new ip

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/__init__.py

@@ -0,0 +1,10 @@
+from pathlib import Path
+
+
+# Check that the test directories exist.
+if not (Path(__file__).parent / 'baseline_images').exists():
+    raise IOError(
+        'The baseline image directory does not exist. '
+        'This is most likely because the test data is not installed. '
+        'You may need to install matplotlib from source to get the '
+        'test data.')

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/conftest.py

@@ -0,0 +1,2 @@
+from matplotlib.testing.conftest import (  # noqa
+    mpl_test_settings, pytest_configure, pytest_unconfigure, pd, xr)

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_afm.py

@@ -0,0 +1,137 @@
+from io import BytesIO
+import pytest
+import logging
+
+from matplotlib import _afm
+from matplotlib import font_manager as fm
+
+
+# See note in afm.py re: use of comma as decimal separator in the
+# UnderlineThickness field and re: use of non-ASCII characters in the Notice
+# field.
+AFM_TEST_DATA = b"""StartFontMetrics 2.0
+Comment Comments are ignored.
+Comment Creation Date:Mon Nov 13 12:34:11 GMT 2017
+FontName MyFont-Bold
+EncodingScheme FontSpecific
+FullName My Font Bold
+FamilyName Test Fonts
+Weight Bold
+ItalicAngle 0.0
+IsFixedPitch false
+UnderlinePosition -100
+UnderlineThickness 56,789
+Version 001.000
+Notice Copyright \xa9 2017 No one.
+FontBBox 0 -321 1234 369
+StartCharMetrics 3
+C 0 ; WX 250 ; N space ; B 0 0 0 0 ;
+C 42 ; WX 1141 ; N foo ; B 40 60 800 360 ;
+C 99 ; WX 583 ; N bar ; B 40 -10 543 210 ;
+EndCharMetrics
+EndFontMetrics
+"""
+
+
+def test_nonascii_str():
+    # This tests that we also decode bytes as utf-8 properly.
+    # Else, font files with non ascii characters fail to load.
+    inp_str = "привет"
+    byte_str = inp_str.encode("utf8")
+
+    ret = _afm._to_str(byte_str)
+    assert ret == inp_str
+
+
+def test_parse_header():
+    fh = BytesIO(AFM_TEST_DATA)
+    header = _afm._parse_header(fh)
+    assert header == {
+        b'StartFontMetrics': 2.0,
+        b'FontName': 'MyFont-Bold',
+        b'EncodingScheme': 'FontSpecific',
+        b'FullName': 'My Font Bold',
+        b'FamilyName': 'Test Fonts',
+        b'Weight': 'Bold',
+        b'ItalicAngle': 0.0,
+        b'IsFixedPitch': False,
+        b'UnderlinePosition': -100,
+        b'UnderlineThickness': 56.789,
+        b'Version': '001.000',
+        b'Notice': b'Copyright \xa9 2017 No one.',
+        b'FontBBox': [0, -321, 1234, 369],
+        b'StartCharMetrics': 3,
+    }
+
+
+def test_parse_char_metrics():
+    fh = BytesIO(AFM_TEST_DATA)
+    _afm._parse_header(fh)  # position
+    metrics = _afm._parse_char_metrics(fh)
+    assert metrics == (
+        {0: (250.0, 'space', [0, 0, 0, 0]),
+         42: (1141.0, 'foo', [40, 60, 800, 360]),
+         99: (583.0, 'bar', [40, -10, 543, 210]),
+         },
+        {'space': (250.0, 'space', [0, 0, 0, 0]),
+         'foo': (1141.0, 'foo', [40, 60, 800, 360]),
+         'bar': (583.0, 'bar', [40, -10, 543, 210]),
+         })
+
+
+def test_get_familyname_guessed():
+    fh = BytesIO(AFM_TEST_DATA)
+    font = _afm.AFM(fh)
+    del font._header[b'FamilyName']  # remove FamilyName, so we have to guess
+    assert font.get_familyname() == 'My Font'
+
+
+def test_font_manager_weight_normalization():
+    font = _afm.AFM(BytesIO(
+        AFM_TEST_DATA.replace(b"Weight Bold\n", b"Weight Custom\n")))
+    assert fm.afmFontProperty("", font).weight == "normal"
+
+
+@pytest.mark.parametrize(
+    "afm_data",
+    [
+        b"""nope
+really nope""",
+        b"""StartFontMetrics 2.0
+Comment Comments are ignored.
+Comment Creation Date:Mon Nov 13 12:34:11 GMT 2017
+FontName MyFont-Bold
+EncodingScheme FontSpecific""",
+    ],
+)
+def test_bad_afm(afm_data):
+    fh = BytesIO(afm_data)
+    with pytest.raises(RuntimeError):
+        _afm._parse_header(fh)
+
+
+@pytest.mark.parametrize(
+    "afm_data",
+    [
+        b"""StartFontMetrics 2.0
+Comment Comments are ignored.
+Comment Creation Date:Mon Nov 13 12:34:11 GMT 2017
+Aardvark bob
+FontName MyFont-Bold
+EncodingScheme FontSpecific
+StartCharMetrics 3""",
+        b"""StartFontMetrics 2.0
+Comment Comments are ignored.
+Comment Creation Date:Mon Nov 13 12:34:11 GMT 2017
+ItalicAngle zero degrees
+FontName MyFont-Bold
+EncodingScheme FontSpecific
+StartCharMetrics 3""",
+    ],
+)
+def test_malformed_header(afm_data, caplog):
+    fh = BytesIO(afm_data)
+    with caplog.at_level(logging.ERROR):
+        _afm._parse_header(fh)
+
+    assert len(caplog.records) == 1

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_agg.py

@@ -0,0 +1,338 @@
+import io
+
+import numpy as np
+from numpy.testing import assert_array_almost_equal
+from PIL import Image, TiffTags
+import pytest
+
+
+from matplotlib import (
+    collections, patheffects, pyplot as plt, transforms as mtransforms,
+    rcParams, rc_context)
+from matplotlib.backends.backend_agg import RendererAgg
+from matplotlib.figure import Figure
+from matplotlib.image import imread
+from matplotlib.path import Path
+from matplotlib.testing.decorators import image_comparison
+from matplotlib.transforms import IdentityTransform
+
+
+def test_repeated_save_with_alpha():
+    # We want an image which has a background color of bluish green, with an
+    # alpha of 0.25.
+
+    fig = Figure([1, 0.4])
+    fig.set_facecolor((0, 1, 0.4))
+    fig.patch.set_alpha(0.25)
+
+    # The target color is fig.patch.get_facecolor()
+
+    buf = io.BytesIO()
+
+    fig.savefig(buf,
+                facecolor=fig.get_facecolor(),
+                edgecolor='none')
+
+    # Save the figure again to check that the
+    # colors don't bleed from the previous renderer.
+    buf.seek(0)
+    fig.savefig(buf,
+                facecolor=fig.get_facecolor(),
+                edgecolor='none')
+
+    # Check the first pixel has the desired color & alpha
+    # (approx: 0, 1.0, 0.4, 0.25)
+    buf.seek(0)
+    assert_array_almost_equal(tuple(imread(buf)[0, 0]),
+                              (0.0, 1.0, 0.4, 0.250),
+                              decimal=3)
+
+
+def test_large_single_path_collection():
+    buff = io.BytesIO()
+
+    # Generates a too-large single path in a path collection that
+    # would cause a segfault if the draw_markers optimization is
+    # applied.
+    f, ax = plt.subplots()
+    collection = collections.PathCollection(
+        [Path([[-10, 5], [10, 5], [10, -5], [-10, -5], [-10, 5]])])
+    ax.add_artist(collection)
+    ax.set_xlim(10**-3, 1)
+    plt.savefig(buff)
+
+
+def test_marker_with_nan():
+    # This creates a marker with nans in it, which was segfaulting the
+    # Agg backend (see #3722)
+    fig, ax = plt.subplots(1)
+    steps = 1000
+    data = np.arange(steps)
+    ax.semilogx(data)
+    ax.fill_between(data, data*0.8, data*1.2)
+    buf = io.BytesIO()
+    fig.savefig(buf, format='png')
+
+
+def test_long_path():
+    buff = io.BytesIO()
+    fig = Figure()
+    ax = fig.subplots()
+    points = np.ones(100_000)
+    points[::2] *= -1
+    ax.plot(points)
+    fig.savefig(buff, format='png')
+
+
+@image_comparison(['agg_filter.png'], remove_text=True)
+def test_agg_filter():
+    def smooth1d(x, window_len):
+        # copied from https://scipy-cookbook.readthedocs.io/
+        s = np.r_[
+            2*x[0] - x[window_len:1:-1], x, 2*x[-1] - x[-1:-window_len:-1]]
+        w = np.hanning(window_len)
+        y = np.convolve(w/w.sum(), s, mode='same')
+        return y[window_len-1:-window_len+1]
+
+    def smooth2d(A, sigma=3):
+        window_len = max(int(sigma), 3) * 2 + 1
+        A = np.apply_along_axis(smooth1d, 0, A, window_len)
+        A = np.apply_along_axis(smooth1d, 1, A, window_len)
+        return A
+
+    class BaseFilter:
+
+        def get_pad(self, dpi):
+            return 0
+
+        def process_image(self, padded_src, dpi):
+            raise NotImplementedError("Should be overridden by subclasses")
+
+        def __call__(self, im, dpi):
+            pad = self.get_pad(dpi)
+            padded_src = np.pad(im, [(pad, pad), (pad, pad), (0, 0)],
+                                "constant")
+            tgt_image = self.process_image(padded_src, dpi)
+            return tgt_image, -pad, -pad
+
+    class OffsetFilter(BaseFilter):
+
+        def __init__(self, offsets=(0, 0)):
+            self.offsets = offsets
+
+        def get_pad(self, dpi):
+            return int(max(self.offsets) / 72 * dpi)
+
+        def process_image(self, padded_src, dpi):
+            ox, oy = self.offsets
+            a1 = np.roll(padded_src, int(ox / 72 * dpi), axis=1)
+            a2 = np.roll(a1, -int(oy / 72 * dpi), axis=0)
+            return a2
+
+    class GaussianFilter(BaseFilter):
+        """Simple Gaussian filter."""
+
+        def __init__(self, sigma, alpha=0.5, color=(0, 0, 0)):
+            self.sigma = sigma
+            self.alpha = alpha
+            self.color = color
+
+        def get_pad(self, dpi):
+            return int(self.sigma*3 / 72 * dpi)
+
+        def process_image(self, padded_src, dpi):
+            tgt_image = np.empty_like(padded_src)
+            tgt_image[:, :, :3] = self.color
+            tgt_image[:, :, 3] = smooth2d(padded_src[:, :, 3] * self.alpha,
+                                          self.sigma / 72 * dpi)
+            return tgt_image
+
+    class DropShadowFilter(BaseFilter):
+
+        def __init__(self, sigma, alpha=0.3, color=(0, 0, 0), offsets=(0, 0)):
+            self.gauss_filter = GaussianFilter(sigma, alpha, color)
+            self.offset_filter = OffsetFilter(offsets)
+
+        def get_pad(self, dpi):
+            return max(self.gauss_filter.get_pad(dpi),
+                       self.offset_filter.get_pad(dpi))
+
+        def process_image(self, padded_src, dpi):
+            t1 = self.gauss_filter.process_image(padded_src, dpi)
+            t2 = self.offset_filter.process_image(t1, dpi)
+            return t2
+
+    fig, ax = plt.subplots()
+
+    # draw lines
+    line1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",
+                     mec="b", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
+    line2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-",
+                     mec="r", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
+
+    gauss = DropShadowFilter(4)
+
+    for line in [line1, line2]:
+
+        # draw shadows with same lines with slight offset.
+        xx = line.get_xdata()
+        yy = line.get_ydata()
+        shadow, = ax.plot(xx, yy)
+        shadow.update_from(line)
+
+        # offset transform
+        transform = mtransforms.offset_copy(line.get_transform(), ax.figure,
+                                            x=4.0, y=-6.0, units='points')
+        shadow.set_transform(transform)
+
+        # adjust zorder of the shadow lines so that it is drawn below the
+        # original lines
+        shadow.set_zorder(line.get_zorder() - 0.5)
+        shadow.set_agg_filter(gauss)
+        shadow.set_rasterized(True)  # to support mixed-mode renderers
+
+    ax.set_xlim(0., 1.)
+    ax.set_ylim(0., 1.)
+
+    ax.xaxis.set_visible(False)
+    ax.yaxis.set_visible(False)
+
+
+def test_too_large_image():
+    fig = plt.figure(figsize=(300, 1000))
+    buff = io.BytesIO()
+    with pytest.raises(ValueError):
+        fig.savefig(buff)
+
+
+def test_chunksize():
+    x = range(200)
+
+    # Test without chunksize
+    fig, ax = plt.subplots()
+    ax.plot(x, np.sin(x))
+    fig.canvas.draw()
+
+    # Test with chunksize
+    fig, ax = plt.subplots()
+    rcParams['agg.path.chunksize'] = 105
+    ax.plot(x, np.sin(x))
+    fig.canvas.draw()
+
+
+@pytest.mark.backend('Agg')
+def test_jpeg_dpi():
+    # Check that dpi is set correctly in jpg files.
+    plt.plot([0, 1, 2], [0, 1, 0])
+    buf = io.BytesIO()
+    plt.savefig(buf, format="jpg", dpi=200)
+    im = Image.open(buf)
+    assert im.info['dpi'] == (200, 200)
+
+
+def test_pil_kwargs_png():
+    from PIL.PngImagePlugin import PngInfo
+    buf = io.BytesIO()
+    pnginfo = PngInfo()
+    pnginfo.add_text("Software", "test")
+    plt.figure().savefig(buf, format="png", pil_kwargs={"pnginfo": pnginfo})
+    im = Image.open(buf)
+    assert im.info["Software"] == "test"
+
+
+def test_pil_kwargs_tiff():
+    buf = io.BytesIO()
+    pil_kwargs = {"description": "test image"}
+    plt.figure().savefig(buf, format="tiff", pil_kwargs=pil_kwargs)
+    im = Image.open(buf)
+    tags = {TiffTags.TAGS_V2[k].name: v for k, v in im.tag_v2.items()}
+    assert tags["ImageDescription"] == "test image"
+
+
+def test_pil_kwargs_webp():
+    plt.plot([0, 1, 2], [0, 1, 0])
+    buf_small = io.BytesIO()
+    pil_kwargs_low = {"quality": 1}
+    plt.savefig(buf_small, format="webp", pil_kwargs=pil_kwargs_low)
+    assert len(pil_kwargs_low) == 1
+    buf_large = io.BytesIO()
+    pil_kwargs_high = {"quality": 100}
+    plt.savefig(buf_large, format="webp", pil_kwargs=pil_kwargs_high)
+    assert len(pil_kwargs_high) == 1
+    assert buf_large.getbuffer().nbytes > buf_small.getbuffer().nbytes
+
+
+def test_webp_alpha():
+    plt.plot([0, 1, 2], [0, 1, 0])
+    buf = io.BytesIO()
+    plt.savefig(buf, format="webp", transparent=True)
+    im = Image.open(buf)
+    assert im.mode == "RGBA"
+
+
+def test_draw_path_collection_error_handling():
+    fig, ax = plt.subplots()
+    ax.scatter([1], [1]).set_paths(Path([(0, 1), (2, 3)]))
+    with pytest.raises(TypeError):
+        fig.canvas.draw()
+
+
+def test_chunksize_fails():
+    # NOTE: This test covers multiple independent test scenarios in a single
+    #       function, because each scenario uses ~2GB of memory and we don't
+    #       want parallel test executors to accidentally run multiple of these
+    #       at the same time.
+
+    N = 100_000
+    dpi = 500
+    w = 5*dpi
+    h = 6*dpi
+
+    # make a Path that spans the whole w-h rectangle
+    x = np.linspace(0, w, N)
+    y = np.ones(N) * h
+    y[::2] = 0
+    path = Path(np.vstack((x, y)).T)
+    # effectively disable path simplification (but leaving it "on")
+    path.simplify_threshold = 0
+
+    # setup the minimal GraphicsContext to draw a Path
+    ra = RendererAgg(w, h, dpi)
+    gc = ra.new_gc()
+    gc.set_linewidth(1)
+    gc.set_foreground('r')
+
+    gc.set_hatch('/')
+    with pytest.raises(OverflowError, match='can not split hatched path'):
+        ra.draw_path(gc, path, IdentityTransform())
+    gc.set_hatch(None)
+
+    with pytest.raises(OverflowError, match='can not split filled path'):
+        ra.draw_path(gc, path, IdentityTransform(), (1, 0, 0))
+
+    # Set to zero to disable, currently defaults to 0, but let's be sure.
+    with rc_context({'agg.path.chunksize': 0}):
+        with pytest.raises(OverflowError, match='Please set'):
+            ra.draw_path(gc, path, IdentityTransform())
+
+    # Set big enough that we do not try to chunk.
+    with rc_context({'agg.path.chunksize': 1_000_000}):
+        with pytest.raises(OverflowError, match='Please reduce'):
+            ra.draw_path(gc, path, IdentityTransform())
+
+    # Small enough we will try to chunk, but big enough we will fail to render.
+    with rc_context({'agg.path.chunksize': 90_000}):
+        with pytest.raises(OverflowError, match='Please reduce'):
+            ra.draw_path(gc, path, IdentityTransform())
+
+    path.should_simplify = False
+    with pytest.raises(OverflowError, match="should_simplify is False"):
+        ra.draw_path(gc, path, IdentityTransform())
+
+
+def test_non_tuple_rgbaface():
+    # This passes rgbaFace as a ndarray to draw_path.
+    fig = plt.figure()
+    fig.add_subplot(projection="3d").scatter(
+        [0, 1, 2], [0, 1, 2], path_effects=[patheffects.Stroke(linewidth=4)])
+    fig.canvas.draw()

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_agg_filter.py

@@ -0,0 +1,33 @@
+import numpy as np
+
+import matplotlib.pyplot as plt
+from matplotlib.testing.decorators import image_comparison
+
+
+@image_comparison(baseline_images=['agg_filter_alpha'],
+                  extensions=['png', 'pdf'])
+def test_agg_filter_alpha():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['pcolormesh.snap'] = False
+
+    ax = plt.axes()
+    x, y = np.mgrid[0:7, 0:8]
+    data = x**2 - y**2
+    mesh = ax.pcolormesh(data, cmap='Reds', zorder=5)
+
+    def manual_alpha(im, dpi):
+        im[:, :, 3] *= 0.6
+        print('CALLED')
+        return im, 0, 0
+
+    # Note: Doing alpha like this is not the same as setting alpha on
+    # the mesh itself. Currently meshes are drawn as independent patches,
+    # and we see fine borders around the blocks of color. See the SO
+    # question for an example: https://stackoverflow.com/q/20678817/
+    mesh.set_agg_filter(manual_alpha)
+
+    # Currently we must enable rasterization for this to have an effect in
+    # the PDF backend.
+    mesh.set_rasterized(True)
+
+    ax.plot([0, 4, 7], [1, 3, 8])

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_animation.py

@@ -0,0 +1,518 @@
+import os
+from pathlib import Path
+import platform
+import re
+import subprocess
+import sys
+import weakref
+
+import numpy as np
+import pytest
+
+import matplotlib as mpl
+from matplotlib import pyplot as plt
+from matplotlib import animation
+from matplotlib.testing.decorators import check_figures_equal
+
+
+@pytest.fixture()
+def anim(request):
+    """Create a simple animation (with options)."""
+    fig, ax = plt.subplots()
+    line, = ax.plot([], [])
+
+    ax.set_xlim(0, 10)
+    ax.set_ylim(-1, 1)
+
+    def init():
+        line.set_data([], [])
+        return line,
+
+    def animate(i):
+        x = np.linspace(0, 10, 100)
+        y = np.sin(x + i)
+        line.set_data(x, y)
+        return line,
+
+    # "klass" can be passed to determine the class returned by the fixture
+    kwargs = dict(getattr(request, 'param', {}))  # make a copy
+    klass = kwargs.pop('klass', animation.FuncAnimation)
+    if 'frames' not in kwargs:
+        kwargs['frames'] = 5
+    return klass(fig=fig, func=animate, init_func=init, **kwargs)
+
+
+class NullMovieWriter(animation.AbstractMovieWriter):
+    """
+    A minimal MovieWriter.  It doesn't actually write anything.
+    It just saves the arguments that were given to the setup() and
+    grab_frame() methods as attributes, and counts how many times
+    grab_frame() is called.
+
+    This class doesn't have an __init__ method with the appropriate
+    signature, and it doesn't define an isAvailable() method, so
+    it cannot be added to the 'writers' registry.
+    """
+
+    def setup(self, fig, outfile, dpi, *args):
+        self.fig = fig
+        self.outfile = outfile
+        self.dpi = dpi
+        self.args = args
+        self._count = 0
+
+    def grab_frame(self, **savefig_kwargs):
+        self.savefig_kwargs = savefig_kwargs
+        self._count += 1
+
+    def finish(self):
+        pass
+
+
+def test_null_movie_writer(anim):
+    # Test running an animation with NullMovieWriter.
+    plt.rcParams["savefig.facecolor"] = "auto"
+    filename = "unused.null"
+    dpi = 50
+    savefig_kwargs = dict(foo=0)
+    writer = NullMovieWriter()
+
+    anim.save(filename, dpi=dpi, writer=writer,
+              savefig_kwargs=savefig_kwargs)
+
+    assert writer.fig == plt.figure(1)  # The figure used by anim fixture
+    assert writer.outfile == filename
+    assert writer.dpi == dpi
+    assert writer.args == ()
+    # we enrich the savefig kwargs to ensure we composite transparent
+    # output to an opaque background
+    for k, v in savefig_kwargs.items():
+        assert writer.savefig_kwargs[k] == v
+    assert writer._count == anim._save_count
+
+
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_animation_delete(anim):
+    if platform.python_implementation() == 'PyPy':
+        # Something in the test setup fixture lingers around into the test and
+        # breaks pytest.warns on PyPy. This garbage collection fixes it.
+        # https://foss.heptapod.net/pypy/pypy/-/issues/3536
+        np.testing.break_cycles()
+    anim = animation.FuncAnimation(**anim)
+    with pytest.warns(Warning, match='Animation was deleted'):
+        del anim
+        np.testing.break_cycles()
+
+
+def test_movie_writer_dpi_default():
+    class DummyMovieWriter(animation.MovieWriter):
+        def _run(self):
+            pass
+
+    # Test setting up movie writer with figure.dpi default.
+    fig = plt.figure()
+
+    filename = "unused.null"
+    fps = 5
+    codec = "unused"
+    bitrate = 1
+    extra_args = ["unused"]
+
+    writer = DummyMovieWriter(fps, codec, bitrate, extra_args)
+    writer.setup(fig, filename)
+    assert writer.dpi == fig.dpi
+
+
+@animation.writers.register('null')
+class RegisteredNullMovieWriter(NullMovieWriter):
+
+    # To be able to add NullMovieWriter to the 'writers' registry,
+    # we must define an __init__ method with a specific signature,
+    # and we must define the class method isAvailable().
+    # (These methods are not actually required to use an instance
+    # of this class as the 'writer' argument of Animation.save().)
+
+    def __init__(self, fps=None, codec=None, bitrate=None,
+                 extra_args=None, metadata=None):
+        pass
+
+    @classmethod
+    def isAvailable(cls):
+        return True
+
+
+WRITER_OUTPUT = [
+    ('ffmpeg', 'movie.mp4'),
+    ('ffmpeg_file', 'movie.mp4'),
+    ('imagemagick', 'movie.gif'),
+    ('imagemagick_file', 'movie.gif'),
+    ('pillow', 'movie.gif'),
+    ('html', 'movie.html'),
+    ('null', 'movie.null')
+]
+
+
+def gen_writers():
+    for writer, output in WRITER_OUTPUT:
+        if not animation.writers.is_available(writer):
+            mark = pytest.mark.skip(
+                f"writer '{writer}' not available on this system")
+            yield pytest.param(writer, None, output, marks=[mark])
+            yield pytest.param(writer, None, Path(output), marks=[mark])
+            continue
+
+        writer_class = animation.writers[writer]
+        for frame_format in getattr(writer_class, 'supported_formats', [None]):
+            yield writer, frame_format, output
+            yield writer, frame_format, Path(output)
+
+
+# Smoke test for saving animations.  In the future, we should probably
+# design more sophisticated tests which compare resulting frames a-la
+# matplotlib.testing.image_comparison
+@pytest.mark.parametrize('writer, frame_format, output', gen_writers())
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_save_animation_smoketest(tmpdir, writer, frame_format, output, anim):
+    if frame_format is not None:
+        plt.rcParams["animation.frame_format"] = frame_format
+    anim = animation.FuncAnimation(**anim)
+    dpi = None
+    codec = None
+    if writer == 'ffmpeg':
+        # Issue #8253
+        anim._fig.set_size_inches((10.85, 9.21))
+        dpi = 100.
+        codec = 'h264'
+
+    # Use temporary directory for the file-based writers, which produce a file
+    # per frame with known names.
+    with tmpdir.as_cwd():
+        anim.save(output, fps=30, writer=writer, bitrate=500, dpi=dpi,
+                  codec=codec)
+
+    del anim
+
+
+@pytest.mark.parametrize('writer', [
+    pytest.param(
+        'ffmpeg', marks=pytest.mark.skipif(
+            not animation.FFMpegWriter.isAvailable(),
+            reason='Requires FFMpeg')),
+    pytest.param(
+        'imagemagick', marks=pytest.mark.skipif(
+            not animation.ImageMagickWriter.isAvailable(),
+            reason='Requires ImageMagick')),
+])
+@pytest.mark.parametrize('html, want', [
+    ('none', None),
+    ('html5', '<video width'),
+    ('jshtml', '<script ')
+])
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_animation_repr_html(writer, html, want, anim):
+    if platform.python_implementation() == 'PyPy':
+        # Something in the test setup fixture lingers around into the test and
+        # breaks pytest.warns on PyPy. This garbage collection fixes it.
+        # https://foss.heptapod.net/pypy/pypy/-/issues/3536
+        np.testing.break_cycles()
+    if (writer == 'imagemagick' and html == 'html5'
+            # ImageMagick delegates to ffmpeg for this format.
+            and not animation.FFMpegWriter.isAvailable()):
+        pytest.skip('Requires FFMpeg')
+    # create here rather than in the fixture otherwise we get __del__ warnings
+    # about producing no output
+    anim = animation.FuncAnimation(**anim)
+    with plt.rc_context({'animation.writer': writer,
+                         'animation.html': html}):
+        html = anim._repr_html_()
+    if want is None:
+        assert html is None
+        with pytest.warns(UserWarning):
+            del anim  # Animation was never run, so will warn on cleanup.
+            np.testing.break_cycles()
+    else:
+        assert want in html
+
+
+@pytest.mark.parametrize(
+    'anim',
+    [{'save_count': 10, 'frames': iter(range(5))}],
+    indirect=['anim']
+)
+def test_no_length_frames(anim):
+    anim.save('unused.null', writer=NullMovieWriter())
+
+
+def test_movie_writer_registry():
+    assert len(animation.writers._registered) > 0
+    mpl.rcParams['animation.ffmpeg_path'] = "not_available_ever_xxxx"
+    assert not animation.writers.is_available("ffmpeg")
+    # something guaranteed to be available in path and exits immediately
+    bin = "true" if sys.platform != 'win32' else "where"
+    mpl.rcParams['animation.ffmpeg_path'] = bin
+    assert animation.writers.is_available("ffmpeg")
+
+
+@pytest.mark.parametrize(
+    "method_name",
+    [pytest.param("to_html5_video", marks=pytest.mark.skipif(
+        not animation.writers.is_available(mpl.rcParams["animation.writer"]),
+        reason="animation writer not installed")),
+     "to_jshtml"])
+@pytest.mark.parametrize('anim', [dict(frames=1)], indirect=['anim'])
+def test_embed_limit(method_name, caplog, tmpdir, anim):
+    caplog.set_level("WARNING")
+    with tmpdir.as_cwd():
+        with mpl.rc_context({"animation.embed_limit": 1e-6}):  # ~1 byte.
+            getattr(anim, method_name)()
+    assert len(caplog.records) == 1
+    record, = caplog.records
+    assert (record.name == "matplotlib.animation"
+            and record.levelname == "WARNING")
+
+
+@pytest.mark.parametrize(
+    "method_name",
+    [pytest.param("to_html5_video", marks=pytest.mark.skipif(
+        not animation.writers.is_available(mpl.rcParams["animation.writer"]),
+        reason="animation writer not installed")),
+     "to_jshtml"])
+@pytest.mark.parametrize('anim', [dict(frames=1)], indirect=['anim'])
+def test_cleanup_temporaries(method_name, tmpdir, anim):
+    with tmpdir.as_cwd():
+        getattr(anim, method_name)()
+        assert list(Path(str(tmpdir)).iterdir()) == []
+
+
+@pytest.mark.skipif(os.name != "posix", reason="requires a POSIX OS")
+def test_failing_ffmpeg(tmpdir, monkeypatch, anim):
+    """
+    Test that we correctly raise a CalledProcessError when ffmpeg fails.
+
+    To do so, mock ffmpeg using a simple executable shell script that
+    succeeds when called with no arguments (so that it gets registered by
+    `isAvailable`), but fails otherwise, and add it to the $PATH.
+    """
+    with tmpdir.as_cwd():
+        monkeypatch.setenv("PATH", ".:" + os.environ["PATH"])
+        exe_path = Path(str(tmpdir), "ffmpeg")
+        exe_path.write_bytes(b"#!/bin/sh\n[[ $@ -eq 0 ]]\n")
+        os.chmod(exe_path, 0o755)
+        with pytest.raises(subprocess.CalledProcessError):
+            anim.save("test.mpeg")
+
+
+@pytest.mark.parametrize("cache_frame_data", [False, True])
+def test_funcanimation_cache_frame_data(cache_frame_data):
+    fig, ax = plt.subplots()
+    line, = ax.plot([], [])
+
+    class Frame(dict):
+        # this subclassing enables to use weakref.ref()
+        pass
+
+    def init():
+        line.set_data([], [])
+        return line,
+
+    def animate(frame):
+        line.set_data(frame['x'], frame['y'])
+        return line,
+
+    frames_generated = []
+
+    def frames_generator():
+        for _ in range(5):
+            x = np.linspace(0, 10, 100)
+            y = np.random.rand(100)
+
+            frame = Frame(x=x, y=y)
+
+            # collect weak references to frames
+            # to validate their references later
+            frames_generated.append(weakref.ref(frame))
+
+            yield frame
+
+    MAX_FRAMES = 100
+    anim = animation.FuncAnimation(fig, animate, init_func=init,
+                                   frames=frames_generator,
+                                   cache_frame_data=cache_frame_data,
+                                   save_count=MAX_FRAMES)
+
+    writer = NullMovieWriter()
+    anim.save('unused.null', writer=writer)
+    assert len(frames_generated) == 5
+    np.testing.break_cycles()
+    for f in frames_generated:
+        # If cache_frame_data is True, then the weakref should be alive;
+        # if cache_frame_data is False, then the weakref should be dead (None).
+        assert (f() is None) != cache_frame_data
+
+
+@pytest.mark.parametrize('return_value', [
+    # User forgot to return (returns None).
+    None,
+    # User returned a string.
+    'string',
+    # User returned an int.
+    1,
+    # User returns a sequence of other objects, e.g., string instead of Artist.
+    ('string', ),
+    # User forgot to return a sequence (handled in `animate` below.)
+    'artist',
+])
+def test_draw_frame(return_value):
+    # test _draw_frame method
+
+    fig, ax = plt.subplots()
+    line, = ax.plot([])
+
+    def animate(i):
+        # general update func
+        line.set_data([0, 1], [0, i])
+        if return_value == 'artist':
+            # *not* a sequence
+            return line
+        else:
+            return return_value
+
+    with pytest.raises(RuntimeError):
+        animation.FuncAnimation(
+            fig, animate, blit=True, cache_frame_data=False
+        )
+
+
+def test_exhausted_animation(tmpdir):
+    fig, ax = plt.subplots()
+
+    def update(frame):
+        return []
+
+    anim = animation.FuncAnimation(
+        fig, update, frames=iter(range(10)), repeat=False,
+        cache_frame_data=False
+    )
+
+    with tmpdir.as_cwd():
+        anim.save("test.gif", writer='pillow')
+
+    with pytest.warns(UserWarning, match="exhausted"):
+        anim._start()
+
+
+def test_no_frame_warning(tmpdir):
+    fig, ax = plt.subplots()
+
+    def update(frame):
+        return []
+
+    anim = animation.FuncAnimation(
+        fig, update, frames=[], repeat=False,
+        cache_frame_data=False
+    )
+
+    with pytest.warns(UserWarning, match="exhausted"):
+        anim._start()
+
+
+@check_figures_equal(extensions=["png"])
+def test_animation_frame(tmpdir, fig_test, fig_ref):
+    # Test the expected image after iterating through a few frames
+    # we save the animation to get the iteration because we are not
+    # in an interactive framework.
+    ax = fig_test.add_subplot()
+    ax.set_xlim(0, 2 * np.pi)
+    ax.set_ylim(-1, 1)
+    x = np.linspace(0, 2 * np.pi, 100)
+    line, = ax.plot([], [])
+
+    def init():
+        line.set_data([], [])
+        return line,
+
+    def animate(i):
+        line.set_data(x, np.sin(x + i / 100))
+        return line,
+
+    anim = animation.FuncAnimation(
+        fig_test, animate, init_func=init, frames=5,
+        blit=True, repeat=False)
+    with tmpdir.as_cwd():
+        anim.save("test.gif")
+
+    # Reference figure without animation
+    ax = fig_ref.add_subplot()
+    ax.set_xlim(0, 2 * np.pi)
+    ax.set_ylim(-1, 1)
+
+    # 5th frame's data
+    ax.plot(x, np.sin(x + 4 / 100))
+
+
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_save_count_override_warnings_has_length(anim):
+
+    save_count = 5
+    frames = list(range(2))
+    match_target = (
+        f'You passed in an explicit {save_count=} '
+        "which is being ignored in favor of "
+        f"{len(frames)=}."
+    )
+
+    with pytest.warns(UserWarning, match=re.escape(match_target)):
+        anim = animation.FuncAnimation(
+            **{**anim, 'frames': frames, 'save_count': save_count}
+        )
+    assert anim._save_count == len(frames)
+    anim._init_draw()
+
+
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_save_count_override_warnings_scaler(anim):
+    save_count = 5
+    frames = 7
+    match_target = (
+        f'You passed in an explicit {save_count=} ' +
+        "which is being ignored in favor of " +
+        f"{frames=}."
+    )
+
+    with pytest.warns(UserWarning, match=re.escape(match_target)):
+        anim = animation.FuncAnimation(
+            **{**anim, 'frames': frames, 'save_count': save_count}
+        )
+
+    assert anim._save_count == frames
+    anim._init_draw()
+
+
+@pytest.mark.parametrize('anim', [dict(klass=dict)], indirect=['anim'])
+def test_disable_cache_warning(anim):
+    cache_frame_data = True
+    frames = iter(range(5))
+    match_target = (
+        f"{frames=!r} which we can infer the length of, "
+        "did not pass an explicit *save_count* "
+        f"and passed {cache_frame_data=}.  To avoid a possibly "
+        "unbounded cache, frame data caching has been disabled. "
+        "To suppress this warning either pass "
+        "`cache_frame_data=False` or `save_count=MAX_FRAMES`."
+    )
+    with pytest.warns(UserWarning, match=re.escape(match_target)):
+        anim = animation.FuncAnimation(
+            **{**anim, 'cache_frame_data': cache_frame_data, 'frames': frames}
+        )
+    assert anim._cache_frame_data is False
+    anim._init_draw()
+
+
+def test_movie_writer_invalid_path(anim):
+    if sys.platform == "win32":
+        match_str = re.escape("[WinError 3] The system cannot find the path specified:")
+    else:
+        match_str = re.escape("[Errno 2] No such file or directory: '/foo")
+    with pytest.raises(FileNotFoundError, match=match_str):
+        anim.save("/foo/bar/aardvark/thiscannotreallyexist.mp4",
+                  writer=animation.FFMpegFileWriter())

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_api.py

@@ -0,0 +1,100 @@
+import re
+
+import numpy as np
+import pytest
+
+from matplotlib import _api
+
+
+@pytest.mark.parametrize('target,test_shape',
+                         [((None, ), (1, 3)),
+                          ((None, 3), (1,)),
+                          ((None, 3), (1, 2)),
+                          ((1, 5), (1, 9)),
+                          ((None, 2, None), (1, 3, 1))
+                          ])
+def test_check_shape(target, test_shape):
+    error_pattern = (f"^'aardvark' must be {len(target)}D.*" +
+                     re.escape(f'has shape {test_shape}'))
+    data = np.zeros(test_shape)
+    with pytest.raises(ValueError, match=error_pattern):
+        _api.check_shape(target, aardvark=data)
+
+
+def test_classproperty_deprecation():
+    class A:
+        @_api.deprecated("0.0.0")
+        @_api.classproperty
+        def f(cls):
+            pass
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        A.f
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        a = A()
+        a.f
+
+
+def test_deprecate_privatize_attribute():
+    class C:
+        def __init__(self): self._attr = 1
+        def _meth(self, arg): return arg
+        attr = _api.deprecate_privatize_attribute("0.0")
+        meth = _api.deprecate_privatize_attribute("0.0")
+
+    c = C()
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        assert c.attr == 1
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        c.attr = 2
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        assert c.attr == 2
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        assert c.meth(42) == 42
+
+
+def test_delete_parameter():
+    @_api.delete_parameter("3.0", "foo")
+    def func1(foo=None):
+        pass
+
+    @_api.delete_parameter("3.0", "foo")
+    def func2(**kwargs):
+        pass
+
+    for func in [func1, func2]:
+        func()  # No warning.
+        with pytest.warns(_api.MatplotlibDeprecationWarning):
+            func(foo="bar")
+
+    def pyplot_wrapper(foo=_api.deprecation._deprecated_parameter):
+        func1(foo)
+
+    pyplot_wrapper()  # No warning.
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        func(foo="bar")
+
+
+def test_make_keyword_only():
+    @_api.make_keyword_only("3.0", "arg")
+    def func(pre, arg, post=None):
+        pass
+
+    func(1, arg=2)  # Check that no warning is emitted.
+
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        func(1, 2)
+    with pytest.warns(_api.MatplotlibDeprecationWarning):
+        func(1, 2, 3)
+
+
+def test_deprecation_alternative():
+    alternative = "`.f1`, `f2`, `f3(x) <.f3>` or `f4(x)<f4>`"
+    @_api.deprecated("1", alternative=alternative)
+    def f():
+        pass
+    assert alternative in f.__doc__
+
+
+def test_empty_check_in_list():
+    with pytest.raises(TypeError, match="No argument to check!"):
+        _api.check_in_list(["a"])

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_arrow_patches.py

@@ -0,0 +1,177 @@
+import pytest
+import platform
+import matplotlib.pyplot as plt
+from matplotlib.testing.decorators import image_comparison
+import matplotlib.patches as mpatches
+
+
+def draw_arrow(ax, t, r):
+    ax.annotate('', xy=(0.5, 0.5 + r), xytext=(0.5, 0.5), size=30,
+                arrowprops=dict(arrowstyle=t,
+                                fc="b", ec='k'))
+
+
+@image_comparison(['fancyarrow_test_image'])
+def test_fancyarrow():
+    # Added 0 to test division by zero error described in issue 3930
+    r = [0.4, 0.3, 0.2, 0.1, 0]
+    t = ["fancy", "simple", mpatches.ArrowStyle.Fancy()]
+
+    fig, axs = plt.subplots(len(t), len(r), squeeze=False,
+                            figsize=(8, 4.5), subplot_kw=dict(aspect=1))
+
+    for i_r, r1 in enumerate(r):
+        for i_t, t1 in enumerate(t):
+            ax = axs[i_t, i_r]
+            draw_arrow(ax, t1, r1)
+            ax.tick_params(labelleft=False, labelbottom=False)
+
+
+@image_comparison(['boxarrow_test_image.png'])
+def test_boxarrow():
+
+    styles = mpatches.BoxStyle.get_styles()
+
+    n = len(styles)
+    spacing = 1.2
+
+    figheight = (n * spacing + .5)
+    fig = plt.figure(figsize=(4 / 1.5, figheight / 1.5))
+
+    fontsize = 0.3 * 72
+
+    for i, stylename in enumerate(sorted(styles)):
+        fig.text(0.5, ((n - i) * spacing - 0.5)/figheight, stylename,
+                 ha="center",
+                 size=fontsize,
+                 transform=fig.transFigure,
+                 bbox=dict(boxstyle=stylename, fc="w", ec="k"))
+
+
+def __prepare_fancyarrow_dpi_cor_test():
+    """
+    Convenience function that prepares and returns a FancyArrowPatch. It aims
+    at being used to test that the size of the arrow head does not depend on
+    the DPI value of the exported picture.
+
+    NB: this function *is not* a test in itself!
+    """
+    fig2 = plt.figure("fancyarrow_dpi_cor_test", figsize=(4, 3), dpi=50)
+    ax = fig2.add_subplot()
+    ax.set_xlim([0, 1])
+    ax.set_ylim([0, 1])
+    ax.add_patch(mpatches.FancyArrowPatch(posA=(0.3, 0.4), posB=(0.8, 0.6),
+                                          lw=3, arrowstyle='->',
+                                          mutation_scale=100))
+    return fig2
+
+
+@image_comparison(['fancyarrow_dpi_cor_100dpi.png'], remove_text=True,
+                  tol=0 if platform.machine() == 'x86_64' else 0.02,
+                  savefig_kwarg=dict(dpi=100))
+def test_fancyarrow_dpi_cor_100dpi():
+    """
+    Check the export of a FancyArrowPatch @ 100 DPI. FancyArrowPatch is
+    instantiated through a dedicated function because another similar test
+    checks a similar export but with a different DPI value.
+
+    Remark: test only a rasterized format.
+    """
+
+    __prepare_fancyarrow_dpi_cor_test()
+
+
+@image_comparison(['fancyarrow_dpi_cor_200dpi.png'], remove_text=True,
+                  tol=0 if platform.machine() == 'x86_64' else 0.02,
+                  savefig_kwarg=dict(dpi=200))
+def test_fancyarrow_dpi_cor_200dpi():
+    """
+    As test_fancyarrow_dpi_cor_100dpi, but exports @ 200 DPI. The relative size
+    of the arrow head should be the same.
+    """
+
+    __prepare_fancyarrow_dpi_cor_test()
+
+
+@image_comparison(['fancyarrow_dash.png'], remove_text=True, style='default')
+def test_fancyarrow_dash():
+    fig, ax = plt.subplots()
+    e = mpatches.FancyArrowPatch((0, 0), (0.5, 0.5),
+                                 arrowstyle='-|>',
+                                 connectionstyle='angle3,angleA=0,angleB=90',
+                                 mutation_scale=10.0,
+                                 linewidth=2,
+                                 linestyle='dashed',
+                                 color='k')
+    e2 = mpatches.FancyArrowPatch((0, 0), (0.5, 0.5),
+                                  arrowstyle='-|>',
+                                  connectionstyle='angle3',
+                                  mutation_scale=10.0,
+                                  linewidth=2,
+                                  linestyle='dotted',
+                                  color='k')
+    ax.add_patch(e)
+    ax.add_patch(e2)
+
+
+@image_comparison(['arrow_styles.png'], style='mpl20', remove_text=True,
+                  tol=0 if platform.machine() == 'x86_64' else 0.005)
+def test_arrow_styles():
+    styles = mpatches.ArrowStyle.get_styles()
+
+    n = len(styles)
+    fig, ax = plt.subplots(figsize=(8, 8))
+    ax.set_xlim(0, 1)
+    ax.set_ylim(-1, n)
+    fig.subplots_adjust(left=0, right=1, bottom=0, top=1)
+
+    for i, stylename in enumerate(sorted(styles)):
+        patch = mpatches.FancyArrowPatch((0.1 + (i % 2)*0.05, i),
+                                         (0.45 + (i % 2)*0.05, i),
+                                         arrowstyle=stylename,
+                                         mutation_scale=25)
+        ax.add_patch(patch)
+
+    for i, stylename in enumerate([']-[', ']-', '-[', '|-|']):
+        style = stylename
+        if stylename[0] != '-':
+            style += ',angleA=ANGLE'
+        if stylename[-1] != '-':
+            style += ',angleB=ANGLE'
+
+        for j, angle in enumerate([-30, 60]):
+            arrowstyle = style.replace('ANGLE', str(angle))
+            patch = mpatches.FancyArrowPatch((0.55, 2*i + j), (0.9, 2*i + j),
+                                             arrowstyle=arrowstyle,
+                                             mutation_scale=25)
+            ax.add_patch(patch)
+
+
+@image_comparison(['connection_styles.png'], style='mpl20', remove_text=True)
+def test_connection_styles():
+    styles = mpatches.ConnectionStyle.get_styles()
+
+    n = len(styles)
+    fig, ax = plt.subplots(figsize=(6, 10))
+    ax.set_xlim(0, 1)
+    ax.set_ylim(-1, n)
+
+    for i, stylename in enumerate(sorted(styles)):
+        patch = mpatches.FancyArrowPatch((0.1, i), (0.8, i + 0.5),
+                                         arrowstyle="->",
+                                         connectionstyle=stylename,
+                                         mutation_scale=25)
+        ax.add_patch(patch)
+
+
+def test_invalid_intersection():
+    conn_style_1 = mpatches.ConnectionStyle.Angle3(angleA=20, angleB=200)
+    p1 = mpatches.FancyArrowPatch((.2, .2), (.5, .5),
+                                  connectionstyle=conn_style_1)
+    with pytest.raises(ValueError):
+        plt.gca().add_patch(p1)
+
+    conn_style_2 = mpatches.ConnectionStyle.Angle3(angleA=20, angleB=199.9)
+    p2 = mpatches.FancyArrowPatch((.2, .2), (.5, .5),
+                                  connectionstyle=conn_style_2)
+    plt.gca().add_patch(p2)

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_artist.py

@@ -0,0 +1,564 @@
+import io
+from itertools import chain
+
+import numpy as np
+
+import pytest
+
+import matplotlib.colors as mcolors
+import matplotlib.pyplot as plt
+import matplotlib.patches as mpatches
+import matplotlib.lines as mlines
+import matplotlib.path as mpath
+import matplotlib.transforms as mtransforms
+import matplotlib.collections as mcollections
+import matplotlib.artist as martist
+import matplotlib.backend_bases as mbackend_bases
+import matplotlib as mpl
+from matplotlib.testing.decorators import check_figures_equal, image_comparison
+
+
+def test_patch_transform_of_none():
+    # tests the behaviour of patches added to an Axes with various transform
+    # specifications
+
+    ax = plt.axes()
+    ax.set_xlim([1, 3])
+    ax.set_ylim([1, 3])
+
+    # Draw an ellipse over data coord (2, 2) by specifying device coords.
+    xy_data = (2, 2)
+    xy_pix = ax.transData.transform(xy_data)
+
+    # Not providing a transform of None puts the ellipse in data coordinates .
+    e = mpatches.Ellipse(xy_data, width=1, height=1, fc='yellow', alpha=0.5)
+    ax.add_patch(e)
+    assert e._transform == ax.transData
+
+    # Providing a transform of None puts the ellipse in device coordinates.
+    e = mpatches.Ellipse(xy_pix, width=120, height=120, fc='coral',
+                         transform=None, alpha=0.5)
+    assert e.is_transform_set()
+    ax.add_patch(e)
+    assert isinstance(e._transform, mtransforms.IdentityTransform)
+
+    # Providing an IdentityTransform puts the ellipse in device coordinates.
+    e = mpatches.Ellipse(xy_pix, width=100, height=100,
+                         transform=mtransforms.IdentityTransform(), alpha=0.5)
+    ax.add_patch(e)
+    assert isinstance(e._transform, mtransforms.IdentityTransform)
+
+    # Not providing a transform, and then subsequently "get_transform" should
+    # not mean that "is_transform_set".
+    e = mpatches.Ellipse(xy_pix, width=120, height=120, fc='coral',
+                         alpha=0.5)
+    intermediate_transform = e.get_transform()
+    assert not e.is_transform_set()
+    ax.add_patch(e)
+    assert e.get_transform() != intermediate_transform
+    assert e.is_transform_set()
+    assert e._transform == ax.transData
+
+
+def test_collection_transform_of_none():
+    # tests the behaviour of collections added to an Axes with various
+    # transform specifications
+
+    ax = plt.axes()
+    ax.set_xlim([1, 3])
+    ax.set_ylim([1, 3])
+
+    # draw an ellipse over data coord (2, 2) by specifying device coords
+    xy_data = (2, 2)
+    xy_pix = ax.transData.transform(xy_data)
+
+    # not providing a transform of None puts the ellipse in data coordinates
+    e = mpatches.Ellipse(xy_data, width=1, height=1)
+    c = mcollections.PatchCollection([e], facecolor='yellow', alpha=0.5)
+    ax.add_collection(c)
+    # the collection should be in data coordinates
+    assert c.get_offset_transform() + c.get_transform() == ax.transData
+
+    # providing a transform of None puts the ellipse in device coordinates
+    e = mpatches.Ellipse(xy_pix, width=120, height=120)
+    c = mcollections.PatchCollection([e], facecolor='coral',
+                                     alpha=0.5)
+    c.set_transform(None)
+    ax.add_collection(c)
+    assert isinstance(c.get_transform(), mtransforms.IdentityTransform)
+
+    # providing an IdentityTransform puts the ellipse in device coordinates
+    e = mpatches.Ellipse(xy_pix, width=100, height=100)
+    c = mcollections.PatchCollection([e],
+                                     transform=mtransforms.IdentityTransform(),
+                                     alpha=0.5)
+    ax.add_collection(c)
+    assert isinstance(c.get_offset_transform(), mtransforms.IdentityTransform)
+
+
+@image_comparison(["clip_path_clipping"], remove_text=True)
+def test_clipping():
+    exterior = mpath.Path.unit_rectangle().deepcopy()
+    exterior.vertices *= 4
+    exterior.vertices -= 2
+    interior = mpath.Path.unit_circle().deepcopy()
+    interior.vertices = interior.vertices[::-1]
+    clip_path = mpath.Path.make_compound_path(exterior, interior)
+
+    star = mpath.Path.unit_regular_star(6).deepcopy()
+    star.vertices *= 2.6
+
+    fig, (ax1, ax2) = plt.subplots(1, 2, sharex=True, sharey=True)
+
+    col = mcollections.PathCollection([star], lw=5, edgecolor='blue',
+                                      facecolor='red', alpha=0.7, hatch='*')
+    col.set_clip_path(clip_path, ax1.transData)
+    ax1.add_collection(col)
+
+    patch = mpatches.PathPatch(star, lw=5, edgecolor='blue', facecolor='red',
+                               alpha=0.7, hatch='*')
+    patch.set_clip_path(clip_path, ax2.transData)
+    ax2.add_patch(patch)
+
+    ax1.set_xlim([-3, 3])
+    ax1.set_ylim([-3, 3])
+
+
+@check_figures_equal(extensions=['png'])
+def test_clipping_zoom(fig_test, fig_ref):
+    # This test places the Axes and sets its limits such that the clip path is
+    # outside the figure entirely. This should not break the clip path.
+    ax_test = fig_test.add_axes([0, 0, 1, 1])
+    l, = ax_test.plot([-3, 3], [-3, 3])
+    # Explicit Path instead of a Rectangle uses clip path processing, instead
+    # of a clip box optimization.
+    p = mpath.Path([[0, 0], [1, 0], [1, 1], [0, 1], [0, 0]])
+    p = mpatches.PathPatch(p, transform=ax_test.transData)
+    l.set_clip_path(p)
+
+    ax_ref = fig_ref.add_axes([0, 0, 1, 1])
+    ax_ref.plot([-3, 3], [-3, 3])
+
+    ax_ref.set(xlim=(0.5, 0.75), ylim=(0.5, 0.75))
+    ax_test.set(xlim=(0.5, 0.75), ylim=(0.5, 0.75))
+
+
+def test_cull_markers():
+    x = np.random.random(20000)
+    y = np.random.random(20000)
+
+    fig, ax = plt.subplots()
+    ax.plot(x, y, 'k.')
+    ax.set_xlim(2, 3)
+
+    pdf = io.BytesIO()
+    fig.savefig(pdf, format="pdf")
+    assert len(pdf.getvalue()) < 8000
+
+    svg = io.BytesIO()
+    fig.savefig(svg, format="svg")
+    assert len(svg.getvalue()) < 20000
+
+
+@image_comparison(['hatching'], remove_text=True, style='default')
+def test_hatching():
+    fig, ax = plt.subplots(1, 1)
+
+    # Default hatch color.
+    rect1 = mpatches.Rectangle((0, 0), 3, 4, hatch='/')
+    ax.add_patch(rect1)
+
+    rect2 = mcollections.RegularPolyCollection(
+        4, sizes=[16000], offsets=[(1.5, 6.5)], offset_transform=ax.transData,
+        hatch='/')
+    ax.add_collection(rect2)
+
+    # Ensure edge color is not applied to hatching.
+    rect3 = mpatches.Rectangle((4, 0), 3, 4, hatch='/', edgecolor='C1')
+    ax.add_patch(rect3)
+
+    rect4 = mcollections.RegularPolyCollection(
+        4, sizes=[16000], offsets=[(5.5, 6.5)], offset_transform=ax.transData,
+        hatch='/', edgecolor='C1')
+    ax.add_collection(rect4)
+
+    ax.set_xlim(0, 7)
+    ax.set_ylim(0, 9)
+
+
+def test_remove():
+    fig, ax = plt.subplots()
+    im = ax.imshow(np.arange(36).reshape(6, 6))
+    ln, = ax.plot(range(5))
+
+    assert fig.stale
+    assert ax.stale
+
+    fig.canvas.draw()
+    assert not fig.stale
+    assert not ax.stale
+    assert not ln.stale
+
+    assert im in ax._mouseover_set
+    assert ln not in ax._mouseover_set
+    assert im.axes is ax
+
+    im.remove()
+    ln.remove()
+
+    for art in [im, ln]:
+        assert art.axes is None
+        assert art.figure is None
+
+    assert im not in ax._mouseover_set
+    assert fig.stale
+    assert ax.stale
+
+
+@image_comparison(["default_edges.png"], remove_text=True, style='default')
+def test_default_edges():
+    # Remove this line when this test image is regenerated.
+    plt.rcParams['text.kerning_factor'] = 6
+
+    fig, [[ax1, ax2], [ax3, ax4]] = plt.subplots(2, 2)
+
+    ax1.plot(np.arange(10), np.arange(10), 'x',
+             np.arange(10) + 1, np.arange(10), 'o')
+    ax2.bar(np.arange(10), np.arange(10), align='edge')
+    ax3.text(0, 0, "BOX", size=24, bbox=dict(boxstyle='sawtooth'))
+    ax3.set_xlim((-1, 1))
+    ax3.set_ylim((-1, 1))
+    pp1 = mpatches.PathPatch(
+        mpath.Path([(0, 0), (1, 0), (1, 1), (0, 0)],
+                   [mpath.Path.MOVETO, mpath.Path.CURVE3,
+                    mpath.Path.CURVE3, mpath.Path.CLOSEPOLY]),
+        fc="none", transform=ax4.transData)
+    ax4.add_patch(pp1)
+
+
+def test_properties():
+    ln = mlines.Line2D([], [])
+    ln.properties()  # Check that no warning is emitted.
+
+
+def test_setp():
+    # Check empty list
+    plt.setp([])
+    plt.setp([[]])
+
+    # Check arbitrary iterables
+    fig, ax = plt.subplots()
+    lines1 = ax.plot(range(3))
+    lines2 = ax.plot(range(3))
+    martist.setp(chain(lines1, lines2), 'lw', 5)
+    plt.setp(ax.spines.values(), color='green')
+
+    # Check *file* argument
+    sio = io.StringIO()
+    plt.setp(lines1, 'zorder', file=sio)
+    assert sio.getvalue() == '  zorder: float\n'
+
+
+def test_None_zorder():
+    fig, ax = plt.subplots()
+    ln, = ax.plot(range(5), zorder=None)
+    assert ln.get_zorder() == mlines.Line2D.zorder
+    ln.set_zorder(123456)
+    assert ln.get_zorder() == 123456
+    ln.set_zorder(None)
+    assert ln.get_zorder() == mlines.Line2D.zorder
+
+
+@pytest.mark.parametrize('accept_clause, expected', [
+    ('', 'unknown'),
+    ("ACCEPTS: [ '-' | '--' | '-.' ]", "[ '-' | '--' | '-.' ]"),
+    ('ACCEPTS: Some description.', 'Some description.'),
+    ('.. ACCEPTS: Some description.', 'Some description.'),
+    ('arg : int', 'int'),
+    ('*arg : int', 'int'),
+    ('arg : int\nACCEPTS: Something else.', 'Something else. '),
+])
+def test_artist_inspector_get_valid_values(accept_clause, expected):
+    class TestArtist(martist.Artist):
+        def set_f(self, arg):
+            pass
+
+    TestArtist.set_f.__doc__ = """
+    Some text.
+
+    %s
+    """ % accept_clause
+    valid_values = martist.ArtistInspector(TestArtist).get_valid_values('f')
+    assert valid_values == expected
+
+
+def test_artist_inspector_get_aliases():
+    # test the correct format and type of get_aliases method
+    ai = martist.ArtistInspector(mlines.Line2D)
+    aliases = ai.get_aliases()
+    assert aliases["linewidth"] == {"lw"}
+
+
+def test_set_alpha():
+    art = martist.Artist()
+    with pytest.raises(TypeError, match='^alpha must be numeric or None'):
+        art.set_alpha('string')
+    with pytest.raises(TypeError, match='^alpha must be numeric or None'):
+        art.set_alpha([1, 2, 3])
+    with pytest.raises(ValueError, match="outside 0-1 range"):
+        art.set_alpha(1.1)
+    with pytest.raises(ValueError, match="outside 0-1 range"):
+        art.set_alpha(np.nan)
+
+
+def test_set_alpha_for_array():
+    art = martist.Artist()
+    with pytest.raises(TypeError, match='^alpha must be numeric or None'):
+        art._set_alpha_for_array('string')
+    with pytest.raises(ValueError, match="outside 0-1 range"):
+        art._set_alpha_for_array(1.1)
+    with pytest.raises(ValueError, match="outside 0-1 range"):
+        art._set_alpha_for_array(np.nan)
+    with pytest.raises(ValueError, match="alpha must be between 0 and 1"):
+        art._set_alpha_for_array([0.5, 1.1])
+    with pytest.raises(ValueError, match="alpha must be between 0 and 1"):
+        art._set_alpha_for_array([0.5, np.nan])
+
+
+def test_callbacks():
+    def func(artist):
+        func.counter += 1
+
+    func.counter = 0
+
+    art = martist.Artist()
+    oid = art.add_callback(func)
+    assert func.counter == 0
+    art.pchanged()  # must call the callback
+    assert func.counter == 1
+    art.set_zorder(10)  # setting a property must also call the callback
+    assert func.counter == 2
+    art.remove_callback(oid)
+    art.pchanged()  # must not call the callback anymore
+    assert func.counter == 2
+
+
+def test_set_signature():
+    """Test autogenerated ``set()`` for Artist subclasses."""
+    class MyArtist1(martist.Artist):
+        def set_myparam1(self, val):
+            pass
+
+    assert hasattr(MyArtist1.set, '_autogenerated_signature')
+    assert 'myparam1' in MyArtist1.set.__doc__
+
+    class MyArtist2(MyArtist1):
+        def set_myparam2(self, val):
+            pass
+
+    assert hasattr(MyArtist2.set, '_autogenerated_signature')
+    assert 'myparam1' in MyArtist2.set.__doc__
+    assert 'myparam2' in MyArtist2.set.__doc__
+
+
+def test_set_is_overwritten():
+    """set() defined in Artist subclasses should not be overwritten."""
+    class MyArtist3(martist.Artist):
+
+        def set(self, **kwargs):
+            """Not overwritten."""
+
+    assert not hasattr(MyArtist3.set, '_autogenerated_signature')
+    assert MyArtist3.set.__doc__ == "Not overwritten."
+
+    class MyArtist4(MyArtist3):
+        pass
+
+    assert MyArtist4.set is MyArtist3.set
+
+
+def test_format_cursor_data_BoundaryNorm():
+    """Test if cursor data is correct when using BoundaryNorm."""
+    X = np.empty((3, 3))
+    X[0, 0] = 0.9
+    X[0, 1] = 0.99
+    X[0, 2] = 0.999
+    X[1, 0] = -1
+    X[1, 1] = 0
+    X[1, 2] = 1
+    X[2, 0] = 0.09
+    X[2, 1] = 0.009
+    X[2, 2] = 0.0009
+
+    # map range -1..1 to 0..256 in 0.1 steps
+    fig, ax = plt.subplots()
+    fig.suptitle("-1..1 to 0..256 in 0.1")
+    norm = mcolors.BoundaryNorm(np.linspace(-1, 1, 20), 256)
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+
+    labels_list = [
+        "[0.9]",
+        "[1.]",
+        "[1.]",
+        "[-1.0]",
+        "[0.0]",
+        "[1.0]",
+        "[0.09]",
+        "[0.009]",
+        "[0.0009]",
+    ]
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.1))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    # map range -1..1 to 0..256 in 0.01 steps
+    fig, ax = plt.subplots()
+    fig.suptitle("-1..1 to 0..256 in 0.01")
+    cmap = mpl.colormaps['RdBu_r'].resampled(200)
+    norm = mcolors.BoundaryNorm(np.linspace(-1, 1, 200), 200)
+    img = ax.imshow(X, cmap=cmap, norm=norm)
+
+    labels_list = [
+        "[0.90]",
+        "[0.99]",
+        "[1.0]",
+        "[-1.00]",
+        "[0.00]",
+        "[1.00]",
+        "[0.09]",
+        "[0.009]",
+        "[0.0009]",
+    ]
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.01))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    # map range -1..1 to 0..256 in 0.01 steps
+    fig, ax = plt.subplots()
+    fig.suptitle("-1..1 to 0..256 in 0.001")
+    cmap = mpl.colormaps['RdBu_r'].resampled(2000)
+    norm = mcolors.BoundaryNorm(np.linspace(-1, 1, 2000), 2000)
+    img = ax.imshow(X, cmap=cmap, norm=norm)
+
+    labels_list = [
+        "[0.900]",
+        "[0.990]",
+        "[0.999]",
+        "[-1.000]",
+        "[0.000]",
+        "[1.000]",
+        "[0.090]",
+        "[0.009]",
+        "[0.0009]",
+    ]
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.001))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    # different testing data set with
+    # out of bounds values for 0..1 range
+    X = np.empty((7, 1))
+    X[0] = -1.0
+    X[1] = 0.0
+    X[2] = 0.1
+    X[3] = 0.5
+    X[4] = 0.9
+    X[5] = 1.0
+    X[6] = 2.0
+
+    labels_list = [
+        "[-1.0]",
+        "[0.0]",
+        "[0.1]",
+        "[0.5]",
+        "[0.9]",
+        "[1.0]",
+        "[2.0]",
+    ]
+
+    fig, ax = plt.subplots()
+    fig.suptitle("noclip, neither")
+    norm = mcolors.BoundaryNorm(
+        np.linspace(0, 1, 4, endpoint=True), 256, clip=False, extend='neither')
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.33))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    fig, ax = plt.subplots()
+    fig.suptitle("noclip, min")
+    norm = mcolors.BoundaryNorm(
+        np.linspace(0, 1, 4, endpoint=True), 256, clip=False, extend='min')
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.33))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    fig, ax = plt.subplots()
+    fig.suptitle("noclip, max")
+    norm = mcolors.BoundaryNorm(
+        np.linspace(0, 1, 4, endpoint=True), 256, clip=False, extend='max')
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.33))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    fig, ax = plt.subplots()
+    fig.suptitle("noclip, both")
+    norm = mcolors.BoundaryNorm(
+        np.linspace(0, 1, 4, endpoint=True), 256, clip=False, extend='both')
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.33))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+    fig, ax = plt.subplots()
+    fig.suptitle("clip, neither")
+    norm = mcolors.BoundaryNorm(
+        np.linspace(0, 1, 4, endpoint=True), 256, clip=True, extend='neither')
+    img = ax.imshow(X, cmap='RdBu_r', norm=norm)
+    for v, label in zip(X.flat, labels_list):
+        # label = "[{:-#.{}g}]".format(v, cbook._g_sig_digits(v, 0.33))
+        assert img.format_cursor_data(v) == label
+
+    plt.close()
+
+
+def test_auto_no_rasterize():
+    class Gen1(martist.Artist):
+        ...
+
+    assert 'draw' in Gen1.__dict__
+    assert Gen1.__dict__['draw'] is Gen1.draw
+
+    class Gen2(Gen1):
+        ...
+
+    assert 'draw' not in Gen2.__dict__
+    assert Gen2.draw is Gen1.draw
+
+
+def test_draw_wraper_forward_input():
+    class TestKlass(martist.Artist):
+        def draw(self, renderer, extra):
+            return extra
+
+    art = TestKlass()
+    renderer = mbackend_bases.RendererBase()
+
+    assert 'aardvark' == art.draw(renderer, 'aardvark')
+    assert 'aardvark' == art.draw(renderer, extra='aardvark')

plotter-app/venv/lib/python3.8/site-packages/matplotlib/tests/test_axis.py

@@ -0,0 +1,10 @@
+import numpy as np
+
+import matplotlib.pyplot as plt
+from matplotlib.axis import XTick
+
+
+def test_tick_labelcolor_array():
+    # Smoke test that we can instantiate a Tick with labelcolor as array.
+    ax = plt.axes()
+    XTick(ax, 0, labelcolor=np.array([1, 0, 0, 1]))