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Commit 21ebc3a

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jkseppanjkseppan
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Merge branch 'pdf-improve' into pdf-gouraud-alpha
Follow the PEP8 naming convention in the new members.
2 parents 0e2b40f + 73de372 commit 21ebc3a
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‎.appveyor.yml

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- activate test-environment
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- echo %PYTHON_VERSION% %TARGET_ARCH%
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# pytest-cov>=2.3.1 due to https://github.com/pytest-dev/pytest-cov/issues/124
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- pip install -q "pytest>=3.4,<4.6" "pytest-cov>=2.3.1" pytest-rerunfailures pytest-timeout pytest-xdist
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- pip install -q "pytest>=3.4,!=4.6.0" "pytest-cov>=2.3.1" pytest-rerunfailures pytest-timeout pytest-xdist
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# Apply patch to `subprocess` on Python versions > 2 and < 3.6.3
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# https://github.com/matplotlib/matplotlib/issues/9176

‎.github/FUNDING.yml

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# These are supported funding model platforms
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custom: https://numfocus.salsalabs.org/donate-to-matplotlib/index.html

‎LICENSE/LICENSE_PAINT

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Copyright 2000 by Object Craft P/L, Melbourne, Australia.
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All Rights Reserved
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Permission to use, copy, modify, and distribute this software and its
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documentation for any purpose and without fee is hereby granted,
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provided that the above copyright notice appear in all copies and that
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both that copyright notice and this permission notice appear in
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supporting documentation, and that the name of Object Craft
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is not be used in advertising or publicity pertaining to
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distribution of the software without specific, written prior
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permission.
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OBJECT CRAFT DISCLAIMS ALL WARRANTIES WITH REGARD TO THIS SOFTWARE,
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INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS, IN NO
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EVENT SHALL OBJECT CRAFT BE LIABLE FOR ANY SPECIAL, INDIRECT OR
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CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM LOSS OF
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USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
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OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
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PERFORMANCE OF THIS SOFTWARE.

‎doc/api/next_api_changes/2019-06-05-JKS.rst

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Removals
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````````
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The following members of ``matplotlib.backends.backend_pdf.PdfFile`` were removed:
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- ``nextObject``
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- ``nextFont``
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- ``nextAlphaState``
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- ``nextHatch``
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- ``nextImage``

‎doc/users/next_whats_new/2019-05-31-AL.rst

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The *fname* argument to `FontProperties` can now be an `os.PathLike`\s
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``````````````````````````````````````````````````````````````````````
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e.g. ``FontProperties(fname=pathlib.Path("/path/to/font.ttf"))``.

‎examples/animation/random_walk.py

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def gen_rand_line(length, dims=2):
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"""
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Create a line using a random walk algorithm
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length is the number of points for the line.
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dims is the number of dimensions the line has.
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Create a line using a random walk algorithm.
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Parameters
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----------
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length : int
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The number of points of the line.
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dims : int
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The number of dimensions of the line.
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"""
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line_data = np.empty((dims, length))
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line_data[:, 0] = np.random.rand(dims)

‎examples/animation/strip_chart.py

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def emitter(p=0.03):
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'return a random value with probability p, else 0'
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"""Return a random value in [0, 1) with probability p, else 0."""
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while True:
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v = np.random.rand(1)
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if v > p:

‎examples/axisartist/demo_axis_direction.py

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def setup_axes(fig, rect):
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"""
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polar projection, but in a rectangular box.
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"""
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"""Polar projection, but in a rectangular box."""
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# see demo_curvelinear_grid.py for details
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tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

‎examples/axisartist/demo_curvelinear_grid2.py

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def curvelinear_test1(fig):
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"""
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grid for custom transform.
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"""
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"""Grid for custom transform."""
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def tr(x, y):
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sgn = np.sign(x)

‎examples/axisartist/simple_axis_pad.py

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def setup_axes(fig, rect):
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"""
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polar projection, but in a rectangular box.
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"""
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"""Polar projection, but in a rectangular box."""
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# see demo_curvelinear_grid.py for details
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tr = Affine2D().scale(np.pi/180., 1.) + PolarAxes.PolarTransform()

‎examples/event_handling/pick_event_demo2.py

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Pick Event Demo2
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================
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compute the mean and standard deviation (stddev) of 100 data sets and plot
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mean vs stddev. When you click on one of the mu, sigma points, plot the raw
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data from the dataset that generated the mean and stddev.
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Compute the mean (mu) and standard deviation (sigma) of 100 data sets and plot
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mu vs. sigma. When you click on one of the (mu, sigma) points, plot the raw
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data from the dataset that generated this point.
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"""
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import numpy as np
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import matplotlib.pyplot as plt

‎examples/images_contours_and_fields/interpolation_methods.py

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"""
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=================================
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Interpolations for imshow/matshow
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=================================
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=========================
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Interpolations for imshow
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=========================
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This example displays the difference between interpolation methods for
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:meth:`~.axes.Axes.imshow` and :meth:`~.axes.Axes.matshow`.
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:meth:`~.axes.Axes.imshow`.
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If `interpolation` is None, it defaults to the ``image.interpolation``
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:doc:`rc parameter </tutorials/introductory/customizing>`.
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If the interpolation is ``'none'``, then no interpolation is performed
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for the Agg, ps and pdf backends. Other backends will default to ``'nearest'``.
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If `interpolation` is None, it defaults to the :rc:`image.interpolation`
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(default: ``'nearest'``). If the interpolation is ``'none'``, then no
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interpolation is performed for the Agg, ps and pdf backends. Other backends
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will default to ``'nearest'``.
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For the Agg, ps and pdf backends, ``interpolation = 'none'`` works well when a
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big image is scaled down, while ``interpolation = 'nearest'`` works well when

‎examples/text_labels_and_annotations/font_file.py

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:doc:`/gallery/text_labels_and_annotations/fonts_demo`.
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"""
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import os
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from matplotlib import font_manager as fm, rcParams
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from pathlib import Path
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import matplotlib as mpl
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from matplotlib import font_manager as fm
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import matplotlib.pyplot as plt
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fig, ax = plt.subplots()
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fpath = os.path.join(rcParams["datapath"], "fonts/ttf/cmr10.ttf")
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fpath = Path(mpl.get_data_path(), "fonts/ttf/cmr10.ttf")
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prop = fm.FontProperties(fname=fpath)
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fname = os.path.split(fpath)[1]
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ax.set_title('This is a special font: {}'.format(fname), fontproperties=prop)
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ax.set_title(f'This is a special font: {fpath.name}', fontproperties=prop)
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ax.set_xlabel('This is the default font')
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plt.show()

‎examples/widgets/span_selector.py

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ax2.set_ylim(thisy.min(), thisy.max())
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fig.canvas.draw()
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# Set useblit=True on most backends for enhanced performance.
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#############################################################################
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# .. note::
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#
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# If the SpanSelector object is garbage collected you will lose the
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# interactivity. You must keep a hard reference to it to prevent this.
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#
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span = SpanSelector(ax1, onselect, 'horizontal', useblit=True,
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rectprops=dict(alpha=0.5, facecolor='red'))
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# Set useblit=True on most backends for enhanced performance.
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plt.show()

‎lib/matplotlib/afm.py

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It is pretty easy to use, and requires only built-in python libs:
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>>> from matplotlib import rcParams
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>>> import matplotlib as mpl
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>>> import os.path
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>>> afm_fname = os.path.join(rcParams['datapath'],
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>>> afm_fname = os.path.join(mpl.get_data_path(),
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... 'fonts', 'afm', 'ptmr8a.afm')
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>>>
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>>> from matplotlib.afm import AFM

‎lib/matplotlib/axes/_axes.py

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ret.set_clim(vmin, vmax)
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elif np.ndim(C) == 2: # C.ndim == 3 is RGB(A) so doesn't need scaling.
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ret.autoscale_None()
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if ret.get_clip_path() is None:
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# image does not already have clipping set, clip to axes patch
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ret.set_clip_path(self.patch)
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ret.sticky_edges.x[:] = [xl, xr]
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ret.sticky_edges.y[:] = [yb, yt]

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