Coverage for difference/tests/test_din99.py: 100%

1"""Define the unit tests for the :mod:`colour.difference.din99` module."""

2

3 from __future__ import annotations

4

5 from itertools import product

6

7 import numpy as np

8

9 from colour.constants import TOLERANCE_ABSOLUTE_TESTS

10 from colour.difference import delta_E_DIN99

11 from colour.utilities import domain_range_scale, ignore_numpy_errors

12

13 __author__ = "Colour Developers"

14 __copyright__ = "Copyright 2013 Colour Developers"

15 __license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"

16 __maintainer__ = "Colour Developers"

17 __email__ = "colour-developers@colour-science.org"

18 __status__ = "Production"

19

20 __all__ = [

21 "TestDelta_E_DIN99",

22]

23

24

25 class TestDelta_E_DIN99:

26 """

27 Define :func:`colour.difference.din99.delta_E_DIN99` definition unit

28 tests methods.

29 """

30

31 def test_delta_E_DIN99(self) -> None:

32 """Test :func:`colour.difference.din99.delta_E_DIN99` definition."""

33

34 np.testing.assert_allclose(

35 delta_E_DIN99(

36 np.array([60.25740000, -34.00990000, 36.26770000]),

37 np.array([60.46260000, -34.17510000, 39.43870000]),

38 ),

39 1.177216620111552,

40 atol=TOLERANCE_ABSOLUTE_TESTS,

41 )

42

43 np.testing.assert_allclose(

44 delta_E_DIN99(

45 np.array([63.01090000, -31.09610000, -5.86630000]),

46 np.array([62.81870000, -29.79460000, -4.08640000]),

47 ),

48 0.987529977993114,

49 atol=TOLERANCE_ABSOLUTE_TESTS,

50 )

51

52 np.testing.assert_allclose(

53 delta_E_DIN99(

54 np.array([35.08310000, -44.11640000, 3.79330000]),

55 np.array([35.02320000, -40.07160000, 1.59010000]),

56 ),

57 1.535894757971742,

58 atol=TOLERANCE_ABSOLUTE_TESTS,

59 )

60

61 np.testing.assert_allclose(

62 delta_E_DIN99(

63 np.array([60.25740000, -34.00990000, 36.26770000]),

64 np.array([60.46260000, -34.17510000, 39.43870000]),

65 textiles=True,

66 ),

67 1.215652775586509,

68 atol=TOLERANCE_ABSOLUTE_TESTS,

69 )

70

71 np.testing.assert_allclose(

72 delta_E_DIN99(

73 np.array([63.01090000, -31.09610000, -5.86630000]),

74 np.array([62.81870000, -29.79460000, -4.08640000]),

75 textiles=True,

76 ),

77 1.025997138865984,

78 atol=TOLERANCE_ABSOLUTE_TESTS,

79 )

80

81 np.testing.assert_allclose(

82 delta_E_DIN99(

83 np.array([35.08310000, -44.11640000, 3.79330000]),

84 np.array([35.02320000, -40.07160000, 1.59010000]),

85 textiles=True,

86 ),

87 1.539922810033725,

88 atol=TOLERANCE_ABSOLUTE_TESTS,

89 )

90

91 def test_n_dimensional_delta_E_DIN99(self) -> None:

92 """

93 Test :func:`colour.difference.din99.delta_E_DIN99` definition

94 n-dimensional arrays support.

95 """

96

97 Lab_1 = np.array([60.25740000, -34.00990000, 36.26770000])

98 Lab_2 = np.array([60.46260000, -34.17510000, 39.43870000])

99 delta_E = delta_E_DIN99(Lab_1, Lab_2)

100

101 Lab_1 = np.tile(Lab_1, (6, 1))

102 Lab_2 = np.tile(Lab_2, (6, 1))

103 delta_E = np.tile(delta_E, 6)

104 np.testing.assert_allclose(

105 delta_E_DIN99(Lab_1, Lab_2), delta_E, atol=TOLERANCE_ABSOLUTE_TESTS

106 )

107

108 Lab_1 = np.reshape(Lab_1, (2, 3, 3))

109 Lab_2 = np.reshape(Lab_2, (2, 3, 3))

110 delta_E = np.reshape(delta_E, (2, 3))

111 np.testing.assert_allclose(

112 delta_E_DIN99(Lab_1, Lab_2), delta_E, atol=TOLERANCE_ABSOLUTE_TESTS

113 )

114

115 def test_domain_range_scale_delta_E_DIN99(self) -> None:

116 """

117 Test :func:`colour.difference.din99.delta_E_DIN99` definition

118 domain and range scale support.

119 """

120

121 Lab_1 = np.array([60.25740000, -34.00990000, 36.26770000])

122 Lab_2 = np.array([60.46260000, -34.17510000, 39.43870000])

123 delta_E = delta_E_DIN99(Lab_1, Lab_2)

124

125 d_r = (("reference", 1), ("1", 0.01), ("100", 1))

126 for scale, factor in d_r:

127 with domain_range_scale(scale):

128 np.testing.assert_allclose(

129 delta_E_DIN99(Lab_1 * factor, Lab_2 * factor),

130 delta_E,

131 atol=TOLERANCE_ABSOLUTE_TESTS,

132 )

133

134 @ignore_numpy_errors

135 def test_nan_delta_E_DIN99(self) -> None:

136 """

137 Test :func:`colour.difference.din99.delta_E_DIN99` definition nan

138 support.

139 """

140

141 cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]

142 cases = np.array(list(set(product(cases, repeat=3))))

143 delta_E_DIN99(cases, cases)