/usr/share/pyshared/matplotlib/testing/compare.py is in python-matplotlib 1.1.1~rc1+git20120423-0ubuntu1.
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""" A set of utilities for comparing results.
"""
#=======================================================================
import matplotlib
from matplotlib.testing.noseclasses import ImageComparisonFailure
import math
import operator
import os
import numpy as np
import shutil
import subprocess
import sys
#=======================================================================
__all__ = [
'compare_float',
'compare_images',
'comparable_formats',
]
#-----------------------------------------------------------------------
def compare_float( expected, actual, relTol = None, absTol = None ):
"""Fail if the floating point values are not close enough, with
the givem message.
You can specify a relative tolerance, absolute tolerance, or both.
"""
if relTol is None and absTol is None:
exMsg = "You haven't specified a 'relTol' relative tolerance "
exMsg += "or a 'absTol' absolute tolerance function argument. "
exMsg += "You must specify one."
raise ValueError, exMsg
msg = ""
if absTol is not None:
absDiff = abs( expected - actual )
if absTol < absDiff:
expectedStr = str( expected )
actualStr = str( actual )
absDiffStr = str( absDiff )
absTolStr = str( absTol )
msg += "\n"
msg += " Expected: " + expectedStr + "\n"
msg += " Actual: " + actualStr + "\n"
msg += " Abs Diff: " + absDiffStr + "\n"
msg += " Abs Tol: " + absTolStr + "\n"
if relTol is not None:
# The relative difference of the two values. If the expected value is
# zero, then return the absolute value of the difference.
relDiff = abs( expected - actual )
if expected:
relDiff = relDiff / abs( expected )
if relTol < relDiff:
# The relative difference is a ratio, so it's always unitless.
relDiffStr = str( relDiff )
relTolStr = str( relTol )
expectedStr = str( expected )
actualStr = str( actual )
msg += "\n"
msg += " Expected: " + expectedStr + "\n"
msg += " Actual: " + actualStr + "\n"
msg += " Rel Diff: " + relDiffStr + "\n"
msg += " Rel Tol: " + relTolStr + "\n"
if msg:
return msg
else:
return None
#-----------------------------------------------------------------------
# A dictionary that maps filename extensions to functions that map
# parameters old and new to a list that can be passed to Popen to
# convert files with that extension to png format.
converter = { }
def make_external_conversion_command(cmd):
def convert(*args):
cmdline = cmd(*args)
oldname, newname = args
pipe = subprocess.Popen(cmdline, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = pipe.communicate()
errcode = pipe.wait()
if not os.path.exists(newname) or errcode:
msg = "Conversion command failed:\n%s\n" % ' '.join(cmdline)
if stdout:
msg += "Standard output:\n%s\n" % stdout
if stderr:
msg += "Standard error:\n%s\n" % stderr
raise IOError, msg
return convert
if matplotlib.checkdep_ghostscript() is not None:
# FIXME: make checkdep_ghostscript return the command
if sys.platform == 'win32':
gs = 'gswin32c'
else:
gs = 'gs'
cmd = lambda old, new: \
[gs, '-q', '-sDEVICE=png16m', '-dNOPAUSE', '-dBATCH',
'-sOutputFile=' + new, old]
converter['pdf'] = make_external_conversion_command(cmd)
converter['eps'] = make_external_conversion_command(cmd)
if matplotlib.checkdep_inkscape() is not None:
cmd = lambda old, new: \
['inkscape', '-z', old, '--export-png', new]
converter['svg'] = make_external_conversion_command(cmd)
def comparable_formats():
'''Returns the list of file formats that compare_images can compare
on this system.'''
return ['png'] + converter.keys()
def convert(filename):
'''
Convert the named file into a png file.
Returns the name of the created file.
'''
base, extension = filename.rsplit('.', 1)
if extension not in converter:
raise ImageComparisonFailure, "Don't know how to convert %s files to png" % extension
newname = base + '_' + extension + '.png'
if not os.path.exists(filename):
raise IOError, "'%s' does not exist" % filename
# Only convert the file if the destination doesn't already exist or
# is out of date.
if (not os.path.exists(newname) or
os.stat(newname).st_mtime < os.stat(filename).st_mtime):
converter[extension](filename, newname)
return newname
verifiers = { }
def verify(filename):
"""
Verify the file through some sort of verification tool.
"""
if not os.path.exists(filename):
raise IOError, "'%s' does not exist" % filename
base, extension = filename.rsplit('.', 1)
verifier = verifiers.get(extension, None)
if verifier is not None:
cmd = verifier(filename)
pipe = subprocess.Popen(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
stdout, stderr = pipe.communicate()
errcode = pipe.wait()
if errcode != 0:
msg = "File verification command failed:\n%s\n" % ' '.join(cmd)
if stdout:
msg += "Standard output:\n%s\n" % stdout
if stderr:
msg += "Standard error:\n%s\n" % stderr
raise IOError, msg
# Turning this off, because it seems to cause multiprocessing issues
if matplotlib.checkdep_xmllint() and False:
verifiers['svg'] = lambda filename: [
'xmllint', '--valid', '--nowarning', '--noout', filename]
def crop_to_same(actual_path, actual_image, expected_path, expected_image):
# clip the images to the same size -- this is useful only when
# comparing eps to pdf
if actual_path[-7:-4] == 'eps' and expected_path[-7:-4] == 'pdf':
aw, ah = actual_image.size
ew, eh = expected_image.size
actual_image = actual_image.crop((aw/2-ew/2, ah/2-eh/2, aw/2+ew/2, ah/2+eh/2))
return actual_image, expected_image
def compare_images( expected, actual, tol, in_decorator=False ):
'''Compare two image files - not the greatest, but fast and good enough.
= EXAMPLE
# img1 = "./baseline/plot.png"
# img2 = "./output/plot.png"
#
# compare_images( img1, img2, 0.001 ):
= INPUT VARIABLES
- expected The filename of the expected image.
- actual The filename of the actual image.
- tol The tolerance (a unitless float). This is used to
determine the 'fuzziness' to use when comparing images.
- in_decorator If called from image_comparison decorator, this should be
True. (default=False)
'''
try:
from PIL import Image, ImageOps, ImageFilter
except ImportError, e:
msg = "Image Comparison requires the Python Imaging Library to " \
"be installed. To run tests without using PIL, then use " \
"the '--without-tag=PIL' command-line option.\n" \
"Importing PIL failed with the following error:\n%s" % e
if in_decorator:
raise NotImplementedError, e
else:
return msg
verify(actual)
# Convert the image to png
extension = expected.split('.')[-1]
if extension != 'png':
actual = convert(actual)
expected = convert(expected)
# open the image files and remove the alpha channel (if it exists)
expectedImage = Image.open( expected ).convert("RGB")
actualImage = Image.open( actual ).convert("RGB")
actualImage, expectedImage = crop_to_same(actual, actualImage, expected, expectedImage)
# normalize the images
expectedImage = ImageOps.autocontrast( expectedImage, 2 )
actualImage = ImageOps.autocontrast( actualImage, 2 )
# compare the resulting image histogram functions
h1 = expectedImage.histogram()
h2 = actualImage.histogram()
rms = math.sqrt( reduce(operator.add, map(lambda a,b: (a-b)**2, h1, h2)) / len(h1) )
diff_image = os.path.join(os.path.dirname(actual),
'failed-diff-'+os.path.basename(actual))
if ( (rms / 10000.0) <= tol ):
if os.path.exists(diff_image):
os.unlink(diff_image)
return None
save_diff_image( expected, actual, diff_image )
if in_decorator:
results = dict(
rms = rms,
expected = str(expected),
actual = str(actual),
diff = str(diff_image),
)
return results
else:
# old-style call from mplTest directory
msg = " Error: Image files did not match.\n" \
" RMS Value: " + str( rms / 10000.0 ) + "\n" \
" Expected:\n " + str( expected ) + "\n" \
" Actual:\n " + str( actual ) + "\n" \
" Difference:\n " + str( diff_image ) + "\n" \
" Tolerance: " + str( tol ) + "\n"
return msg
def save_diff_image( expected, actual, output ):
from PIL import Image
expectedImage = Image.open( expected ).convert("RGB")
actualImage = Image.open( actual ).convert("RGB")
actualImage, expectedImage = crop_to_same(actual, actualImage, expected, expectedImage)
expectedImage = np.array(expectedImage).astype(np.float)
actualImage = np.array(actualImage).astype(np.float)
assert expectedImage.ndim==actualImage.ndim
assert expectedImage.shape==actualImage.shape
absDiffImage = abs(expectedImage-actualImage)
# expand differences in luminance domain
absDiffImage *= 10
save_image_np = np.clip(absDiffImage,0,255).astype(np.uint8)
save_image = Image.fromarray(save_image_np)
save_image.save(output)
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