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Python

import numpy as np
from io import BytesIO
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=dict(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]]
colLabels = rowLabels = [''] * 5
rows = len(data)
ind = np.arange(len(colLabels)) + 0.3 # the x locations for the groups
cellText = []
width = 0.4 # the width of the bars
yoff = np.zeros(len(colLabels))
# 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]
cellText.append([''])
plt.xticks([])
plt.xlim(0, 5)
plt.legend([''] * 5, loc=(1.2, 0.2))
# Add a table at the bottom of the axes
cellText.reverse()
plt.table(cellText=cellText, rowLabels=rowLabels, colLabels=colLabels,
loc='bottom')
@image_comparison(['bbox_inches_tight_suptile_legend'],
remove_text=False, savefig_kwarg={'bbox_inches': 'tight'})
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_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 = plt.figure()
ax = fig.add_subplot(111)
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