matplotlib/lib/matplotlib/tests/test_compare_images.py at main · spha-code/matplotlib · GitHub

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from pathlib import Path

import shutil

import numpy as np

import pytest

from pytest import approx

from matplotlib import _image

from matplotlib.testing.compare import compare_images

from matplotlib.testing.decorators import _image_directories

from matplotlib.testing.exceptions import ImageComparisonFailure

# Tests of the image comparison algorithm.

@pytest.mark.parametrize(

'im1, im2, tol, expect_rms',

[

# Comparison of an image and the same image with minor differences.

# This expects the images to compare equal under normal tolerance, and

# have a small RMS.

('basn3p02.png', 'basn3p02-minorchange.png', 10, None),

# Now test with no tolerance.

('basn3p02.png', 'basn3p02-minorchange.png', 0, 6.50646),

# Comparison with an image that is shifted by 1px in the X axis.

('basn3p02.png', 'basn3p02-1px-offset.png', 0, 90.15611),

# Comparison with an image with half the pixels shifted by 1px in the X

# axis.

('basn3p02.png', 'basn3p02-half-1px-offset.png', 0, 63.75),

# Comparison of an image and the same image scrambled.

# This expects the images to compare completely different, with a very

# large RMS.

# Note: The image has been scrambled in a specific way, by having

# each color component of each pixel randomly placed somewhere in the

# image. It contains exactly the same number of pixels of each color

# value of R, G and B, but in a totally different position.

# Test with no tolerance to make sure that we pick up even a very small

# RMS error.

('basn3p02.png', 'basn3p02-scrambled.png', 0, 172.63582),

# Comparison of an image and a slightly brighter image.

# The two images are solid color, with the second image being exactly 1

# color value brighter.

# This expects the images to compare equal under normal tolerance, and

# have an RMS of exactly 1.

('all127.png', 'all128.png', 0, 1),

# Now test the reverse comparison.

('all128.png', 'all127.png', 0, 1),

])

def test_image_comparison_expect_rms(im1, im2, tol, expect_rms, tmp_path,

monkeypatch):

"""

Compare two images, expecting a particular RMS error.

im1 and im2 are filenames relative to the baseline_dir directory.

tol is the tolerance to pass to compare_images.

expect_rms is the expected RMS value, or None. If None, the test will

succeed if compare_images succeeds. Otherwise, the test will succeed if

compare_images fails and returns an RMS error almost equal to this value.

"""

# Change the working directory using monkeypatch to use a temporary

# test specific directory

monkeypatch.chdir(tmp_path)

baseline_dir, result_dir = map(Path, _image_directories(lambda: "dummy"))

# Copy "test" image to result_dir, so that compare_images writes

# the diff to result_dir, rather than to the source tree

result_im2 = result_dir / im1

shutil.copyfile(baseline_dir / im2, result_im2)

results = compare_images(

baseline_dir / im1, result_im2, tol=tol, in_decorator=True)

if expect_rms is None:

assert results is None

else:

assert results is not None

assert results['rms'] == approx(expect_rms, abs=1e-4)

def test_invalid_input():

img = np.zeros((16, 16, 4), dtype=np.uint8)