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"""
Tests specific to the lines module.
"""
import itertools
import platform
import timeit
from types import SimpleNamespace
from cycler import cycler
import numpy as np
from numpy.testing import assert_array_equal
import pytest
import matplotlib
import matplotlib as mpl
from matplotlib import _path
import matplotlib.lines as mlines
from matplotlib.markers import MarkerStyle
from matplotlib.path import Path
import matplotlib.pyplot as plt
import matplotlib.transforms as mtransforms
from matplotlib.testing.decorators import image_comparison, check_figures_equal
def test_segment_hits():
"""Test a problematic case."""
cx, cy = 553, 902
x, y = np.array([553., 553.]), np.array([95., 947.])
radius = 6.94
assert_array_equal(mlines.segment_hits(cx, cy, x, y, radius), [0])
# Runtimes on a loaded system are inherently flaky. Not so much that a rerun
# won't help, hopefully.
@pytest.mark.flaky(reruns=3)
def test_invisible_Line_rendering():
"""
GitHub issue #1256 identified a bug in Line.draw method
Despite visibility attribute set to False, the draw method was not
returning early enough and some pre-rendering code was executed
though not necessary.
Consequence was an excessive draw time for invisible Line instances
holding a large number of points (Npts> 10**6)
"""
# Creates big x and y data:
N = 10**7
x = np.linspace(0, 1, N)
y = np.random.normal(size=N)
# Create a plot figure:
fig = plt.figure()
ax = plt.subplot()
# Create a "big" Line instance:
l = mlines.Line2D(x, y)
l.set_visible(False)
# but don't add it to the Axis instance `ax`
# [here Interactive panning and zooming is pretty responsive]
# Time the canvas drawing:
t_no_line = min(timeit.repeat(fig.canvas.draw, number=1, repeat=3))
# (gives about 25 ms)
# Add the big invisible Line:
ax.add_line(l)
# [Now interactive panning and zooming is very slow]
# Time the canvas drawing:
t_invisible_line = min(timeit.repeat(fig.canvas.draw, number=1, repeat=3))
# gives about 290 ms for N = 10**7 pts
slowdown_factor = t_invisible_line / t_no_line
slowdown_threshold = 2 # trying to avoid false positive failures
assert slowdown_factor < slowdown_threshold
def test_set_line_coll_dash():
fig, ax = plt.subplots()
np.random.seed(0)
# Testing setting linestyles for line collections.
# This should not produce an error.
ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
def test_invalid_line_data():
with pytest.raises(RuntimeError, match='xdata must be'):
mlines.Line2D(0, [])
with pytest.raises(RuntimeError, match='ydata must be'):
mlines.Line2D([], 1)
line = mlines.Line2D([], [])
with pytest.raises(RuntimeError, match='x must be'):
line.set_xdata(0)
with pytest.raises(RuntimeError, match='y must be'):
line.set_ydata(0)
@image_comparison(['line_dashes'], remove_text=True, tol=0.003)
def test_line_dashes():
# Tolerance introduced after reordering of floating-point operations
# Remove when regenerating the images
fig, ax = plt.subplots()
ax.plot(range(10), linestyle=(0, (3, 3)), lw=5)
def test_line_colors():
fig, ax = plt.subplots()
ax.plot(range(10), color='none')
ax.plot(range(10), color='r')
ax.plot(range(10), color='.3')
ax.plot(range(10), color=(1, 0, 0, 1))
ax.plot(range(10), color=(1, 0, 0))
fig.canvas.draw()
def test_valid_colors():
line = mlines.Line2D([], [])
with pytest.raises(ValueError):
line.set_color("foobar")
def test_linestyle_variants():
fig, ax = plt.subplots()
for ls in ["-", "solid", "--", "dashed",
"-.", "dashdot", ":", "dotted",
(0, None), (0, ()), (0, []), # gh-22930
]:
ax.plot(range(10), linestyle=ls)
fig.canvas.draw()
def test_valid_linestyles():
line = mlines.Line2D([], [])
with pytest.raises(ValueError):
line.set_linestyle('aardvark')
@image_comparison(['drawstyle_variants.png'], remove_text=True,
tol=0 if platform.machine() == 'x86_64' else 0.03)
def test_drawstyle_variants():
fig, axs = plt.subplots(6)
dss = ["default", "steps-mid", "steps-pre", "steps-post", "steps", None]
# We want to check that drawstyles are properly handled even for very long
# lines (for which the subslice optimization is on); however, we need
# to zoom in so that the difference between the drawstyles is actually
# visible.
for ax, ds in zip(axs.flat, dss):
ax.plot(range(2000), drawstyle=ds)
ax.set(xlim=(0, 2), ylim=(0, 2))
@check_figures_equal(extensions=('png',))
def test_no_subslice_with_transform(fig_ref, fig_test):
ax = fig_ref.add_subplot()
x = np.arange(2000)
ax.plot(x + 2000, x)
ax = fig_test.add_subplot()
t = mtransforms.Affine2D().translate(2000.0, 0.0)
ax.plot(x, x, transform=t+ax.transData)
def test_valid_drawstyles():
line = mlines.Line2D([], [])
with pytest.raises(ValueError):
line.set_drawstyle('foobar')
def test_set_drawstyle():
x = np.linspace(0, 2*np.pi, 10)
y = np.sin(x)
fig, ax = plt.subplots()
line, = ax.plot(x, y)
line.set_drawstyle("steps-pre")
assert len(line.get_path().vertices) == 2*len(x)-1
line.set_drawstyle("default")
assert len(line.get_path().vertices) == len(x)
@image_comparison(['line_collection_dashes'], remove_text=True, style='mpl20',
tol=0 if platform.machine() == 'x86_64' else 0.65)
def test_set_line_coll_dash_image():
fig, ax = plt.subplots()
np.random.seed(0)
ax.contour(np.random.randn(20, 30), linestyles=[(0, (3, 3))])
@image_comparison(['marker_fill_styles.png'], remove_text=True)
def test_marker_fill_styles():
colors = itertools.cycle([[0, 0, 1], 'g', '#ff0000', 'c', 'm', 'y',
np.array([0, 0, 0])])
altcolor = 'lightgreen'
y = np.array([1, 1])
x = np.array([0, 9])
fig, ax = plt.subplots()
# This hard-coded list of markers correspond to an earlier iteration of
# MarkerStyle.filled_markers; the value of that attribute has changed but
# we kept the old value here to not regenerate the baseline image.
# Replace with mlines.Line2D.filled_markers when the image is regenerated.
for j, marker in enumerate("ov^<>8sp*hHDdPX"):
for i, fs in enumerate(mlines.Line2D.fillStyles):
color = next(colors)
ax.plot(j * 10 + x, y + i + .5 * (j % 2),
marker=marker,
markersize=20,
markerfacecoloralt=altcolor,
fillstyle=fs,
label=fs,
linewidth=5,
color=color,
markeredgecolor=color,
markeredgewidth=2)
ax.set_ylim([0, 7.5])
ax.set_xlim([-5, 155])
def test_markerfacecolor_fillstyle():
"""Test that markerfacecolor does not override fillstyle='none'."""
l, = plt.plot([1, 3, 2], marker=MarkerStyle('o', fillstyle='none'),
markerfacecolor='red')
assert l.get_fillstyle() == 'none'
assert l.get_markerfacecolor() == 'none'
@image_comparison(['scaled_lines'], style='default')
def test_lw_scaling():
th = np.linspace(0, 32)
fig, ax = plt.subplots()
lins_styles = ['dashed', 'dotted', 'dashdot']
cy = cycler(matplotlib.rcParams['axes.prop_cycle'])
for j, (ls, sty) in enumerate(zip(lins_styles, cy)):
for lw in np.linspace(.5, 10, 10):
ax.plot(th, j*np.ones(50) + .1 * lw, linestyle=ls, lw=lw, **sty)
def test_is_sorted_and_has_non_nan():
assert _path.is_sorted_and_has_non_nan(np.array([1, 2, 3]))
assert _path.is_sorted_and_has_non_nan(np.array([1, np.nan, 3]))
assert not _path.is_sorted_and_has_non_nan([3, 5] + [np.nan] * 100 + [0, 2])
# [2, 256] byteswapped:
assert not _path.is_sorted_and_has_non_nan(np.array([33554432, 65536], ">i4"))
n = 2 * mlines.Line2D._subslice_optim_min_size
plt.plot([np.nan] * n, range(n))
@check_figures_equal(extensions=['png'])
def test_step_markers(fig_test, fig_ref):
fig_test.subplots().step([0, 1], "-o")
fig_ref.subplots().plot([0, 0, 1], [0, 1, 1], "-o", markevery=[0, 2])
@pytest.mark.parametrize("parent", ["figure", "axes"])
@check_figures_equal(extensions=('png',))
def test_markevery(fig_test, fig_ref, parent):
np.random.seed(42)
x = np.linspace(0, 1, 14)
y = np.random.rand(len(x))
cases_test = [None, 4, (2, 5), [1, 5, 11],
[0, -1], slice(5, 10, 2),
np.arange(len(x))[y > 0.5],
0.3, (0.3, 0.4)]
cases_ref = ["11111111111111", "10001000100010", "00100001000010",
"01000100000100", "10000000000001", "00000101010000",
"01110001110110", "11011011011110", "01010011011101"]
if parent == "figure":
# float markevery ("relative to axes size") is not supported.
cases_test = cases_test[:-2]
cases_ref = cases_ref[:-2]
def add_test(x, y, *, markevery):
fig_test.add_artist(
mlines.Line2D(x, y, marker="o", markevery=markevery))
def add_ref(x, y, *, markevery):
fig_ref.add_artist(
mlines.Line2D(x, y, marker="o", markevery=markevery))
elif parent == "axes":
axs_test = iter(fig_test.subplots(3, 3).flat)
axs_ref = iter(fig_ref.subplots(3, 3).flat)
def add_test(x, y, *, markevery):
next(axs_test).plot(x, y, "-gD", markevery=markevery)
def add_ref(x, y, *, markevery):
next(axs_ref).plot(x, y, "-gD", markevery=markevery)
for case in cases_test:
add_test(x, y, markevery=case)
for case in cases_ref:
me = np.array(list(case)).astype(int).astype(bool)
add_ref(x, y, markevery=me)
def test_markevery_figure_line_unsupported_relsize():
fig = plt.figure()
fig.add_artist(mlines.Line2D([0, 1], [0, 1], marker="o", markevery=.5))
with pytest.raises(ValueError):
fig.canvas.draw()
def test_marker_as_markerstyle():
fig, ax = plt.subplots()
line, = ax.plot([2, 4, 3], marker=MarkerStyle("D"))
fig.canvas.draw()
assert line.get_marker() == "D"
# continue with smoke tests:
line.set_marker("s")
fig.canvas.draw()
line.set_marker(MarkerStyle("o"))
fig.canvas.draw()
# test Path roundtrip
triangle1 = Path._create_closed([[-1, -1], [1, -1], [0, 2]])
line2, = ax.plot([1, 3, 2], marker=MarkerStyle(triangle1), ms=22)
line3, = ax.plot([0, 2, 1], marker=triangle1, ms=22)
assert_array_equal(line2.get_marker().vertices, triangle1.vertices)
assert_array_equal(line3.get_marker().vertices, triangle1.vertices)
@image_comparison(['striped_line.png'], remove_text=True, style='mpl20')
def test_striped_lines():
rng = np.random.default_rng(19680801)
_, ax = plt.subplots()
ax.plot(rng.uniform(size=12), color='orange', gapcolor='blue',
linestyle='--', lw=5, label=' ')
ax.plot(rng.uniform(size=12), color='red', gapcolor='black',
linestyle=(0, (2, 5, 4, 2)), lw=5, label=' ', alpha=0.5)
ax.legend(handlelength=5)
@check_figures_equal(extensions=['png'])
def test_odd_dashes(fig_test, fig_ref):
fig_test.add_subplot().plot([1, 2], dashes=[1, 2, 3])
fig_ref.add_subplot().plot([1, 2], dashes=[1, 2, 3, 1, 2, 3])
def test_picking():
fig, ax = plt.subplots()
mouse_event = SimpleNamespace(x=fig.bbox.width // 2,
y=fig.bbox.height // 2 + 15)
# Default pickradius is 5, so event should not pick this line.
l0, = ax.plot([0, 1], [0, 1], picker=True)
found, indices = l0.contains(mouse_event)
assert not found
# But with a larger pickradius, this should be picked.
l1, = ax.plot([0, 1], [0, 1], picker=True, pickradius=20)
found, indices = l1.contains(mouse_event)
assert found
assert_array_equal(indices['ind'], [0])
# And if we modify the pickradius after creation, it should work as well.
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(extensions=['png'])
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)
with pytest.warns(mpl.MatplotlibDeprecationWarning):
line1.set_xy1(.2, .3)
with pytest.warns(mpl.MatplotlibDeprecationWarning):
line2.set_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)
def test_axline_small_slope():
"""Test that small slopes are not coerced to zero in the transform."""
line = plt.axline((0, 0), slope=1e-14)
p1 = line.get_transform().transform_point((0, 0))
p2 = line.get_transform().transform_point((1, 1))
# y-values must be slightly different
dy = p2[1] - p1[1]
assert dy > 0
assert dy < 4e-12
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