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add tests. cmc stops naning

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This commit is contained in:
Matt Terry
2013-07-22 15:31:27 -07:00
parent f9ca27a979
commit 28f58a2c50
5 changed files with 161 additions and 76 deletions
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skimage/color/__init__.py
+3
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@@ -96,5 +96,8 @@ __all__ = ['convert_colorspace',
'is_gray',
'color_dict',
'label2rgb',
'deltaE_cie76',
'deltaE_ciede94',
'deltaE_ciede2000',
'deltaE_cmc',
]
skimage/color/delta_e.py
+12 -15
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@@ -112,10 +112,8 @@ def deltaE_ciede94(lab1, lab2, kH=1, kC=1, kL=1, k1=0.045, k2=0.015):
dl = l1 - l2
c1 = np.sqrt(a1**2 + b1**2)
c2 = np.sqrt(a2**2 + b2**2)
da = a1 - a2
db = b1 - b2
dc = c1 - c2
dh_ab = np.sqrt(da**2 + db**2 + dc**2)
dh_ab = np.sqrt(deltaE_cie76(lab1, lab2)**2 - dl**2 - dc**2)
SL = 1
SC = 1 + k1*c1
@@ -186,11 +184,11 @@ def deltaE_ciede2000(lab1, lab2, kL=1, kC=1, kH=1):
cc = c1_prime * c2_prime
mask1 = cc == 0.
mask2 = (-mask1) * (dh_prime > np.pi)
mask3 = (-mask1) * (dh_prime < -np.pi)
dh_prime[mask1] = 0.
dh_prime[mask2] += 2*np.pi
dh_prime[mask3] -= 2*np.pi
mask2 = np.logical_and(-mask1, dh_prime > np.pi)
mask3 = np.logical_and(-mask1, dh_prime < -np.pi)
dh_prime = np.where(mask1, 0., dh_prime)
dh_prime += np.where(mask2, 2*np.pi, 0)
dh_prime -= np.where(mask3, 2*np.pi, 0)
dH_prime = 2 * np.sqrt(cc) * np.sin(dh_prime/2)
@@ -198,9 +196,10 @@ def deltaE_ciede2000(lab1, lab2, kL=1, kC=1, kH=1):
mask0 = np.logical_and(np.abs(h1_prime - h2_prime) > np.pi, cc != 0.)
mask1 = np.logical_and(mask0, Hbar_prime < 2*np.pi)
mask2 = np.logical_and(mask0, Hbar_prime >= 2*np.pi)
Hbar_prime[mask1] += 2*np.pi
Hbar_prime[mask2] -= 2*np.pi
Hbar_prime[cc == 0.] *= 2
Hbar_prime += np.where(mask1, 2*np.pi, 0)
Hbar_prime -= np.where(mask2, 2*np.pi, 0)
Hbar_prime *= np.where(cc == 0., 2, 1)
Hbar_prime *= 0.5
deg = np.pi/180.
@@ -269,10 +268,8 @@ def deltaE_cmc(lab1, lab2, kL=1, kC=1):
c1 = np.sqrt(a1**2 + b1**2)
c2 = np.sqrt(a2**2 + b2**2)
dC = c1 - c2
da = a1 - a2
db = b1 - b2
dH = np.sqrt(da**2 + db**2 - dC**2)
dl = l1 - l2
dH = np.sqrt(deltaE_cie76(lab1, lab2)**2 - dl**2 - dC**2)
dL = l1 - l2
skimage/color/tests/ciede2000_test_data.txt
+1
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@@ -1,5 +1,6 @@
# input, intermediate, and output values for CIEDE2000 dE function
# data taken from "The CIEDE2000 Color-Difference Formula: Implementation Notes, ..." http://www.ece.rochester.edu/~gsharma/ciede2000/ciede2000noteCRNA.pdf
# tab delimited data
# pair 1 L1 a1 b1 ap1 cp1 hp1 hbar1 G T SL SC SH RT dE 2 L2 a2 b2 ap2 cp2 hp2
1 1 50.0000 2.6772 -79.7751 2.6774 79.8200 271.9222 270.9611 0.0001 0.6907 1.0000 4.6578 1.8421 -1.7042 2.0425 2 50.0000 0.0000 -82.7485 0.0000 82.7485 270.0000
2 1 50.0000 3.1571 -77.2803 3.1573 77.3448 272.3395 271.1698 0.0001 0.6843 1.0000 4.6021 1.8216 -1.7070 2.8615 2 50.0000 0.0000 -82.7485 0.0000 82.7485 270.0000
skimage/color/tests/test_ciede2000.py
-61
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@@ -1,61 +0,0 @@
"""Test for correctness of color distance functions
Authors
-------
Matt Terry
:license: modified BSD
"""
from os.path import abspath, dirname, join as pjoin
import numpy as np
from numpy.testing import assert_array_almost_equal
from skimage.color import deltaE_ciede2000
def test_ciede2000_dE():
dtype = [('pair', int),
('1', int),
('L1', float),
('a1', float),
('b1', float),
('a1_prime', float),
('C1_prime', float),
('h1_prime', float),
('hbar_prime', float),
('G', float),
('T', float),
('SL', float),
('SC', float),
('SH', float),
('RT', float),
('dE', float),
('2', int),
('L2', float),
('a2', float),
('b2', float),
('a2_prime', float),
('C2_prime', float),
('h2_prime', float),
]
# note: ciede_test_data.txt contains several intermediate quantities
path = pjoin(dirname(abspath(__file__)), 'ciede_test_data.txt')
data = np.loadtxt(path, dtype=dtype)
N = len(data)
lab1 = np.zeros((N, 3))
lab1[:, 0] = data['L1']
lab1[:, 1] = data['a1']
lab1[:, 2] = data['b1']
lab2 = np.zeros((N, 3))
lab2[:, 0] = data['L2']
lab2[:, 1] = data['a2']
lab2[:, 2] = data['b2']
dE2 = deltaE_ciede2000(lab1, lab2)
assert_array_almost_equal(dE2, data['dE'])
skimage/color/tests/test_dE.py
+145
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@@ -0,0 +1,145 @@
"""Test for correctness of color distance functions
Authors
-------
Matt Terry
:license: modified BSD
"""
from os.path import abspath, dirname, join as pjoin
import numpy as np
from numpy.testing import assert_array_almost_equal
from skimage.color import (deltaE_cie76,
deltaE_ciede94,
deltaE_ciede2000,
deltaE_cmc)
def test_ciede2000_dE():
data = load_ciede2000_data()
N = len(data)
lab1 = np.zeros((N, 3))
lab1[:, 0] = data['L1']
lab1[:, 1] = data['a1']
lab1[:, 2] = data['b1']
lab2 = np.zeros((N, 3))
lab2[:, 0] = data['L2']
lab2[:, 1] = data['a2']
lab2[:, 2] = data['b2']
dE2 = deltaE_ciede2000(lab1, lab2)
assert_array_almost_equal(dE2, data['dE'])
def load_ciede2000_data():
dtype = [('pair', int),
('1', int),
('L1', float),
('a1', float),
('b1', float),
('a1_prime', float),
('C1_prime', float),
('h1_prime', float),
('hbar_prime', float),
('G', float),
('T', float),
('SL', float),
('SC', float),
('SH', float),
('RT', float),
('dE', float),
('2', int),
('L2', float),
('a2', float),
('b2', float),
('a2_prime', float),
('C2_prime', float),
('h2_prime', float),
]
# note: ciede_test_data.txt contains several intermediate quantities
path = pjoin(dirname(abspath(__file__)), 'ciede_test_data.txt')
return np.loadtxt(path, dtype=dtype)
def test_cie76():
data = load_ciede2000_data()
N = len(data)
lab1 = np.zeros((N, 3))
lab1[:, 0] = data['L1']
lab1[:, 1] = data['a1']
lab1[:, 2] = data['b1']
lab2 = np.zeros((N, 3))
lab2[:, 0] = data['L2']
lab2[:, 1] = data['a2']
lab2[:, 2] = data['b2']
dE2 = deltaE_cie76(lab1, lab2)
oracle = np.array([
4.00106328, 6.31415011, 9.1776999, 2.06270077, 2.36957073,
2.91529271, 2.23606798, 2.23606798, 4.98000036, 4.9800004,
4.98000044, 4.98000049, 4.98000036, 4.9800004, 4.98000044,
3.53553391, 36.86800781, 31.91002977, 30.25309901, 27.40894015,
0.89242934, 0.7972, 0.8583065, 0.82982507, 3.1819238,
2.21334297, 1.53890382, 4.60630929, 6.58467989, 3.88641412,
1.50514845, 2.3237848, 0.94413208, 1.31910843
])
assert_array_almost_equal(dE2, oracle)
def test_ciede94():
data = load_ciede2000_data()
N = len(data)
lab1 = np.zeros((N, 3))
lab1[:, 0] = data['L1']
lab1[:, 1] = data['a1']
lab1[:, 2] = data['b1']
lab2 = np.zeros((N, 3))
lab2[:, 0] = data['L2']
lab2[:, 1] = data['a2']
lab2[:, 2] = data['b2']
dE2 = deltaE_ciede94(lab1, lab2)
oracle = np.array([
1.39503887, 1.93410055, 2.45433566, 0.68449187, 0.6695627,
0.69194527, 2.23606798, 2.03163832, 4.80069441, 4.80069445,
4.80069449, 4.80069453, 4.80069441, 4.80069445, 4.80069449,
3.40774352, 34.6891632, 29.44137328, 27.91408781, 24.93766082,
0.82213163, 0.71658427, 0.8048753, 0.75284394, 1.39099471,
1.24808929, 1.29795787, 1.82045088, 2.55613309, 1.42491303,
1.41945261, 2.3225685, 0.93853308, 1.30654464
])
assert_array_almost_equal(dE2, oracle)
def test_cmc():
data = load_ciede2000_data()
N = len(data)
lab1 = np.zeros((N, 3))
lab1[:, 0] = data['L1']
lab1[:, 1] = data['a1']
lab1[:, 2] = data['b1']
lab2 = np.zeros((N, 3))
lab2[:, 0] = data['L2']
lab2[:, 1] = data['a2']
lab2[:, 2] = data['b2']
dE2 = deltaE_cmc(lab1, lab2)
oracle = np.array([
1.73873611, 2.49660844, 3.30494501, 0.85735576, 0.88332927,
0.97822692, 3.50480874, 2.87930032, 6.5783807, 6.57838075,
6.5783808, 6.57838086, 6.67492321, 6.67492326, 6.67492331,
4.66852997, 42.10875485, 39.45889064, 38.36005919, 33.93663807,
1.14400168, 1.00600419, 1.11302547, 1.05335328, 1.42822951,
1.2548143, 1.76838061, 2.02583367, 3.08695508, 1.74893533,
1.90095165, 1.70258148, 1.80317207, 2.44934417
])
assert_array_almost_equal(dE2, oracle)