441 lines
14 KiB
Python
441 lines
14 KiB
Python
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"""
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Tests specific to the lines module.
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"""
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import itertools
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import platform
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import timeit
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from types import SimpleNamespace
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from cycler import cycler
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import numpy as np
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from numpy.testing import assert_array_equal
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import pytest
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import matplotlib
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import matplotlib as mpl
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from matplotlib import _path
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import matplotlib.lines as mlines
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from matplotlib.markers import MarkerStyle
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from matplotlib.path import Path
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import matplotlib.pyplot as plt
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import matplotlib.transforms as mtransforms
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from matplotlib.testing.decorators import image_comparison, check_figures_equal
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def test_segment_hits():
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"""Test a problematic case."""
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cx, cy = 553, 902
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x, y = np.array([553., 553.]), np.array([95., 947.])
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radius = 6.94
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assert_array_equal(mlines.segment_hits(cx, cy, x, y, radius), [0])
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# Runtimes on a loaded system are inherently flaky. Not so much that a rerun
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# won't help, hopefully.
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@pytest.mark.flaky(reruns=3)
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def test_invisible_Line_rendering():
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"""
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GitHub issue #1256 identified a bug in Line.draw method
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Despite visibility attribute set to False, the draw method was not
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returning early enough and some pre-rendering code was executed
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though not necessary.
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Consequence was an excessive draw time for invisible Line instances
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holding a large number of points (Npts> 10**6)
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"""
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# Creates big x and y data:
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N = 10**7
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x = np.linspace(0, 1, N)
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y = np.random.normal(size=N)
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# Create a plot figure:
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fig = plt.figure()
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ax = plt.subplot()
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# Create a "big" Line instance:
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l = mlines.Line2D(x, y)
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l.set_visible(False)
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# but don't add it to the Axis instance `ax`
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# [here Interactive panning and zooming is pretty responsive]
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# Time the canvas drawing:
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t_no_line = min(timeit.repeat(fig.canvas.draw, number=1, repeat=3))
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# (gives about 25 ms)
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# Add the big invisible Line:
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ax.add_line(l)
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# [Now interactive panning and zooming is very slow]
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# Time the canvas drawing:
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t_invisible_line = min(timeit.repeat(fig.canvas.draw, number=1, repeat=3))
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# gives about 290 ms for N = 10**7 pts
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slowdown_factor = t_invisible_line / t_no_line
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slowdown_threshold = 2 # trying to avoid false positive failures
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assert slowdown_factor < slowdown_threshold
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def test_set_line_coll_dash():
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fig, ax = plt.subplots()
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np.random.seed(0)
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# Testing setting linestyles for line collections.
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# This should not produce an error.
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ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
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def test_invalid_line_data():
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with pytest.raises(RuntimeError, match='xdata must be'):
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mlines.Line2D(0, [])
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with pytest.raises(RuntimeError, match='ydata must be'):
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mlines.Line2D([], 1)
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line = mlines.Line2D([], [])
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# when deprecation cycle is completed
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# with pytest.raises(RuntimeError, match='x must be'):
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with pytest.warns(mpl.MatplotlibDeprecationWarning):
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line.set_xdata(0)
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# with pytest.raises(RuntimeError, match='y must be'):
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with pytest.warns(mpl.MatplotlibDeprecationWarning):
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line.set_ydata(0)
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@image_comparison(['line_dashes'], remove_text=True, tol=0.002)
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def test_line_dashes():
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# Tolerance introduced after reordering of floating-point operations
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# Remove when regenerating the images
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fig, ax = plt.subplots()
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ax.plot(range(10), linestyle=(0, (3, 3)), lw=5)
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def test_line_colors():
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fig, ax = plt.subplots()
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ax.plot(range(10), color='none')
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ax.plot(range(10), color='r')
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ax.plot(range(10), color='.3')
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ax.plot(range(10), color=(1, 0, 0, 1))
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ax.plot(range(10), color=(1, 0, 0))
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fig.canvas.draw()
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def test_valid_colors():
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line = mlines.Line2D([], [])
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with pytest.raises(ValueError):
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line.set_color("foobar")
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def test_linestyle_variants():
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fig, ax = plt.subplots()
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for ls in ["-", "solid", "--", "dashed",
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"-.", "dashdot", ":", "dotted",
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(0, None), (0, ()), (0, []), # gh-22930
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]:
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ax.plot(range(10), linestyle=ls)
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fig.canvas.draw()
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def test_valid_linestyles():
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line = mlines.Line2D([], [])
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with pytest.raises(ValueError):
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line.set_linestyle('aardvark')
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@image_comparison(['drawstyle_variants.png'], remove_text=True)
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def test_drawstyle_variants():
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fig, axs = plt.subplots(6)
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dss = ["default", "steps-mid", "steps-pre", "steps-post", "steps", None]
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# We want to check that drawstyles are properly handled even for very long
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# lines (for which the subslice optimization is on); however, we need
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# to zoom in so that the difference between the drawstyles is actually
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# visible.
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for ax, ds in zip(axs.flat, dss):
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ax.plot(range(2000), drawstyle=ds)
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ax.set(xlim=(0, 2), ylim=(0, 2))
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@check_figures_equal(extensions=('png',))
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def test_no_subslice_with_transform(fig_ref, fig_test):
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ax = fig_ref.add_subplot()
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x = np.arange(2000)
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ax.plot(x + 2000, x)
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ax = fig_test.add_subplot()
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t = mtransforms.Affine2D().translate(2000.0, 0.0)
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ax.plot(x, x, transform=t+ax.transData)
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def test_valid_drawstyles():
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line = mlines.Line2D([], [])
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with pytest.raises(ValueError):
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line.set_drawstyle('foobar')
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def test_set_drawstyle():
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x = np.linspace(0, 2*np.pi, 10)
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y = np.sin(x)
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fig, ax = plt.subplots()
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line, = ax.plot(x, y)
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line.set_drawstyle("steps-pre")
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assert len(line.get_path().vertices) == 2*len(x)-1
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line.set_drawstyle("default")
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assert len(line.get_path().vertices) == len(x)
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@image_comparison(
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['line_collection_dashes'], remove_text=True, style='mpl20',
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tol=0.65 if platform.machine() in ('aarch64', 'ppc64le', 's390x') else 0)
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def test_set_line_coll_dash_image():
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fig, ax = plt.subplots()
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np.random.seed(0)
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ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
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@image_comparison(['marker_fill_styles.png'], remove_text=True)
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def test_marker_fill_styles():
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colors = itertools.cycle([[0, 0, 1], 'g', '#ff0000', 'c', 'm', 'y',
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np.array([0, 0, 0])])
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altcolor = 'lightgreen'
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y = np.array([1, 1])
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x = np.array([0, 9])
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fig, ax = plt.subplots()
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# This hard-coded list of markers correspond to an earlier iteration of
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# MarkerStyle.filled_markers; the value of that attribute has changed but
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# we kept the old value here to not regenerate the baseline image.
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# Replace with mlines.Line2D.filled_markers when the image is regenerated.
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for j, marker in enumerate("ov^<>8sp*hHDdPX"):
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for i, fs in enumerate(mlines.Line2D.fillStyles):
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color = next(colors)
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ax.plot(j * 10 + x, y + i + .5 * (j % 2),
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marker=marker,
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markersize=20,
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markerfacecoloralt=altcolor,
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fillstyle=fs,
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label=fs,
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linewidth=5,
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color=color,
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markeredgecolor=color,
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markeredgewidth=2)
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ax.set_ylim([0, 7.5])
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ax.set_xlim([-5, 155])
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def test_markerfacecolor_fillstyle():
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"""Test that markerfacecolor does not override fillstyle='none'."""
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l, = plt.plot([1, 3, 2], marker=MarkerStyle('o', fillstyle='none'),
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markerfacecolor='red')
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assert l.get_fillstyle() == 'none'
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assert l.get_markerfacecolor() == 'none'
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@image_comparison(['scaled_lines'], style='default')
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def test_lw_scaling():
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th = np.linspace(0, 32)
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fig, ax = plt.subplots()
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lins_styles = ['dashed', 'dotted', 'dashdot']
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cy = cycler(matplotlib.rcParams['axes.prop_cycle'])
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for j, (ls, sty) in enumerate(zip(lins_styles, cy)):
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for lw in np.linspace(.5, 10, 10):
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ax.plot(th, j*np.ones(50) + .1 * lw, linestyle=ls, lw=lw, **sty)
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def test_is_sorted_and_has_non_nan():
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assert _path.is_sorted_and_has_non_nan(np.array([1, 2, 3]))
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assert _path.is_sorted_and_has_non_nan(np.array([1, np.nan, 3]))
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assert not _path.is_sorted_and_has_non_nan([3, 5] + [np.nan] * 100 + [0, 2])
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# [2, 256] byteswapped:
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assert not _path.is_sorted_and_has_non_nan(np.array([33554432, 65536], ">i4"))
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n = 2 * mlines.Line2D._subslice_optim_min_size
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plt.plot([np.nan] * n, range(n))
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@check_figures_equal()
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def test_step_markers(fig_test, fig_ref):
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fig_test.subplots().step([0, 1], "-o")
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fig_ref.subplots().plot([0, 0, 1], [0, 1, 1], "-o", markevery=[0, 2])
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@pytest.mark.parametrize("parent", ["figure", "axes"])
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@check_figures_equal(extensions=('png',))
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def test_markevery(fig_test, fig_ref, parent):
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np.random.seed(42)
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x = np.linspace(0, 1, 14)
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y = np.random.rand(len(x))
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cases_test = [None, 4, (2, 5), [1, 5, 11],
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[0, -1], slice(5, 10, 2),
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np.arange(len(x))[y > 0.5],
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0.3, (0.3, 0.4)]
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cases_ref = ["11111111111111", "10001000100010", "00100001000010",
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"01000100000100", "10000000000001", "00000101010000",
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"01110001110110", "11011011011110", "01010011011101"]
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if parent == "figure":
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# float markevery ("relative to axes size") is not supported.
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cases_test = cases_test[:-2]
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cases_ref = cases_ref[:-2]
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def add_test(x, y, *, markevery):
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fig_test.add_artist(
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mlines.Line2D(x, y, marker="o", markevery=markevery))
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def add_ref(x, y, *, markevery):
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fig_ref.add_artist(
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mlines.Line2D(x, y, marker="o", markevery=markevery))
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elif parent == "axes":
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axs_test = iter(fig_test.subplots(3, 3).flat)
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axs_ref = iter(fig_ref.subplots(3, 3).flat)
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def add_test(x, y, *, markevery):
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next(axs_test).plot(x, y, "-gD", markevery=markevery)
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def add_ref(x, y, *, markevery):
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next(axs_ref).plot(x, y, "-gD", markevery=markevery)
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for case in cases_test:
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add_test(x, y, markevery=case)
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for case in cases_ref:
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me = np.array(list(case)).astype(int).astype(bool)
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add_ref(x, y, markevery=me)
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def test_markevery_figure_line_unsupported_relsize():
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fig = plt.figure()
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fig.add_artist(mlines.Line2D([0, 1], [0, 1], marker="o", markevery=.5))
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with pytest.raises(ValueError):
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fig.canvas.draw()
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def test_marker_as_markerstyle():
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fig, ax = plt.subplots()
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line, = ax.plot([2, 4, 3], marker=MarkerStyle("D"))
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fig.canvas.draw()
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assert line.get_marker() == "D"
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# continue with smoke tests:
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line.set_marker("s")
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fig.canvas.draw()
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line.set_marker(MarkerStyle("o"))
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fig.canvas.draw()
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# test Path roundtrip
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triangle1 = Path._create_closed([[-1, -1], [1, -1], [0, 2]])
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line2, = ax.plot([1, 3, 2], marker=MarkerStyle(triangle1), ms=22)
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line3, = ax.plot([0, 2, 1], marker=triangle1, ms=22)
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assert_array_equal(line2.get_marker().vertices, triangle1.vertices)
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assert_array_equal(line3.get_marker().vertices, triangle1.vertices)
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@image_comparison(['striped_line.png'], remove_text=True, style='mpl20')
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def test_striped_lines():
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rng = np.random.default_rng(19680801)
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_, ax = plt.subplots()
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ax.plot(rng.uniform(size=12), color='orange', gapcolor='blue',
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linestyle='--', lw=5, label=' ')
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ax.plot(rng.uniform(size=12), color='red', gapcolor='black',
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linestyle=(0, (2, 5, 4, 2)), lw=5, label=' ', alpha=0.5)
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ax.legend(handlelength=5)
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|
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@check_figures_equal()
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def test_odd_dashes(fig_test, fig_ref):
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fig_test.add_subplot().plot([1, 2], dashes=[1, 2, 3])
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fig_ref.add_subplot().plot([1, 2], dashes=[1, 2, 3, 1, 2, 3])
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|
|
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||
|
|
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def test_picking():
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fig, ax = plt.subplots()
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mouse_event = SimpleNamespace(x=fig.bbox.width // 2,
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y=fig.bbox.height // 2 + 15)
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|
|
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|
# Default pickradius is 5, so event should not pick this line.
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|
l0, = ax.plot([0, 1], [0, 1], picker=True)
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|
found, indices = l0.contains(mouse_event)
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|
assert not found
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||
|
|
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||
|
|
# But with a larger pickradius, this should be picked.
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|
|
l1, = ax.plot([0, 1], [0, 1], picker=True, pickradius=20)
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|
|
found, indices = l1.contains(mouse_event)
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||
|
|
assert found
|
||
|
|
assert_array_equal(indices['ind'], [0])
|
||
|
|
|
||
|
|
# And if we modify the pickradius after creation, it should work as well.
|
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|
|
l2, = ax.plot([0, 1], [0, 1], picker=True)
|
||
|
|
found, indices = l2.contains(mouse_event)
|
||
|
|
assert not found
|
||
|
|
l2.set_pickradius(20)
|
||
|
|
found, indices = l2.contains(mouse_event)
|
||
|
|
assert found
|
||
|
|
assert_array_equal(indices['ind'], [0])
|
||
|
|
|
||
|
|
|
||
|
|
@check_figures_equal()
|
||
|
|
def test_input_copy(fig_test, fig_ref):
|
||
|
|
|
||
|
|
t = np.arange(0, 6, 2)
|
||
|
|
l, = fig_test.add_subplot().plot(t, t, ".-")
|
||
|
|
t[:] = range(3)
|
||
|
|
# Trigger cache invalidation
|
||
|
|
l.set_drawstyle("steps")
|
||
|
|
fig_ref.add_subplot().plot([0, 2, 4], [0, 2, 4], ".-", drawstyle="steps")
|
||
|
|
|
||
|
|
|
||
|
|
@check_figures_equal(extensions=["png"])
|
||
|
|
def test_markevery_prop_cycle(fig_test, fig_ref):
|
||
|
|
"""Test that we can set markevery prop_cycle."""
|
||
|
|
cases = [None, 8, (30, 8), [16, 24, 30], [0, -1],
|
||
|
|
slice(100, 200, 3), 0.1, 0.3, 1.5,
|
||
|
|
(0.0, 0.1), (0.45, 0.1)]
|
||
|
|
|
||
|
|
cmap = mpl.colormaps['jet']
|
||
|
|
colors = cmap(np.linspace(0.2, 0.8, len(cases)))
|
||
|
|
|
||
|
|
x = np.linspace(-1, 1)
|
||
|
|
y = 5 * x**2
|
||
|
|
|
||
|
|
axs = fig_ref.add_subplot()
|
||
|
|
for i, markevery in enumerate(cases):
|
||
|
|
axs.plot(y - i, 'o-', markevery=markevery, color=colors[i])
|
||
|
|
|
||
|
|
matplotlib.rcParams['axes.prop_cycle'] = cycler(markevery=cases,
|
||
|
|
color=colors)
|
||
|
|
|
||
|
|
ax = fig_test.add_subplot()
|
||
|
|
for i, _ in enumerate(cases):
|
||
|
|
ax.plot(y - i, 'o-')
|
||
|
|
|
||
|
|
|
||
|
|
def test_axline_setters():
|
||
|
|
fig, ax = plt.subplots()
|
||
|
|
line1 = ax.axline((.1, .1), slope=0.6)
|
||
|
|
line2 = ax.axline((.1, .1), (.8, .4))
|
||
|
|
# Testing xy1, xy2 and slope setters.
|
||
|
|
# This should not produce an error.
|
||
|
|
line1.set_xy1(.2, .3)
|
||
|
|
line1.set_slope(2.4)
|
||
|
|
line2.set_xy1(.3, .2)
|
||
|
|
line2.set_xy2(.6, .8)
|
||
|
|
# Testing xy1, xy2 and slope getters.
|
||
|
|
# Should return the modified values.
|
||
|
|
assert line1.get_xy1() == (.2, .3)
|
||
|
|
assert line1.get_slope() == 2.4
|
||
|
|
assert line2.get_xy1() == (.3, .2)
|
||
|
|
assert line2.get_xy2() == (.6, .8)
|
||
|
|
# Testing setting xy2 and slope together.
|
||
|
|
# These test should raise a ValueError
|
||
|
|
with pytest.raises(ValueError,
|
||
|
|
match="Cannot set an 'xy2' value while 'slope' is set"):
|
||
|
|
line1.set_xy2(.2, .3)
|
||
|
|
|
||
|
|
with pytest.raises(ValueError,
|
||
|
|
match="Cannot set a 'slope' value while 'xy2' is set"):
|
||
|
|
line2.set_slope(3)
|