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Update napoleon type aliases and specifiers
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‎.travis.yml‎

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before_install:
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- |
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MODIFIED_FILES=$(git diff --name-only "$TRAVIS_COMMIT_RANGE" 2>/dev/null)
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if [ $? -eq 0 ]; then
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if ! echo "$MODIFIED_FILES" | grep -qvE '(.md)|(.rst)|(.html)'
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if [ $? -eq 0 ] && ! echo "$MODIFIED_FILES" | grep -qvE '(.md)|(.rst)|(.html)'
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then
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echo "Only doc files were updated, not running the CI."
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exit
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fi
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echo "Only doc files were updated, not running the CI."
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exit
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fi
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- wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh
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- bash miniconda.sh -b -p $HOME/miniconda

‎WHATSNEW.rst‎

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* Fix issue where `~proplot.styletools.show_cmaps` and `~proplot.styletools.show_cycles`
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draw empty axes (:pr:`100`).
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* Add back the :ref:`default .proplorc file <The .proplotrc file>` to docs (:pr:`101`).
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* Add back the default .proplorc file section to docs (:pr:`101`).
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To do this, ``conf.py`` auto-generates a file in ``_static``.
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Internals

‎docs/1dplots.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---

‎docs/2dplots.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---

‎docs/api.rst‎

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.. automodsumm:: proplot.figure
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:toctree: api
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:skip: SubplotsContainer
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Gridspec class
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.. automodsumm:: proplot.gridspec
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:toctree: api
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:skip: SubplotsContainer
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Axes classes

‎docs/basics.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---

‎docs/cartesian.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---
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pplt.rc.reset()
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# %% [raw] raw_mimetype="text/restructuredtext"
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# .. _pandas: https://pandas.pydata.org
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#
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# .. _ug_datetime:
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#
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# Datetime axes

‎docs/colorbars_legends.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---
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# them from the `~matplotlib.artist.Artist` labels (non-numeric labels will be
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# applied to the colorbar as tick labels). This feature is useful for labeling
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# discrete plot elements that bear some numeric relationship to each other.
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#
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# Similar to `proplot.axes.CartesianAxes.format`, you can flexibly specify
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# major tick locations, minor tick locations, and major tick labels using the
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# `locator`, `minorlocator`, `formatter`, `ticks`, `minorticks`, and `ticklabels`
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# If you pass legend artists that are grouped into tuples (see this `matplotlib guide
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# <https://matplotlib.org/stable/tutorials/intermediate/legend_guide.html#legend-handlers>`__),
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# the default label will be inferred from the artists in the tuple.
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#
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# You can also draw legends with centered rows by passing ``center=True`` or by passing
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# a list of lists of plot handles to ``legend``. This is accomplished by stacking
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# multiple single-row, horizontally centered legends, then adding an encompassing

‎docs/colormaps.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---
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# :ref:`subclassed from <ug_cmaps_new>`
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# `matplotlib.colors.LinearSegmentedColormap`.
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#
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# ProPlot :ref:`adds several features <why_colormaps_cyles>` to help you use
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# ProPlot :ref:`adds several features <why_colormaps_cycles>` to help you use
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# colormaps effectively in your figures. This section documents the new registered
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# colormaps, explains how to make and modify colormaps, and shows how to apply them
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# to your plots.

‎docs/colors.py‎

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# extension: .py
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# format_name: percent
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# format_version: '1.3'
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# jupytext_version: 1.4.2
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# jupytext_version: 1.11.4
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# kernelspec:
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# display_name: Python 3 (ipykernel)
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# display_name: Python 3
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# language: python
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# name: python3
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# ---

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