A C++ header-only plotting library based on pybind11 and matplotlib
This project aims to replace matplotlibcpp using pybind11 as backend.
It is supposed to provide the user with almost full access to matplotlib features in C++, by implementing as many wrapper classes of matplotlib module as possible (like axes::Axes, figure::Figure). And its primary advantage over conventional matplotlibcpp is that the user can pass a variety of arguments as in the form of args and kwargs thanks to pybind11, without the need for coversion to map<string, string>, thus leading to more flexibility.
- pybind11 >= 2.4.3
sudo apt install pybind11-dev(on Ubuntu20.04)- or manual install
- matplotlib >= 3.4.0
- numpy for
mplot3d - (xtensor == 0.24.0 + xtl, only for
gallerydemos)
$ mdkir build; cd build;
$ cmake .. -DADD_DEMO=0 (-DCMAKE_INSTALL_PREFIX=<custom path>)
$ make -j
$ make install
$ (make uninstall)For using matplotlibcpp17 from CMakeLists.txt, see hello_world example.
find_package(matplotlibcpp17)
...
target_link_libraries(a.out matplotlibcpp17::matplotlibcpp17)Or you could just add include path to include directory and compile your codes as descibed in minimal example.
The user will need to capsulate arguments in Args(arg1, arg2, ...) == pybind11:tuple and keyword arguments in Kwargs("k1"_a = v1, "k2"_a = v2, ...) == pybind11::dict. The returned value is either a pybind11::object or a corresponding wrapper class. Please refer to the reference and examples below.
- exception:
subplots,TBDs - conversion: Wrapper class of matplotlibcpp17 like ::container::BarContainer needs to be passed to python interpreter using
unwrap()method in args and kwargs.
g++ ./hello_world/hello_world.cpp -std=c++17 -I./include -I/usr/include/python3.x -I<path to pybind11> -lpython3.x
./a.outgives
From gallery/subplots_axes_and_figures/align_labels_demo.cpp.
auto plt = matplotlibcpp17::pyplot::import();
// corresponding wrapper class for returned value is implemented in this library
/// gs is of type gridspec::GridSpec
auto gs = GridSpec(2, 2);
/// pass wrapper class object like gs[0, :] of ::gridspec::SubplotSpec to the interpreter using .unwrap() method as python object
auto ax = fig.add_subplot(Args(gs(0, py::slice(0, 2, 1)).unwrap()));
ax.plot(Args(arange(0, 1000000, 10000)));
ax.set_ylabel(Args("YLabel0"));
ax.set_xlabel(Args("XLabel0"));
From gallery/lines_bars_and_markers/bar_label_demo.cpp. Here subplots() returns tuple<Figure, Axes>.
auto [fig, ax] = plt.subplots();
auto p1 = ax.bar(Args(ind, menMeans, width),
Kwargs("yerr"_a = menStd, "label"_a = "Men"));
auto p2 = ax.bar(
Args(ind, womenMeans, width),
Kwargs("bottom"_a = menMeans, "yerr"_a = womenStd, "label"_a = "Women"));
ax.axhline(Args(0), Kwargs("color"_a = "grey", "linewidth"_a = 0.8));
ax.set_ylabel(Args("Scores"));
ax.set_title(Args("Scores by group and gender"));
ax.set_xticks(Args(ind, py::make_tuple("G1", "G2", "G3", "G4", "G5")));
ax.legend();
// pass wrapper class object like p1 of ::container::BarContainer to the interpreter using .unwrap() method as python object
ax.bar_label(Args(p1.unwrap()), Kwargs("label_type"_a = "center"));
ax.bar_label(Args(p2.unwrap()), Kwargs("label_type"_a = "center"));
ax.bar_label(Args(p2.unwrap()));
plt.show();
Fucntions like subplots, TBDs are overloaded because they return different types depending on the arguments. Here subplots() returns tuple<Figure, vector<Axes>>.
From gallery/lines_bars_and_markers
auto [fig, axes] =
plt.subplots(1, 3,
Kwargs("figsize"_a = py::make_tuple(9, 3),
"subplot_kw"_a = py::dict("aspect"_a = "equal")));
auto ax1 = axes[0], ax2 = axes[1], ax3 = axes[2];
Use .unwrap() method to pass wrapper class of matplotlibcpp17 to plotting functions.
From gallery/images_contours_and_fields/quiver_demo.cpp
auto plt = matplotlibcpp17::pyplot::import();
auto [fig1, ax1] = plt.subplots();
ax1.set_title(Args("Arrows scale with plot width, not view"));
auto Q = ax1.quiver(Args(X, Y, U, V, M),
Kwargs("units"_a = "x", "pivot"_a = "tip",
"width"_a = 0.022, "scale"_a = 1.0 / 0.15));
auto qk =
ax1.quiverkey(Args(Q.unwrap(), 0.9, 0.9, 1, R"($1 \frac{m}{s}$)"),
Kwargs("labelpos"_a = "E", "coordinates"_a = "figure"));
ax1.scatter(Args(X, Y), Kwargs("color"_a = "0.5", "s"_a = 1));
Currently only ArtistAnimation is supported. FuncAnimation interface maybe implemented in the future.
From gallery/artist_animation/random_walk.cpp
gallery folder contains corresponding examples from the official website of matplotlib with the same structure.
If you do not need to build the demos, use -DADD_DEMO=0 (by default it is 1).
$ mkdir build; cd build
$ cmake .. -DADD_DEMO={0, 1} -DUSE_GUI={0, 1}
$ make -jIf you do not need to see the demo with plt.show(), use -DUSE_GUI=0 (by default it is 1). Otherwise the executables will plt.savefig() to gallery/images directory.
make <gallery directory name> runs all the executables under that directory.
make lines_bars_and_markersContributions to this project are welcome if you could add or want/need more modules :)