def test_domain_range_scale_XYZ_to_sd(self):
"""
Tests :func:`colour.recovery.XYZ_to_sd` definition domain
and range scale support.
"""
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
m = ('Jakob 2019', 'Mallett 2019', 'Meng 2015', 'Otsu 2018',
'Smits 1999')
v = [
sd_to_XYZ_integration(
XYZ_to_sd(XYZ,
method,
cmfs=self._cmfs,
illuminant=self._sd_D65), self._cmfs, self._sd_D65)
for method in m
]
d_r = (('reference', 1, 1), (1, 1, 0.01), (100, 100, 1))
for method, value in zip(m, v):
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd(XYZ * factor_a,
method,
cmfs=self._cmfs,
illuminant=self._sd_D65), self._cmfs,
self._sd_D65),
value * factor_b,
decimal=7)
def test_domain_range_scale_XYZ_to_sd(self):
"""
Tests :func:`colour.recovery.XYZ_to_sd` definition domain
and range scale support.
"""
cmfs = (STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'].
copy().align(DEFAULT_SPECTRAL_SHAPE_MENG_2015))
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
m = ('Smits 1999', 'Meng 2015')
v = [
sd_to_XYZ_integration(XYZ_to_sd(XYZ, method), cmfs) for method in m
]
d_r = (('reference', 1, 1), (1, 1, 0.01), (100, 100, 1))
for method, value in zip(m, v):
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd(XYZ * factor_a, method), cmfs),
value * factor_b,
decimal=7)