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Mini Shell
Mini Shell
import io
from types import SimpleNamespace
import numpy as np
from numpy.testing import assert_array_equal, assert_array_almost_equal
import pytest
import matplotlib as mpl
import matplotlib.pyplot as plt
from matplotlib.backend_bases import MouseEvent
import matplotlib.collections as mcollections
import matplotlib.colors as mcolors
import matplotlib.transforms as mtransforms
from matplotlib.collections import (Collection, LineCollection,
EventCollection, PolyCollection)
from matplotlib.testing.decorators import check_figures_equal, image_comparison
from matplotlib._api.deprecation import MatplotlibDeprecationWarning
def generate_EventCollection_plot():
"""Generate the initial collection and plot it."""
positions = np.array([0., 1., 2., 3., 5., 8., 13., 21.])
extra_positions = np.array([34., 55., 89.])
orientation = 'horizontal'
lineoffset = 1
linelength = .5
linewidth = 2
color = [1, 0, 0, 1]
linestyle = 'solid'
antialiased = True
coll = EventCollection(positions,
orientation=orientation,
lineoffset=lineoffset,
linelength=linelength,
linewidth=linewidth,
color=color,
linestyle=linestyle,
antialiased=antialiased
)
fig, ax = plt.subplots()
ax.add_collection(coll)
ax.set_title('EventCollection: default')
props = {'positions': positions,
'extra_positions': extra_positions,
'orientation': orientation,
'lineoffset': lineoffset,
'linelength': linelength,
'linewidth': linewidth,
'color': color,
'linestyle': linestyle,
'antialiased': antialiased
}
ax.set_xlim(-1, 22)
ax.set_ylim(0, 2)
return ax, coll, props
@image_comparison(['EventCollection_plot__default'])
def test__EventCollection__get_props():
_, coll, props = generate_EventCollection_plot()
# check that the default segments have the correct coordinates
check_segments(coll,
props['positions'],
props['linelength'],
props['lineoffset'],
props['orientation'])
# check that the default positions match the input positions
np.testing.assert_array_equal(props['positions'], coll.get_positions())
# check that the default orientation matches the input orientation
assert props['orientation'] == coll.get_orientation()
# check that the default orientation matches the input orientation
assert coll.is_horizontal()
# check that the default linelength matches the input linelength
assert props['linelength'] == coll.get_linelength()
# check that the default lineoffset matches the input lineoffset
assert props['lineoffset'] == coll.get_lineoffset()
# check that the default linestyle matches the input linestyle
assert coll.get_linestyle() == [(0, None)]
# check that the default color matches the input color
for color in [coll.get_color(), *coll.get_colors()]:
np.testing.assert_array_equal(color, props['color'])
@image_comparison(['EventCollection_plot__set_positions'])
def test__EventCollection__set_positions():
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'], props['extra_positions']])
coll.set_positions(new_positions)
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll, new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: set_positions')
splt.set_xlim(-1, 90)
@image_comparison(['EventCollection_plot__add_positions'])
def test__EventCollection__add_positions():
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][0]])
coll.switch_orientation() # Test adding in the vertical orientation, too.
coll.add_positions(props['extra_positions'][0])
coll.switch_orientation()
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: add_positions')
splt.set_xlim(-1, 35)
@image_comparison(['EventCollection_plot__append_positions'])
def test__EventCollection__append_positions():
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][2]])
coll.append_positions(props['extra_positions'][2])
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: append_positions')
splt.set_xlim(-1, 90)
@image_comparison(['EventCollection_plot__extend_positions'])
def test__EventCollection__extend_positions():
splt, coll, props = generate_EventCollection_plot()
new_positions = np.hstack([props['positions'],
props['extra_positions'][1:]])
coll.extend_positions(props['extra_positions'][1:])
np.testing.assert_array_equal(new_positions, coll.get_positions())
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: extend_positions')
splt.set_xlim(-1, 90)
@image_comparison(['EventCollection_plot__switch_orientation'])
def test__EventCollection__switch_orientation():
splt, coll, props = generate_EventCollection_plot()
new_orientation = 'vertical'
coll.switch_orientation()
assert new_orientation == coll.get_orientation()
assert not coll.is_horizontal()
new_positions = coll.get_positions()
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'], new_orientation)
splt.set_title('EventCollection: switch_orientation')
splt.set_ylim(-1, 22)
splt.set_xlim(0, 2)
@image_comparison(['EventCollection_plot__switch_orientation__2x'])
def test__EventCollection__switch_orientation_2x():
"""
Check that calling switch_orientation twice sets the orientation back to
the default.
"""
splt, coll, props = generate_EventCollection_plot()
coll.switch_orientation()
coll.switch_orientation()
new_positions = coll.get_positions()
assert props['orientation'] == coll.get_orientation()
assert coll.is_horizontal()
np.testing.assert_array_equal(props['positions'], new_positions)
check_segments(coll,
new_positions,
props['linelength'],
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: switch_orientation 2x')
@image_comparison(['EventCollection_plot__set_orientation'])
def test__EventCollection__set_orientation():
splt, coll, props = generate_EventCollection_plot()
new_orientation = 'vertical'
coll.set_orientation(new_orientation)
assert new_orientation == coll.get_orientation()
assert not coll.is_horizontal()
check_segments(coll,
props['positions'],
props['linelength'],
props['lineoffset'],
new_orientation)
splt.set_title('EventCollection: set_orientation')
splt.set_ylim(-1, 22)
splt.set_xlim(0, 2)
@image_comparison(['EventCollection_plot__set_linelength'])
def test__EventCollection__set_linelength():
splt, coll, props = generate_EventCollection_plot()
new_linelength = 15
coll.set_linelength(new_linelength)
assert new_linelength == coll.get_linelength()
check_segments(coll,
props['positions'],
new_linelength,
props['lineoffset'],
props['orientation'])
splt.set_title('EventCollection: set_linelength')
splt.set_ylim(-20, 20)
@image_comparison(['EventCollection_plot__set_lineoffset'])
def test__EventCollection__set_lineoffset():
splt, coll, props = generate_EventCollection_plot()
new_lineoffset = -5.
coll.set_lineoffset(new_lineoffset)
assert new_lineoffset == coll.get_lineoffset()
check_segments(coll,
props['positions'],
props['linelength'],
new_lineoffset,
props['orientation'])
splt.set_title('EventCollection: set_lineoffset')
splt.set_ylim(-6, -4)
@image_comparison([
'EventCollection_plot__set_linestyle',
'EventCollection_plot__set_linestyle',
'EventCollection_plot__set_linewidth',
])
def test__EventCollection__set_prop():
for prop, value, expected in [
('linestyle', 'dashed', [(0, (6.0, 6.0))]),
('linestyle', (0, (6., 6.)), [(0, (6.0, 6.0))]),
('linewidth', 5, 5),
]:
splt, coll, _ = generate_EventCollection_plot()
coll.set(**{prop: value})
assert plt.getp(coll, prop) == expected
splt.set_title(f'EventCollection: set_{prop}')
@image_comparison(['EventCollection_plot__set_color'])
def test__EventCollection__set_color():
splt, coll, _ = generate_EventCollection_plot()
new_color = np.array([0, 1, 1, 1])
coll.set_color(new_color)
for color in [coll.get_color(), *coll.get_colors()]:
np.testing.assert_array_equal(color, new_color)
splt.set_title('EventCollection: set_color')
def check_segments(coll, positions, linelength, lineoffset, orientation):
"""
Test helper checking that all values in the segment are correct, given a
particular set of inputs.
"""
segments = coll.get_segments()
if (orientation.lower() == 'horizontal'
or orientation.lower() == 'none' or orientation is None):
# if horizontal, the position in is in the y-axis
pos1 = 1
pos2 = 0
elif orientation.lower() == 'vertical':
# if vertical, the position in is in the x-axis
pos1 = 0
pos2 = 1
else:
raise ValueError("orientation must be 'horizontal' or 'vertical'")
# test to make sure each segment is correct
for i, segment in enumerate(segments):
assert segment[0, pos1] == lineoffset + linelength / 2
assert segment[1, pos1] == lineoffset - linelength / 2
assert segment[0, pos2] == positions[i]
assert segment[1, pos2] == positions[i]
def test_null_collection_datalim():
col = mcollections.PathCollection([])
col_data_lim = col.get_datalim(mtransforms.IdentityTransform())
assert_array_equal(col_data_lim.get_points(),
mtransforms.Bbox.null().get_points())
def test_add_collection():
# Test if data limits are unchanged by adding an empty collection.
# GitHub issue #1490, pull #1497.
plt.figure()
ax = plt.axes()
coll = ax.scatter([0, 1], [0, 1])
ax.add_collection(coll)
bounds = ax.dataLim.bounds
coll = ax.scatter([], [])
assert ax.dataLim.bounds == bounds
@mpl.style.context('mpl20')
@check_figures_equal(extensions=['png'])
def test_collection_log_datalim(fig_test, fig_ref):
# Data limits should respect the minimum x/y when using log scale.
x_vals = [4.38462e-6, 5.54929e-6, 7.02332e-6, 8.88889e-6, 1.12500e-5,
1.42383e-5, 1.80203e-5, 2.28070e-5, 2.88651e-5, 3.65324e-5,
4.62363e-5, 5.85178e-5, 7.40616e-5, 9.37342e-5, 1.18632e-4]
y_vals = [0.0, 0.1, 0.182, 0.332, 0.604, 1.1, 2.0, 3.64, 6.64, 12.1, 22.0,
39.6, 71.3]
x, y = np.meshgrid(x_vals, y_vals)
x = x.flatten()
y = y.flatten()
ax_test = fig_test.subplots()
ax_test.set_xscale('log')
ax_test.set_yscale('log')
ax_test.margins = 0
ax_test.scatter(x, y)
ax_ref = fig_ref.subplots()
ax_ref.set_xscale('log')
ax_ref.set_yscale('log')
ax_ref.plot(x, y, marker="o", ls="")
def test_quiver_limits():
ax = plt.axes()
x, y = np.arange(8), np.arange(10)
u = v = np.linspace(0, 10, 80).reshape(10, 8)
q = plt.quiver(x, y, u, v)
assert q.get_datalim(ax.transData).bounds == (0., 0., 7., 9.)
plt.figure()
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.quiver(x, y, np.sin(x), np.cos(y), transform=trans)
assert ax.dataLim.bounds == (20.0, 30.0, 15.0, 6.0)
def test_barb_limits():
ax = plt.axes()
x = np.linspace(-5, 10, 20)
y = np.linspace(-2, 4, 10)
y, x = np.meshgrid(y, x)
trans = mtransforms.Affine2D().translate(25, 32) + ax.transData
plt.barbs(x, y, np.sin(x), np.cos(y), transform=trans)
# The calculated bounds are approximately the bounds of the original data,
# this is because the entire path is taken into account when updating the
# datalim.
assert_array_almost_equal(ax.dataLim.bounds, (20, 30, 15, 6),
decimal=1)
@image_comparison(['EllipseCollection_test_image.png'], remove_text=True)
def test_EllipseCollection():
# Test basic functionality
fig, ax = plt.subplots()
x = np.arange(4)
y = np.arange(3)
X, Y = np.meshgrid(x, y)
XY = np.vstack((X.ravel(), Y.ravel())).T
ww = X / x[-1]
hh = Y / y[-1]
aa = np.ones_like(ww) * 20 # first axis is 20 degrees CCW from x axis
ec = mcollections.EllipseCollection(ww, hh, aa,
units='x',
offsets=XY,
transOffset=ax.transData,
facecolors='none')
ax.add_collection(ec)
ax.autoscale_view()
@image_comparison(['polycollection_close.png'], remove_text=True)
def test_polycollection_close():
from mpl_toolkits.mplot3d import Axes3D
vertsQuad = [
[[0., 0.], [0., 1.], [1., 1.], [1., 0.]],
[[0., 1.], [2., 3.], [2., 2.], [1., 1.]],
[[2., 2.], [2., 3.], [4., 1.], [3., 1.]],
[[3., 0.], [3., 1.], [4., 1.], [4., 0.]]]
fig = plt.figure()
ax = fig.add_axes(Axes3D(fig, auto_add_to_figure=False))
colors = ['r', 'g', 'b', 'y', 'k']
zpos = list(range(5))
poly = mcollections.PolyCollection(
vertsQuad * len(zpos), linewidth=0.25)
poly.set_alpha(0.7)
# need to have a z-value for *each* polygon = element!
zs = []
cs = []
for z, c in zip(zpos, colors):
zs.extend([z] * len(vertsQuad))
cs.extend([c] * len(vertsQuad))
poly.set_color(cs)
ax.add_collection3d(poly, zs=zs, zdir='y')
# axis limit settings:
ax.set_xlim3d(0, 4)
ax.set_zlim3d(0, 3)
ax.set_ylim3d(0, 4)
@image_comparison(['regularpolycollection_rotate.png'], remove_text=True)
def test_regularpolycollection_rotate():
xx, yy = np.mgrid[:10, :10]
xy_points = np.transpose([xx.flatten(), yy.flatten()])
rotations = np.linspace(0, 2*np.pi, len(xy_points))
fig, ax = plt.subplots()
for xy, alpha in zip(xy_points, rotations):
col = mcollections.RegularPolyCollection(
4, sizes=(100,), rotation=alpha,
offsets=[xy], transOffset=ax.transData)
ax.add_collection(col, autolim=True)
ax.autoscale_view()
@image_comparison(['regularpolycollection_scale.png'], remove_text=True)
def test_regularpolycollection_scale():
# See issue #3860
class SquareCollection(mcollections.RegularPolyCollection):
def __init__(self, **kwargs):
super().__init__(4, rotation=np.pi/4., **kwargs)
def get_transform(self):
"""Return transform scaling circle areas to data space."""
ax = self.axes
pts2pixels = 72.0 / ax.figure.dpi
scale_x = pts2pixels * ax.bbox.width / ax.viewLim.width
scale_y = pts2pixels * ax.bbox.height / ax.viewLim.height
return mtransforms.Affine2D().scale(scale_x, scale_y)
fig, ax = plt.subplots()
xy = [(0, 0)]
# Unit square has a half-diagonal of `1/sqrt(2)`, so `pi * r**2` equals...
circle_areas = [np.pi / 2]
squares = SquareCollection(sizes=circle_areas, offsets=xy,
transOffset=ax.transData)
ax.add_collection(squares, autolim=True)
ax.axis([-1, 1, -1, 1])
def test_picking():
fig, ax = plt.subplots()
col = ax.scatter([0], [0], [1000], picker=True)
fig.savefig(io.BytesIO(), dpi=fig.dpi)
mouse_event = SimpleNamespace(x=325, y=240)
found, indices = col.contains(mouse_event)
assert found
assert_array_equal(indices['ind'], [0])
def test_linestyle_single_dashes():
plt.scatter([0, 1, 2], [0, 1, 2], linestyle=(0., [2., 2.]))
plt.draw()
@image_comparison(['size_in_xy.png'], remove_text=True)
def test_size_in_xy():
fig, ax = plt.subplots()
widths, heights, angles = (10, 10), 10, 0
widths = 10, 10
coords = [(10, 10), (15, 15)]
e = mcollections.EllipseCollection(
widths, heights, angles,
units='xy',
offsets=coords,
transOffset=ax.transData)
ax.add_collection(e)
ax.set_xlim(0, 30)
ax.set_ylim(0, 30)
def test_pandas_indexing(pd):
# Should not fail break when faced with a
# non-zero indexed series
index = [11, 12, 13]
ec = fc = pd.Series(['red', 'blue', 'green'], index=index)
lw = pd.Series([1, 2, 3], index=index)
ls = pd.Series(['solid', 'dashed', 'dashdot'], index=index)
aa = pd.Series([True, False, True], index=index)
Collection(edgecolors=ec)
Collection(facecolors=fc)
Collection(linewidths=lw)
Collection(linestyles=ls)
Collection(antialiaseds=aa)
@mpl.style.context('default')
def test_lslw_bcast():
col = mcollections.PathCollection([])
col.set_linestyles(['-', '-'])
col.set_linewidths([1, 2, 3])
assert col.get_linestyles() == [(0, None)] * 6
assert col.get_linewidths() == [1, 2, 3] * 2
col.set_linestyles(['-', '-', '-'])
assert col.get_linestyles() == [(0, None)] * 3
assert (col.get_linewidths() == [1, 2, 3]).all()
@mpl.style.context('default')
def test_capstyle():
col = mcollections.PathCollection([], capstyle='round')
assert col.get_capstyle() == 'round'
col.set_capstyle('butt')
assert col.get_capstyle() == 'butt'
@mpl.style.context('default')
def test_joinstyle():
col = mcollections.PathCollection([], joinstyle='round')
assert col.get_joinstyle() == 'round'
col.set_joinstyle('miter')
assert col.get_joinstyle() == 'miter'
@image_comparison(['cap_and_joinstyle.png'])
def test_cap_and_joinstyle_image():
fig, ax = plt.subplots()
ax.set_xlim([-0.5, 1.5])
ax.set_ylim([-0.5, 2.5])
x = np.array([0.0, 1.0, 0.5])
ys = np.array([[0.0], [0.5], [1.0]]) + np.array([[0.0, 0.0, 1.0]])
segs = np.zeros((3, 3, 2))
segs[:, :, 0] = x
segs[:, :, 1] = ys
line_segments = LineCollection(segs, linewidth=[10, 15, 20])
line_segments.set_capstyle("round")
line_segments.set_joinstyle("miter")
ax.add_collection(line_segments)
ax.set_title('Line collection with customized caps and joinstyle')
@image_comparison(['scatter_post_alpha.png'],
remove_text=True, style='default')
def test_scatter_post_alpha():
fig, ax = plt.subplots()
sc = ax.scatter(range(5), range(5), c=range(5))
sc.set_alpha(.1)
def test_scatter_alpha_array():
x = np.arange(5)
alpha = x / 5
# With colormapping.
fig, (ax0, ax1) = plt.subplots(2)
sc0 = ax0.scatter(x, x, c=x, alpha=alpha)
sc1 = ax1.scatter(x, x, c=x)
sc1.set_alpha(alpha)
plt.draw()
assert_array_equal(sc0.get_facecolors()[:, -1], alpha)
assert_array_equal(sc1.get_facecolors()[:, -1], alpha)
# Without colormapping.
fig, (ax0, ax1) = plt.subplots(2)
sc0 = ax0.scatter(x, x, color=['r', 'g', 'b', 'c', 'm'], alpha=alpha)
sc1 = ax1.scatter(x, x, color='r', alpha=alpha)
plt.draw()
assert_array_equal(sc0.get_facecolors()[:, -1], alpha)
assert_array_equal(sc1.get_facecolors()[:, -1], alpha)
# Without colormapping, and set alpha afterward.
fig, (ax0, ax1) = plt.subplots(2)
sc0 = ax0.scatter(x, x, color=['r', 'g', 'b', 'c', 'm'])
sc0.set_alpha(alpha)
sc1 = ax1.scatter(x, x, color='r')
sc1.set_alpha(alpha)
plt.draw()
assert_array_equal(sc0.get_facecolors()[:, -1], alpha)
assert_array_equal(sc1.get_facecolors()[:, -1], alpha)
def test_pathcollection_legend_elements():
np.random.seed(19680801)
x, y = np.random.rand(2, 10)
y = np.random.rand(10)
c = np.random.randint(0, 5, size=10)
s = np.random.randint(10, 300, size=10)
fig, ax = plt.subplots()
sc = ax.scatter(x, y, c=c, s=s, cmap="jet", marker="o", linewidths=0)
h, l = sc.legend_elements(fmt="{x:g}")
assert len(h) == 5
assert_array_equal(np.array(l).astype(float), np.arange(5))
colors = np.array([line.get_color() for line in h])
colors2 = sc.cmap(np.arange(5)/4)
assert_array_equal(colors, colors2)
l1 = ax.legend(h, l, loc=1)
h2, lab2 = sc.legend_elements(num=9)
assert len(h2) == 9
l2 = ax.legend(h2, lab2, loc=2)
h, l = sc.legend_elements(prop="sizes", alpha=0.5, color="red")
alpha = np.array([line.get_alpha() for line in h])
assert_array_equal(alpha, 0.5)
color = np.array([line.get_markerfacecolor() for line in h])
assert_array_equal(color, "red")
l3 = ax.legend(h, l, loc=4)
h, l = sc.legend_elements(prop="sizes", num=4, fmt="{x:.2f}",
func=lambda x: 2*x)
actsizes = [line.get_markersize() for line in h]
labeledsizes = np.sqrt(np.array(l).astype(float)/2)
assert_array_almost_equal(actsizes, labeledsizes)
l4 = ax.legend(h, l, loc=3)
loc = mpl.ticker.MaxNLocator(nbins=9, min_n_ticks=9-1,
steps=[1, 2, 2.5, 3, 5, 6, 8, 10])
h5, lab5 = sc.legend_elements(num=loc)
assert len(h2) == len(h5)
levels = [-1, 0, 55.4, 260]
h6, lab6 = sc.legend_elements(num=levels, prop="sizes", fmt="{x:g}")
assert_array_equal(np.array(lab6).astype(float), levels[2:])
for l in [l1, l2, l3, l4]:
ax.add_artist(l)
fig.canvas.draw()
def test_EventCollection_nosort():
# Check that EventCollection doesn't modify input in place
arr = np.array([3, 2, 1, 10])
coll = EventCollection(arr)
np.testing.assert_array_equal(arr, np.array([3, 2, 1, 10]))
def test_collection_set_verts_array():
verts = np.arange(80, dtype=np.double).reshape(10, 4, 2)
col_arr = PolyCollection(verts)
col_list = PolyCollection(list(verts))
assert len(col_arr._paths) == len(col_list._paths)
for ap, lp in zip(col_arr._paths, col_list._paths):
assert np.array_equal(ap._vertices, lp._vertices)
assert np.array_equal(ap._codes, lp._codes)
verts_tuple = np.empty(10, dtype=object)
verts_tuple[:] = [tuple(tuple(y) for y in x) for x in verts]
col_arr_tuple = PolyCollection(verts_tuple)
assert len(col_arr._paths) == len(col_arr_tuple._paths)
for ap, atp in zip(col_arr._paths, col_arr_tuple._paths):
assert np.array_equal(ap._vertices, atp._vertices)
assert np.array_equal(ap._codes, atp._codes)
def test_collection_set_array():
vals = [*range(10)]
# Test set_array with list
c = Collection()
c.set_array(vals)
# Test set_array with wrong dtype
with pytest.raises(TypeError, match="^Image data of dtype"):
c.set_array("wrong_input")
# Test if array kwarg is copied
vals[5] = 45
assert np.not_equal(vals, c.get_array()).any()
def test_blended_collection_autolim():
a = [1, 2, 4]
height = .2
xy_pairs = np.column_stack([np.repeat(a, 2), np.tile([0, height], len(a))])
line_segs = xy_pairs.reshape([len(a), 2, 2])
f, ax = plt.subplots()
trans = mtransforms.blended_transform_factory(ax.transData, ax.transAxes)
ax.add_collection(LineCollection(line_segs, transform=trans))
ax.autoscale_view(scalex=True, scaley=False)
np.testing.assert_allclose(ax.get_xlim(), [1., 4.])
def test_singleton_autolim():
fig, ax = plt.subplots()
ax.scatter(0, 0)
np.testing.assert_allclose(ax.get_ylim(), [-0.06, 0.06])
np.testing.assert_allclose(ax.get_xlim(), [-0.06, 0.06])
@pytest.mark.parametrize('flat_ref, kwargs', [
(True, {}),
(False, {}),
(True, dict(antialiased=False)),
(False, dict(transform='__initialization_delayed__')),
])
@check_figures_equal(extensions=['png'])
def test_quadmesh_deprecated_signature(
fig_test, fig_ref, flat_ref, kwargs):
# test that the new and old quadmesh signature produce the same results
# remove when the old QuadMesh.__init__ signature expires (v3.5+2)
from matplotlib.collections import QuadMesh
x = [0, 1, 2, 3.]
y = [1, 2, 3.]
X, Y = np.meshgrid(x, y)
X += 0.2 * Y
coords = np.stack([X, Y], axis=-1)
assert coords.shape == (3, 4, 2)
C = np.linspace(0, 2, 6).reshape(2, 3)
ax = fig_test.add_subplot()
ax.set(xlim=(0, 5), ylim=(0, 4))
if 'transform' in kwargs:
kwargs['transform'] = mtransforms.Affine2D().scale(1.2) + ax.transData
qmesh = QuadMesh(coords, **kwargs)
qmesh.set_array(C)
ax.add_collection(qmesh)
assert qmesh._shading == 'flat'
ax = fig_ref.add_subplot()
ax.set(xlim=(0, 5), ylim=(0, 4))
if 'transform' in kwargs:
kwargs['transform'] = mtransforms.Affine2D().scale(1.2) + ax.transData
with pytest.warns(MatplotlibDeprecationWarning):
qmesh = QuadMesh(4 - 1, 3 - 1,
coords.copy().reshape(-1, 2) if flat_ref else coords,
**kwargs)
qmesh.set_array(C.flatten() if flat_ref else C)
ax.add_collection(qmesh)
assert qmesh._shading == 'flat'
@check_figures_equal(extensions=['png'])
def test_quadmesh_deprecated_positional(fig_test, fig_ref):
# test that positional parameters are still accepted with the old signature
# and work correctly
# remove when the old QuadMesh.__init__ signature expires (v3.5+2)
from matplotlib.collections import QuadMesh
x = [0, 1, 2, 3.]
y = [1, 2, 3.]
X, Y = np.meshgrid(x, y)
X += 0.2 * Y
coords = np.stack([X, Y], axis=-1)
assert coords.shape == (3, 4, 2)
coords_flat = coords.copy().reshape(-1, 2)
C = np.linspace(0, 2, 12).reshape(3, 4)
ax = fig_test.add_subplot()
ax.set(xlim=(0, 5), ylim=(0, 4))
qmesh = QuadMesh(coords, antialiased=False, shading='gouraud')
qmesh.set_array(C)
ax.add_collection(qmesh)
ax = fig_ref.add_subplot()
ax.set(xlim=(0, 5), ylim=(0, 4))
with pytest.warns(MatplotlibDeprecationWarning):
qmesh = QuadMesh(4 - 1, 3 - 1, coords.copy().reshape(-1, 2),
False, 'gouraud')
qmesh.set_array(C)
ax.add_collection(qmesh)
def test_quadmesh_set_array_validation():
x = np.arange(11)
y = np.arange(8)
z = np.random.random((7, 10))
fig, ax = plt.subplots()
coll = ax.pcolormesh(x, y, z)
# Test deprecated warning when faulty shape is passed.
with pytest.warns(MatplotlibDeprecationWarning):
coll.set_array(z.reshape(10, 7))
z = np.arange(54).reshape((6, 9))
with pytest.raises(TypeError, match=r"Dimensions of A \(6, 9\) "
r"are incompatible with X \(11\) and/or Y \(8\)"):
coll.set_array(z)
with pytest.raises(TypeError, match=r"Dimensions of A \(54,\) "
r"are incompatible with X \(11\) and/or Y \(8\)"):
coll.set_array(z.ravel())
x = np.arange(10)
y = np.arange(7)
z = np.random.random((7, 10))
fig, ax = plt.subplots()
coll = ax.pcolormesh(x, y, z, shading='gouraud')
def test_quadmesh_get_coordinates():
x = [0, 1, 2]
y = [2, 4, 6]
z = np.ones(shape=(2, 2))
xx, yy = np.meshgrid(x, y)
coll = plt.pcolormesh(xx, yy, z)
# shape (3, 3, 2)
coords = np.stack([xx.T, yy.T]).T
assert_array_equal(coll.get_coordinates(), coords)
def test_quadmesh_set_array():
x = np.arange(4)
y = np.arange(4)
z = np.arange(9).reshape((3, 3))
fig, ax = plt.subplots()
coll = ax.pcolormesh(x, y, np.ones(z.shape))
# Test that the collection is able to update with a 2d array
coll.set_array(z)
fig.canvas.draw()
assert np.array_equal(coll.get_array(), z)
# Check that pre-flattened arrays work too
coll.set_array(np.ones(9))
fig.canvas.draw()
assert np.array_equal(coll.get_array(), np.ones(9))
z = np.arange(16).reshape((4, 4))
fig, ax = plt.subplots()
coll = ax.pcolormesh(x, y, np.ones(z.shape), shading='gouraud')
# Test that the collection is able to update with a 2d array
coll.set_array(z)
fig.canvas.draw()
assert np.array_equal(coll.get_array(), z)
# Check that pre-flattened arrays work too
coll.set_array(np.ones(16))
fig.canvas.draw()
assert np.array_equal(coll.get_array(), np.ones(16))
def test_quadmesh_vmin_vmax():
# test when vmin/vmax on the norm changes, the quadmesh gets updated
fig, ax = plt.subplots()
cmap = mpl.cm.get_cmap('plasma')
norm = mpl.colors.Normalize(vmin=0, vmax=1)
coll = ax.pcolormesh([[1]], cmap=cmap, norm=norm)
fig.canvas.draw()
assert np.array_equal(coll.get_facecolors()[0, :], cmap(norm(1)))
# Change the vmin/vmax of the norm so that the color is from
# the bottom of the colormap now
norm.vmin, norm.vmax = 1, 2
fig.canvas.draw()
assert np.array_equal(coll.get_facecolors()[0, :], cmap(norm(1)))
def test_quadmesh_alpha_array():
x = np.arange(4)
y = np.arange(4)
z = np.arange(9).reshape((3, 3))
alpha = z / z.max()
alpha_flat = alpha.ravel()
# Provide 2-D alpha:
fig, (ax0, ax1) = plt.subplots(2)
coll1 = ax0.pcolormesh(x, y, z, alpha=alpha)
coll2 = ax1.pcolormesh(x, y, z)
coll2.set_alpha(alpha)
plt.draw()
assert_array_equal(coll1.get_facecolors()[:, -1], alpha_flat)
assert_array_equal(coll2.get_facecolors()[:, -1], alpha_flat)
# Or provide 1-D alpha:
fig, (ax0, ax1) = plt.subplots(2)
coll1 = ax0.pcolormesh(x, y, z, alpha=alpha_flat)
coll2 = ax1.pcolormesh(x, y, z)
coll2.set_alpha(alpha_flat)
plt.draw()
assert_array_equal(coll1.get_facecolors()[:, -1], alpha_flat)
assert_array_equal(coll2.get_facecolors()[:, -1], alpha_flat)
def test_alpha_validation():
# Most of the relevant testing is in test_artist and test_colors.
fig, ax = plt.subplots()
pc = ax.pcolormesh(np.arange(12).reshape((3, 4)))
with pytest.raises(ValueError, match="^Data array shape"):
pc.set_alpha([0.5, 0.6])
pc.update_scalarmappable()
def test_legend_inverse_size_label_relationship():
"""
Ensure legend markers scale appropriately when label and size are
inversely related.
Here label = 5 / size
"""
np.random.seed(19680801)
X = np.random.random(50)
Y = np.random.random(50)
C = 1 - np.random.random(50)
S = 5 / C
legend_sizes = [0.2, 0.4, 0.6, 0.8]
fig, ax = plt.subplots()
sc = ax.scatter(X, Y, s=S)
handles, labels = sc.legend_elements(
prop='sizes', num=legend_sizes, func=lambda s: 5 / s
)
# Convert markersize scale to 's' scale
handle_sizes = [x.get_markersize() for x in handles]
handle_sizes = [5 / x**2 for x in handle_sizes]
assert_array_almost_equal(handle_sizes, legend_sizes, decimal=1)
@mpl.style.context('default')
@pytest.mark.parametrize('pcfunc', [plt.pcolor, plt.pcolormesh])
def test_color_logic(pcfunc):
z = np.arange(12).reshape(3, 4)
# Explicitly set an edgecolor.
pc = pcfunc(z, edgecolors='red', facecolors='none')
pc.update_scalarmappable() # This is called in draw().
# Define 2 reference "colors" here for multiple use.
face_default = mcolors.to_rgba_array(pc._get_default_facecolor())
mapped = pc.get_cmap()(pc.norm((z.ravel())))
# Github issue #1302:
assert mcolors.same_color(pc.get_edgecolor(), 'red')
# Check setting attributes after initialization:
pc = pcfunc(z)
pc.set_facecolor('none')
pc.set_edgecolor('red')
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), 'none')
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
pc.set_alpha(0.5)
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 0.5]])
pc.set_alpha(None) # restore default alpha
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
# Reset edgecolor to default.
pc.set_edgecolor(None)
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_edgecolor(), mapped)
pc.set_facecolor(None) # restore default for facecolor
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), mapped)
assert mcolors.same_color(pc.get_edgecolor(), 'none')
# Turn off colormapping entirely:
pc.set_array(None)
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_edgecolor(), 'none')
assert mcolors.same_color(pc.get_facecolor(), face_default) # not mapped
# Turn it back on by restoring the array (must be 1D!):
pc.set_array(z.ravel())
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), mapped)
assert mcolors.same_color(pc.get_edgecolor(), 'none')
# Give color via tuple rather than string.
pc = pcfunc(z, edgecolors=(1, 0, 0), facecolors=(0, 1, 0))
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), mapped)
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
# Provide an RGB array; mapping overrides it.
pc = pcfunc(z, edgecolors=(1, 0, 0), facecolors=np.ones((12, 3)))
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), mapped)
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
# Turn off the mapping.
pc.set_array(None)
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), np.ones((12, 3)))
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
# And an RGBA array.
pc = pcfunc(z, edgecolors=(1, 0, 0), facecolors=np.ones((12, 4)))
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), mapped)
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
# Turn off the mapping.
pc.set_array(None)
pc.update_scalarmappable()
assert mcolors.same_color(pc.get_facecolor(), np.ones((12, 4)))
assert mcolors.same_color(pc.get_edgecolor(), [[1, 0, 0, 1]])
def test_LineCollection_args():
with pytest.warns(MatplotlibDeprecationWarning):
lc = LineCollection(None, 2.2, 'r', zorder=3, facecolors=[0, 1, 0, 1])
assert lc.get_linewidth()[0] == 2.2
assert mcolors.same_color(lc.get_edgecolor(), 'r')
assert lc.get_zorder() == 3
assert mcolors.same_color(lc.get_facecolor(), [[0, 1, 0, 1]])
# To avoid breaking mplot3d, LineCollection internally sets the facecolor
# kwarg if it has not been specified. Hence we need the following test
# for LineCollection._set_default().
lc = LineCollection(None, facecolor=None)
assert mcolors.same_color(lc.get_facecolor(), 'none')
def test_array_wrong_dimensions():
z = np.arange(12).reshape(3, 4)
pc = plt.pcolor(z)
with pytest.raises(ValueError, match="^Collections can only map"):
pc.set_array(z)
pc.update_scalarmappable()
pc = plt.pcolormesh(z)
pc.set_array(z) # 2D is OK for Quadmesh
pc.update_scalarmappable()
def test_quadmesh_cursor_data():
fig, ax = plt.subplots()
*_, qm = ax.hist2d(
np.arange(11)**2, 100 + np.arange(11)**2) # width-10 bins
x, y = ax.transData.transform([1, 101])
event = MouseEvent('motion_notify_event', fig.canvas, x, y)
assert qm.get_cursor_data(event) == 4 # (0**2, 1**2, 2**2, 3**2)
for out_xydata in []:
x, y = ax.transData.transform([-1, 101])
event = MouseEvent('motion_notify_event', fig.canvas, x, y)
assert qm.get_cursor_data(event) is None
def test_get_segments():
segments = np.tile(np.linspace(0, 1, 256), (2, 1)).T
lc = LineCollection([segments])
readback, = lc.get_segments()
# these should comeback un-changed!
assert np.all(segments == readback)
def test_set_offsets_late():
identity = mtransforms.IdentityTransform()
sizes = [2]
null = mcollections.CircleCollection(sizes=sizes)
init = mcollections.CircleCollection(sizes=sizes, offsets=(10, 10))
late = mcollections.CircleCollection(sizes=sizes)
late.set_offsets((10, 10))
# Bbox.__eq__ doesn't compare bounds
null_bounds = null.get_datalim(identity).bounds
init_bounds = init.get_datalim(identity).bounds
late_bounds = late.get_datalim(identity).bounds
# offsets and transform are applied when set after initialization
assert null_bounds != init_bounds
assert init_bounds == late_bounds
def test_set_offset_transform():
with pytest.warns(MatplotlibDeprecationWarning,
match='.transOffset. without .offsets. has no effect'):
mcollections.Collection([],
transOffset=mtransforms.IdentityTransform())
skew = mtransforms.Affine2D().skew(2, 2)
init = mcollections.Collection([], offsets=[], transOffset=skew)
late = mcollections.Collection([])
late.set_offset_transform(skew)
assert skew == init.get_offset_transform() == late.get_offset_transform()
def test_set_offset_units():
# passing the offsets in initially (i.e. via scatter)
# should yield the same results as `set_offsets`
x = np.linspace(0, 10, 5)
y = np.sin(x)
d = x * np.timedelta64(24, 'h') + np.datetime64('2021-11-29')
sc = plt.scatter(d, y)
off0 = sc.get_offsets()
sc.set_offsets(list(zip(d, y)))
np.testing.assert_allclose(off0, sc.get_offsets())
# try the other way around
fig, ax = plt.subplots()
sc = ax.scatter(y, d)
off0 = sc.get_offsets()
sc.set_offsets(list(zip(y, d)))
np.testing.assert_allclose(off0, sc.get_offsets())
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