def test_cdf_match_lut(self):
# Intensity values at 3,4,5,6
test_cdf = np.zeros((8))
test_cdf[3] = 0.25
test_cdf[4] = .5
test_cdf[5] = 0.75
test_cdf[6:] = 1.0
# Intensity values at 1,2,3,4 (test minus 2)
match_cdf = np.zeros((8))
match_cdf[1] = 0.25
match_cdf[2] = .5
match_cdf[3] = 0.75
match_cdf[4:] = 1
logging.debug("match cdf: {}".format(match_cdf))
# Test all values are mapped down by 2
expected_lut = np.array([1, 1, 1, 1, 2, 3, 4, 4])
lut = hm.cdf_match_lut(test_cdf, match_cdf)
np.testing.assert_array_equal(lut, expected_lut)
# Intensity values all at 4
match_cdf = np.zeros((8))
match_cdf[4:] = 1
# Test all values are mapped to 4
expected_lut = np.array([4, 4, 4, 4, 4, 4, 4, 4])
lut = hm.cdf_match_lut(test_cdf, match_cdf)
np.testing.assert_array_equal(lut, expected_lut)
test_cdf = np.array([0, 9.99999881e-01])
match_cdf = np.array([0, 1])
self.assertRaises(hm.CDFException, hm.cdf_match_lut, test_cdf, match_cdf)
def test_cdf_match_lut(self):
# Intensity values at 3,4,5,6
test_cdf = numpy.zeros((8))
test_cdf[3] = 0.25
test_cdf[4] = .5
test_cdf[5] = 0.75
test_cdf[6:] = 1.0
# Intensity values at 1,2,3,4 (test minus 2)
match_cdf = numpy.zeros((8))
match_cdf[1] = 0.25
match_cdf[2] = .5
match_cdf[3] = 0.75
match_cdf[4:] = 1
logging.debug("match cdf: {}".format(match_cdf))
# Test all values are mapped down by 2
expected_lut = numpy.array([1, 1, 1, 1, 2, 3, 4, 4])
lut = hm.cdf_match_lut(test_cdf, match_cdf)
numpy.testing.assert_array_equal(lut, expected_lut)
# Intensity values all at 4
match_cdf = numpy.zeros((8))
match_cdf[4:] = 1
# Test all values are mapped to 4
expected_lut = numpy.array([4, 4, 4, 4, 4, 4, 4, 4])
lut = hm.cdf_match_lut(test_cdf, match_cdf)
numpy.testing.assert_array_equal(lut, expected_lut)
test_cdf = numpy.array([0, 9.99999881e-01])
match_cdf = numpy.array([0, 1])
self.assertRaises(hm.CDFException, hm.cdf_match_lut, test_cdf,
match_cdf)
def test_cdf_normalization_band(self):
for testno in (
1,
2,
):
input_bands, reference_bands, golden_lut = \
_get_test_data(testno)
colors = ('Red', 'Green', 'Blue')
for color in colors:
in_band = input_bands[color]
ref_band = reference_bands[color]
print ref_band.min()
print ref_band.max()
in_cdf = colorimage.get_cdf(in_band)
ref_cdf = colorimage.get_cdf(ref_band)
color_lut = histogram_match.cdf_match_lut(in_cdf, ref_cdf)
try:
assert numpy.array_equal(color_lut, golden_lut[color])
except AssertionError:
print "Got: {}".format(color_lut)
print "Expected: {}".format(golden_lut[color])
raise Exception("Color {} for test data {} failed" \
.format(color, testno))
def test_cdf_normalization_band(self):
for testno in (1,2,):
input_bands, reference_bands, golden_lut = \
_get_test_data(testno)
colors = ('Red', 'Green', 'Blue')
for color in colors:
in_band = input_bands[color]
ref_band = reference_bands[color]
in_cdf = colorimage.get_cdf(in_band)
ref_cdf = colorimage.get_cdf(ref_band)
color_lut = histogram_match.cdf_match_lut(in_cdf, ref_cdf)
assert np.array_equal(color_lut, golden_lut[color])
def test_cdf_normalization_band(self):
for testno in (
1,
2,
):
input_bands, reference_bands, golden_lut = \
_get_test_data(testno)
colors = ('Red', 'Green', 'Blue')
for color in colors:
in_band = input_bands[color]
ref_band = reference_bands[color]
in_cdf = colorimage.get_cdf(in_band)
ref_cdf = colorimage.get_cdf(ref_band)
color_lut = histogram_match.cdf_match_lut(in_cdf, ref_cdf)
assert np.array_equal(color_lut, golden_lut[color])
def test_cdf_normalization_band(self):
for testno in (1,2,):
input_bands, reference_bands, golden_lut = \
_get_test_data(testno)
colors = ('Red', 'Green', 'Blue')
for color in colors:
in_band = input_bands[color]
ref_band = reference_bands[color]
print ref_band.min()
print ref_band.max()
in_cdf = colorimage.get_cdf(in_band)
ref_cdf = colorimage.get_cdf(ref_band)
color_lut = histogram_match.cdf_match_lut(in_cdf, ref_cdf)
try:
assert numpy.array_equal(color_lut, golden_lut[color])
except AssertionError:
print "Got: {}".format(color_lut)
print "Expected: {}".format(golden_lut[color])
raise Exception("Color {} for test data {} failed" \
.format(color, testno))
