def test_n_dimensional_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition
n-dimensional arrays support.
"""
xy = np.array([0.26415, 0.37770])
xy_n = D65
P_e = 0.157118186993525
np.testing.assert_almost_equal(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
P_e,
decimal=7)
xy = np.tile(xy, (6, 1))
xy_n = np.tile(xy_n, (6, 1))
P_e = np.tile(P_e, 6)
np.testing.assert_almost_equal(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
P_e,
decimal=7)
xy = np.reshape(xy, (2, 3, 2))
xy_n = np.reshape(xy_n, (2, 3, 2))
P_e = np.reshape(P_e, (2, 3))
np.testing.assert_almost_equal(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
P_e,
decimal=7)
def test_nan_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition
nan support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=2))
for case in cases:
try:
excitation_purity(case, case, CIE_2_1931_CMFS)
except ValueError:
pass
def test_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition.
"""
xy = np.array([0.54369557, 0.32107944])
xy_n = D65
self.assertAlmostEqual(excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.622885671878446,
places=7)
xy = np.array([0.37605506, 0.24452225])
self.assertAlmostEqual(excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.438347859215887,
places=7)
def test_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition.
"""
xy = np.array([0.26415, 0.37770])
xy_n = D65
self.assertAlmostEqual(excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.157118186993525,
places=7)
xy = np.array([0.35000, 0.25000])
self.assertAlmostEqual(excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.370659424135609,
places=7)
def test_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition.
"""
xy = np.array([0.54369557, 0.32107944])
xy_n = D65
self.assertAlmostEqual(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.622885671878446,
places=7)
xy = np.array([0.37605506, 0.24452225])
self.assertAlmostEqual(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.438347859215887,
places=7)
def test_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition.
"""
xy = np.array([0.26415, 0.37770])
xy_n = D65
self.assertAlmostEqual(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.157118186993525,
places=7)
xy = np.array([0.35000, 0.25000])
self.assertAlmostEqual(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS),
0.370659424135609,
places=7)
def test_n_dimensional_excitation_purity(self):
"""
Tests :func:`colour.colorimetry.dominant.excitation_purity` definition
n-dimensional arrays support.
"""
xy = np.array([0.54369557, 0.32107944])
xy_n = D65
P_e = excitation_purity(xy, xy_n, CIE_2_1931_CMFS)
xy = np.tile(xy, (6, 1))
xy_n = np.tile(xy_n, (6, 1))
P_e = np.tile(P_e, 6)
np.testing.assert_almost_equal(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS), P_e, decimal=7)
xy = np.reshape(xy, (2, 3, 2))
xy_n = np.reshape(xy_n, (2, 3, 2))
P_e = np.reshape(P_e, (2, 3))
np.testing.assert_almost_equal(
excitation_purity(xy, xy_n, CIE_2_1931_CMFS), P_e, decimal=7)
