def test_n_dimensional_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
n-dimensional arrays support.
"""
Lab_1 = np.array([100.00000000, 21.57210357, 272.22819350])
Lab_2 = np.array([100.00000000, 426.67945353, 72.39590835])
delta_E = 94.035649026659485
np.testing.assert_almost_equal(delta_E_CIE2000(Lab_1, Lab_2),
delta_E,
decimal=7)
Lab_1 = np.tile(Lab_1, (6, 1))
Lab_2 = np.tile(Lab_2, (6, 1))
delta_E = np.tile(delta_E, 6)
np.testing.assert_almost_equal(delta_E_CIE2000(Lab_1, Lab_2),
delta_E,
decimal=7)
Lab_1 = np.reshape(Lab_1, (2, 3, 3))
Lab_2 = np.reshape(Lab_2, (2, 3, 3))
delta_E = np.reshape(delta_E, (2, 3))
np.testing.assert_almost_equal(delta_E_CIE2000(Lab_1, Lab_2),
delta_E,
decimal=7)
def test_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition.
"""
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 426.67945353, 72.39590835])),
94.0356490267,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 74.05216981, 276.45318193])),
14.8790641937,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 8.32281957, -73.58297716])),
68.2309487895,
places=7)
def test_n_dimensional_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
n-dimensional arrays support.
"""
Lab1 = np.array([100.00000000, 21.57210357, 272.22819350])
Lab2 = np.array([100.00000000, 426.67945353, 72.39590835])
delta_E = 94.035649026659485
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab1, Lab2),
delta_E,
decimal=7)
Lab1 = np.tile(Lab1, (6, 1))
Lab2 = np.tile(Lab2, (6, 1))
delta_E = np.tile(delta_E, 6)
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab1, Lab2),
delta_E,
decimal=7)
Lab1 = np.reshape(Lab1, (2, 3, 3))
Lab2 = np.reshape(Lab2, (2, 3, 3))
delta_E = np.reshape(delta_E, (2, 3))
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab1, Lab2),
delta_E,
decimal=7)
def test_nan_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition nan
support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=3))
for case in cases:
Lab_1 = np.array(case)
Lab_2 = np.array(case)
delta_E_CIE2000(Lab_1, Lab_2)
def test_nan_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition nan
support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=3))
for case in cases:
Lab1 = np.array(case)
Lab2 = np.array(case)
delta_E_CIE2000(Lab1, Lab2)
def test_domain_range_scale_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
domain and range scale support.
"""
Lab_1 = np.array([100.00000000, 21.57210357, 272.22819350])
Lab_2 = np.array([100.00000000, 426.67945353, 72.39590835])
delta_E = delta_E_CIE2000(Lab_1, Lab_2)
d_r = (('reference', 1), (1, 0.01), (100, 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab_1 * factor, Lab_2 * factor),
delta_E,
decimal=7)
def test_domain_range_scale_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
domain and range scale support.
"""
Lab_1 = np.array([100.00000000, 21.57210357, 272.22819350])
Lab_2 = np.array([100.00000000, 426.67945353, 72.39590835])
delta_E = delta_E_CIE2000(Lab_1, Lab_2)
d_r = (('reference', 1), (1, 0.01), (100, 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab_1 * factor, Lab_2 * factor),
delta_E,
decimal=7)
def test_de2000() -> None:
rgb = get_random_01x01x01_with_corners(1000)
xyz = sRGB_to_XYZ(rgb)
lab = XYZ_to_Lab(xyz)
de = delta_E_CIE2000(lab[:-1], lab[1:])
my_de = dE_2000_jit(lab[:-1], lab[1:])
assert np.allclose(de, my_de), np.hstack(
[de.reshape(-1, 1), my_de.reshape(-1, 1)])
def test_delta_E_CIE2000(self):
"""Test :func:`colour.difference.delta_e.delta_E_CIE2000` definition."""
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 426.67945353, 72.39590835]),
),
94.03564903,
places=7,
)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 74.05216981, 276.45318193]),
),
14.87906419,
places=7,
)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 8.32281957, -73.58297716]),
),
68.23094879,
places=7,
)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 426.67945353, 72.39590835]),
textiles=True,
),
95.79205352,
places=7,
)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 74.05216981, 276.45318193]),
textiles=True,
),
23.55420943,
places=7,
)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 8.32281957, -73.58297716]),
textiles=True,
),
70.63198003,
places=7,
)
def test_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition.
"""
self.assertAlmostEqual(delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 426.67945353, 72.39590835])),
94.0356490267,
places=7)
self.assertAlmostEqual(delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 74.05216981, 276.45318193])),
14.8790641937,
places=7)
self.assertAlmostEqual(delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 8.32281957, -73.58297716])),
68.2309487895,
places=7)
def test_delta_E_CIE2000(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition.
"""
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 426.67945353, 72.39590835])),
94.03564903,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 74.05216981, 276.45318193])),
14.87906419,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([100.00000000, 8.32281957, -73.58297716])),
68.23094879,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 426.67945353, 72.39590835]),
textiles=True),
95.79205352,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 74.05216981, 276.45318193]),
textiles=True),
23.55420943,
places=7)
self.assertAlmostEqual(
delta_E_CIE2000(
np.array([100.00000000, 21.57210357, 272.22819350]),
np.array([50.00000000, 8.32281957, -73.58297716]),
textiles=True),
70.63198003,
places=7)
def test_delta_E_CIE2000_Sharma2004(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
using Sharma (2004) dataset.
References
----------
- :cite:`Sharma2005b`
"""
Lab_1 = np.array([
[50.0000, 2.6772, -79.7751],
[50.0000, 3.1571, -77.2803],
[50.0000, 2.8361, -74.0200],
[50.0000, -1.3802, -84.2814],
[50.0000, -1.1848, -84.8006],
[50.0000, -0.9009, -85.5211],
[50.0000, 0.0000, 0.0000],
[50.0000, -1.0000, 2.0000],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[60.2574, -34.0099, 36.2677],
[63.0109, -31.0961, -5.8663],
[61.2901, 3.7196, -5.3901],
[35.0831, -44.1164, 3.7933],
[22.7233, 20.0904, -46.6940],
[36.4612, 47.8580, 18.3852],
[90.8027, -2.0831, 1.4410],
[90.9257, -0.5406, -0.9208],
[6.7747, -0.2908, -2.4247],
[2.0776, 0.0795, -1.1350],
])
Lab_2 = np.array([
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, -1.0000, 2.0000],
[50.0000, 0.0000, 0.0000],
[50.0000, -2.4900, 0.0009],
[50.0000, -2.4900, 0.0010],
[50.0000, -2.4900, 0.0011],
[50.0000, -2.4900, 0.0012],
[50.0000, 0.0009, -2.4900],
[50.0000, 0.0010, -2.4900],
[50.0000, 0.0011, -2.4900],
[50.0000, 0.0000, -2.5000],
[73.0000, 25.0000, -18.0000],
[61.0000, -5.0000, 29.0000],
[56.0000, -27.0000, -3.0000],
[58.0000, 24.0000, 15.0000],
[50.0000, 3.1736, 0.5854],
[50.0000, 3.2972, 0.0000],
[50.0000, 1.8634, 0.5757],
[50.0000, 3.2592, 0.3350],
[60.4626, -34.1751, 39.4387],
[62.8187, -29.7946, -4.0864],
[61.4292, 2.2480, -4.9620],
[35.0232, -40.0716, 1.5901],
[23.0331, 14.9730, -42.5619],
[36.2715, 50.5065, 21.2231],
[91.1528, -1.6435, 0.0447],
[88.6381, -0.8985, -0.7239],
[5.8714, -0.0985, -2.2286],
[0.9033, -0.0636, -0.5514],
])
d_E = np.array([
2.0425, 2.8615, 3.4412, 1.0000, 1.0000, 1.0000, 2.3669, 2.3669,
7.1792, 7.1792, 7.2195, 7.2195, 4.8045, 4.8045, 4.7461, 4.3065,
27.1492, 22.8977, 31.9030, 19.4535, 1.0000, 1.0000, 1.0000, 1.0000,
1.2644, 1.2630, 1.8731, 1.8645, 2.0373, 1.4146, 1.4441, 1.5381,
0.6377, 0.9082
])
np.testing.assert_almost_equal(delta_E_CIE2000(Lab_1, Lab_2),
d_E,
decimal=4)
def test_delta_E_CIE2000_Sharma2004(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
using Sharma (2004) dataset.
References
----------
.. [1] Sharma, G., Wu, W., & Dalal, E. N. (2005). The CIEDE2000
color‐difference formula: Implementation notes, supplementary
test data, and mathematical observations. Color Research &
Application, 30(1), 21–30. doi:10.1002/col.20070
"""
Lab1 = np.array(
[[50.0000, 2.6772, -79.7751],
[50.0000, 3.1571, -77.2803],
[50.0000, 2.8361, -74.0200],
[50.0000, -1.3802, -84.2814],
[50.0000, -1.1848, -84.8006],
[50.0000, -0.9009, -85.5211],
[50.0000, 0.0000, 0.0000],
[50.0000, -1.0000, 2.0000],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[60.2574, -34.0099, 36.2677],
[63.0109, -31.0961, -5.8663],
[61.2901, 3.7196, -5.3901],
[35.0831, -44.1164, 3.7933],
[22.7233, 20.0904, -46.6940],
[36.4612, 47.8580, 18.3852],
[90.8027, -2.0831, 1.4410],
[90.9257, -0.5406, -0.9208],
[6.7747, -0.2908, -2.4247],
[2.0776, 0.0795, -1.1350]])
Lab2 = np.array(
[[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, -1.0000, 2.0000],
[50.0000, 0.0000, 0.0000],
[50.0000, -2.4900, 0.0009],
[50.0000, -2.4900, 0.0010],
[50.0000, -2.4900, 0.0011],
[50.0000, -2.4900, 0.0012],
[50.0000, 0.0009, -2.4900],
[50.0000, 0.0010, -2.4900],
[50.0000, 0.0011, -2.4900],
[50.0000, 0.0000, -2.5000],
[73.0000, 25.0000, -18.0000],
[61.0000, -5.0000, 29.0000],
[56.0000, -27.0000, -3.0000],
[58.0000, 24.0000, 15.0000],
[50.0000, 3.1736, 0.5854],
[50.0000, 3.2972, 0.0000],
[50.0000, 1.8634, 0.5757],
[50.0000, 3.2592, 0.3350],
[60.4626, -34.1751, 39.4387],
[62.8187, -29.7946, -4.0864],
[61.4292, 2.2480, -4.9620],
[35.0232, -40.0716, 1.5901],
[23.0331, 14.9730, -42.5619],
[36.2715, 50.5065, 21.2231],
[91.1528, -1.6435, 0.0447],
[88.6381, -0.8985, -0.7239],
[5.8714, -0.0985, -2.2286],
[0.9033, -0.0636, -0.5514]])
d_E = np.array(
[2.0425,
2.8615,
3.4412,
1.0000,
1.0000,
1.0000,
2.3669,
2.3669,
7.1792,
7.1792,
7.2195,
7.2195,
4.8045,
4.8045,
4.7461,
4.3065,
27.1492,
22.8977,
31.9030,
19.4535,
1.0000,
1.0000,
1.0000,
1.0000,
1.2644,
1.2630,
1.8731,
1.8645,
2.0373,
1.4146,
1.4441,
1.5381,
0.6377,
0.9082])
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab1, Lab2),
d_E,
decimal=4)
def test_delta_E_CIE2000_Sharma2004(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
using Sharma (2004) dataset.
References
----------
:cite:`Sharma2005b`
"""
Lab_1 = np.array([
[50.0000, 2.6772, -79.7751],
[50.0000, 3.1571, -77.2803],
[50.0000, 2.8361, -74.0200],
[50.0000, -1.3802, -84.2814],
[50.0000, -1.1848, -84.8006],
[50.0000, -0.9009, -85.5211],
[50.0000, 0.0000, 0.0000],
[50.0000, -1.0000, 2.0000],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, 2.4900, -0.0010],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000],
[60.2574, -34.0099, 36.2677],
[63.0109, -31.0961, -5.8663],
[61.2901, 3.7196, -5.3901],
[35.0831, -44.1164, 3.7933],
[22.7233, 20.0904, -46.6940],
[36.4612, 47.8580, 18.3852],
[90.8027, -2.0831, 1.4410],
[90.9257, -0.5406, -0.9208],
[6.7747, -0.2908, -2.4247],
[2.0776, 0.0795, -1.1350],
])
Lab_2 = np.array([
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, -1.0000, 2.0000],
[50.0000, 0.0000, 0.0000],
[50.0000, -2.4900, 0.0009],
[50.0000, -2.4900, 0.0010],
[50.0000, -2.4900, 0.0011],
[50.0000, -2.4900, 0.0012],
[50.0000, 0.0009, -2.4900],
[50.0000, 0.0010, -2.4900],
[50.0000, 0.0011, -2.4900],
[50.0000, 0.0000, -2.5000],
[73.0000, 25.0000, -18.0000],
[61.0000, -5.0000, 29.0000],
[56.0000, -27.0000, -3.0000],
[58.0000, 24.0000, 15.0000],
[50.0000, 3.1736, 0.5854],
[50.0000, 3.2972, 0.0000],
[50.0000, 1.8634, 0.5757],
[50.0000, 3.2592, 0.3350],
[60.4626, -34.1751, 39.4387],
[62.8187, -29.7946, -4.0864],
[61.4292, 2.2480, -4.9620],
[35.0232, -40.0716, 1.5901],
[23.0331, 14.9730, -42.5619],
[36.2715, 50.5065, 21.2231],
[91.1528, -1.6435, 0.0447],
[88.6381, -0.8985, -0.7239],
[5.8714, -0.0985, -2.2286],
[0.9033, -0.0636, -0.5514],
])
d_E = np.array([
2.0425, 2.8615, 3.4412, 1.0000, 1.0000, 1.0000, 2.3669, 2.3669,
7.1792, 7.1792, 7.2195, 7.2195, 4.8045, 4.8045, 4.7461, 4.3065,
27.1492, 22.8977, 31.9030, 19.4535, 1.0000, 1.0000, 1.0000, 1.0000,
1.2644, 1.2630, 1.8731, 1.8645, 2.0373, 1.4146, 1.4441, 1.5381,
0.6377, 0.9082
])
np.testing.assert_almost_equal(
delta_E_CIE2000(Lab_1, Lab_2), d_E, decimal=4)
def test_delta_E_CIE2000_Sharma2004(self):
"""
Tests :func:`colour.difference.delta_e.delta_E_CIE2000` definition
using Sharma (2004) dataset.
References
----------
.. [1] Sharma, G., Wu, W., & Dalal, E. N. (2005). The CIEDE2000
color‐difference formula: Implementation notes, supplementary
test data, and mathematical observations. Color Research &
Application, 30(1), 21–30. doi:10.1002/col.20070
"""
Lab1 = np.array([[50.0000, 2.6772, -79.7751],
[50.0000, 3.1571, -77.2803],
[50.0000, 2.8361, -74.0200],
[50.0000, -1.3802, -84.2814],
[50.0000, -1.1848,
-84.8006], [50.0000, -0.9009, -85.5211],
[50.0000, 0.0000, 0.0000], [50.0000, -1.0000, 2.0000],
[50.0000, 2.4900,
-0.0010], [50.0000, 2.4900, -0.0010],
[50.0000, 2.4900,
-0.0010], [50.0000, 2.4900, -0.0010],
[50.0000, -0.0010,
2.4900], [50.0000, -0.0010, 2.4900],
[50.0000, -0.0010, 2.4900], [50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000], [50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000], [50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000], [50.0000, 2.5000, 0.0000],
[50.0000, 2.5000, 0.0000], [50.0000, 2.5000, 0.0000],
[60.2574, -34.0099, 36.2677],
[63.0109, -31.0961, -5.8663],
[61.2901, 3.7196, -5.3901],
[35.0831, -44.1164, 3.7933],
[22.7233, 20.0904, -46.6940],
[36.4612, 47.8580,
18.3852], [90.8027, -2.0831, 1.4410],
[90.9257, -0.5406,
-0.9208], [6.7747, -0.2908, -2.4247],
[2.0776, 0.0795, -1.1350]])
Lab2 = np.array([[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000, -82.7485],
[50.0000, 0.0000,
-82.7485], [50.0000, -1.0000, 2.0000],
[50.0000, 0.0000, 0.0000], [50.0000, -2.4900, 0.0009],
[50.0000, -2.4900,
0.0010], [50.0000, -2.4900, 0.0011],
[50.0000, -2.4900,
0.0012], [50.0000, 0.0009, -2.4900],
[50.0000, 0.0010,
-2.4900], [50.0000, 0.0011, -2.4900],
[50.0000, 0.0000, -2.5000],
[73.0000, 25.0000, -18.0000],
[61.0000, -5.0000, 29.0000],
[56.0000, -27.0000,
-3.0000], [58.0000, 24.0000, 15.0000],
[50.0000, 3.1736, 0.5854], [50.0000, 3.2972, 0.0000],
[50.0000, 1.8634, 0.5757], [50.0000, 3.2592, 0.3350],
[60.4626, -34.1751, 39.4387],
[62.8187, -29.7946, -4.0864],
[61.4292, 2.2480, -4.9620],
[35.0232, -40.0716, 1.5901],
[23.0331, 14.9730, -42.5619],
[36.2715, 50.5065,
21.2231], [91.1528, -1.6435, 0.0447],
[88.6381, -0.8985,
-0.7239], [5.8714, -0.0985, -2.2286],
[0.9033, -0.0636, -0.5514]])
d_E = np.array([
2.0425, 2.8615, 3.4412, 1.0000, 1.0000, 1.0000, 2.3669, 2.3669,
7.1792, 7.1792, 7.2195, 7.2195, 4.8045, 4.8045, 4.7461, 4.3065,
27.1492, 22.8977, 31.9030, 19.4535, 1.0000, 1.0000, 1.0000, 1.0000,
1.2644, 1.2630, 1.8731, 1.8645, 2.0373, 1.4146, 1.4441, 1.5381,
0.6377, 0.9082
])
np.testing.assert_almost_equal(delta_E_CIE2000(Lab1, Lab2),
d_E,
decimal=4)
def closest_pixel(pixel, temp, colors):
"""Helper function, finds closest pixel color based on palette"""
if pixel in temp:
return temp[pixel]
temp[pixel] = min(colors, key=lambda func: delta_E_CIE2000(pixel, func))
return temp[pixel]
