demo + utils venv
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d3m1g0d
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import os
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# Check that the test directories exist
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if not os.path.exists(os.path.join(
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os.path.dirname(__file__), 'baseline_images')):
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raise IOError(
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'The baseline image directory does not exist. '
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'This is most likely because the test data is not installed. '
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'You may need to install matplotlib from source to get the '
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'test data.')
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L 416.240417 146.518235
|
||||
z
|
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" style="fill:#0000ff;fill-opacity:0.765635378415;stroke:#000000;stroke-opacity:0.765635378415;"/>
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<path clip-path="url(#p9fde8b4859)" d="M 427.364546 134.102909
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L 425.128478 138.575045
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L 429.600614 138.575045
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||||
z
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" style="fill:#0000ff;fill-opacity:0.84364174006;stroke:#000000;stroke-opacity:0.84364174006;"/>
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<path clip-path="url(#p9fde8b4859)" d="M 440.744456 126.148
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||||
L 438.508388 130.620136
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||||
L 442.980524 130.620136
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||||
z
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" style="fill:#0000ff;fill-opacity:0.921763195619;stroke:#000000;stroke-opacity:0.921763195619;"/>
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<path clip-path="url(#p9fde8b4859)" d="M 454.144122 118.181346
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L 451.908054 122.653482
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L 456.38019 122.653482
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||||
z
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" style="fill:#0000ff;stroke:#000000;"/>
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</g>
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</g>
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</g>
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<defs>
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<clipPath id="p9fde8b4859">
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<rect height="345.6" width="446.4" x="72.0" y="43.2"/>
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</clipPath>
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</defs>
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||||
</svg>
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@@ -0,0 +1,3 @@
|
||||
from matplotlib.testing.conftest import (mpl_test_settings,
|
||||
mpl_image_comparison_parameters,
|
||||
pytest_configure, pytest_unconfigure)
|
||||
@@ -0,0 +1,43 @@
|
||||
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
from mpl_toolkits.axes_grid1 import ImageGrid
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['imagegrid_cbar_mode'],
|
||||
extensions=['png'],
|
||||
remove_text=True,
|
||||
style='mpl20')
|
||||
def test_imagegrid_cbar_mode_edge():
|
||||
X, Y = np.meshgrid(np.linspace(0, 6, 30), np.linspace(0, 6, 30))
|
||||
arr = np.sin(X) * np.cos(Y) + 1j*(np.sin(3*Y) * np.cos(Y/2.))
|
||||
|
||||
fig = plt.figure(figsize=(18, 9))
|
||||
|
||||
positions = (241, 242, 243, 244, 245, 246, 247, 248)
|
||||
directions = ['row']*4 + ['column']*4
|
||||
cbar_locations = ['left', 'right', 'top', 'bottom']*2
|
||||
|
||||
for position, direction, location in zip(positions,
|
||||
directions,
|
||||
cbar_locations):
|
||||
grid = ImageGrid(fig, position,
|
||||
nrows_ncols=(2, 2),
|
||||
direction=direction,
|
||||
cbar_location=location,
|
||||
cbar_size='20%',
|
||||
cbar_mode='edge')
|
||||
ax1, ax2, ax3, ax4, = grid
|
||||
|
||||
im1 = ax1.imshow(arr.real, cmap='nipy_spectral')
|
||||
im2 = ax2.imshow(arr.imag, cmap='hot')
|
||||
im3 = ax3.imshow(np.abs(arr), cmap='jet')
|
||||
im4 = ax4.imshow(np.arctan2(arr.imag, arr.real), cmap='hsv')
|
||||
|
||||
# Some of these colorbars will be overridden by later ones,
|
||||
# depending on the direction and cbar_location
|
||||
ax1.cax.colorbar(im1)
|
||||
ax2.cax.colorbar(im2)
|
||||
ax3.cax.colorbar(im3)
|
||||
ax4.cax.colorbar(im4)
|
||||
@@ -0,0 +1,424 @@
|
||||
import matplotlib
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
|
||||
from mpl_toolkits.axes_grid1 import host_subplot
|
||||
from mpl_toolkits.axes_grid1 import make_axes_locatable
|
||||
from mpl_toolkits.axes_grid1 import AxesGrid
|
||||
from mpl_toolkits.axes_grid1 import ImageGrid
|
||||
from mpl_toolkits.axes_grid1.inset_locator import (
|
||||
zoomed_inset_axes,
|
||||
mark_inset,
|
||||
inset_axes,
|
||||
BboxConnectorPatch
|
||||
)
|
||||
from mpl_toolkits.axes_grid1.anchored_artists import (
|
||||
AnchoredSizeBar,
|
||||
AnchoredDirectionArrows)
|
||||
|
||||
from matplotlib.colors import LogNorm
|
||||
from matplotlib.transforms import Bbox, TransformedBbox, \
|
||||
blended_transform_factory
|
||||
from itertools import product
|
||||
|
||||
import pytest
|
||||
import platform
|
||||
|
||||
import numpy as np
|
||||
from numpy.testing import assert_array_equal, assert_array_almost_equal
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['divider_append_axes'])
|
||||
def test_divider_append_axes():
|
||||
|
||||
# the random data
|
||||
np.random.seed(0)
|
||||
x = np.random.randn(1000)
|
||||
y = np.random.randn(1000)
|
||||
|
||||
fig, axScatter = plt.subplots()
|
||||
|
||||
# the scatter plot:
|
||||
axScatter.scatter(x, y)
|
||||
|
||||
# create new axes on the right and on the top of the current axes
|
||||
# The first argument of the new_vertical(new_horizontal) method is
|
||||
# the height (width) of the axes to be created in inches.
|
||||
divider = make_axes_locatable(axScatter)
|
||||
axHistbot = divider.append_axes("bottom", 1.2, pad=0.1, sharex=axScatter)
|
||||
axHistright = divider.append_axes("right", 1.2, pad=0.1, sharey=axScatter)
|
||||
axHistleft = divider.append_axes("left", 1.2, pad=0.1, sharey=axScatter)
|
||||
axHisttop = divider.append_axes("top", 1.2, pad=0.1, sharex=axScatter)
|
||||
|
||||
# now determine nice limits by hand:
|
||||
binwidth = 0.25
|
||||
xymax = max(np.max(np.abs(x)), np.max(np.abs(y)))
|
||||
lim = (int(xymax/binwidth) + 1) * binwidth
|
||||
|
||||
bins = np.arange(-lim, lim + binwidth, binwidth)
|
||||
axHisttop.hist(x, bins=bins)
|
||||
axHistbot.hist(x, bins=bins)
|
||||
axHistleft.hist(y, bins=bins, orientation='horizontal')
|
||||
axHistright.hist(y, bins=bins, orientation='horizontal')
|
||||
|
||||
axHistbot.invert_yaxis()
|
||||
axHistleft.invert_xaxis()
|
||||
|
||||
axHisttop.xaxis.set_ticklabels(())
|
||||
axHistbot.xaxis.set_ticklabels(())
|
||||
axHistleft.yaxis.set_ticklabels(())
|
||||
axHistright.yaxis.set_ticklabels(())
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['twin_axes_empty_and_removed'],
|
||||
extensions=["png"], tol=1)
|
||||
def test_twin_axes_empty_and_removed():
|
||||
# Purely cosmetic font changes (avoid overlap)
|
||||
matplotlib.rcParams.update({"font.size": 8})
|
||||
matplotlib.rcParams.update({"xtick.labelsize": 8})
|
||||
matplotlib.rcParams.update({"ytick.labelsize": 8})
|
||||
generators = [ "twinx", "twiny", "twin" ]
|
||||
modifiers = [ "", "host invisible", "twin removed", "twin invisible",
|
||||
"twin removed\nhost invisible" ]
|
||||
# Unmodified host subplot at the beginning for reference
|
||||
h = host_subplot(len(modifiers)+1, len(generators), 2)
|
||||
h.text(0.5, 0.5, "host_subplot", horizontalalignment="center",
|
||||
verticalalignment="center")
|
||||
# Host subplots with various modifications (twin*, visibility) applied
|
||||
for i, (mod, gen) in enumerate(product(modifiers, generators),
|
||||
len(generators)+1):
|
||||
h = host_subplot(len(modifiers)+1, len(generators), i)
|
||||
t = getattr(h, gen)()
|
||||
if "twin invisible" in mod:
|
||||
t.axis[:].set_visible(False)
|
||||
if "twin removed" in mod:
|
||||
t.remove()
|
||||
if "host invisible" in mod:
|
||||
h.axis[:].set_visible(False)
|
||||
h.text(0.5, 0.5, gen + ("\n" + mod if mod else ""),
|
||||
horizontalalignment="center", verticalalignment="center")
|
||||
plt.subplots_adjust(wspace=0.5, hspace=1)
|
||||
|
||||
|
||||
def test_axesgrid_colorbar_log_smoketest():
|
||||
fig = plt.figure()
|
||||
grid = AxesGrid(fig, 111, # modified to be only subplot
|
||||
nrows_ncols=(1, 1),
|
||||
label_mode="L",
|
||||
cbar_location="top",
|
||||
cbar_mode="single",
|
||||
)
|
||||
|
||||
Z = 10000 * np.random.rand(10, 10)
|
||||
im = grid[0].imshow(Z, interpolation="nearest", norm=LogNorm())
|
||||
|
||||
grid.cbar_axes[0].colorbar(im)
|
||||
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['inset_locator'], style='default', extensions=['png'],
|
||||
remove_text=True)
|
||||
def test_inset_locator():
|
||||
def get_demo_image():
|
||||
from matplotlib.cbook import get_sample_data
|
||||
import numpy as np
|
||||
f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
|
||||
z = np.load(f)
|
||||
# z is a numpy array of 15x15
|
||||
return z, (-3, 4, -4, 3)
|
||||
|
||||
fig, ax = plt.subplots(figsize=[5, 4])
|
||||
|
||||
# prepare the demo image
|
||||
Z, extent = get_demo_image()
|
||||
Z2 = np.zeros([150, 150], dtype="d")
|
||||
ny, nx = Z.shape
|
||||
Z2[30:30 + ny, 30:30 + nx] = Z
|
||||
|
||||
# extent = [-3, 4, -4, 3]
|
||||
ax.imshow(Z2, extent=extent, interpolation="nearest",
|
||||
origin="lower")
|
||||
|
||||
axins = zoomed_inset_axes(ax, zoom=6, loc='upper right')
|
||||
axins.imshow(Z2, extent=extent, interpolation="nearest",
|
||||
origin="lower")
|
||||
axins.yaxis.get_major_locator().set_params(nbins=7)
|
||||
axins.xaxis.get_major_locator().set_params(nbins=7)
|
||||
# sub region of the original image
|
||||
x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
|
||||
axins.set_xlim(x1, x2)
|
||||
axins.set_ylim(y1, y2)
|
||||
|
||||
plt.xticks(visible=False)
|
||||
plt.yticks(visible=False)
|
||||
|
||||
# draw a bbox of the region of the inset axes in the parent axes and
|
||||
# connecting lines between the bbox and the inset axes area
|
||||
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
|
||||
|
||||
asb = AnchoredSizeBar(ax.transData,
|
||||
0.5,
|
||||
'0.5',
|
||||
loc='lower center',
|
||||
pad=0.1, borderpad=0.5, sep=5,
|
||||
frameon=False)
|
||||
ax.add_artist(asb)
|
||||
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['inset_axes'], style='default', extensions=['png'],
|
||||
remove_text=True)
|
||||
def test_inset_axes():
|
||||
def get_demo_image():
|
||||
from matplotlib.cbook import get_sample_data
|
||||
import numpy as np
|
||||
f = get_sample_data("axes_grid/bivariate_normal.npy", asfileobj=False)
|
||||
z = np.load(f)
|
||||
# z is a numpy array of 15x15
|
||||
return z, (-3, 4, -4, 3)
|
||||
|
||||
fig, ax = plt.subplots(figsize=[5, 4])
|
||||
|
||||
# prepare the demo image
|
||||
Z, extent = get_demo_image()
|
||||
Z2 = np.zeros([150, 150], dtype="d")
|
||||
ny, nx = Z.shape
|
||||
Z2[30:30 + ny, 30:30 + nx] = Z
|
||||
|
||||
# extent = [-3, 4, -4, 3]
|
||||
ax.imshow(Z2, extent=extent, interpolation="nearest",
|
||||
origin="lower")
|
||||
|
||||
# creating our inset axes with a bbox_transform parameter
|
||||
axins = inset_axes(ax, width=1., height=1., bbox_to_anchor=(1, 1),
|
||||
bbox_transform=ax.transAxes)
|
||||
|
||||
axins.imshow(Z2, extent=extent, interpolation="nearest",
|
||||
origin="lower")
|
||||
axins.yaxis.get_major_locator().set_params(nbins=7)
|
||||
axins.xaxis.get_major_locator().set_params(nbins=7)
|
||||
# sub region of the original image
|
||||
x1, x2, y1, y2 = -1.5, -0.9, -2.5, -1.9
|
||||
axins.set_xlim(x1, x2)
|
||||
axins.set_ylim(y1, y2)
|
||||
|
||||
plt.xticks(visible=False)
|
||||
plt.yticks(visible=False)
|
||||
|
||||
# draw a bbox of the region of the inset axes in the parent axes and
|
||||
# connecting lines between the bbox and the inset axes area
|
||||
mark_inset(ax, axins, loc1=2, loc2=4, fc="none", ec="0.5")
|
||||
|
||||
asb = AnchoredSizeBar(ax.transData,
|
||||
0.5,
|
||||
'0.5',
|
||||
loc='lower center',
|
||||
pad=0.1, borderpad=0.5, sep=5,
|
||||
frameon=False)
|
||||
ax.add_artist(asb)
|
||||
|
||||
|
||||
def test_inset_axes_complete():
|
||||
dpi = 100
|
||||
figsize = (6, 5)
|
||||
fig, ax = plt.subplots(figsize=figsize, dpi=dpi)
|
||||
fig.subplots_adjust(.1, .1, .9, .9)
|
||||
|
||||
ins = inset_axes(ax, width=2., height=2., borderpad=0)
|
||||
fig.canvas.draw()
|
||||
assert_array_almost_equal(
|
||||
ins.get_position().extents,
|
||||
np.array(((0.9*figsize[0]-2.)/figsize[0],
|
||||
(0.9*figsize[1]-2.)/figsize[1], 0.9, 0.9)))
|
||||
|
||||
ins = inset_axes(ax, width="40%", height="30%", borderpad=0)
|
||||
fig.canvas.draw()
|
||||
assert_array_almost_equal(
|
||||
ins.get_position().extents,
|
||||
np.array((.9-.8*.4, .9-.8*.3, 0.9, 0.9)))
|
||||
|
||||
ins = inset_axes(ax, width=1., height=1.2, bbox_to_anchor=(200, 100),
|
||||
loc=3, borderpad=0)
|
||||
fig.canvas.draw()
|
||||
assert_array_almost_equal(
|
||||
ins.get_position().extents,
|
||||
np.array((200./dpi/figsize[0], 100./dpi/figsize[1],
|
||||
(200./dpi+1)/figsize[0], (100./dpi+1.2)/figsize[1])))
|
||||
|
||||
ins1 = inset_axes(ax, width="35%", height="60%", loc=3, borderpad=1)
|
||||
ins2 = inset_axes(ax, width="100%", height="100%",
|
||||
bbox_to_anchor=(0, 0, .35, .60),
|
||||
bbox_transform=ax.transAxes, loc=3, borderpad=1)
|
||||
fig.canvas.draw()
|
||||
assert_array_equal(ins1.get_position().extents,
|
||||
ins2.get_position().extents)
|
||||
|
||||
with pytest.raises(ValueError):
|
||||
ins = inset_axes(ax, width="40%", height="30%",
|
||||
bbox_to_anchor=(0.4, 0.5))
|
||||
|
||||
with pytest.warns(UserWarning):
|
||||
ins = inset_axes(ax, width="40%", height="30%",
|
||||
bbox_transform=ax.transAxes)
|
||||
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['fill_facecolor'], extensions=['png'],
|
||||
remove_text=True, style='mpl20')
|
||||
def test_fill_facecolor():
|
||||
fig, ax = plt.subplots(1, 5)
|
||||
fig.set_size_inches(5, 5)
|
||||
for i in range(1, 4):
|
||||
ax[i].yaxis.set_visible(False)
|
||||
ax[4].yaxis.tick_right()
|
||||
bbox = Bbox.from_extents(0, 0.4, 1, 0.6)
|
||||
|
||||
# fill with blue by setting 'fc' field
|
||||
bbox1 = TransformedBbox(bbox, ax[0].transData)
|
||||
bbox2 = TransformedBbox(bbox, ax[1].transData)
|
||||
# set color to BboxConnectorPatch
|
||||
p = BboxConnectorPatch(
|
||||
bbox1, bbox2, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
|
||||
ec="r", fc="b")
|
||||
p.set_clip_on(False)
|
||||
ax[0].add_patch(p)
|
||||
# set color to marked area
|
||||
axins = zoomed_inset_axes(ax[0], 1, loc='upper right')
|
||||
axins.set_xlim(0, 0.2)
|
||||
axins.set_ylim(0, 0.2)
|
||||
plt.gca().axes.get_xaxis().set_ticks([])
|
||||
plt.gca().axes.get_yaxis().set_ticks([])
|
||||
mark_inset(ax[0], axins, loc1=2, loc2=4, fc="b", ec="0.5")
|
||||
|
||||
# fill with yellow by setting 'facecolor' field
|
||||
bbox3 = TransformedBbox(bbox, ax[1].transData)
|
||||
bbox4 = TransformedBbox(bbox, ax[2].transData)
|
||||
# set color to BboxConnectorPatch
|
||||
p = BboxConnectorPatch(
|
||||
bbox3, bbox4, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
|
||||
ec="r", facecolor="y")
|
||||
p.set_clip_on(False)
|
||||
ax[1].add_patch(p)
|
||||
# set color to marked area
|
||||
axins = zoomed_inset_axes(ax[1], 1, loc='upper right')
|
||||
axins.set_xlim(0, 0.2)
|
||||
axins.set_ylim(0, 0.2)
|
||||
plt.gca().axes.get_xaxis().set_ticks([])
|
||||
plt.gca().axes.get_yaxis().set_ticks([])
|
||||
mark_inset(ax[1], axins, loc1=2, loc2=4, facecolor="y", ec="0.5")
|
||||
|
||||
# fill with green by setting 'color' field
|
||||
bbox5 = TransformedBbox(bbox, ax[2].transData)
|
||||
bbox6 = TransformedBbox(bbox, ax[3].transData)
|
||||
# set color to BboxConnectorPatch
|
||||
p = BboxConnectorPatch(
|
||||
bbox5, bbox6, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
|
||||
ec="r", color="g")
|
||||
p.set_clip_on(False)
|
||||
ax[2].add_patch(p)
|
||||
# set color to marked area
|
||||
axins = zoomed_inset_axes(ax[2], 1, loc='upper right')
|
||||
axins.set_xlim(0, 0.2)
|
||||
axins.set_ylim(0, 0.2)
|
||||
plt.gca().axes.get_xaxis().set_ticks([])
|
||||
plt.gca().axes.get_yaxis().set_ticks([])
|
||||
mark_inset(ax[2], axins, loc1=2, loc2=4, color="g", ec="0.5")
|
||||
|
||||
# fill with green but color won't show if set fill to False
|
||||
bbox7 = TransformedBbox(bbox, ax[3].transData)
|
||||
bbox8 = TransformedBbox(bbox, ax[4].transData)
|
||||
# BboxConnectorPatch won't show green
|
||||
p = BboxConnectorPatch(
|
||||
bbox7, bbox8, loc1a=1, loc2a=2, loc1b=4, loc2b=3,
|
||||
ec="r", fc="g", fill=False)
|
||||
p.set_clip_on(False)
|
||||
ax[3].add_patch(p)
|
||||
# marked area won't show green
|
||||
axins = zoomed_inset_axes(ax[3], 1, loc='upper right')
|
||||
axins.set_xlim(0, 0.2)
|
||||
axins.set_ylim(0, 0.2)
|
||||
axins.get_xaxis().set_ticks([])
|
||||
axins.get_yaxis().set_ticks([])
|
||||
mark_inset(ax[3], axins, loc1=2, loc2=4, fc="g", ec="0.5", fill=False)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['zoomed_axes',
|
||||
'inverted_zoomed_axes'],
|
||||
extensions=['png'])
|
||||
def test_zooming_with_inverted_axes():
|
||||
fig, ax = plt.subplots()
|
||||
ax.plot([1, 2, 3], [1, 2, 3])
|
||||
ax.axis([1, 3, 1, 3])
|
||||
inset_ax = zoomed_inset_axes(ax, zoom=2.5, loc='lower right')
|
||||
inset_ax.axis([1.1, 1.4, 1.1, 1.4])
|
||||
|
||||
fig, ax = plt.subplots()
|
||||
ax.plot([1, 2, 3], [1, 2, 3])
|
||||
ax.axis([3, 1, 3, 1])
|
||||
inset_ax = zoomed_inset_axes(ax, zoom=2.5, loc='lower right')
|
||||
inset_ax.axis([1.4, 1.1, 1.4, 1.1])
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['anchored_direction_arrows'],
|
||||
tol={'aarch64': 0.02}.get(platform.machine(), 0.0),
|
||||
extensions=['png'])
|
||||
def test_anchored_direction_arrows():
|
||||
fig, ax = plt.subplots()
|
||||
ax.imshow(np.zeros((10, 10)))
|
||||
|
||||
simple_arrow = AnchoredDirectionArrows(ax.transAxes, 'X', 'Y')
|
||||
ax.add_artist(simple_arrow)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['anchored_direction_arrows_many_args'],
|
||||
extensions=['png'])
|
||||
def test_anchored_direction_arrows_many_args():
|
||||
fig, ax = plt.subplots()
|
||||
ax.imshow(np.ones((10, 10)))
|
||||
|
||||
direction_arrows = AnchoredDirectionArrows(
|
||||
ax.transAxes, 'A', 'B', loc='upper right', color='red',
|
||||
aspect_ratio=-0.5, pad=0.6, borderpad=2, frameon=True, alpha=0.7,
|
||||
sep_x=-0.06, sep_y=-0.08, back_length=0.1, head_width=9,
|
||||
head_length=10, tail_width=5)
|
||||
ax.add_artist(direction_arrows)
|
||||
|
||||
|
||||
def test_axes_locatable_position():
|
||||
fig, ax = plt.subplots()
|
||||
divider = make_axes_locatable(ax)
|
||||
cax = divider.append_axes('right', size='5%', pad='2%')
|
||||
fig.canvas.draw()
|
||||
assert np.isclose(cax.get_position(original=False).width,
|
||||
0.03621495327102808)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['image_grid'], extensions=['png'],
|
||||
remove_text=True, style='mpl20',
|
||||
savefig_kwarg={'bbox_inches': 'tight'})
|
||||
def test_image_grid():
|
||||
# test that image grid works with bbox_inches=tight.
|
||||
im = np.arange(100)
|
||||
im.shape = 10, 10
|
||||
|
||||
fig = plt.figure(1, (4., 4.))
|
||||
grid = ImageGrid(fig, 111, nrows_ncols=(2, 2), axes_pad=0.1)
|
||||
|
||||
for i in range(4):
|
||||
grid[i].imshow(im)
|
||||
grid[i].set_title('test {0}{0}'.format(i))
|
||||
|
||||
|
||||
def test_gettightbbox():
|
||||
|
||||
fig, ax = plt.subplots(figsize=(8, 6))
|
||||
|
||||
l, = ax.plot([1, 2, 3], [0, 1, 0])
|
||||
|
||||
ax_zoom = zoomed_inset_axes(ax, 4)
|
||||
ax_zoom.plot([1, 2, 3], [0, 1, 0])
|
||||
|
||||
mark_inset(ax, ax_zoom, loc1=1, loc2=3, fc="none", ec='0.3')
|
||||
bbox = fig.get_tightbbox(fig.canvas.get_renderer())
|
||||
np.testing.assert_array_almost_equal(bbox.extents,
|
||||
[-18.022743, -14.118056, 7.332813, 5.4625])
|
||||
+142
@@ -0,0 +1,142 @@
|
||||
import re
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from mpl_toolkits.axisartist.angle_helper import (
|
||||
FormatterDMS, FormatterHMS, select_step, select_step24, select_step360)
|
||||
|
||||
|
||||
_MS_RE = (
|
||||
r'''\$ # Mathtext
|
||||
(
|
||||
# The sign sometimes appears on a 0 when a fraction is shown.
|
||||
# Check later that there's only one.
|
||||
(?P<degree_sign>-)?
|
||||
(?P<degree>[0-9.]+) # Degrees value
|
||||
{degree} # Degree symbol (to be replaced by format.)
|
||||
)?
|
||||
(
|
||||
(?(degree)\\,) # Separator if degrees are also visible.
|
||||
(?P<minute_sign>-)?
|
||||
(?P<minute>[0-9.]+) # Minutes value
|
||||
{minute} # Minute symbol (to be replaced by format.)
|
||||
)?
|
||||
(
|
||||
(?(minute)\\,) # Separator if minutes are also visible.
|
||||
(?P<second_sign>-)?
|
||||
(?P<second>[0-9.]+) # Seconds value
|
||||
{second} # Second symbol (to be replaced by format.)
|
||||
)?
|
||||
\$ # Mathtext
|
||||
'''
|
||||
)
|
||||
DMS_RE = re.compile(_MS_RE.format(degree=re.escape(FormatterDMS.deg_mark),
|
||||
minute=re.escape(FormatterDMS.min_mark),
|
||||
second=re.escape(FormatterDMS.sec_mark)),
|
||||
re.VERBOSE)
|
||||
HMS_RE = re.compile(_MS_RE.format(degree=re.escape(FormatterHMS.deg_mark),
|
||||
minute=re.escape(FormatterHMS.min_mark),
|
||||
second=re.escape(FormatterHMS.sec_mark)),
|
||||
re.VERBOSE)
|
||||
|
||||
|
||||
def dms2float(degrees, minutes=0, seconds=0):
|
||||
return degrees + minutes / 60.0 + seconds / 3600.0
|
||||
|
||||
|
||||
@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
|
||||
((-180, 180, 10), {'hour': False}, np.arange(-180, 181, 30), 1.0),
|
||||
((-12, 12, 10), {'hour': True}, np.arange(-12, 13, 2), 1.0)
|
||||
])
|
||||
def test_select_step(args, kwargs, expected_levels, expected_factor):
|
||||
levels, n, factor = select_step(*args, **kwargs)
|
||||
|
||||
assert n == len(levels)
|
||||
np.testing.assert_array_equal(levels, expected_levels)
|
||||
assert factor == expected_factor
|
||||
|
||||
|
||||
@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
|
||||
((-180, 180, 10), {}, np.arange(-180, 181, 30), 1.0),
|
||||
((-12, 12, 10), {}, np.arange(-750, 751, 150), 60.0)
|
||||
])
|
||||
def test_select_step24(args, kwargs, expected_levels, expected_factor):
|
||||
levels, n, factor = select_step24(*args, **kwargs)
|
||||
|
||||
assert n == len(levels)
|
||||
np.testing.assert_array_equal(levels, expected_levels)
|
||||
assert factor == expected_factor
|
||||
|
||||
|
||||
@pytest.mark.parametrize('args, kwargs, expected_levels, expected_factor', [
|
||||
((dms2float(20, 21.2), dms2float(21, 33.3), 5), {},
|
||||
np.arange(1215, 1306, 15), 60.0),
|
||||
((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=33.3), 5), {},
|
||||
np.arange(73820, 73835, 2), 3600.0),
|
||||
((dms2float(20, 21.2), dms2float(20, 53.3), 5), {},
|
||||
np.arange(1220, 1256, 5), 60.0),
|
||||
((21.2, 33.3, 5), {},
|
||||
np.arange(20, 35, 2), 1.0),
|
||||
((dms2float(20, 21.2), dms2float(21, 33.3), 5), {},
|
||||
np.arange(1215, 1306, 15), 60.0),
|
||||
((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=33.3), 5), {},
|
||||
np.arange(73820, 73835, 2), 3600.0),
|
||||
((dms2float(20.5, seconds=21.2), dms2float(20.5, seconds=21.4), 5), {},
|
||||
np.arange(7382120, 7382141, 5), 360000.0),
|
||||
# test threshold factor
|
||||
((dms2float(20.5, seconds=11.2), dms2float(20.5, seconds=53.3), 5),
|
||||
{'threshold_factor': 60}, np.arange(12301, 12310), 600.0),
|
||||
((dms2float(20.5, seconds=11.2), dms2float(20.5, seconds=53.3), 5),
|
||||
{'threshold_factor': 1}, np.arange(20502, 20517, 2), 1000.0),
|
||||
])
|
||||
def test_select_step360(args, kwargs, expected_levels, expected_factor):
|
||||
levels, n, factor = select_step360(*args, **kwargs)
|
||||
|
||||
assert n == len(levels)
|
||||
np.testing.assert_array_equal(levels, expected_levels)
|
||||
assert factor == expected_factor
|
||||
|
||||
|
||||
@pytest.mark.parametrize('Formatter, regex',
|
||||
[(FormatterDMS, DMS_RE),
|
||||
(FormatterHMS, HMS_RE)],
|
||||
ids=['Degree/Minute/Second', 'Hour/Minute/Second'])
|
||||
@pytest.mark.parametrize('direction, factor, values', [
|
||||
("left", 60, [0, -30, -60]),
|
||||
("left", 600, [12301, 12302, 12303]),
|
||||
("left", 3600, [0, -30, -60]),
|
||||
("left", 36000, [738210, 738215, 738220]),
|
||||
("left", 360000, [7382120, 7382125, 7382130]),
|
||||
("left", 1., [45, 46, 47]),
|
||||
("left", 10., [452, 453, 454]),
|
||||
])
|
||||
def test_formatters(Formatter, regex, direction, factor, values):
|
||||
fmt = Formatter()
|
||||
result = fmt(direction, factor, values)
|
||||
|
||||
prev_degree = prev_minute = prev_second = None
|
||||
for tick, value in zip(result, values):
|
||||
m = regex.match(tick)
|
||||
assert m is not None, '"%s" is not an expected tick format.' % (tick, )
|
||||
|
||||
sign = sum(m.group(sign + '_sign') is not None
|
||||
for sign in ('degree', 'minute', 'second'))
|
||||
assert sign <= 1, \
|
||||
'Only one element of tick "%s" may have a sign.' % (tick, )
|
||||
sign = 1 if sign == 0 else -1
|
||||
|
||||
degree = float(m.group('degree') or prev_degree or 0)
|
||||
minute = float(m.group('minute') or prev_minute or 0)
|
||||
second = float(m.group('second') or prev_second or 0)
|
||||
if Formatter == FormatterHMS:
|
||||
# 360 degrees as plot range -> 24 hours as labelled range
|
||||
expected_value = pytest.approx((value // 15) / factor)
|
||||
else:
|
||||
expected_value = pytest.approx(value / factor)
|
||||
assert sign * dms2float(degree, minute, second) == expected_value, \
|
||||
'"%s" does not match expected tick value.' % (tick, )
|
||||
|
||||
prev_degree = degree
|
||||
prev_minute = minute
|
||||
prev_second = second
|
||||
+94
@@ -0,0 +1,94 @@
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
|
||||
from mpl_toolkits.axisartist import AxisArtistHelperRectlinear
|
||||
from mpl_toolkits.axisartist.axis_artist import (AxisArtist, AxisLabel,
|
||||
LabelBase, Ticks, TickLabels)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axis_artist_ticks'],
|
||||
extensions=['png'], style='default')
|
||||
def test_ticks():
|
||||
fig, ax = plt.subplots()
|
||||
|
||||
ax.xaxis.set_visible(False)
|
||||
ax.yaxis.set_visible(False)
|
||||
|
||||
locs_angles = [((i / 10, 0.0), i * 30) for i in range(-1, 12)]
|
||||
|
||||
ticks_in = Ticks(ticksize=10, axis=ax.xaxis)
|
||||
ticks_in.set_locs_angles(locs_angles)
|
||||
ax.add_artist(ticks_in)
|
||||
|
||||
ticks_out = Ticks(ticksize=10, tick_out=True, color='C3', axis=ax.xaxis)
|
||||
ticks_out.set_locs_angles(locs_angles)
|
||||
ax.add_artist(ticks_out)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axis_artist_labelbase'],
|
||||
extensions=['png'], style='default')
|
||||
def test_labelbase():
|
||||
fig, ax = plt.subplots()
|
||||
|
||||
ax.plot([0.5], [0.5], "o")
|
||||
|
||||
label = LabelBase(0.5, 0.5, "Test")
|
||||
label._set_ref_angle(-90)
|
||||
label._set_offset_radius(offset_radius=50)
|
||||
label.set_rotation(-90)
|
||||
label.set(ha="center", va="top")
|
||||
ax.add_artist(label)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axis_artist_ticklabels'],
|
||||
extensions=['png'], style='default')
|
||||
def test_ticklabels():
|
||||
fig, ax = plt.subplots()
|
||||
|
||||
ax.xaxis.set_visible(False)
|
||||
ax.yaxis.set_visible(False)
|
||||
|
||||
ax.plot([0.2, 0.4], [0.5, 0.5], "o")
|
||||
|
||||
ticks = Ticks(ticksize=10, axis=ax.xaxis)
|
||||
ax.add_artist(ticks)
|
||||
locs_angles_labels = [((0.2, 0.5), -90, "0.2"),
|
||||
((0.4, 0.5), -120, "0.4")]
|
||||
tick_locs_angles = [(xy, a + 180) for xy, a, l in locs_angles_labels]
|
||||
ticks.set_locs_angles(tick_locs_angles)
|
||||
|
||||
ticklabels = TickLabels(axis_direction="left")
|
||||
ticklabels._locs_angles_labels = locs_angles_labels
|
||||
ticklabels.set_pad(10)
|
||||
ax.add_artist(ticklabels)
|
||||
|
||||
ax.plot([0.5], [0.5], "s")
|
||||
axislabel = AxisLabel(0.5, 0.5, "Test")
|
||||
axislabel._set_offset_radius(20)
|
||||
axislabel._set_ref_angle(0)
|
||||
axislabel.set_axis_direction("bottom")
|
||||
ax.add_artist(axislabel)
|
||||
|
||||
ax.set_xlim(0, 1)
|
||||
ax.set_ylim(0, 1)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axis_artist'],
|
||||
extensions=['png'], style='default')
|
||||
def test_axis_artist():
|
||||
fig, ax = plt.subplots()
|
||||
|
||||
ax.xaxis.set_visible(False)
|
||||
ax.yaxis.set_visible(False)
|
||||
|
||||
for loc in ('left', 'right', 'bottom'):
|
||||
_helper = AxisArtistHelperRectlinear.Fixed(ax, loc=loc)
|
||||
axisline = AxisArtist(ax, _helper, offset=None, axis_direction=loc)
|
||||
ax.add_artist(axisline)
|
||||
|
||||
# Settings for bottom AxisArtist.
|
||||
axisline.set_label("TTT")
|
||||
axisline.major_ticks.set_tick_out(False)
|
||||
axisline.label.set_pad(5)
|
||||
|
||||
ax.set_ylabel("Test")
|
||||
+89
@@ -0,0 +1,89 @@
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
from matplotlib.transforms import IdentityTransform
|
||||
|
||||
from mpl_toolkits.axisartist.axislines import SubplotZero, Subplot
|
||||
from mpl_toolkits.axisartist import SubplotHost, ParasiteAxesAuxTrans
|
||||
|
||||
from mpl_toolkits.axisartist import Axes
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['SubplotZero'],
|
||||
extensions=['png'], style='default')
|
||||
def test_SubplotZero():
|
||||
fig = plt.figure()
|
||||
|
||||
ax = SubplotZero(fig, 1, 1, 1)
|
||||
fig.add_subplot(ax)
|
||||
|
||||
ax.axis["xzero"].set_visible(True)
|
||||
ax.axis["xzero"].label.set_text("Axis Zero")
|
||||
|
||||
for n in ["top", "right"]:
|
||||
ax.axis[n].set_visible(False)
|
||||
|
||||
xx = np.arange(0, 2 * np.pi, 0.01)
|
||||
ax.plot(xx, np.sin(xx))
|
||||
ax.set_ylabel("Test")
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['Subplot'],
|
||||
extensions=['png'], style='default')
|
||||
def test_Subplot():
|
||||
fig = plt.figure()
|
||||
|
||||
ax = Subplot(fig, 1, 1, 1)
|
||||
fig.add_subplot(ax)
|
||||
|
||||
xx = np.arange(0, 2 * np.pi, 0.01)
|
||||
ax.plot(xx, np.sin(xx))
|
||||
ax.set_ylabel("Test")
|
||||
|
||||
ax.axis["top"].major_ticks.set_tick_out(True)
|
||||
ax.axis["bottom"].major_ticks.set_tick_out(True)
|
||||
|
||||
ax.axis["bottom"].set_label("Tk0")
|
||||
|
||||
|
||||
def test_Axes():
|
||||
fig = plt.figure()
|
||||
ax = Axes(fig, [0.15, 0.1, 0.65, 0.8])
|
||||
fig.add_axes(ax)
|
||||
ax.plot([1, 2, 3], [0, 1, 2])
|
||||
|
||||
ax.set_xscale('log')
|
||||
|
||||
plt.show()
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['ParasiteAxesAuxTrans_meshplot'],
|
||||
extensions=['png'], remove_text=True, style='default',
|
||||
tol=0.075)
|
||||
def test_ParasiteAxesAuxTrans():
|
||||
|
||||
data = np.ones((6, 6))
|
||||
data[2, 2] = 2
|
||||
data[0, :] = 0
|
||||
data[-2, :] = 0
|
||||
data[:, 0] = 0
|
||||
data[:, -2] = 0
|
||||
x = np.arange(6)
|
||||
y = np.arange(6)
|
||||
xx, yy = np.meshgrid(x, y)
|
||||
|
||||
funcnames = ['pcolor', 'pcolormesh', 'contourf']
|
||||
|
||||
fig = plt.figure()
|
||||
for i, name in enumerate(funcnames):
|
||||
|
||||
ax1 = SubplotHost(fig, 1, 3, i+1)
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
ax2 = ParasiteAxesAuxTrans(ax1, IdentityTransform())
|
||||
ax1.parasites.append(ax2)
|
||||
getattr(ax2, name)(xx, yy, data)
|
||||
ax1.set_xlim((0, 5))
|
||||
ax1.set_ylim((0, 5))
|
||||
|
||||
ax2.contour(xx, yy, data, colors='k')
|
||||
+33
@@ -0,0 +1,33 @@
|
||||
import numpy as np
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
from matplotlib.transforms import Bbox
|
||||
|
||||
from mpl_toolkits.axisartist.clip_path import clip_line_to_rect
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['clip_path'],
|
||||
extensions=['png'], style='default')
|
||||
def test_clip_path():
|
||||
x = np.array([-3, -2, -1, 0., 1, 2, 3, 2, 1, 0, -1, -2, -3, 5])
|
||||
y = np.arange(len(x))
|
||||
|
||||
fig, ax = plt.subplots()
|
||||
ax.plot(x, y, lw=1)
|
||||
|
||||
bbox = Bbox.from_extents(-2, 3, 2, 12.5)
|
||||
rect = plt.Rectangle(bbox.p0, bbox.width, bbox.height,
|
||||
facecolor='none', edgecolor='k', ls='--')
|
||||
ax.add_patch(rect)
|
||||
|
||||
clipped_lines, ticks = clip_line_to_rect(x, y, bbox)
|
||||
for lx, ly in clipped_lines:
|
||||
ax.plot(lx, ly, lw=1, color='C1')
|
||||
for px, py in zip(lx, ly):
|
||||
assert bbox.contains(px, py)
|
||||
|
||||
ccc = iter(['C3o', 'C2x', 'C3o', 'C2x'])
|
||||
for ttt in ticks:
|
||||
cc = next(ccc)
|
||||
for (xx, yy), aa in ttt:
|
||||
ax.plot([xx], [yy], cc)
|
||||
+123
@@ -0,0 +1,123 @@
|
||||
import numpy as np
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.projections as mprojections
|
||||
import matplotlib.transforms as mtransforms
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
from mpl_toolkits.axisartist.axislines import Subplot
|
||||
from mpl_toolkits.axisartist.floating_axes import (
|
||||
FloatingSubplot,
|
||||
GridHelperCurveLinear)
|
||||
from mpl_toolkits.axisartist.grid_finder import FixedLocator
|
||||
from mpl_toolkits.axisartist import angle_helper
|
||||
|
||||
|
||||
def test_subplot():
|
||||
fig = plt.figure(figsize=(5, 5))
|
||||
fig.clf()
|
||||
|
||||
ax = Subplot(fig, 111)
|
||||
fig.add_subplot(ax)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['curvelinear3'],
|
||||
extensions=['png'], style='default', tol=0.01)
|
||||
def test_curvelinear3():
|
||||
fig = plt.figure(figsize=(5, 5))
|
||||
fig.clf()
|
||||
|
||||
tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
|
||||
mprojections.PolarAxes.PolarTransform())
|
||||
|
||||
grid_locator1 = angle_helper.LocatorDMS(15)
|
||||
tick_formatter1 = angle_helper.FormatterDMS()
|
||||
|
||||
grid_locator2 = FixedLocator([2, 4, 6, 8, 10])
|
||||
|
||||
grid_helper = GridHelperCurveLinear(tr,
|
||||
extremes=(0, 360, 10, 3),
|
||||
grid_locator1=grid_locator1,
|
||||
grid_locator2=grid_locator2,
|
||||
tick_formatter1=tick_formatter1,
|
||||
tick_formatter2=None)
|
||||
|
||||
ax1 = FloatingSubplot(fig, 111, grid_helper=grid_helper)
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
r_scale = 10
|
||||
tr2 = mtransforms.Affine2D().scale(1, 1 / r_scale) + tr
|
||||
grid_locator2 = FixedLocator([30, 60, 90])
|
||||
grid_helper2 = GridHelperCurveLinear(tr2,
|
||||
extremes=(0, 360,
|
||||
10 * r_scale, 3 * r_scale),
|
||||
grid_locator2=grid_locator2)
|
||||
|
||||
ax1.axis["right"] = axis = grid_helper2.new_fixed_axis("right", axes=ax1)
|
||||
|
||||
ax1.axis["left"].label.set_text("Test 1")
|
||||
ax1.axis["right"].label.set_text("Test 2")
|
||||
|
||||
for an in ["left", "right"]:
|
||||
ax1.axis[an].set_visible(False)
|
||||
|
||||
axis = grid_helper.new_floating_axis(1, 7, axes=ax1,
|
||||
axis_direction="bottom")
|
||||
ax1.axis["z"] = axis
|
||||
axis.toggle(all=True, label=True)
|
||||
axis.label.set_text("z = ?")
|
||||
axis.label.set_visible(True)
|
||||
axis.line.set_color("0.5")
|
||||
|
||||
ax2 = ax1.get_aux_axes(tr)
|
||||
|
||||
xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
|
||||
ax2.scatter(xx, yy)
|
||||
l, = ax2.plot(xx, yy, "k-")
|
||||
l.set_clip_path(ax1.patch)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['curvelinear4'],
|
||||
extensions=['png'], style='default', tol=0.015)
|
||||
def test_curvelinear4():
|
||||
fig = plt.figure(figsize=(5, 5))
|
||||
fig.clf()
|
||||
|
||||
tr = (mtransforms.Affine2D().scale(np.pi / 180, 1) +
|
||||
mprojections.PolarAxes.PolarTransform())
|
||||
|
||||
grid_locator1 = angle_helper.LocatorDMS(5)
|
||||
tick_formatter1 = angle_helper.FormatterDMS()
|
||||
|
||||
grid_locator2 = FixedLocator([2, 4, 6, 8, 10])
|
||||
|
||||
grid_helper = GridHelperCurveLinear(tr,
|
||||
extremes=(120, 30, 10, 0),
|
||||
grid_locator1=grid_locator1,
|
||||
grid_locator2=grid_locator2,
|
||||
tick_formatter1=tick_formatter1,
|
||||
tick_formatter2=None)
|
||||
|
||||
ax1 = FloatingSubplot(fig, 111, grid_helper=grid_helper)
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
ax1.axis["left"].label.set_text("Test 1")
|
||||
ax1.axis["right"].label.set_text("Test 2")
|
||||
|
||||
for an in ["top"]:
|
||||
ax1.axis[an].set_visible(False)
|
||||
|
||||
axis = grid_helper.new_floating_axis(1, 70, axes=ax1,
|
||||
axis_direction="bottom")
|
||||
ax1.axis["z"] = axis
|
||||
axis.toggle(all=True, label=True)
|
||||
axis.label.set_axis_direction("top")
|
||||
axis.label.set_text("z = ?")
|
||||
axis.label.set_visible(True)
|
||||
axis.line.set_color("0.5")
|
||||
|
||||
ax2 = ax1.get_aux_axes(tr)
|
||||
|
||||
xx, yy = [67, 90, 75, 30], [2, 5, 8, 4]
|
||||
ax2.scatter(xx, yy)
|
||||
l, = ax2.plot(xx, yy, "k-")
|
||||
l.set_clip_path(ax1.patch)
|
||||
+13
@@ -0,0 +1,13 @@
|
||||
from mpl_toolkits.axisartist.grid_finder import (
|
||||
FormatterPrettyPrint,
|
||||
MaxNLocator)
|
||||
|
||||
|
||||
def test_pretty_print_format():
|
||||
locator = MaxNLocator()
|
||||
locs, nloc, factor = locator(0, 100)
|
||||
|
||||
fmt = FormatterPrettyPrint()
|
||||
|
||||
assert fmt("left", None, locs) == \
|
||||
[r'$\mathdefault{%d}$' % (l, ) for l in locs]
|
||||
+214
@@ -0,0 +1,214 @@
|
||||
import numpy as np
|
||||
import platform
|
||||
|
||||
import matplotlib.pyplot as plt
|
||||
from matplotlib.path import Path
|
||||
from matplotlib.projections import PolarAxes
|
||||
from matplotlib.transforms import Affine2D, Transform
|
||||
from matplotlib.testing.decorators import image_comparison
|
||||
|
||||
from mpl_toolkits.axes_grid1.parasite_axes import ParasiteAxesAuxTrans
|
||||
from mpl_toolkits.axisartist import SubplotHost
|
||||
from mpl_toolkits.axes_grid1.parasite_axes import host_subplot_class_factory
|
||||
from mpl_toolkits.axisartist import angle_helper
|
||||
from mpl_toolkits.axisartist.axislines import Axes
|
||||
from mpl_toolkits.axisartist.grid_helper_curvelinear import \
|
||||
GridHelperCurveLinear
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['custom_transform'],
|
||||
extensions=['png'], style='default', tol=0.03)
|
||||
def test_custom_transform():
|
||||
class MyTransform(Transform):
|
||||
input_dims = 2
|
||||
output_dims = 2
|
||||
is_separable = False
|
||||
|
||||
def __init__(self, resolution):
|
||||
"""
|
||||
Resolution is the number of steps to interpolate between each input
|
||||
line segment to approximate its path in transformed space.
|
||||
"""
|
||||
Transform.__init__(self)
|
||||
self._resolution = resolution
|
||||
|
||||
def transform(self, ll):
|
||||
x, y = ll.T
|
||||
return np.column_stack([x, y - x])
|
||||
|
||||
transform_non_affine = transform
|
||||
|
||||
def transform_path(self, path):
|
||||
vertices = path.vertices
|
||||
ipath = path.interpolated(self._resolution)
|
||||
return Path(self.transform(ipath.vertices), ipath.codes)
|
||||
|
||||
transform_path_non_affine = transform_path
|
||||
|
||||
def inverted(self):
|
||||
return MyTransformInv(self._resolution)
|
||||
|
||||
class MyTransformInv(Transform):
|
||||
input_dims = 2
|
||||
output_dims = 2
|
||||
is_separable = False
|
||||
|
||||
def __init__(self, resolution):
|
||||
Transform.__init__(self)
|
||||
self._resolution = resolution
|
||||
|
||||
def transform(self, ll):
|
||||
x, y = ll.T
|
||||
return np.column_stack([x, y + x])
|
||||
|
||||
def inverted(self):
|
||||
return MyTransform(self._resolution)
|
||||
|
||||
fig = plt.figure()
|
||||
|
||||
SubplotHost = host_subplot_class_factory(Axes)
|
||||
|
||||
tr = MyTransform(1)
|
||||
grid_helper = GridHelperCurveLinear(tr)
|
||||
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
|
||||
ax1.parasites.append(ax2)
|
||||
ax2.plot([3, 6], [5.0, 10.])
|
||||
|
||||
ax1.set_aspect(1.)
|
||||
ax1.set_xlim(0, 10)
|
||||
ax1.set_ylim(0, 10)
|
||||
|
||||
ax1.grid(True)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['polar_box'],
|
||||
tol={'aarch64': 0.04}.get(platform.machine(), 0.03),
|
||||
extensions=['png'], style='default')
|
||||
def test_polar_box():
|
||||
fig = plt.figure(figsize=(5, 5))
|
||||
|
||||
# PolarAxes.PolarTransform takes radian. However, we want our coordinate
|
||||
# system in degree
|
||||
tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform()
|
||||
|
||||
# polar projection, which involves cycle, and also has limits in
|
||||
# its coordinates, needs a special method to find the extremes
|
||||
# (min, max of the coordinate within the view).
|
||||
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
|
||||
lon_cycle=360,
|
||||
lat_cycle=None,
|
||||
lon_minmax=None,
|
||||
lat_minmax=(0, np.inf))
|
||||
|
||||
grid_locator1 = angle_helper.LocatorDMS(12)
|
||||
tick_formatter1 = angle_helper.FormatterDMS()
|
||||
|
||||
grid_helper = GridHelperCurveLinear(tr,
|
||||
extreme_finder=extreme_finder,
|
||||
grid_locator1=grid_locator1,
|
||||
tick_formatter1=tick_formatter1)
|
||||
|
||||
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
|
||||
|
||||
ax1.axis["right"].major_ticklabels.set_visible(True)
|
||||
ax1.axis["top"].major_ticklabels.set_visible(True)
|
||||
|
||||
# let right axis shows ticklabels for 1st coordinate (angle)
|
||||
ax1.axis["right"].get_helper().nth_coord_ticks = 0
|
||||
# let bottom axis shows ticklabels for 2nd coordinate (radius)
|
||||
ax1.axis["bottom"].get_helper().nth_coord_ticks = 1
|
||||
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
ax1.axis["lat"] = axis = grid_helper.new_floating_axis(0, 45, axes=ax1)
|
||||
axis.label.set_text("Test")
|
||||
axis.label.set_visible(True)
|
||||
axis.get_helper()._extremes = 2, 12
|
||||
|
||||
ax1.axis["lon"] = axis = grid_helper.new_floating_axis(1, 6, axes=ax1)
|
||||
axis.label.set_text("Test 2")
|
||||
axis.get_helper()._extremes = -180, 90
|
||||
|
||||
# A parasite axes with given transform
|
||||
ax2 = ParasiteAxesAuxTrans(ax1, tr, "equal")
|
||||
assert ax2.transData == tr + ax1.transData
|
||||
# Anything you draw in ax2 will match the ticks and grids of ax1.
|
||||
ax1.parasites.append(ax2)
|
||||
ax2.plot(np.linspace(0, 30, 50), np.linspace(10, 10, 50))
|
||||
|
||||
ax1.set_aspect(1.)
|
||||
ax1.set_xlim(-5, 12)
|
||||
ax1.set_ylim(-5, 10)
|
||||
|
||||
ax1.grid(True)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axis_direction'],
|
||||
extensions=['png'], style='default', tol=0.03)
|
||||
def test_axis_direction():
|
||||
fig = plt.figure(figsize=(5, 5))
|
||||
|
||||
# PolarAxes.PolarTransform takes radian. However, we want our coordinate
|
||||
# system in degree
|
||||
tr = Affine2D().scale(np.pi / 180., 1.) + PolarAxes.PolarTransform()
|
||||
|
||||
# polar projection, which involves cycle, and also has limits in
|
||||
# its coordinates, needs a special method to find the extremes
|
||||
# (min, max of the coordinate within the view).
|
||||
|
||||
# 20, 20 : number of sampling points along x, y direction
|
||||
extreme_finder = angle_helper.ExtremeFinderCycle(20, 20,
|
||||
lon_cycle=360,
|
||||
lat_cycle=None,
|
||||
lon_minmax=None,
|
||||
lat_minmax=(0, np.inf),
|
||||
)
|
||||
|
||||
grid_locator1 = angle_helper.LocatorDMS(12)
|
||||
tick_formatter1 = angle_helper.FormatterDMS()
|
||||
|
||||
grid_helper = GridHelperCurveLinear(tr,
|
||||
extreme_finder=extreme_finder,
|
||||
grid_locator1=grid_locator1,
|
||||
tick_formatter1=tick_formatter1)
|
||||
|
||||
ax1 = SubplotHost(fig, 1, 1, 1, grid_helper=grid_helper)
|
||||
|
||||
for axis in ax1.axis.values():
|
||||
axis.set_visible(False)
|
||||
|
||||
fig.add_subplot(ax1)
|
||||
|
||||
ax1.axis["lat1"] = axis = grid_helper.new_floating_axis(
|
||||
0, 130,
|
||||
axes=ax1, axis_direction="left")
|
||||
axis.label.set_text("Test")
|
||||
axis.label.set_visible(True)
|
||||
axis.get_helper()._extremes = 0.001, 10
|
||||
|
||||
ax1.axis["lat2"] = axis = grid_helper.new_floating_axis(
|
||||
0, 50,
|
||||
axes=ax1, axis_direction="right")
|
||||
axis.label.set_text("Test")
|
||||
axis.label.set_visible(True)
|
||||
axis.get_helper()._extremes = 0.001, 10
|
||||
|
||||
ax1.axis["lon"] = axis = grid_helper.new_floating_axis(
|
||||
1, 10,
|
||||
axes=ax1, axis_direction="bottom")
|
||||
axis.label.set_text("Test 2")
|
||||
axis.get_helper()._extremes = 50, 130
|
||||
axis.major_ticklabels.set_axis_direction("top")
|
||||
axis.label.set_axis_direction("top")
|
||||
|
||||
grid_helper.grid_finder.grid_locator1.den = 5
|
||||
grid_helper.grid_finder.grid_locator2._nbins = 5
|
||||
|
||||
ax1.set_aspect(1.)
|
||||
ax1.set_xlim(-8, 8)
|
||||
ax1.set_ylim(-4, 12)
|
||||
|
||||
ax1.grid(True)
|
||||
@@ -0,0 +1,814 @@
|
||||
import pytest
|
||||
|
||||
from mpl_toolkits.mplot3d import Axes3D, axes3d, proj3d, art3d
|
||||
from matplotlib import cm
|
||||
from matplotlib.testing.decorators import image_comparison, check_figures_equal
|
||||
from matplotlib.collections import LineCollection
|
||||
from matplotlib.patches import Circle
|
||||
import matplotlib.pyplot as plt
|
||||
import numpy as np
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['bar3d'], remove_text=True)
|
||||
def test_bar3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
for c, z in zip(['r', 'g', 'b', 'y'], [30, 20, 10, 0]):
|
||||
xs = np.arange(20)
|
||||
ys = np.arange(20)
|
||||
cs = [c] * len(xs)
|
||||
cs[0] = 'c'
|
||||
ax.bar(xs, ys, zs=z, zdir='y', align='edge', color=cs, alpha=0.8)
|
||||
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['bar3d_shaded'],
|
||||
remove_text=True,
|
||||
extensions=['png']
|
||||
)
|
||||
def test_bar3d_shaded():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
x = np.arange(4)
|
||||
y = np.arange(5)
|
||||
x2d, y2d = np.meshgrid(x, y)
|
||||
x2d, y2d = x2d.ravel(), y2d.ravel()
|
||||
z = x2d + y2d
|
||||
ax.bar3d(x2d, y2d, x2d * 0, 1, 1, z, shade=True)
|
||||
fig.canvas.draw()
|
||||
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['bar3d_notshaded'],
|
||||
remove_text=True,
|
||||
extensions=['png']
|
||||
)
|
||||
def test_bar3d_notshaded():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
x = np.arange(4)
|
||||
y = np.arange(5)
|
||||
x2d, y2d = np.meshgrid(x, y)
|
||||
x2d, y2d = x2d.ravel(), y2d.ravel()
|
||||
z = x2d + y2d
|
||||
ax.bar3d(x2d, y2d, x2d * 0, 1, 1, z, shade=False)
|
||||
fig.canvas.draw()
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['contour3d'],
|
||||
remove_text=True, style='mpl20')
|
||||
def test_contour3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
cset = ax.contour(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
|
||||
cset = ax.contour(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
|
||||
cset = ax.contour(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
|
||||
ax.set_xlim(-40, 40)
|
||||
ax.set_ylim(-40, 40)
|
||||
ax.set_zlim(-100, 100)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['contourf3d'], remove_text=True)
|
||||
def test_contourf3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
cset = ax.contourf(X, Y, Z, zdir='z', offset=-100, cmap=cm.coolwarm)
|
||||
cset = ax.contourf(X, Y, Z, zdir='x', offset=-40, cmap=cm.coolwarm)
|
||||
cset = ax.contourf(X, Y, Z, zdir='y', offset=40, cmap=cm.coolwarm)
|
||||
ax.set_xlim(-40, 40)
|
||||
ax.set_ylim(-40, 40)
|
||||
ax.set_zlim(-100, 100)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['contourf3d_fill'], remove_text=True)
|
||||
def test_contourf3d_fill():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
X, Y = np.meshgrid(np.arange(-2, 2, 0.25), np.arange(-2, 2, 0.25))
|
||||
Z = X.clip(0, 0)
|
||||
# This produces holes in the z=0 surface that causes rendering errors if
|
||||
# the Poly3DCollection is not aware of path code information (issue #4784)
|
||||
Z[::5, ::5] = 0.1
|
||||
cset = ax.contourf(X, Y, Z, offset=0, levels=[-0.1, 0], cmap=cm.coolwarm)
|
||||
ax.set_xlim(-2, 2)
|
||||
ax.set_ylim(-2, 2)
|
||||
ax.set_zlim(-1, 1)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['tricontour'], remove_text=True,
|
||||
style='mpl20', extensions=['png'])
|
||||
def test_tricontour():
|
||||
fig = plt.figure()
|
||||
|
||||
np.random.seed(19680801)
|
||||
x = np.random.rand(1000) - 0.5
|
||||
y = np.random.rand(1000) - 0.5
|
||||
z = -(x**2 + y**2)
|
||||
|
||||
ax = fig.add_subplot(1, 2, 1, projection='3d')
|
||||
ax.tricontour(x, y, z)
|
||||
ax = fig.add_subplot(1, 2, 2, projection='3d')
|
||||
ax.tricontourf(x, y, z)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['lines3d'], remove_text=True)
|
||||
def test_lines3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
theta = np.linspace(-4 * np.pi, 4 * np.pi, 100)
|
||||
z = np.linspace(-2, 2, 100)
|
||||
r = z ** 2 + 1
|
||||
x = r * np.sin(theta)
|
||||
y = r * np.cos(theta)
|
||||
ax.plot(x, y, z)
|
||||
|
||||
|
||||
# Reason for flakiness of SVG test is still unknown.
|
||||
@image_comparison(baseline_images=['mixedsubplot'], remove_text=True,
|
||||
extensions=['png', 'pdf',
|
||||
pytest.mark.xfail('svg', strict=False)])
|
||||
def test_mixedsubplots():
|
||||
def f(t):
|
||||
s1 = np.cos(2*np.pi*t)
|
||||
e1 = np.exp(-t)
|
||||
return np.multiply(s1, e1)
|
||||
|
||||
t1 = np.arange(0.0, 5.0, 0.1)
|
||||
t2 = np.arange(0.0, 5.0, 0.02)
|
||||
|
||||
fig = plt.figure(figsize=plt.figaspect(2.))
|
||||
ax = fig.add_subplot(2, 1, 1)
|
||||
l = ax.plot(t1, f(t1), 'bo',
|
||||
t2, f(t2), 'k--', markerfacecolor='green')
|
||||
ax.grid(True)
|
||||
|
||||
ax = fig.add_subplot(2, 1, 2, projection='3d')
|
||||
X, Y = np.meshgrid(np.arange(-5, 5, 0.25), np.arange(-5, 5, 0.25))
|
||||
R = np.sqrt(X ** 2 + Y ** 2)
|
||||
Z = np.sin(R)
|
||||
|
||||
surf = ax.plot_surface(X, Y, Z, rcount=40, ccount=40,
|
||||
linewidth=0, antialiased=False)
|
||||
|
||||
ax.set_zlim3d(-1, 1)
|
||||
|
||||
|
||||
@check_figures_equal(extensions=['png'])
|
||||
def test_tight_layout_text(fig_test, fig_ref):
|
||||
# text is currently ignored in tight layout. So the order of text() and
|
||||
# tight_layout() calls should not influence the result.
|
||||
ax1 = fig_test.gca(projection='3d')
|
||||
ax1.text(.5, .5, .5, s='some string')
|
||||
fig_test.tight_layout()
|
||||
|
||||
ax2 = fig_ref.gca(projection='3d')
|
||||
fig_ref.tight_layout()
|
||||
ax2.text(.5, .5, .5, s='some string')
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['scatter3d'], remove_text=True)
|
||||
def test_scatter3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
ax.scatter(np.arange(10), np.arange(10), np.arange(10),
|
||||
c='r', marker='o')
|
||||
ax.scatter(np.arange(10, 20), np.arange(10, 20), np.arange(10, 20),
|
||||
c='b', marker='^')
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['scatter3d_color'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_scatter3d_color():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
ax.scatter(np.arange(10), np.arange(10), np.arange(10),
|
||||
color='r', marker='o')
|
||||
ax.scatter(np.arange(10, 20), np.arange(10, 20), np.arange(10, 20),
|
||||
color='b', marker='s')
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['plot_3d_from_2d'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_plot_3d_from_2d():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
xs = np.arange(0, 5)
|
||||
ys = np.arange(5, 10)
|
||||
ax.plot(xs, ys, zs=0, zdir='x')
|
||||
ax.plot(xs, ys, zs=0, zdir='y')
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['surface3d'], remove_text=True)
|
||||
def test_surface3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
X = np.arange(-5, 5, 0.25)
|
||||
Y = np.arange(-5, 5, 0.25)
|
||||
X, Y = np.meshgrid(X, Y)
|
||||
R = np.sqrt(X ** 2 + Y ** 2)
|
||||
Z = np.sin(R)
|
||||
surf = ax.plot_surface(X, Y, Z, rcount=40, ccount=40, cmap=cm.coolwarm,
|
||||
lw=0, antialiased=False)
|
||||
ax.set_zlim(-1.01, 1.01)
|
||||
fig.colorbar(surf, shrink=0.5, aspect=5)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['surface3d_shaded'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_surface3d_shaded():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
X = np.arange(-5, 5, 0.25)
|
||||
Y = np.arange(-5, 5, 0.25)
|
||||
X, Y = np.meshgrid(X, Y)
|
||||
R = np.sqrt(X ** 2 + Y ** 2)
|
||||
Z = np.sin(R)
|
||||
surf = ax.plot_surface(X, Y, Z, rstride=5, cstride=5,
|
||||
color=[0.25, 1, 0.25], lw=1, antialiased=False)
|
||||
ax.set_zlim(-1.01, 1.01)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['text3d'])
|
||||
def test_text3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
zdirs = (None, 'x', 'y', 'z', (1, 1, 0), (1, 1, 1))
|
||||
xs = (2, 6, 4, 9, 7, 2)
|
||||
ys = (6, 4, 8, 7, 2, 2)
|
||||
zs = (4, 2, 5, 6, 1, 7)
|
||||
|
||||
for zdir, x, y, z in zip(zdirs, xs, ys, zs):
|
||||
label = '(%d, %d, %d), dir=%s' % (x, y, z, zdir)
|
||||
ax.text(x, y, z, label, zdir)
|
||||
|
||||
ax.text(1, 1, 1, "red", color='red')
|
||||
ax.text2D(0.05, 0.95, "2D Text", transform=ax.transAxes)
|
||||
ax.set_xlim3d(0, 10)
|
||||
ax.set_ylim3d(0, 10)
|
||||
ax.set_zlim3d(0, 10)
|
||||
ax.set_xlabel('X axis')
|
||||
ax.set_ylabel('Y axis')
|
||||
ax.set_zlabel('Z axis')
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['trisurf3d'], remove_text=True, tol=0.03)
|
||||
def test_trisurf3d():
|
||||
n_angles = 36
|
||||
n_radii = 8
|
||||
radii = np.linspace(0.125, 1.0, n_radii)
|
||||
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
|
||||
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
|
||||
angles[:, 1::2] += np.pi/n_angles
|
||||
|
||||
x = np.append(0, (radii*np.cos(angles)).flatten())
|
||||
y = np.append(0, (radii*np.sin(angles)).flatten())
|
||||
z = np.sin(-x*y)
|
||||
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
ax.plot_trisurf(x, y, z, cmap=cm.jet, linewidth=0.2)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['trisurf3d_shaded'], remove_text=True,
|
||||
tol=0.03, extensions=['png'])
|
||||
def test_trisurf3d_shaded():
|
||||
n_angles = 36
|
||||
n_radii = 8
|
||||
radii = np.linspace(0.125, 1.0, n_radii)
|
||||
angles = np.linspace(0, 2*np.pi, n_angles, endpoint=False)
|
||||
angles = np.repeat(angles[..., np.newaxis], n_radii, axis=1)
|
||||
angles[:, 1::2] += np.pi/n_angles
|
||||
|
||||
x = np.append(0, (radii*np.cos(angles)).flatten())
|
||||
y = np.append(0, (radii*np.sin(angles)).flatten())
|
||||
z = np.sin(-x*y)
|
||||
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
ax.plot_trisurf(x, y, z, color=[1, 0.5, 0], linewidth=0.2)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['wireframe3d'], remove_text=True)
|
||||
def test_wireframe3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
ax.plot_wireframe(X, Y, Z, rcount=13, ccount=13)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['wireframe3dzerocstride'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_wireframe3dzerocstride():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
ax.plot_wireframe(X, Y, Z, rcount=13, ccount=0)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['wireframe3dzerorstride'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_wireframe3dzerorstride():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
ax.plot_wireframe(X, Y, Z, rstride=0, cstride=10)
|
||||
|
||||
|
||||
def test_wireframe3dzerostrideraises():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
with pytest.raises(ValueError):
|
||||
ax.plot_wireframe(X, Y, Z, rstride=0, cstride=0)
|
||||
|
||||
|
||||
def test_mixedsamplesraises():
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(111, projection='3d')
|
||||
X, Y, Z = axes3d.get_test_data(0.05)
|
||||
with pytest.raises(ValueError):
|
||||
ax.plot_wireframe(X, Y, Z, rstride=10, ccount=50)
|
||||
with pytest.raises(ValueError):
|
||||
ax.plot_surface(X, Y, Z, cstride=50, rcount=10)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['quiver3d'], remove_text=True)
|
||||
def test_quiver3d():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
x, y, z = np.ogrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
|
||||
|
||||
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
|
||||
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
|
||||
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
|
||||
np.sin(np.pi * z))
|
||||
|
||||
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True)
|
||||
|
||||
@image_comparison(baseline_images=['quiver3d_empty'], remove_text=True)
|
||||
def test_quiver3d_empty():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
x, y, z = np.ogrid[-1:0.8:0j, -1:0.8:0j, -1:0.6:0j]
|
||||
|
||||
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
|
||||
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
|
||||
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
|
||||
np.sin(np.pi * z))
|
||||
|
||||
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True)
|
||||
|
||||
@image_comparison(baseline_images=['quiver3d_masked'], remove_text=True)
|
||||
def test_quiver3d_masked():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
# Using mgrid here instead of ogrid because masked_where doesn't
|
||||
# seem to like broadcasting very much...
|
||||
x, y, z = np.mgrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
|
||||
|
||||
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
|
||||
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
|
||||
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
|
||||
np.sin(np.pi * z))
|
||||
u = np.ma.masked_where((-0.4 < x) & (x < 0.1), u, copy=False)
|
||||
v = np.ma.masked_where((0.1 < y) & (y < 0.7), v, copy=False)
|
||||
|
||||
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tip', normalize=True)
|
||||
|
||||
@image_comparison(baseline_images=['quiver3d_pivot_middle'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_quiver3d_pivot_middle():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
x, y, z = np.ogrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
|
||||
|
||||
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
|
||||
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
|
||||
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
|
||||
np.sin(np.pi * z))
|
||||
|
||||
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='middle', normalize=True)
|
||||
|
||||
@image_comparison(baseline_images=['quiver3d_pivot_tail'], remove_text=True,
|
||||
extensions=['png'])
|
||||
def test_quiver3d_pivot_tail():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
x, y, z = np.ogrid[-1:0.8:10j, -1:0.8:10j, -1:0.6:3j]
|
||||
|
||||
u = np.sin(np.pi * x) * np.cos(np.pi * y) * np.cos(np.pi * z)
|
||||
v = -np.cos(np.pi * x) * np.sin(np.pi * y) * np.cos(np.pi * z)
|
||||
w = (np.sqrt(2.0 / 3.0) * np.cos(np.pi * x) * np.cos(np.pi * y) *
|
||||
np.sin(np.pi * z))
|
||||
|
||||
ax.quiver(x, y, z, u, v, w, length=0.1, pivot='tail', normalize=True)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['poly3dcollection_closed'],
|
||||
remove_text=True)
|
||||
def test_poly3dcollection_closed():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
|
||||
poly1 = np.array([[0, 0, 1], [0, 1, 1], [0, 0, 0]], float)
|
||||
poly2 = np.array([[0, 1, 1], [1, 1, 1], [1, 1, 0]], float)
|
||||
c1 = art3d.Poly3DCollection([poly1], linewidths=3, edgecolor='k',
|
||||
facecolor=(0.5, 0.5, 1, 0.5), closed=True)
|
||||
c2 = art3d.Poly3DCollection([poly2], linewidths=3, edgecolor='k',
|
||||
facecolor=(1, 0.5, 0.5, 0.5), closed=False)
|
||||
ax.add_collection3d(c1)
|
||||
ax.add_collection3d(c2)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axes3d_labelpad'], extensions=['png'])
|
||||
def test_axes3d_labelpad():
|
||||
from matplotlib import rcParams
|
||||
|
||||
fig = plt.figure()
|
||||
ax = Axes3D(fig)
|
||||
# labelpad respects rcParams
|
||||
assert ax.xaxis.labelpad == rcParams['axes.labelpad']
|
||||
# labelpad can be set in set_label
|
||||
ax.set_xlabel('X LABEL', labelpad=10)
|
||||
assert ax.xaxis.labelpad == 10
|
||||
ax.set_ylabel('Y LABEL')
|
||||
ax.set_zlabel('Z LABEL')
|
||||
# or manually
|
||||
ax.yaxis.labelpad = 20
|
||||
ax.zaxis.labelpad = -40
|
||||
|
||||
# Tick labels also respect tick.pad (also from rcParams)
|
||||
for i, tick in enumerate(ax.yaxis.get_major_ticks()):
|
||||
tick.set_pad(tick.get_pad() - i * 5)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axes3d_cla'], extensions=['png'])
|
||||
def test_axes3d_cla():
|
||||
# fixed in pull request 4553
|
||||
fig = plt.figure()
|
||||
ax = fig.add_subplot(1,1,1, projection='3d')
|
||||
ax.set_axis_off()
|
||||
ax.cla() # make sure the axis displayed is 3D (not 2D)
|
||||
|
||||
def test_plotsurface_1d_raises():
|
||||
x = np.linspace(0.5, 10, num=100)
|
||||
y = np.linspace(0.5, 10, num=100)
|
||||
X, Y = np.meshgrid(x, y)
|
||||
z = np.random.randn(100)
|
||||
|
||||
fig = plt.figure(figsize=(14,6))
|
||||
ax = fig.add_subplot(1, 2, 1, projection='3d')
|
||||
with pytest.raises(ValueError):
|
||||
ax.plot_surface(X, Y, z)
|
||||
|
||||
|
||||
def _test_proj_make_M():
|
||||
# eye point
|
||||
E = np.array([1000, -1000, 2000])
|
||||
R = np.array([100, 100, 100])
|
||||
V = np.array([0, 0, 1])
|
||||
viewM = proj3d.view_transformation(E, R, V)
|
||||
perspM = proj3d.persp_transformation(100, -100)
|
||||
M = np.dot(perspM, viewM)
|
||||
return M
|
||||
|
||||
|
||||
def test_proj_transform():
|
||||
M = _test_proj_make_M()
|
||||
|
||||
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 300.0
|
||||
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 300.0
|
||||
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 300.0
|
||||
|
||||
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
|
||||
ixs, iys, izs = proj3d.inv_transform(txs, tys, tzs, M)
|
||||
|
||||
np.testing.assert_almost_equal(ixs, xs)
|
||||
np.testing.assert_almost_equal(iys, ys)
|
||||
np.testing.assert_almost_equal(izs, zs)
|
||||
|
||||
|
||||
def _test_proj_draw_axes(M, s=1, *args, **kwargs):
|
||||
xs = [0, s, 0, 0]
|
||||
ys = [0, 0, s, 0]
|
||||
zs = [0, 0, 0, s]
|
||||
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
|
||||
o, ax, ay, az = zip(txs, tys)
|
||||
lines = [(o, ax), (o, ay), (o, az)]
|
||||
|
||||
fig, ax = plt.subplots(*args, **kwargs)
|
||||
linec = LineCollection(lines)
|
||||
ax.add_collection(linec)
|
||||
for x, y, t in zip(txs, tys, ['o', 'x', 'y', 'z']):
|
||||
ax.text(x, y, t)
|
||||
|
||||
return fig, ax
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['proj3d_axes_cube'], extensions=['png'],
|
||||
remove_text=True, style='default')
|
||||
def test_proj_axes_cube():
|
||||
M = _test_proj_make_M()
|
||||
|
||||
ts = '0 1 2 3 0 4 5 6 7 4'.split()
|
||||
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 300.0
|
||||
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 300.0
|
||||
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 300.0
|
||||
|
||||
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
|
||||
|
||||
fig, ax = _test_proj_draw_axes(M, s=400)
|
||||
|
||||
ax.scatter(txs, tys, c=tzs)
|
||||
ax.plot(txs, tys, c='r')
|
||||
for x, y, t in zip(txs, tys, ts):
|
||||
ax.text(x, y, t)
|
||||
|
||||
ax.set_xlim(-0.2, 0.2)
|
||||
ax.set_ylim(-0.2, 0.2)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['proj3d_axes_cube_ortho'],
|
||||
extensions=['png'], remove_text=True, style='default')
|
||||
def test_proj_axes_cube_ortho():
|
||||
E = np.array([200, 100, 100])
|
||||
R = np.array([0, 0, 0])
|
||||
V = np.array([0, 0, 1])
|
||||
viewM = proj3d.view_transformation(E, R, V)
|
||||
orthoM = proj3d.ortho_transformation(-1, 1)
|
||||
M = np.dot(orthoM, viewM)
|
||||
|
||||
ts = '0 1 2 3 0 4 5 6 7 4'.split()
|
||||
xs = np.array([0, 1, 1, 0, 0, 0, 1, 1, 0, 0]) * 100
|
||||
ys = np.array([0, 0, 1, 1, 0, 0, 0, 1, 1, 0]) * 100
|
||||
zs = np.array([0, 0, 0, 0, 0, 1, 1, 1, 1, 1]) * 100
|
||||
|
||||
txs, tys, tzs = proj3d.proj_transform(xs, ys, zs, M)
|
||||
|
||||
fig, ax = _test_proj_draw_axes(M, s=150)
|
||||
|
||||
ax.scatter(txs, tys, s=300-tzs)
|
||||
ax.plot(txs, tys, c='r')
|
||||
for x, y, t in zip(txs, tys, ts):
|
||||
ax.text(x, y, t)
|
||||
|
||||
ax.set_xlim(-200, 200)
|
||||
ax.set_ylim(-200, 200)
|
||||
|
||||
def test_rot():
|
||||
V = [1, 0, 0, 1]
|
||||
rotated_V = proj3d.rot_x(V, np.pi / 6)
|
||||
np.testing.assert_allclose(rotated_V, [1, 0, 0, 1])
|
||||
|
||||
V = [0, 1, 0, 1]
|
||||
rotated_V = proj3d.rot_x(V, np.pi / 6)
|
||||
np.testing.assert_allclose(rotated_V, [0, np.sqrt(3) / 2, 0.5, 1])
|
||||
|
||||
|
||||
def test_world():
|
||||
xmin, xmax = 100, 120
|
||||
ymin, ymax = -100, 100
|
||||
zmin, zmax = 0.1, 0.2
|
||||
M = proj3d.world_transformation(xmin, xmax, ymin, ymax, zmin, zmax)
|
||||
np.testing.assert_allclose(M,
|
||||
[[5e-2, 0, 0, -5],
|
||||
[0, 5e-3, 0, 5e-1],
|
||||
[0, 0, 1e1, -1],
|
||||
[0, 0, 0, 1]])
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['proj3d_lines_dists'], extensions=['png'],
|
||||
remove_text=True, style='default')
|
||||
def test_lines_dists():
|
||||
fig, ax = plt.subplots(figsize=(4, 6), subplot_kw=dict(aspect='equal'))
|
||||
|
||||
xs = (0, 30)
|
||||
ys = (20, 150)
|
||||
ax.plot(xs, ys)
|
||||
p0, p1 = zip(xs, ys)
|
||||
|
||||
xs = (0, 0, 20, 30)
|
||||
ys = (100, 150, 30, 200)
|
||||
ax.scatter(xs, ys)
|
||||
|
||||
dist = proj3d.line2d_seg_dist(p0, p1, (xs[0], ys[0]))
|
||||
dist = proj3d.line2d_seg_dist(p0, p1, np.array((xs, ys)))
|
||||
for x, y, d in zip(xs, ys, dist):
|
||||
c = Circle((x, y), d, fill=0)
|
||||
ax.add_patch(c)
|
||||
|
||||
ax.set_xlim(-50, 150)
|
||||
ax.set_ylim(0, 300)
|
||||
|
||||
|
||||
def test_autoscale():
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
ax.margins(x=0, y=.1, z=.2)
|
||||
ax.plot([0, 1], [0, 1], [0, 1])
|
||||
assert ax.get_w_lims() == (0, 1, -.1, 1.1, -.2, 1.2)
|
||||
ax.autoscale(False)
|
||||
ax.set_autoscalez_on(True)
|
||||
ax.plot([0, 2], [0, 2], [0, 2])
|
||||
assert ax.get_w_lims() == (0, 1, -.1, 1.1, -.4, 2.4)
|
||||
|
||||
|
||||
@image_comparison(baseline_images=['axes3d_ortho'], style='default')
|
||||
def test_axes3d_ortho():
|
||||
fig = plt.figure()
|
||||
ax = fig.gca(projection='3d')
|
||||
ax.set_proj_type('ortho')
|
||||
|
||||
|
||||
@pytest.mark.parametrize('value', [np.inf, np.nan])
|
||||
@pytest.mark.parametrize(('setter', 'side'), [
|
||||
('set_xlim3d', 'left'),
|
||||
('set_xlim3d', 'right'),
|
||||
('set_ylim3d', 'bottom'),
|
||||
('set_ylim3d', 'top'),
|
||||
('set_zlim3d', 'bottom'),
|
||||
('set_zlim3d', 'top'),
|
||||
])
|
||||
def test_invalid_axes_limits(setter, side, value):
|
||||
limit = {side: value}
|
||||
fig = plt.figure()
|
||||
obj = fig.add_subplot(111, projection='3d')
|
||||
with pytest.raises(ValueError):
|
||||
getattr(obj, setter)(**limit)
|
||||
|
||||
|
||||
class TestVoxels(object):
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-simple'],
|
||||
extensions=['png'],
|
||||
remove_text=True
|
||||
)
|
||||
def test_simple(self):
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
x, y, z = np.indices((5, 4, 3))
|
||||
voxels = (x == y) | (y == z)
|
||||
ax.voxels(voxels)
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-edge-style'],
|
||||
extensions=['png'],
|
||||
remove_text=True,
|
||||
style='default'
|
||||
)
|
||||
def test_edge_style(self):
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
x, y, z = np.indices((5, 5, 4))
|
||||
voxels = ((x - 2)**2 + (y - 2)**2 + (z-1.5)**2) < 2.2**2
|
||||
v = ax.voxels(voxels, linewidths=3, edgecolor='C1')
|
||||
|
||||
# change the edge color of one voxel
|
||||
v[max(v.keys())].set_edgecolor('C2')
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-named-colors'],
|
||||
extensions=['png'],
|
||||
remove_text=True
|
||||
)
|
||||
def test_named_colors(self):
|
||||
""" test with colors set to a 3d object array of strings """
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
x, y, z = np.indices((10, 10, 10))
|
||||
voxels = (x == y) | (y == z)
|
||||
voxels = voxels & ~(x * y * z < 1)
|
||||
colors = np.zeros((10, 10, 10), dtype=np.object_)
|
||||
colors.fill('C0')
|
||||
colors[(x < 5) & (y < 5)] = '0.25'
|
||||
colors[(x + z) < 10] = 'cyan'
|
||||
ax.voxels(voxels, facecolors=colors)
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-rgb-data'],
|
||||
extensions=['png'],
|
||||
remove_text=True
|
||||
)
|
||||
def test_rgb_data(self):
|
||||
""" test with colors set to a 4d float array of rgb data """
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
x, y, z = np.indices((10, 10, 10))
|
||||
voxels = (x == y) | (y == z)
|
||||
colors = np.zeros((10, 10, 10, 3))
|
||||
colors[...,0] = x/9.0
|
||||
colors[...,1] = y/9.0
|
||||
colors[...,2] = z/9.0
|
||||
ax.voxels(voxels, facecolors=colors)
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-alpha'],
|
||||
extensions=['png'],
|
||||
remove_text=True
|
||||
)
|
||||
def test_alpha(self):
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
x, y, z = np.indices((10, 10, 10))
|
||||
v1 = x == y
|
||||
v2 = np.abs(x - y) < 2
|
||||
voxels = v1 | v2
|
||||
colors = np.zeros((10, 10, 10, 4))
|
||||
colors[v2] = [1, 0, 0, 0.5]
|
||||
colors[v1] = [0, 1, 0, 0.5]
|
||||
v = ax.voxels(voxels, facecolors=colors)
|
||||
|
||||
assert type(v) is dict
|
||||
for coord, poly in v.items():
|
||||
assert voxels[coord], "faces returned for absent voxel"
|
||||
assert isinstance(poly, art3d.Poly3DCollection)
|
||||
|
||||
@image_comparison(
|
||||
baseline_images=['voxels-xyz'],
|
||||
extensions=['png'],
|
||||
tol=0.01
|
||||
)
|
||||
def test_xyz(self):
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
def midpoints(x):
|
||||
sl = ()
|
||||
for i in range(x.ndim):
|
||||
x = (x[sl + np.index_exp[:-1]] +
|
||||
x[sl + np.index_exp[1:]]) / 2.0
|
||||
sl += np.index_exp[:]
|
||||
return x
|
||||
|
||||
# prepare some coordinates, and attach rgb values to each
|
||||
r, g, b = np.indices((17, 17, 17)) / 16.0
|
||||
rc = midpoints(r)
|
||||
gc = midpoints(g)
|
||||
bc = midpoints(b)
|
||||
|
||||
# define a sphere about [0.5, 0.5, 0.5]
|
||||
sphere = (rc - 0.5)**2 + (gc - 0.5)**2 + (bc - 0.5)**2 < 0.5**2
|
||||
|
||||
# combine the color components
|
||||
colors = np.zeros(sphere.shape + (3,))
|
||||
colors[..., 0] = rc
|
||||
colors[..., 1] = gc
|
||||
colors[..., 2] = bc
|
||||
|
||||
# and plot everything
|
||||
ax.voxels(r, g, b, sphere,
|
||||
facecolors=colors,
|
||||
edgecolors=np.clip(2*colors - 0.5, 0, 1), # brighter
|
||||
linewidth=0.5)
|
||||
|
||||
def test_calling_conventions(self):
|
||||
x, y, z = np.indices((3, 4, 5))
|
||||
filled = np.ones((2, 3, 4))
|
||||
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
|
||||
# all the valid calling conventions
|
||||
for kw in (dict(), dict(edgecolor='k')):
|
||||
ax.voxels(filled, **kw)
|
||||
ax.voxels(filled=filled, **kw)
|
||||
ax.voxels(x, y, z, filled, **kw)
|
||||
ax.voxels(x, y, z, filled=filled, **kw)
|
||||
|
||||
# duplicate argument
|
||||
with pytest.raises(TypeError) as exc:
|
||||
ax.voxels(x, y, z, filled, filled=filled)
|
||||
exc.match(".*voxels.*")
|
||||
# missing arguments
|
||||
with pytest.raises(TypeError) as exc:
|
||||
ax.voxels(x, y)
|
||||
exc.match(".*voxels.*")
|
||||
# x,y,z are positional only - this passes them on as attributes of
|
||||
# Poly3DCollection
|
||||
with pytest.raises(AttributeError):
|
||||
ax.voxels(filled=filled, x=x, y=y, z=z)
|
||||
|
||||
|
||||
def test_inverted_cla():
|
||||
# Github PR #5450. Setting autoscale should reset
|
||||
# axes to be non-inverted.
|
||||
fig, ax = plt.subplots(subplot_kw={"projection": "3d"})
|
||||
# 1. test that a new axis is not inverted per default
|
||||
assert not ax.xaxis_inverted()
|
||||
assert not ax.yaxis_inverted()
|
||||
assert not ax.zaxis_inverted()
|
||||
ax.set_xlim(1, 0)
|
||||
ax.set_ylim(1, 0)
|
||||
ax.set_zlim(1, 0)
|
||||
assert ax.xaxis_inverted()
|
||||
assert ax.yaxis_inverted()
|
||||
assert ax.zaxis_inverted()
|
||||
ax.cla()
|
||||
assert not ax.xaxis_inverted()
|
||||
assert not ax.yaxis_inverted()
|
||||
assert not ax.zaxis_inverted()
|
||||
Reference in New Issue
Block a user