AIM-PIbd-32-Kurbanova-A-A/aimenv/Lib/site-packages/matplotlib/tests/test_bbox_tight.py
2024-10-02 22:15:59 +04:00

176 lines
6.2 KiB
Python

from io import BytesIO
import platform
import numpy as np
from matplotlib.testing.decorators import image_comparison
import matplotlib.pyplot as plt
import matplotlib.path as mpath
import matplotlib.patches as mpatches
from matplotlib.ticker import FuncFormatter
@image_comparison(['bbox_inches_tight'], remove_text=True,
savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight():
#: Test that a figure saved using bbox_inches='tight' is clipped correctly
data = [[66386, 174296, 75131, 577908, 32015],
[58230, 381139, 78045, 99308, 160454],
[89135, 80552, 152558, 497981, 603535],
[78415, 81858, 150656, 193263, 69638],
[139361, 331509, 343164, 781380, 52269]]
col_labels = row_labels = [''] * 5
rows = len(data)
ind = np.arange(len(col_labels)) + 0.3 # the x locations for the groups
cell_text = []
width = 0.4 # the width of the bars
yoff = np.zeros(len(col_labels))
# the bottom values for stacked bar chart
fig, ax = plt.subplots(1, 1)
for row in range(rows):
ax.bar(ind, data[row], width, bottom=yoff, align='edge', color='b')
yoff = yoff + data[row]
cell_text.append([''])
plt.xticks([])
plt.xlim(0, 5)
plt.legend([''] * 5, loc=(1.2, 0.2))
fig.legend([''] * 5, bbox_to_anchor=(0, 0.2), loc='lower left')
# Add a table at the bottom of the axes
cell_text.reverse()
plt.table(cellText=cell_text, rowLabels=row_labels, colLabels=col_labels,
loc='bottom')
@image_comparison(['bbox_inches_tight_suptile_legend'],
savefig_kwarg={'bbox_inches': 'tight'},
tol=0.02 if platform.machine() == 'arm64' else 0)
def test_bbox_inches_tight_suptile_legend():
plt.plot(np.arange(10), label='a straight line')
plt.legend(bbox_to_anchor=(0.9, 1), loc='upper left')
plt.title('Axis title')
plt.suptitle('Figure title')
# put an extra long y tick on to see that the bbox is accounted for
def y_formatter(y, pos):
if int(y) == 4:
return 'The number 4'
else:
return str(y)
plt.gca().yaxis.set_major_formatter(FuncFormatter(y_formatter))
plt.xlabel('X axis')
@image_comparison(['bbox_inches_tight_suptile_non_default.png'],
savefig_kwarg={'bbox_inches': 'tight'},
tol=0.1) # large tolerance because only testing clipping.
def test_bbox_inches_tight_suptitle_non_default():
fig, ax = plt.subplots()
fig.suptitle('Booo', x=0.5, y=1.1)
@image_comparison(['bbox_inches_tight_layout.png'], remove_text=True,
style='mpl20',
savefig_kwarg=dict(bbox_inches='tight', pad_inches='layout'))
def test_bbox_inches_tight_layout_constrained():
fig, ax = plt.subplots(layout='constrained')
fig.get_layout_engine().set(h_pad=0.5)
ax.set_aspect('equal')
def test_bbox_inches_tight_layout_notconstrained(tmp_path):
# pad_inches='layout' should be ignored when not using constrained/
# compressed layout. Smoke test that savefig doesn't error in this case.
fig, ax = plt.subplots()
fig.savefig(tmp_path / 'foo.png', bbox_inches='tight', pad_inches='layout')
@image_comparison(['bbox_inches_tight_clipping'],
remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_clipping():
# tests bbox clipping on scatter points, and path clipping on a patch
# to generate an appropriately tight bbox
plt.scatter(np.arange(10), np.arange(10))
ax = plt.gca()
ax.set_xlim(0, 5)
ax.set_ylim(0, 5)
# make a massive rectangle and clip it with a path
patch = mpatches.Rectangle([-50, -50], 100, 100,
transform=ax.transData,
facecolor='blue', alpha=0.5)
path = mpath.Path.unit_regular_star(5).deepcopy()
path.vertices *= 0.25
patch.set_clip_path(path, transform=ax.transAxes)
plt.gcf().artists.append(patch)
@image_comparison(['bbox_inches_tight_raster'],
remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_tight_raster():
"""Test rasterization with tight_layout"""
fig, ax = plt.subplots()
ax.plot([1.0, 2.0], rasterized=True)
def test_only_on_non_finite_bbox():
fig, ax = plt.subplots()
ax.annotate("", xy=(0, float('nan')))
ax.set_axis_off()
# we only need to test that it does not error out on save
fig.savefig(BytesIO(), bbox_inches='tight', format='png')
def test_tight_pcolorfast():
fig, ax = plt.subplots()
ax.pcolorfast(np.arange(4).reshape((2, 2)))
ax.set(ylim=(0, .1))
buf = BytesIO()
fig.savefig(buf, bbox_inches="tight")
buf.seek(0)
height, width, _ = plt.imread(buf).shape
# Previously, the bbox would include the area of the image clipped out by
# the axes, resulting in a very tall image given the y limits of (0, 0.1).
assert width > height
def test_noop_tight_bbox():
from PIL import Image
x_size, y_size = (10, 7)
dpi = 100
# make the figure just the right size up front
fig = plt.figure(frameon=False, dpi=dpi, figsize=(x_size/dpi, y_size/dpi))
ax = fig.add_axes((0, 0, 1, 1))
ax.set_axis_off()
ax.xaxis.set_visible(False)
ax.yaxis.set_visible(False)
data = np.arange(x_size * y_size).reshape(y_size, x_size)
ax.imshow(data, rasterized=True)
# When a rasterized Artist is included, a mixed-mode renderer does
# additional bbox adjustment. It should also be a no-op, and not affect the
# next save.
fig.savefig(BytesIO(), bbox_inches='tight', pad_inches=0, format='pdf')
out = BytesIO()
fig.savefig(out, bbox_inches='tight', pad_inches=0)
out.seek(0)
im = np.asarray(Image.open(out))
assert (im[:, :, 3] == 255).all()
assert not (im[:, :, :3] == 255).all()
assert im.shape == (7, 10, 4)
@image_comparison(['bbox_inches_fixed_aspect'], extensions=['png'],
remove_text=True, savefig_kwarg={'bbox_inches': 'tight'})
def test_bbox_inches_fixed_aspect():
with plt.rc_context({'figure.constrained_layout.use': True}):
fig, ax = plt.subplots()
ax.plot([0, 1])
ax.set_xlim(0, 1)
ax.set_aspect('equal')