from __future__ import (absolute_import, division, print_function,

unicode_literals)

import six

import os

import shutil

from nose.tools import assert_equal, assert_not_equal, assert_almost_equal

from matplotlib.testing.compare import compare_images

from matplotlib.testing.decorators import _image_directories

baseline_dir, result_dir = _image_directories(lambda: 'dummy func')

# Tests of the image comparison algorithm.

def image_comparison_expect_rms(im1, im2, tol, expect_rms):

"""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.

"""

im1 = os.path.join(baseline_dir, im1)

im2_src = os.path.join(baseline_dir, im2)

im2 = os.path.join(result_dir, im2)

# Move im2 from baseline_dir to result_dir. This will ensure that

# compare_images writes the diff file to result_dir, instead of trying to

# write to the (possibly read-only) baseline_dir.

shutil.copyfile(im2_src, im2)

results = compare_images(im1, im2, tol=tol, in_decorator=True)

if expect_rms is None:

assert_equal(None, results)

else:

assert_not_equal(None, results)

assert_almost_equal(expect_rms, results['rms'], places=4)

def test_image_compare_basic():

#: Test 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.

im1 = 'basn3p02.png'

im2 = 'basn3p02-minorchange.png'

image_comparison_expect_rms(im1, im2, tol=10, expect_rms=None)

# Now test with no tolerance.

image_comparison_expect_rms(im1, im2, tol=0, expect_rms=6.50646)

def test_image_compare_1px_offset():

#: Test comparison with an image that is shifted by 1px in the X axis.

im1 = 'basn3p02.png'

im2 = 'basn3p02-1px-offset.png'

image_comparison_expect_rms(im1, im2, tol=0, expect_rms=90.15611)

def test_image_compare_half_1px_offset():

#: Test comparison with an image with half the pixels shifted by 1px in

#: the X axis.

im1 = 'basn3p02.png'

im2 = 'basn3p02-half-1px-offset.png'

image_comparison_expect_rms(im1, im2, tol=0, expect_rms=63.75)

def test_image_compare_scrambled():

#: Test 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.

im1 = 'basn3p02.png'

im2 = 'basn3p02-scrambled.png'

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

# error.

image_comparison_expect_rms(im1, im2, tol=0, expect_rms=172.63582)

def test_image_compare_shade_difference():

#: Test 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.

im1 = 'all127.png'

im2 = 'all128.png'

image_comparison_expect_rms(im1, im2, tol=0, expect_rms=1.0)

# Now test the reverse comparison.

image_comparison_expect_rms(im2, im1, tol=0, expect_rms=1.0)

if __name__ == '__main__':

import nose

nose.runmodule(argv=['-s', '--with-doctest'], exit=False)