Traktor/myenv/Lib/site-packages/matplotlib/tests/test_artist.py

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2024-05-23 01:57:24 +02:00
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')