You cannot select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
249 lines
7.4 KiB
Python
249 lines
7.4 KiB
Python
import io
|
|
|
|
import numpy as np
|
|
from numpy.testing import assert_array_almost_equal
|
|
import pytest
|
|
|
|
from matplotlib import (
|
|
collections, path, pyplot as plt, transforms as mtransforms, rcParams)
|
|
from matplotlib.image import imread
|
|
from matplotlib.figure import Figure
|
|
from matplotlib.testing.decorators import image_comparison
|
|
|
|
|
|
def test_repeated_save_with_alpha():
|
|
# We want an image which has a background color of bluish green, with an
|
|
# alpha of 0.25.
|
|
|
|
fig = Figure([1, 0.4])
|
|
fig.set_facecolor((0, 1, 0.4))
|
|
fig.patch.set_alpha(0.25)
|
|
|
|
# The target color is fig.patch.get_facecolor()
|
|
|
|
buf = io.BytesIO()
|
|
|
|
fig.savefig(buf,
|
|
facecolor=fig.get_facecolor(),
|
|
edgecolor='none')
|
|
|
|
# Save the figure again to check that the
|
|
# colors don't bleed from the previous renderer.
|
|
buf.seek(0)
|
|
fig.savefig(buf,
|
|
facecolor=fig.get_facecolor(),
|
|
edgecolor='none')
|
|
|
|
# Check the first pixel has the desired color & alpha
|
|
# (approx: 0, 1.0, 0.4, 0.25)
|
|
buf.seek(0)
|
|
assert_array_almost_equal(tuple(imread(buf)[0, 0]),
|
|
(0.0, 1.0, 0.4, 0.250),
|
|
decimal=3)
|
|
|
|
|
|
def test_large_single_path_collection():
|
|
buff = io.BytesIO()
|
|
|
|
# Generates a too-large single path in a path collection that
|
|
# would cause a segfault if the draw_markers optimization is
|
|
# applied.
|
|
f, ax = plt.subplots()
|
|
collection = collections.PathCollection(
|
|
[path.Path([[-10, 5], [10, 5], [10, -5], [-10, -5], [-10, 5]])])
|
|
ax.add_artist(collection)
|
|
ax.set_xlim(10**-3, 1)
|
|
plt.savefig(buff)
|
|
|
|
|
|
def test_marker_with_nan():
|
|
# This creates a marker with nans in it, which was segfaulting the
|
|
# Agg backend (see #3722)
|
|
fig, ax = plt.subplots(1)
|
|
steps = 1000
|
|
data = np.arange(steps)
|
|
ax.semilogx(data)
|
|
ax.fill_between(data, data*0.8, data*1.2)
|
|
buf = io.BytesIO()
|
|
fig.savefig(buf, format='png')
|
|
|
|
|
|
def test_long_path():
|
|
buff = io.BytesIO()
|
|
|
|
fig, ax = plt.subplots()
|
|
np.random.seed(0)
|
|
points = np.random.rand(70000)
|
|
ax.plot(points)
|
|
fig.savefig(buff, format='png')
|
|
|
|
|
|
@image_comparison(['agg_filter.png'], remove_text=True)
|
|
def test_agg_filter():
|
|
def smooth1d(x, window_len):
|
|
# copied from http://www.scipy.org/Cookbook/SignalSmooth
|
|
s = np.r_[
|
|
2*x[0] - x[window_len:1:-1], x, 2*x[-1] - x[-1:-window_len:-1]]
|
|
w = np.hanning(window_len)
|
|
y = np.convolve(w/w.sum(), s, mode='same')
|
|
return y[window_len-1:-window_len+1]
|
|
|
|
def smooth2d(A, sigma=3):
|
|
window_len = max(int(sigma), 3) * 2 + 1
|
|
A = np.apply_along_axis(smooth1d, 0, A, window_len)
|
|
A = np.apply_along_axis(smooth1d, 1, A, window_len)
|
|
return A
|
|
|
|
class BaseFilter:
|
|
|
|
def get_pad(self, dpi):
|
|
return 0
|
|
|
|
def process_image(padded_src, dpi):
|
|
raise NotImplementedError("Should be overridden by subclasses")
|
|
|
|
def __call__(self, im, dpi):
|
|
pad = self.get_pad(dpi)
|
|
padded_src = np.pad(im, [(pad, pad), (pad, pad), (0, 0)],
|
|
"constant")
|
|
tgt_image = self.process_image(padded_src, dpi)
|
|
return tgt_image, -pad, -pad
|
|
|
|
class OffsetFilter(BaseFilter):
|
|
|
|
def __init__(self, offsets=(0, 0)):
|
|
self.offsets = offsets
|
|
|
|
def get_pad(self, dpi):
|
|
return int(max(self.offsets) / 72 * dpi)
|
|
|
|
def process_image(self, padded_src, dpi):
|
|
ox, oy = self.offsets
|
|
a1 = np.roll(padded_src, int(ox / 72 * dpi), axis=1)
|
|
a2 = np.roll(a1, -int(oy / 72 * dpi), axis=0)
|
|
return a2
|
|
|
|
class GaussianFilter(BaseFilter):
|
|
"""Simple Gaussian filter."""
|
|
|
|
def __init__(self, sigma, alpha=0.5, color=(0, 0, 0)):
|
|
self.sigma = sigma
|
|
self.alpha = alpha
|
|
self.color = color
|
|
|
|
def get_pad(self, dpi):
|
|
return int(self.sigma*3 / 72 * dpi)
|
|
|
|
def process_image(self, padded_src, dpi):
|
|
tgt_image = np.empty_like(padded_src)
|
|
tgt_image[:, :, :3] = self.color
|
|
tgt_image[:, :, 3] = smooth2d(padded_src[:, :, 3] * self.alpha,
|
|
self.sigma / 72 * dpi)
|
|
return tgt_image
|
|
|
|
class DropShadowFilter(BaseFilter):
|
|
|
|
def __init__(self, sigma, alpha=0.3, color=(0, 0, 0), offsets=(0, 0)):
|
|
self.gauss_filter = GaussianFilter(sigma, alpha, color)
|
|
self.offset_filter = OffsetFilter(offsets)
|
|
|
|
def get_pad(self, dpi):
|
|
return max(self.gauss_filter.get_pad(dpi),
|
|
self.offset_filter.get_pad(dpi))
|
|
|
|
def process_image(self, padded_src, dpi):
|
|
t1 = self.gauss_filter.process_image(padded_src, dpi)
|
|
t2 = self.offset_filter.process_image(t1, dpi)
|
|
return t2
|
|
|
|
fig, ax = plt.subplots()
|
|
|
|
# draw lines
|
|
l1, = ax.plot([0.1, 0.5, 0.9], [0.1, 0.9, 0.5], "bo-",
|
|
mec="b", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
|
|
l2, = ax.plot([0.1, 0.5, 0.9], [0.5, 0.2, 0.7], "ro-",
|
|
mec="r", mfc="w", lw=5, mew=3, ms=10, label="Line 1")
|
|
|
|
gauss = DropShadowFilter(4)
|
|
|
|
for l in [l1, l2]:
|
|
|
|
# draw shadows with same lines with slight offset.
|
|
xx = l.get_xdata()
|
|
yy = l.get_ydata()
|
|
shadow, = ax.plot(xx, yy)
|
|
shadow.update_from(l)
|
|
|
|
# offset transform
|
|
ot = mtransforms.offset_copy(l.get_transform(), ax.figure,
|
|
x=4.0, y=-6.0, units='points')
|
|
|
|
shadow.set_transform(ot)
|
|
|
|
# adjust zorder of the shadow lines so that it is drawn below the
|
|
# original lines
|
|
shadow.set_zorder(l.get_zorder() - 0.5)
|
|
shadow.set_agg_filter(gauss)
|
|
shadow.set_rasterized(True) # to support mixed-mode renderers
|
|
|
|
ax.set_xlim(0., 1.)
|
|
ax.set_ylim(0., 1.)
|
|
|
|
ax.xaxis.set_visible(False)
|
|
ax.yaxis.set_visible(False)
|
|
|
|
|
|
def test_too_large_image():
|
|
fig = plt.figure(figsize=(300, 1000))
|
|
buff = io.BytesIO()
|
|
with pytest.raises(ValueError):
|
|
fig.savefig(buff)
|
|
|
|
|
|
def test_chunksize():
|
|
x = range(200)
|
|
|
|
# Test without chunksize
|
|
fig, ax = plt.subplots()
|
|
ax.plot(x, np.sin(x))
|
|
fig.canvas.draw()
|
|
|
|
# Test with chunksize
|
|
fig, ax = plt.subplots()
|
|
rcParams['agg.path.chunksize'] = 105
|
|
ax.plot(x, np.sin(x))
|
|
fig.canvas.draw()
|
|
|
|
|
|
@pytest.mark.backend('Agg')
|
|
def test_jpeg_dpi():
|
|
Image = pytest.importorskip("PIL.Image")
|
|
# Check that dpi is set correctly in jpg files.
|
|
plt.plot([0, 1, 2], [0, 1, 0])
|
|
buf = io.BytesIO()
|
|
plt.savefig(buf, format="jpg", dpi=200)
|
|
im = Image.open(buf)
|
|
assert im.info['dpi'] == (200, 200)
|
|
|
|
|
|
def test_pil_kwargs_png():
|
|
Image = pytest.importorskip("PIL.Image")
|
|
from PIL.PngImagePlugin import PngInfo
|
|
buf = io.BytesIO()
|
|
pnginfo = PngInfo()
|
|
pnginfo.add_text("Software", "test")
|
|
plt.figure().savefig(buf, format="png", pil_kwargs={"pnginfo": pnginfo})
|
|
im = Image.open(buf)
|
|
assert im.info["Software"] == "test"
|
|
|
|
|
|
def test_pil_kwargs_tiff():
|
|
Image = pytest.importorskip("PIL.Image")
|
|
from PIL.TiffTags import TAGS_V2 as TAGS
|
|
buf = io.BytesIO()
|
|
pil_kwargs = {"description": "test image"}
|
|
plt.figure().savefig(buf, format="tiff", pil_kwargs=pil_kwargs)
|
|
im = Image.open(buf)
|
|
tags = {TAGS[k].name: v for k, v in im.tag_v2.items()}
|
|
assert tags["ImageDescription"] == "test image"
|