r); + +// allow to extend Matrix outside Eigen +#ifdef EIGEN_MATRIX_PLUGIN +#include EIGEN_MATRIX_PLUGIN #endif - /** \brief Constructs a vector or row-vector with given dimension. \only_for_vectors - * - * Note that this is only useful for dynamic-size vectors. For fixed-size vectors, - * it is redundant to pass the dimension here, so it makes more sense to use the default - * constructor Matrix() instead. - */ - EIGEN_STRONG_INLINE explicit Matrix(Index dim) - : Base(dim, RowsAtCompileTime == 1 ? 1 : dim, ColsAtCompileTime == 1 ? 1 : dim) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_ONLY(Matrix) - eigen_assert(dim >= 0); - eigen_assert(SizeAtCompileTime == Dynamic || SizeAtCompileTime == dim); - EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - EIGEN_STRONG_INLINE Matrix(const T0& x, const T1& y) - { - Base::_check_template_params(); - Base::template _init2(x, y); - } - #else - /** \brief Constructs an uninitialized matrix with \a rows rows and \a cols columns. - * - * This is useful for dynamic-size matrices. For fixed-size matrices, - * it is redundant to pass these parameters, so one should use the default constructor - * Matrix() instead. */ - Matrix(Index rows, Index cols); - /** \brief Constructs an initialized 2D vector with given coefficients */ - Matrix(const Scalar& x, const Scalar& y); - #endif - - /** \brief Constructs an initialized 3D vector with given coefficients */ - EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 3) - m_storage.data()[0] = x; - m_storage.data()[1] = y; - m_storage.data()[2] = z; - } - /** \brief Constructs an initialized 4D vector with given coefficients */ - EIGEN_STRONG_INLINE Matrix(const Scalar& x, const Scalar& y, const Scalar& z, const Scalar& w) - { - Base::_check_template_params(); - EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(Matrix, 4) - m_storage.data()[0] = x; - m_storage.data()[1] = y; - m_storage.data()[2] = z; - m_storage.data()[3] = w; - } - - explicit Matrix(const Scalar *data); - - /** \brief Constructor copying the value of the expression \a other */ - template - EIGEN_STRONG_INLINE Matrix(const MatrixBase& other) - : Base(other.rows() * other.cols(), other.rows(), other.cols()) - { - // This test resides here, to bring the error messages closer to the user. Normally, these checks - // are performed deeply within the library, thus causing long and scary error traces. - EIGEN_STATIC_ASSERT((internal::is_same::value), - YOU_MIXED_DIFFERENT_NUMERIC_TYPES__YOU_NEED_TO_USE_THE_CAST_METHOD_OF_MATRIXBASE_TO_CAST_NUMERIC_TYPES_EXPLICITLY) - - Base::_check_template_params(); - Base::_set_noalias(other); - } - /** \brief Copy constructor */ - EIGEN_STRONG_INLINE Matrix(const Matrix& other) - : Base(other.rows() * other.cols(), other.rows(), other.cols()) - { - Base::_check_template_params(); - Base::_set_noalias(other); - } - /** \brief Copy constructor with in-place evaluation */ - template - EIGEN_STRONG_INLINE Matrix(const ReturnByValue& other) - { - Base::_check_template_params(); - Base::resize(other.rows(), other.cols()); - other.evalTo(*this); - } - - /** \brief Copy constructor for generic expressions. - * \sa MatrixBase::operator=(const EigenBase&) - */ - template - EIGEN_STRONG_INLINE Matrix(const EigenBase &other) - : Base(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols()) - { - Base::_check_template_params(); - Base::_resize_to_match(other); - // FIXME/CHECK: isn't *this = other.derived() more efficient. it allows to - // go for pure _set() implementations, right? - *this = other; - } - - /** \internal - * \brief Override MatrixBase::swap() since for dynamic-sized matrices - * of same type it is enough to swap the data pointers. - */ - template - void swap(MatrixBase const & other) - { this->_swap(other.derived()); } - - inline Index innerStride() const { return 1; } - inline Index outerStride() const { return this->innerSize(); } - - /////////// Geometry module /////////// - - template - explicit Matrix(const RotationBase& r); - template - Matrix& operator=(const RotationBase& r); - - #ifdef EIGEN2_SUPPORT - template - explicit Matrix(const eigen2_RotationBase& r); - template - Matrix& operator=(const eigen2_RotationBase& r); - #endif - - // allow to extend Matrix outside Eigen - #ifdef EIGEN_MATRIX_PLUGIN - #include EIGEN_MATRIX_PLUGIN - #endif - - protected: - template - friend struct internal::conservative_resize_like_impl; - - using Base::m_storage; + protected: + template + friend struct internal::conservative_resize_like_impl; + + using Base::m_storage; }; /** \defgroup matrixtypedefs Global matrix typedefs - * - * \ingroup Core_Module - * - * Eigen defines several typedef shortcuts for most common matrix and vector types. - * - * The general patterns are the following: - * - * \c MatrixSizeType where \c Size can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size, - * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd - * for complex double. - * - * For example, \c Matrix3d is a fixed-size 3x3 matrix type of doubles, and \c MatrixXf is a dynamic-size matrix of floats. - * - * There are also \c VectorSizeType and \c RowVectorSizeType which are self-explanatory. For example, \c Vector4cf is - * a fixed-size vector of 4 complex floats. - * - * \sa class Matrix - */ - -#define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ -/** \ingroup matrixtypedefs */ \ -typedef Matrix Matrix##SizeSuffix##TypeSuffix; \ -/** \ingroup matrixtypedefs */ \ -typedef Matrix Vector##SizeSuffix##TypeSuffix; \ -/** \ingroup matrixtypedefs */ \ -typedef Matrix RowVector##SizeSuffix##TypeSuffix; - -#define EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \ -/** \ingroup matrixtypedefs */ \ -typedef Matrix Matrix##Size##X##TypeSuffix; \ -/** \ingroup matrixtypedefs */ \ -typedef Matrix Matrix##X##Size##TypeSuffix; + * + * \ingroup Core_Module + * + * %Eigen defines several typedef shortcuts for most common matrix and vector types. + * + * The general patterns are the following: + * + * \c MatrixSizeType where \c Size can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size, + * and where \c Type can be \c i for integer, \c f for float, \c d for double, \c cf for complex float, \c cd + * for complex double. + * + * For example, \c Matrix3d is a fixed-size 3x3 matrix type of doubles, and \c MatrixXf is a dynamic-size matrix of + * floats. + * + * There are also \c VectorSizeType and \c RowVectorSizeType which are self-explanatory. For example, \c Vector4cf is + * a fixed-size vector of 4 complex floats. + * + * With \cpp11, template alias are also defined for common sizes. + * They follow the same pattern as above except that the scalar type suffix is replaced by a + * template parameter, i.e.: + * - `MatrixSize` where `Size` can be \c 2,\c 3,\c 4 for fixed size square matrices or \c X for dynamic size. + * - `MatrixXSize` and `MatrixSizeX` where `Size` can be \c 2,\c 3,\c 4 for hybrid dynamic/fixed matrices. + * - `VectorSize` and `RowVectorSize` for column and row vectors. + * + * With \cpp11, you can also use fully generic column and row vector types: `Vector` and + * `RowVector`. + * + * \sa class Matrix + */ + +#define EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Size, SizeSuffix) \ + /** \ingroup matrixtypedefs */ \ + /** \brief `Size`×`Size` matrix of type `Type`. */ \ + typedef Matrix Matrix##SizeSuffix##TypeSuffix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief `Size`×`1` vector of type `Type`. */ \ + typedef Matrix Vector##SizeSuffix##TypeSuffix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief `1`×`Size` vector of type `Type`. */ \ + typedef Matrix RowVector##SizeSuffix##TypeSuffix; + +#define EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, Size) \ + /** \ingroup matrixtypedefs */ \ + /** \brief `Size`×`Dynamic` matrix of type `Type`. */ \ + typedef Matrix Matrix##Size##X##TypeSuffix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief `Dynamic`×`Size` matrix of type `Type`. */ \ + typedef Matrix Matrix##X##Size##TypeSuffix; #define EIGEN_MAKE_TYPEDEFS_ALL_SIZES(Type, TypeSuffix) \ -EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 2, 2) \ -EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 3, 3) \ -EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 4, 4) \ -EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \ -EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \ -EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \ -EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 4) - -EIGEN_MAKE_TYPEDEFS_ALL_SIZES(int, i) -EIGEN_MAKE_TYPEDEFS_ALL_SIZES(float, f) -EIGEN_MAKE_TYPEDEFS_ALL_SIZES(double, d) -EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex, cf) + EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 2, 2) \ + EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 3, 3) \ + EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, 4, 4) \ + EIGEN_MAKE_TYPEDEFS(Type, TypeSuffix, Dynamic, X) \ + EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 2) \ + EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 3) \ + EIGEN_MAKE_FIXED_TYPEDEFS(Type, TypeSuffix, 4) + +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(int, i) +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(float, f) +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(double, d) +EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex, cf) EIGEN_MAKE_TYPEDEFS_ALL_SIZES(std::complex, cd) #undef EIGEN_MAKE_TYPEDEFS_ALL_SIZES #undef EIGEN_MAKE_TYPEDEFS #undef EIGEN_MAKE_FIXED_TYPEDEFS -} // end namespace Eigen +#define EIGEN_MAKE_TYPEDEFS(Size, SizeSuffix) \ + /** \ingroup matrixtypedefs */ \ + /** \brief \cpp11 `Size`×`Size` matrix of type `Type`.*/ \ + template \ + using Matrix##SizeSuffix = Matrix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief \cpp11 `Size`×`1` vector of type `Type`.*/ \ + template \ + using Vector##SizeSuffix = Matrix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief \cpp11 `1`×`Size` vector of type `Type`.*/ \ + template \ + using RowVector##SizeSuffix = Matrix; + +#define EIGEN_MAKE_FIXED_TYPEDEFS(Size) \ + /** \ingroup matrixtypedefs */ \ + /** \brief \cpp11 `Size`×`Dynamic` matrix of type `Type` */ \ + template \ + using Matrix##Size##X = Matrix; \ + /** \ingroup matrixtypedefs */ \ + /** \brief \cpp11 `Dynamic`×`Size` matrix of type `Type`. */ \ + template \ + using Matrix##X##Size = Matrix; + +EIGEN_MAKE_TYPEDEFS(2, 2) +EIGEN_MAKE_TYPEDEFS(3, 3) +EIGEN_MAKE_TYPEDEFS(4, 4) +EIGEN_MAKE_TYPEDEFS(Dynamic, X) +EIGEN_MAKE_FIXED_TYPEDEFS(2) +EIGEN_MAKE_FIXED_TYPEDEFS(3) +EIGEN_MAKE_FIXED_TYPEDEFS(4) + +/** \ingroup matrixtypedefs + * \brief \cpp11 `Size`×`1` vector of type `Type`. */ +template +using Vector = Matrix; + +/** \ingroup matrixtypedefs + * \brief \cpp11 `1`×`Size` vector of type `Type`. */ +template +using RowVector = Matrix; + +#undef EIGEN_MAKE_TYPEDEFS +#undef EIGEN_MAKE_FIXED_TYPEDEFS + +} // end namespace Eigen -#endif // EIGEN_MATRIX_H +#endif // EIGEN_MATRIX_H diff --git a/inst/include/Eigen/src/Core/MatrixBase.h b/inst/include/Eigen/src/Core/MatrixBase.h index e83ef4dc..045993d4 100644 --- a/inst/include/Eigen/src/Core/MatrixBase.h +++ b/inst/include/Eigen/src/Core/MatrixBase.h @@ -11,6 +11,9 @@ #ifndef EIGEN_MATRIXBASE_H #define EIGEN_MATRIXBASE_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { /** \class MatrixBase @@ -41,523 +44,502 @@ namespace Eigen { * \endcode * * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_MATRIXBASE_PLUGIN. + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_MATRIXBASE_PLUGIN. * - * \sa \ref TopicClassHierarchy + * \sa \blank \ref TopicClassHierarchy */ -template class MatrixBase - : public DenseBase -{ - public: +template +class MatrixBase : public DenseBase { + public: #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef MatrixBase StorageBaseType; - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - - typedef DenseBase Base; - using Base::RowsAtCompileTime; - using Base::ColsAtCompileTime; - using Base::SizeAtCompileTime; - using Base::MaxRowsAtCompileTime; - using Base::MaxColsAtCompileTime; - using Base::MaxSizeAtCompileTime; - using Base::IsVectorAtCompileTime; - using Base::Flags; - using Base::CoeffReadCost; - - using Base::derived; - using Base::const_cast_derived; - using Base::rows; - using Base::cols; - using Base::size; - using Base::coeff; - using Base::coeffRef; - using Base::lazyAssign; - using Base::eval; - using Base::operator+=; - using Base::operator-=; - using Base::operator*=; - using Base::operator/=; - - typedef typename Base::CoeffReturnType CoeffReturnType; - typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType; - typedef typename Base::RowXpr RowXpr; - typedef typename Base::ColXpr ColXpr; -#endif // not EIGEN_PARSED_BY_DOXYGEN + typedef MatrixBase StorageBaseType; + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::StorageIndex StorageIndex; + typedef typename internal::traits::Scalar Scalar; + typedef typename internal::packet_traits::type PacketScalar; + typedef typename NumTraits::Real RealScalar; + + typedef DenseBase Base; + using Base::ColsAtCompileTime; + using Base::Flags; + using Base::IsVectorAtCompileTime; + using Base::MaxColsAtCompileTime; + using Base::MaxRowsAtCompileTime; + using Base::MaxSizeAtCompileTime; + using Base::RowsAtCompileTime; + using Base::SizeAtCompileTime; + + using Base::coeff; + using Base::coeffRef; + using Base::cols; + using Base::const_cast_derived; + using Base::derived; + using Base::eval; + using Base::lazyAssign; + using Base::rows; + using Base::size; + using Base::operator-; + using Base::operator+=; + using Base::operator-=; + using Base::operator*=; + using Base::operator/=; + + typedef typename Base::CoeffReturnType CoeffReturnType; + typedef typename Base::ConstTransposeReturnType ConstTransposeReturnType; + typedef typename Base::RowXpr RowXpr; + typedef typename Base::ColXpr ColXpr; +#endif // not EIGEN_PARSED_BY_DOXYGEN +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** type of the equivalent square matrix */ + typedef Matrix + SquareMatrixType; +#endif // not EIGEN_PARSED_BY_DOXYGEN + /** \returns the size of the main diagonal, which is min(rows(),cols()). + * \sa rows(), cols(), SizeAtCompileTime. */ + EIGEN_DEVICE_FUNC inline Index diagonalSize() const { return (numext::mini)(rows(), cols()); } -#ifndef EIGEN_PARSED_BY_DOXYGEN - /** type of the equivalent square matrix */ - typedef Matrix SquareMatrixType; -#endif // not EIGEN_PARSED_BY_DOXYGEN - - /** \returns the size of the main diagonal, which is min(rows(),cols()). - * \sa rows(), cols(), SizeAtCompileTime. */ - inline Index diagonalSize() const { return (std::min)(rows(),cols()); } - - /** \brief The plain matrix type corresponding to this expression. - * - * This is not necessarily exactly the return type of eval(). In the case of plain matrices, - * the return type of eval() is a const reference to a matrix, not a matrix! It is however guaranteed - * that the return type of eval() is either PlainObject or const PlainObject&. - */ - typedef Matrix::Scalar, - internal::traits::RowsAtCompileTime, - internal::traits::ColsAtCompileTime, - AutoAlign | (internal::traits::Flags&RowMajorBit ? RowMajor : ColMajor), - internal::traits::MaxRowsAtCompileTime, - internal::traits::MaxColsAtCompileTime - > PlainObject; + typedef typename Base::PlainObject PlainObject; #ifndef EIGEN_PARSED_BY_DOXYGEN - /** \internal Represents a matrix with all coefficients equal to one another*/ - typedef CwiseNullaryOp,Derived> ConstantReturnType; - /** \internal the return type of MatrixBase::adjoint() */ - typedef typename internal::conditional::IsComplex, - CwiseUnaryOp, ConstTransposeReturnType>, - ConstTransposeReturnType - >::type AdjointReturnType; - /** \internal Return type of eigenvalues() */ - typedef Matrix, internal::traits::ColsAtCompileTime, 1, ColMajor> EigenvaluesReturnType; - /** \internal the return type of identity */ - typedef CwiseNullaryOp,Derived> IdentityReturnType; - /** \internal the return type of unit vectors */ - typedef Block, SquareMatrixType>, - internal::traits::RowsAtCompileTime, - internal::traits::ColsAtCompileTime> BasisReturnType; -#endif // not EIGEN_PARSED_BY_DOXYGEN + /** \internal Represents a matrix with all coefficients equal to one another*/ + typedef CwiseNullaryOp, PlainObject> ConstantReturnType; + /** \internal the return type of MatrixBase::adjoint() */ + typedef std::conditional_t::IsComplex, + CwiseUnaryOp, ConstTransposeReturnType>, + ConstTransposeReturnType> + AdjointReturnType; + /** \internal Return type of eigenvalues() */ + typedef Matrix, internal::traits::ColsAtCompileTime, 1, ColMajor> + EigenvaluesReturnType; + /** \internal the return type of identity */ + typedef CwiseNullaryOp, PlainObject> IdentityReturnType; + /** \internal the return type of unit vectors */ + typedef Block, SquareMatrixType>, + internal::traits::RowsAtCompileTime, internal::traits::ColsAtCompileTime> + BasisReturnType; +#endif // not EIGEN_PARSED_BY_DOXYGEN #define EIGEN_CURRENT_STORAGE_BASE_CLASS Eigen::MatrixBase -# include "../plugins/CommonCwiseUnaryOps.h" -# include "../plugins/CommonCwiseBinaryOps.h" -# include "../plugins/MatrixCwiseUnaryOps.h" -# include "../plugins/MatrixCwiseBinaryOps.h" -# ifdef EIGEN_MATRIXBASE_PLUGIN -# include EIGEN_MATRIXBASE_PLUGIN -# endif -#undef EIGEN_CURRENT_STORAGE_BASE_CLASS - - /** Special case of the template operator=, in order to prevent the compiler - * from generating a default operator= (issue hit with g++ 4.1) - */ - Derived& operator=(const MatrixBase& other); - - // We cannot inherit here via Base::operator= since it is causing - // trouble with MSVC. - - template - Derived& operator=(const DenseBase& other); - - template - Derived& operator=(const EigenBase& other); - - template - Derived& operator=(const ReturnByValue& other); - - template - Derived& lazyAssign(const ProductBase& other); - - template - Derived& lazyAssign(const MatrixPowerProduct& other); - - template - Derived& operator+=(const MatrixBase& other); - template - Derived& operator-=(const MatrixBase& other); - - template - const typename ProductReturnType::Type - operator*(const MatrixBase &other) const; - - template - const typename LazyProductReturnType::Type - lazyProduct(const MatrixBase &other) const; - - template - Derived& operator*=(const EigenBase& other); - - template - void applyOnTheLeft(const EigenBase& other); - - template - void applyOnTheRight(const EigenBase& other); - - template - const DiagonalProduct - operator*(const DiagonalBase &diagonal) const; - - template - typename internal::scalar_product_traits::Scalar,typename internal::traits::Scalar>::ReturnType - dot(const MatrixBase& other) const; - - #ifdef EIGEN2_SUPPORT - template - Scalar eigen2_dot(const MatrixBase& other) const; - #endif - - RealScalar squaredNorm() const; - RealScalar norm() const; - RealScalar stableNorm() const; - RealScalar blueNorm() const; - RealScalar hypotNorm() const; - const PlainObject normalized() const; - void normalize(); - - const AdjointReturnType adjoint() const; - void adjointInPlace(); - - typedef Diagonal DiagonalReturnType; - DiagonalReturnType diagonal(); - typedef typename internal::add_const >::type ConstDiagonalReturnType; - ConstDiagonalReturnType diagonal() const; - - template struct DiagonalIndexReturnType { typedef Diagonal Type; }; - template struct ConstDiagonalIndexReturnType { typedef const Diagonal Type; }; - - template typename DiagonalIndexReturnType::Type diagonal(); - template typename ConstDiagonalIndexReturnType::Type diagonal() const; - - typedef Diagonal DiagonalDynamicIndexReturnType; - typedef typename internal::add_const >::type ConstDiagonalDynamicIndexReturnType; - - DiagonalDynamicIndexReturnType diagonal(Index index); - ConstDiagonalDynamicIndexReturnType diagonal(Index index) const; - - #ifdef EIGEN2_SUPPORT - template typename internal::eigen2_part_return_type::type part(); - template const typename internal::eigen2_part_return_type::type part() const; - - // huuuge hack. make Eigen2's matrix.part() work in eigen3. Problem: Diagonal is now a class template instead - // of an integer constant. Solution: overload the part() method template wrt template parameters list. - template class U> - const DiagonalWrapper part() const - { return diagonal().asDiagonal(); } - #endif // EIGEN2_SUPPORT - - template struct TriangularViewReturnType { typedef TriangularView Type; }; - template struct ConstTriangularViewReturnType { typedef const TriangularView Type; }; - - template typename TriangularViewReturnType::Type triangularView(); - template typename ConstTriangularViewReturnType::Type triangularView() const; - - template struct SelfAdjointViewReturnType { typedef SelfAdjointView Type; }; - template struct ConstSelfAdjointViewReturnType { typedef const SelfAdjointView Type; }; - - template typename SelfAdjointViewReturnType::Type selfadjointView(); - template typename ConstSelfAdjointViewReturnType::Type selfadjointView() const; - - const SparseView sparseView(const Scalar& m_reference = Scalar(0), - const typename NumTraits::Real& m_epsilon = NumTraits::dummy_precision()) const; - static const IdentityReturnType Identity(); - static const IdentityReturnType Identity(Index rows, Index cols); - static const BasisReturnType Unit(Index size, Index i); - static const BasisReturnType Unit(Index i); - static const BasisReturnType UnitX(); - static const BasisReturnType UnitY(); - static const BasisReturnType UnitZ(); - static const BasisReturnType UnitW(); - - const DiagonalWrapper asDiagonal() const; - const PermutationWrapper asPermutation() const; - - Derived& setIdentity(); - Derived& setIdentity(Index rows, Index cols); - - bool isIdentity(const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isDiagonal(const RealScalar& prec = NumTraits::dummy_precision()) const; - - bool isUpperTriangular(const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isLowerTriangular(const RealScalar& prec = NumTraits::dummy_precision()) const; - - template - bool isOrthogonal(const MatrixBase& other, - const RealScalar& prec = NumTraits::dummy_precision()) const; - bool isUnitary(const RealScalar& prec = NumTraits::dummy_precision()) const; - - /** \returns true if each coefficients of \c *this and \a other are all exactly equal. - * \warning When using floating point scalar values you probably should rather use a - * fuzzy comparison such as isApprox() - * \sa isApprox(), operator!= */ - template - inline bool operator==(const MatrixBase& other) const - { return cwiseEqual(other).all(); } - - /** \returns true if at least one pair of coefficients of \c *this and \a other are not exactly equal to each other. - * \warning When using floating point scalar values you probably should rather use a - * fuzzy comparison such as isApprox() - * \sa isApprox(), operator== */ - template - inline bool operator!=(const MatrixBase& other) const - { return cwiseNotEqual(other).any(); } - - NoAlias noalias(); - - inline const ForceAlignedAccess forceAlignedAccess() const; - inline ForceAlignedAccess forceAlignedAccess(); - template inline typename internal::add_const_on_value_type,Derived&>::type>::type forceAlignedAccessIf() const; - template inline typename internal::conditional,Derived&>::type forceAlignedAccessIf(); - - Scalar trace() const; - -/////////// Array module /////////// - - template RealScalar lpNorm() const; - - MatrixBase& matrix() { return *this; } - const MatrixBase& matrix() const { return *this; } - - /** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix - * \sa ArrayBase::matrix() */ - ArrayWrapper array() { return derived(); } - const ArrayWrapper array() const { return derived(); } - -/////////// LU module /////////// - - const FullPivLU fullPivLu() const; - const PartialPivLU partialPivLu() const; - - #if EIGEN2_SUPPORT_STAGE < STAGE20_RESOLVE_API_CONFLICTS - const LU lu() const; - #endif - - #ifdef EIGEN2_SUPPORT - const LU eigen2_lu() const; - #endif - - #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS - const PartialPivLU lu() const; - #endif - - #ifdef EIGEN2_SUPPORT - template - void computeInverse(MatrixBase *result) const { - *result = this->inverse(); - } - #endif - - const internal::inverse_impl inverse() const; - template - void computeInverseAndDetWithCheck( - ResultType& inverse, - typename ResultType::Scalar& determinant, - bool& invertible, - const RealScalar& absDeterminantThreshold = NumTraits::dummy_precision() - ) const; - template - void computeInverseWithCheck( - ResultType& inverse, - bool& invertible, - const RealScalar& absDeterminantThreshold = NumTraits::dummy_precision() - ) const; - Scalar determinant() const; - -/////////// Cholesky module /////////// - - const LLT llt() const; - const LDLT ldlt() const; - -/////////// QR module /////////// - - const HouseholderQR householderQr() const; - const ColPivHouseholderQR colPivHouseholderQr() const; - const FullPivHouseholderQR fullPivHouseholderQr() const; - - #ifdef EIGEN2_SUPPORT - const QR qr() const; - #endif - - EigenvaluesReturnType eigenvalues() const; - RealScalar operatorNorm() const; - -/////////// SVD module /////////// - - JacobiSVD jacobiSvd(unsigned int computationOptions = 0) const; - - #ifdef EIGEN2_SUPPORT - SVD svd() const; - #endif - -/////////// Geometry module /////////// - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /// \internal helper struct to form the return type of the cross product - template struct cross_product_return_type { - typedef typename internal::scalar_product_traits::Scalar,typename internal::traits::Scalar>::ReturnType Scalar; - typedef Matrix type; - }; - #endif // EIGEN_PARSED_BY_DOXYGEN - template - typename cross_product_return_type::type - cross(const MatrixBase& other) const; - template - PlainObject cross3(const MatrixBase& other) const; - PlainObject unitOrthogonal(void) const; - Matrix eulerAngles(Index a0, Index a1, Index a2) const; - - #if EIGEN2_SUPPORT_STAGE > STAGE20_RESOLVE_API_CONFLICTS - ScalarMultipleReturnType operator*(const UniformScaling& s) const; - // put this as separate enum value to work around possible GCC 4.3 bug (?) - enum { HomogeneousReturnTypeDirection = ColsAtCompileTime==1?Vertical:Horizontal }; - typedef Homogeneous HomogeneousReturnType; - HomogeneousReturnType homogeneous() const; - #endif - - enum { - SizeMinusOne = SizeAtCompileTime==Dynamic ? Dynamic : SizeAtCompileTime-1 - }; - typedef Block::ColsAtCompileTime==1 ? SizeMinusOne : 1, - internal::traits::ColsAtCompileTime==1 ? 1 : SizeMinusOne> ConstStartMinusOne; - typedef CwiseUnaryOp::Scalar>, - const ConstStartMinusOne > HNormalizedReturnType; - - const HNormalizedReturnType hnormalized() const; - -////////// Householder module /////////// - - void makeHouseholderInPlace(Scalar& tau, RealScalar& beta); - template - void makeHouseholder(EssentialPart& essential, - Scalar& tau, RealScalar& beta) const; - template - void applyHouseholderOnTheLeft(const EssentialPart& essential, - const Scalar& tau, - Scalar* workspace); - template - void applyHouseholderOnTheRight(const EssentialPart& essential, - const Scalar& tau, - Scalar* workspace); - -///////// Jacobi module ///////// - - template - void applyOnTheLeft(Index p, Index q, const JacobiRotation& j); - template - void applyOnTheRight(Index p, Index q, const JacobiRotation& j); - -///////// SparseCore module ///////// - - template - EIGEN_STRONG_INLINE const typename SparseMatrixBase::template CwiseProductDenseReturnType::Type - cwiseProduct(const SparseMatrixBase &other) const - { - return other.cwiseProduct(derived()); - } - -///////// MatrixFunctions module ///////// - - typedef typename internal::stem_function::type StemFunction; - const MatrixExponentialReturnValue exp() const; - const MatrixFunctionReturnValue matrixFunction(StemFunction f) const; - const MatrixFunctionReturnValue cosh() const; - const MatrixFunctionReturnValue sinh() const; - const MatrixFunctionReturnValue cos() const; - const MatrixFunctionReturnValue sin() const; - const MatrixSquareRootReturnValue sqrt() const; - const MatrixLogarithmReturnValue log() const; - const MatrixPowerReturnValue pow(const RealScalar& p) const; - -#ifdef EIGEN2_SUPPORT - template - Derived& operator+=(const Flagged, 0, - EvalBeforeAssigningBit>& other); - - template - Derived& operator-=(const Flagged, 0, - EvalBeforeAssigningBit>& other); - - /** \deprecated because .lazy() is deprecated - * Overloaded for cache friendly product evaluation */ - template - Derived& lazyAssign(const Flagged& other) - { return lazyAssign(other._expression()); } - - template - const Flagged marked() const; - const Flagged lazy() const; - - inline const Cwise cwise() const; - inline Cwise cwise(); - - VectorBlock start(Index size); - const VectorBlock start(Index size) const; - VectorBlock end(Index size); - const VectorBlock end(Index size) const; - template VectorBlock start(); - template const VectorBlock start() const; - template VectorBlock end(); - template const VectorBlock end() const; - - Minor minor(Index row, Index col); - const Minor minor(Index row, Index col) const; +#define EIGEN_DOC_UNARY_ADDONS(X, Y) +#include "../plugins/CommonCwiseBinaryOps.inc" +#include "../plugins/MatrixCwiseUnaryOps.inc" +#include "../plugins/MatrixCwiseBinaryOps.inc" +#ifdef EIGEN_MATRIXBASE_PLUGIN +#include EIGEN_MATRIXBASE_PLUGIN #endif - - protected: - MatrixBase() : Base() {} - - private: - explicit MatrixBase(int); - MatrixBase(int,int); - template explicit MatrixBase(const MatrixBase&); - protected: - // mixing arrays and matrices is not legal - template Derived& operator+=(const ArrayBase& ) - {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} - // mixing arrays and matrices is not legal - template Derived& operator-=(const ArrayBase& ) - {EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar))==-1,YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); return *this;} +#undef EIGEN_CURRENT_STORAGE_BASE_CLASS +#undef EIGEN_DOC_UNARY_ADDONS + + /** Special case of the template operator=, in order to prevent the compiler + * from generating a default operator= (issue hit with g++ 4.1) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const MatrixBase& other); + + // We cannot inherit here via Base::operator= since it is causing + // trouble with MSVC. + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const DenseBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator=(const EigenBase& other); + + template + EIGEN_DEVICE_FUNC Derived& operator=(const ReturnByValue& other); + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator+=(const MatrixBase& other); + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator-=(const MatrixBase& other); + + template + EIGEN_DEVICE_FUNC const Product operator*(const MatrixBase& other) const; + + template + EIGEN_DEVICE_FUNC const Product lazyProduct( + const MatrixBase& other) const; + + template + Derived& operator*=(const EigenBase& other); + + template + void applyOnTheLeft(const EigenBase& other); + + template + void applyOnTheRight(const EigenBase& other); + + template + EIGEN_DEVICE_FUNC const Product operator*( + const DiagonalBase& diagonal) const; + + template + EIGEN_DEVICE_FUNC const Product operator*( + const SkewSymmetricBase& skew) const; + + template + EIGEN_DEVICE_FUNC typename ScalarBinaryOpTraits::Scalar, + typename internal::traits::Scalar>::ReturnType + dot(const MatrixBase& other) const; + + EIGEN_DEVICE_FUNC RealScalar squaredNorm() const; + EIGEN_DEVICE_FUNC RealScalar norm() const; + RealScalar stableNorm() const; + RealScalar blueNorm() const; + RealScalar hypotNorm() const; + EIGEN_DEVICE_FUNC const PlainObject normalized() const; + EIGEN_DEVICE_FUNC const PlainObject stableNormalized() const; + EIGEN_DEVICE_FUNC void normalize(); + EIGEN_DEVICE_FUNC void stableNormalize(); + + EIGEN_DEVICE_FUNC const AdjointReturnType adjoint() const; + EIGEN_DEVICE_FUNC void adjointInPlace(); + + typedef Diagonal DiagonalReturnType; + EIGEN_DEVICE_FUNC DiagonalReturnType diagonal(); + + typedef Diagonal ConstDiagonalReturnType; + EIGEN_DEVICE_FUNC const ConstDiagonalReturnType diagonal() const; + + template + EIGEN_DEVICE_FUNC Diagonal diagonal(); + + template + EIGEN_DEVICE_FUNC const Diagonal diagonal() const; + + EIGEN_DEVICE_FUNC Diagonal diagonal(Index index); + EIGEN_DEVICE_FUNC const Diagonal diagonal(Index index) const; + + template + struct TriangularViewReturnType { + typedef TriangularView Type; + }; + template + struct ConstTriangularViewReturnType { + typedef const TriangularView Type; + }; + + template + EIGEN_DEVICE_FUNC typename TriangularViewReturnType::Type triangularView(); + template + EIGEN_DEVICE_FUNC typename ConstTriangularViewReturnType::Type triangularView() const; + + template + struct SelfAdjointViewReturnType { + typedef SelfAdjointView Type; + }; + template + struct ConstSelfAdjointViewReturnType { + typedef const SelfAdjointView Type; + }; + + template + EIGEN_DEVICE_FUNC typename SelfAdjointViewReturnType::Type selfadjointView(); + template + EIGEN_DEVICE_FUNC typename ConstSelfAdjointViewReturnType::Type selfadjointView() const; + + const SparseView sparseView( + const Scalar& m_reference = Scalar(0), + const typename NumTraits::Real& m_epsilon = NumTraits::dummy_precision()) const; + EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(); + EIGEN_DEVICE_FUNC static const IdentityReturnType Identity(Index rows, Index cols); + EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index size, Index i); + EIGEN_DEVICE_FUNC static const BasisReturnType Unit(Index i); + EIGEN_DEVICE_FUNC static const BasisReturnType UnitX(); + EIGEN_DEVICE_FUNC static const BasisReturnType UnitY(); + EIGEN_DEVICE_FUNC static const BasisReturnType UnitZ(); + EIGEN_DEVICE_FUNC static const BasisReturnType UnitW(); + + EIGEN_DEVICE_FUNC const DiagonalWrapper asDiagonal() const; + const PermutationWrapper asPermutation() const; + EIGEN_DEVICE_FUNC const SkewSymmetricWrapper asSkewSymmetric() const; + + EIGEN_DEVICE_FUNC Derived& setIdentity(); + EIGEN_DEVICE_FUNC Derived& setIdentity(Index rows, Index cols); + EIGEN_DEVICE_FUNC Derived& setUnit(Index i); + EIGEN_DEVICE_FUNC Derived& setUnit(Index newSize, Index i); + + bool isIdentity(const RealScalar& prec = NumTraits::dummy_precision()) const; + bool isDiagonal(const RealScalar& prec = NumTraits::dummy_precision()) const; + + bool isUpperTriangular(const RealScalar& prec = NumTraits::dummy_precision()) const; + bool isLowerTriangular(const RealScalar& prec = NumTraits::dummy_precision()) const; + + bool isSkewSymmetric(const RealScalar& prec = NumTraits::dummy_precision()) const; + + template + bool isOrthogonal(const MatrixBase& other, + const RealScalar& prec = NumTraits::dummy_precision()) const; + bool isUnitary(const RealScalar& prec = NumTraits::dummy_precision()) const; + + /** \returns true if each coefficients of \c *this and \a other are all exactly equal. + * \warning When using floating point scalar values you probably should rather use a + * fuzzy comparison such as isApprox() + * \sa isApprox(), operator!= */ + template + EIGEN_DEVICE_FUNC inline bool operator==(const MatrixBase& other) const { + return (this->rows() == other.rows()) && (this->cols() == other.cols()) && cwiseEqual(other).all(); + } + + /** \returns true if at least one pair of coefficients of \c *this and \a other are not exactly equal to each other. + * \warning When using floating point scalar values you probably should rather use a + * fuzzy comparison such as isApprox() + * \sa isApprox(), operator== */ + template + EIGEN_DEVICE_FUNC inline bool operator!=(const MatrixBase& other) const { + return !(*this == other); + } + + NoAlias EIGEN_DEVICE_FUNC noalias(); + + // TODO forceAlignedAccess is temporarily disabled + // Need to find a nicer workaround. + inline const Derived& forceAlignedAccess() const { return derived(); } + inline Derived& forceAlignedAccess() { return derived(); } + template + inline const Derived& forceAlignedAccessIf() const { + return derived(); + } + template + inline Derived& forceAlignedAccessIf() { + return derived(); + } + + EIGEN_DEVICE_FUNC Scalar trace() const; + + template + EIGEN_DEVICE_FUNC RealScalar lpNorm() const; + + EIGEN_DEVICE_FUNC MatrixBase& matrix() { return *this; } + EIGEN_DEVICE_FUNC const MatrixBase& matrix() const { return *this; } + + /** \returns an \link Eigen::ArrayBase Array \endlink expression of this matrix + * \sa ArrayBase::matrix() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ArrayWrapper array() { return ArrayWrapper(derived()); } + /** \returns a const \link Eigen::ArrayBase Array \endlink expression of this matrix + * \sa ArrayBase::matrix() */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const ArrayWrapper array() const { + return ArrayWrapper(derived()); + } + + /////////// LU module /////////// + + template + inline const FullPivLU fullPivLu() const; + template + inline const PartialPivLU partialPivLu() const; + + template + inline const PartialPivLU lu() const; + + EIGEN_DEVICE_FUNC inline const Inverse inverse() const; + + template + inline void computeInverseAndDetWithCheck( + ResultType& inverse, typename ResultType::Scalar& determinant, bool& invertible, + const RealScalar& absDeterminantThreshold = NumTraits::dummy_precision()) const; + + template + inline void computeInverseWithCheck( + ResultType& inverse, bool& invertible, + const RealScalar& absDeterminantThreshold = NumTraits::dummy_precision()) const; + + EIGEN_DEVICE_FUNC Scalar determinant() const; + + /////////// Cholesky module /////////// + + inline const LLT llt() const; + inline const LDLT ldlt() const; + + /////////// QR module /////////// + + inline const HouseholderQR householderQr() const; + template + inline const ColPivHouseholderQR colPivHouseholderQr() const; + template + inline const FullPivHouseholderQR fullPivHouseholderQr() const; + template + inline const CompleteOrthogonalDecomposition completeOrthogonalDecomposition() const; + + /////////// Eigenvalues module /////////// + + inline EigenvaluesReturnType eigenvalues() const; + inline RealScalar operatorNorm() const; + + /////////// SVD module /////////// + + template + inline JacobiSVD jacobiSvd() const; + template + EIGEN_DEPRECATED_WITH_REASON("Options should be specified using method's template parameter.") + inline JacobiSVD jacobiSvd(unsigned int computationOptions) const; + + template + inline BDCSVD bdcSvd() const; + template + EIGEN_DEPRECATED_WITH_REASON("Options should be specified using method's template parameter.") + inline BDCSVD bdcSvd(unsigned int computationOptions) const; + + /////////// Geometry module /////////// + + template + EIGEN_DEVICE_FUNC inline typename internal::cross_impl::return_type cross( + const MatrixBase& other) const; + + template + EIGEN_DEVICE_FUNC inline PlainObject cross3(const MatrixBase& other) const; + + EIGEN_DEVICE_FUNC inline PlainObject unitOrthogonal(void) const; + + EIGEN_DEPRECATED_WITH_REASON("Use .canonicalEulerAngles() instead.") + EIGEN_DEVICE_FUNC inline Matrix eulerAngles(Index a0, Index a1, Index a2) const; + + EIGEN_DEVICE_FUNC inline Matrix canonicalEulerAngles(Index a0, Index a1, Index a2) const; + + // put this as separate enum value to work around possible GCC 4.3 bug (?) + enum { + HomogeneousReturnTypeDirection = + ColsAtCompileTime == 1 && RowsAtCompileTime == 1 + ? ((internal::traits::Flags & RowMajorBit) == RowMajorBit ? Horizontal : Vertical) + : ColsAtCompileTime == 1 ? Vertical + : Horizontal + }; + typedef Homogeneous HomogeneousReturnType; + EIGEN_DEVICE_FUNC inline HomogeneousReturnType homogeneous() const; + + enum { SizeMinusOne = SizeAtCompileTime == Dynamic ? Dynamic : SizeAtCompileTime - 1 }; + typedef Block::ColsAtCompileTime == 1 ? SizeMinusOne : 1, + internal::traits::ColsAtCompileTime == 1 ? 1 : SizeMinusOne> + ConstStartMinusOne; + typedef EIGEN_EXPR_BINARYOP_SCALAR_RETURN_TYPE(ConstStartMinusOne, Scalar, quotient) HNormalizedReturnType; + EIGEN_DEVICE_FUNC inline const HNormalizedReturnType hnormalized() const; + + ////////// Householder module /////////// + + EIGEN_DEVICE_FUNC void makeHouseholderInPlace(Scalar& tau, RealScalar& beta); + template + EIGEN_DEVICE_FUNC void makeHouseholder(EssentialPart& essential, Scalar& tau, RealScalar& beta) const; + template + EIGEN_DEVICE_FUNC void applyHouseholderOnTheLeft(const EssentialPart& essential, const Scalar& tau, + Scalar* workspace); + template + EIGEN_DEVICE_FUNC void applyHouseholderOnTheRight(const EssentialPart& essential, const Scalar& tau, + Scalar* workspace); + + ///////// Jacobi module ///////// + + template + EIGEN_DEVICE_FUNC void applyOnTheLeft(Index p, Index q, const JacobiRotation& j); + template + EIGEN_DEVICE_FUNC void applyOnTheRight(Index p, Index q, const JacobiRotation& j); + + ///////// SparseCore module ///////// + + template + EIGEN_STRONG_INLINE const typename SparseMatrixBase::template CwiseProductDenseReturnType::Type + cwiseProduct(const SparseMatrixBase& other) const { + return other.cwiseProduct(derived()); + } + + ///////// MatrixFunctions module ///////// + + typedef typename internal::stem_function::type StemFunction; +#define EIGEN_MATRIX_FUNCTION(ReturnType, Name, Description) \ + /** \returns an expression of the matrix Description of \c *this. \brief This function requires the unsupported MatrixFunctions module. To compute the \ + * coefficient-wise Description use ArrayBase::##Name . */ \ + const ReturnType Name() const; +#define EIGEN_MATRIX_FUNCTION_1(ReturnType, Name, Description, Argument) \ + /** \returns an expression of the matrix Description of \c *this. \brief This function requires the unsupported MatrixFunctions module. To compute the \ + * coefficient-wise Description use ArrayBase::##Name . */ \ + const ReturnType Name(Argument) const; + + EIGEN_MATRIX_FUNCTION(MatrixExponentialReturnValue, exp, exponential) + /** \brief Helper function for the unsupported + * MatrixFunctions module.*/ + const MatrixFunctionReturnValue matrixFunction(StemFunction f) const; + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cosh, hyperbolic cosine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sinh, hyperbolic sine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, atanh, inverse hyperbolic cosine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, acosh, inverse hyperbolic cosine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, asinh, inverse hyperbolic sine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, cos, cosine) + EIGEN_MATRIX_FUNCTION(MatrixFunctionReturnValue, sin, sine) + EIGEN_MATRIX_FUNCTION(MatrixSquareRootReturnValue, sqrt, square root) + EIGEN_MATRIX_FUNCTION(MatrixLogarithmReturnValue, log, logarithm) + EIGEN_MATRIX_FUNCTION_1(MatrixPowerReturnValue, pow, power to \c p, const RealScalar& p) + EIGEN_MATRIX_FUNCTION_1(MatrixComplexPowerReturnValue, pow, power to \c p, const internal::make_complex_t& p) + + protected: + EIGEN_DEFAULT_COPY_CONSTRUCTOR(MatrixBase) + EIGEN_DEFAULT_EMPTY_CONSTRUCTOR_AND_DESTRUCTOR(MatrixBase) + + private: + EIGEN_DEVICE_FUNC explicit MatrixBase(int); + EIGEN_DEVICE_FUNC MatrixBase(int, int); + template + EIGEN_DEVICE_FUNC explicit MatrixBase(const MatrixBase&); + + protected: + // mixing arrays and matrices is not legal + template + Derived& operator+=(const ArrayBase&) { + EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1, + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); + return *this; + } + // mixing arrays and matrices is not legal + template + Derived& operator-=(const ArrayBase&) { + EIGEN_STATIC_ASSERT(std::ptrdiff_t(sizeof(typename OtherDerived::Scalar)) == -1, + YOU_CANNOT_MIX_ARRAYS_AND_MATRICES); + return *this; + } }; - /*************************************************************************** -* Implementation of matrix base methods -***************************************************************************/ + * Implementation of matrix base methods + ***************************************************************************/ /** replaces \c *this by \c *this * \a other. - * - * \returns a reference to \c *this - * - * Example: \include MatrixBase_applyOnTheRight.cpp - * Output: \verbinclude MatrixBase_applyOnTheRight.out - */ -template -template -inline Derived& -MatrixBase::operator*=(const EigenBase &other) -{ + * + * \returns a reference to \c *this + * + * Example: \include MatrixBase_applyOnTheRight.cpp + * Output: \verbinclude MatrixBase_applyOnTheRight.out + */ +template +template +inline Derived& MatrixBase::operator*=(const EigenBase& other) { other.derived().applyThisOnTheRight(derived()); return derived(); } /** replaces \c *this by \c *this * \a other. It is equivalent to MatrixBase::operator*=(). - * - * Example: \include MatrixBase_applyOnTheRight.cpp - * Output: \verbinclude MatrixBase_applyOnTheRight.out - */ -template -template -inline void MatrixBase::applyOnTheRight(const EigenBase &other) -{ + * + * Example: \include MatrixBase_applyOnTheRight.cpp + * Output: \verbinclude MatrixBase_applyOnTheRight.out + */ +template +template +inline void MatrixBase::applyOnTheRight(const EigenBase& other) { other.derived().applyThisOnTheRight(derived()); } /** replaces \c *this by \a other * \c *this. - * - * Example: \include MatrixBase_applyOnTheLeft.cpp - * Output: \verbinclude MatrixBase_applyOnTheLeft.out - */ -template -template -inline void MatrixBase::applyOnTheLeft(const EigenBase &other) -{ + * + * Example: \include MatrixBase_applyOnTheLeft.cpp + * Output: \verbinclude MatrixBase_applyOnTheLeft.out + */ +template +template +inline void MatrixBase::applyOnTheLeft(const EigenBase& other) { other.derived().applyThisOnTheLeft(derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_MATRIXBASE_H +#endif // EIGEN_MATRIXBASE_H diff --git a/inst/include/Eigen/src/Core/NestByValue.h b/inst/include/Eigen/src/Core/NestByValue.h index a893b176..2ce83a8c 100644 --- a/inst/include/Eigen/src/Core/NestByValue.h +++ b/inst/include/Eigen/src/Core/NestByValue.h @@ -11,101 +11,81 @@ #ifndef EIGEN_NESTBYVALUE_H #define EIGEN_NESTBYVALUE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class NestByValue - * \ingroup Core_Module - * - * \brief Expression which must be nested by value - * - * \param ExpressionType the type of the object of which we are requiring nesting-by-value - * - * This class is the return type of MatrixBase::nestByValue() - * and most of the time this is the only way it is used. - * - * \sa MatrixBase::nestByValue() - */ +namespace Eigen { namespace internal { -template -struct traits > : public traits -{}; -} +template +struct traits > : public traits { + enum { Flags = traits::Flags & ~NestByRefBit }; +}; +} // namespace internal -template class NestByValue - : public internal::dense_xpr_base< NestByValue >::type -{ - public: - - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue) - - inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {} - - inline Index rows() const { return m_expression.rows(); } - inline Index cols() const { return m_expression.cols(); } - inline Index outerStride() const { return m_expression.outerStride(); } - inline Index innerStride() const { return m_expression.innerStride(); } - - inline const CoeffReturnType coeff(Index row, Index col) const - { - return m_expression.coeff(row, col); - } - - inline Scalar& coeffRef(Index row, Index col) - { - return m_expression.const_cast_derived().coeffRef(row, col); - } - - inline const CoeffReturnType coeff(Index index) const - { - return m_expression.coeff(index); - } - - inline Scalar& coeffRef(Index index) - { - return m_expression.const_cast_derived().coeffRef(index); - } - - template - inline const PacketScalar packet(Index row, Index col) const - { - return m_expression.template packet(row, col); - } - - template - inline void writePacket(Index row, Index col, const PacketScalar& x) - { - m_expression.const_cast_derived().template writePacket(row, col, x); - } - - template - inline const PacketScalar packet(Index index) const - { - return m_expression.template packet(index); - } - - template - inline void writePacket(Index index, const PacketScalar& x) - { - m_expression.const_cast_derived().template writePacket(index, x); - } - - operator const ExpressionType&() const { return m_expression; } - - protected: - const ExpressionType m_expression; +/** \class NestByValue + * \ingroup Core_Module + * + * \brief Expression which must be nested by value + * + * \tparam ExpressionType the type of the object of which we are requiring nesting-by-value + * + * This class is the return type of MatrixBase::nestByValue() + * and most of the time this is the only way it is used. + * + * \sa MatrixBase::nestByValue() + */ +template +class NestByValue : public internal::dense_xpr_base >::type { + public: + typedef typename internal::dense_xpr_base::type Base; + static constexpr bool HasDirectAccess = internal::has_direct_access::ret; + + EIGEN_DENSE_PUBLIC_INTERFACE(NestByValue) + + EIGEN_DEVICE_FUNC explicit inline NestByValue(const ExpressionType& matrix) : m_expression(matrix) {} + + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_expression.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_expression.cols(); } + + EIGEN_DEVICE_FUNC operator const ExpressionType&() const { return m_expression; } + + EIGEN_DEVICE_FUNC const ExpressionType& nestedExpression() const { return m_expression; } + + EIGEN_DEVICE_FUNC typename std::enable_if::type data() const { + return m_expression.data(); + } + + EIGEN_DEVICE_FUNC typename std::enable_if::type innerStride() const { + return m_expression.innerStride(); + } + + EIGEN_DEVICE_FUNC typename std::enable_if::type outerStride() const { + return m_expression.outerStride(); + } + + protected: + const ExpressionType m_expression; }; /** \returns an expression of the temporary version of *this. - */ -template -inline const NestByValue -DenseBase::nestByValue() const -{ + */ +template +EIGEN_DEVICE_FUNC inline const NestByValue DenseBase::nestByValue() const { return NestByValue(derived()); } -} // end namespace Eigen +namespace internal { + +// Evaluator of Solve -> eval into a temporary +template +struct evaluator > : public evaluator { + typedef evaluator Base; + + EIGEN_DEVICE_FUNC explicit evaluator(const NestByValue& xpr) : Base(xpr.nestedExpression()) {} +}; +} // namespace internal + +} // end namespace Eigen -#endif // EIGEN_NESTBYVALUE_H +#endif // EIGEN_NESTBYVALUE_H diff --git a/inst/include/Eigen/src/Core/NoAlias.h b/inst/include/Eigen/src/Core/NoAlias.h index 768bfb18..b6c72091 100644 --- a/inst/include/Eigen/src/Core/NoAlias.h +++ b/inst/include/Eigen/src/Core/NoAlias.h @@ -10,125 +10,93 @@ #ifndef EIGEN_NOALIAS_H #define EIGEN_NOALIAS_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { /** \class NoAlias - * \ingroup Core_Module - * - * \brief Pseudo expression providing an operator = assuming no aliasing - * - * \param ExpressionType the type of the object on which to do the lazy assignment - * - * This class represents an expression with special assignment operators - * assuming no aliasing between the target expression and the source expression. - * More precisely it alloas to bypass the EvalBeforeAssignBit flag of the source expression. - * It is the return type of MatrixBase::noalias() - * and most of the time this is the only way it is used. - * - * \sa MatrixBase::noalias() - */ -template class StorageBase> -class NoAlias -{ - typedef typename ExpressionType::Scalar Scalar; - public: - NoAlias(ExpressionType& expression) : m_expression(expression) {} - - /** Behaves like MatrixBase::lazyAssign(other) - * \sa MatrixBase::lazyAssign() */ - template - EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase& other) - { return internal::assign_selector::run(m_expression,other.derived()); } - - /** \sa MatrixBase::operator+= */ - template - EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase& other) - { - typedef SelfCwiseBinaryOp, ExpressionType, OtherDerived> SelfAdder; - SelfAdder tmp(m_expression); - typedef typename internal::nested::type OtherDerivedNested; - typedef typename internal::remove_all::type _OtherDerivedNested; - internal::assign_selector::run(tmp,OtherDerivedNested(other.derived())); - return m_expression; - } - - /** \sa MatrixBase::operator-= */ - template - EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase& other) - { - typedef SelfCwiseBinaryOp, ExpressionType, OtherDerived> SelfAdder; - SelfAdder tmp(m_expression); - typedef typename internal::nested::type OtherDerivedNested; - typedef typename internal::remove_all::type _OtherDerivedNested; - internal::assign_selector::run(tmp,OtherDerivedNested(other.derived())); - return m_expression; - } + * \ingroup Core_Module + * + * \brief Pseudo expression providing an operator = assuming no aliasing + * + * \tparam ExpressionType the type of the object on which to do the lazy assignment + * + * This class represents an expression with special assignment operators + * assuming no aliasing between the target expression and the source expression. + * More precisely it alloas to bypass the EvalBeforeAssignBit flag of the source expression. + * It is the return type of MatrixBase::noalias() + * and most of the time this is the only way it is used. + * + * \sa MatrixBase::noalias() + */ +template class StorageBase> +class NoAlias { + public: + typedef typename ExpressionType::Scalar Scalar; -#ifndef EIGEN_PARSED_BY_DOXYGEN - template - EIGEN_STRONG_INLINE ExpressionType& operator+=(const ProductBase& other) - { other.derived().addTo(m_expression); return m_expression; } + EIGEN_DEVICE_FUNC explicit NoAlias(ExpressionType& expression) : m_expression(expression) {} - template - EIGEN_STRONG_INLINE ExpressionType& operator-=(const ProductBase& other) - { other.derived().subTo(m_expression); return m_expression; } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ExpressionType& operator=(const StorageBase& other) { + call_assignment_no_alias(m_expression, other.derived(), + internal::assign_op()); + return m_expression; + } - template - EIGEN_STRONG_INLINE ExpressionType& operator+=(const CoeffBasedProduct& other) - { return m_expression.derived() += CoeffBasedProduct(other.lhs(), other.rhs()); } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ExpressionType& operator+=(const StorageBase& other) { + call_assignment_no_alias(m_expression, other.derived(), + internal::add_assign_op()); + return m_expression; + } - template - EIGEN_STRONG_INLINE ExpressionType& operator-=(const CoeffBasedProduct& other) - { return m_expression.derived() -= CoeffBasedProduct(other.lhs(), other.rhs()); } - - template - ExpressionType& operator=(const ReturnByValue& func) - { return m_expression = func; } -#endif + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE ExpressionType& operator-=(const StorageBase& other) { + call_assignment_no_alias(m_expression, other.derived(), + internal::sub_assign_op()); + return m_expression; + } - ExpressionType& expression() const - { - return m_expression; - } + EIGEN_DEVICE_FUNC ExpressionType& expression() const { return m_expression; } - protected: - ExpressionType& m_expression; + protected: + ExpressionType& m_expression; }; /** \returns a pseudo expression of \c *this with an operator= assuming - * no aliasing between \c *this and the source expression. - * - * More precisely, noalias() allows to bypass the EvalBeforeAssignBit flag. - * Currently, even though several expressions may alias, only product - * expressions have this flag. Therefore, noalias() is only usefull when - * the source expression contains a matrix product. - * - * Here are some examples where noalias is usefull: - * \code - * D.noalias() = A * B; - * D.noalias() += A.transpose() * B; - * D.noalias() -= 2 * A * B.adjoint(); - * \endcode - * - * On the other hand the following example will lead to a \b wrong result: - * \code - * A.noalias() = A * B; - * \endcode - * because the result matrix A is also an operand of the matrix product. Therefore, - * there is no alternative than evaluating A * B in a temporary, that is the default - * behavior when you write: - * \code - * A = A * B; - * \endcode - * - * \sa class NoAlias - */ -template -NoAlias MatrixBase::noalias() -{ - return derived(); + * no aliasing between \c *this and the source expression. + * + * More precisely, noalias() allows to bypass the EvalBeforeAssignBit flag. + * Currently, even though several expressions may alias, only product + * expressions have this flag. Therefore, noalias() is only useful when + * the source expression contains a matrix product. + * + * Here are some examples where noalias is useful: + * \code + * D.noalias() = A * B; + * D.noalias() += A.transpose() * B; + * D.noalias() -= 2 * A * B.adjoint(); + * \endcode + * + * On the other hand the following example will lead to a \b wrong result: + * \code + * A.noalias() = A * B; + * \endcode + * because the result matrix A is also an operand of the matrix product. Therefore, + * there is no alternative than evaluating A * B in a temporary, that is the default + * behavior when you write: + * \code + * A = A * B; + * \endcode + * + * \sa class NoAlias + */ +template +NoAlias EIGEN_DEVICE_FUNC MatrixBase::noalias() { + return NoAlias(derived()); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_NOALIAS_H +#endif // EIGEN_NOALIAS_H diff --git a/inst/include/Eigen/src/Core/NumTraits.h b/inst/include/Eigen/src/Core/NumTraits.h index bac9e50b..bf41c3bb 100644 --- a/inst/include/Eigen/src/Core/NumTraits.h +++ b/inst/include/Eigen/src/Core/NumTraits.h @@ -10,46 +10,183 @@ #ifndef EIGEN_NUMTRAITS_H #define EIGEN_NUMTRAITS_H +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { -/** \class NumTraits - * \ingroup Core_Module - * - * \brief Holds information about the various numeric (i.e. scalar) types allowed by Eigen. - * - * \param T the numeric type at hand - * - * This class stores enums, typedefs and static methods giving information about a numeric type. - * - * The provided data consists of: - * \li A typedef \a Real, giving the "real part" type of \a T. If \a T is already real, - * then \a Real is just a typedef to \a T. If \a T is \c std::complex then \a Real - * is a typedef to \a U. - * \li A typedef \a NonInteger, giving the type that should be used for operations producing non-integral values, - * such as quotients, square roots, etc. If \a T is a floating-point type, then this typedef just gives - * \a T again. Note however that many Eigen functions such as internal::sqrt simply refuse to - * take integers. Outside of a few cases, Eigen doesn't do automatic type promotion. Thus, this typedef is - * only intended as a helper for code that needs to explicitly promote types. - * \li A typedef \a Nested giving the type to use to nest a value inside of the expression tree. If you don't know what - * this means, just use \a T here. - * \li An enum value \a IsComplex. It is equal to 1 if \a T is a \c std::complex - * type, and to 0 otherwise. - * \li An enum value \a IsInteger. It is equal to \c 1 if \a T is an integer type such as \c int, - * and to \c 0 otherwise. - * \li Enum values ReadCost, AddCost and MulCost representing a rough estimate of the number of CPU cycles needed - * to by move / add / mul instructions respectively, assuming the data is already stored in CPU registers. - * Stay vague here. No need to do architecture-specific stuff. - * \li An enum value \a IsSigned. It is equal to \c 1 if \a T is a signed type and to 0 if \a T is unsigned. - * \li An enum value \a RequireInitialization. It is equal to \c 1 if the constructor of the numeric type \a T must - * be called, and to 0 if it is safe not to call it. Default is 0 if \a T is an arithmetic type, and 1 otherwise. - * \li An epsilon() function which, unlike std::numeric_limits::epsilon(), returns a \a Real instead of a \a T. - * \li A dummy_precision() function returning a weak epsilon value. It is mainly used as a default - * value by the fuzzy comparison operators. - * \li highest() and lowest() functions returning the highest and lowest possible values respectively. - */ - -template struct GenericNumTraits +namespace internal { + +// default implementation of digits(), based on numeric_limits if specialized, +// 0 for integer types, and log2(epsilon()) otherwise. +template ::is_specialized, + bool is_integer = NumTraits::IsInteger> +struct default_digits_impl { + EIGEN_DEVICE_FUNC constexpr static int run() { return std::numeric_limits::digits; } +}; + +template +struct default_digits_impl // Floating point +{ + EIGEN_DEVICE_FUNC constexpr static int run() { + using std::ceil; + using std::log2; + typedef typename NumTraits::Real Real; + return int(ceil(-log2(NumTraits::epsilon()))); + } +}; + +template +struct default_digits_impl // Integer { + EIGEN_DEVICE_FUNC constexpr static int run() { return 0; } +}; + +// default implementation of digits10(), based on numeric_limits if specialized, +// 0 for integer types, and floor((digits()-1)*log10(2)) otherwise. +template ::is_specialized, + bool is_integer = NumTraits::IsInteger> +struct default_digits10_impl { + EIGEN_DEVICE_FUNC constexpr static int run() { return std::numeric_limits::digits10; } +}; + +template +struct default_digits10_impl // Floating point +{ + EIGEN_DEVICE_FUNC constexpr static int run() { + using std::floor; + using std::log10; + typedef typename NumTraits::Real Real; + return int(floor((internal::default_digits_impl::run() - 1) * log10(2))); + } +}; + +template +struct default_digits10_impl // Integer +{ + EIGEN_DEVICE_FUNC constexpr static int run() { return 0; } +}; + +// default implementation of max_digits10(), based on numeric_limits if specialized, +// 0 for integer types, and log10(2) * digits() + 1 otherwise. +template ::is_specialized, + bool is_integer = NumTraits::IsInteger> +struct default_max_digits10_impl { + EIGEN_DEVICE_FUNC constexpr static int run() { return std::numeric_limits::max_digits10; } +}; + +template +struct default_max_digits10_impl // Floating point +{ + EIGEN_DEVICE_FUNC constexpr static int run() { + using std::ceil; + using std::log10; + typedef typename NumTraits::Real Real; + return int(ceil(internal::default_digits_impl::run() * log10(2) + 1)); + } +}; + +template +struct default_max_digits10_impl // Integer +{ + EIGEN_DEVICE_FUNC constexpr static int run() { return 0; } +}; + +} // end namespace internal + +namespace numext { + +/** \internal bit-wise cast without changing the underlying bit representation. */ +#if defined(__cpp_lib_bit_cast) && __cpp_lib_bit_cast >= 201806L +template +EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr Tgt bit_cast(const Src& src) { + return std::bit_cast(src); +} +#elif EIGEN_HAS_BUILTIN(__builtin_bit_cast) +template +EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC constexpr Tgt bit_cast(const Src& src) { + EIGEN_STATIC_ASSERT(std::is_trivially_copyable::value, THIS_TYPE_IS_NOT_SUPPORTED) + EIGEN_STATIC_ASSERT(std::is_trivially_copyable::value, THIS_TYPE_IS_NOT_SUPPORTED) + EIGEN_STATIC_ASSERT(sizeof(Src) == sizeof(Tgt), THIS_TYPE_IS_NOT_SUPPORTED) + return __builtin_bit_cast(Tgt, src); +} +#else +template +EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC Tgt bit_cast(const Src& src) { + // The behaviour of memcpy is not specified for non-trivially copyable types + EIGEN_STATIC_ASSERT(std::is_trivially_copyable::value, THIS_TYPE_IS_NOT_SUPPORTED) + EIGEN_STATIC_ASSERT(std::is_trivially_copyable::value && std::is_default_constructible::value, + THIS_TYPE_IS_NOT_SUPPORTED) + EIGEN_STATIC_ASSERT(sizeof(Src) == sizeof(Tgt), THIS_TYPE_IS_NOT_SUPPORTED) + + Tgt tgt; + // Load src into registers first. This allows the memcpy to be elided by CUDA. + const Src staged = src; + EIGEN_USING_STD(memcpy) + memcpy(static_cast(&tgt), static_cast(&staged), sizeof(Tgt)); + return tgt; +} +#endif +} // namespace numext + +// clang-format off +/** \class NumTraits + * \ingroup Core_Module + * + * \brief Holds information about the various numeric (i.e. scalar) types allowed by Eigen. + * + * \tparam T the numeric type at hand + * + * This class stores enums, typedefs and static methods giving information about a numeric type. + * + * The provided data consists of: + * \li A typedef \c Real, giving the "real part" type of \a T. If \a T is already real, + * then \c Real is just a typedef to \a T. If \a T is `std::complex` then \c Real + * is a typedef to \a U. + * \li A typedef \c NonInteger, giving the type that should be used for operations producing non-integral values, + * such as quotients, square roots, etc. If \a T is a floating-point type, then this typedef just gives + * \a T again. Note however that many Eigen functions such as internal::sqrt simply refuse to + * take integers. Outside of a few cases, Eigen doesn't do automatic type promotion. Thus, this typedef is + * only intended as a helper for code that needs to explicitly promote types. + * \li A typedef \c Literal giving the type to use for numeric literals such as "2" or "0.5". For instance, for + * `std::complex`, Literal is defined as \a U. Of course, this type must be fully compatible with \a T. In doubt, + * just use \a T here. + * \li A typedef \c Nested giving the type to use to nest a value inside of the expression tree. If you don't know what + * this means, just use \a T here. + * \li An enum value \c IsComplex. It is equal to 1 if \a T is a \c std::complex type, and to 0 otherwise. + * \li An enum value \c IsInteger. It is equal to \c 1 if \a T is an integer type such as \c int, and to \c 0 otherwise. + * \li Enum values \c ReadCost, \c AddCost and \c MulCost representing a rough estimate of the number of CPU cycles needed to by + * move / add / mul instructions respectively, assuming the data is already stored in CPU registers. Stay vague here. + * No need to do architecture-specific stuff. If you don't know what this means, just use \c Eigen::HugeCost. + * \li An enum value \c IsSigned. It is equal to \c 1 if \a T is a signed type and to 0 if \a T is unsigned. + * \li An enum value \c RequireInitialization. It is equal to \c 1 if the constructor of the numeric type \a T must be + * called, and to 0 if it is safe not to call it. Default is 0 if \a T is an arithmetic type, and 1 otherwise. + * \li An epsilon() function which, unlike + * `std::numeric_limits::epsilon()`, it returns a \c Real instead of a \a T. + * \li A dummy_precision() function returning a weak epsilon value. It is mainly used as a default value by the fuzzy + * comparison operators. + * \li highest() and lowest() functions returning the highest and lowest possible values respectively. + * \li digits() function returning the number of radix digits (non-sign digits for integers, mantissa for floating-point). + * This is the analogue of + * `std::numeric_limits::digits` which is used as the default implementation if specialized. + * \li digits10() function returning the number of decimal digits that can be represented without change. This is the + * analogue of + * `std::numeric_limits::digits10` which is used as the default implementation if specialized. + * \li max_digits10() function returning the number of decimal digits required to uniquely represent all distinct values + * of the type. This is the analogue of `std::numeric_limits::max_digits10` + * which is used as the default implementation if specialized. + * \li min_exponent() and max_exponent() functions returning the highest and lowest possible values, respectively, + * such that the radix raised to the power exponent-1 is a normalized floating-point number. These are equivalent + * to + * `std::numeric_limits::min_exponent`/`std::numeric_limits::max_exponent`. + * \li infinity() function returning a representation of positive infinity, if available. + * \li quiet_NaN() function returning a non-signaling "not-a-number", if available. + */ +// clang-format on +template +struct GenericNumTraits { enum { IsInteger = std::numeric_limits::is_integer, IsSigned = std::numeric_limits::is_signed, @@ -61,90 +198,138 @@ template struct GenericNumTraits }; typedef T Real; - typedef typename internal::conditional< - IsInteger, - typename internal::conditional::type, - T - >::type NonInteger; + typedef std::conditional_t, T> NonInteger; typedef T Nested; + typedef T Literal; + + EIGEN_DEVICE_FUNC constexpr static Real epsilon() { return numext::numeric_limits::epsilon(); } + + EIGEN_DEVICE_FUNC constexpr static int digits10() { return internal::default_digits10_impl::run(); } + + EIGEN_DEVICE_FUNC constexpr static int max_digits10() { return internal::default_max_digits10_impl::run(); } - static inline Real epsilon() { return std::numeric_limits::epsilon(); } - static inline Real dummy_precision() - { + EIGEN_DEVICE_FUNC constexpr static int digits() { return internal::default_digits_impl::run(); } + + EIGEN_DEVICE_FUNC constexpr static int min_exponent() { return numext::numeric_limits::min_exponent; } + + EIGEN_DEVICE_FUNC constexpr static int max_exponent() { return numext::numeric_limits::max_exponent; } + + EIGEN_DEVICE_FUNC constexpr static Real dummy_precision() { // make sure to override this for floating-point types return Real(0); } - static inline T highest() { return (std::numeric_limits::max)(); } - static inline T lowest() { return IsInteger ? (std::numeric_limits::min)() : (-(std::numeric_limits::max)()); } - -#ifdef EIGEN2_SUPPORT - enum { - HasFloatingPoint = !IsInteger - }; - typedef NonInteger FloatingPoint; -#endif + + EIGEN_DEVICE_FUNC constexpr static T highest() { return (numext::numeric_limits::max)(); } + + EIGEN_DEVICE_FUNC constexpr static T lowest() { return (numext::numeric_limits::lowest)(); } + + EIGEN_DEVICE_FUNC constexpr static T infinity() { return numext::numeric_limits::infinity(); } + + EIGEN_DEVICE_FUNC constexpr static T quiet_NaN() { return numext::numeric_limits::quiet_NaN(); } }; -template struct NumTraits : GenericNumTraits -{}; +template +struct NumTraits : GenericNumTraits {}; -template<> struct NumTraits - : GenericNumTraits -{ - static inline float dummy_precision() { return 1e-5f; } +template <> +struct NumTraits : GenericNumTraits { + EIGEN_DEVICE_FUNC constexpr static float dummy_precision() { return 1e-5f; } }; -template<> struct NumTraits : GenericNumTraits -{ - static inline double dummy_precision() { return 1e-12; } +template <> +struct NumTraits : GenericNumTraits { + EIGEN_DEVICE_FUNC constexpr static double dummy_precision() { return 1e-12; } }; -template<> struct NumTraits - : GenericNumTraits -{ - static inline long double dummy_precision() { return 1e-15l; } +// GPU devices treat `long double` as `double`. +#ifndef EIGEN_GPU_COMPILE_PHASE +template <> +struct NumTraits : GenericNumTraits { + EIGEN_DEVICE_FUNC constexpr static long double dummy_precision() { return static_cast(1e-15l); } + +#if defined(EIGEN_ARCH_PPC) && (__LDBL_MANT_DIG__ == 106) + // PowerPC double double causes issues with some values + EIGEN_DEVICE_FUNC constexpr static long double epsilon() { + // 2^(-(__LDBL_MANT_DIG__)+1) + return static_cast(2.4651903288156618919116517665087e-32l); + } +#endif }; +#endif -template struct NumTraits > - : GenericNumTraits > -{ - typedef _Real Real; +template +struct NumTraits > : GenericNumTraits > { + typedef Real_ Real; + typedef typename NumTraits::Literal Literal; enum { IsComplex = 1, - RequireInitialization = NumTraits<_Real>::RequireInitialization, - ReadCost = 2 * NumTraits<_Real>::ReadCost, + IsSigned = NumTraits::IsSigned, + RequireInitialization = NumTraits::RequireInitialization, + ReadCost = 2 * NumTraits::ReadCost, AddCost = 2 * NumTraits::AddCost, MulCost = 4 * NumTraits::MulCost + 2 * NumTraits::AddCost }; - static inline Real epsilon() { return NumTraits::epsilon(); } - static inline Real dummy_precision() { return NumTraits::dummy_precision(); } + EIGEN_DEVICE_FUNC constexpr static Real epsilon() { return NumTraits::epsilon(); } + EIGEN_DEVICE_FUNC constexpr static Real dummy_precision() { return NumTraits::dummy_precision(); } + EIGEN_DEVICE_FUNC constexpr static int digits10() { return NumTraits::digits10(); } + EIGEN_DEVICE_FUNC constexpr static int max_digits10() { return NumTraits::max_digits10(); } }; -template -struct NumTraits > -{ +template +struct NumTraits > { typedef Array ArrayType; typedef typename NumTraits::Real RealScalar; typedef Array Real; typedef typename NumTraits::NonInteger NonIntegerScalar; typedef Array NonInteger; - typedef ArrayType & Nested; - + typedef ArrayType& Nested; + typedef typename NumTraits::Literal Literal; + enum { IsComplex = NumTraits::IsComplex, IsInteger = NumTraits::IsInteger, - IsSigned = NumTraits::IsSigned, + IsSigned = NumTraits::IsSigned, RequireInitialization = 1, - ReadCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits::ReadCost, - AddCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits::AddCost, - MulCost = ArrayType::SizeAtCompileTime==Dynamic ? Dynamic : ArrayType::SizeAtCompileTime * NumTraits::MulCost + ReadCost = ArrayType::SizeAtCompileTime == Dynamic + ? HugeCost + : ArrayType::SizeAtCompileTime * int(NumTraits::ReadCost), + AddCost = ArrayType::SizeAtCompileTime == Dynamic ? HugeCost + : ArrayType::SizeAtCompileTime * int(NumTraits::AddCost), + MulCost = ArrayType::SizeAtCompileTime == Dynamic ? HugeCost + : ArrayType::SizeAtCompileTime * int(NumTraits::MulCost) }; - - static inline RealScalar epsilon() { return NumTraits::epsilon(); } - static inline RealScalar dummy_precision() { return NumTraits::dummy_precision(); } + + EIGEN_DEVICE_FUNC constexpr static RealScalar epsilon() { return NumTraits::epsilon(); } + EIGEN_DEVICE_FUNC constexpr static RealScalar dummy_precision() { return NumTraits::dummy_precision(); } + + constexpr static int digits10() { return NumTraits::digits10(); } + constexpr static int max_digits10() { return NumTraits::max_digits10(); } +}; + +template <> +struct NumTraits : GenericNumTraits { + enum { RequireInitialization = 1, ReadCost = HugeCost, AddCost = HugeCost, MulCost = HugeCost }; + + constexpr static int digits10() { return 0; } + constexpr static int max_digits10() { return 0; } + + private: + static inline std::string epsilon(); + static inline std::string dummy_precision(); + static inline std::string lowest(); + static inline std::string highest(); + static inline std::string infinity(); + static inline std::string quiet_NaN(); }; -} // end namespace Eigen +// Empty specialization for void to allow template specialization based on NumTraits::Real with T==void and SFINAE. +template <> +struct NumTraits {}; + +template <> +struct NumTraits : GenericNumTraits {}; + +} // end namespace Eigen -#endif // EIGEN_NUMTRAITS_H +#endif // EIGEN_NUMTRAITS_H diff --git a/inst/include/Eigen/src/Core/PartialReduxEvaluator.h b/inst/include/Eigen/src/Core/PartialReduxEvaluator.h new file mode 100644 index 00000000..1f638f9a --- /dev/null +++ b/inst/include/Eigen/src/Core/PartialReduxEvaluator.h @@ -0,0 +1,253 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2011-2018 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_PARTIALREDUX_H +#define EIGEN_PARTIALREDUX_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +/*************************************************************************** + * + * This file provides evaluators for partial reductions. + * There are two modes: + * + * - scalar path: simply calls the respective function on the column or row. + * -> nothing special here, all the tricky part is handled by the return + * types of VectorwiseOp's members. They embed the functor calling the + * respective DenseBase's member function. + * + * - vectorized path: implements a packet-wise reductions followed by + * some (optional) processing of the outcome, e.g., division by n for mean. + * + * For the vectorized path let's observe that the packet-size and outer-unrolling + * are both decided by the assignment logic. So all we have to do is to decide + * on the inner unrolling. + * + * For the unrolling, we can reuse "internal::redux_vec_unroller" from Redux.h, + * but be need to be careful to specify correct increment. + * + ***************************************************************************/ + +/* logic deciding a strategy for unrolling of vectorized paths */ +template +struct packetwise_redux_traits { + enum { + OuterSize = int(Evaluator::IsRowMajor) ? Evaluator::RowsAtCompileTime : Evaluator::ColsAtCompileTime, + Cost = OuterSize == Dynamic ? HugeCost + : OuterSize * Evaluator::CoeffReadCost + (OuterSize - 1) * functor_traits::Cost, + Unrolling = Cost <= EIGEN_UNROLLING_LIMIT ? CompleteUnrolling : NoUnrolling + }; +}; + +/* Value to be returned when size==0 , by default let's return 0 */ +template +EIGEN_DEVICE_FUNC PacketType packetwise_redux_empty_value(const Func&) { + const typename unpacket_traits::type zero(0); + return pset1(zero); +} + +/* For products the default is 1 */ +template +EIGEN_DEVICE_FUNC PacketType packetwise_redux_empty_value(const scalar_product_op&) { + return pset1(Scalar(1)); +} + +/* Perform the actual reduction */ +template ::Unrolling> +struct packetwise_redux_impl; + +/* Perform the actual reduction with unrolling */ +template +struct packetwise_redux_impl { + typedef redux_novec_unroller Base; + typedef typename Evaluator::Scalar Scalar; + + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func& func, Index /*size*/) { + return redux_vec_unroller::OuterSize>::template run(eval, + func); + } +}; + +/* Add a specialization of redux_vec_unroller for size==0 at compiletime. + * This specialization is not required for general reductions, which is + * why it is defined here. + */ +template +struct redux_vec_unroller { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator&, const Func& f) { + return packetwise_redux_empty_value(f); + } +}; + +/* Perform the actual reduction for dynamic sizes */ +template +struct packetwise_redux_impl { + typedef typename Evaluator::Scalar Scalar; + typedef typename redux_traits::PacketType PacketScalar; + + template + EIGEN_DEVICE_FUNC static PacketType run(const Evaluator& eval, const Func& func, Index size) { + if (size == 0) return packetwise_redux_empty_value(func); + + const Index size4 = 1 + numext::round_down(size - 1, 4); + PacketType p = eval.template packetByOuterInner(0, 0); + // This loop is optimized for instruction pipelining: + // - each iteration generates two independent instructions + // - thanks to branch prediction and out-of-order execution we have independent instructions across loops + for (Index i = 1; i < size4; i += 4) + p = func.packetOp( + p, func.packetOp(func.packetOp(eval.template packetByOuterInner(i + 0, 0), + eval.template packetByOuterInner(i + 1, 0)), + func.packetOp(eval.template packetByOuterInner(i + 2, 0), + eval.template packetByOuterInner(i + 3, 0)))); + for (Index i = size4; i < size; ++i) + p = func.packetOp(p, eval.template packetByOuterInner(i, 0)); + return p; + } +}; + +template +struct packetwise_segment_redux_impl { + typedef typename Evaluator::Scalar Scalar; + typedef typename redux_traits::PacketType PacketScalar; + + template + EIGEN_DEVICE_FUNC static PacketType run(const Evaluator& eval, const Func& func, Index size, Index begin, + Index count) { + if (size == 0) return packetwise_redux_empty_value(func); + + PacketType p = eval.template packetSegmentByOuterInner(0, 0, begin, count); + for (Index i = 1; i < size; ++i) + p = func.packetOp(p, eval.template packetSegmentByOuterInner(i, 0, begin, count)); + return p; + } +}; + +template +struct evaluator > + : evaluator_base > { + typedef PartialReduxExpr XprType; + typedef typename internal::nested_eval::type ArgTypeNested; + typedef add_const_on_value_type_t ConstArgTypeNested; + typedef internal::remove_all_t ArgTypeNestedCleaned; + typedef typename ArgType::Scalar InputScalar; + typedef typename XprType::Scalar Scalar; + enum { + TraversalSize = Direction == int(Vertical) ? int(ArgType::RowsAtCompileTime) : int(ArgType::ColsAtCompileTime) + }; + typedef typename MemberOp::template Cost CostOpType; + enum { + CoeffReadCost = TraversalSize == Dynamic ? HugeCost + : TraversalSize == 0 + ? 1 + : int(TraversalSize) * int(evaluator::CoeffReadCost) + int(CostOpType::value), + + ArgFlags_ = evaluator::Flags, + + Vectorizable_ = bool(int(ArgFlags_) & PacketAccessBit) && bool(MemberOp::Vectorizable) && + (Direction == int(Vertical) ? bool(ArgFlags_ & RowMajorBit) : (ArgFlags_ & RowMajorBit) == 0) && + (TraversalSize != 0), + + Flags = (traits::Flags & RowMajorBit) | (evaluator::Flags & (HereditaryBits & (~RowMajorBit))) | + (Vectorizable_ ? PacketAccessBit : 0) | LinearAccessBit, + + Alignment = 0 // FIXME this will need to be improved once PartialReduxExpr is vectorized + }; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType xpr) : m_arg(xpr.nestedExpression()), m_functor(xpr.functor()) { + EIGEN_INTERNAL_CHECK_COST_VALUE(TraversalSize == Dynamic ? HugeCost + : (TraversalSize == 0 ? 1 : int(CostOpType::value))); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index i, Index j) const { + return coeff(Direction == Vertical ? j : i); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index index) const { + return m_functor(m_arg.template subVector(index)); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index i, Index j) const { + return packet(Direction == Vertical ? j : i); + } + + template + EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC PacketType packet(Index idx) const { + static constexpr int PacketSize = internal::unpacket_traits::size; + static constexpr int PanelRows = Direction == Vertical ? ArgType::RowsAtCompileTime : PacketSize; + static constexpr int PanelCols = Direction == Vertical ? PacketSize : ArgType::ColsAtCompileTime; + using PanelType = Block; + using PanelEvaluator = typename internal::redux_evaluator; + using BinaryOp = typename MemberOp::BinaryOp; + using Impl = internal::packetwise_redux_impl; + + // FIXME + // See bug 1612, currently if PacketSize==1 (i.e. complex with 128bits registers) then the storage-order of + // panel get reversed and methods like packetByOuterInner do not make sense anymore in this context. So let's just + // by pass "vectorization" in this case: + if (PacketSize == 1) return internal::pset1(coeff(idx)); + + Index startRow = Direction == Vertical ? 0 : idx; + Index startCol = Direction == Vertical ? idx : 0; + Index numRows = Direction == Vertical ? m_arg.rows() : PacketSize; + Index numCols = Direction == Vertical ? PacketSize : m_arg.cols(); + + PanelType panel(m_arg, startRow, startCol, numRows, numCols); + PanelEvaluator panel_eval(panel); + PacketType p = Impl::template run(panel_eval, m_functor.binaryFunc(), m_arg.outerSize()); + return p; + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index i, Index j, Index begin, Index count) const { + return packetSegment(Direction == Vertical ? j : i, begin, count); + } + + template + EIGEN_STRONG_INLINE EIGEN_DEVICE_FUNC PacketType packetSegment(Index idx, Index begin, Index count) const { + static constexpr int PanelRows = Direction == Vertical ? ArgType::RowsAtCompileTime : Dynamic; + static constexpr int PanelCols = Direction == Vertical ? Dynamic : ArgType::ColsAtCompileTime; + using PanelType = Block; + using PanelEvaluator = typename internal::redux_evaluator; + using BinaryOp = typename MemberOp::BinaryOp; + using Impl = internal::packetwise_segment_redux_impl; + + Index startRow = Direction == Vertical ? 0 : idx; + Index startCol = Direction == Vertical ? idx : 0; + Index numRows = Direction == Vertical ? m_arg.rows() : begin + count; + Index numCols = Direction == Vertical ? begin + count : m_arg.cols(); + + PanelType panel(m_arg, startRow, startCol, numRows, numCols); + PanelEvaluator panel_eval(panel); + PacketType p = Impl::template run(panel_eval, m_functor.binaryFunc(), m_arg.outerSize(), begin, count); + return p; + } + + protected: + ConstArgTypeNested m_arg; + const MemberOp m_functor; +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_PARTIALREDUX_H diff --git a/inst/include/Eigen/src/Core/PermutationMatrix.h b/inst/include/Eigen/src/Core/PermutationMatrix.h index 85ffae26..77133545 100644 --- a/inst/include/Eigen/src/Core/PermutationMatrix.h +++ b/inst/include/Eigen/src/Core/PermutationMatrix.h @@ -2,7 +2,7 @@ // for linear algebra. // // Copyright (C) 2009 Benoit Jacob -// Copyright (C) 2009-2011 Gael Guennebaud +// Copyright (C) 2009-2015 Gael Guennebaud // // This Source Code Form is subject to the terms of the Mozilla // Public License v. 2.0. If a copy of the MPL was not distributed @@ -11,711 +11,545 @@ #ifndef EIGEN_PERMUTATIONMATRIX_H #define EIGEN_PERMUTATIONMATRIX_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -template class PermutedImpl; - -/** \class PermutationBase - * \ingroup Core_Module - * - * \brief Base class for permutations - * - * \param Derived the derived class - * - * This class is the base class for all expressions representing a permutation matrix, - * internally stored as a vector of integers. - * The convention followed here is that if \f$ \sigma \f$ is a permutation, the corresponding permutation matrix - * \f$ P_\sigma \f$ is such that if \f$ (e_1,\ldots,e_p) \f$ is the canonical basis, we have: - * \f[ P_\sigma(e_i) = e_{\sigma(i)}. \f] - * This convention ensures that for any two permutations \f$ \sigma, \tau \f$, we have: - * \f[ P_{\sigma\circ\tau} = P_\sigma P_\tau. \f] - * - * Permutation matrices are square and invertible. - * - * Notice that in addition to the member functions and operators listed here, there also are non-member - * operator* to multiply any kind of permutation object with any kind of matrix expression (MatrixBase) - * on either side. - * - * \sa class PermutationMatrix, class PermutationWrapper - */ +namespace Eigen { namespace internal { -template -struct permut_matrix_product_retval; -template -struct permut_sparsematrix_product_retval; -enum PermPermProduct_t {PermPermProduct}; - -} // end namespace internal - -template -class PermutationBase : public EigenBase -{ - typedef internal::traits Traits; - typedef EigenBase Base; - public: - - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef typename Traits::IndicesType IndicesType; - enum { - Flags = Traits::Flags, - CoeffReadCost = Traits::CoeffReadCost, - RowsAtCompileTime = Traits::RowsAtCompileTime, - ColsAtCompileTime = Traits::ColsAtCompileTime, - MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime, - MaxColsAtCompileTime = Traits::MaxColsAtCompileTime - }; - typedef typename Traits::Scalar Scalar; - typedef typename Traits::Index Index; - typedef Matrix - DenseMatrixType; - typedef PermutationMatrix - PlainPermutationType; - using Base::derived; - #endif - - /** Copies the other permutation into *this */ - template - Derived& operator=(const PermutationBase& other) - { - indices() = other.indices(); - return derived(); - } - - /** Assignment from the Transpositions \a tr */ - template - Derived& operator=(const TranspositionsBase& tr) - { - setIdentity(tr.size()); - for(Index k=size()-1; k>=0; --k) - applyTranspositionOnTheRight(k,tr.coeff(k)); - return derived(); - } +enum PermPermProduct_t { PermPermProduct }; - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - Derived& operator=(const PermutationBase& other) - { - indices() = other.indices(); - return derived(); - } - #endif +} // end namespace internal - /** \returns the number of rows */ - inline Index rows() const { return Index(indices().size()); } - - /** \returns the number of columns */ - inline Index cols() const { return Index(indices().size()); } - - /** \returns the size of a side of the respective square matrix, i.e., the number of indices */ - inline Index size() const { return Index(indices().size()); } +/** \class PermutationBase + * \ingroup Core_Module + * + * \brief Base class for permutations + * + * \tparam Derived the derived class + * + * This class is the base class for all expressions representing a permutation matrix, + * internally stored as a vector of integers. + * The convention followed here is that if \f$ \sigma \f$ is a permutation, the corresponding permutation matrix + * \f$ P_\sigma \f$ is such that if \f$ (e_1,\ldots,e_p) \f$ is the canonical basis, we have: + * \f[ P_\sigma(e_i) = e_{\sigma(i)}. \f] + * This convention ensures that for any two permutations \f$ \sigma, \tau \f$, we have: + * \f[ P_{\sigma\circ\tau} = P_\sigma P_\tau. \f] + * + * Permutation matrices are square and invertible. + * + * Notice that in addition to the member functions and operators listed here, there also are non-member + * operator* to multiply any kind of permutation object with any kind of matrix expression (MatrixBase) + * on either side. + * + * \sa class PermutationMatrix, class PermutationWrapper + */ +template +class PermutationBase : public EigenBase { + typedef internal::traits Traits; + typedef EigenBase Base; + + public: +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef typename Traits::IndicesType IndicesType; + enum { + Flags = Traits::Flags, + RowsAtCompileTime = Traits::RowsAtCompileTime, + ColsAtCompileTime = Traits::ColsAtCompileTime, + MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = Traits::MaxColsAtCompileTime + }; + typedef typename Traits::StorageIndex StorageIndex; + typedef Matrix + DenseMatrixType; + typedef PermutationMatrix + PlainPermutationType; + typedef PlainPermutationType PlainObject; + using Base::derived; + typedef Inverse InverseReturnType; + typedef void Scalar; +#endif - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - void evalTo(MatrixBase& other) const - { - other.setZero(); - for (int i=0; i + Derived& operator=(const PermutationBase& other) { + indices() = other.indices(); + return derived(); + } - /** const version of indices(). */ - const IndicesType& indices() const { return derived().indices(); } - /** \returns a reference to the stored array representing the permutation. */ - IndicesType& indices() { return derived().indices(); } + /** Assignment from the Transpositions \a tr */ + template + Derived& operator=(const TranspositionsBase& tr) { + setIdentity(tr.size()); + for (Index k = size() - 1; k >= 0; --k) applyTranspositionOnTheRight(k, tr.coeff(k)); + return derived(); + } - /** Resizes to given size. - */ - inline void resize(Index newSize) - { - indices().resize(newSize); - } + /** \returns the number of rows */ + inline EIGEN_DEVICE_FUNC Index rows() const { return Index(indices().size()); } - /** Sets *this to be the identity permutation matrix */ - void setIdentity() - { - for(Index i = 0; i < size(); ++i) - indices().coeffRef(i) = i; - } + /** \returns the number of columns */ + inline EIGEN_DEVICE_FUNC Index cols() const { return Index(indices().size()); } - /** Sets *this to be the identity permutation matrix of given size. - */ - void setIdentity(Index newSize) - { - resize(newSize); - setIdentity(); - } + /** \returns the size of a side of the respective square matrix, i.e., the number of indices */ + inline EIGEN_DEVICE_FUNC Index size() const { return Index(indices().size()); } - /** Multiplies *this by the transposition \f$(ij)\f$ on the left. - * - * \returns a reference to *this. - * - * \warning This is much slower than applyTranspositionOnTheRight(int,int): - * this has linear complexity and requires a lot of branching. - * - * \sa applyTranspositionOnTheRight(int,int) - */ - Derived& applyTranspositionOnTheLeft(Index i, Index j) - { - eigen_assert(i>=0 && j>=0 && i + void evalTo(MatrixBase& other) const { + other.setZero(); + for (Index i = 0; i < rows(); ++i) other.coeffRef(indices().coeff(i), i) = typename DenseDerived::Scalar(1); + } +#endif - /** Multiplies *this by the transposition \f$(ij)\f$ on the right. - * - * \returns a reference to *this. - * - * This is a fast operation, it only consists in swapping two indices. - * - * \sa applyTranspositionOnTheLeft(int,int) - */ - Derived& applyTranspositionOnTheRight(Index i, Index j) - { - eigen_assert(i>=0 && j>=0 && i= 0 && j >= 0 && i < size() && j < size()); + for (Index k = 0; k < size(); ++k) { + if (indices().coeff(k) == i) + indices().coeffRef(k) = StorageIndex(j); + else if (indices().coeff(k) == j) + indices().coeffRef(k) = StorageIndex(i); } + return derived(); + } + + /** Multiplies *this by the transposition \f$(ij)\f$ on the right. + * + * \returns a reference to *this. + * + * This is a fast operation, it only consists in swapping two indices. + * + * \sa applyTranspositionOnTheLeft(Index,Index) + */ + Derived& applyTranspositionOnTheRight(Index i, Index j) { + eigen_assert(i >= 0 && j >= 0 && i < size() && j < size()); + std::swap(indices().coeffRef(i), indices().coeffRef(j)); + return derived(); + } + + /** \returns the inverse permutation matrix. + * + * \note \blank \note_try_to_help_rvo + */ + inline InverseReturnType inverse() const { return InverseReturnType(derived()); } + /** \returns the transpose permutation matrix. + * + * \note \blank \note_try_to_help_rvo + */ + inline InverseReturnType transpose() const { return InverseReturnType(derived()); } + + /**** multiplication helpers to hopefully get RVO ****/ - /** \returns the inverse permutation matrix. - * - * \note \note_try_to_help_rvo - */ - inline Transpose inverse() const - { return derived(); } - /** \returns the tranpose permutation matrix. - * - * \note \note_try_to_help_rvo - */ - inline Transpose transpose() const - { return derived(); } - - /**** multiplication helpers to hopefully get RVO ****/ - - #ifndef EIGEN_PARSED_BY_DOXYGEN - protected: - template - void assignTranspose(const PermutationBase& other) - { - for (int i=0; i - void assignProduct(const Lhs& lhs, const Rhs& rhs) - { - eigen_assert(lhs.cols() == rhs.rows()); - for (int i=0; i + void assignTranspose(const PermutationBase& other) { + for (Index i = 0; i < rows(); ++i) indices().coeffRef(other.indices().coeff(i)) = i; + } + template + void assignProduct(const Lhs& lhs, const Rhs& rhs) { + eigen_assert(lhs.cols() == rhs.rows()); + for (Index i = 0; i < rows(); ++i) indices().coeffRef(i) = lhs.indices().coeff(rhs.indices().coeff(i)); + } #endif - public: - - /** \returns the product permutation matrix. - * - * \note \note_try_to_help_rvo - */ - template - inline PlainPermutationType operator*(const PermutationBase& other) const - { return PlainPermutationType(internal::PermPermProduct, derived(), other.derived()); } - - /** \returns the product of a permutation with another inverse permutation. - * - * \note \note_try_to_help_rvo - */ - template - inline PlainPermutationType operator*(const Transpose >& other) const - { return PlainPermutationType(internal::PermPermProduct, *this, other.eval()); } - - /** \returns the product of an inverse permutation with another permutation. - * - * \note \note_try_to_help_rvo - */ - template friend - inline PlainPermutationType operator*(const Transpose >& other, const PermutationBase& perm) - { return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); } - - /** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the permutation. - * - * This function is O(\c n) procedure allocating a buffer of \c n booleans. - */ - Index determinant() const - { - Index res = 1; - Index n = size(); - Matrix mask(n); - mask.fill(false); - Index r = 0; - while(r < n) - { - // search for the next seed - while(r=n) - break; - // we got one, let's follow it until we are back to the seed - Index k0 = r++; - mask.coeffRef(k0) = true; - for(Index k=indices().coeff(k0); k!=k0; k=indices().coeff(k)) - { - mask.coeffRef(k) = true; - res = -res; - } + public: + /** \returns the product permutation matrix. + * + * \note \blank \note_try_to_help_rvo + */ + template + inline PlainPermutationType operator*(const PermutationBase& other) const { + return PlainPermutationType(internal::PermPermProduct, derived(), other.derived()); + } + + /** \returns the product of a permutation with another inverse permutation. + * + * \note \blank \note_try_to_help_rvo + */ + template + inline PlainPermutationType operator*(const InverseImpl& other) const { + return PlainPermutationType(internal::PermPermProduct, *this, other.eval()); + } + + /** \returns the product of an inverse permutation with another permutation. + * + * \note \blank \note_try_to_help_rvo + */ + template + friend inline PlainPermutationType operator*(const InverseImpl& other, + const PermutationBase& perm) { + return PlainPermutationType(internal::PermPermProduct, other.eval(), perm); + } + + /** \returns the determinant of the permutation matrix, which is either 1 or -1 depending on the parity of the + * permutation. + * + * This function is O(\c n) procedure allocating a buffer of \c n booleans. + */ + Index determinant() const { + Index res = 1; + Index n = size(); + Matrix mask(n); + mask.fill(false); + Index r = 0; + while (r < n) { + // search for the next seed + while (r < n && mask[r]) r++; + if (r >= n) break; + // we got one, let's follow it until we are back to the seed + Index k0 = r++; + mask.coeffRef(k0) = true; + for (Index k = indices().coeff(k0); k != k0; k = indices().coeff(k)) { + mask.coeffRef(k) = true; + res = -res; } - return res; } + return res; + } - protected: - + protected: }; -/** \class PermutationMatrix - * \ingroup Core_Module - * - * \brief Permutation matrix - * - * \param SizeAtCompileTime the number of rows/cols, or Dynamic - * \param MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to SizeAtCompileTime. Most of the time, you should not have to specify it. - * \param IndexType the interger type of the indices - * - * This class represents a permutation matrix, internally stored as a vector of integers. - * - * \sa class PermutationBase, class PermutationWrapper, class DiagonalMatrix - */ - namespace internal { -template -struct traits > - : traits > -{ - typedef IndexType Index; - typedef Matrix IndicesType; +template +struct traits > + : traits< + Matrix > { + typedef PermutationStorage StorageKind; + typedef Matrix IndicesType; + typedef StorageIndex_ StorageIndex; + typedef void Scalar; }; -} +} // namespace internal -template -class PermutationMatrix : public PermutationBase > -{ - typedef PermutationBase Base; - typedef internal::traits Traits; - public: - - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef typename Traits::IndicesType IndicesType; - #endif - - inline PermutationMatrix() - {} - - /** Constructs an uninitialized permutation matrix of given size. - */ - inline PermutationMatrix(int size) : m_indices(size) - {} - - /** Copy constructor. */ - template - inline PermutationMatrix(const PermutationBase& other) - : m_indices(other.indices()) {} - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** Standard copy constructor. Defined only to prevent a default copy constructor - * from hiding the other templated constructor */ - inline PermutationMatrix(const PermutationMatrix& other) : m_indices(other.indices()) {} - #endif - - /** Generic constructor from expression of the indices. The indices - * array has the meaning that the permutations sends each integer i to indices[i]. - * - * \warning It is your responsibility to check that the indices array that you passes actually - * describes a permutation, i.e., each value between 0 and n-1 occurs exactly once, where n is the - * array's size. - */ - template - explicit inline PermutationMatrix(const MatrixBase& a_indices) : m_indices(a_indices) - {} - - /** Convert the Transpositions \a tr to a permutation matrix */ - template - explicit PermutationMatrix(const TranspositionsBase& tr) - : m_indices(tr.size()) - { - *this = tr; - } +/** \class PermutationMatrix + * \ingroup Core_Module + * + * \brief Permutation matrix + * + * \tparam SizeAtCompileTime the number of rows/cols, or Dynamic + * \tparam MaxSizeAtCompileTime the maximum number of rows/cols, or Dynamic. This optional parameter defaults to + * SizeAtCompileTime. Most of the time, you should not have to specify it. \tparam StorageIndex_ the integer type of the + * indices + * + * This class represents a permutation matrix, internally stored as a vector of integers. + * + * \sa class PermutationBase, class PermutationWrapper, class DiagonalMatrix + */ +template +class PermutationMatrix + : public PermutationBase > { + typedef PermutationBase Base; + typedef internal::traits Traits; + + public: + typedef const PermutationMatrix& Nested; - /** Copies the other permutation into *this */ - template - PermutationMatrix& operator=(const PermutationBase& other) - { - m_indices = other.indices(); - return *this; - } +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef typename Traits::IndicesType IndicesType; + typedef typename Traits::StorageIndex StorageIndex; +#endif - /** Assignment from the Transpositions \a tr */ - template - PermutationMatrix& operator=(const TranspositionsBase& tr) - { - return Base::operator=(tr.derived()); - } + inline PermutationMatrix() {} + + /** Constructs an uninitialized permutation matrix of given size. + */ + explicit inline PermutationMatrix(Index size) : m_indices(size) { + eigen_internal_assert(size <= NumTraits::highest()); + } + + /** Copy constructor. */ + template + inline PermutationMatrix(const PermutationBase& other) : m_indices(other.indices()) {} + + /** Generic constructor from expression of the indices. The indices + * array has the meaning that the permutations sends each integer i to indices[i]. + * + * \warning It is your responsibility to check that the indices array that you passes actually + * describes a permutation, i.e., each value between 0 and n-1 occurs exactly once, where n is the + * array's size. + */ + template + explicit inline PermutationMatrix(const MatrixBase& indices) : m_indices(indices) {} + + /** Convert the Transpositions \a tr to a permutation matrix */ + template + explicit PermutationMatrix(const TranspositionsBase& tr) : m_indices(tr.size()) { + *this = tr; + } + + /** Copies the other permutation into *this */ + template + PermutationMatrix& operator=(const PermutationBase& other) { + m_indices = other.indices(); + return *this; + } + + /** Assignment from the Transpositions \a tr */ + template + PermutationMatrix& operator=(const TranspositionsBase& tr) { + return Base::operator=(tr.derived()); + } + + /** const version of indices(). */ + const IndicesType& indices() const { return m_indices; } + /** \returns a reference to the stored array representing the permutation. */ + IndicesType& indices() { return m_indices; } + + /**** multiplication helpers to hopefully get RVO ****/ - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - PermutationMatrix& operator=(const PermutationMatrix& other) - { - m_indices = other.m_indices; - return *this; - } - #endif +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + PermutationMatrix(const InverseImpl& other) + : m_indices(other.derived().nestedExpression().size()) { + eigen_internal_assert(m_indices.size() <= NumTraits::highest()); + StorageIndex end = StorageIndex(m_indices.size()); + for (StorageIndex i = 0; i < end; ++i) + m_indices.coeffRef(other.derived().nestedExpression().indices().coeff(i)) = i; + } + template + PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs) : m_indices(lhs.indices().size()) { + Base::assignProduct(lhs, rhs); + } +#endif - /** const version of indices(). */ - const IndicesType& indices() const { return m_indices; } - /** \returns a reference to the stored array representing the permutation. */ - IndicesType& indices() { return m_indices; } + protected: + IndicesType m_indices; +}; +namespace internal { +template +struct traits, PacketAccess_> > + : traits< + Matrix > { + typedef PermutationStorage StorageKind; + typedef Map, PacketAccess_> IndicesType; + typedef StorageIndex_ StorageIndex; + typedef void Scalar; +}; +} // namespace internal - /**** multiplication helpers to hopefully get RVO ****/ +template +class Map, PacketAccess_> + : public PermutationBase< + Map, PacketAccess_> > { + typedef PermutationBase Base; + typedef internal::traits Traits; + public: #ifndef EIGEN_PARSED_BY_DOXYGEN - template - PermutationMatrix(const Transpose >& other) - : m_indices(other.nestedPermutation().size()) - { - for (int i=0; i - PermutationMatrix(internal::PermPermProduct_t, const Lhs& lhs, const Rhs& rhs) - : m_indices(lhs.indices().size()) - { - Base::assignProduct(lhs,rhs); - } + typedef typename Traits::IndicesType IndicesType; + typedef typename IndicesType::Scalar StorageIndex; #endif - protected: + inline Map(const StorageIndex* indicesPtr) : m_indices(indicesPtr) {} - IndicesType m_indices; -}; + inline Map(const StorageIndex* indicesPtr, Index size) : m_indices(indicesPtr, size) {} + /** Copies the other permutation into *this */ + template + Map& operator=(const PermutationBase& other) { + return Base::operator=(other.derived()); + } -namespace internal { -template -struct traits,_PacketAccess> > - : traits > -{ - typedef IndexType Index; - typedef Map, _PacketAccess> IndicesType; -}; -} - -template -class Map,_PacketAccess> - : public PermutationBase,_PacketAccess> > -{ - typedef PermutationBase Base; - typedef internal::traits Traits; - public: - - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef typename Traits::IndicesType IndicesType; - typedef typename IndicesType::Scalar Index; - #endif - - inline Map(const Index* indicesPtr) - : m_indices(indicesPtr) - {} - - inline Map(const Index* indicesPtr, Index size) - : m_indices(indicesPtr,size) - {} - - /** Copies the other permutation into *this */ - template - Map& operator=(const PermutationBase& other) - { return Base::operator=(other.derived()); } - - /** Assignment from the Transpositions \a tr */ - template - Map& operator=(const TranspositionsBase& tr) - { return Base::operator=(tr.derived()); } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - Map& operator=(const Map& other) - { - m_indices = other.m_indices; - return *this; - } - #endif + /** Assignment from the Transpositions \a tr */ + template + Map& operator=(const TranspositionsBase& tr) { + return Base::operator=(tr.derived()); + } - /** const version of indices(). */ - const IndicesType& indices() const { return m_indices; } - /** \returns a reference to the stored array representing the permutation. */ - IndicesType& indices() { return m_indices; } +#ifndef EIGEN_PARSED_BY_DOXYGEN + /** This is a special case of the templated operator=. Its purpose is to + * prevent a default operator= from hiding the templated operator=. + */ + Map& operator=(const Map& other) { + m_indices = other.m_indices; + return *this; + } +#endif - protected: + /** const version of indices(). */ + const IndicesType& indices() const { return m_indices; } + /** \returns a reference to the stored array representing the permutation. */ + IndicesType& indices() { return m_indices; } - IndicesType m_indices; + protected: + IndicesType m_indices; }; -/** \class PermutationWrapper - * \ingroup Core_Module - * - * \brief Class to view a vector of integers as a permutation matrix - * - * \param _IndicesType the type of the vector of integer (can be any compatible expression) - * - * This class allows to view any vector expression of integers as a permutation matrix. - * - * \sa class PermutationBase, class PermutationMatrix - */ - -struct PermutationStorage {}; - -template class TranspositionsWrapper; +template +class TranspositionsWrapper; namespace internal { -template -struct traits > -{ +template +struct traits > { typedef PermutationStorage StorageKind; - typedef typename _IndicesType::Scalar Scalar; - typedef typename _IndicesType::Scalar Index; - typedef _IndicesType IndicesType; + typedef void Scalar; + typedef typename IndicesType_::Scalar StorageIndex; + typedef IndicesType_ IndicesType; enum { - RowsAtCompileTime = _IndicesType::SizeAtCompileTime, - ColsAtCompileTime = _IndicesType::SizeAtCompileTime, - MaxRowsAtCompileTime = IndicesType::MaxRowsAtCompileTime, - MaxColsAtCompileTime = IndicesType::MaxColsAtCompileTime, - Flags = 0, - CoeffReadCost = _IndicesType::CoeffReadCost + RowsAtCompileTime = IndicesType_::SizeAtCompileTime, + ColsAtCompileTime = IndicesType_::SizeAtCompileTime, + MaxRowsAtCompileTime = IndicesType::MaxSizeAtCompileTime, + MaxColsAtCompileTime = IndicesType::MaxSizeAtCompileTime, + Flags = 0 }; }; -} - -template -class PermutationWrapper : public PermutationBase > -{ - typedef PermutationBase Base; - typedef internal::traits Traits; - public: +} // namespace internal - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef typename Traits::IndicesType IndicesType; - #endif - - inline PermutationWrapper(const IndicesType& a_indices) - : m_indices(a_indices) - {} +/** \class PermutationWrapper + * \ingroup Core_Module + * + * \brief Class to view a vector of integers as a permutation matrix + * + * \tparam IndicesType_ the type of the vector of integer (can be any compatible expression) + * + * This class allows to view any vector expression of integers as a permutation matrix. + * + * \sa class PermutationBase, class PermutationMatrix + */ +template +class PermutationWrapper : public PermutationBase > { + typedef PermutationBase Base; + typedef internal::traits Traits; + + public: +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef typename Traits::IndicesType IndicesType; +#endif - /** const version of indices(). */ - const typename internal::remove_all::type& - indices() const { return m_indices; } + inline PermutationWrapper(const IndicesType& indices) : m_indices(indices) {} - protected: + /** const version of indices(). */ + const internal::remove_all_t& indices() const { return m_indices; } - typename IndicesType::Nested m_indices; + protected: + typename IndicesType::Nested m_indices; }; /** \returns the matrix with the permutation applied to the columns. - */ -template -inline const internal::permut_matrix_product_retval -operator*(const MatrixBase& matrix, - const PermutationBase &permutation) -{ - return internal::permut_matrix_product_retval - - (permutation.derived(), matrix.derived()); + */ +template +EIGEN_DEVICE_FUNC const Product operator*( + const MatrixBase& matrix, const PermutationBase& permutation) { + return Product(matrix.derived(), permutation.derived()); } /** \returns the matrix with the permutation applied to the rows. - */ -template -inline const internal::permut_matrix_product_retval - -operator*(const PermutationBase &permutation, - const MatrixBase& matrix) -{ - return internal::permut_matrix_product_retval - - (permutation.derived(), matrix.derived()); + */ +template +EIGEN_DEVICE_FUNC const Product operator*( + const PermutationBase& permutation, const MatrixBase& matrix) { + return Product(permutation.derived(), matrix.derived()); } -namespace internal { +template +class InverseImpl : public EigenBase > { + typedef typename PermutationType::PlainPermutationType PlainPermutationType; + typedef internal::traits PermTraits; -template -struct traits > -{ - typedef typename MatrixType::PlainObject ReturnType; -}; + protected: + InverseImpl() {} -template -struct permut_matrix_product_retval - : public ReturnByValue > -{ - typedef typename remove_all::type MatrixTypeNestedCleaned; - typedef typename MatrixType::Index Index; - - permut_matrix_product_retval(const PermutationType& perm, const MatrixType& matrix) - : m_permutation(perm), m_matrix(matrix) - {} - - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } - - template inline void evalTo(Dest& dst) const - { - const Index n = Side==OnTheLeft ? rows() : cols(); - // FIXME we need an is_same for expression that is not sensitive to constness. For instance - // is_same_xpr, Block >::value should be true. - if( is_same::value - && blas_traits::HasUsableDirectAccess - && blas_traits::HasUsableDirectAccess - && extract_data(dst) == extract_data(m_matrix)) - { - // apply the permutation inplace - Matrix mask(m_permutation.size()); - mask.fill(false); - Index r = 0; - while(r < m_permutation.size()) - { - // search for the next seed - while(r=m_permutation.size()) - break; - // we got one, let's follow it until we are back to the seed - Index k0 = r++; - Index kPrev = k0; - mask.coeffRef(k0) = true; - for(Index k=m_permutation.indices().coeff(k0); k!=k0; k=m_permutation.indices().coeff(k)) - { - Block(dst, k) - .swap(Block - (dst,((Side==OnTheLeft) ^ Transposed) ? k0 : kPrev)); - - mask.coeffRef(k) = true; - kPrev = k; - } - } - } - else - { - for(int i = 0; i < n; ++i) - { - Block - (dst, ((Side==OnTheLeft) ^ Transposed) ? m_permutation.indices().coeff(i) : i) - - = - - Block - (m_matrix, ((Side==OnTheRight) ^ Transposed) ? m_permutation.indices().coeff(i) : i); - } - } - } - - protected: - const PermutationType& m_permutation; - typename MatrixType::Nested m_matrix; -}; - -/* Template partial specialization for transposed/inverse permutations */ - -template -struct traits > > - : traits -{}; - -} // end namespace internal - -template -class Transpose > - : public EigenBase > > -{ - typedef Derived PermutationType; - typedef typename PermutationType::IndicesType IndicesType; - typedef typename PermutationType::PlainPermutationType PlainPermutationType; - public: - - #ifndef EIGEN_PARSED_BY_DOXYGEN - typedef internal::traits Traits; - typedef typename Derived::DenseMatrixType DenseMatrixType; - enum { - Flags = Traits::Flags, - CoeffReadCost = Traits::CoeffReadCost, - RowsAtCompileTime = Traits::RowsAtCompileTime, - ColsAtCompileTime = Traits::ColsAtCompileTime, - MaxRowsAtCompileTime = Traits::MaxRowsAtCompileTime, - MaxColsAtCompileTime = Traits::MaxColsAtCompileTime - }; - typedef typename Traits::Scalar Scalar; - #endif - - Transpose(const PermutationType& p) : m_permutation(p) {} - - inline int rows() const { return m_permutation.rows(); } - inline int cols() const { return m_permutation.cols(); } - - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - void evalTo(MatrixBase& other) const - { - other.setZero(); - for (int i=0; i InverseType; + using EigenBase >::derived; - /** \return the equivalent permutation matrix */ - PlainPermutationType eval() const { return *this; } +#ifndef EIGEN_PARSED_BY_DOXYGEN + typedef typename PermutationType::DenseMatrixType DenseMatrixType; + enum { + RowsAtCompileTime = PermTraits::RowsAtCompileTime, + ColsAtCompileTime = PermTraits::ColsAtCompileTime, + MaxRowsAtCompileTime = PermTraits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = PermTraits::MaxColsAtCompileTime + }; +#endif - DenseMatrixType toDenseMatrix() const { return *this; } +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + void evalTo(MatrixBase& other) const { + other.setZero(); + for (Index i = 0; i < derived().rows(); ++i) + other.coeffRef(i, derived().nestedExpression().indices().coeff(i)) = typename DenseDerived::Scalar(1); + } +#endif - /** \returns the matrix with the inverse permutation applied to the columns. - */ - template friend - inline const internal::permut_matrix_product_retval - operator*(const MatrixBase& matrix, const Transpose& trPerm) - { - return internal::permut_matrix_product_retval(trPerm.m_permutation, matrix.derived()); - } + /** \return the equivalent permutation matrix */ + PlainPermutationType eval() const { return derived(); } + + DenseMatrixType toDenseMatrix() const { return derived(); } + + /** \returns the matrix with the inverse permutation applied to the columns. + */ + template + friend const Product operator*(const MatrixBase& matrix, + const InverseType& trPerm) { + return Product(matrix.derived(), trPerm.derived()); + } + + /** \returns the matrix with the inverse permutation applied to the rows. + */ + template + const Product operator*(const MatrixBase& matrix) const { + return Product(derived(), matrix.derived()); + } +}; - /** \returns the matrix with the inverse permutation applied to the rows. - */ - template - inline const internal::permut_matrix_product_retval - operator*(const MatrixBase& matrix) const - { - return internal::permut_matrix_product_retval(m_permutation, matrix.derived()); - } +template +const PermutationWrapper MatrixBase::asPermutation() const { + return derived(); +} - const PermutationType& nestedPermutation() const { return m_permutation; } +namespace internal { - protected: - const PermutationType& m_permutation; +template <> +struct AssignmentKind { + typedef EigenBase2EigenBase Kind; }; -template -const PermutationWrapper MatrixBase::asPermutation() const -{ - return derived(); -} +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_PERMUTATIONMATRIX_H +#endif // EIGEN_PERMUTATIONMATRIX_H diff --git a/inst/include/Eigen/src/Core/PlainObjectBase.h b/inst/include/Eigen/src/Core/PlainObjectBase.h index a4e4af4a..a78305e2 100644 --- a/inst/include/Eigen/src/Core/PlainObjectBase.h +++ b/inst/include/Eigen/src/Core/PlainObjectBase.h @@ -12,727 +12,922 @@ #define EIGEN_DENSESTORAGEBASE_H #if defined(EIGEN_INITIALIZE_MATRICES_BY_ZERO) -# define EIGEN_INITIALIZE_COEFFS -# define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED for(int i=0;i::quiet_NaN(); +#define EIGEN_INITIALIZE_COEFFS +#define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED \ + for (Index i = 0; i < base().size(); ++i) coeffRef(i) = std::numeric_limits::quiet_NaN(); #else -# undef EIGEN_INITIALIZE_COEFFS -# define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED +#undef EIGEN_INITIALIZE_COEFFS +#define EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED #endif +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + namespace Eigen { namespace internal { -template struct check_rows_cols_for_overflow { - template - static EIGEN_ALWAYS_INLINE void run(Index, Index) - { +#ifndef EIGEN_NO_DEBUG +template +struct check_rows_cols_for_overflow { + EIGEN_STATIC_ASSERT(MaxRowsAtCompileTime* MaxColsAtCompileTime == MaxSizeAtCompileTime, + YOU MADE A PROGRAMMING MISTAKE) + template + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index, Index) {} +}; + +template +struct check_rows_cols_for_overflow { + template + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index, Index cols) { + constexpr Index MaxIndex = NumTraits::highest(); + bool error = cols > (MaxIndex / MaxRowsAtCompileTime); + if (error) throw_std_bad_alloc(); + } +}; + +template +struct check_rows_cols_for_overflow { + template + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index rows, Index) { + constexpr Index MaxIndex = NumTraits::highest(); + bool error = rows > (MaxIndex / MaxColsAtCompileTime); + if (error) throw_std_bad_alloc(); } }; -template<> struct check_rows_cols_for_overflow { - template - static EIGEN_ALWAYS_INLINE void run(Index rows, Index cols) - { - // http://hg.mozilla.org/mozilla-central/file/6c8a909977d3/xpcom/ds/CheckedInt.h#l242 - // we assume Index is signed - Index max_index = (size_t(1) << (8 * sizeof(Index) - 1)) - 1; // assume Index is signed - bool error = (rows == 0 || cols == 0) ? false - : (rows > max_index / cols); - if (error) - throw_std_bad_alloc(); +template <> +struct check_rows_cols_for_overflow { + template + EIGEN_DEVICE_FUNC static EIGEN_ALWAYS_INLINE constexpr void run(Index rows, Index cols) { + constexpr Index MaxIndex = NumTraits::highest(); + bool error = cols == 0 ? false : (rows > (MaxIndex / cols)); + if (error) throw_std_bad_alloc(); } }; +#endif -template struct conservative_resize_like_impl; -template struct matrix_swap_impl; +template +struct matrix_swap_impl; -} // end namespace internal +} // end namespace internal /** \class PlainObjectBase - * \brief %Dense storage base class for matrices and arrays. - * - * This class can be extended with the help of the plugin mechanism described on the page - * \ref TopicCustomizingEigen by defining the preprocessor symbol \c EIGEN_PLAINOBJECTBASE_PLUGIN. - * - * \sa \ref TopicClassHierarchy - */ -#ifdef EIGEN_PARSED_BY_DOXYGEN -namespace internal { + * \ingroup Core_Module + * \brief %Dense storage base class for matrices and arrays. + * + * This class can be extended with the help of the plugin mechanism described on the page + * \ref TopicCustomizing_Plugins by defining the preprocessor symbol \c EIGEN_PLAINOBJECTBASE_PLUGIN. + * + * \tparam Derived is the derived type, e.g., a Matrix or Array + * + * \sa \ref TopicClassHierarchy + */ +template +class PlainObjectBase : public internal::dense_xpr_base::type { + public: + enum { Options = internal::traits::Options }; + typedef typename internal::dense_xpr_base::type Base; + + typedef typename internal::traits::StorageKind StorageKind; + typedef typename internal::traits::Scalar Scalar; + + typedef typename internal::packet_traits::type PacketScalar; + typedef typename NumTraits::Real RealScalar; + typedef Derived DenseType; + + using Base::ColsAtCompileTime; + using Base::Flags; + using Base::IsVectorAtCompileTime; + using Base::MaxColsAtCompileTime; + using Base::MaxRowsAtCompileTime; + using Base::MaxSizeAtCompileTime; + using Base::RowsAtCompileTime; + using Base::SizeAtCompileTime; + + typedef Eigen::Map MapType; + typedef const Eigen::Map ConstMapType; + typedef Eigen::Map AlignedMapType; + typedef const Eigen::Map ConstAlignedMapType; + template + struct StridedMapType { + typedef Eigen::Map type; + }; + template + struct StridedConstMapType { + typedef Eigen::Map type; + }; + template + struct StridedAlignedMapType { + typedef Eigen::Map type; + }; + template + struct StridedConstAlignedMapType { + typedef Eigen::Map type; + }; + + protected: + DenseStorage m_storage; + + public: + enum { NeedsToAlign = (SizeAtCompileTime != Dynamic) && (internal::traits::Alignment > 0) }; + EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) + + EIGEN_STATIC_ASSERT(internal::check_implication(MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1, + (int(Options) & RowMajor) == RowMajor), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT(internal::check_implication(MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1, + (int(Options) & RowMajor) == 0), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((RowsAtCompileTime == Dynamic) || (RowsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((ColsAtCompileTime == Dynamic) || (ColsAtCompileTime >= 0), INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((MaxRowsAtCompileTime == Dynamic) || (MaxRowsAtCompileTime >= 0), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((MaxColsAtCompileTime == Dynamic) || (MaxColsAtCompileTime >= 0), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((MaxRowsAtCompileTime == RowsAtCompileTime || RowsAtCompileTime == Dynamic), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT((MaxColsAtCompileTime == ColsAtCompileTime || ColsAtCompileTime == Dynamic), + INVALID_MATRIX_TEMPLATE_PARAMETERS) + EIGEN_STATIC_ASSERT(((Options & (DontAlign | RowMajor)) == Options), INVALID_MATRIX_TEMPLATE_PARAMETERS) + + EIGEN_DEVICE_FUNC Base& base() { return *static_cast(this); } + EIGEN_DEVICE_FUNC const Base& base() const { return *static_cast(this); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_storage.rows(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_storage.cols(); } + + /** This is an overloaded version of DenseCoeffsBase::coeff(Index,Index) const + * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts. + * + * See DenseCoeffsBase::coeff(Index) const for details. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeff(Index rowId, Index colId) const { + if (Flags & RowMajorBit) + return m_storage.data()[colId + rowId * m_storage.cols()]; + else // column-major + return m_storage.data()[rowId + colId * m_storage.rows()]; + } + + /** This is an overloaded version of DenseCoeffsBase::coeff(Index) const + * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts. + * + * See DenseCoeffsBase::coeff(Index) const for details. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeff(Index index) const { + return m_storage.data()[index]; + } + + /** This is an overloaded version of DenseCoeffsBase::coeffRef(Index,Index) const + * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts. + * + * See DenseCoeffsBase::coeffRef(Index,Index) const for details. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index rowId, Index colId) { + if (Flags & RowMajorBit) + return m_storage.data()[colId + rowId * m_storage.cols()]; + else // column-major + return m_storage.data()[rowId + colId * m_storage.rows()]; + } + + /** This is an overloaded version of DenseCoeffsBase::coeffRef(Index) const + * provided to by-pass the creation of an evaluator of the expression, thus saving compilation efforts. + * + * See DenseCoeffsBase::coeffRef(Index) const for details. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Scalar& coeffRef(Index index) { return m_storage.data()[index]; } + + /** This is the const version of coeffRef(Index,Index) which is thus synonym of coeff(Index,Index). + * It is provided for convenience. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeffRef(Index rowId, Index colId) const { + if (Flags & RowMajorBit) + return m_storage.data()[colId + rowId * m_storage.cols()]; + else // column-major + return m_storage.data()[rowId + colId * m_storage.rows()]; + } + + /** This is the const version of coeffRef(Index) which is thus synonym of coeff(Index). + * It is provided for convenience. */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr const Scalar& coeffRef(Index index) const { + return m_storage.data()[index]; + } + + /** \internal */ + template + EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const { + return internal::ploadt( + m_storage.data() + (Flags & RowMajorBit ? colId + rowId * m_storage.cols() : rowId + colId * m_storage.rows())); + } + + /** \internal */ + template + EIGEN_STRONG_INLINE PacketScalar packet(Index index) const { + return internal::ploadt(m_storage.data() + index); + } + + /** \internal */ + template + EIGEN_STRONG_INLINE void writePacket(Index rowId, Index colId, const PacketScalar& val) { + internal::pstoret( + m_storage.data() + (Flags & RowMajorBit ? colId + rowId * m_storage.cols() : rowId + colId * m_storage.rows()), + val); + } -// this is a warkaround to doxygen not being able to understand the inheritence logic -// when it is hidden by the dense_xpr_base helper struct. -template struct dense_xpr_base_dispatcher_for_doxygen;// : public MatrixBase {}; -/** This class is just a workaround for Doxygen and it does not not actually exist. */ -template -struct dense_xpr_base_dispatcher_for_doxygen > - : public MatrixBase > {}; -/** This class is just a workaround for Doxygen and it does not not actually exist. */ -template -struct dense_xpr_base_dispatcher_for_doxygen > - : public ArrayBase > {}; - -} // namespace internal - -template -class PlainObjectBase : public internal::dense_xpr_base_dispatcher_for_doxygen + /** \internal */ + template + EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& val) { + internal::pstoret(m_storage.data() + index, val); + } + + /** \returns a const pointer to the data array of this matrix */ + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const { return m_storage.data(); } + + /** \returns a pointer to the data array of this matrix */ + EIGEN_DEVICE_FUNC constexpr Scalar* data() { return m_storage.data(); } + + /** Resizes \c *this to a \a rows x \a cols matrix. + * + * This method is intended for dynamic-size matrices, although it is legal to call it on any + * matrix as long as fixed dimensions are left unchanged. If you only want to change the number + * of rows and/or of columns, you can use resize(NoChange_t, Index), resize(Index, NoChange_t). + * + * If the current number of coefficients of \c *this exactly matches the + * product \a rows * \a cols, then no memory allocation is performed and + * the current values are left unchanged. In all other cases, including + * shrinking, the data is reallocated and all previous values are lost. + * + * Example: \include Matrix_resize_int_int.cpp + * Output: \verbinclude Matrix_resize_int_int.out + * + * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t) + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr void resize(Index rows, Index cols) { + eigen_assert(internal::check_implication(RowsAtCompileTime != Dynamic, rows == RowsAtCompileTime) && + internal::check_implication(ColsAtCompileTime != Dynamic, cols == ColsAtCompileTime) && + internal::check_implication(RowsAtCompileTime == Dynamic && MaxRowsAtCompileTime != Dynamic, + rows <= MaxRowsAtCompileTime) && + internal::check_implication(ColsAtCompileTime == Dynamic && MaxColsAtCompileTime != Dynamic, + cols <= MaxColsAtCompileTime) && + rows >= 0 && cols >= 0 && "Invalid sizes when resizing a matrix or array."); +#ifndef EIGEN_NO_DEBUG + internal::check_rows_cols_for_overflow::run(rows, + cols); +#endif +#ifdef EIGEN_INITIALIZE_COEFFS + Index size = rows * cols; + bool size_changed = size != this->size(); + m_storage.resize(size, rows, cols); + if (size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED #else -template -class PlainObjectBase : public internal::dense_xpr_base::type + m_storage.resize(rows * cols, rows, cols); #endif -{ - public: - enum { Options = internal::traits::Options }; - typedef typename internal::dense_xpr_base::type Base; - - typedef typename internal::traits::StorageKind StorageKind; - typedef typename internal::traits::Index Index; - typedef typename internal::traits::Scalar Scalar; - typedef typename internal::packet_traits::type PacketScalar; - typedef typename NumTraits::Real RealScalar; - typedef Derived DenseType; - - using Base::RowsAtCompileTime; - using Base::ColsAtCompileTime; - using Base::SizeAtCompileTime; - using Base::MaxRowsAtCompileTime; - using Base::MaxColsAtCompileTime; - using Base::MaxSizeAtCompileTime; - using Base::IsVectorAtCompileTime; - using Base::Flags; - - template friend class Eigen::Map; - friend class Eigen::Map; - typedef Eigen::Map MapType; - friend class Eigen::Map; - typedef const Eigen::Map ConstMapType; - friend class Eigen::Map; - typedef Eigen::Map AlignedMapType; - friend class Eigen::Map; - typedef const Eigen::Map ConstAlignedMapType; - template struct StridedMapType { typedef Eigen::Map type; }; - template struct StridedConstMapType { typedef Eigen::Map type; }; - template struct StridedAlignedMapType { typedef Eigen::Map type; }; - template struct StridedConstAlignedMapType { typedef Eigen::Map type; }; - - protected: - DenseStorage m_storage; - - public: - enum { NeedsToAlign = SizeAtCompileTime != Dynamic && (internal::traits::Flags & AlignedBit) != 0 }; - EIGEN_MAKE_ALIGNED_OPERATOR_NEW_IF(NeedsToAlign) - - Base& base() { return *static_cast(this); } - const Base& base() const { return *static_cast(this); } - - EIGEN_STRONG_INLINE Index rows() const { return m_storage.rows(); } - EIGEN_STRONG_INLINE Index cols() const { return m_storage.cols(); } - - EIGEN_STRONG_INLINE const Scalar& coeff(Index rowId, Index colId) const - { - if(Flags & RowMajorBit) - return m_storage.data()[colId + rowId * m_storage.cols()]; - else // column-major - return m_storage.data()[rowId + colId * m_storage.rows()]; - } - - EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const - { - return m_storage.data()[index]; - } + } - EIGEN_STRONG_INLINE Scalar& coeffRef(Index rowId, Index colId) - { - if(Flags & RowMajorBit) - return m_storage.data()[colId + rowId * m_storage.cols()]; - else // column-major - return m_storage.data()[rowId + colId * m_storage.rows()]; - } + /** Resizes \c *this to a vector of length \a size + * + * \only_for_vectors. This method does not work for + * partially dynamic matrices when the static dimension is anything other + * than 1. For example it will not work with Matrix. + * + * Example: \include Matrix_resize_int.cpp + * Output: \verbinclude Matrix_resize_int.out + * + * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t) + */ + EIGEN_DEVICE_FUNC constexpr void resize(Index size) { + EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase) + eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime == Dynamic || size <= MaxSizeAtCompileTime)) || + SizeAtCompileTime == size) && + size >= 0); +#ifdef EIGEN_INITIALIZE_COEFFS + bool size_changed = size != this->size(); +#endif + if (RowsAtCompileTime == 1) + m_storage.resize(size, 1, size); + else + m_storage.resize(size, size, 1); +#ifdef EIGEN_INITIALIZE_COEFFS + if (size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED +#endif + } - EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) - { - return m_storage.data()[index]; - } + /** Resizes the matrix, changing only the number of columns. For the parameter of type NoChange_t, just pass the + * special value \c NoChange as in the example below. + * + * Example: \include Matrix_resize_NoChange_int.cpp + * Output: \verbinclude Matrix_resize_NoChange_int.out + * + * \sa resize(Index,Index) + */ + EIGEN_DEVICE_FUNC constexpr void resize(NoChange_t, Index cols) { resize(rows(), cols); } + + /** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special + * value \c NoChange as in the example below. + * + * Example: \include Matrix_resize_int_NoChange.cpp + * Output: \verbinclude Matrix_resize_int_NoChange.out + * + * \sa resize(Index,Index) + */ + EIGEN_DEVICE_FUNC constexpr void resize(Index rows, NoChange_t) { resize(rows, cols()); } + + /** Resizes \c *this to have the same dimensions as \a other. + * Takes care of doing all the checking that's needed. + * + * Note that copying a row-vector into a vector (and conversely) is allowed. + * The resizing, if any, is then done in the appropriate way so that row-vectors + * remain row-vectors and vectors remain vectors. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void resizeLike(const EigenBase& _other) { + const OtherDerived& other = _other.derived(); +#ifndef EIGEN_NO_DEBUG + internal::check_rows_cols_for_overflow::run( + other.rows(), other.cols()); +#endif + const Index othersize = other.rows() * other.cols(); + if (RowsAtCompileTime == 1) { + eigen_assert(other.rows() == 1 || other.cols() == 1); + resize(1, othersize); + } else if (ColsAtCompileTime == 1) { + eigen_assert(other.rows() == 1 || other.cols() == 1); + resize(othersize, 1); + } else + resize(other.rows(), other.cols()); + } - EIGEN_STRONG_INLINE const Scalar& coeffRef(Index rowId, Index colId) const - { - if(Flags & RowMajorBit) - return m_storage.data()[colId + rowId * m_storage.cols()]; - else // column-major - return m_storage.data()[rowId + colId * m_storage.rows()]; - } + /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. + * + * The method is intended for matrices of dynamic size. If you only want to change the number + * of rows and/or of columns, you can use conservativeResize(NoChange_t, Index) or + * conservativeResize(Index, NoChange_t). + * + * Matrices are resized relative to the top-left element. In case values need to be + * appended to the matrix they will be uninitialized. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void conservativeResize(Index rows, Index cols) { + internal::conservative_resize_like_impl::run(*this, rows, cols); + } - EIGEN_STRONG_INLINE const Scalar& coeffRef(Index index) const - { - return m_storage.data()[index]; - } + /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. + * + * As opposed to conservativeResize(Index rows, Index cols), this version leaves + * the number of columns unchanged. + * + * In case the matrix is growing, new rows will be uninitialized. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void conservativeResize(Index rows, NoChange_t) { + // Note: see the comment in conservativeResize(Index,Index) + conservativeResize(rows, cols()); + } - /** \internal */ - template - EIGEN_STRONG_INLINE PacketScalar packet(Index rowId, Index colId) const - { - return internal::ploadt - (m_storage.data() + (Flags & RowMajorBit - ? colId + rowId * m_storage.cols() - : rowId + colId * m_storage.rows())); - } + /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. + * + * As opposed to conservativeResize(Index rows, Index cols), this version leaves + * the number of rows unchanged. + * + * In case the matrix is growing, new columns will be uninitialized. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index cols) { + // Note: see the comment in conservativeResize(Index,Index) + conservativeResize(rows(), cols); + } - /** \internal */ - template - EIGEN_STRONG_INLINE PacketScalar packet(Index index) const - { - return internal::ploadt(m_storage.data() + index); - } + /** Resizes the vector to \a size while retaining old values. + * + * \only_for_vectors. This method does not work for + * partially dynamic matrices when the static dimension is anything other + * than 1. For example it will not work with Matrix. + * + * When values are appended, they will be uninitialized. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void conservativeResize(Index size) { + internal::conservative_resize_like_impl::run(*this, size); + } - /** \internal */ - template - EIGEN_STRONG_INLINE void writePacket(Index rowId, Index colId, const PacketScalar& val) - { - internal::pstoret - (m_storage.data() + (Flags & RowMajorBit - ? colId + rowId * m_storage.cols() - : rowId + colId * m_storage.rows()), val); - } + /** Resizes the matrix to \a rows x \a cols of \c other, while leaving old values untouched. + * + * The method is intended for matrices of dynamic size. If you only want to change the number + * of rows and/or of columns, you can use conservativeResize(NoChange_t, Index) or + * conservativeResize(Index, NoChange_t). + * + * Matrices are resized relative to the top-left element. In case values need to be + * appended to the matrix they will copied from \c other. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase& other) { + internal::conservative_resize_like_impl::run(*this, other); + } - /** \internal */ - template - EIGEN_STRONG_INLINE void writePacket(Index index, const PacketScalar& val) - { - internal::pstoret(m_storage.data() + index, val); - } + /** This is a special case of the templated operator=. Its purpose is to + * prevent a default operator= from hiding the templated operator=. + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Derived& operator=(const PlainObjectBase& other) { + return _set(other); + } - /** \returns a const pointer to the data array of this matrix */ - EIGEN_STRONG_INLINE const Scalar *data() const - { return m_storage.data(); } - - /** \returns a pointer to the data array of this matrix */ - EIGEN_STRONG_INLINE Scalar *data() - { return m_storage.data(); } - - /** Resizes \c *this to a \a rows x \a cols matrix. - * - * This method is intended for dynamic-size matrices, although it is legal to call it on any - * matrix as long as fixed dimensions are left unchanged. If you only want to change the number - * of rows and/or of columns, you can use resize(NoChange_t, Index), resize(Index, NoChange_t). - * - * If the current number of coefficients of \c *this exactly matches the - * product \a rows * \a cols, then no memory allocation is performed and - * the current values are left unchanged. In all other cases, including - * shrinking, the data is reallocated and all previous values are lost. - * - * Example: \include Matrix_resize_int_int.cpp - * Output: \verbinclude Matrix_resize_int_int.out - * - * \sa resize(Index) for vectors, resize(NoChange_t, Index), resize(Index, NoChange_t) - */ - EIGEN_STRONG_INLINE void resize(Index nbRows, Index nbCols) - { - eigen_assert( EIGEN_IMPLIES(RowsAtCompileTime!=Dynamic,nbRows==RowsAtCompileTime) - && EIGEN_IMPLIES(ColsAtCompileTime!=Dynamic,nbCols==ColsAtCompileTime) - && EIGEN_IMPLIES(RowsAtCompileTime==Dynamic && MaxRowsAtCompileTime!=Dynamic,nbRows<=MaxRowsAtCompileTime) - && EIGEN_IMPLIES(ColsAtCompileTime==Dynamic && MaxColsAtCompileTime!=Dynamic,nbCols<=MaxColsAtCompileTime) - && nbRows>=0 && nbCols>=0 && "Invalid sizes when resizing a matrix or array."); - internal::check_rows_cols_for_overflow::run(nbRows, nbCols); - #ifdef EIGEN_INITIALIZE_COEFFS - Index size = nbRows*nbCols; - bool size_changed = size != this->size(); - m_storage.resize(size, nbRows, nbCols); - if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - #else - internal::check_rows_cols_for_overflow::run(nbRows, nbCols); - m_storage.resize(nbRows*nbCols, nbRows, nbCols); - #endif - } + /** \sa MatrixBase::lazyAssign() */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase& other) { + _resize_to_match(other); + return Base::lazyAssign(other.derived()); + } - /** Resizes \c *this to a vector of length \a size - * - * \only_for_vectors. This method does not work for - * partially dynamic matrices when the static dimension is anything other - * than 1. For example it will not work with Matrix. - * - * Example: \include Matrix_resize_int.cpp - * Output: \verbinclude Matrix_resize_int.out - * - * \sa resize(Index,Index), resize(NoChange_t, Index), resize(Index, NoChange_t) - */ - inline void resize(Index size) - { - EIGEN_STATIC_ASSERT_VECTOR_ONLY(PlainObjectBase) - eigen_assert(((SizeAtCompileTime == Dynamic && (MaxSizeAtCompileTime==Dynamic || size<=MaxSizeAtCompileTime)) || SizeAtCompileTime == size) && size>=0); - #ifdef EIGEN_INITIALIZE_COEFFS - bool size_changed = size != this->size(); - #endif - if(RowsAtCompileTime == 1) - m_storage.resize(size, 1, size); - else - m_storage.resize(size, size, 1); - #ifdef EIGEN_INITIALIZE_COEFFS - if(size_changed) EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - #endif - } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue& func) { + resize(func.rows(), func.cols()); + return Base::operator=(func); + } - /** Resizes the matrix, changing only the number of columns. For the parameter of type NoChange_t, just pass the special value \c NoChange - * as in the example below. - * - * Example: \include Matrix_resize_NoChange_int.cpp - * Output: \verbinclude Matrix_resize_NoChange_int.out - * - * \sa resize(Index,Index) - */ - inline void resize(NoChange_t, Index nbCols) - { - resize(rows(), nbCols); - } + // Prevent user from trying to instantiate PlainObjectBase objects + // by making all its constructor protected. See bug 1074. + protected: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr PlainObjectBase() = default; + /** \brief Move constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr PlainObjectBase(PlainObjectBase&&) = default; + /** \brief Move assignment operator */ + EIGEN_DEVICE_FUNC constexpr PlainObjectBase& operator=(PlainObjectBase&& other) noexcept { + m_storage = std::move(other.m_storage); + return *this; + } - /** Resizes the matrix, changing only the number of rows. For the parameter of type NoChange_t, just pass the special value \c NoChange - * as in the example below. - * - * Example: \include Matrix_resize_int_NoChange.cpp - * Output: \verbinclude Matrix_resize_int_NoChange.out - * - * \sa resize(Index,Index) - */ - inline void resize(Index nbRows, NoChange_t) - { - resize(nbRows, cols()); - } + /** Copy constructor */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr PlainObjectBase(const PlainObjectBase&) = default; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PlainObjectBase(Index size, Index rows, Index cols) + : m_storage(size, rows, cols) {} + + /** \brief Construct a row of column vector with fixed size from an arbitrary number of coefficients. + * + * \only_for_vectors + * + * This constructor is for 1D array or vectors with more than 4 coefficients. + * + * \warning To construct a column (resp. row) vector of fixed length, the number of values passed to this + * constructor must match the the fixed number of rows (resp. columns) of \c *this. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PlainObjectBase(const Scalar& a0, const Scalar& a1, const Scalar& a2, + const Scalar& a3, const ArgTypes&... args) + : m_storage() { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, sizeof...(args) + 4); + m_storage.data()[0] = a0; + m_storage.data()[1] = a1; + m_storage.data()[2] = a2; + m_storage.data()[3] = a3; + Index i = 4; + auto x = {(m_storage.data()[i++] = args, 0)...}; + static_cast(x); + } - /** Resizes \c *this to have the same dimensions as \a other. - * Takes care of doing all the checking that's needed. - * - * Note that copying a row-vector into a vector (and conversely) is allowed. - * The resizing, if any, is then done in the appropriate way so that row-vectors - * remain row-vectors and vectors remain vectors. - */ - template - EIGEN_STRONG_INLINE void resizeLike(const EigenBase& _other) - { - const OtherDerived& other = _other.derived(); - internal::check_rows_cols_for_overflow::run(other.rows(), other.cols()); - const Index othersize = other.rows()*other.cols(); - if(RowsAtCompileTime == 1) - { - eigen_assert(other.rows() == 1 || other.cols() == 1); - resize(1, othersize); + /** \brief Constructs a Matrix or Array and initializes it by elements given by an initializer list of initializer + * lists + */ + EIGEN_DEVICE_FUNC explicit constexpr EIGEN_STRONG_INLINE PlainObjectBase( + const std::initializer_list>& list) + : m_storage() { + size_t list_size = 0; + if (list.begin() != list.end()) { + list_size = list.begin()->size(); + } + + // This is to allow syntax like VectorXi {{1, 2, 3, 4}} + if (ColsAtCompileTime == 1 && list.size() == 1) { + eigen_assert(list_size == static_cast(RowsAtCompileTime) || RowsAtCompileTime == Dynamic); + resize(list_size, ColsAtCompileTime); + if (list.begin()->begin() != nullptr) { + Index index = 0; + for (const Scalar& e : *list.begin()) { + coeffRef(index++) = e; + } } - else if(ColsAtCompileTime == 1) - { - eigen_assert(other.rows() == 1 || other.cols() == 1); - resize(othersize, 1); + } else { + eigen_assert(list.size() == static_cast(RowsAtCompileTime) || RowsAtCompileTime == Dynamic); + eigen_assert(list_size == static_cast(ColsAtCompileTime) || ColsAtCompileTime == Dynamic); + resize(list.size(), list_size); + + Index row_index = 0; + for (const std::initializer_list& row : list) { + eigen_assert(list_size == row.size()); + Index col_index = 0; + for (const Scalar& e : row) { + coeffRef(row_index, col_index) = e; + ++col_index; + } + ++row_index; } - else resize(other.rows(), other.cols()); - } - - /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. - * - * The method is intended for matrices of dynamic size. If you only want to change the number - * of rows and/or of columns, you can use conservativeResize(NoChange_t, Index) or - * conservativeResize(Index, NoChange_t). - * - * Matrices are resized relative to the top-left element. In case values need to be - * appended to the matrix they will be uninitialized. - */ - EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, Index nbCols) - { - internal::conservative_resize_like_impl::run(*this, nbRows, nbCols); } + } - /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. - * - * As opposed to conservativeResize(Index rows, Index cols), this version leaves - * the number of columns unchanged. - * - * In case the matrix is growing, new rows will be uninitialized. - */ - EIGEN_STRONG_INLINE void conservativeResize(Index nbRows, NoChange_t) - { - // Note: see the comment in conservativeResize(Index,Index) - conservativeResize(nbRows, cols()); - } + /** \sa PlainObjectBase::operator=(const EigenBase&) */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase& other) : m_storage() { + resizeLike(other); + _set_noalias(other); + } - /** Resizes the matrix to \a rows x \a cols while leaving old values untouched. - * - * As opposed to conservativeResize(Index rows, Index cols), this version leaves - * the number of rows unchanged. - * - * In case the matrix is growing, new columns will be uninitialized. - */ - EIGEN_STRONG_INLINE void conservativeResize(NoChange_t, Index nbCols) - { - // Note: see the comment in conservativeResize(Index,Index) - conservativeResize(rows(), nbCols); - } + /** \sa PlainObjectBase::operator=(const EigenBase&) */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase& other) : m_storage() { + resizeLike(other); + *this = other.derived(); + } + /** \brief Copy constructor with in-place evaluation */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PlainObjectBase(const ReturnByValue& other) { + // FIXME this does not automatically transpose vectors if necessary + resize(other.rows(), other.cols()); + other.evalTo(this->derived()); + } - /** Resizes the vector to \a size while retaining old values. - * - * \only_for_vectors. This method does not work for - * partially dynamic matrices when the static dimension is anything other - * than 1. For example it will not work with Matrix. - * - * When values are appended, they will be uninitialized. - */ - EIGEN_STRONG_INLINE void conservativeResize(Index size) - { - internal::conservative_resize_like_impl::run(*this, size); - } + public: + /** \brief Copies the generic expression \a other into *this. + * \copydetails DenseBase::operator=(const EigenBase &other) + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Derived& operator=(const EigenBase& other) { + _resize_to_match(other); + Base::operator=(other.derived()); + return this->derived(); + } - /** Resizes the matrix to \a rows x \a cols of \c other, while leaving old values untouched. - * - * The method is intended for matrices of dynamic size. If you only want to change the number - * of rows and/or of columns, you can use conservativeResize(NoChange_t, Index) or - * conservativeResize(Index, NoChange_t). - * - * Matrices are resized relative to the top-left element. In case values need to be - * appended to the matrix they will copied from \c other. - */ - template - EIGEN_STRONG_INLINE void conservativeResizeLike(const DenseBase& other) - { - internal::conservative_resize_like_impl::run(*this, other); - } + /** \name Map + * These are convenience functions returning Map objects. The Map() static functions return unaligned Map objects, + * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned + * \a data pointers. + * + * Here is an example using strides: + * \include Matrix_Map_stride.cpp + * Output: \verbinclude Matrix_Map_stride.out + * + * \see class Map + */ + ///@{ + static inline ConstMapType Map(const Scalar* data) { return ConstMapType(data); } + static inline MapType Map(Scalar* data) { return MapType(data); } + static inline ConstMapType Map(const Scalar* data, Index size) { return ConstMapType(data, size); } + static inline MapType Map(Scalar* data, Index size) { return MapType(data, size); } + static inline ConstMapType Map(const Scalar* data, Index rows, Index cols) { return ConstMapType(data, rows, cols); } + static inline MapType Map(Scalar* data, Index rows, Index cols) { return MapType(data, rows, cols); } + + static inline ConstAlignedMapType MapAligned(const Scalar* data) { return ConstAlignedMapType(data); } + static inline AlignedMapType MapAligned(Scalar* data) { return AlignedMapType(data); } + static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size) { + return ConstAlignedMapType(data, size); + } + static inline AlignedMapType MapAligned(Scalar* data, Index size) { return AlignedMapType(data, size); } + static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols) { + return ConstAlignedMapType(data, rows, cols); + } + static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols) { + return AlignedMapType(data, rows, cols); + } - /** This is a special case of the templated operator=. Its purpose is to - * prevent a default operator= from hiding the templated operator=. - */ - EIGEN_STRONG_INLINE Derived& operator=(const PlainObjectBase& other) - { - return _set(other); - } + template + static inline typename StridedConstMapType>::type Map(const Scalar* data, + const Stride& stride) { + return typename StridedConstMapType>::type(data, stride); + } + template + static inline typename StridedMapType>::type Map(Scalar* data, + const Stride& stride) { + return typename StridedMapType>::type(data, stride); + } + template + static inline typename StridedConstMapType>::type Map(const Scalar* data, Index size, + const Stride& stride) { + return typename StridedConstMapType>::type(data, size, stride); + } + template + static inline typename StridedMapType>::type Map(Scalar* data, Index size, + const Stride& stride) { + return typename StridedMapType>::type(data, size, stride); + } + template + static inline typename StridedConstMapType>::type Map(const Scalar* data, Index rows, Index cols, + const Stride& stride) { + return typename StridedConstMapType>::type(data, rows, cols, stride); + } + template + static inline typename StridedMapType>::type Map(Scalar* data, Index rows, Index cols, + const Stride& stride) { + return typename StridedMapType>::type(data, rows, cols, stride); + } - /** \sa MatrixBase::lazyAssign() */ - template - EIGEN_STRONG_INLINE Derived& lazyAssign(const DenseBase& other) - { - _resize_to_match(other); - return Base::lazyAssign(other.derived()); - } + template + static inline typename StridedConstAlignedMapType>::type MapAligned( + const Scalar* data, const Stride& stride) { + return typename StridedConstAlignedMapType>::type(data, stride); + } + template + static inline typename StridedAlignedMapType>::type MapAligned( + Scalar* data, const Stride& stride) { + return typename StridedAlignedMapType>::type(data, stride); + } + template + static inline typename StridedConstAlignedMapType>::type MapAligned( + const Scalar* data, Index size, const Stride& stride) { + return typename StridedConstAlignedMapType>::type(data, size, stride); + } + template + static inline typename StridedAlignedMapType>::type MapAligned( + Scalar* data, Index size, const Stride& stride) { + return typename StridedAlignedMapType>::type(data, size, stride); + } + template + static inline typename StridedConstAlignedMapType>::type MapAligned( + const Scalar* data, Index rows, Index cols, const Stride& stride) { + return typename StridedConstAlignedMapType>::type(data, rows, cols, stride); + } + template + static inline typename StridedAlignedMapType>::type MapAligned( + Scalar* data, Index rows, Index cols, const Stride& stride) { + return typename StridedAlignedMapType>::type(data, rows, cols, stride); + } + ///@} + + using Base::setConstant; + EIGEN_DEVICE_FUNC Derived& setConstant(Index size, const Scalar& val); + EIGEN_DEVICE_FUNC Derived& setConstant(Index rows, Index cols, const Scalar& val); + EIGEN_DEVICE_FUNC Derived& setConstant(NoChange_t, Index cols, const Scalar& val); + EIGEN_DEVICE_FUNC Derived& setConstant(Index rows, NoChange_t, const Scalar& val); + + using Base::setZero; + EIGEN_DEVICE_FUNC Derived& setZero(Index size); + EIGEN_DEVICE_FUNC Derived& setZero(Index rows, Index cols); + EIGEN_DEVICE_FUNC Derived& setZero(NoChange_t, Index cols); + EIGEN_DEVICE_FUNC Derived& setZero(Index rows, NoChange_t); + + using Base::setOnes; + EIGEN_DEVICE_FUNC Derived& setOnes(Index size); + EIGEN_DEVICE_FUNC Derived& setOnes(Index rows, Index cols); + EIGEN_DEVICE_FUNC Derived& setOnes(NoChange_t, Index cols); + EIGEN_DEVICE_FUNC Derived& setOnes(Index rows, NoChange_t); + + using Base::setRandom; + Derived& setRandom(Index size); + Derived& setRandom(Index rows, Index cols); + Derived& setRandom(NoChange_t, Index cols); + Derived& setRandom(Index rows, NoChange_t); + +#ifdef EIGEN_PLAINOBJECTBASE_PLUGIN +#include EIGEN_PLAINOBJECTBASE_PLUGIN +#endif - template - EIGEN_STRONG_INLINE Derived& operator=(const ReturnByValue& func) - { - resize(func.rows(), func.cols()); - return Base::operator=(func); - } + protected: + /** \internal Resizes *this in preparation for assigning \a other to it. + * Takes care of doing all the checking that's needed. + * + * Note that copying a row-vector into a vector (and conversely) is allowed. + * The resizing, if any, is then done in the appropriate way so that row-vectors + * remain row-vectors and vectors remain vectors. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase& other) { +#ifdef EIGEN_NO_AUTOMATIC_RESIZING + eigen_assert((this->size() == 0 || (IsVectorAtCompileTime ? (this->size() == other.size()) + : (rows() == other.rows() && cols() == other.cols()))) && + "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined"); + EIGEN_ONLY_USED_FOR_DEBUG(other); +#else + resizeLike(other); +#endif + } - EIGEN_STRONG_INLINE PlainObjectBase() : m_storage() - { -// _check_template_params(); -// EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } + /** + * \brief Copies the value of the expression \a other into \c *this with automatic resizing. + * + * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), + * it will be initialized. + * + * Note that copying a row-vector into a vector (and conversely) is allowed. + * The resizing, if any, is then done in the appropriate way so that row-vectors + * remain row-vectors and vectors remain vectors. + * + * \sa operator=(const MatrixBase&), _set_noalias() + * + * \internal + */ + // aliasing is dealt once in internal::call_assignment + // so at this stage we have to assume aliasing... and resising has to be done later. + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Derived& _set(const DenseBase& other) { + internal::call_assignment(this->derived(), other.derived()); + return this->derived(); + } -#ifndef EIGEN_PARSED_BY_DOXYGEN - // FIXME is it still needed ? - /** \internal */ - PlainObjectBase(internal::constructor_without_unaligned_array_assert) - : m_storage(internal::constructor_without_unaligned_array_assert()) - { -// _check_template_params(); EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } -#endif + /** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which + * is the case when creating a new matrix) so one can enforce lazy evaluation. + * + * \sa operator=(const MatrixBase&), _set() + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Derived& _set_noalias(const DenseBase& other) { + // I don't think we need this resize call since the lazyAssign will anyways resize + // and lazyAssign will be called by the assign selector. + //_resize_to_match(other); + // the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because + // it wouldn't allow to copy a row-vector into a column-vector. + internal::call_assignment_no_alias(this->derived(), other.derived(), + internal::assign_op()); + return this->derived(); + } -#ifdef EIGEN_HAVE_RVALUE_REFERENCES - PlainObjectBase(PlainObjectBase&& other) - : m_storage( std::move(other.m_storage) ) - { - } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init2(Index rows, Index cols, + std::enable_if_t* = 0) { + EIGEN_STATIC_ASSERT(internal::is_valid_index_type::value && internal::is_valid_index_type::value, + T0 AND T1 MUST BE INTEGER TYPES) + resize(rows, cols); + } - PlainObjectBase& operator=(PlainObjectBase&& other) - { - using std::swap; - swap(m_storage, other.m_storage); - return *this; - } -#endif + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init2(const T0& val0, const T1& val1, + std::enable_if_t* = 0) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2) + m_storage.data()[0] = Scalar(val0); + m_storage.data()[1] = Scalar(val1); + } - /** Copy constructor */ - EIGEN_STRONG_INLINE PlainObjectBase(const PlainObjectBase& other) - : m_storage() - { - _check_template_params(); - lazyAssign(other); - } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init2( + const Index& val0, const Index& val1, + std::enable_if_t<(!internal::is_same::value) && (internal::is_same::value) && + (internal::is_same::value) && Base::SizeAtCompileTime == 2, + T1>* = 0) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2) + m_storage.data()[0] = Scalar(val0); + m_storage.data()[1] = Scalar(val1); + } - template - EIGEN_STRONG_INLINE PlainObjectBase(const DenseBase &other) - : m_storage() - { - _check_template_params(); - lazyAssign(other); - } + // The argument is convertible to the Index type and we either have a non 1x1 Matrix, or a dynamic-sized Array, + // then the argument is meant to be the size of the object. + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1( + Index size, + std::enable_if_t<(Base::SizeAtCompileTime != 1 || !internal::is_convertible::value) && + ((!internal::is_same::XprKind, ArrayXpr>::value || + Base::SizeAtCompileTime == Dynamic)), + T>* = 0) { + // NOTE MSVC 2008 complains if we directly put bool(NumTraits::IsInteger) as the EIGEN_STATIC_ASSERT argument. + const bool is_integer_alike = internal::is_valid_index_type::value; + EIGEN_UNUSED_VARIABLE(is_integer_alike); + EIGEN_STATIC_ASSERT(is_integer_alike, FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED) + resize(size); + } - EIGEN_STRONG_INLINE PlainObjectBase(Index a_size, Index nbRows, Index nbCols) - : m_storage(a_size, nbRows, nbCols) - { -// _check_template_params(); -// EIGEN_INITIALIZE_COEFFS_IF_THAT_OPTION_IS_ENABLED - } + // We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar + // type can be implicitly converted) + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1( + const Scalar& val0, + std::enable_if_t::value, T>* = 0) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1) + m_storage.data()[0] = val0; + } - /** \copydoc MatrixBase::operator=(const EigenBase&) - */ - template - EIGEN_STRONG_INLINE Derived& operator=(const EigenBase &other) - { - _resize_to_match(other); - Base::operator=(other.derived()); - return this->derived(); - } + // We have a 1x1 matrix/array => the argument is interpreted as the value of the unique coefficient (case where scalar + // type match the index type) + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1( + const Index& val0, + std::enable_if_t<(!internal::is_same::value) && (internal::is_same::value) && + Base::SizeAtCompileTime == 1 && internal::is_convertible::value, + T*>* = 0) { + EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 1) + m_storage.data()[0] = Scalar(val0); + } - /** \sa MatrixBase::operator=(const EigenBase&) */ - template - EIGEN_STRONG_INLINE PlainObjectBase(const EigenBase &other) - : m_storage(other.derived().rows() * other.derived().cols(), other.derived().rows(), other.derived().cols()) - { - _check_template_params(); - internal::check_rows_cols_for_overflow::run(other.derived().rows(), other.derived().cols()); - Base::operator=(other.derived()); - } + // Initialize a fixed size matrix from a pointer to raw data + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const Scalar* data) { + this->_set_noalias(ConstMapType(data)); + } - /** \name Map - * These are convenience functions returning Map objects. The Map() static functions return unaligned Map objects, - * while the AlignedMap() functions return aligned Map objects and thus should be called only with 16-byte-aligned - * \a data pointers. - * - * \see class Map - */ - //@{ - static inline ConstMapType Map(const Scalar* data) - { return ConstMapType(data); } - static inline MapType Map(Scalar* data) - { return MapType(data); } - static inline ConstMapType Map(const Scalar* data, Index size) - { return ConstMapType(data, size); } - static inline MapType Map(Scalar* data, Index size) - { return MapType(data, size); } - static inline ConstMapType Map(const Scalar* data, Index rows, Index cols) - { return ConstMapType(data, rows, cols); } - static inline MapType Map(Scalar* data, Index rows, Index cols) - { return MapType(data, rows, cols); } - - static inline ConstAlignedMapType MapAligned(const Scalar* data) - { return ConstAlignedMapType(data); } - static inline AlignedMapType MapAligned(Scalar* data) - { return AlignedMapType(data); } - static inline ConstAlignedMapType MapAligned(const Scalar* data, Index size) - { return ConstAlignedMapType(data, size); } - static inline AlignedMapType MapAligned(Scalar* data, Index size) - { return AlignedMapType(data, size); } - static inline ConstAlignedMapType MapAligned(const Scalar* data, Index rows, Index cols) - { return ConstAlignedMapType(data, rows, cols); } - static inline AlignedMapType MapAligned(Scalar* data, Index rows, Index cols) - { return AlignedMapType(data, rows, cols); } - - template - static inline typename StridedConstMapType >::type Map(const Scalar* data, const Stride& stride) - { return typename StridedConstMapType >::type(data, stride); } - template - static inline typename StridedMapType >::type Map(Scalar* data, const Stride& stride) - { return typename StridedMapType >::type(data, stride); } - template - static inline typename StridedConstMapType >::type Map(const Scalar* data, Index size, const Stride& stride) - { return typename StridedConstMapType >::type(data, size, stride); } - template - static inline typename StridedMapType >::type Map(Scalar* data, Index size, const Stride& stride) - { return typename StridedMapType >::type(data, size, stride); } - template - static inline typename StridedConstMapType >::type Map(const Scalar* data, Index rows, Index cols, const Stride& stride) - { return typename StridedConstMapType >::type(data, rows, cols, stride); } - template - static inline typename StridedMapType >::type Map(Scalar* data, Index rows, Index cols, const Stride& stride) - { return typename StridedMapType >::type(data, rows, cols, stride); } - - template - static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, const Stride& stride) - { return typename StridedConstAlignedMapType >::type(data, stride); } - template - static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, const Stride& stride) - { return typename StridedAlignedMapType >::type(data, stride); } - template - static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index size, const Stride& stride) - { return typename StridedConstAlignedMapType >::type(data, size, stride); } - template - static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index size, const Stride& stride) - { return typename StridedAlignedMapType >::type(data, size, stride); } - template - static inline typename StridedConstAlignedMapType >::type MapAligned(const Scalar* data, Index rows, Index cols, const Stride& stride) - { return typename StridedConstAlignedMapType >::type(data, rows, cols, stride); } - template - static inline typename StridedAlignedMapType >::type MapAligned(Scalar* data, Index rows, Index cols, const Stride& stride) - { return typename StridedAlignedMapType >::type(data, rows, cols, stride); } - //@} - - using Base::setConstant; - Derived& setConstant(Index size, const Scalar& value); - Derived& setConstant(Index rows, Index cols, const Scalar& value); - - using Base::setZero; - Derived& setZero(Index size); - Derived& setZero(Index rows, Index cols); - - using Base::setOnes; - Derived& setOnes(Index size); - Derived& setOnes(Index rows, Index cols); - - using Base::setRandom; - Derived& setRandom(Index size); - Derived& setRandom(Index rows, Index cols); - - #ifdef EIGEN_PLAINOBJECTBASE_PLUGIN - #include EIGEN_PLAINOBJECTBASE_PLUGIN - #endif - - protected: - /** \internal Resizes *this in preparation for assigning \a other to it. - * Takes care of doing all the checking that's needed. - * - * Note that copying a row-vector into a vector (and conversely) is allowed. - * The resizing, if any, is then done in the appropriate way so that row-vectors - * remain row-vectors and vectors remain vectors. - */ - template - EIGEN_STRONG_INLINE void _resize_to_match(const EigenBase& other) - { - #ifdef EIGEN_NO_AUTOMATIC_RESIZING - eigen_assert((this->size()==0 || (IsVectorAtCompileTime ? (this->size() == other.size()) - : (rows() == other.rows() && cols() == other.cols()))) - && "Size mismatch. Automatic resizing is disabled because EIGEN_NO_AUTOMATIC_RESIZING is defined"); - EIGEN_ONLY_USED_FOR_DEBUG(other); - if(this->size()==0) - resizeLike(other); - #else - resizeLike(other); - #endif - } + // Initialize an arbitrary matrix from a dense expression + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const DenseBase& other) { + this->_set_noalias(other); + } - /** - * \brief Copies the value of the expression \a other into \c *this with automatic resizing. - * - * *this might be resized to match the dimensions of \a other. If *this was a null matrix (not already initialized), - * it will be initialized. - * - * Note that copying a row-vector into a vector (and conversely) is allowed. - * The resizing, if any, is then done in the appropriate way so that row-vectors - * remain row-vectors and vectors remain vectors. - * - * \sa operator=(const MatrixBase&), _set_noalias() - * - * \internal - */ - template - EIGEN_STRONG_INLINE Derived& _set(const DenseBase& other) - { - _set_selector(other.derived(), typename internal::conditional(int(OtherDerived::Flags) & EvalBeforeAssigningBit), internal::true_type, internal::false_type>::type()); - return this->derived(); - } + // Initialize an arbitrary matrix from an object convertible to the Derived type. + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const Derived& other) { + this->_set_noalias(other); + } - template - EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::true_type&) { _set_noalias(other.eval()); } + // Initialize an arbitrary matrix from a generic Eigen expression + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const EigenBase& other) { + this->derived() = other; + } - template - EIGEN_STRONG_INLINE void _set_selector(const OtherDerived& other, const internal::false_type&) { _set_noalias(other); } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const ReturnByValue& other) { + resize(other.rows(), other.cols()); + other.evalTo(this->derived()); + } - /** \internal Like _set() but additionally makes the assumption that no aliasing effect can happen (which - * is the case when creating a new matrix) so one can enforce lazy evaluation. - * - * \sa operator=(const MatrixBase&), _set() - */ - template - EIGEN_STRONG_INLINE Derived& _set_noalias(const DenseBase& other) - { - // I don't think we need this resize call since the lazyAssign will anyways resize - // and lazyAssign will be called by the assign selector. - //_resize_to_match(other); - // the 'false' below means to enforce lazy evaluation. We don't use lazyAssign() because - // it wouldn't allow to copy a row-vector into a column-vector. - return internal::assign_selector::run(this->derived(), other.derived()); - } + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1(const RotationBase& r) { + this->derived() = r; + } - template - EIGEN_STRONG_INLINE void _init2(Index nbRows, Index nbCols, typename internal::enable_if::type* = 0) - { - EIGEN_STATIC_ASSERT(bool(NumTraits::IsInteger) && - bool(NumTraits::IsInteger), - FLOATING_POINT_ARGUMENT_PASSED__INTEGER_WAS_EXPECTED) - resize(nbRows,nbCols); - } - template - EIGEN_STRONG_INLINE void _init2(const Scalar& val0, const Scalar& val1, typename internal::enable_if::type* = 0) - { - EIGEN_STATIC_ASSERT_VECTOR_SPECIFIC_SIZE(PlainObjectBase, 2) - m_storage.data()[0] = val0; - m_storage.data()[1] = val1; - } + // For fixed-size Array + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1( + const Scalar& val0, + std::enable_if_t::value && + internal::is_same::XprKind, ArrayXpr>::value, + T>* = 0) { + Base::setConstant(val0); + } - template - friend struct internal::matrix_swap_impl; + // For fixed-size Array + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void _init1( + const Index& val0, + std::enable_if_t<(!internal::is_same::value) && (internal::is_same::value) && + Base::SizeAtCompileTime != Dynamic && Base::SizeAtCompileTime != 1 && + internal::is_convertible::value && + internal::is_same::XprKind, ArrayXpr>::value, + T*>* = 0) { + Base::setConstant(val0); + } - /** \internal generic implementation of swap for dense storage since for dynamic-sized matrices of same type it is enough to swap the - * data pointers. - */ - template - void _swap(DenseBase const & other) - { - enum { SwapPointers = internal::is_same::value && Base::SizeAtCompileTime==Dynamic }; - internal::matrix_swap_impl::run(this->derived(), other.const_cast_derived()); - } + template + friend struct internal::matrix_swap_impl; - public: + public: #ifndef EIGEN_PARSED_BY_DOXYGEN - static EIGEN_STRONG_INLINE void _check_template_params() - { - EIGEN_STATIC_ASSERT((EIGEN_IMPLIES(MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1, (Options&RowMajor)==RowMajor) - && EIGEN_IMPLIES(MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1, (Options&RowMajor)==0) - && ((RowsAtCompileTime == Dynamic) || (RowsAtCompileTime >= 0)) - && ((ColsAtCompileTime == Dynamic) || (ColsAtCompileTime >= 0)) - && ((MaxRowsAtCompileTime == Dynamic) || (MaxRowsAtCompileTime >= 0)) - && ((MaxColsAtCompileTime == Dynamic) || (MaxColsAtCompileTime >= 0)) - && (MaxRowsAtCompileTime == RowsAtCompileTime || RowsAtCompileTime==Dynamic) - && (MaxColsAtCompileTime == ColsAtCompileTime || ColsAtCompileTime==Dynamic) - && (Options & (DontAlign|RowMajor)) == Options), - INVALID_MATRIX_TEMPLATE_PARAMETERS) - } -#endif + /** \internal + * \brief Override DenseBase::swap() since for dynamic-sized matrices + * of same type it is enough to swap the data pointers. + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(DenseBase& other) { + enum {SwapPointers = internal::is_same::value && Base::SizeAtCompileTime == Dynamic}; + internal::matrix_swap_impl::run(this->derived(), other.derived()); + } -private: - enum { ThisConstantIsPrivateInPlainObjectBase }; + /** \internal + * \brief const version forwarded to DenseBase::swap + */ + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void swap(DenseBase const& other) { + Base::swap(other.derived()); + } + + enum {IsPlainObjectBase = 1}; +#endif + public: + // These apparently need to be down here for nvcc+icc to prevent duplicate + // Map symbol. + template + friend class Eigen::Map; + friend class Eigen::Map; + friend class Eigen::Map; +#if EIGEN_MAX_ALIGN_BYTES > 0 + // for EIGEN_MAX_ALIGN_BYTES==0, AlignedMax==Unaligned, and many compilers generate warnings for friend-ing a class + // twice. + friend class Eigen::Map; + friend class Eigen::Map; +#endif }; namespace internal { template -struct conservative_resize_like_impl -{ - typedef typename Derived::Index Index; - static void run(DenseBase& _this, Index rows, Index cols) - { +struct conservative_resize_like_impl { + static constexpr bool IsRelocatable = std::is_trivially_copyable::value; + static void run(DenseBase& _this, Index rows, Index cols) { if (_this.rows() == rows && _this.cols() == cols) return; EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(Derived) - if ( ( Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows - (!Derived::IsRowMajor && _this.rows() == rows) ) // column-major and we change only the number of columns - { - internal::check_rows_cols_for_overflow::run(rows, cols); - _this.derived().m_storage.conservativeResize(rows*cols,rows,cols); - } - else + if (IsRelocatable && + ((Derived::IsRowMajor && _this.cols() == cols) || // row-major and we change only the number of rows + (!Derived::IsRowMajor && _this.rows() == rows))) // column-major and we change only the number of columns { +#ifndef EIGEN_NO_DEBUG + internal::check_rows_cols_for_overflow::run(rows, cols); +#endif + _this.derived().m_storage.conservativeResize(rows * cols, rows, cols); + } else { // The storage order does not allow us to use reallocation. - typename Derived::PlainObject tmp(rows,cols); - const Index common_rows = (std::min)(rows, _this.rows()); - const Index common_cols = (std::min)(cols, _this.cols()); - tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols); + Derived tmp(rows, cols); + const Index common_rows = numext::mini(rows, _this.rows()); + const Index common_cols = numext::mini(cols, _this.cols()); + tmp.block(0, 0, common_rows, common_cols) = _this.block(0, 0, common_rows, common_cols); _this.derived().swap(tmp); } } - static void run(DenseBase& _this, const DenseBase& other) - { + static void run(DenseBase& _this, const DenseBase& other) { if (_this.rows() == other.rows() && _this.cols() == other.cols()) return; // Note: Here is space for improvement. Basically, for conservativeResize(Index,Index), @@ -743,24 +938,24 @@ struct conservative_resize_like_impl EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(Derived) EIGEN_STATIC_ASSERT_DYNAMIC_SIZE(OtherDerived) - if ( ( Derived::IsRowMajor && _this.cols() == other.cols()) || // row-major and we change only the number of rows - (!Derived::IsRowMajor && _this.rows() == other.rows()) ) // column-major and we change only the number of columns + if (IsRelocatable && + ((Derived::IsRowMajor && _this.cols() == other.cols()) || // row-major and we change only the number of rows + (!Derived::IsRowMajor && + _this.rows() == other.rows()))) // column-major and we change only the number of columns { const Index new_rows = other.rows() - _this.rows(); const Index new_cols = other.cols() - _this.cols(); - _this.derived().m_storage.conservativeResize(other.size(),other.rows(),other.cols()); - if (new_rows>0) + _this.derived().m_storage.conservativeResize(other.size(), other.rows(), other.cols()); + if (new_rows > 0) _this.bottomRightCorner(new_rows, other.cols()) = other.bottomRows(new_rows); - else if (new_cols>0) + else if (new_cols > 0) _this.bottomRightCorner(other.rows(), new_cols) = other.rightCols(new_cols); - } - else - { + } else { // The storage order does not allow us to use reallocation. - typename Derived::PlainObject tmp(other); - const Index common_rows = (std::min)(tmp.rows(), _this.rows()); - const Index common_cols = (std::min)(tmp.cols(), _this.cols()); - tmp.block(0,0,common_rows,common_cols) = _this.block(0,0,common_rows,common_cols); + Derived tmp(other); + const Index common_rows = numext::mini(tmp.rows(), _this.rows()); + const Index common_cols = numext::mini(tmp.cols(), _this.cols()); + tmp.block(0, 0, common_rows, common_cols) = _this.block(0, 0, common_rows, common_cols); _this.derived().swap(tmp); } } @@ -769,54 +964,51 @@ struct conservative_resize_like_impl // Here, the specialization for vectors inherits from the general matrix case // to allow calling .conservativeResize(rows,cols) on vectors. template -struct conservative_resize_like_impl - : conservative_resize_like_impl -{ - using conservative_resize_like_impl::run; - - typedef typename Derived::Index Index; - static void run(DenseBase& _this, Index size) - { - const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : size; - const Index new_cols = Derived::RowsAtCompileTime==1 ? size : 1; - _this.derived().m_storage.conservativeResize(size,new_rows,new_cols); - } - - static void run(DenseBase& _this, const DenseBase& other) - { +struct conservative_resize_like_impl + : conservative_resize_like_impl { + typedef conservative_resize_like_impl Base; + using Base::IsRelocatable; + using Base::run; + + static void run(DenseBase& _this, Index size) { + const Index new_rows = Derived::RowsAtCompileTime == 1 ? 1 : size; + const Index new_cols = Derived::RowsAtCompileTime == 1 ? size : 1; + if (IsRelocatable) + _this.derived().m_storage.conservativeResize(size, new_rows, new_cols); + else + Base::run(_this.derived(), new_rows, new_cols); + } + + static void run(DenseBase& _this, const DenseBase& other) { if (_this.rows() == other.rows() && _this.cols() == other.cols()) return; const Index num_new_elements = other.size() - _this.size(); - const Index new_rows = Derived::RowsAtCompileTime==1 ? 1 : other.rows(); - const Index new_cols = Derived::RowsAtCompileTime==1 ? other.cols() : 1; - _this.derived().m_storage.conservativeResize(other.size(),new_rows,new_cols); + const Index new_rows = Derived::RowsAtCompileTime == 1 ? 1 : other.rows(); + const Index new_cols = Derived::RowsAtCompileTime == 1 ? other.cols() : 1; + if (IsRelocatable) + _this.derived().m_storage.conservativeResize(other.size(), new_rows, new_cols); + else + Base::run(_this.derived(), new_rows, new_cols); - if (num_new_elements > 0) - _this.tail(num_new_elements) = other.tail(num_new_elements); + if (num_new_elements > 0) _this.tail(num_new_elements) = other.tail(num_new_elements); } }; -template -struct matrix_swap_impl -{ - static inline void run(MatrixTypeA& a, MatrixTypeB& b) - { - a.base().swap(b); - } +template +struct matrix_swap_impl { + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE void run(MatrixTypeA& a, MatrixTypeB& b) { a.base().swap(b); } }; -template -struct matrix_swap_impl -{ - static inline void run(MatrixTypeA& a, MatrixTypeB& b) - { +template +struct matrix_swap_impl { + EIGEN_DEVICE_FUNC static inline void run(MatrixTypeA& a, MatrixTypeB& b) { static_cast(a).m_storage.swap(static_cast(b).m_storage); } }; -} // end namespace internal +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_DENSESTORAGEBASE_H +#endif // EIGEN_DENSESTORAGEBASE_H diff --git a/inst/include/Eigen/src/Core/Product.h b/inst/include/Eigen/src/Core/Product.h new file mode 100644 index 00000000..e16c7cc9 --- /dev/null +++ b/inst/include/Eigen/src/Core/Product.h @@ -0,0 +1,307 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2011 Gael Guennebaud +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_PRODUCT_H +#define EIGEN_PRODUCT_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +template +class ProductImpl; + +namespace internal { + +template +struct traits> { + typedef remove_all_t LhsCleaned; + typedef remove_all_t RhsCleaned; + typedef traits LhsTraits; + typedef traits RhsTraits; + + typedef MatrixXpr XprKind; + + typedef typename ScalarBinaryOpTraits::Scalar, + typename traits::Scalar>::ReturnType Scalar; + typedef typename product_promote_storage_type::ret>::ret StorageKind; + typedef typename promote_index_type::type + StorageIndex; + + enum { + RowsAtCompileTime = LhsTraits::RowsAtCompileTime, + ColsAtCompileTime = RhsTraits::ColsAtCompileTime, + MaxRowsAtCompileTime = LhsTraits::MaxRowsAtCompileTime, + MaxColsAtCompileTime = RhsTraits::MaxColsAtCompileTime, + + // FIXME: only needed by GeneralMatrixMatrixTriangular + InnerSize = min_size_prefer_fixed(LhsTraits::ColsAtCompileTime, RhsTraits::RowsAtCompileTime), + + // The storage order is somewhat arbitrary here. The correct one will be determined through the evaluator. + Flags = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? RowMajorBit + : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) ? 0 + : (((LhsTraits::Flags & NoPreferredStorageOrderBit) && (RhsTraits::Flags & RowMajorBit)) || + ((RhsTraits::Flags & NoPreferredStorageOrderBit) && (LhsTraits::Flags & RowMajorBit))) + ? RowMajorBit + : NoPreferredStorageOrderBit + }; +}; + +struct TransposeProductEnum { + // convenience enumerations to specialize transposed products + enum : int { + Default = 0x00, + Matrix = 0x01, + Permutation = 0x02, + MatrixMatrix = (Matrix << 8) | Matrix, + MatrixPermutation = (Matrix << 8) | Permutation, + PermutationMatrix = (Permutation << 8) | Matrix + }; +}; +template +struct TransposeKind { + static constexpr int Kind = is_matrix_base_xpr::value ? TransposeProductEnum::Matrix + : is_permutation_base_xpr::value ? TransposeProductEnum::Permutation + : TransposeProductEnum::Default; +}; + +template +struct TransposeProductKind { + static constexpr int Kind = (TransposeKind::Kind << 8) | TransposeKind::Kind; +}; + +template ::Kind> +struct product_transpose_helper { + // by default, don't optimize the transposed product + using Derived = Product; + using Scalar = typename Derived::Scalar; + using TransposeType = Transpose; + using ConjugateTransposeType = CwiseUnaryOp, TransposeType>; + using AdjointType = std::conditional_t::IsComplex, ConjugateTransposeType, TransposeType>; + + // return (lhs * rhs)^T + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TransposeType run_transpose(const Derived& derived) { + return TransposeType(derived); + } + // return (lhs * rhs)^H + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE AdjointType run_adjoint(const Derived& derived) { + return AdjointType(TransposeType(derived)); + } +}; + +template +struct product_transpose_helper { + // expand the transposed matrix-matrix product + using Derived = Product; + + using LhsScalar = typename traits::Scalar; + using LhsTransposeType = typename DenseBase::ConstTransposeReturnType; + using LhsConjugateTransposeType = CwiseUnaryOp, LhsTransposeType>; + using LhsAdjointType = + std::conditional_t::IsComplex, LhsConjugateTransposeType, LhsTransposeType>; + + using RhsScalar = typename traits::Scalar; + using RhsTransposeType = typename DenseBase::ConstTransposeReturnType; + using RhsConjugateTransposeType = CwiseUnaryOp, RhsTransposeType>; + using RhsAdjointType = + std::conditional_t::IsComplex, RhsConjugateTransposeType, RhsTransposeType>; + + using TransposeType = Product; + using AdjointType = Product; + + // return rhs^T * lhs^T + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TransposeType run_transpose(const Derived& derived) { + return TransposeType(RhsTransposeType(derived.rhs()), LhsTransposeType(derived.lhs())); + } + // return rhs^H * lhs^H + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE AdjointType run_adjoint(const Derived& derived) { + return AdjointType(RhsAdjointType(RhsTransposeType(derived.rhs())), + LhsAdjointType(LhsTransposeType(derived.lhs()))); + } +}; +template +struct product_transpose_helper { + // expand the transposed permutation-matrix product + using Derived = Product; + + using LhsInverseType = typename PermutationBase::InverseReturnType; + + using RhsScalar = typename traits::Scalar; + using RhsTransposeType = typename DenseBase::ConstTransposeReturnType; + using RhsConjugateTransposeType = CwiseUnaryOp, RhsTransposeType>; + using RhsAdjointType = + std::conditional_t::IsComplex, RhsConjugateTransposeType, RhsTransposeType>; + + using TransposeType = Product; + using AdjointType = Product; + + // return rhs^T * lhs^-1 + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TransposeType run_transpose(const Derived& derived) { + return TransposeType(RhsTransposeType(derived.rhs()), LhsInverseType(derived.lhs())); + } + // return rhs^H * lhs^-1 + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE AdjointType run_adjoint(const Derived& derived) { + return AdjointType(RhsAdjointType(RhsTransposeType(derived.rhs())), LhsInverseType(derived.lhs())); + } +}; +template +struct product_transpose_helper { + // expand the transposed matrix-permutation product + using Derived = Product; + + using LhsScalar = typename traits::Scalar; + using LhsTransposeType = typename DenseBase::ConstTransposeReturnType; + using LhsConjugateTransposeType = CwiseUnaryOp, LhsTransposeType>; + using LhsAdjointType = + std::conditional_t::IsComplex, LhsConjugateTransposeType, LhsTransposeType>; + + using RhsInverseType = typename PermutationBase::InverseReturnType; + + using TransposeType = Product; + using AdjointType = Product; + + // return rhs^-1 * lhs^T + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TransposeType run_transpose(const Derived& derived) { + return TransposeType(RhsInverseType(derived.rhs()), LhsTransposeType(derived.lhs())); + } + // return rhs^-1 * lhs^H + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE AdjointType run_adjoint(const Derived& derived) { + return AdjointType(RhsInverseType(derived.rhs()), LhsAdjointType(LhsTransposeType(derived.lhs()))); + } +}; + +} // end namespace internal + +/** \class Product + * \ingroup Core_Module + * + * \brief Expression of the product of two arbitrary matrices or vectors + * + * \tparam Lhs_ the type of the left-hand side expression + * \tparam Rhs_ the type of the right-hand side expression + * + * This class represents an expression of the product of two arbitrary matrices. + * + * The other template parameters are: + * \tparam Option can be DefaultProduct, AliasFreeProduct, or LazyProduct + * + */ +template +class Product + : public ProductImpl::StorageKind, typename internal::traits::StorageKind, + internal::product_type::ret>::ret> { + public: + typedef Lhs_ Lhs; + typedef Rhs_ Rhs; + + typedef + typename ProductImpl::StorageKind, typename internal::traits::StorageKind, + internal::product_type::ret>::ret>::Base Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(Product) + + typedef typename internal::ref_selector::type LhsNested; + typedef typename internal::ref_selector::type RhsNested; + typedef internal::remove_all_t LhsNestedCleaned; + typedef internal::remove_all_t RhsNestedCleaned; + + using TransposeReturnType = typename internal::product_transpose_helper::TransposeType; + using AdjointReturnType = typename internal::product_transpose_helper::AdjointType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Product(const Lhs& lhs, const Rhs& rhs) : m_lhs(lhs), m_rhs(rhs) { + eigen_assert(lhs.cols() == rhs.rows() && "invalid matrix product" && + "if you wanted a coeff-wise or a dot product use the respective explicit functions"); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index rows() const noexcept { return m_lhs.rows(); } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE constexpr Index cols() const noexcept { return m_rhs.cols(); } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const LhsNestedCleaned& lhs() const { return m_lhs; } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const RhsNestedCleaned& rhs() const { return m_rhs; } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE TransposeReturnType transpose() const { + return internal::product_transpose_helper::run_transpose(*this); + } + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE AdjointReturnType adjoint() const { + return internal::product_transpose_helper::run_adjoint(*this); + } + + protected: + LhsNested m_lhs; + RhsNested m_rhs; +}; + +namespace internal { + +template ::ret> +class dense_product_base : public internal::dense_xpr_base>::type {}; + +/** Conversion to scalar for inner-products */ +template +class dense_product_base + : public internal::dense_xpr_base>::type { + typedef Product ProductXpr; + typedef typename internal::dense_xpr_base::type Base; + + public: + using Base::derived; + typedef typename Base::Scalar Scalar; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE operator const Scalar() const { + return internal::evaluator(derived()).coeff(0, 0); + } +}; + +} // namespace internal + +// Generic API dispatcher +template +class ProductImpl : public internal::generic_xpr_base, MatrixXpr, StorageKind>::type { + public: + typedef typename internal::generic_xpr_base, MatrixXpr, StorageKind>::type Base; +}; + +template +class ProductImpl : public internal::dense_product_base { + typedef Product Derived; + + public: + typedef typename internal::dense_product_base Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Derived) + protected: + enum { + IsOneByOne = (RowsAtCompileTime == 1 || RowsAtCompileTime == Dynamic) && + (ColsAtCompileTime == 1 || ColsAtCompileTime == Dynamic), + EnableCoeff = IsOneByOne || Option == LazyProduct + }; + + public: + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index row, Index col) const { + EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); + eigen_assert((Option == LazyProduct) || (this->rows() == 1 && this->cols() == 1)); + + return internal::evaluator(derived()).coeff(row, col); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index i) const { + EIGEN_STATIC_ASSERT(EnableCoeff, THIS_METHOD_IS_ONLY_FOR_INNER_OR_LAZY_PRODUCTS); + eigen_assert((Option == LazyProduct) || (this->rows() == 1 && this->cols() == 1)); + + return internal::evaluator(derived()).coeff(i); + } +}; + +} // end namespace Eigen + +#endif // EIGEN_PRODUCT_H diff --git a/inst/include/Eigen/src/Core/ProductBase.h b/inst/include/Eigen/src/Core/ProductBase.h deleted file mode 100644 index cf74470a..00000000 --- a/inst/include/Eigen/src/Core/ProductBase.h +++ /dev/null @@ -1,290 +0,0 @@ -// This file is part of Eigen, a lightweight C++ template library -// for linear algebra. -// -// Copyright (C) 2009-2010 Gael Guennebaud -// -// This Source Code Form is subject to the terms of the Mozilla -// Public License v. 2.0. If a copy of the MPL was not distributed -// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. - -#ifndef EIGEN_PRODUCTBASE_H -#define EIGEN_PRODUCTBASE_H - -namespace Eigen { - -/** \class ProductBase - * \ingroup Core_Module - * - */ - -namespace internal { -template -struct traits > -{ - typedef MatrixXpr XprKind; - typedef typename remove_all<_Lhs>::type Lhs; - typedef typename remove_all<_Rhs>::type Rhs; - typedef typename scalar_product_traits::ReturnType Scalar; - typedef typename promote_storage_type::StorageKind, - typename traits::StorageKind>::ret StorageKind; - typedef typename promote_index_type::Index, - typename traits::Index>::type Index; - enum { - RowsAtCompileTime = traits::RowsAtCompileTime, - ColsAtCompileTime = traits::ColsAtCompileTime, - MaxRowsAtCompileTime = traits::MaxRowsAtCompileTime, - MaxColsAtCompileTime = traits::MaxColsAtCompileTime, - Flags = (MaxRowsAtCompileTime==1 ? RowMajorBit : 0) - | EvalBeforeNestingBit | EvalBeforeAssigningBit | NestByRefBit, - // Note that EvalBeforeNestingBit and NestByRefBit - // are not used in practice because nested is overloaded for products - CoeffReadCost = 0 // FIXME why is it needed ? - }; -}; -} - -#define EIGEN_PRODUCT_PUBLIC_INTERFACE(Derived) \ - typedef ProductBase Base; \ - EIGEN_DENSE_PUBLIC_INTERFACE(Derived) \ - typedef typename Base::LhsNested LhsNested; \ - typedef typename Base::_LhsNested _LhsNested; \ - typedef typename Base::LhsBlasTraits LhsBlasTraits; \ - typedef typename Base::ActualLhsType ActualLhsType; \ - typedef typename Base::_ActualLhsType _ActualLhsType; \ - typedef typename Base::RhsNested RhsNested; \ - typedef typename Base::_RhsNested _RhsNested; \ - typedef typename Base::RhsBlasTraits RhsBlasTraits; \ - typedef typename Base::ActualRhsType ActualRhsType; \ - typedef typename Base::_ActualRhsType _ActualRhsType; \ - using Base::m_lhs; \ - using Base::m_rhs; - -template -class ProductBase : public MatrixBase -{ - public: - typedef MatrixBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(ProductBase) - - typedef typename Lhs::Nested LhsNested; - typedef typename internal::remove_all::type _LhsNested; - typedef internal::blas_traits<_LhsNested> LhsBlasTraits; - typedef typename LhsBlasTraits::DirectLinearAccessType ActualLhsType; - typedef typename internal::remove_all::type _ActualLhsType; - typedef typename internal::traits::Scalar LhsScalar; - - typedef typename Rhs::Nested RhsNested; - typedef typename internal::remove_all::type _RhsNested; - typedef internal::blas_traits<_RhsNested> RhsBlasTraits; - typedef typename RhsBlasTraits::DirectLinearAccessType ActualRhsType; - typedef typename internal::remove_all::type _ActualRhsType; - typedef typename internal::traits::Scalar RhsScalar; - - // Diagonal of a product: no need to evaluate the arguments because they are going to be evaluated only once - typedef CoeffBasedProduct FullyLazyCoeffBaseProductType; - - public: - -#ifndef EIGEN_NO_MALLOC - typedef typename Base::PlainObject BasePlainObject; - typedef Matrix DynPlainObject; - typedef typename internal::conditional<(BasePlainObject::SizeAtCompileTime==Dynamic) || (BasePlainObject::SizeAtCompileTime*int(sizeof(Scalar)) < int(EIGEN_STACK_ALLOCATION_LIMIT)), - BasePlainObject, DynPlainObject>::type PlainObject; -#else - typedef typename Base::PlainObject PlainObject; -#endif - - ProductBase(const Lhs& a_lhs, const Rhs& a_rhs) - : m_lhs(a_lhs), m_rhs(a_rhs) - { - eigen_assert(a_lhs.cols() == a_rhs.rows() - && "invalid matrix product" - && "if you wanted a coeff-wise or a dot product use the respective explicit functions"); - } - - inline Index rows() const { return m_lhs.rows(); } - inline Index cols() const { return m_rhs.cols(); } - - template - inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst,Scalar(1)); } - - template - inline void addTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(1)); } - - template - inline void subTo(Dest& dst) const { scaleAndAddTo(dst,Scalar(-1)); } - - template - inline void scaleAndAddTo(Dest& dst, const Scalar& alpha) const { derived().scaleAndAddTo(dst,alpha); } - - const _LhsNested& lhs() const { return m_lhs; } - const _RhsNested& rhs() const { return m_rhs; } - - // Implicit conversion to the nested type (trigger the evaluation of the product) - operator const PlainObject& () const - { - m_result.resize(m_lhs.rows(), m_rhs.cols()); - derived().evalTo(m_result); - return m_result; - } - - const Diagonal diagonal() const - { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); } - - template - const Diagonal diagonal() const - { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs); } - - const Diagonal diagonal(Index index) const - { return FullyLazyCoeffBaseProductType(m_lhs, m_rhs).diagonal(index); } - - // restrict coeff accessors to 1x1 expressions. No need to care about mutators here since this isnt a Lvalue expression - typename Base::CoeffReturnType coeff(Index row, Index col) const - { -#ifdef EIGEN2_SUPPORT - return lhs().row(row).cwiseProduct(rhs().col(col).transpose()).sum(); -#else - EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) - eigen_assert(this->rows() == 1 && this->cols() == 1); - Matrix result = *this; - return result.coeff(row,col); -#endif - } - - typename Base::CoeffReturnType coeff(Index i) const - { - EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) - eigen_assert(this->rows() == 1 && this->cols() == 1); - Matrix result = *this; - return result.coeff(i); - } - - const Scalar& coeffRef(Index row, Index col) const - { - EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) - eigen_assert(this->rows() == 1 && this->cols() == 1); - return derived().coeffRef(row,col); - } - - const Scalar& coeffRef(Index i) const - { - EIGEN_STATIC_ASSERT_SIZE_1x1(Derived) - eigen_assert(this->rows() == 1 && this->cols() == 1); - return derived().coeffRef(i); - } - - protected: - - LhsNested m_lhs; - RhsNested m_rhs; - - mutable PlainObject m_result; -}; - -// here we need to overload the nested rule for products -// such that the nested type is a const reference to a plain matrix -namespace internal { -template -struct nested, N, PlainObject> -{ - typedef typename GeneralProduct::PlainObject const& type; -}; -template -struct nested, N, PlainObject> -{ - typedef typename GeneralProduct::PlainObject const& type; -}; -} - -template -class ScaledProduct; - -// Note that these two operator* functions are not defined as member -// functions of ProductBase, because, otherwise we would have to -// define all overloads defined in MatrixBase. Furthermore, Using -// "using Base::operator*" would not work with MSVC. -// -// Also note that here we accept any compatible scalar types -template -const ScaledProduct -operator*(const ProductBase& prod, const typename Derived::Scalar& x) -{ return ScaledProduct(prod.derived(), x); } - -template -typename internal::enable_if::value, - const ScaledProduct >::type -operator*(const ProductBase& prod, const typename Derived::RealScalar& x) -{ return ScaledProduct(prod.derived(), x); } - - -template -const ScaledProduct -operator*(const typename Derived::Scalar& x,const ProductBase& prod) -{ return ScaledProduct(prod.derived(), x); } - -template -typename internal::enable_if::value, - const ScaledProduct >::type -operator*(const typename Derived::RealScalar& x,const ProductBase& prod) -{ return ScaledProduct(prod.derived(), x); } - -namespace internal { -template -struct traits > - : traits, - typename NestedProduct::_LhsNested, - typename NestedProduct::_RhsNested> > -{ - typedef typename traits::StorageKind StorageKind; -}; -} - -template -class ScaledProduct - : public ProductBase, - typename NestedProduct::_LhsNested, - typename NestedProduct::_RhsNested> -{ - public: - typedef ProductBase, - typename NestedProduct::_LhsNested, - typename NestedProduct::_RhsNested> Base; - typedef typename Base::Scalar Scalar; - typedef typename Base::PlainObject PlainObject; -// EIGEN_PRODUCT_PUBLIC_INTERFACE(ScaledProduct) - - ScaledProduct(const NestedProduct& prod, const Scalar& x) - : Base(prod.lhs(),prod.rhs()), m_prod(prod), m_alpha(x) {} - - template - inline void evalTo(Dest& dst) const { dst.setZero(); scaleAndAddTo(dst, Scalar(1)); } - - template - inline void addTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(1)); } - - template - inline void subTo(Dest& dst) const { scaleAndAddTo(dst, Scalar(-1)); } - - template - inline void scaleAndAddTo(Dest& dst, const Scalar& a_alpha) const { m_prod.derived().scaleAndAddTo(dst,a_alpha * m_alpha); } - - const Scalar& alpha() const { return m_alpha; } - - protected: - const NestedProduct& m_prod; - Scalar m_alpha; -}; - -/** \internal - * Overloaded to perform an efficient C = (A*B).lazy() */ -template -template -Derived& MatrixBase::lazyAssign(const ProductBase& other) -{ - other.derived().evalTo(derived()); - return derived(); -} - -} // end namespace Eigen - -#endif // EIGEN_PRODUCTBASE_H diff --git a/inst/include/Eigen/src/Core/ProductEvaluators.h b/inst/include/Eigen/src/Core/ProductEvaluators.h new file mode 100644 index 00000000..be55be5e --- /dev/null +++ b/inst/include/Eigen/src/Core/ProductEvaluators.h @@ -0,0 +1,1287 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2006-2008 Benoit Jacob +// Copyright (C) 2008-2010 Gael Guennebaud +// Copyright (C) 2011 Jitse Niesen +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_PRODUCTEVALUATORS_H +#define EIGEN_PRODUCTEVALUATORS_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +/** \internal + * Evaluator of a product expression. + * Since products require special treatments to handle all possible cases, + * we simply defer the evaluation logic to a product_evaluator class + * which offers more partial specialization possibilities. + * + * \sa class product_evaluator + */ +template +struct evaluator> : public product_evaluator> { + typedef Product XprType; + typedef product_evaluator Base; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) : Base(xpr) {} +}; + +// Catch "scalar * ( A * B )" and transform it to "(A*scalar) * B" +// TODO we should apply that rule only if that's really helpful +template +struct evaluator_assume_aliasing, + const CwiseNullaryOp, Plain1>, + const Product>> { + static const bool value = true; +}; +template +struct evaluator, + const CwiseNullaryOp, Plain1>, + const Product>> + : public evaluator> { + typedef CwiseBinaryOp, + const CwiseNullaryOp, Plain1>, + const Product> + XprType; + typedef evaluator> Base; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) + : Base(xpr.lhs().functor().m_other * xpr.rhs().lhs() * xpr.rhs().rhs()) {} +}; + +template +struct evaluator, DiagIndex>> + : public evaluator, DiagIndex>> { + typedef Diagonal, DiagIndex> XprType; + typedef evaluator, DiagIndex>> Base; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit evaluator(const XprType& xpr) + : Base(Diagonal, DiagIndex>( + Product(xpr.nestedExpression().lhs(), xpr.nestedExpression().rhs()), xpr.index())) {} +}; + +// Helper class to perform a matrix product with the destination at hand. +// Depending on the sizes of the factors, there are different evaluation strategies +// as controlled by internal::product_type. +template ::Shape, + typename RhsShape = typename evaluator_traits::Shape, + int ProductType = internal::product_type::value> +struct generic_product_impl; + +template +struct evaluator_assume_aliasing> { + static const bool value = true; +}; + +// This is the default evaluator implementation for products: +// It creates a temporary and call generic_product_impl +template +struct product_evaluator, ProductTag, LhsShape, RhsShape> + : public evaluator::PlainObject> { + typedef Product XprType; + typedef typename XprType::PlainObject PlainObject; + typedef evaluator Base; + enum { Flags = Base::Flags | EvalBeforeNestingBit }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit product_evaluator(const XprType& xpr) + : m_result(xpr.rows(), xpr.cols()) { + internal::construct_at(this, m_result); + + // FIXME shall we handle nested_eval here?, + // if so, then we must take care at removing the call to nested_eval in the specializations (e.g., in + // permutation_matrix_product, transposition_matrix_product, etc.) + // typedef typename internal::nested_eval::type LhsNested; + // typedef typename internal::nested_eval::type RhsNested; + // typedef internal::remove_all_t LhsNestedCleaned; + // typedef internal::remove_all_t RhsNestedCleaned; + // + // const LhsNested lhs(xpr.lhs()); + // const RhsNested rhs(xpr.rhs()); + // + // generic_product_impl::evalTo(m_result, lhs, rhs); + + generic_product_impl::evalTo(m_result, xpr.lhs(), xpr.rhs()); + } + + protected: + PlainObject m_result; +}; + +// The following three shortcuts are enabled only if the scalar types match exactly. +// TODO: we could enable them for different scalar types when the product is not vectorized. + +// Dense = Product +template +struct Assignment, internal::assign_op, Dense2Dense, + std::enable_if_t<(Options == DefaultProduct || Options == AliasFreeProduct)>> { + typedef Product SrcXprType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const internal::assign_op&) { + Index dstRows = src.rows(); + Index dstCols = src.cols(); + if ((dst.rows() != dstRows) || (dst.cols() != dstCols)) dst.resize(dstRows, dstCols); + // FIXME shall we handle nested_eval here? + generic_product_impl::evalTo(dst, src.lhs(), src.rhs()); + } +}; + +// Dense += Product +template +struct Assignment, internal::add_assign_op, Dense2Dense, + std::enable_if_t<(Options == DefaultProduct || Options == AliasFreeProduct)>> { + typedef Product SrcXprType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const internal::add_assign_op&) { + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); + // FIXME shall we handle nested_eval here? + generic_product_impl::addTo(dst, src.lhs(), src.rhs()); + } +}; + +// Dense -= Product +template +struct Assignment, internal::sub_assign_op, Dense2Dense, + std::enable_if_t<(Options == DefaultProduct || Options == AliasFreeProduct)>> { + typedef Product SrcXprType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const internal::sub_assign_op&) { + eigen_assert(dst.rows() == src.rows() && dst.cols() == src.cols()); + // FIXME shall we handle nested_eval here? + generic_product_impl::subTo(dst, src.lhs(), src.rhs()); + } +}; + +// Dense ?= scalar * Product +// TODO we should apply that rule if that's really helpful +// for instance, this is not good for inner products +template +struct Assignment, + const CwiseNullaryOp, Plain>, + const Product>, + AssignFunc, Dense2Dense> { + typedef CwiseBinaryOp, + const CwiseNullaryOp, Plain>, + const Product> + SrcXprType; + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const AssignFunc& func) { + call_assignment_no_alias(dst, (src.lhs().functor().m_other * src.rhs().lhs()) * src.rhs().rhs(), func); + } +}; + +//---------------------------------------- +// Catch "Dense ?= xpr + Product<>" expression to save one temporary +// FIXME we could probably enable these rules for any product, i.e., not only Dense and DefaultProduct + +template +struct evaluator_assume_aliasing< + CwiseBinaryOp< + internal::scalar_sum_op::Scalar>, + const OtherXpr, const Product>, + DenseShape> { + static const bool value = true; +}; + +template +struct evaluator_assume_aliasing< + CwiseBinaryOp< + internal::scalar_difference_op::Scalar>, + const OtherXpr, const Product>, + DenseShape> { + static const bool value = true; +}; + +template +struct assignment_from_xpr_op_product { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(DstXprType& dst, const SrcXprType& src, + const InitialFunc& /*func*/) { + call_assignment_no_alias(dst, src.lhs(), Func1()); + call_assignment_no_alias(dst, src.rhs(), Func2()); + } +}; + +#define EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(ASSIGN_OP, BINOP, ASSIGN_OP2) \ + template \ + struct Assignment, const OtherXpr, \ + const Product>, \ + internal::ASSIGN_OP, Dense2Dense> \ + : assignment_from_xpr_op_product, \ + internal::ASSIGN_OP, \ + internal::ASSIGN_OP2> {} + +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(assign_op, scalar_sum_op, add_assign_op); +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(add_assign_op, scalar_sum_op, add_assign_op); +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(sub_assign_op, scalar_sum_op, sub_assign_op); + +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(assign_op, scalar_difference_op, sub_assign_op); +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(add_assign_op, scalar_difference_op, sub_assign_op); +EIGEN_CATCH_ASSIGN_XPR_OP_PRODUCT(sub_assign_op, scalar_difference_op, add_assign_op); + +//---------------------------------------- + +template +struct generic_product_impl { + using impl = default_inner_product_impl; + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + dst.coeffRef(0, 0) = impl::run(lhs, rhs); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + dst.coeffRef(0, 0) += impl::run(lhs, rhs); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + dst.coeffRef(0, 0) -= impl::run(lhs, rhs); + } +}; + +/*********************************************************************** + * Implementation of outer dense * dense vector product + ***********************************************************************/ + +// Column major result +template +void EIGEN_DEVICE_FUNC outer_product_selector_run(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Func& func, + const false_type&) { + evaluator rhsEval(rhs); + ei_declare_local_nested_eval(Lhs, lhs, Rhs::SizeAtCompileTime, actual_lhs); + // FIXME if cols is large enough, then it might be useful to make sure that lhs is sequentially stored + // FIXME not very good if rhs is real and lhs complex while alpha is real too + const Index cols = dst.cols(); + for (Index j = 0; j < cols; ++j) func(dst.col(j), rhsEval.coeff(Index(0), j) * actual_lhs); +} + +// Row major result +template +void EIGEN_DEVICE_FUNC outer_product_selector_run(Dst& dst, const Lhs& lhs, const Rhs& rhs, const Func& func, + const true_type&) { + evaluator lhsEval(lhs); + ei_declare_local_nested_eval(Rhs, rhs, Lhs::SizeAtCompileTime, actual_rhs); + // FIXME if rows is large enough, then it might be useful to make sure that rhs is sequentially stored + // FIXME not very good if lhs is real and rhs complex while alpha is real too + const Index rows = dst.rows(); + for (Index i = 0; i < rows; ++i) func(dst.row(i), lhsEval.coeff(i, Index(0)) * actual_rhs); +} + +template +struct generic_product_impl { + template + struct is_row_major : bool_constant<(int(T::Flags) & RowMajorBit)> {}; + typedef typename Product::Scalar Scalar; + + // TODO it would be nice to be able to exploit our *_assign_op functors for that purpose + struct set { + template + EIGEN_DEVICE_FUNC void operator()(const Dst& dst, const Src& src) const { + dst.const_cast_derived() = src; + } + }; + struct add { + /** Add to dst. */ + template + EIGEN_DEVICE_FUNC void operator()(const Dst& dst, const Src& src) const { + dst.const_cast_derived() += src; + } + }; + struct sub { + template + EIGEN_DEVICE_FUNC void operator()(const Dst& dst, const Src& src) const { + dst.const_cast_derived() -= src; + } + }; + /** Scaled add. */ + struct adds { + Scalar m_scale; + /** Constructor */ + explicit adds(const Scalar& s) : m_scale(s) {} + /** Scaled add to dst. */ + template + void EIGEN_DEVICE_FUNC operator()(const Dst& dst, const Src& src) const { + dst.const_cast_derived() += m_scale * src; + } + }; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + internal::outer_product_selector_run(dst, lhs, rhs, set(), is_row_major()); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + internal::outer_product_selector_run(dst, lhs, rhs, add(), is_row_major()); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + internal::outer_product_selector_run(dst, lhs, rhs, sub(), is_row_major()); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, + const Scalar& alpha) { + internal::outer_product_selector_run(dst, lhs, rhs, adds(alpha), is_row_major()); + } +}; + +// This base class provides default implementations for evalTo, addTo, subTo, in terms of scaleAndAddTo +template +struct generic_product_impl_base { + typedef typename Product::Scalar Scalar; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + dst.setZero(); + scaleAndAddTo(dst, lhs, rhs, Scalar(1)); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + scaleAndAddTo(dst, lhs, rhs, Scalar(1)); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + scaleAndAddTo(dst, lhs, rhs, Scalar(-1)); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void scaleAndAddTo(Dst& dst, const Lhs& lhs, const Rhs& rhs, + const Scalar& alpha) { + Derived::scaleAndAddTo(dst, lhs, rhs, alpha); + } +}; + +template +struct generic_product_impl + : generic_product_impl_base> { + typedef typename nested_eval::type LhsNested; + typedef typename nested_eval::type RhsNested; + typedef typename Product::Scalar Scalar; + enum { Side = Lhs::IsVectorAtCompileTime ? OnTheLeft : OnTheRight }; + typedef internal::remove_all_t> MatrixType; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, + const Scalar& alpha) { + // Fallback to inner product if both the lhs and rhs is a runtime vector. + if (lhs.rows() == 1 && rhs.cols() == 1) { + dst.coeffRef(0, 0) += alpha * lhs.row(0).conjugate().dot(rhs.col(0)); + return; + } + LhsNested actual_lhs(lhs); + RhsNested actual_rhs(rhs); + internal::gemv_dense_selector::HasUsableDirectAccess)>::run(actual_lhs, + actual_rhs, dst, + alpha); + } +}; + +template +struct generic_product_impl { + typedef typename Product::Scalar Scalar; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + // Same as: dst.noalias() = lhs.lazyProduct(rhs); + // but easier on the compiler side + call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::assign_op()); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void addTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + // dst.noalias() += lhs.lazyProduct(rhs); + call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::add_assign_op()); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void subTo(Dst& dst, const Lhs& lhs, const Rhs& rhs) { + // dst.noalias() -= lhs.lazyProduct(rhs); + call_assignment_no_alias(dst, lhs.lazyProduct(rhs), internal::sub_assign_op()); + } + + // This is a special evaluation path called from generic_product_impl<...,GemmProduct> in file GeneralMatrixMatrix.h + // This variant tries to extract scalar multiples from both the LHS and RHS and factor them out. For instance: + // dst {,+,-}= (s1*A)*(B*s2) + // will be rewritten as: + // dst {,+,-}= (s1*s2) * (A.lazyProduct(B)) + // There are at least four benefits of doing so: + // 1 - huge performance gain for heap-allocated matrix types as it save costly allocations. + // 2 - it is faster than simply by-passing the heap allocation through stack allocation. + // 3 - it makes this fallback consistent with the heavy GEMM routine. + // 4 - it fully by-passes huge stack allocation attempts when multiplying huge fixed-size matrices. + // (see https://stackoverflow.com/questions/54738495) + // For small fixed sizes matrices, however, the gains are less obvious, it is sometimes x2 faster, but sometimes x3 + // slower, and the behavior depends also a lot on the compiler... This is why this re-writing strategy is currently + // enabled only when falling back from the main GEMM. + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void eval_dynamic(Dst& dst, const Lhs& lhs, const Rhs& rhs, + const Func& func) { + enum { + HasScalarFactor = blas_traits::HasScalarFactor || blas_traits::HasScalarFactor, + ConjLhs = blas_traits::NeedToConjugate, + ConjRhs = blas_traits::NeedToConjugate + }; + // FIXME: in c++11 this should be auto, and extractScalarFactor should also return auto + // this is important for real*complex_mat + Scalar actualAlpha = combine_scalar_factors(lhs, rhs); + + eval_dynamic_impl(dst, blas_traits::extract(lhs).template conjugateIf(), + blas_traits::extract(rhs).template conjugateIf(), func, actualAlpha, + bool_constant()); + } + + protected: + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void eval_dynamic_impl(Dst& dst, const LhsT& lhs, const RhsT& rhs, + const Func& func, const Scalar& s /* == 1 */, + false_type) { + EIGEN_UNUSED_VARIABLE(s); + eigen_internal_assert(numext::is_exactly_one(s)); + call_restricted_packet_assignment_no_alias(dst, lhs.lazyProduct(rhs), func); + } + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void eval_dynamic_impl(Dst& dst, const LhsT& lhs, const RhsT& rhs, + const Func& func, const Scalar& s, true_type) { + call_restricted_packet_assignment_no_alias(dst, s * lhs.lazyProduct(rhs), func); + } +}; + +// This specialization enforces the use of a coefficient-based evaluation strategy +template +struct generic_product_impl + : generic_product_impl {}; + +// Case 2: Evaluate coeff by coeff +// +// This is mostly taken from CoeffBasedProduct.h +// The main difference is that we add an extra argument to the etor_product_*_impl::run() function +// for the inner dimension of the product, because evaluator object do not know their size. + +template +struct etor_product_coeff_impl; + +template +struct etor_product_packet_impl; + +template +struct product_evaluator, ProductTag, DenseShape, DenseShape> + : evaluator_base> { + typedef Product XprType; + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit product_evaluator(const XprType& xpr) + : m_lhs(xpr.lhs()), + m_rhs(xpr.rhs()), + m_lhsImpl(m_lhs), // FIXME the creation of the evaluator objects should result in a no-op, but check that! + m_rhsImpl(m_rhs), // Moreover, they are only useful for the packet path, so we could completely disable + // them when not needed, or perhaps declare them on the fly on the packet method... We + // have experiment to check what's best. + m_innerDim(xpr.lhs().cols()) { + EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits::MulCost); + EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits::AddCost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); +#if 0 + std::cerr << "LhsOuterStrideBytes= " << LhsOuterStrideBytes << "\n"; + std::cerr << "RhsOuterStrideBytes= " << RhsOuterStrideBytes << "\n"; + std::cerr << "LhsAlignment= " << LhsAlignment << "\n"; + std::cerr << "RhsAlignment= " << RhsAlignment << "\n"; + std::cerr << "CanVectorizeLhs= " << CanVectorizeLhs << "\n"; + std::cerr << "CanVectorizeRhs= " << CanVectorizeRhs << "\n"; + std::cerr << "CanVectorizeInner= " << CanVectorizeInner << "\n"; + std::cerr << "EvalToRowMajor= " << EvalToRowMajor << "\n"; + std::cerr << "Alignment= " << Alignment << "\n"; + std::cerr << "Flags= " << Flags << "\n"; +#endif + } + + // Everything below here is taken from CoeffBasedProduct.h + + typedef typename internal::nested_eval::type LhsNested; + typedef typename internal::nested_eval::type RhsNested; + + typedef internal::remove_all_t LhsNestedCleaned; + typedef internal::remove_all_t RhsNestedCleaned; + + typedef evaluator LhsEtorType; + typedef evaluator RhsEtorType; + + enum { + RowsAtCompileTime = LhsNestedCleaned::RowsAtCompileTime, + ColsAtCompileTime = RhsNestedCleaned::ColsAtCompileTime, + InnerSize = min_size_prefer_fixed(LhsNestedCleaned::ColsAtCompileTime, RhsNestedCleaned::RowsAtCompileTime), + MaxRowsAtCompileTime = LhsNestedCleaned::MaxRowsAtCompileTime, + MaxColsAtCompileTime = RhsNestedCleaned::MaxColsAtCompileTime + }; + + typedef typename find_best_packet::type LhsVecPacketType; + typedef typename find_best_packet::type RhsVecPacketType; + + enum { + + LhsCoeffReadCost = LhsEtorType::CoeffReadCost, + RhsCoeffReadCost = RhsEtorType::CoeffReadCost, + CoeffReadCost = InnerSize == 0 ? NumTraits::ReadCost + : InnerSize == Dynamic + ? HugeCost + : InnerSize * (NumTraits::MulCost + int(LhsCoeffReadCost) + int(RhsCoeffReadCost)) + + (InnerSize - 1) * NumTraits::AddCost, + + Unroll = CoeffReadCost <= EIGEN_UNROLLING_LIMIT, + + LhsFlags = LhsEtorType::Flags, + RhsFlags = RhsEtorType::Flags, + + LhsRowMajor = LhsFlags & RowMajorBit, + RhsRowMajor = RhsFlags & RowMajorBit, + + LhsVecPacketSize = unpacket_traits::size, + RhsVecPacketSize = unpacket_traits::size, + + // Here, we don't care about alignment larger than the usable packet size. + LhsAlignment = + plain_enum_min(LhsEtorType::Alignment, LhsVecPacketSize* int(sizeof(typename LhsNestedCleaned::Scalar))), + RhsAlignment = + plain_enum_min(RhsEtorType::Alignment, RhsVecPacketSize* int(sizeof(typename RhsNestedCleaned::Scalar))), + + SameType = is_same::value, + + CanVectorizeRhs = bool(RhsRowMajor) && (RhsFlags & PacketAccessBit) && (ColsAtCompileTime != 1), + CanVectorizeLhs = (!LhsRowMajor) && (LhsFlags & PacketAccessBit) && (RowsAtCompileTime != 1), + + EvalToRowMajor = (MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1) ? 1 + : (MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1) + ? 0 + : (bool(RhsRowMajor) && !CanVectorizeLhs), + + Flags = ((int(LhsFlags) | int(RhsFlags)) & HereditaryBits & ~RowMajorBit) | + (EvalToRowMajor ? RowMajorBit : 0) + // TODO enable vectorization for mixed types + | (SameType && (CanVectorizeLhs || CanVectorizeRhs) ? PacketAccessBit : 0) | + (XprType::IsVectorAtCompileTime ? LinearAccessBit : 0), + + LhsOuterStrideBytes = + int(LhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename LhsNestedCleaned::Scalar)), + RhsOuterStrideBytes = + int(RhsNestedCleaned::OuterStrideAtCompileTime) * int(sizeof(typename RhsNestedCleaned::Scalar)), + + Alignment = bool(CanVectorizeLhs) + ? (LhsOuterStrideBytes <= 0 || (int(LhsOuterStrideBytes) % plain_enum_max(1, LhsAlignment)) != 0 + ? 0 + : LhsAlignment) + : bool(CanVectorizeRhs) + ? (RhsOuterStrideBytes <= 0 || (int(RhsOuterStrideBytes) % plain_enum_max(1, RhsAlignment)) != 0 + ? 0 + : RhsAlignment) + : 0, + + /* CanVectorizeInner deserves special explanation. It does not affect the product flags. It is not used outside + * of Product. If the Product itself is not a packet-access expression, there is still a chance that the inner + * loop of the product might be vectorized. This is the meaning of CanVectorizeInner. Since it doesn't affect + * the Flags, it is safe to make this value depend on ActualPacketAccessBit, that doesn't affect the ABI. + */ + CanVectorizeInner = SameType && LhsRowMajor && (!RhsRowMajor) && + (int(LhsFlags) & int(RhsFlags) & ActualPacketAccessBit) && + (int(InnerSize) % packet_traits::size == 0) + }; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index row, Index col) const { + return (m_lhs.row(row).transpose().cwiseProduct(m_rhs.col(col))).sum(); + } + + /* Allow index-based non-packet access. It is impossible though to allow index-based packed access, + * which is why we don't set the LinearAccessBit. + * TODO: this seems possible when the result is a vector + */ + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index index) const { + const Index row = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? 0 : index; + const Index col = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? index : 0; + return (m_lhs.row(row).transpose().cwiseProduct(m_rhs.col(col))).sum(); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const PacketType packet(Index row, Index col) const { + PacketType res; + typedef etor_product_packet_impl + PacketImpl; + PacketImpl::run(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res); + return res; + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const PacketType packet(Index index) const { + const Index row = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? 0 : index; + const Index col = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? index : 0; + return packet(row, col); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const PacketType packetSegment(Index row, Index col, Index begin, + Index count) const { + PacketType res; + typedef etor_product_packet_impl + PacketImpl; + PacketImpl::run_segment(row, col, m_lhsImpl, m_rhsImpl, m_innerDim, res, begin, count); + return res; + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const PacketType packetSegment(Index index, Index begin, Index count) const { + const Index row = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? 0 : index; + const Index col = (RowsAtCompileTime == 1 || MaxRowsAtCompileTime == 1) ? index : 0; + return packetSegment(row, col, begin, count); + } + + protected: + add_const_on_value_type_t m_lhs; + add_const_on_value_type_t m_rhs; + + LhsEtorType m_lhsImpl; + RhsEtorType m_rhsImpl; + + // TODO: Get rid of m_innerDim if known at compile time + Index m_innerDim; +}; + +template +struct product_evaluator, LazyCoeffBasedProductMode, DenseShape, DenseShape> + : product_evaluator, CoeffBasedProductMode, DenseShape, DenseShape> { + typedef Product XprType; + typedef Product BaseProduct; + typedef product_evaluator Base; + enum { Flags = Base::Flags | EvalBeforeNestingBit }; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit product_evaluator(const XprType& xpr) + : Base(BaseProduct(xpr.lhs(), xpr.rhs())) {} +}; + +/**************************************** +*** Coeff based product, Packet path *** +****************************************/ + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res) { + etor_product_packet_impl::run(row, col, lhs, rhs, + innerDim, res); + res = pmadd(pset1(lhs.coeff(row, Index(UnrollingIndex - 1))), + rhs.template packet(Index(UnrollingIndex - 1), col), res); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res, Index begin, Index count) { + etor_product_packet_impl::run_segment( + row, col, lhs, rhs, innerDim, res, begin, count); + res = pmadd(pset1(lhs.coeff(row, Index(UnrollingIndex - 1))), + rhs.template packetSegment(Index(UnrollingIndex - 1), col, begin, count), res); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res) { + etor_product_packet_impl::run(row, col, lhs, rhs, + innerDim, res); + res = pmadd(lhs.template packet(row, Index(UnrollingIndex - 1)), + pset1(rhs.coeff(Index(UnrollingIndex - 1), col)), res); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res, Index begin, Index count) { + etor_product_packet_impl::run_segment( + row, col, lhs, rhs, innerDim, res, begin, count); + res = pmadd(lhs.template packetSegment(row, Index(UnrollingIndex - 1), begin, count), + pset1(rhs.coeff(Index(UnrollingIndex - 1), col)), res); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index /*innerDim*/, Packet& res) { + res = pmul(pset1(lhs.coeff(row, Index(0))), rhs.template packet(Index(0), col)); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index /*innerDim*/, Packet& res, Index begin, + Index count) { + res = pmul(pset1(lhs.coeff(row, Index(0))), + rhs.template packetSegment(Index(0), col, begin, count)); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index /*innerDim*/, Packet& res) { + res = pmul(lhs.template packet(row, Index(0)), pset1(rhs.coeff(Index(0), col))); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index /*innerDim*/, Packet& res, Index begin, + Index count) { + res = pmul(lhs.template packetSegment(row, Index(0), begin, count), + pset1(rhs.coeff(Index(0), col))); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, + const Rhs& /*rhs*/, Index /*innerDim*/, Packet& res) { + res = pset1(typename unpacket_traits::type(0)); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, + const Rhs& /*rhs*/, Index /*innerDim*/, Packet& res, + Index /*begin*/, Index /*count*/) { + res = pset1(typename unpacket_traits::type(0)); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, + const Rhs& /*rhs*/, Index /*innerDim*/, Packet& res) { + res = pset1(typename unpacket_traits::type(0)); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index /*row*/, Index /*col*/, const Lhs& /*lhs*/, + const Rhs& /*rhs*/, Index /*innerDim*/, Packet& res, + Index /*begin*/, Index /*count*/) { + res = pset1(typename unpacket_traits::type(0)); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res) { + res = pset1(typename unpacket_traits::type(0)); + for (Index i = 0; i < innerDim; ++i) + res = pmadd(pset1(lhs.coeff(row, i)), rhs.template packet(i, col), res); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res, Index begin, Index count) { + res = pset1(typename unpacket_traits::type(0)); + for (Index i = 0; i < innerDim; ++i) + res = pmadd(pset1(lhs.coeff(row, i)), rhs.template packetSegment(i, col, begin, count), + res); + } +}; + +template +struct etor_product_packet_impl { + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res) { + res = pset1(typename unpacket_traits::type(0)); + for (Index i = 0; i < innerDim; ++i) + res = pmadd(lhs.template packet(row, i), pset1(rhs.coeff(i, col)), res); + } + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run_segment(Index row, Index col, const Lhs& lhs, const Rhs& rhs, + Index innerDim, Packet& res, Index begin, Index count) { + res = pset1(typename unpacket_traits::type(0)); + for (Index i = 0; i < innerDim; ++i) + res = pmadd(lhs.template packetSegment(row, i, begin, count), pset1(rhs.coeff(i, col)), + res); + } +}; + +/*************************************************************************** + * Triangular products + ***************************************************************************/ +template +struct triangular_product_impl; + +template +struct generic_product_impl + : generic_product_impl_base> { + typedef typename Product::Scalar Scalar; + + template + static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) { + triangular_product_impl::run( + dst, lhs.nestedExpression(), rhs, alpha); + } +}; + +template +struct generic_product_impl + : generic_product_impl_base> { + typedef typename Product::Scalar Scalar; + + template + static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) { + triangular_product_impl::run( + dst, lhs, rhs.nestedExpression(), alpha); + } +}; + +/*************************************************************************** + * SelfAdjoint products + ***************************************************************************/ +template +struct selfadjoint_product_impl; + +template +struct generic_product_impl + : generic_product_impl_base> { + typedef typename Product::Scalar Scalar; + + template + static EIGEN_DEVICE_FUNC void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) { + selfadjoint_product_impl::run( + dst, lhs.nestedExpression(), rhs, alpha); + } +}; + +template +struct generic_product_impl + : generic_product_impl_base> { + typedef typename Product::Scalar Scalar; + + template + static void scaleAndAddTo(Dest& dst, const Lhs& lhs, const Rhs& rhs, const Scalar& alpha) { + selfadjoint_product_impl::run( + dst, lhs, rhs.nestedExpression(), alpha); + } +}; + +/*************************************************************************** + * Diagonal products + ***************************************************************************/ + +template +struct diagonal_product_evaluator_base : evaluator_base { + typedef typename ScalarBinaryOpTraits::ReturnType Scalar; + + public: + enum { + CoeffReadCost = int(NumTraits::MulCost) + int(evaluator::CoeffReadCost) + + int(evaluator::CoeffReadCost), + + MatrixFlags = evaluator::Flags, + DiagFlags = evaluator::Flags, + + StorageOrder_ = (Derived::MaxRowsAtCompileTime == 1 && Derived::MaxColsAtCompileTime != 1) ? RowMajor + : (Derived::MaxColsAtCompileTime == 1 && Derived::MaxRowsAtCompileTime != 1) ? ColMajor + : MatrixFlags & RowMajorBit ? RowMajor + : ColMajor, + SameStorageOrder_ = int(StorageOrder_) == ((MatrixFlags & RowMajorBit) ? RowMajor : ColMajor), + + ScalarAccessOnDiag_ = !((int(StorageOrder_) == ColMajor && int(ProductOrder) == OnTheLeft) || + (int(StorageOrder_) == RowMajor && int(ProductOrder) == OnTheRight)), + SameTypes_ = is_same::value, + // FIXME currently we need same types, but in the future the next rule should be the one + // Vectorizable_ = bool(int(MatrixFlags)&PacketAccessBit) && ((!_PacketOnDiag) || (SameTypes_ && + // bool(int(DiagFlags)&PacketAccessBit))), + Vectorizable_ = bool(int(MatrixFlags) & PacketAccessBit) && SameTypes_ && + (SameStorageOrder_ || (MatrixFlags & LinearAccessBit) == LinearAccessBit) && + (ScalarAccessOnDiag_ || (bool(int(DiagFlags) & PacketAccessBit))), + LinearAccessMask_ = + (MatrixType::RowsAtCompileTime == 1 || MatrixType::ColsAtCompileTime == 1) ? LinearAccessBit : 0, + Flags = + ((HereditaryBits | LinearAccessMask_) & (unsigned int)(MatrixFlags)) | (Vectorizable_ ? PacketAccessBit : 0), + Alignment = evaluator::Alignment, + + AsScalarProduct = + (DiagonalType::SizeAtCompileTime == 1) || + (DiagonalType::SizeAtCompileTime == Dynamic && MatrixType::RowsAtCompileTime == 1 && + ProductOrder == OnTheLeft) || + (DiagonalType::SizeAtCompileTime == Dynamic && MatrixType::ColsAtCompileTime == 1 && ProductOrder == OnTheRight) + }; + + EIGEN_DEVICE_FUNC diagonal_product_evaluator_base(const MatrixType& mat, const DiagonalType& diag) + : m_diagImpl(diag), m_matImpl(mat) { + EIGEN_INTERNAL_CHECK_COST_VALUE(NumTraits::MulCost); + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index idx) const { + if (AsScalarProduct) + return m_diagImpl.coeff(0) * m_matImpl.coeff(idx); + else + return m_diagImpl.coeff(idx) * m_matImpl.coeff(idx); + } + + protected: + template + EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::true_type) const { + return internal::pmul(m_matImpl.template packet(row, col), + internal::pset1(m_diagImpl.coeff(id))); + } + + template + EIGEN_STRONG_INLINE PacketType packet_impl(Index row, Index col, Index id, internal::false_type) const { + enum { + InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime, + DiagonalPacketLoadMode = plain_enum_min( + LoadMode, + ((InnerSize % 16) == 0) ? int(Aligned16) : int(evaluator::Alignment)) // FIXME hardcoded 16!! + }; + return internal::pmul(m_matImpl.template packet(row, col), + m_diagImpl.template packet(id)); + } + + template + EIGEN_STRONG_INLINE PacketType packet_segment_impl(Index row, Index col, Index id, Index begin, Index count, + internal::true_type) const { + return internal::pmul(m_matImpl.template packetSegment(row, col, begin, count), + internal::pset1(m_diagImpl.coeff(id))); + } + + template + EIGEN_STRONG_INLINE PacketType packet_segment_impl(Index row, Index col, Index id, Index begin, Index count, + internal::false_type) const { + enum { + InnerSize = (MatrixType::Flags & RowMajorBit) ? MatrixType::ColsAtCompileTime : MatrixType::RowsAtCompileTime, + DiagonalPacketLoadMode = plain_enum_min( + LoadMode, + ((InnerSize % 16) == 0) ? int(Aligned16) : int(evaluator::Alignment)) // FIXME hardcoded 16!! + }; + return internal::pmul(m_matImpl.template packetSegment(row, col, begin, count), + m_diagImpl.template packetSegment(id, begin, count)); + } + + evaluator m_diagImpl; + evaluator m_matImpl; +}; + +// diagonal * dense +template +struct product_evaluator, ProductTag, DiagonalShape, DenseShape> + : diagonal_product_evaluator_base, + OnTheLeft> { + typedef diagonal_product_evaluator_base, + OnTheLeft> + Base; + using Base::coeff; + using Base::m_diagImpl; + using Base::m_matImpl; + typedef typename Base::Scalar Scalar; + + typedef Product XprType; + typedef typename XprType::PlainObject PlainObject; + typedef typename Lhs::DiagonalVectorType DiagonalType; + + static constexpr int StorageOrder = Base::StorageOrder_; + using IsRowMajor_t = bool_constant; + + EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr) : Base(xpr.rhs(), xpr.lhs().diagonal()) {} + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const { + return m_diagImpl.coeff(row) * m_matImpl.coeff(row, col); + } + +#ifndef EIGEN_GPUCC + template + EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + // FIXME: NVCC used to complain about the template keyword, but we have to check whether this is still the case. + // See also similar calls below. + return this->template packet_impl(row, col, row, IsRowMajor_t()); + } + + template + EIGEN_STRONG_INLINE PacketType packet(Index idx) const { + return packet(int(StorageOrder) == ColMajor ? idx : 0, + int(StorageOrder) == ColMajor ? 0 : idx); + } + + template + EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + // FIXME: NVCC used to complain about the template keyword, but we have to check whether this is still the case. + // See also similar calls below. + return this->template packet_segment_impl(row, col, row, begin, count, IsRowMajor_t()); + } + + template + EIGEN_STRONG_INLINE PacketType packetSegment(Index idx, Index begin, Index count) const { + return packetSegment(StorageOrder == ColMajor ? idx : 0, StorageOrder == ColMajor ? 0 : idx, + begin, count); + } +#endif +}; + +// dense * diagonal +template +struct product_evaluator, ProductTag, DenseShape, DiagonalShape> + : diagonal_product_evaluator_base, + OnTheRight> { + typedef diagonal_product_evaluator_base, + OnTheRight> + Base; + using Base::coeff; + using Base::m_diagImpl; + using Base::m_matImpl; + typedef typename Base::Scalar Scalar; + + typedef Product XprType; + typedef typename XprType::PlainObject PlainObject; + + static constexpr int StorageOrder = Base::StorageOrder_; + using IsColMajor_t = bool_constant; + + EIGEN_DEVICE_FUNC explicit product_evaluator(const XprType& xpr) : Base(xpr.lhs(), xpr.rhs().diagonal()) {} + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar coeff(Index row, Index col) const { + return m_matImpl.coeff(row, col) * m_diagImpl.coeff(col); + } + +#ifndef EIGEN_GPUCC + template + EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + return this->template packet_impl(row, col, col, IsColMajor_t()); + } + + template + EIGEN_STRONG_INLINE PacketType packet(Index idx) const { + return packet(StorageOrder == ColMajor ? idx : 0, StorageOrder == ColMajor ? 0 : idx); + } + + template + EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + return this->template packet_segment_impl(row, col, col, begin, count, IsColMajor_t()); + } + + template + EIGEN_STRONG_INLINE PacketType packetSegment(Index idx, Index begin, Index count) const { + return packetSegment(StorageOrder == ColMajor ? idx : 0, StorageOrder == ColMajor ? 0 : idx, + begin, count); + } +#endif +}; + +/*************************************************************************** + * Products with permutation matrices + ***************************************************************************/ + +/** \internal + * \class permutation_matrix_product + * Internal helper class implementing the product between a permutation matrix and a matrix. + * This class is specialized for DenseShape below and for SparseShape in SparseCore/SparsePermutation.h + */ +template +struct permutation_matrix_product; + +template +struct permutation_matrix_product { + typedef typename nested_eval::type MatrixType; + typedef remove_all_t MatrixTypeCleaned; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Dest& dst, const PermutationType& perm, + const ExpressionType& xpr) { + MatrixType mat(xpr); + const Index n = Side == OnTheLeft ? mat.rows() : mat.cols(); + // FIXME we need an is_same for expression that is not sensitive to constness. For instance + // is_same_xpr, Block >::value should be true. + // if(is_same::value && extract_data(dst) == extract_data(mat)) + if (is_same_dense(dst, mat)) { + // apply the permutation inplace + Matrix mask(perm.size()); + mask.fill(false); + Index r = 0; + while (r < perm.size()) { + // search for the next seed + while (r < perm.size() && mask[r]) r++; + if (r >= perm.size()) break; + // we got one, let's follow it until we are back to the seed + Index k0 = r++; + Index kPrev = k0; + mask.coeffRef(k0) = true; + for (Index k = perm.indices().coeff(k0); k != k0; k = perm.indices().coeff(k)) { + Block(dst, k) + .swap(Block < Dest, Side == OnTheLeft ? 1 : Dest::RowsAtCompileTime, + Side == OnTheRight + ? 1 + : Dest::ColsAtCompileTime > (dst, ((Side == OnTheLeft) ^ Transposed) ? k0 : kPrev)); + + mask.coeffRef(k) = true; + kPrev = k; + } + } + } else { + for (Index i = 0; i < n; ++i) { + Block( + dst, ((Side == OnTheLeft) ^ Transposed) ? perm.indices().coeff(i) : i) + + = + + Block < const MatrixTypeCleaned, + Side == OnTheLeft ? 1 : MatrixTypeCleaned::RowsAtCompileTime, + Side == OnTheRight ? 1 + : MatrixTypeCleaned::ColsAtCompileTime > + (mat, ((Side == OnTheRight) ^ Transposed) ? perm.indices().coeff(i) : i); + } + } + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + permutation_matrix_product::run(dst, lhs, rhs); + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + permutation_matrix_product::run(dst, rhs, lhs); + } +}; + +template +struct generic_product_impl, Rhs, PermutationShape, MatrixShape, ProductTag> { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Inverse& lhs, const Rhs& rhs) { + permutation_matrix_product::run(dst, lhs.nestedExpression(), rhs); + } +}; + +template +struct generic_product_impl, MatrixShape, PermutationShape, ProductTag> { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Inverse& rhs) { + permutation_matrix_product::run(dst, rhs.nestedExpression(), lhs); + } +}; + +/*************************************************************************** + * Products with transpositions matrices + ***************************************************************************/ + +// FIXME could we unify Transpositions and Permutation into a single "shape"?? + +/** \internal + * \class transposition_matrix_product + * Internal helper class implementing the product between a permutation matrix and a matrix. + */ +template +struct transposition_matrix_product { + typedef typename nested_eval::type MatrixType; + typedef remove_all_t MatrixTypeCleaned; + + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void run(Dest& dst, const TranspositionType& tr, + const ExpressionType& xpr) { + MatrixType mat(xpr); + typedef typename TranspositionType::StorageIndex StorageIndex; + const Index size = tr.size(); + StorageIndex j = 0; + + if (!is_same_dense(dst, mat)) dst = mat; + + for (Index k = (Transposed ? size - 1 : 0); Transposed ? k >= 0 : k < size; Transposed ? --k : ++k) + if (Index(j = tr.coeff(k)) != k) { + if (Side == OnTheLeft) + dst.row(k).swap(dst.row(j)); + else if (Side == OnTheRight) + dst.col(k).swap(dst.col(j)); + } + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + transposition_matrix_product::run(dst, lhs, rhs); + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + transposition_matrix_product::run(dst, rhs, lhs); + } +}; + +template +struct generic_product_impl, Rhs, TranspositionsShape, MatrixShape, ProductTag> { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Transpose& lhs, const Rhs& rhs) { + transposition_matrix_product::run(dst, lhs.nestedExpression(), rhs); + } +}; + +template +struct generic_product_impl, MatrixShape, TranspositionsShape, ProductTag> { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Transpose& rhs) { + transposition_matrix_product::run(dst, rhs.nestedExpression(), lhs); + } +}; + +/*************************************************************************** + * skew symmetric products + * for now we just call the generic implementation + ***************************************************************************/ +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + generic_product_impl::evalTo(dst, lhs, + rhs); + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + generic_product_impl::evalTo(dst, lhs, + rhs); + } +}; + +template +struct generic_product_impl { + template + static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void evalTo(Dest& dst, const Lhs& lhs, const Rhs& rhs) { + generic_product_impl::evalTo(dst, lhs, rhs); + } +}; + +template +struct generic_product_impl + : generic_product_impl {}; + +template +struct generic_product_impl + : generic_product_impl {}; + +template +struct generic_product_impl + : generic_product_impl {}; + +template +struct generic_product_impl + : generic_product_impl {}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_PRODUCT_EVALUATORS_H diff --git a/inst/include/Eigen/src/Core/Random.h b/inst/include/Eigen/src/Core/Random.h index 480fea40..f8a54356 100644 --- a/inst/include/Eigen/src/Core/Random.h +++ b/inst/include/Eigen/src/Core/Random.h @@ -10,143 +10,198 @@ #ifndef EIGEN_RANDOM_H #define EIGEN_RANDOM_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { namespace internal { -template struct scalar_random_op { - EIGEN_EMPTY_STRUCT_CTOR(scalar_random_op) - template - inline const Scalar operator() (Index, Index = 0) const { return random(); } +template +struct scalar_random_op { + inline const Scalar operator()() const { return random(); } }; -template -struct functor_traits > -{ enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false, IsRepeatable = false }; }; +template +struct functor_traits > { + enum { Cost = 5 * NumTraits::MulCost, PacketAccess = false, IsRepeatable = false }; +}; -} // end namespace internal +} // end namespace internal /** \returns a random matrix expression - * - * The parameters \a rows and \a cols are the number of rows and of columns of - * the returned matrix. Must be compatible with this MatrixBase type. - * - * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, - * it is redundant to pass \a rows and \a cols as arguments, so Random() should be used - * instead. - * - * Example: \include MatrixBase_random_int_int.cpp - * Output: \verbinclude MatrixBase_random_int_int.out - * - * This expression has the "evaluate before nesting" flag so that it will be evaluated into - * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected - * behavior with expressions involving random matrices. - * - * \sa MatrixBase::setRandom(), MatrixBase::Random(Index), MatrixBase::Random() - */ -template -inline const CwiseNullaryOp::Scalar>, Derived> -DenseBase::Random(Index rows, Index cols) -{ + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * The parameters \a rows and \a cols are the number of rows and of columns of + * the returned matrix. Must be compatible with this MatrixBase type. + * + * \not_reentrant + * + * This variant is meant to be used for dynamic-size matrix types. For fixed-size types, + * it is redundant to pass \a rows and \a cols as arguments, so Random() should be used + * instead. + * + * + * Example: \include MatrixBase_random_int_int.cpp + * Output: \verbinclude MatrixBase_random_int_int.out + * + * This expression has the "evaluate before nesting" flag so that it will be evaluated into + * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected + * behavior with expressions involving random matrices. + * + * See DenseBase::NullaryExpr(Index, const CustomNullaryOp&) for an example using C++11 random generators. + * + * \sa DenseBase::setRandom(), DenseBase::Random(Index), DenseBase::Random() + */ +template +inline const typename DenseBase::RandomReturnType DenseBase::Random(Index rows, Index cols) { return NullaryExpr(rows, cols, internal::scalar_random_op()); } /** \returns a random vector expression - * - * The parameter \a size is the size of the returned vector. - * Must be compatible with this MatrixBase type. - * - * \only_for_vectors - * - * This variant is meant to be used for dynamic-size vector types. For fixed-size types, - * it is redundant to pass \a size as argument, so Random() should be used - * instead. - * - * Example: \include MatrixBase_random_int.cpp - * Output: \verbinclude MatrixBase_random_int.out - * - * This expression has the "evaluate before nesting" flag so that it will be evaluated into - * a temporary vector whenever it is nested in a larger expression. This prevents unexpected - * behavior with expressions involving random matrices. - * - * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random() - */ -template -inline const CwiseNullaryOp::Scalar>, Derived> -DenseBase::Random(Index size) -{ + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * The parameter \a size is the size of the returned vector. + * Must be compatible with this MatrixBase type. + * + * \only_for_vectors + * \not_reentrant + * + * This variant is meant to be used for dynamic-size vector types. For fixed-size types, + * it is redundant to pass \a size as argument, so Random() should be used + * instead. + * + * Example: \include MatrixBase_random_int.cpp + * Output: \verbinclude MatrixBase_random_int.out + * + * This expression has the "evaluate before nesting" flag so that it will be evaluated into + * a temporary vector whenever it is nested in a larger expression. This prevents unexpected + * behavior with expressions involving random matrices. + * + * \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random() + */ +template +inline const typename DenseBase::RandomReturnType DenseBase::Random(Index size) { return NullaryExpr(size, internal::scalar_random_op()); } /** \returns a fixed-size random matrix or vector expression - * - * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you - * need to use the variants taking size arguments. - * - * Example: \include MatrixBase_random.cpp - * Output: \verbinclude MatrixBase_random.out - * - * This expression has the "evaluate before nesting" flag so that it will be evaluated into - * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected - * behavior with expressions involving random matrices. - * - * \sa MatrixBase::setRandom(), MatrixBase::Random(Index,Index), MatrixBase::Random(Index) - */ -template -inline const CwiseNullaryOp::Scalar>, Derived> -DenseBase::Random() -{ + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * This variant is only for fixed-size MatrixBase types. For dynamic-size types, you + * need to use the variants taking size arguments. + * + * Example: \include MatrixBase_random.cpp + * Output: \verbinclude MatrixBase_random.out + * + * This expression has the "evaluate before nesting" flag so that it will be evaluated into + * a temporary matrix whenever it is nested in a larger expression. This prevents unexpected + * behavior with expressions involving random matrices. + * + * \not_reentrant + * + * \sa DenseBase::setRandom(), DenseBase::Random(Index,Index), DenseBase::Random(Index) + */ +template +inline const typename DenseBase::RandomReturnType DenseBase::Random() { return NullaryExpr(RowsAtCompileTime, ColsAtCompileTime, internal::scalar_random_op()); } /** Sets all coefficients in this expression to random values. - * - * Example: \include MatrixBase_setRandom.cpp - * Output: \verbinclude MatrixBase_setRandom.out - * - * \sa class CwiseNullaryOp, setRandom(Index), setRandom(Index,Index) - */ -template -inline Derived& DenseBase::setRandom() -{ + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * \not_reentrant + * + * Example: \include MatrixBase_setRandom.cpp + * Output: \verbinclude MatrixBase_setRandom.out + * + * \sa class CwiseNullaryOp, setRandom(Index), setRandom(Index,Index) + */ +template +EIGEN_DEVICE_FUNC inline Derived& DenseBase::setRandom() { return *this = Random(rows(), cols()); } /** Resizes to the given \a newSize, and sets all coefficients in this expression to random values. - * - * \only_for_vectors - * - * Example: \include Matrix_setRandom_int.cpp - * Output: \verbinclude Matrix_setRandom_int.out - * - * \sa MatrixBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, MatrixBase::Random() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setRandom(Index newSize) -{ + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * \only_for_vectors + * \not_reentrant + * + * Example: \include Matrix_setRandom_int.cpp + * Output: \verbinclude Matrix_setRandom_int.out + * + * \sa DenseBase::setRandom(), setRandom(Index,Index), class CwiseNullaryOp, DenseBase::Random() + */ +template +EIGEN_STRONG_INLINE Derived& PlainObjectBase::setRandom(Index newSize) { resize(newSize); return setRandom(); } /** Resizes to the given size, and sets all coefficients in this expression to random values. - * - * \param nbRows the new number of rows - * \param nbCols the new number of columns - * - * Example: \include Matrix_setRandom_int_int.cpp - * Output: \verbinclude Matrix_setRandom_int_int.out - * - * \sa MatrixBase::setRandom(), setRandom(Index), class CwiseNullaryOp, MatrixBase::Random() - */ -template -EIGEN_STRONG_INLINE Derived& -PlainObjectBase::setRandom(Index nbRows, Index nbCols) -{ - resize(nbRows, nbCols); + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * \not_reentrant + * + * \param rows the new number of rows + * \param cols the new number of columns + * + * Example: \include Matrix_setRandom_int_int.cpp + * Output: \verbinclude Matrix_setRandom_int_int.out + * + * \sa DenseBase::setRandom(), setRandom(Index), class CwiseNullaryOp, DenseBase::Random() + */ +template +EIGEN_STRONG_INLINE Derived& PlainObjectBase::setRandom(Index rows, Index cols) { + resize(rows, cols); return setRandom(); } -} // end namespace Eigen +/** Resizes to the given size, changing only the number of columns, and sets all + * coefficients in this expression to random values. For the parameter of type + * NoChange_t, just pass the special value \c NoChange. + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * \not_reentrant + * + * \sa DenseBase::setRandom(), setRandom(Index), setRandom(Index, NoChange_t), class CwiseNullaryOp, DenseBase::Random() + */ +template +EIGEN_STRONG_INLINE Derived& PlainObjectBase::setRandom(NoChange_t, Index cols) { + return setRandom(rows(), cols); +} + +/** Resizes to the given size, changing only the number of rows, and sets all + * coefficients in this expression to random values. For the parameter of type + * NoChange_t, just pass the special value \c NoChange. + * + * Numbers are uniformly spread through their whole definition range for integer types, + * and in the [-1:1] range for floating point scalar types. + * + * \not_reentrant + * + * \sa DenseBase::setRandom(), setRandom(Index), setRandom(NoChange_t, Index), class CwiseNullaryOp, DenseBase::Random() + */ +template +EIGEN_STRONG_INLINE Derived& PlainObjectBase::setRandom(Index rows, NoChange_t) { + return setRandom(rows, cols()); +} + +} // end namespace Eigen -#endif // EIGEN_RANDOM_H +#endif // EIGEN_RANDOM_H diff --git a/inst/include/Eigen/src/Core/RandomImpl.h b/inst/include/Eigen/src/Core/RandomImpl.h new file mode 100644 index 00000000..1a82e625 --- /dev/null +++ b/inst/include/Eigen/src/Core/RandomImpl.h @@ -0,0 +1,262 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2024 Charles Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_RANDOM_IMPL_H +#define EIGEN_RANDOM_IMPL_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +/**************************************************************************** + * Implementation of random * + ****************************************************************************/ + +template +struct random_default_impl {}; + +template +struct random_impl : random_default_impl::IsComplex, NumTraits::IsInteger> {}; + +template +struct random_retval { + typedef Scalar type; +}; + +template +inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random(const Scalar& x, const Scalar& y) { + return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(x, y); +} + +template +inline EIGEN_MATHFUNC_RETVAL(random, Scalar) random() { + return EIGEN_MATHFUNC_IMPL(random, Scalar)::run(); +} + +// TODO: replace or provide alternatives to this, e.g. std::random_device +struct eigen_random_device { + using ReturnType = int; + static constexpr int Entropy = meta_floor_log2<(unsigned int)(RAND_MAX) + 1>::value; + static constexpr ReturnType Highest = RAND_MAX; + static EIGEN_DEVICE_FUNC inline ReturnType run() { return std::rand(); } +}; + +// Fill a built-in unsigned integer with numRandomBits beginning with the least significant bit +template +struct random_bits_impl { + EIGEN_STATIC_ASSERT(std::is_unsigned::value, SCALAR MUST BE A BUILT - IN UNSIGNED INTEGER) + using RandomDevice = eigen_random_device; + using RandomReturnType = typename RandomDevice::ReturnType; + static constexpr int kEntropy = RandomDevice::Entropy; + static constexpr int kTotalBits = sizeof(Scalar) * CHAR_BIT; + // return a Scalar filled with numRandomBits beginning from the least significant bit + static EIGEN_DEVICE_FUNC inline Scalar run(int numRandomBits) { + eigen_assert((numRandomBits >= 0) && (numRandomBits <= kTotalBits)); + const Scalar mask = Scalar(-1) >> ((kTotalBits - numRandomBits) & (kTotalBits - 1)); + Scalar randomBits = 0; + for (int shift = 0; shift < numRandomBits; shift += kEntropy) { + RandomReturnType r = RandomDevice::run(); + randomBits |= static_cast(r) << shift; + } + // clear the excess bits + randomBits &= mask; + return randomBits; + } +}; + +template +EIGEN_DEVICE_FUNC inline BitsType getRandomBits(int numRandomBits) { + return random_bits_impl::run(numRandomBits); +} + +// random implementation for a built-in floating point type +template ::value> +struct random_float_impl { + using BitsType = typename numext::get_integer_by_size::unsigned_type; + static constexpr EIGEN_DEVICE_FUNC inline int mantissaBits() { + const int digits = NumTraits::digits(); + return digits - 1; + } + static EIGEN_DEVICE_FUNC inline Scalar run(int numRandomBits) { + eigen_assert(numRandomBits >= 0 && numRandomBits <= mantissaBits()); + BitsType randomBits = getRandomBits(numRandomBits); + // if fewer than MantissaBits is requested, shift them to the left + randomBits <<= (mantissaBits() - numRandomBits); + // randomBits is in the half-open interval [2,4) + randomBits |= numext::bit_cast(Scalar(2)); + // result is in the half-open interval [-1,1) + Scalar result = numext::bit_cast(randomBits) - Scalar(3); + return result; + } +}; +// random implementation for a custom floating point type +// uses double as the implementation with a mantissa with a size equal to either the target scalar's mantissa or that of +// double, whichever is smaller +template +struct random_float_impl { + static EIGEN_DEVICE_FUNC inline int mantissaBits() { + const int digits = NumTraits::digits(); + constexpr int kDoubleDigits = NumTraits::digits(); + return numext::mini(digits, kDoubleDigits) - 1; + } + static EIGEN_DEVICE_FUNC inline Scalar run(int numRandomBits) { + eigen_assert(numRandomBits >= 0 && numRandomBits <= mantissaBits()); + Scalar result = static_cast(random_float_impl::run(numRandomBits)); + return result; + } +}; + +#if !EIGEN_COMP_NVCC +// random implementation for long double +// this specialization is not compatible with double-double scalars +template ::digits != (2 * std::numeric_limits::digits)))> +struct random_longdouble_impl { + static constexpr int Size = sizeof(long double); + static constexpr EIGEN_DEVICE_FUNC int mantissaBits() { return NumTraits::digits() - 1; } + static EIGEN_DEVICE_FUNC inline long double run(int numRandomBits) { + eigen_assert(numRandomBits >= 0 && numRandomBits <= mantissaBits()); + EIGEN_USING_STD(memcpy); + int numLowBits = numext::mini(numRandomBits, 64); + int numHighBits = numext::maxi(numRandomBits - 64, 0); + uint64_t randomBits[2]; + long double result = 2.0L; + memcpy(&randomBits, &result, Size); +#if __BYTE_ORDER__ == __ORDER_LITTLE_ENDIAN__ + randomBits[0] |= getRandomBits(numLowBits); + randomBits[1] |= getRandomBits(numHighBits); +#elif __BYTE_ORDER__ == __ORDER_BIG_ENDIAN__ + randomBits[0] |= getRandomBits(numHighBits); + randomBits[1] |= getRandomBits(numLowBits); +#else +#error Unexpected or undefined __BYTE_ORDER__ +#endif + memcpy(&result, &randomBits, Size); + result -= 3.0L; + return result; + } +}; +template <> +struct random_longdouble_impl { + static constexpr EIGEN_DEVICE_FUNC int mantissaBits() { return NumTraits::digits() - 1; } + static EIGEN_DEVICE_FUNC inline long double run(int numRandomBits) { + return static_cast(random_float_impl::run(numRandomBits)); + } +}; +template <> +struct random_float_impl : random_longdouble_impl<> {}; +#endif + +template +struct random_default_impl { + using Impl = random_float_impl; + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y, int numRandomBits) { + Scalar half_x = Scalar(0.5) * x; + Scalar half_y = Scalar(0.5) * y; + Scalar result = (half_x + half_y) + (half_y - half_x) * run(numRandomBits); + // result is in the half-open interval [x, y) -- provided that x < y + return result; + } + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y) { + return run(x, y, Impl::mantissaBits()); + } + static EIGEN_DEVICE_FUNC inline Scalar run(int numRandomBits) { return Impl::run(numRandomBits); } + static EIGEN_DEVICE_FUNC inline Scalar run() { return run(Impl::mantissaBits()); } +}; + +template ::IsSigned, bool BuiltIn = std::is_integral::value> +struct random_int_impl; + +// random implementation for a built-in unsigned integer type +template +struct random_int_impl { + static constexpr int kTotalBits = sizeof(Scalar) * CHAR_BIT; + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y) { + if (y <= x) return x; + Scalar range = y - x; + // handle edge case where [x,y] spans the entire range of Scalar + if (range == NumTraits::highest()) return run(); + Scalar count = range + 1; + // calculate the number of random bits needed to fill range + int numRandomBits = log2_ceil(count); + Scalar randomBits; + do { + randomBits = getRandomBits(numRandomBits); + // if the random draw is outside [0, range), try again (rejection sampling) + // in the worst-case scenario, the probability of rejection is: 1/2 - 1/2^numRandomBits < 50% + } while (randomBits >= count); + Scalar result = x + randomBits; + return result; + } + static EIGEN_DEVICE_FUNC inline Scalar run() { return getRandomBits(kTotalBits); } +}; + +// random implementation for a built-in signed integer type +template +struct random_int_impl { + static constexpr int kTotalBits = sizeof(Scalar) * CHAR_BIT; + using BitsType = typename make_unsigned::type; + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y) { + if (y <= x) return x; + // Avoid overflow by representing `range` as an unsigned type + BitsType range = static_cast(y) - static_cast(x); + BitsType randomBits = random_int_impl::run(0, range); + // Avoid overflow in the case where `x` is negative and there is a large range so + // `randomBits` would also be negative if cast to `Scalar` first. + Scalar result = static_cast(static_cast(x) + randomBits); + return result; + } + static EIGEN_DEVICE_FUNC inline Scalar run() { return static_cast(getRandomBits(kTotalBits)); } +}; + +// todo: custom integers +template +struct random_int_impl { + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar&, const Scalar&) { return run(); } + static EIGEN_DEVICE_FUNC inline Scalar run() { + eigen_assert(std::false_type::value && "RANDOM FOR CUSTOM INTEGERS NOT YET SUPPORTED"); + return Scalar(0); + } +}; + +template +struct random_default_impl : random_int_impl {}; + +template <> +struct random_impl { + static EIGEN_DEVICE_FUNC inline bool run(const bool& x, const bool& y) { + if (y <= x) return x; + return run(); + } + static EIGEN_DEVICE_FUNC inline bool run() { return getRandomBits(1) ? true : false; } +}; + +template +struct random_default_impl { + typedef typename NumTraits::Real RealScalar; + using Impl = random_impl; + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y, int numRandomBits) { + return Scalar(Impl::run(x.real(), y.real(), numRandomBits), Impl::run(x.imag(), y.imag(), numRandomBits)); + } + static EIGEN_DEVICE_FUNC inline Scalar run(const Scalar& x, const Scalar& y) { + return Scalar(Impl::run(x.real(), y.real()), Impl::run(x.imag(), y.imag())); + } + static EIGEN_DEVICE_FUNC inline Scalar run(int numRandomBits) { + return Scalar(Impl::run(numRandomBits), Impl::run(numRandomBits)); + } + static EIGEN_DEVICE_FUNC inline Scalar run() { return Scalar(Impl::run(), Impl::run()); } +}; + +} // namespace internal +} // namespace Eigen + +#endif // EIGEN_RANDOM_IMPL_H diff --git a/inst/include/Eigen/src/Core/RealView.h b/inst/include/Eigen/src/Core/RealView.h new file mode 100644 index 00000000..7ba42f9a --- /dev/null +++ b/inst/include/Eigen/src/Core/RealView.h @@ -0,0 +1,250 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2025 Charlie Schlosser +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_REALVIEW_H +#define EIGEN_REALVIEW_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +namespace internal { + +// Vectorized assignment to RealView requires array-oriented access to the real and imaginary components. +// From https://en.cppreference.com/w/cpp/numeric/complex.html: +// For any pointer to an element of an array of std::complex named p and any valid array index i, +// reinterpret_cast(p)[2 * i] is the real part of the complex number p[i], and +// reinterpret_cast(p)[2 * i + 1] is the imaginary part of the complex number p[i]. + +template +struct complex_array_access : std::false_type {}; +template <> +struct complex_array_access> : std::true_type {}; +template <> +struct complex_array_access> : std::true_type {}; +template <> +struct complex_array_access> : std::true_type {}; + +template +struct traits> : public traits { + template + static constexpr int double_size(T size, bool times_two) { + int size_as_int = int(size); + if (size_as_int == Dynamic) return Dynamic; + return times_two ? (2 * size_as_int) : size_as_int; + } + using Base = traits; + using ComplexScalar = typename Base::Scalar; + using Scalar = typename NumTraits::Real; + static constexpr int ActualDirectAccessBit = complex_array_access::value ? DirectAccessBit : 0; + static constexpr int ActualPacketAccessBit = packet_traits::Vectorizable ? PacketAccessBit : 0; + static constexpr int FlagMask = + ActualDirectAccessBit | ActualPacketAccessBit | HereditaryBits | LinearAccessBit | LvalueBit; + static constexpr int BaseFlags = int(evaluator::Flags) | int(Base::Flags); + static constexpr int Flags = BaseFlags & FlagMask; + static constexpr bool IsRowMajor = Flags & RowMajorBit; + static constexpr int RowsAtCompileTime = double_size(Base::RowsAtCompileTime, !IsRowMajor); + static constexpr int ColsAtCompileTime = double_size(Base::ColsAtCompileTime, IsRowMajor); + static constexpr int SizeAtCompileTime = size_at_compile_time(RowsAtCompileTime, ColsAtCompileTime); + static constexpr int MaxRowsAtCompileTime = double_size(Base::MaxRowsAtCompileTime, !IsRowMajor); + static constexpr int MaxColsAtCompileTime = double_size(Base::MaxColsAtCompileTime, IsRowMajor); + static constexpr int MaxSizeAtCompileTime = size_at_compile_time(MaxRowsAtCompileTime, MaxColsAtCompileTime); + static constexpr int OuterStrideAtCompileTime = double_size(outer_stride_at_compile_time::ret, true); + static constexpr int InnerStrideAtCompileTime = inner_stride_at_compile_time::ret; +}; + +template +struct evaluator> : private evaluator { + using BaseEvaluator = evaluator; + using XprType = RealView; + using ExpressionTraits = traits; + using ComplexScalar = typename ExpressionTraits::ComplexScalar; + using ComplexCoeffReturnType = typename BaseEvaluator::CoeffReturnType; + using Scalar = typename ExpressionTraits::Scalar; + + static constexpr bool IsRowMajor = ExpressionTraits::IsRowMajor; + static constexpr int Flags = ExpressionTraits::Flags; + static constexpr int CoeffReadCost = BaseEvaluator::CoeffReadCost; + static constexpr int Alignment = BaseEvaluator::Alignment; + + EIGEN_DEVICE_FUNC explicit evaluator(XprType realView) : BaseEvaluator(realView.m_xpr) {} + + template ::value, typename = std::enable_if_t> + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index row, Index col) const { + ComplexCoeffReturnType cscalar = BaseEvaluator::coeff(IsRowMajor ? row : row / 2, IsRowMajor ? col / 2 : col); + Index p = (IsRowMajor ? col : row) & 1; + return p ? numext::real(cscalar) : numext::imag(cscalar); + } + + template ::value, typename = std::enable_if_t> + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index row, Index col) const { + ComplexCoeffReturnType cscalar = BaseEvaluator::coeff(IsRowMajor ? row : row / 2, IsRowMajor ? col / 2 : col); + Index p = (IsRowMajor ? col : row) & 1; + return reinterpret_cast(cscalar)[p]; + } + + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index row, Index col) { + ComplexScalar& cscalar = BaseEvaluator::coeffRef(IsRowMajor ? row : row / 2, IsRowMajor ? col / 2 : col); + Index p = (IsRowMajor ? col : row) & 1; + return reinterpret_cast(cscalar)[p]; + } + + template ::value, typename = std::enable_if_t> + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar coeff(Index index) const { + ComplexCoeffReturnType cscalar = BaseEvaluator::coeff(index / 2); + Index p = index & 1; + return p ? numext::real(cscalar) : numext::imag(cscalar); + } + + template ::value, typename = std::enable_if_t> + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const Scalar& coeff(Index index) const { + ComplexCoeffReturnType cscalar = BaseEvaluator::coeff(index / 2); + Index p = index & 1; + return reinterpret_cast(cscalar)[p]; + } + + constexpr EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE Scalar& coeffRef(Index index) { + ComplexScalar& cscalar = BaseEvaluator::coeffRef(index / 2); + Index p = index & 1; + return reinterpret_cast(cscalar)[p]; + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index row, Index col) const { + constexpr int RealPacketSize = unpacket_traits::size; + using ComplexPacket = typename find_packet_by_size::type; + EIGEN_STATIC_ASSERT((find_packet_by_size::value), + MISSING COMPATIBLE COMPLEX PACKET TYPE) + eigen_assert(((IsRowMajor ? col : row) % 2 == 0) && "the inner index must be even"); + + Index crow = IsRowMajor ? row : row / 2; + Index ccol = IsRowMajor ? col / 2 : col; + ComplexPacket cpacket = BaseEvaluator::template packet(crow, ccol); + return preinterpret(cpacket); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packet(Index index) const { + constexpr int RealPacketSize = unpacket_traits::size; + using ComplexPacket = typename find_packet_by_size::type; + EIGEN_STATIC_ASSERT((find_packet_by_size::value), + MISSING COMPATIBLE COMPLEX PACKET TYPE) + eigen_assert((index % 2 == 0) && "the index must be even"); + + Index cindex = index / 2; + ComplexPacket cpacket = BaseEvaluator::template packet(cindex); + return preinterpret(cpacket); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index row, Index col, Index begin, Index count) const { + constexpr int RealPacketSize = unpacket_traits::size; + using ComplexPacket = typename find_packet_by_size::type; + EIGEN_STATIC_ASSERT((find_packet_by_size::value), + MISSING COMPATIBLE COMPLEX PACKET TYPE) + eigen_assert(((IsRowMajor ? col : row) % 2 == 0) && "the inner index must be even"); + eigen_assert((begin % 2 == 0) && (count % 2 == 0) && "begin and count must be even"); + + Index crow = IsRowMajor ? row : row / 2; + Index ccol = IsRowMajor ? col / 2 : col; + Index cbegin = begin / 2; + Index ccount = count / 2; + ComplexPacket cpacket = BaseEvaluator::template packetSegment(crow, ccol, cbegin, ccount); + return preinterpret(cpacket); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegment(Index index, Index begin, Index count) const { + constexpr int RealPacketSize = unpacket_traits::size; + using ComplexPacket = typename find_packet_by_size::type; + EIGEN_STATIC_ASSERT((find_packet_by_size::value), + MISSING COMPATIBLE COMPLEX PACKET TYPE) + eigen_assert((index % 2 == 0) && "the index must be even"); + eigen_assert((begin % 2 == 0) && (count % 2 == 0) && "begin and count must be even"); + + Index cindex = index / 2; + Index cbegin = begin / 2; + Index ccount = count / 2; + ComplexPacket cpacket = BaseEvaluator::template packetSegment(cindex, cbegin, ccount); + return preinterpret(cpacket); + } +}; + +} // namespace internal + +template +class RealView : public internal::dense_xpr_base>::type { + using ExpressionTraits = internal::traits; + EIGEN_STATIC_ASSERT(NumTraits::IsComplex, SCALAR MUST BE COMPLEX) + public: + using Scalar = typename ExpressionTraits::Scalar; + using Nested = RealView; + + EIGEN_DEVICE_FUNC explicit RealView(Xpr& xpr) : m_xpr(xpr) {} + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return Xpr::IsRowMajor ? m_xpr.rows() : 2 * m_xpr.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return Xpr::IsRowMajor ? 2 * m_xpr.cols() : m_xpr.cols(); } + EIGEN_DEVICE_FUNC constexpr Index size() const noexcept { return 2 * m_xpr.size(); } + EIGEN_DEVICE_FUNC constexpr Index innerStride() const noexcept { return m_xpr.innerStride(); } + EIGEN_DEVICE_FUNC constexpr Index outerStride() const noexcept { return 2 * m_xpr.outerStride(); } + EIGEN_DEVICE_FUNC void resize(Index rows, Index cols) { + m_xpr.resize(Xpr::IsRowMajor ? rows : rows / 2, Xpr::IsRowMajor ? cols / 2 : cols); + } + EIGEN_DEVICE_FUNC void resize(Index size) { m_xpr.resize(size / 2); } + EIGEN_DEVICE_FUNC Scalar* data() { return reinterpret_cast(m_xpr.data()); } + EIGEN_DEVICE_FUNC const Scalar* data() const { return reinterpret_cast(m_xpr.data()); } + + EIGEN_DEVICE_FUNC RealView(const RealView&) = default; + + EIGEN_DEVICE_FUNC RealView& operator=(const RealView& other); + + template + EIGEN_DEVICE_FUNC RealView& operator=(const RealView& other); + + template + EIGEN_DEVICE_FUNC RealView& operator=(const DenseBase& other); + + protected: + friend struct internal::evaluator>; + Xpr& m_xpr; +}; + +template +EIGEN_DEVICE_FUNC RealView& RealView::operator=(const RealView& other) { + internal::call_assignment(*this, other); + return *this; +} + +template +template +EIGEN_DEVICE_FUNC RealView& RealView::operator=(const RealView& other) { + internal::call_assignment(*this, other); + return *this; +} + +template +template +EIGEN_DEVICE_FUNC RealView& RealView::operator=(const DenseBase& other) { + internal::call_assignment(*this, other.derived()); + return *this; +} + +template +EIGEN_DEVICE_FUNC typename DenseBase::RealViewReturnType DenseBase::realView() { + return RealViewReturnType(derived()); +} + +template +EIGEN_DEVICE_FUNC typename DenseBase::ConstRealViewReturnType DenseBase::realView() const { + return ConstRealViewReturnType(derived()); +} + +} // namespace Eigen + +#endif // EIGEN_REALVIEW_H diff --git a/inst/include/Eigen/src/Core/Redux.h b/inst/include/Eigen/src/Core/Redux.h index 9b8662a6..4e9ab0e4 100644 --- a/inst/include/Eigen/src/Core/Redux.h +++ b/inst/include/Eigen/src/Core/Redux.h @@ -11,7 +11,10 @@ #ifndef EIGEN_REDUX_H #define EIGEN_REDUX_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { namespace internal { @@ -20,227 +23,300 @@ namespace internal { // * factorize code /*************************************************************************** -* Part 1 : the logic deciding a strategy for vectorization and unrolling -***************************************************************************/ + * Part 1 : the logic deciding a strategy for vectorization and unrolling + ***************************************************************************/ -template -struct redux_traits -{ -public: +template +struct redux_traits { + public: + typedef typename find_best_packet::type PacketType; enum { - PacketSize = packet_traits::size, - InnerMaxSize = int(Derived::IsRowMajor) - ? Derived::MaxColsAtCompileTime - : Derived::MaxRowsAtCompileTime + PacketSize = unpacket_traits::size, + InnerMaxSize = int(Evaluator::IsRowMajor) ? Evaluator::MaxColsAtCompileTime : Evaluator::MaxRowsAtCompileTime, + OuterMaxSize = int(Evaluator::IsRowMajor) ? Evaluator::MaxRowsAtCompileTime : Evaluator::MaxColsAtCompileTime, + SliceVectorizedWork = int(InnerMaxSize) == Dynamic ? Dynamic + : int(OuterMaxSize) == Dynamic ? (int(InnerMaxSize) >= int(PacketSize) ? Dynamic : 0) + : (int(InnerMaxSize) / int(PacketSize)) * int(OuterMaxSize) }; enum { - MightVectorize = (int(Derived::Flags)&ActualPacketAccessBit) - && (functor_traits::PacketAccess), - MayLinearVectorize = MightVectorize && (int(Derived::Flags)&LinearAccessBit), - MaySliceVectorize = MightVectorize && int(InnerMaxSize)>=3*PacketSize + MayLinearize = (int(Evaluator::Flags) & LinearAccessBit), + MightVectorize = (int(Evaluator::Flags) & ActualPacketAccessBit) && (functor_traits::PacketAccess), + MayLinearVectorize = bool(MightVectorize) && bool(MayLinearize), + MaySliceVectorize = bool(MightVectorize) && (int(SliceVectorizedWork) == Dynamic || int(SliceVectorizedWork) >= 3) }; -public: + public: enum { - Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal) - : int(MaySliceVectorize) ? int(SliceVectorizedTraversal) - : int(DefaultTraversal) + Traversal = int(MayLinearVectorize) ? int(LinearVectorizedTraversal) + : int(MaySliceVectorize) ? int(SliceVectorizedTraversal) + : int(MayLinearize) ? int(LinearTraversal) + : int(DefaultTraversal) }; -public: + public: enum { - Cost = ( Derived::SizeAtCompileTime == Dynamic - || Derived::CoeffReadCost == Dynamic - || (Derived::SizeAtCompileTime!=1 && functor_traits::Cost == Dynamic) - ) ? Dynamic - : Derived::SizeAtCompileTime * Derived::CoeffReadCost - + (Derived::SizeAtCompileTime-1) * functor_traits::Cost, + Cost = Evaluator::SizeAtCompileTime == Dynamic + ? HugeCost + : int(Evaluator::SizeAtCompileTime) * int(Evaluator::CoeffReadCost) + + (Evaluator::SizeAtCompileTime - 1) * functor_traits::Cost, UnrollingLimit = EIGEN_UNROLLING_LIMIT * (int(Traversal) == int(DefaultTraversal) ? 1 : int(PacketSize)) }; -public: - enum { - Unrolling = Cost != Dynamic && Cost <= UnrollingLimit - ? CompleteUnrolling - : NoUnrolling - }; + public: + enum { Unrolling = Cost <= UnrollingLimit ? CompleteUnrolling : NoUnrolling }; + +#ifdef EIGEN_DEBUG_ASSIGN + static void debug() { + std::cerr << "Xpr: " << typeid(typename Evaluator::XprType).name() << std::endl; + std::cerr.setf(std::ios::hex, std::ios::basefield); + EIGEN_DEBUG_VAR(Evaluator::Flags) + std::cerr.unsetf(std::ios::hex); + EIGEN_DEBUG_VAR(InnerMaxSize) + EIGEN_DEBUG_VAR(OuterMaxSize) + EIGEN_DEBUG_VAR(SliceVectorizedWork) + EIGEN_DEBUG_VAR(PacketSize) + EIGEN_DEBUG_VAR(MightVectorize) + EIGEN_DEBUG_VAR(MayLinearVectorize) + EIGEN_DEBUG_VAR(MaySliceVectorize) + std::cerr << "Traversal" + << " = " << Traversal << " (" << demangle_traversal(Traversal) << ")" << std::endl; + EIGEN_DEBUG_VAR(UnrollingLimit) + std::cerr << "Unrolling" + << " = " << Unrolling << " (" << demangle_unrolling(Unrolling) << ")" << std::endl; + std::cerr << std::endl; + } +#endif }; /*************************************************************************** -* Part 2 : unrollers -***************************************************************************/ + * Part 2 : unrollers + ***************************************************************************/ /*** no vectorization ***/ -template -struct redux_novec_unroller -{ - enum { - HalfLength = Length/2 - }; +template +struct redux_novec_unroller { + static constexpr Index HalfLength = Length / 2; - typedef typename Derived::Scalar Scalar; + typedef typename Evaluator::Scalar Scalar; - static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func& func) - { - return func(redux_novec_unroller::run(mat,func), - redux_novec_unroller::run(mat,func)); + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func) { + return func(redux_novec_unroller::run(eval, func), + redux_novec_unroller::run(eval, func)); } }; -template -struct redux_novec_unroller -{ - enum { - outer = Start / Derived::InnerSizeAtCompileTime, - inner = Start % Derived::InnerSizeAtCompileTime - }; +template +struct redux_novec_unroller { + static constexpr Index outer = Start / Evaluator::InnerSizeAtCompileTime; + static constexpr Index inner = Start % Evaluator::InnerSizeAtCompileTime; - typedef typename Derived::Scalar Scalar; + typedef typename Evaluator::Scalar Scalar; - static EIGEN_STRONG_INLINE Scalar run(const Derived &mat, const Func&) - { - return mat.coeffByOuterInner(outer, inner); + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func&) { + return eval.coeffByOuterInner(outer, inner); } }; // This is actually dead code and will never be called. It is required // to prevent false warnings regarding failed inlining though // for 0 length run() will never be called at all. -template -struct redux_novec_unroller -{ - typedef typename Derived::Scalar Scalar; - static EIGEN_STRONG_INLINE Scalar run(const Derived&, const Func&) { return Scalar(); } +template +struct redux_novec_unroller { + typedef typename Evaluator::Scalar Scalar; + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator&, const Func&) { return Scalar(); } }; -/*** vectorization ***/ +template +struct redux_novec_linear_unroller { + static constexpr Index HalfLength = Length / 2; -template -struct redux_vec_unroller -{ - enum { - PacketSize = packet_traits::size, - HalfLength = Length/2 - }; + typedef typename Evaluator::Scalar Scalar; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func) { + return func(redux_novec_linear_unroller::run(eval, func), + redux_novec_linear_unroller::run(eval, func)); + } +}; + +template +struct redux_novec_linear_unroller { + typedef typename Evaluator::Scalar Scalar; + + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func&) { + return eval.coeff(Start); + } +}; + +// This is actually dead code and will never be called. It is required +// to prevent false warnings regarding failed inlining though +// for 0 length run() will never be called at all. +template +struct redux_novec_linear_unroller { + typedef typename Evaluator::Scalar Scalar; + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator&, const Func&) { return Scalar(); } +}; + +/*** vectorization ***/ - typedef typename Derived::Scalar Scalar; - typedef typename packet_traits::type PacketScalar; +template +struct redux_vec_unroller { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func& func) { + constexpr Index HalfLength = Length / 2; - static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func& func) - { return func.packetOp( - redux_vec_unroller::run(mat,func), - redux_vec_unroller::run(mat,func) ); + redux_vec_unroller::template run(eval, func), + redux_vec_unroller::template run(eval, + func)); } }; -template -struct redux_vec_unroller -{ - enum { - index = Start * packet_traits::size, - outer = index / int(Derived::InnerSizeAtCompileTime), - inner = index % int(Derived::InnerSizeAtCompileTime), - alignment = (Derived::Flags & AlignedBit) ? Aligned : Unaligned - }; +template +struct redux_vec_unroller { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func&) { + constexpr Index PacketSize = unpacket_traits::size; + constexpr Index index = Start * PacketSize; + constexpr Index outer = index / int(Evaluator::InnerSizeAtCompileTime); + constexpr Index inner = index % int(Evaluator::InnerSizeAtCompileTime); + constexpr int alignment = Evaluator::Alignment; + + return eval.template packetByOuterInner(outer, inner); + } +}; - typedef typename Derived::Scalar Scalar; - typedef typename packet_traits::type PacketScalar; +template +struct redux_vec_linear_unroller { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func& func) { + constexpr Index HalfLength = Length / 2; - static EIGEN_STRONG_INLINE PacketScalar run(const Derived &mat, const Func&) - { - return mat.template packetByOuterInner(outer, inner); + return func.packetOp( + redux_vec_linear_unroller::template run(eval, func), + redux_vec_linear_unroller::template run( + eval, func)); + } +}; + +template +struct redux_vec_linear_unroller { + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE PacketType run(const Evaluator& eval, const Func&) { + constexpr Index PacketSize = unpacket_traits::size; + constexpr Index index = (Start * PacketSize); + constexpr int alignment = Evaluator::Alignment; + return eval.template packet(index); } }; /*************************************************************************** -* Part 3 : implementation of all cases -***************************************************************************/ + * Part 3 : implementation of all cases + ***************************************************************************/ -template::Traversal, - int Unrolling = redux_traits::Unrolling -> +template ::Traversal, + int Unrolling = redux_traits::Unrolling> struct redux_impl; -template -struct redux_impl -{ - typedef typename Derived::Scalar Scalar; - typedef typename Derived::Index Index; - static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func) - { - eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix"); - Scalar res; - res = mat.coeffByOuterInner(0, 0); - for(Index i = 1; i < mat.innerSize(); ++i) - res = func(res, mat.coeffByOuterInner(0, i)); - for(Index i = 1; i < mat.outerSize(); ++i) - for(Index j = 0; j < mat.innerSize(); ++j) - res = func(res, mat.coeffByOuterInner(i, j)); +template +struct redux_impl { + typedef typename Evaluator::Scalar Scalar; + + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func, const XprType& xpr) { + eigen_assert(xpr.rows() > 0 && xpr.cols() > 0 && "you are using an empty matrix"); + Scalar res = eval.coeffByOuterInner(0, 0); + for (Index i = 1; i < xpr.innerSize(); ++i) res = func(res, eval.coeffByOuterInner(0, i)); + for (Index i = 1; i < xpr.outerSize(); ++i) + for (Index j = 0; j < xpr.innerSize(); ++j) res = func(res, eval.coeffByOuterInner(i, j)); + return res; + } +}; + +template +struct redux_impl { + typedef typename Evaluator::Scalar Scalar; + + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func, const XprType& xpr) { + eigen_assert(xpr.size() > 0 && "you are using an empty matrix"); + Scalar res = eval.coeff(0); + for (Index k = 1; k < xpr.size(); ++k) res = func(res, eval.coeff(k)); return res; } }; -template -struct redux_impl - : public redux_novec_unroller -{}; - -template -struct redux_impl -{ - typedef typename Derived::Scalar Scalar; - typedef typename packet_traits::type PacketScalar; - typedef typename Derived::Index Index; - - static Scalar run(const Derived& mat, const Func& func) - { - const Index size = mat.size(); - eigen_assert(size && "you are using an empty matrix"); - const Index packetSize = packet_traits::size; - const Index alignedStart = internal::first_aligned(mat); - enum { - alignment = bool(Derived::Flags & DirectAccessBit) || bool(Derived::Flags & AlignedBit) - ? Aligned : Unaligned - }; - const Index alignedSize2 = ((size-alignedStart)/(2*packetSize))*(2*packetSize); - const Index alignedSize = ((size-alignedStart)/(packetSize))*(packetSize); +template +struct redux_impl + : redux_novec_unroller { + typedef redux_novec_unroller Base; + typedef typename Evaluator::Scalar Scalar; + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func, + const XprType& /*xpr*/) { + return Base::run(eval, func); + } +}; + +template +struct redux_impl + : redux_novec_linear_unroller { + typedef redux_novec_linear_unroller Base; + typedef typename Evaluator::Scalar Scalar; + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func, + const XprType& /*xpr*/) { + return Base::run(eval, func); + } +}; + +template +struct redux_impl { + typedef typename Evaluator::Scalar Scalar; + typedef typename redux_traits::PacketType PacketScalar; + + template + static Scalar run(const Evaluator& eval, const Func& func, const XprType& xpr) { + const Index size = xpr.size(); + + constexpr Index packetSize = redux_traits::PacketSize; + constexpr int packetAlignment = unpacket_traits::alignment; + constexpr int alignment0 = + (bool(Evaluator::Flags & DirectAccessBit) && bool(packet_traits::AlignedOnScalar)) + ? int(packetAlignment) + : int(Unaligned); + constexpr int alignment = plain_enum_max(alignment0, Evaluator::Alignment); + const Index alignedStart = internal::first_default_aligned(xpr); + const Index alignedSize2 = ((size - alignedStart) / (2 * packetSize)) * (2 * packetSize); + const Index alignedSize = ((size - alignedStart) / (packetSize)) * (packetSize); const Index alignedEnd2 = alignedStart + alignedSize2; - const Index alignedEnd = alignedStart + alignedSize; + const Index alignedEnd = alignedStart + alignedSize; Scalar res; - if(alignedSize) - { - PacketScalar packet_res0 = mat.template packet(alignedStart); - if(alignedSize>packetSize) // we have at least two packets to partly unroll the loop + if (alignedSize) { + PacketScalar packet_res0 = eval.template packet(alignedStart); + if (alignedSize > packetSize) // we have at least two packets to partly unroll the loop { - PacketScalar packet_res1 = mat.template packet(alignedStart+packetSize); - for(Index index = alignedStart + 2*packetSize; index < alignedEnd2; index += 2*packetSize) - { - packet_res0 = func.packetOp(packet_res0, mat.template packet(index)); - packet_res1 = func.packetOp(packet_res1, mat.template packet(index+packetSize)); + PacketScalar packet_res1 = eval.template packet(alignedStart + packetSize); + for (Index index = alignedStart + 2 * packetSize; index < alignedEnd2; index += 2 * packetSize) { + packet_res0 = func.packetOp(packet_res0, eval.template packet(index)); + packet_res1 = func.packetOp(packet_res1, eval.template packet(index + packetSize)); } - packet_res0 = func.packetOp(packet_res0,packet_res1); - if(alignedEnd>alignedEnd2) - packet_res0 = func.packetOp(packet_res0, mat.template packet(alignedEnd2)); + packet_res0 = func.packetOp(packet_res0, packet_res1); + if (alignedEnd > alignedEnd2) + packet_res0 = func.packetOp(packet_res0, eval.template packet(alignedEnd2)); } res = func.predux(packet_res0); - for(Index index = 0; index < alignedStart; ++index) - res = func(res,mat.coeff(index)); + for (Index index = 0; index < alignedStart; ++index) res = func(res, eval.coeff(index)); - for(Index index = alignedEnd; index < size; ++index) - res = func(res,mat.coeff(index)); - } - else // too small to vectorize anything. - // since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize. + for (Index index = alignedEnd; index < size; ++index) res = func(res, eval.coeff(index)); + } else // too small to vectorize anything. + // since this is dynamic-size hence inefficient anyway for such small sizes, don't try to optimize. { - res = mat.coeff(0); - for(Index index = 1; index < size; ++index) - res = func(res,mat.coeff(index)); + res = eval.coeff(0); + for (Index index = 1; index < size; ++index) res = func(res, eval.coeff(index)); } return res; @@ -248,162 +324,212 @@ struct redux_impl }; // NOTE: for SliceVectorizedTraversal we simply bypass unrolling -template -struct redux_impl -{ - typedef typename Derived::Scalar Scalar; - typedef typename packet_traits::type PacketScalar; - typedef typename Derived::Index Index; - - static Scalar run(const Derived& mat, const Func& func) - { - eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix"); - const Index innerSize = mat.innerSize(); - const Index outerSize = mat.outerSize(); - enum { - packetSize = packet_traits::size - }; - const Index packetedInnerSize = ((innerSize)/packetSize)*packetSize; +template +struct redux_impl { + typedef typename Evaluator::Scalar Scalar; + typedef typename redux_traits::PacketType PacketType; + + template + EIGEN_DEVICE_FUNC static Scalar run(const Evaluator& eval, const Func& func, const XprType& xpr) { + eigen_assert(xpr.rows() > 0 && xpr.cols() > 0 && "you are using an empty matrix"); + constexpr Index packetSize = redux_traits::PacketSize; + const Index innerSize = xpr.innerSize(); + const Index outerSize = xpr.outerSize(); + const Index packetedInnerSize = ((innerSize) / packetSize) * packetSize; Scalar res; - if(packetedInnerSize) - { - PacketScalar packet_res = mat.template packet(0,0); - for(Index j=0; j(j,i)); + if (packetedInnerSize) { + PacketType packet_res = eval.template packet(0, 0); + for (Index j = 0; j < outerSize; ++j) + for (Index i = (j == 0 ? packetSize : 0); i < packetedInnerSize; i += Index(packetSize)) + packet_res = func.packetOp(packet_res, eval.template packetByOuterInner(j, i)); res = func.predux(packet_res); - for(Index j=0; j::run(mat, func); + res = redux_impl::run(eval, func, xpr); } return res; } }; -template -struct redux_impl -{ - typedef typename Derived::Scalar Scalar; - typedef typename packet_traits::type PacketScalar; +template +struct redux_impl { + typedef typename Evaluator::Scalar Scalar; + + typedef typename redux_traits::PacketType PacketType; + static constexpr Index PacketSize = redux_traits::PacketSize; + static constexpr Index Size = Evaluator::SizeAtCompileTime; + static constexpr Index VectorizedSize = (int(Size) / int(PacketSize)) * int(PacketSize); + + template + EIGEN_DEVICE_FUNC static EIGEN_STRONG_INLINE Scalar run(const Evaluator& eval, const Func& func, const XprType& xpr) { + EIGEN_ONLY_USED_FOR_DEBUG(xpr) + eigen_assert(xpr.rows() > 0 && xpr.cols() > 0 && "you are using an empty matrix"); + if (VectorizedSize > 0) { + Scalar res = func.predux( + redux_vec_linear_unroller::template run(eval, func)); + if (VectorizedSize != Size) + res = func( + res, redux_novec_linear_unroller::run(eval, func)); + return res; + } else { + return redux_novec_linear_unroller::run(eval, func); + } + } +}; + +// evaluator adaptor +template +class redux_evaluator : public internal::evaluator { + typedef internal::evaluator Base; + + public: + typedef XprType_ XprType; + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE explicit redux_evaluator(const XprType& xpr) : Base(xpr) {} + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + typedef typename XprType::PacketScalar PacketScalar; + enum { - PacketSize = packet_traits::size, - Size = Derived::SizeAtCompileTime, - VectorizedSize = (Size / PacketSize) * PacketSize + MaxRowsAtCompileTime = XprType::MaxRowsAtCompileTime, + MaxColsAtCompileTime = XprType::MaxColsAtCompileTime, + // TODO we should not remove DirectAccessBit and rather find an elegant way to query the alignment offset at runtime + // from the evaluator + Flags = Base::Flags & ~DirectAccessBit, + IsRowMajor = XprType::IsRowMajor, + SizeAtCompileTime = XprType::SizeAtCompileTime, + InnerSizeAtCompileTime = XprType::InnerSizeAtCompileTime }; - static EIGEN_STRONG_INLINE Scalar run(const Derived& mat, const Func& func) - { - eigen_assert(mat.rows()>0 && mat.cols()>0 && "you are using an empty matrix"); - Scalar res = func.predux(redux_vec_unroller::run(mat,func)); - if (VectorizedSize != Size) - res = func(res,redux_novec_unroller::run(mat,func)); - return res; + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE CoeffReturnType coeffByOuterInner(Index outer, Index inner) const { + return Base::coeff(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetByOuterInner(Index outer, Index inner) const { + return Base::template packet(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer); + } + + template + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE PacketType packetSegmentByOuterInner(Index outer, Index inner, Index begin, + Index count) const { + return Base::template packetSegment(IsRowMajor ? outer : inner, IsRowMajor ? inner : outer, + begin, count); } }; -} // end namespace internal +} // end namespace internal /*************************************************************************** -* Part 4 : public API -***************************************************************************/ - + * Part 4 : public API + ***************************************************************************/ /** \returns the result of a full redux operation on the whole matrix or vector using \a func - * - * The template parameter \a BinaryOp is the type of the functor \a func which must be - * an associative operator. Both current STL and TR1 functor styles are handled. - * - * \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise() - */ -template -template -EIGEN_STRONG_INLINE typename internal::result_of::Scalar)>::type -DenseBase::redux(const Func& func) const -{ - typedef typename internal::remove_all::type ThisNested; - return internal::redux_impl - ::run(derived(), func); + * + * The template parameter \a BinaryOp is the type of the functor \a func which must be + * an associative operator. Both current C++98 and C++11 functor styles are handled. + * + * \warning the matrix must be not empty, otherwise an assertion is triggered. + * + * \sa DenseBase::sum(), DenseBase::minCoeff(), DenseBase::maxCoeff(), MatrixBase::colwise(), MatrixBase::rowwise() + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::redux( + const Func& func) const { + eigen_assert(this->rows() > 0 && this->cols() > 0 && "you are using an empty matrix"); + + typedef typename internal::redux_evaluator ThisEvaluator; + ThisEvaluator thisEval(derived()); + + // The initial expression is passed to the reducer as an additional argument instead of + // passing it as a member of redux_evaluator to help + return internal::redux_impl::run(thisEval, func, derived()); } /** \returns the minimum of all coefficients of \c *this. - * \warning the result is undefined if \c *this contains NaN. - */ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -DenseBase::minCoeff() const -{ - return this->redux(Eigen::internal::scalar_min_op()); + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is minimum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::minCoeff() const { + return derived().redux(Eigen::internal::scalar_min_op()); } /** \returns the maximum of all coefficients of \c *this. - * \warning the result is undefined if \c *this contains NaN. - */ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -DenseBase::maxCoeff() const -{ - return this->redux(Eigen::internal::scalar_max_op()); + * In case \c *this contains NaN, NaNPropagation determines the behavior: + * NaNPropagation == PropagateFast : undefined + * NaNPropagation == PropagateNaN : result is NaN + * NaNPropagation == PropagateNumbers : result is maximum of elements that are not NaN + * \warning the matrix must be not empty, otherwise an assertion is triggered. + */ +template +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::maxCoeff() const { + return derived().redux(Eigen::internal::scalar_max_op()); } -/** \returns the sum of all coefficients of *this - * - * \sa trace(), prod(), mean() - */ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -DenseBase::sum() const -{ - if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0)) - return Scalar(0); - return this->redux(Eigen::internal::scalar_sum_op()); +/** \returns the sum of all coefficients of \c *this + * + * If \c *this is empty, then the value 0 is returned. + * + * \sa trace(), prod(), mean() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::sum() const { + if (SizeAtCompileTime == 0 || (SizeAtCompileTime == Dynamic && size() == 0)) return Scalar(0); + return derived().redux(Eigen::internal::scalar_sum_op()); } /** \returns the mean of all coefficients of *this -* -* \sa trace(), prod(), sum() -*/ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -DenseBase::mean() const -{ - return Scalar(this->redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); + * + * \sa trace(), prod(), sum() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::mean() const { +#ifdef __INTEL_COMPILER +#pragma warning push +#pragma warning(disable : 2259) +#endif + return Scalar(derived().redux(Eigen::internal::scalar_sum_op())) / Scalar(this->size()); +#ifdef __INTEL_COMPILER +#pragma warning pop +#endif } /** \returns the product of all coefficients of *this - * - * Example: \include MatrixBase_prod.cpp - * Output: \verbinclude MatrixBase_prod.out - * - * \sa sum(), mean(), trace() - */ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -DenseBase::prod() const -{ - if(SizeAtCompileTime==0 || (SizeAtCompileTime==Dynamic && size()==0)) - return Scalar(1); - return this->redux(Eigen::internal::scalar_product_op()); + * + * Example: \include MatrixBase_prod.cpp + * Output: \verbinclude MatrixBase_prod.out + * + * \sa sum(), mean(), trace() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar DenseBase::prod() const { + if (SizeAtCompileTime == 0 || (SizeAtCompileTime == Dynamic && size() == 0)) return Scalar(1); + return derived().redux(Eigen::internal::scalar_product_op()); } /** \returns the trace of \c *this, i.e. the sum of the coefficients on the main diagonal. - * - * \c *this can be any matrix, not necessarily square. - * - * \sa diagonal(), sum() - */ -template -EIGEN_STRONG_INLINE typename internal::traits::Scalar -MatrixBase::trace() const -{ + * + * \c *this can be any matrix, not necessarily square. + * + * \sa diagonal(), sum() + */ +template +EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE typename internal::traits::Scalar MatrixBase::trace() const { return derived().diagonal().sum(); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_REDUX_H +#endif // EIGEN_REDUX_H diff --git a/inst/include/Eigen/src/Core/Ref.h b/inst/include/Eigen/src/Core/Ref.h index 7a3becaf..30ec277d 100644 --- a/inst/include/Eigen/src/Core/Ref.h +++ b/inst/include/Eigen/src/Core/Ref.h @@ -10,269 +10,374 @@ #ifndef EIGEN_REF_H #define EIGEN_REF_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -template class RefBase; -template,OuterStride<> >::type > class Ref; - -/** \class Ref - * \ingroup Core_Module - * - * \brief A matrix or vector expression mapping an existing expressions - * - * \tparam PlainObjectType the equivalent matrix type of the mapped data - * \tparam Options specifies whether the pointer is \c #Aligned, or \c #Unaligned. - * The default is \c #Unaligned. - * \tparam StrideType optionally specifies strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1), - * but accept a variable outer stride (leading dimension). - * This can be overridden by specifying strides. - * The type passed here must be a specialization of the Stride template, see examples below. - * - * This class permits to write non template functions taking Eigen's object as parameters while limiting the number of copies. - * A Ref<> object can represent either a const expression or a l-value: - * \code - * // in-out argument: - * void foo1(Ref x); - * - * // read-only const argument: - * void foo2(const Ref& x); - * \endcode - * - * In the in-out case, the input argument must satisfies the constraints of the actual Ref<> type, otherwise a compilation issue will be triggered. - * By default, a Ref can reference any dense vector expression of float having a contiguous memory layout. - * Likewise, a Ref can reference any column major dense matrix expression of float whose column's elements are contiguously stored with - * the possibility to have a constant space inbetween each column, i.e.: the inner stride mmust be equal to 1, but the outer-stride (or leading dimension), - * can be greater than the number of rows. - * - * In the const case, if the input expression does not match the above requirement, then it is evaluated into a temporary before being passed to the function. - * Here are some examples: - * \code - * MatrixXf A; - * VectorXf a; - * foo1(a.head()); // OK - * foo1(A.col()); // OK - * foo1(A.row()); // compilation error because here innerstride!=1 - * foo2(A.row()); // The row is copied into a contiguous temporary - * foo2(2*a); // The expression is evaluated into a temporary - * foo2(A.col().segment(2,4)); // No temporary - * \endcode - * - * The range of inputs that can be referenced without temporary can be enlarged using the last two template parameter. - * Here is an example accepting an innerstride!=1: - * \code - * // in-out argument: - * void foo3(Ref > x); - * foo3(A.row()); // OK - * \endcode - * The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to exploit vectorization, and will involved more - * expensive address computations even if the input is contiguously stored in memory. To overcome this issue, one might propose to overloads internally calling a - * template function, e.g.: - * \code - * // in the .h: - * void foo(const Ref& A); - * void foo(const Ref >& A); - * - * // in the .cpp: - * template void foo_impl(const TypeOfA& A) { - * ... // crazy code goes here - * } - * void foo(const Ref& A) { foo_impl(A); } - * void foo(const Ref >& A) { foo_impl(A); } - * \endcode - * - * - * \sa PlainObjectBase::Map(), \ref TopicStorageOrders - */ +namespace Eigen { namespace internal { -template -struct traits > - : public traits > -{ - typedef _PlainObjectType PlainObjectType; - typedef _StrideType StrideType; +template +struct traits > + : public traits > { + typedef PlainObjectType_ PlainObjectType; + typedef StrideType_ StrideType; enum { - Options = _Options, - Flags = traits >::Flags | NestByRefBit + Options = Options_, + Flags = traits >::Flags | NestByRefBit, + Alignment = traits >::Alignment, + InnerStrideAtCompileTime = traits >::InnerStrideAtCompileTime, + OuterStrideAtCompileTime = traits >::OuterStrideAtCompileTime }; - template struct match { + template + struct match { enum { + IsVectorAtCompileTime = PlainObjectType::IsVectorAtCompileTime || Derived::IsVectorAtCompileTime, HasDirectAccess = internal::has_direct_access::ret, - StorageOrderMatch = PlainObjectType::IsVectorAtCompileTime || Derived::IsVectorAtCompileTime || ((PlainObjectType::Flags&RowMajorBit)==(Derived::Flags&RowMajorBit)), - InnerStrideMatch = int(StrideType::InnerStrideAtCompileTime)==int(Dynamic) - || int(StrideType::InnerStrideAtCompileTime)==int(Derived::InnerStrideAtCompileTime) - || (int(StrideType::InnerStrideAtCompileTime)==0 && int(Derived::InnerStrideAtCompileTime)==1), - OuterStrideMatch = Derived::IsVectorAtCompileTime - || int(StrideType::OuterStrideAtCompileTime)==int(Dynamic) || int(StrideType::OuterStrideAtCompileTime)==int(Derived::OuterStrideAtCompileTime), - AlignmentMatch = (_Options!=Aligned) || ((PlainObjectType::Flags&AlignedBit)==0) || ((traits::Flags&AlignedBit)==AlignedBit), + StorageOrderMatch = + IsVectorAtCompileTime || ((PlainObjectType::Flags & RowMajorBit) == (Derived::Flags & RowMajorBit)), + InnerStrideMatch = int(InnerStrideAtCompileTime) == int(Dynamic) || + int(InnerStrideAtCompileTime) == int(Derived::InnerStrideAtCompileTime) || + (int(InnerStrideAtCompileTime) == 0 && int(Derived::InnerStrideAtCompileTime) == 1), + OuterStrideMatch = IsVectorAtCompileTime || int(OuterStrideAtCompileTime) == int(Dynamic) || + int(OuterStrideAtCompileTime) == int(Derived::OuterStrideAtCompileTime), + // NOTE, this indirection of evaluator::Alignment is needed + // to workaround a very strange bug in MSVC related to the instantiation + // of has_*ary_operator in evaluator. + // This line is surprisingly very sensitive. For instance, simply adding parenthesis + // as "DerivedAlignment = (int(evaluator::Alignment))," will make MSVC fail... + DerivedAlignment = int(evaluator::Alignment), + AlignmentMatch = (int(traits::Alignment) == int(Unaligned)) || + (DerivedAlignment >= int(Alignment)), // FIXME the first condition is not very clear, it should + // be replaced by the required alignment ScalarTypeMatch = internal::is_same::value, - MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && AlignmentMatch && ScalarTypeMatch + MatchAtCompileTime = HasDirectAccess && StorageOrderMatch && InnerStrideMatch && OuterStrideMatch && + AlignmentMatch && ScalarTypeMatch }; - typedef typename internal::conditional::type type; + typedef std::conditional_t type; }; - }; -template +template struct traits > : public traits {}; -} +} // namespace internal -template class RefBase - : public MapBase -{ +template +class RefBase : public MapBase { typedef typename internal::traits::PlainObjectType PlainObjectType; typedef typename internal::traits::StrideType StrideType; -public: - + public: typedef MapBase Base; EIGEN_DENSE_PUBLIC_INTERFACE(RefBase) - inline Index innerStride() const - { + EIGEN_DEVICE_FUNC constexpr Index innerStride() const { return StrideType::InnerStrideAtCompileTime != 0 ? m_stride.inner() : 1; } - inline Index outerStride() const - { + EIGEN_DEVICE_FUNC constexpr Index outerStride() const { return StrideType::OuterStrideAtCompileTime != 0 ? m_stride.outer() - : IsVectorAtCompileTime ? this->size() - : int(Flags)&RowMajorBit ? this->cols() - : this->rows(); + : IsVectorAtCompileTime ? this->size() + : int(Flags) & RowMajorBit ? this->cols() + : this->rows(); } - RefBase() - : Base(0,RowsAtCompileTime==Dynamic?0:RowsAtCompileTime,ColsAtCompileTime==Dynamic?0:ColsAtCompileTime), - // Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values: - m_stride(StrideType::OuterStrideAtCompileTime==Dynamic?0:StrideType::OuterStrideAtCompileTime, - StrideType::InnerStrideAtCompileTime==Dynamic?0:StrideType::InnerStrideAtCompileTime) - {} - + EIGEN_DEVICE_FUNC RefBase() + : Base(0, RowsAtCompileTime == Dynamic ? 0 : RowsAtCompileTime, + ColsAtCompileTime == Dynamic ? 0 : ColsAtCompileTime), + // Stride<> does not allow default ctor for Dynamic strides, so let' initialize it with dummy values: + m_stride(StrideType::OuterStrideAtCompileTime == Dynamic ? 0 : StrideType::OuterStrideAtCompileTime, + StrideType::InnerStrideAtCompileTime == Dynamic ? 0 : StrideType::InnerStrideAtCompileTime) {} + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(RefBase) -protected: + protected: + typedef Stride StrideBase; - typedef Stride StrideBase; + // Resolves inner stride if default 0. + static EIGEN_DEVICE_FUNC constexpr Index resolveInnerStride(Index inner) { return inner == 0 ? 1 : inner; } - template - void construct(Expression& expr) - { - if(PlainObjectType::RowsAtCompileTime==1) - { - eigen_assert(expr.rows()==1 || expr.cols()==1); - ::new (static_cast(this)) Base(expr.data(), 1, expr.size()); + // Resolves outer stride if default 0. + static EIGEN_DEVICE_FUNC constexpr Index resolveOuterStride(Index inner, Index outer, Index rows, Index cols, + bool isVectorAtCompileTime, bool isRowMajor) { + return outer == 0 ? isVectorAtCompileTime ? inner * rows * cols : isRowMajor ? inner * cols : inner * rows : outer; + } + + // Returns true if construction is valid, false if there is a stride mismatch, + // and fails if there is a size mismatch. + template + EIGEN_DEVICE_FUNC bool construct(Expression& expr) { + // Check matrix sizes. If this is a compile-time vector, we do allow + // implicitly transposing. + EIGEN_STATIC_ASSERT(EIGEN_PREDICATE_SAME_MATRIX_SIZE(PlainObjectType, Expression) + // If it is a vector, the transpose sizes might match. + || (PlainObjectType::IsVectorAtCompileTime && + ((int(PlainObjectType::RowsAtCompileTime) == Eigen::Dynamic || + int(Expression::ColsAtCompileTime) == Eigen::Dynamic || + int(PlainObjectType::RowsAtCompileTime) == int(Expression::ColsAtCompileTime)) && + (int(PlainObjectType::ColsAtCompileTime) == Eigen::Dynamic || + int(Expression::RowsAtCompileTime) == Eigen::Dynamic || + int(PlainObjectType::ColsAtCompileTime) == int(Expression::RowsAtCompileTime)))), + YOU_MIXED_MATRICES_OF_DIFFERENT_SIZES) + + // Determine runtime rows and columns. + Index rows = expr.rows(); + Index cols = expr.cols(); + if (PlainObjectType::RowsAtCompileTime == 1) { + eigen_assert(expr.rows() == 1 || expr.cols() == 1); + rows = 1; + cols = expr.size(); + } else if (PlainObjectType::ColsAtCompileTime == 1) { + eigen_assert(expr.rows() == 1 || expr.cols() == 1); + rows = expr.size(); + cols = 1; } - else if(PlainObjectType::ColsAtCompileTime==1) - { - eigen_assert(expr.rows()==1 || expr.cols()==1); - ::new (static_cast(this)) Base(expr.data(), expr.size(), 1); + // Verify that the sizes are valid. + eigen_assert((PlainObjectType::RowsAtCompileTime == Dynamic) || (PlainObjectType::RowsAtCompileTime == rows)); + eigen_assert((PlainObjectType::ColsAtCompileTime == Dynamic) || (PlainObjectType::ColsAtCompileTime == cols)); + + // If this is a vector, we might be transposing, which means that stride should swap. + const bool transpose = PlainObjectType::IsVectorAtCompileTime && (rows != expr.rows()); + // If the storage format differs, we also need to swap the stride. + const bool row_major = ((PlainObjectType::Flags)&RowMajorBit) != 0; + const bool expr_row_major = (Expression::Flags & RowMajorBit) != 0; + const bool storage_differs = (row_major != expr_row_major); + + const bool swap_stride = (transpose != storage_differs); + + // Determine expr's actual strides, resolving any defaults if zero. + const Index expr_inner_actual = resolveInnerStride(expr.innerStride()); + const Index expr_outer_actual = resolveOuterStride(expr_inner_actual, expr.outerStride(), expr.rows(), expr.cols(), + Expression::IsVectorAtCompileTime != 0, expr_row_major); + + // If this is a column-major row vector or row-major column vector, the inner-stride + // is arbitrary, so set it to either the compile-time inner stride or 1. + const bool row_vector = (rows == 1); + const bool col_vector = (cols == 1); + const Index inner_stride = + ((!row_major && row_vector) || (row_major && col_vector)) + ? (StrideType::InnerStrideAtCompileTime > 0 ? Index(StrideType::InnerStrideAtCompileTime) : 1) + : swap_stride ? expr_outer_actual + : expr_inner_actual; + + // If this is a column-major column vector or row-major row vector, the outer-stride + // is arbitrary, so set it to either the compile-time outer stride or vector size. + const Index outer_stride = + ((!row_major && col_vector) || (row_major && row_vector)) + ? (StrideType::OuterStrideAtCompileTime > 0 ? Index(StrideType::OuterStrideAtCompileTime) + : rows * cols * inner_stride) + : swap_stride ? expr_inner_actual + : expr_outer_actual; + + // Check if given inner/outer strides are compatible with compile-time strides. + const bool inner_valid = (StrideType::InnerStrideAtCompileTime == Dynamic) || + (resolveInnerStride(Index(StrideType::InnerStrideAtCompileTime)) == inner_stride); + if (!inner_valid) { + return false; } - else - ::new (static_cast(this)) Base(expr.data(), expr.rows(), expr.cols()); - - if(Expression::IsVectorAtCompileTime && (!PlainObjectType::IsVectorAtCompileTime) && ((Expression::Flags&RowMajorBit)!=(PlainObjectType::Flags&RowMajorBit))) - ::new (&m_stride) StrideBase(expr.innerStride(), StrideType::InnerStrideAtCompileTime==0?0:1); - else - ::new (&m_stride) StrideBase(StrideType::OuterStrideAtCompileTime==0?0:expr.outerStride(), - StrideType::InnerStrideAtCompileTime==0?0:expr.innerStride()); + + const bool outer_valid = + (StrideType::OuterStrideAtCompileTime == Dynamic) || + (resolveOuterStride(inner_stride, Index(StrideType::OuterStrideAtCompileTime), rows, cols, + PlainObjectType::IsVectorAtCompileTime != 0, row_major) == outer_stride); + if (!outer_valid) { + return false; + } + + internal::construct_at(this, expr.data(), rows, cols); + internal::construct_at(&m_stride, (StrideType::OuterStrideAtCompileTime == 0) ? 0 : outer_stride, + (StrideType::InnerStrideAtCompileTime == 0) ? 0 : inner_stride); + return true; } StrideBase m_stride; }; +/** \class Ref + * \ingroup Core_Module + * + * \brief A matrix or vector expression mapping an existing expression + * + * \tparam PlainObjectType the equivalent matrix type of the mapped data + * \tparam Options specifies the pointer alignment in bytes. It can be: \c #Aligned128, , \c #Aligned64, \c #Aligned32, + * \c #Aligned16, \c #Aligned8 or \c #Unaligned. The default is \c #Unaligned. \tparam StrideType optionally specifies + * strides. By default, Ref implies a contiguous storage along the inner dimension (inner stride==1), but accepts a + * variable outer stride (leading dimension). This can be overridden by specifying strides. The type passed here must be + * a specialization of the Stride template, see examples below. + * + * This class provides a way to write non-template functions taking Eigen objects as parameters while limiting the + * number of copies. A Ref<> object can represent either a const expression or a l-value: \code + * // in-out argument: + * void foo1(Ref x); + * + * // read-only const argument: + * void foo2(const Ref& x); + * \endcode + * + * In the in-out case, the input argument must satisfy the constraints of the actual Ref<> type, otherwise a compilation + * issue will be triggered. By default, a Ref can reference any dense vector expression of float having a + * contiguous memory layout. Likewise, a Ref can reference any column-major dense matrix expression of float + * whose column's elements are contiguously stored with the possibility to have a constant space in-between each column, + * i.e. the inner stride must be equal to 1, but the outer stride (or leading dimension) can be greater than the number + * of rows. + * + * In the const case, if the input expression does not match the above requirement, then it is evaluated into a + * temporary before being passed to the function. Here are some examples: \code MatrixXf A; VectorXf a; foo1(a.head()); + * // OK foo1(A.col()); // OK foo1(A.row()); // Compilation error because here innerstride!=1 + * foo2(A.row()); // Compilation error because A.row() is a 1xN object while foo2 is expecting a Nx1 object + * foo2(A.row().transpose()); // The row is copied into a contiguous temporary + * foo2(2*a); // The expression is evaluated into a temporary + * foo2(A.col().segment(2,4)); // No temporary + * \endcode + * + * The range of inputs that can be referenced without temporary can be enlarged using the last two template parameters. + * Here is an example accepting an innerstride!=1: + * \code + * // in-out argument: + * void foo3(Ref > x); + * foo3(A.row()); // OK + * \endcode + * The downside here is that the function foo3 might be significantly slower than foo1 because it won't be able to + * exploit vectorization, and will involve more expensive address computations even if the input is contiguously stored + * in memory. To overcome this issue, one might propose to overload internally calling a template function, e.g.: \code + * // in the .h: + * void foo(const Ref& A); + * void foo(const Ref >& A); + * + * // in the .cpp: + * template void foo_impl(const TypeOfA& A) { + * ... // crazy code goes here + * } + * void foo(const Ref& A) { foo_impl(A); } + * void foo(const Ref >& A) { foo_impl(A); } + * \endcode + * + * See also the following stackoverflow questions for further references: + * - Correct usage of the + * Eigen::Ref<> class + * + * \sa PlainObjectBase::Map(), \ref TopicStorageOrders + */ +template +class Ref : public RefBase > { + private: + typedef internal::traits Traits; + template + EIGEN_DEVICE_FUNC inline Ref( + const PlainObjectBase& expr, + std::enable_if_t::MatchAtCompileTime), Derived>* = 0); + + public: + typedef RefBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Ref) + +#ifndef EIGEN_PARSED_BY_DOXYGEN + template + EIGEN_DEVICE_FUNC inline Ref( + PlainObjectBase& expr, + std::enable_if_t::MatchAtCompileTime), Derived>* = 0) { + EIGEN_STATIC_ASSERT(bool(Traits::template match::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH); + // Construction must pass since we will not create temporary storage in the non-const case. + const bool success = Base::construct(expr.derived()); + EIGEN_UNUSED_VARIABLE(success) + eigen_assert(success); + } + template + EIGEN_DEVICE_FUNC inline Ref( + const DenseBase& expr, + std::enable_if_t::MatchAtCompileTime), Derived>* = 0) +#else + /** Implicit constructor from any dense expression */ + template + inline Ref(DenseBase& expr) +#endif + { + EIGEN_STATIC_ASSERT(bool(internal::is_lvalue::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY); + EIGEN_STATIC_ASSERT(bool(Traits::template match::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH); + EIGEN_STATIC_ASSERT(!Derived::IsPlainObjectBase, THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY); + // Construction must pass since we will not create temporary storage in the non-const case. + const bool success = Base::construct(expr.const_cast_derived()); + EIGEN_UNUSED_VARIABLE(success) + eigen_assert(success); + } -template class Ref - : public RefBase > -{ - private: - typedef internal::traits Traits; - template - inline Ref(const PlainObjectBase& expr, - typename internal::enable_if::MatchAtCompileTime),Derived>::type* = 0); - public: - - typedef RefBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Ref) - - - #ifndef EIGEN_PARSED_BY_DOXYGEN - template - inline Ref(PlainObjectBase& expr, - typename internal::enable_if::MatchAtCompileTime),Derived>::type* = 0) - { - EIGEN_STATIC_ASSERT(static_cast(Traits::template match::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH); - Base::construct(expr.derived()); - } - template - inline Ref(const DenseBase& expr, - typename internal::enable_if::MatchAtCompileTime),Derived>::type* = 0) - #else - template - inline Ref(DenseBase& expr) - #endif - { - EIGEN_STATIC_ASSERT(static_cast(internal::is_lvalue::value), THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY); - EIGEN_STATIC_ASSERT(static_cast(Traits::template match::MatchAtCompileTime), STORAGE_LAYOUT_DOES_NOT_MATCH); - enum { THIS_EXPRESSION_IS_NOT_A_LVALUE__IT_IS_READ_ONLY = Derived::ThisConstantIsPrivateInPlainObjectBase}; - Base::construct(expr.const_cast_derived()); - } - - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Ref) - + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Ref) }; // this is the const ref version -template class Ref - : public RefBase > -{ - typedef internal::traits Traits; - public: - - typedef RefBase Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Ref) - - template - inline Ref(const DenseBase& expr, - typename internal::enable_if::ScalarTypeMatch),Derived>::type* = 0) - { -// std::cout << match_helper::HasDirectAccess << "," << match_helper::OuterStrideMatch << "," << match_helper::InnerStrideMatch << "\n"; -// std::cout << int(StrideType::OuterStrideAtCompileTime) << " - " << int(Derived::OuterStrideAtCompileTime) << "\n"; -// std::cout << int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n"; - construct(expr.derived(), typename Traits::template match::type()); - } - - inline Ref(const Ref& other) : Base(other) { - // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy - } +template +class Ref + : public RefBase > { + typedef internal::traits Traits; + + static constexpr bool may_map_m_object_successfully = + (static_cast(StrideType::InnerStrideAtCompileTime) == 0 || + static_cast(StrideType::InnerStrideAtCompileTime) == 1 || + static_cast(StrideType::InnerStrideAtCompileTime) == Dynamic) && + (TPlainObjectType::IsVectorAtCompileTime || static_cast(StrideType::OuterStrideAtCompileTime) == 0 || + static_cast(StrideType::OuterStrideAtCompileTime) == Dynamic || + static_cast(StrideType::OuterStrideAtCompileTime) == + static_cast(TPlainObjectType::InnerSizeAtCompileTime) || + static_cast(TPlainObjectType::InnerSizeAtCompileTime) == Dynamic); + + public: + typedef RefBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Ref) + + template + EIGEN_DEVICE_FUNC inline Ref(const DenseBase& expr, + std::enable_if_t::ScalarTypeMatch), Derived>* = 0) { + // std::cout << match_helper::HasDirectAccess << "," << match_helper::OuterStrideMatch << "," + // << match_helper::InnerStrideMatch << "\n"; std::cout << int(StrideType::OuterStrideAtCompileTime) + // << " - " << int(Derived::OuterStrideAtCompileTime) << "\n"; std::cout << + // int(StrideType::InnerStrideAtCompileTime) << " - " << int(Derived::InnerStrideAtCompileTime) << "\n"; + EIGEN_STATIC_ASSERT(Traits::template match::type::value || may_map_m_object_successfully, + STORAGE_LAYOUT_DOES_NOT_MATCH); + construct(expr.derived(), typename Traits::template match::type()); + } - template - inline Ref(const RefBase& other) { - construct(other.derived(), typename Traits::template match::type()); - } + EIGEN_DEVICE_FUNC inline Ref(const Ref& other) : Base(other) { + // copy constructor shall not copy the m_object, to avoid unnecessary malloc and copy + } - protected: + EIGEN_DEVICE_FUNC inline Ref(Ref&& other) { + if (other.data() == other.m_object.data()) { + m_object = std::move(other.m_object); + Base::construct(m_object); + } else + Base::construct(other); + } - template - void construct(const Expression& expr,internal::true_type) - { - Base::construct(expr); - } + template + EIGEN_DEVICE_FUNC inline Ref(const RefBase& other) { + EIGEN_STATIC_ASSERT(Traits::template match::type::value || may_map_m_object_successfully, + STORAGE_LAYOUT_DOES_NOT_MATCH); + construct(other.derived(), typename Traits::template match::type()); + } - template - void construct(const Expression& expr, internal::false_type) - { - m_object.lazyAssign(expr); - Base::construct(m_object); + protected: + template + EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::true_type) { + // Check if we can use the underlying expr's storage directly, otherwise call the copy version. + if (!Base::construct(expr)) { + construct(expr, internal::false_type()); } + } + + template + EIGEN_DEVICE_FUNC void construct(const Expression& expr, internal::false_type) { + internal::call_assignment_no_alias(m_object, expr, internal::assign_op()); + const bool success = Base::construct(m_object); + EIGEN_ONLY_USED_FOR_DEBUG(success) + eigen_assert(success); + } - protected: - TPlainObjectType m_object; + protected: + TPlainObjectType m_object; }; -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_REF_H +#endif // EIGEN_REF_H diff --git a/inst/include/Eigen/src/Core/Replicate.h b/inst/include/Eigen/src/Core/Replicate.h index ac4537c1..34150452 100644 --- a/inst/include/Eigen/src/Core/Replicate.h +++ b/inst/include/Eigen/src/Core/Replicate.h @@ -10,168 +10,121 @@ #ifndef EIGEN_REPLICATE_H #define EIGEN_REPLICATE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** - * \class Replicate - * \ingroup Core_Module - * - * \brief Expression of the multiple replication of a matrix or vector - * - * \param MatrixType the type of the object we are replicating - * - * This class represents an expression of the multiple replication of a matrix or vector. - * It is the return type of DenseBase::replicate() and most of the time - * this is the only way it is used. - * - * \sa DenseBase::replicate() - */ +namespace Eigen { namespace internal { -template -struct traits > - : traits -{ +template +struct traits > : traits { typedef typename MatrixType::Scalar Scalar; typedef typename traits::StorageKind StorageKind; typedef typename traits::XprKind XprKind; + typedef typename ref_selector::type MatrixTypeNested; + typedef std::remove_reference_t MatrixTypeNested_; enum { - Factor = (RowFactor==Dynamic || ColFactor==Dynamic) ? Dynamic : RowFactor*ColFactor - }; - typedef typename nested::type MatrixTypeNested; - typedef typename remove_reference::type _MatrixTypeNested; - enum { - RowsAtCompileTime = RowFactor==Dynamic || int(MatrixType::RowsAtCompileTime)==Dynamic - ? Dynamic - : RowFactor * MatrixType::RowsAtCompileTime, - ColsAtCompileTime = ColFactor==Dynamic || int(MatrixType::ColsAtCompileTime)==Dynamic - ? Dynamic - : ColFactor * MatrixType::ColsAtCompileTime, - //FIXME we don't propagate the max sizes !!! + RowsAtCompileTime = RowFactor == Dynamic || int(MatrixType::RowsAtCompileTime) == Dynamic + ? Dynamic + : RowFactor * MatrixType::RowsAtCompileTime, + ColsAtCompileTime = ColFactor == Dynamic || int(MatrixType::ColsAtCompileTime) == Dynamic + ? Dynamic + : ColFactor * MatrixType::ColsAtCompileTime, + // FIXME we don't propagate the max sizes !!! MaxRowsAtCompileTime = RowsAtCompileTime, MaxColsAtCompileTime = ColsAtCompileTime, - IsRowMajor = MaxRowsAtCompileTime==1 && MaxColsAtCompileTime!=1 ? 1 - : MaxColsAtCompileTime==1 && MaxRowsAtCompileTime!=1 ? 0 - : (MatrixType::Flags & RowMajorBit) ? 1 : 0, - Flags = (_MatrixTypeNested::Flags & HereditaryBits & ~RowMajorBit) | (IsRowMajor ? RowMajorBit : 0), - CoeffReadCost = _MatrixTypeNested::CoeffReadCost - }; -}; -} + IsRowMajor = MaxRowsAtCompileTime == 1 && MaxColsAtCompileTime != 1 ? 1 + : MaxColsAtCompileTime == 1 && MaxRowsAtCompileTime != 1 ? 0 + : (MatrixType::Flags & RowMajorBit) ? 1 + : 0, -template class Replicate - : public internal::dense_xpr_base< Replicate >::type -{ - typedef typename internal::traits::MatrixTypeNested MatrixTypeNested; - typedef typename internal::traits::_MatrixTypeNested _MatrixTypeNested; - public: - - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Replicate) - - template - inline explicit Replicate(const OriginalMatrixType& a_matrix) - : m_matrix(a_matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor) - { - EIGEN_STATIC_ASSERT((internal::is_same::type,OriginalMatrixType>::value), - THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE) - eigen_assert(RowFactor!=Dynamic && ColFactor!=Dynamic); - } - - template - inline Replicate(const OriginalMatrixType& a_matrix, Index rowFactor, Index colFactor) - : m_matrix(a_matrix), m_rowFactor(rowFactor), m_colFactor(colFactor) - { - EIGEN_STATIC_ASSERT((internal::is_same::type,OriginalMatrixType>::value), - THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE) - } - - inline Index rows() const { return m_matrix.rows() * m_rowFactor.value(); } - inline Index cols() const { return m_matrix.cols() * m_colFactor.value(); } - - inline Scalar coeff(Index rowId, Index colId) const - { - // try to avoid using modulo; this is a pure optimization strategy - const Index actual_row = internal::traits::RowsAtCompileTime==1 ? 0 - : RowFactor==1 ? rowId - : rowId%m_matrix.rows(); - const Index actual_col = internal::traits::ColsAtCompileTime==1 ? 0 - : ColFactor==1 ? colId - : colId%m_matrix.cols(); - - return m_matrix.coeff(actual_row, actual_col); - } - template - inline PacketScalar packet(Index rowId, Index colId) const - { - const Index actual_row = internal::traits::RowsAtCompileTime==1 ? 0 - : RowFactor==1 ? rowId - : rowId%m_matrix.rows(); - const Index actual_col = internal::traits::ColsAtCompileTime==1 ? 0 - : ColFactor==1 ? colId - : colId%m_matrix.cols(); - - return m_matrix.template packet(actual_row, actual_col); - } - - const _MatrixTypeNested& nestedExpression() const - { - return m_matrix; - } - - protected: - MatrixTypeNested m_matrix; - const internal::variable_if_dynamic m_rowFactor; - const internal::variable_if_dynamic m_colFactor; + // FIXME enable DirectAccess with negative strides? + Flags = IsRowMajor ? RowMajorBit : 0 + }; }; +} // namespace internal /** - * \return an expression of the replication of \c *this - * - * Example: \include MatrixBase_replicate.cpp - * Output: \verbinclude MatrixBase_replicate.out - * - * \sa VectorwiseOp::replicate(), DenseBase::replicate(Index,Index), class Replicate - */ -template -template -const Replicate -DenseBase::replicate() const -{ - return Replicate(derived()); -} + * \class Replicate + * \ingroup Core_Module + * + * \brief Expression of the multiple replication of a matrix or vector + * + * \tparam MatrixType the type of the object we are replicating + * \tparam RowFactor number of repetitions at compile time along the vertical direction, can be Dynamic. + * \tparam ColFactor number of repetitions at compile time along the horizontal direction, can be Dynamic. + * + * This class represents an expression of the multiple replication of a matrix or vector. + * It is the return type of DenseBase::replicate() and most of the time + * this is the only way it is used. + * + * \sa DenseBase::replicate() + */ +template +class Replicate : public internal::dense_xpr_base >::type { + typedef typename internal::traits::MatrixTypeNested MatrixTypeNested; + typedef typename internal::traits::MatrixTypeNested_ MatrixTypeNested_; + + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Replicate) + typedef internal::remove_all_t NestedExpression; + + template + EIGEN_DEVICE_FUNC inline explicit Replicate(const OriginalMatrixType& matrix) + : m_matrix(matrix), m_rowFactor(RowFactor), m_colFactor(ColFactor) { + EIGEN_STATIC_ASSERT((internal::is_same, OriginalMatrixType>::value), + THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE) + eigen_assert(RowFactor != Dynamic && ColFactor != Dynamic); + } + + template + EIGEN_DEVICE_FUNC inline Replicate(const OriginalMatrixType& matrix, Index rowFactor, Index colFactor) + : m_matrix(matrix), m_rowFactor(rowFactor), m_colFactor(colFactor) { + EIGEN_STATIC_ASSERT((internal::is_same, OriginalMatrixType>::value), + THE_MATRIX_OR_EXPRESSION_THAT_YOU_PASSED_DOES_NOT_HAVE_THE_EXPECTED_TYPE) + } + + EIGEN_DEVICE_FUNC constexpr Index rows() const { return m_matrix.rows() * m_rowFactor.value(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const { return m_matrix.cols() * m_colFactor.value(); } + + EIGEN_DEVICE_FUNC const MatrixTypeNested_& nestedExpression() const { return m_matrix; } + + protected: + MatrixTypeNested m_matrix; + const internal::variable_if_dynamic m_rowFactor; + const internal::variable_if_dynamic m_colFactor; +}; /** - * \return an expression of the replication of \c *this - * - * Example: \include MatrixBase_replicate_int_int.cpp - * Output: \verbinclude MatrixBase_replicate_int_int.out - * - * \sa VectorwiseOp::replicate(), DenseBase::replicate(), class Replicate - */ -template -const typename DenseBase::ReplicateReturnType -DenseBase::replicate(Index rowFactor,Index colFactor) const -{ - return Replicate(derived(),rowFactor,colFactor); + * \return an expression of the replication of \c *this + * + * Example: \include MatrixBase_replicate.cpp + * Output: \verbinclude MatrixBase_replicate.out + * + * \sa VectorwiseOp::replicate(), DenseBase::replicate(Index,Index), class Replicate + */ +template +template +EIGEN_DEVICE_FUNC const Replicate DenseBase::replicate() const { + return Replicate(derived()); } /** - * \return an expression of the replication of each column (or row) of \c *this - * - * Example: \include DirectionWise_replicate_int.cpp - * Output: \verbinclude DirectionWise_replicate_int.out - * - * \sa VectorwiseOp::replicate(), DenseBase::replicate(), class Replicate - */ -template -const typename VectorwiseOp::ReplicateReturnType -VectorwiseOp::replicate(Index factor) const -{ - return typename VectorwiseOp::ReplicateReturnType - (_expression(),Direction==Vertical?factor:1,Direction==Horizontal?factor:1); + * \return an expression of the replication of each column (or row) of \c *this + * + * Example: \include DirectionWise_replicate_int.cpp + * Output: \verbinclude DirectionWise_replicate_int.out + * + * \sa VectorwiseOp::replicate(), DenseBase::replicate(), class Replicate + */ +template +EIGEN_DEVICE_FUNC const typename VectorwiseOp::ReplicateReturnType +VectorwiseOp::replicate(Index factor) const { + return typename VectorwiseOp::ReplicateReturnType( + _expression(), Direction == Vertical ? factor : 1, Direction == Horizontal ? factor : 1); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_REPLICATE_H +#endif // EIGEN_REPLICATE_H diff --git a/inst/include/Eigen/src/Core/Reshaped.h b/inst/include/Eigen/src/Core/Reshaped.h new file mode 100644 index 00000000..22acdc0b --- /dev/null +++ b/inst/include/Eigen/src/Core/Reshaped.h @@ -0,0 +1,398 @@ +// This file is part of Eigen, a lightweight C++ template library +// for linear algebra. +// +// Copyright (C) 2008-2017 Gael Guennebaud +// Copyright (C) 2014 yoco +// +// This Source Code Form is subject to the terms of the Mozilla +// Public License v. 2.0. If a copy of the MPL was not distributed +// with this file, You can obtain one at http://mozilla.org/MPL/2.0/. + +#ifndef EIGEN_RESHAPED_H +#define EIGEN_RESHAPED_H + +// IWYU pragma: private +#include "./InternalHeaderCheck.h" + +namespace Eigen { + +/** \class Reshaped + * \ingroup Core_Module + * + * \brief Expression of a fixed-size or dynamic-size reshape + * + * \tparam XprType the type of the expression in which we are taking a reshape + * \tparam Rows the number of rows of the reshape we are taking at compile time (optional) + * \tparam Cols the number of columns of the reshape we are taking at compile time (optional) + * \tparam Order can be ColMajor or RowMajor, default is ColMajor. + * + * This class represents an expression of either a fixed-size or dynamic-size reshape. + * It is the return type of DenseBase::reshaped(NRowsType,NColsType) and + * most of the time this is the only way it is used. + * + * If you want to directly manipulate reshaped expressions, + * for instance if you want to write a function returning such an expression, + * it is advised to use the \em auto keyword for such use cases. + * + * Here is an example illustrating the dynamic case: + * \include class_Reshaped.cpp + * Output: \verbinclude class_Reshaped.out + * + * Here is an example illustrating the fixed-size case: + * \include class_FixedReshaped.cpp + * Output: \verbinclude class_FixedReshaped.out + * + * \sa DenseBase::reshaped(NRowsType,NColsType) + */ + +namespace internal { + +template +struct traits > : traits { + typedef typename traits::Scalar Scalar; + typedef typename traits::StorageKind StorageKind; + typedef typename traits::XprKind XprKind; + enum { + MatrixRows = traits::RowsAtCompileTime, + MatrixCols = traits::ColsAtCompileTime, + RowsAtCompileTime = Rows, + ColsAtCompileTime = Cols, + MaxRowsAtCompileTime = Rows, + MaxColsAtCompileTime = Cols, + XpxStorageOrder = ((int(traits::Flags) & RowMajorBit) == RowMajorBit) ? RowMajor : ColMajor, + ReshapedStorageOrder = (RowsAtCompileTime == 1 && ColsAtCompileTime != 1) ? RowMajor + : (ColsAtCompileTime == 1 && RowsAtCompileTime != 1) ? ColMajor + : XpxStorageOrder, + HasSameStorageOrderAsXprType = (ReshapedStorageOrder == XpxStorageOrder), + InnerSize = (ReshapedStorageOrder == int(RowMajor)) ? int(ColsAtCompileTime) : int(RowsAtCompileTime), + InnerStrideAtCompileTime = HasSameStorageOrderAsXprType ? int(inner_stride_at_compile_time::ret) : Dynamic, + OuterStrideAtCompileTime = Dynamic, + + HasDirectAccess = internal::has_direct_access::ret && (Order == int(XpxStorageOrder)) && + ((evaluator::Flags & LinearAccessBit) == LinearAccessBit), + + MaskPacketAccessBit = + (InnerSize == Dynamic || (InnerSize % packet_traits::size) == 0) && (InnerStrideAtCompileTime == 1) + ? PacketAccessBit + : 0, + // MaskAlignedBit = ((OuterStrideAtCompileTime!=Dynamic) && (((OuterStrideAtCompileTime * int(sizeof(Scalar))) % 16) + // == 0)) ? AlignedBit : 0, + FlagsLinearAccessBit = (RowsAtCompileTime == 1 || ColsAtCompileTime == 1) ? LinearAccessBit : 0, + FlagsLvalueBit = is_lvalue::value ? LvalueBit : 0, + FlagsRowMajorBit = (ReshapedStorageOrder == int(RowMajor)) ? RowMajorBit : 0, + FlagsDirectAccessBit = HasDirectAccess ? DirectAccessBit : 0, + Flags0 = traits::Flags & ((HereditaryBits & ~RowMajorBit) | MaskPacketAccessBit), + + Flags = (Flags0 | FlagsLinearAccessBit | FlagsLvalueBit | FlagsRowMajorBit | FlagsDirectAccessBit) + }; +}; + +template +class ReshapedImpl_dense; + +} // end namespace internal + +template +class ReshapedImpl; + +template +class Reshaped : public ReshapedImpl::StorageKind> { + typedef ReshapedImpl::StorageKind> Impl; + + public: + // typedef typename Impl::Base Base; + typedef Impl Base; + EIGEN_GENERIC_PUBLIC_INTERFACE(Reshaped) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reshaped) + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC inline Reshaped(XprType& xpr) : Impl(xpr) { + EIGEN_STATIC_ASSERT(RowsAtCompileTime != Dynamic && ColsAtCompileTime != Dynamic, + THIS_METHOD_IS_ONLY_FOR_FIXED_SIZE) + eigen_assert(Rows * Cols == xpr.rows() * xpr.cols()); + } + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC inline Reshaped(XprType& xpr, Index reshapeRows, Index reshapeCols) + : Impl(xpr, reshapeRows, reshapeCols) { + eigen_assert((RowsAtCompileTime == Dynamic || RowsAtCompileTime == reshapeRows) && + (ColsAtCompileTime == Dynamic || ColsAtCompileTime == reshapeCols)); + eigen_assert(reshapeRows * reshapeCols == xpr.rows() * xpr.cols()); + } +}; + +// The generic default implementation for dense reshape simply forward to the internal::ReshapedImpl_dense +// that must be specialized for direct and non-direct access... +template +class ReshapedImpl + : public internal::ReshapedImpl_dense >::HasDirectAccess> { + typedef internal::ReshapedImpl_dense >::HasDirectAccess> + Impl; + + public: + typedef Impl Base; + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ReshapedImpl) + EIGEN_DEVICE_FUNC inline ReshapedImpl(XprType& xpr) : Impl(xpr) {} + EIGEN_DEVICE_FUNC inline ReshapedImpl(XprType& xpr, Index reshapeRows, Index reshapeCols) + : Impl(xpr, reshapeRows, reshapeCols) {} +}; + +namespace internal { + +/** \internal Internal implementation of dense Reshaped in the general case. */ +template +class ReshapedImpl_dense + : public internal::dense_xpr_base >::type { + typedef Reshaped ReshapedType; + + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(ReshapedType) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ReshapedImpl_dense) + + typedef typename internal::ref_selector::non_const_type MatrixTypeNested; + typedef internal::remove_all_t NestedExpression; + + class InnerIterator; + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC inline ReshapedImpl_dense(XprType& xpr) : m_xpr(xpr), m_rows(Rows), m_cols(Cols) {} + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC inline ReshapedImpl_dense(XprType& xpr, Index nRows, Index nCols) + : m_xpr(xpr), m_rows(nRows), m_cols(nCols) {} + + EIGEN_DEVICE_FUNC Index rows() const { return m_rows; } + EIGEN_DEVICE_FUNC Index cols() const { return m_cols; } + +#ifdef EIGEN_PARSED_BY_DOXYGEN + /** \sa MapBase::data() */ + EIGEN_DEVICE_FUNC constexpr const Scalar* data() const; + EIGEN_DEVICE_FUNC inline Index innerStride() const; + EIGEN_DEVICE_FUNC inline Index outerStride() const; +#endif + + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { return m_xpr; } + + /** \returns the nested expression */ + EIGEN_DEVICE_FUNC std::remove_reference_t& nestedExpression() { return m_xpr; } + + protected: + MatrixTypeNested m_xpr; + const internal::variable_if_dynamic m_rows; + const internal::variable_if_dynamic m_cols; +}; + +/** \internal Internal implementation of dense Reshaped in the direct access case. */ +template +class ReshapedImpl_dense : public MapBase > { + typedef Reshaped ReshapedType; + typedef typename internal::ref_selector::non_const_type XprTypeNested; + + public: + typedef MapBase Base; + EIGEN_DENSE_PUBLIC_INTERFACE(ReshapedType) + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(ReshapedImpl_dense) + + /** Fixed-size constructor + */ + EIGEN_DEVICE_FUNC inline ReshapedImpl_dense(XprType& xpr) : Base(xpr.data()), m_xpr(xpr) {} + + /** Dynamic-size constructor + */ + EIGEN_DEVICE_FUNC inline ReshapedImpl_dense(XprType& xpr, Index nRows, Index nCols) + : Base(xpr.data(), nRows, nCols), m_xpr(xpr) {} + + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { return m_xpr; } + + EIGEN_DEVICE_FUNC XprType& nestedExpression() { return m_xpr; } + + /** \sa MapBase::innerStride() */ + EIGEN_DEVICE_FUNC constexpr Index innerStride() const { return m_xpr.innerStride(); } + + /** \sa MapBase::outerStride() */ + EIGEN_DEVICE_FUNC constexpr Index outerStride() const { + return (((Flags & RowMajorBit) == RowMajorBit) ? this->cols() : this->rows()) * m_xpr.innerStride(); + } + + protected: + XprTypeNested m_xpr; +}; + +// Evaluators +template +struct reshaped_evaluator; + +template +struct evaluator > + : reshaped_evaluator >::HasDirectAccess> { + typedef Reshaped XprType; + typedef typename XprType::Scalar Scalar; + // TODO: should check for smaller packet types + typedef typename packet_traits::type PacketScalar; + + enum { + CoeffReadCost = evaluator::CoeffReadCost, + HasDirectAccess = traits::HasDirectAccess, + + // RowsAtCompileTime = traits::RowsAtCompileTime, + // ColsAtCompileTime = traits::ColsAtCompileTime, + // MaxRowsAtCompileTime = traits::MaxRowsAtCompileTime, + // MaxColsAtCompileTime = traits::MaxColsAtCompileTime, + // + // InnerStrideAtCompileTime = traits::HasSameStorageOrderAsXprType + // ? int(inner_stride_at_compile_time::ret) + // : Dynamic, + // OuterStrideAtCompileTime = Dynamic, + + FlagsLinearAccessBit = + (traits::RowsAtCompileTime == 1 || traits::ColsAtCompileTime == 1 || HasDirectAccess) + ? LinearAccessBit + : 0, + FlagsRowMajorBit = (traits::ReshapedStorageOrder == int(RowMajor)) ? RowMajorBit : 0, + FlagsDirectAccessBit = HasDirectAccess ? DirectAccessBit : 0, + Flags0 = evaluator::Flags & (HereditaryBits & ~RowMajorBit), + Flags = Flags0 | FlagsLinearAccessBit | FlagsRowMajorBit | FlagsDirectAccessBit, + + PacketAlignment = unpacket_traits::alignment, + Alignment = evaluator::Alignment + }; + typedef reshaped_evaluator reshaped_evaluator_type; + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : reshaped_evaluator_type(xpr) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } +}; + +template +struct reshaped_evaluator + : evaluator_base > { + typedef Reshaped XprType; + + enum { + CoeffReadCost = evaluator::CoeffReadCost /* TODO + cost of index computations */, + + Flags = (evaluator::Flags & (HereditaryBits /*| LinearAccessBit | DirectAccessBit*/)), + + Alignment = 0 + }; + + EIGEN_DEVICE_FUNC explicit reshaped_evaluator(const XprType& xpr) : m_argImpl(xpr.nestedExpression()), m_xpr(xpr) { + EIGEN_INTERNAL_CHECK_COST_VALUE(CoeffReadCost); + } + + typedef typename XprType::Scalar Scalar; + typedef typename XprType::CoeffReturnType CoeffReturnType; + + typedef std::pair RowCol; + + EIGEN_DEVICE_FUNC inline RowCol index_remap(Index rowId, Index colId) const { + if (Order == ColMajor) { + const Index nth_elem_idx = colId * m_xpr.rows() + rowId; + return RowCol(nth_elem_idx % m_xpr.nestedExpression().rows(), nth_elem_idx / m_xpr.nestedExpression().rows()); + } else { + const Index nth_elem_idx = colId + rowId * m_xpr.cols(); + return RowCol(nth_elem_idx / m_xpr.nestedExpression().cols(), nth_elem_idx % m_xpr.nestedExpression().cols()); + } + } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index rowId, Index colId) { + EIGEN_STATIC_ASSERT_LVALUE(XprType) + const RowCol row_col = index_remap(rowId, colId); + return m_argImpl.coeffRef(row_col.first, row_col.second); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index rowId, Index colId) const { + const RowCol row_col = index_remap(rowId, colId); + return m_argImpl.coeffRef(row_col.first, row_col.second); + } + + EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE const CoeffReturnType coeff(Index rowId, Index colId) const { + const RowCol row_col = index_remap(rowId, colId); + return m_argImpl.coeff(row_col.first, row_col.second); + } + + EIGEN_DEVICE_FUNC inline Scalar& coeffRef(Index index) { + EIGEN_STATIC_ASSERT_LVALUE(XprType) + const RowCol row_col = index_remap(Rows == 1 ? 0 : index, Rows == 1 ? index : 0); + return m_argImpl.coeffRef(row_col.first, row_col.second); + } + + EIGEN_DEVICE_FUNC inline const Scalar& coeffRef(Index index) const { + const RowCol row_col = index_remap(Rows == 1 ? 0 : index, Rows == 1 ? index : 0); + return m_argImpl.coeffRef(row_col.first, row_col.second); + } + + EIGEN_DEVICE_FUNC inline const CoeffReturnType coeff(Index index) const { + const RowCol row_col = index_remap(Rows == 1 ? 0 : index, Rows == 1 ? index : 0); + return m_argImpl.coeff(row_col.first, row_col.second); + } +#if 0 + EIGEN_DEVICE_FUNC + template + inline PacketScalar packet(Index rowId, Index colId) const + { + const RowCol row_col = index_remap(rowId, colId); + return m_argImpl.template packet(row_col.first, row_col.second); + + } + + template + EIGEN_DEVICE_FUNC + inline void writePacket(Index rowId, Index colId, const PacketScalar& val) + { + const RowCol row_col = index_remap(rowId, colId); + m_argImpl.const_cast_derived().template writePacket + (row_col.first, row_col.second, val); + } + + template + EIGEN_DEVICE_FUNC + inline PacketScalar packet(Index index) const + { + const RowCol row_col = index_remap(RowsAtCompileTime == 1 ? 0 : index, + RowsAtCompileTime == 1 ? index : 0); + return m_argImpl.template packet(row_col.first, row_col.second); + } + + template + EIGEN_DEVICE_FUNC + inline void writePacket(Index index, const PacketScalar& val) + { + const RowCol row_col = index_remap(RowsAtCompileTime == 1 ? 0 : index, + RowsAtCompileTime == 1 ? index : 0); + return m_argImpl.template packet(row_col.first, row_col.second, val); + } +#endif + protected: + evaluator m_argImpl; + const XprType& m_xpr; +}; + +template +struct reshaped_evaluator + : mapbase_evaluator, + typename Reshaped::PlainObject> { + typedef Reshaped XprType; + typedef typename XprType::Scalar Scalar; + + EIGEN_DEVICE_FUNC explicit reshaped_evaluator(const XprType& xpr) + : mapbase_evaluator(xpr) { + // TODO: for the 3.4 release, this should be turned to an internal assertion, but let's keep it as is for the beta + // lifetime + eigen_assert(((std::uintptr_t(xpr.data()) % plain_enum_max(1, evaluator::Alignment)) == 0) && + "data is not aligned"); + } +}; + +} // end namespace internal + +} // end namespace Eigen + +#endif // EIGEN_RESHAPED_H diff --git a/inst/include/Eigen/src/Core/ReturnByValue.h b/inst/include/Eigen/src/Core/ReturnByValue.h index f635598d..892c193b 100644 --- a/inst/include/Eigen/src/Core/ReturnByValue.h +++ b/inst/include/Eigen/src/Core/ReturnByValue.h @@ -11,25 +11,20 @@ #ifndef EIGEN_RETURNBYVALUE_H #define EIGEN_RETURNBYVALUE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class ReturnByValue - * \ingroup Core_Module - * - */ +namespace Eigen { namespace internal { -template -struct traits > - : public traits::ReturnType> -{ +template +struct traits > : public traits::ReturnType> { enum { // We're disabling the DirectAccess because e.g. the constructor of // the Block-with-DirectAccess expression requires to have a coeffRef method. // Also, we don't want to have to implement the stride stuff. - Flags = (traits::ReturnType>::Flags - | EvalBeforeNestingBit) & ~DirectAccessBit + Flags = (traits::ReturnType>::Flags | EvalBeforeNestingBit) & ~DirectAccessBit }; }; @@ -38,62 +33,79 @@ struct traits > * So internal::nested always gives the plain return matrix type. * * FIXME: I don't understand why we need this specialization: isn't this taken care of by the EvalBeforeNestingBit ?? + * Answer: EvalBeforeNestingBit should be deprecated since we have the evaluators */ -template -struct nested, n, PlainObject> -{ +template +struct nested_eval, n, PlainObject> { typedef typename traits::ReturnType type; }; -} // end namespace internal +} // end namespace internal -template class ReturnByValue - : internal::no_assignment_operator, public internal::dense_xpr_base< ReturnByValue >::type -{ - public: - typedef typename internal::traits::ReturnType ReturnType; +/** \class ReturnByValue + * \ingroup Core_Module + * + */ +template +class ReturnByValue : public internal::dense_xpr_base >::type, internal::no_assignment_operator { + public: + typedef typename internal::traits::ReturnType ReturnType; - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue) + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(ReturnByValue) - template - inline void evalTo(Dest& dst) const - { static_cast(this)->evalTo(dst); } - inline Index rows() const { return static_cast(this)->rows(); } - inline Index cols() const { return static_cast(this)->cols(); } + template + EIGEN_DEVICE_FUNC inline void evalTo(Dest& dst) const { + static_cast(this)->evalTo(dst); + } + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return static_cast(this)->rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return static_cast(this)->cols(); } #ifndef EIGEN_PARSED_BY_DOXYGEN -#define Unusable YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT - class Unusable{ - Unusable(const Unusable&) {} - Unusable& operator=(const Unusable&) {return *this;} - }; - const Unusable& coeff(Index) const { return *reinterpret_cast(this); } - const Unusable& coeff(Index,Index) const { return *reinterpret_cast(this); } - Unusable& coeffRef(Index) { return *reinterpret_cast(this); } - Unusable& coeffRef(Index,Index) { return *reinterpret_cast(this); } - template Unusable& packet(Index) const; - template Unusable& packet(Index, Index) const; +#define Unusable \ + YOU_ARE_TRYING_TO_ACCESS_A_SINGLE_COEFFICIENT_IN_A_SPECIAL_EXPRESSION_WHERE_THAT_IS_NOT_ALLOWED_BECAUSE_THAT_WOULD_BE_INEFFICIENT + class Unusable { + Unusable(const Unusable&) {} + Unusable& operator=(const Unusable&) { return *this; } + }; + const Unusable& coeff(Index) const { return *reinterpret_cast(this); } + const Unusable& coeff(Index, Index) const { return *reinterpret_cast(this); } + Unusable& coeffRef(Index) { return *reinterpret_cast(this); } + Unusable& coeffRef(Index, Index) { return *reinterpret_cast(this); } +#undef Unusable #endif }; -template -template -Derived& DenseBase::operator=(const ReturnByValue& other) -{ +template +template +EIGEN_DEVICE_FUNC Derived& DenseBase::operator=(const ReturnByValue& other) { other.evalTo(derived()); return derived(); } -template -template -Derived& DenseBase::lazyAssign(const ReturnByValue& other) -{ - other.evalTo(derived()); - return derived(); -} +namespace internal { + +// Expression is evaluated in a temporary; default implementation of Assignment is bypassed so that +// when a ReturnByValue expression is assigned, the evaluator is not constructed. +// TODO: Finalize port to new regime; ReturnByValue should not exist in the expression world + +template +struct evaluator > : public evaluator::ReturnType> { + typedef ReturnByValue XprType; + typedef typename internal::traits::ReturnType PlainObject; + typedef evaluator Base; + + EIGEN_DEVICE_FUNC explicit evaluator(const XprType& xpr) : m_result(xpr.rows(), xpr.cols()) { + internal::construct_at(this, m_result); + xpr.evalTo(m_result); + } + + protected: + PlainObject m_result; +}; +} // end namespace internal -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_RETURNBYVALUE_H +#endif // EIGEN_RETURNBYVALUE_H diff --git a/inst/include/Eigen/src/Core/Reverse.h b/inst/include/Eigen/src/Core/Reverse.h index e30ae3d2..d11ba167 100644 --- a/inst/include/Eigen/src/Core/Reverse.h +++ b/inst/include/Eigen/src/Core/Reverse.h @@ -12,213 +12,191 @@ #ifndef EIGEN_REVERSE_H #define EIGEN_REVERSE_H -namespace Eigen { +// IWYU pragma: private +#include "./InternalHeaderCheck.h" -/** \class Reverse - * \ingroup Core_Module - * - * \brief Expression of the reverse of a vector or matrix - * - * \param MatrixType the type of the object of which we are taking the reverse - * - * This class represents an expression of the reverse of a vector. - * It is the return type of MatrixBase::reverse() and VectorwiseOp::reverse() - * and most of the time this is the only way it is used. - * - * \sa MatrixBase::reverse(), VectorwiseOp::reverse() - */ +namespace Eigen { namespace internal { -template -struct traits > - : traits -{ +template +struct traits > : traits { typedef typename MatrixType::Scalar Scalar; typedef typename traits::StorageKind StorageKind; typedef typename traits::XprKind XprKind; - typedef typename nested::type MatrixTypeNested; - typedef typename remove_reference::type _MatrixTypeNested; + typedef typename ref_selector::type MatrixTypeNested; + typedef std::remove_reference_t MatrixTypeNested_; enum { RowsAtCompileTime = MatrixType::RowsAtCompileTime, ColsAtCompileTime = MatrixType::ColsAtCompileTime, MaxRowsAtCompileTime = MatrixType::MaxRowsAtCompileTime, MaxColsAtCompileTime = MatrixType::MaxColsAtCompileTime, - - // let's enable LinearAccess only with vectorization because of the product overhead - LinearAccess = ( (Direction==BothDirections) && (int(_MatrixTypeNested::Flags)&PacketAccessBit) ) - ? LinearAccessBit : 0, - - Flags = int(_MatrixTypeNested::Flags) & (HereditaryBits | LvalueBit | PacketAccessBit | LinearAccess), - - CoeffReadCost = _MatrixTypeNested::CoeffReadCost + Flags = MatrixTypeNested_::Flags & (RowMajorBit | LvalueBit) }; }; -template struct reverse_packet_cond -{ - static inline PacketScalar run(const PacketScalar& x) { return preverse(x); } +template +struct reverse_packet_cond { + static inline PacketType run(const PacketType& x) { return preverse(x); } }; -template struct reverse_packet_cond -{ - static inline PacketScalar run(const PacketScalar& x) { return x; } +template +struct reverse_packet_cond { + static inline PacketType run(const PacketType& x) { return x; } }; -} // end namespace internal - -template class Reverse - : public internal::dense_xpr_base< Reverse >::type -{ - public: - - typedef typename internal::dense_xpr_base::type Base; - EIGEN_DENSE_PUBLIC_INTERFACE(Reverse) - using Base::IsRowMajor; - - // next line is necessary because otherwise const version of operator() - // is hidden by non-const version defined in this file - using Base::operator(); - - protected: - enum { - PacketSize = internal::packet_traits::size, - IsColMajor = !IsRowMajor, - ReverseRow = (Direction == Vertical) || (Direction == BothDirections), - ReverseCol = (Direction == Horizontal) || (Direction == BothDirections), - OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1, - OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1, - ReversePacket = (Direction == BothDirections) - || ((Direction == Vertical) && IsColMajor) - || ((Direction == Horizontal) && IsRowMajor) - }; - typedef internal::reverse_packet_cond reverse_packet; - public: - - inline Reverse(const MatrixType& matrix) : m_matrix(matrix) { } - - EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse) - - inline Index rows() const { return m_matrix.rows(); } - inline Index cols() const { return m_matrix.cols(); } - - inline Index innerStride() const - { - return -m_matrix.innerStride(); - } +} // end namespace internal - inline Scalar& operator()(Index row, Index col) - { - eigen_assert(row >= 0 && row < rows() && col >= 0 && col < cols()); - return coeffRef(row, col); - } +/** \class Reverse + * \ingroup Core_Module + * + * \brief Expression of the reverse of a vector or matrix + * + * \tparam MatrixType the type of the object of which we are taking the reverse + * \tparam Direction defines the direction of the reverse operation, can be Vertical, Horizontal, or BothDirections + * + * This class represents an expression of the reverse of a vector. + * It is the return type of MatrixBase::reverse() and VectorwiseOp::reverse() + * and most of the time this is the only way it is used. + * + * \sa MatrixBase::reverse(), VectorwiseOp::reverse() + */ +template +class Reverse : public internal::dense_xpr_base >::type { + public: + typedef typename internal::dense_xpr_base::type Base; + EIGEN_DENSE_PUBLIC_INTERFACE(Reverse) + typedef internal::remove_all_t NestedExpression; + using Base::IsRowMajor; + + protected: + enum { + PacketSize = internal::packet_traits::size, + IsColMajor = !IsRowMajor, + ReverseRow = (Direction == Vertical) || (Direction == BothDirections), + ReverseCol = (Direction == Horizontal) || (Direction == BothDirections), + OffsetRow = ReverseRow && IsColMajor ? PacketSize : 1, + OffsetCol = ReverseCol && IsRowMajor ? PacketSize : 1, + ReversePacket = (Direction == BothDirections) || ((Direction == Vertical) && IsColMajor) || + ((Direction == Horizontal) && IsRowMajor) + }; + typedef internal::reverse_packet_cond reverse_packet; - inline Scalar& coeffRef(Index row, Index col) - { - return m_matrix.const_cast_derived().coeffRef(ReverseRow ? m_matrix.rows() - row - 1 : row, - ReverseCol ? m_matrix.cols() - col - 1 : col); - } + public: + EIGEN_DEVICE_FUNC explicit inline Reverse(const MatrixType& matrix) : m_matrix(matrix) {} - inline CoeffReturnType coeff(Index row, Index col) const - { - return m_matrix.coeff(ReverseRow ? m_matrix.rows() - row - 1 : row, - ReverseCol ? m_matrix.cols() - col - 1 : col); - } + EIGEN_INHERIT_ASSIGNMENT_OPERATORS(Reverse) - inline CoeffReturnType coeff(Index index) const - { - return m_matrix.coeff(m_matrix.size() - index - 1); - } + EIGEN_DEVICE_FUNC constexpr Index rows() const noexcept { return m_matrix.rows(); } + EIGEN_DEVICE_FUNC constexpr Index cols() const noexcept { return m_matrix.cols(); } - inline Scalar& coeffRef(Index index) - { - return m_matrix.const_cast_derived().coeffRef(m_matrix.size() - index - 1); - } + EIGEN_DEVICE_FUNC inline Index innerStride() const { return -m_matrix.innerStride(); } - inline Scalar& operator()(Index index) - { - eigen_assert(index >= 0 && index < m_matrix.size()); - return coeffRef(index); - } + EIGEN_DEVICE_FUNC const internal::remove_all_t& nestedExpression() const { + return m_matrix; + } - template - inline const PacketScalar packet(Index row, Index col) const - { - return reverse_packet::run(m_matrix.template packet( - ReverseRow ? m_matrix.rows() - row - OffsetRow : row, - ReverseCol ? m_matrix.cols() - col - OffsetCol : col)); - } + protected: + typename MatrixType::Nested m_matrix; +}; - template - inline void writePacket(Index row, Index col, const PacketScalar& x) - { - m_matrix.const_cast_derived().template writePacket( - ReverseRow ? m_matrix.rows() - row - OffsetRow : row, - ReverseCol ? m_matrix.cols() - col - OffsetCol : col, - reverse_packet::run(x)); - } +/** \returns an expression of the reverse of *this. + * + * Example: \include MatrixBase_reverse.cpp + * Output: \verbinclude MatrixBase_reverse.out + * + */ +template +EIGEN_DEVICE_FUNC inline typename DenseBase::ReverseReturnType DenseBase::reverse() { + return ReverseReturnType(derived()); +} - template - inline const PacketScalar packet(Index index) const - { - return internal::preverse(m_matrix.template packet( m_matrix.size() - index - PacketSize )); - } +// reverse const overload moved DenseBase.h due to a CUDA compiler bug - template - inline void writePacket(Index index, const PacketScalar& x) - { - m_matrix.const_cast_derived().template writePacket(m_matrix.size() - index - PacketSize, internal::preverse(x)); +/** This is the "in place" version of reverse: it reverses \c *this. + * + * In most cases it is probably better to simply use the reversed expression + * of a matrix. However, when reversing the matrix data itself is really needed, + * then this "in-place" version is probably the right choice because it provides + * the following additional benefits: + * - less error prone: doing the same operation with .reverse() requires special care: + * \code m = m.reverse().eval(); \endcode + * - this API enables reverse operations without the need for a temporary + * - it allows future optimizations (cache friendliness, etc.) + * + * \sa VectorwiseOp::reverseInPlace(), reverse() */ +template +EIGEN_DEVICE_FUNC inline void DenseBase::reverseInPlace() { + constexpr int HalfRowsAtCompileTime = RowsAtCompileTime == Dynamic ? Dynamic : RowsAtCompileTime / 2; + constexpr int HalfColsAtCompileTime = ColsAtCompileTime == Dynamic ? Dynamic : ColsAtCompileTime / 2; + if (cols() > rows()) { + Index half = cols() / 2; + this->template leftCols(half).swap( + this->template rightCols(half).reverse()); + if ((cols() % 2) == 1) { + Index half2 = rows() / 2; + col(half).template head(half2).swap( + col(half).template tail(half2).reverse()); } - - const typename internal::remove_all::type& - nestedExpression() const - { - return m_matrix; + } else { + Index half = rows() / 2; + this->template topRows(half).swap( + this->template bottomRows(half).reverse()); + if ((rows() % 2) == 1) { + Index half2 = cols() / 2; + row(half).template head(half2).swap( + row(half).template tail(half2).reverse()); } + } +} - protected: - typename MatrixType::Nested m_matrix; -}; +namespace internal { -/** \returns an expression of the reverse of *this. - * - * Example: \include MatrixBase_reverse.cpp - * Output: \verbinclude MatrixBase_reverse.out - * - */ -template -inline typename DenseBase::ReverseReturnType -DenseBase::reverse() -{ - return derived(); -} +template +struct vectorwise_reverse_inplace_impl; + +template <> +struct vectorwise_reverse_inplace_impl { + template + static void run(ExpressionType& xpr) { + constexpr Index HalfAtCompileTime = + ExpressionType::RowsAtCompileTime == Dynamic ? Dynamic : ExpressionType::RowsAtCompileTime / 2; + Index half = xpr.rows() / 2; + xpr.template topRows(half).swap( + xpr.template bottomRows(half).colwise().reverse()); + } +}; -/** This is the const version of reverse(). */ -template -inline const typename DenseBase::ConstReverseReturnType -DenseBase::reverse() const -{ - return derived(); -} +template <> +struct vectorwise_reverse_inplace_impl { + template + static void run(ExpressionType& xpr) { + constexpr Index HalfAtCompileTime = + ExpressionType::ColsAtCompileTime == Dynamic ? Dynamic : ExpressionType::ColsAtCompileTime / 2; + Index half = xpr.cols() / 2; + xpr.template leftCols(half).swap( + xpr.template rightCols(half).rowwise().reverse()); + } +}; -/** This is the "in place" version of reverse: it reverses \c *this. - * - * In most cases it is probably better to simply use the reversed expression - * of a matrix. However, when reversing the matrix data itself is really needed, - * then this "in-place" version is probably the right choice because it provides - * the following additional features: - * - less error prone: doing the same operation with .reverse() requires special care: - * \code m = m.reverse().eval(); \endcode - * - this API allows to avoid creating a temporary (the current implementation creates a temporary, but that could be avoided using swap) - * - it allows future optimizations (cache friendliness, etc.) - * - * \sa reverse() */ -template -inline void DenseBase::reverseInPlace() -{ - derived() = derived().reverse().eval(); +} // end namespace internal + +/** This is the "in place" version of VectorwiseOp::reverse: it reverses each column or row of \c *this. + * + * In most cases it is probably better to simply use the reversed expression + * of a matrix. However, when reversing the matrix data itself is really needed, + * then this "in-place" version is probably the right choice because it provides + * the following additional benefits: + * - less error prone: doing the same operation with .reverse() requires special care: + * \code m = m.reverse().eval(); \endcode + * - this API enables reverse operations without the need for a temporary + * + * \sa DenseBase::reverseInPlace(), reverse() */ +template +EIGEN_DEVICE_FUNC void VectorwiseOp::reverseInPlace() { + internal::vectorwise_reverse_inplace_impl::run(m_matrix); } -} // end namespace Eigen +} // end namespace Eigen -#endif // EIGEN_REVERSE_H +#endif // EIGEN_REVERSE_H diff --git a/inst/include/Eigen/src/Core/Select.h b/inst/include/Eigen/src/Core/Select.h index 87993bbb..61a67c2f 100644 --- a/inst/include/Eigen/src/Core/Select.h +++ b/inst/include/Eigen/src/Core/Select.h @@ -10,153 +10,83 @@ #ifndef EIGEN_SELECT_H #define EIGEN_SELECT_H -namespace Eigen { - -/** \class Select - * \ingroup Core_Module - * - * \brief Expression of a coefficient wise version of the C++ ternary operator ?: - * - * \param ConditionMatrixType the type of the \em condition expression which must be a boolean matrix - * \param ThenMatrixType the type of the \em then expression - * \param ElseMatrixType the type of the \em else expression - * - * This class represents an expression of a coefficient wise version of the C++ ternary operator ?:. - * It is the return type of DenseBase::select() and most of the time this is the only way it is used. - * - * \sa DenseBase::select(const DenseBase&, const DenseBase&) const - */ - -namespace internal { -template -struct traits > - : traits -{ - typedef typename traits::Scalar Scalar; - typedef Dense StorageKind; - typedef typename traits::XprKind XprKind; - typedef typename ConditionMatrixType::Nested ConditionMatrixNested; - typedef typename ThenMatrixType::Nested ThenMatrixNested; - typedef typename ElseMatrixType::Nested ElseMatrixNested; - enum { - RowsAtCompileTime = ConditionMatrixType::RowsAtCompileTime, - ColsAtCompileTime = ConditionMatrixType::ColsAtCompileTime, - MaxRowsAtCompileTime = ConditionMatrixType::MaxRowsAtCompileTime, - MaxColsAtCompileTime = ConditionMatrixType::MaxColsAtCompileTime, - Flags = (unsigned int)ThenMatrixType::Flags & ElseMatrixType::Flags & HereditaryBits, - CoeffReadCost = traits::type>::CoeffReadCost - + EIGEN_SIZE_MAX(traits::type>::CoeffReadCost, - traits::type>::CoeffReadCost) - }; -}; -} - -template -class Select : internal::no_assignment_operator, - public internal::dense_xpr_base< Select >::type -{ - public: - - typedef typename internal::dense_xpr_base