def test_domain_range_scale_XYZ_to_sd_Meng2015(self):
"""
Test :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015` definition
domain and range scale support.
"""
XYZ_i = np.array([0.20654008, 0.12197225, 0.05136952])
XYZ_o = sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ_i, self._cmfs, self._sd_D65),
self._cmfs,
self._sd_D65,
)
d_r = (("reference", 1, 1), ("1", 1, 0.01), ("100", 100, 1))
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_Meng2015(
XYZ_i * factor_a, self._cmfs, self._sd_D65
),
self._cmfs,
self._sd_D65,
),
XYZ_o * factor_b,
decimal=7,
)
def test_XYZ_to_sd_Meng2015(self):
"""Test :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015` definition."""
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, self._cmfs, self._sd_D65),
self._cmfs,
self._sd_D65,
)
/ 100,
XYZ,
decimal=7,
)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, self._cmfs, self._sd_E),
self._cmfs,
self._sd_E,
)
/ 100,
XYZ,
decimal=7,
)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(
XYZ,
self._cmfs,
self._sd_D65,
optimisation_kwargs={
"options": {
"ftol": 1e-10,
}
},
),
self._cmfs,
self._sd_D65,
)
/ 100,
XYZ,
decimal=7,
)
shape = SpectralShape(400, 700, 5)
# pylint: disable=E1102
cmfs = reshape_msds(self._cmfs, shape)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, cmfs, self._sd_D65), cmfs, self._sd_D65
)
/ 100,
XYZ,
decimal=7,
)
def test_XYZ_to_sd_Meng2015(self):
"""
Tests :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015`
definition.
"""
cmfs = (STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer'].
copy().trim(DEFAULT_SPECTRAL_SHAPE))
shape = SpectralShape(cmfs.shape.start, cmfs.shape.end, 5)
cmfs_c = cmfs.copy().align(shape)
XYZ = np.array([0.21781186, 0.12541048, 0.04697113])
np.testing.assert_almost_equal(
sd_to_XYZ_integration(XYZ_to_sd_Meng2015(XYZ, cmfs_c), cmfs_c) /
100,
XYZ,
decimal=7)
shape = SpectralShape(cmfs.shape.start, cmfs.shape.end, 10)
cmfs_c = cmfs.copy().align(shape)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(XYZ_to_sd_Meng2015(XYZ, cmfs_c), cmfs_c) /
100,
XYZ,
decimal=7)
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, cmfs_c, ILLUMINANTS_SDS['D65']), cmfs_c,
ILLUMINANTS_SDS['D65']) / 100,
XYZ,
decimal=7)
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(
XYZ,
cmfs_c,
optimisation_parameters={'options': {
'ftol': 1e-10,
}}), cmfs_c) / 100,
XYZ,
decimal=7)
shape = SpectralShape(400, 700, 5)
cmfs_c = cmfs.copy().align(shape)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(XYZ_to_sd_Meng2015(XYZ, cmfs_c), cmfs_c) /
100,
XYZ,
decimal=7)
def test_domain_range_scale_XYZ_to_sd_Meng2015(self):
"""
Tests :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015`
definition domain and range scale support.
"""
XYZ_i = np.array([0.21781186, 0.12541048, 0.04697113])
XYZ_o = sd_to_XYZ_integration(XYZ_to_sd_Meng2015(XYZ_i))
d_r = (('reference', 1, 1), (1, 1, 0.01), (100, 100, 1))
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_Meng2015(XYZ_i * factor_a)),
XYZ_o * factor_b,
decimal=7)
def test_XYZ_to_sd_Meng2015(self):
"""
Tests :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015`
definition.
"""
cmfs = STANDARD_OBSERVERS_CMFS['CIE 1931 2 Degree Standard Observer']
shape = SpectralShape(cmfs.shape.start, cmfs.shape.end, 5)
cmfs_c = cmfs.copy().align(shape)
XYZ = np.array([0.21781186, 0.12541048, 0.04697113])
np.testing.assert_almost_equal(
sd_to_XYZ_integration(XYZ_to_sd_Meng2015(XYZ), cmfs=cmfs_c) / 100,
XYZ,
decimal=7)
shape = SpectralShape(cmfs.shape.start, cmfs.shape.end, 10)
cmfs_c = cmfs.copy().align(shape)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, interval=10), cmfs=cmfs_c) / 100,
XYZ,
decimal=7)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(
XYZ,
interval=10,
optimisation_parameters={
'options': {
'ftol': 1e-10,
'maxiter': 2000
}
}),
cmfs=cmfs_c) / 100,
XYZ,
decimal=7)
shape = SpectralShape(400, 700, 5)
cmfs_c = cmfs.copy().align(shape)
np.testing.assert_almost_equal(
sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, cmfs=cmfs_c), cmfs=cmfs_c) / 100,
XYZ,
decimal=7)
def test_XYZ_to_sd_Meng2015(self):
"""
Tests :func:`colour.recovery.meng2015.XYZ_to_sd_Meng2015` definition.
"""
XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, self._cmfs, self._sd_D65), self._cmfs,
self._sd_D65) / 100,
XYZ,
decimal=7)
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, self._cmfs, self._sd_E), self._cmfs,
self._sd_E) / 100,
XYZ,
decimal=7)
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(
XYZ,
self._cmfs,
self._sd_D65,
optimisation_kwargs={'options': {
'ftol': 1e-10,
}}), self._cmfs, self._sd_D65) / 100,
XYZ,
decimal=7)
shape = SpectralShape(400, 700, 5)
cmfs = self._cmfs.copy().align(shape)
np.testing.assert_almost_equal(sd_to_XYZ_integration(
XYZ_to_sd_Meng2015(XYZ, cmfs, self._sd_D65), cmfs, self._sd_D65) /
100,
XYZ,
decimal=7)