def RGB_to_coefficients(self, RGB: ArrayLike) -> NDArray:
"""
Look up a given *RGB* colourspace array and return corresponding
coefficients. Interpolation is used for colours not on the table grid.
Parameters
----------
RGB
*RGB* colourspace array.
Returns
-------
:class:`numpy.ndarray`
Corresponding coefficients that can be passed to
:func:`colour.recovery.jakob2019.sd_Jakob2019` to obtain a spectral
distribution.
Raises
------
RuntimeError
If the pre-computed lookup table has not been generated or read.
Examples
--------
>>> from colour import MSDS_CMFS, SDS_ILLUMINANTS
>>> from colour.models import RGB_COLOURSPACE_sRGB
>>> cmfs = (
... MSDS_CMFS['CIE 1931 2 Degree Standard Observer'].
... copy().align(SpectralShape(360, 780, 10))
... )
>>> illuminant = SDS_ILLUMINANTS['D65'].copy().align(cmfs.shape)
>>> LUT = LUT3D_Jakob2019()
>>> LUT.generate(
... RGB_COLOURSPACE_sRGB, cmfs, illuminant, 3, lambda x: x)
>>> RGB = np.array([0.70573936, 0.19248266, 0.22354169])
>>> LUT.RGB_to_coefficients(RGB) # doctest: +ELLIPSIS
array([ 1.5013448...e-04, -1.4679754...e-01, 3.4020219...e+01])
"""
if self._interpolator is not None:
RGB = as_float_array(RGB)
value_max = np.max(RGB, axis=-1)
chroma = RGB / (value_max[..., np.newaxis] + 1e-10)
i_m = np.argmax(RGB, axis=-1)
i_1 = index_along_last_axis(RGB, i_m)
i_2 = index_along_last_axis(chroma, (i_m + 2) % 3)
i_3 = index_along_last_axis(chroma, (i_m + 1) % 3)
indexes = np.stack([i_m, i_1, i_2, i_3], axis=-1)
return self._interpolator(indexes).squeeze()
else:
raise RuntimeError(
"The pre-computed lookup table has not been read or generated!"
)
def test_compare_with_argmin_argmax(self):
"""
Tests :func:`colour.utilities.array.index_along_last_axis` definition
by comparison with :func:`argmin` and :func:`argmax`.
"""
a = np.random.random((2, 3, 4, 5, 6, 7))
np.testing.assert_equal(
index_along_last_axis(a, np.argmin(a, axis=-1)), np.min(a,
axis=-1))
np.testing.assert_equal(
index_along_last_axis(a, np.argmax(a, axis=-1)), np.max(a,
axis=-1))
def test_index_along_last_axis(self):
"""
Tests :func:`colour.utilities.array.index_along_last_axis` definition.
"""
a = np.array([[[[0.51090627, 0.86191718, 0.8687926],
[0.82738158, 0.80587656, 0.28285687]],
[[0.84085977, 0.03851814, 0.06057988],
[0.94659267, 0.79308353, 0.30870888]]],
[[[0.50758436, 0.24066455, 0.20199051],
[0.4507304, 0.84189245, 0.81160878]],
[[0.75421871, 0.88187494, 0.01612045],
[0.38777511, 0.58905552, 0.32970469]]],
[[[0.99285824, 0.738076, 0.0716432],
[0.35847844, 0.0367514, 0.18586322]],
[[0.72674561, 0.0822759, 0.9771182],
[0.90644279, 0.09689787, 0.93483977]]]])
indexes = np.array([[[0, 1], [0, 1]], [[2, 1], [2, 1]], [[2, 1],
[2, 0]]])
np.testing.assert_equal(
index_along_last_axis(a, indexes),
np.array([[[0.51090627, 0.80587656], [0.84085977, 0.79308353]],
[[0.20199051, 0.84189245], [0.01612045, 0.58905552]],
[[0.0716432, 0.0367514], [0.9771182, 0.90644279]]]))
def RGB_to_coefficients(self, RGB):
"""
Look up a given *RGB* colourspace array and return corresponding
coefficients. Interpolation is used for colours not on the table grid.
Parameters
----------
RGB : ndarray, (3,)
*RGB* colourspace array.
Returns
-------
coefficients : ndarray, (3,)
Corresponding coefficients that can be passed to
:func:`colour.recovery.jakob2019.sd_Jakob2019` to obtain a spectral
distribution.
Examples
--------
>>> from colour.models import RGB_COLOURSPACE_sRGB
>>> cmfs = MSDS_CMFS_STANDARD_OBSERVER[
... 'CIE 1931 2 Degree Standard Observer'].copy().align(
... SpectralShape(360, 780, 10))
>>> illuminant = SDS_ILLUMINANTS['D65'].copy().align(cmfs.shape)
>>> LUT = LUT3D_Jakob2019()
>>> LUT.generate(
... RGB_COLOURSPACE_sRGB, cmfs, illuminant, 3, lambda x: x)
>>> RGB = np.array([0.70573936, 0.19248266, 0.22354169])
>>> LUT.RGB_to_coefficients(RGB) # doctest: +ELLIPSIS
array([ 1.5012557...e-04, -1.4678661...e-01, 3.4017293...e+01])
"""
RGB = as_float_array(RGB)
value_max = np.max(RGB, axis=-1)
chroma = RGB / (np.expand_dims(value_max, -1) + 1e-10)
i_m = np.argmax(RGB, axis=-1)
i_1 = index_along_last_axis(RGB, i_m)
i_2 = index_along_last_axis(chroma, (i_m + 2) % 3)
i_3 = index_along_last_axis(chroma, (i_m + 1) % 3)
indexes = np.stack([i_m, i_1, i_2, i_3], axis=-1)
return self._interpolator(indexes).squeeze()
def test_exceptions(self):
"""
Tests :func:`colour.utilities.array.index_along_last_axis` definition
handling of invalid inputs.
"""
a = as_float_array([[11, 12], [21, 22]])
# Bad shape
with self.assertRaises(ValueError):
indexes = np.array([0])
index_along_last_axis(a, indexes)
# Indexes out of range
with self.assertRaises(IndexError):
indexes = np.array([123, 456])
index_along_last_axis(a, indexes)
# Non-integer indexes
with self.assertRaises(IndexError):
indexes = np.array([0., 0.])
index_along_last_axis(a, indexes)