def test_XYZ_to_K_ab_HunterLab1966(self):
"""
Test :func:`colour.models.hunter_lab.XYZ_to_K_ab_HunterLab1966`
definition.
"""
np.testing.assert_almost_equal(
XYZ_to_K_ab_HunterLab1966(
np.array([0.20654008, 0.12197225, 0.05136952]) * 100),
np.array([80.32152090, 14.59816495]),
decimal=7,
)
np.testing.assert_almost_equal(
XYZ_to_K_ab_HunterLab1966(
np.array([0.14222010, 0.23042768, 0.10495772]) * 100),
np.array([66.65154834, 20.86664881]),
decimal=7,
)
np.testing.assert_almost_equal(
XYZ_to_K_ab_HunterLab1966(
np.array([0.07818780, 0.06157201, 0.28099326]) * 100),
np.array([49.41960269, 34.14235426]),
decimal=7,
)
def XYZ_to_Hunter_Rdab(
XYZ,
XYZ_n=HUNTERLAB_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']
['D50'].XYZ_n,
K_ab=HUNTERLAB_ILLUMINANTS['CIE 1931 2 Degree Standard Observer']
['D50'].K_ab):
"""
Converts from *CIE XYZ* tristimulus values to *Hunter Rd,a,b* colour scale.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
XYZ_n : array_like, optional
Reference *illuminant* tristimulus values.
K_ab : array_like, optional
Reference *illuminant* chromaticity coefficients, if ``K_ab`` is set to
*None* it will be computed using
:func:`colour.XYZ_to_K_ab_HunterLab1966`.
Returns
-------
ndarray
*Hunter Rd,a,b* colour scale array.
Notes
-----
- Input *CIE XYZ* and reference *illuminant* tristimulus values are in
domain [0, 100].
References
----------
- :cite:`HunterLab2012a`
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313]) * 100
>>> D50 = HUNTERLAB_ILLUMINANTS[
... 'CIE 1931 2 Degree Standard Observer']['D50']
>>> XYZ_to_Hunter_Rdab(XYZ, D50.XYZ_n, D50.K_ab)
... # doctest: +ELLIPSIS
array([ 10.08 , -18.6765376..., -3.4432992...])
"""
X, Y, Z = tsplit(XYZ)
X_n, Y_n, Z_n = tsplit(XYZ_n)
K_a, K_b = (tsplit(XYZ_to_K_ab_HunterLab1966(XYZ_n))
if K_ab is None else tsplit(K_ab))
f = 0.51 * ((21 + 0.2 * Y) / (1 + 0.2 * Y))
Y_Yn = Y / Y_n
R_d = Y
a_Rd = K_a * f * (X / X_n - Y_Yn)
b_Rd = K_b * f * (Y_Yn - Z / Z_n)
R_d_ab = tstack((R_d, a_Rd, b_Rd))
return R_d_ab
def test_n_dimensional_XYZ_to_K_ab_HunterLab1966(self):
"""
Tests :func:`colour.models.hunter_lab.XYZ_to_K_ab_HunterLab1966`
definition n-dimensional support.
"""
XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) * 100
K_ab = XYZ_to_K_ab_HunterLab1966(XYZ)
XYZ = np.tile(XYZ, (6, 1))
K_ab = np.tile(K_ab, (6, 1))
np.testing.assert_almost_equal(
XYZ_to_K_ab_HunterLab1966(XYZ), K_ab, decimal=7)
XYZ = np.reshape(XYZ, (2, 3, 3))
K_ab = np.reshape(K_ab, (2, 3, 2))
np.testing.assert_almost_equal(
XYZ_to_K_ab_HunterLab1966(XYZ), K_ab, decimal=7)
def test_XYZ_to_K_ab_HunterLab1966(self):
"""
Tests :func:`colour.models.hunter_lab.XYZ_to_K_ab_HunterLab1966`
definition.
"""
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(
np.array([0.07049534, 0.10080000, 0.09558313]) * 100),
np.array([46.92561332, 19.91297447]),
decimal=7)
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(
np.array([0.47097710, 0.34950000, 0.11301649]) * 100),
np.array([121.29129933, 21.65291746]),
decimal=7)
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(
np.array([0.25506814, 0.19150000, 0.08849752]) * 100),
np.array([89.26020100, 19.16068641]),
decimal=7)
def test_n_dimensional_XYZ_to_K_ab_HunterLab1966(self):
"""
Tests :func:`colour.models.hunter_lab.XYZ_to_K_ab_HunterLab1966`
definition n-dimensions support.
"""
XYZ = np.array([0.07049534, 0.10080000, 0.09558313]) * 100
K_ab = 46.9256133, 19.9129745
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(XYZ),
K_ab,
decimal=7)
XYZ = np.tile(XYZ, (6, 1))
K_ab = np.tile(K_ab, (6, 1))
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(XYZ),
K_ab,
decimal=7)
XYZ = np.reshape(XYZ, (2, 3, 3))
K_ab = np.reshape(K_ab, (2, 3, 2))
np.testing.assert_almost_equal(XYZ_to_K_ab_HunterLab1966(XYZ),
K_ab,
decimal=7)
def XYZ_to_Hunter_Rdab(
XYZ: ArrayLike,
XYZ_n: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB[
"CIE 1931 2 Degree Standard Observer"]["D65"].XYZ_n,
K_ab: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB[
"CIE 1931 2 Degree Standard Observer"]["D65"].K_ab,
) -> NDArray:
"""
Convert from *CIE XYZ* tristimulus values to *Hunter Rd,a,b* colour scale.
Parameters
----------
XYZ
*CIE XYZ* tristimulus values.
XYZ_n
Reference *illuminant* tristimulus values.
K_ab
Reference *illuminant* chromaticity coefficients, if ``K_ab`` is set to
*None* it will be computed using
:func:`colour.XYZ_to_K_ab_HunterLab1966`.
Returns
-------
:class:`numpy.ndarray`
*Hunter Rd,a,b* colour scale array.
Notes
-----
+------------+------------------------+--------------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+========================+====================+
| ``XYZ`` | [0, 100] | [0, 1] |
+------------+------------------------+--------------------+
| ``XYZ_n`` | [0, 100] | [0, 1] |
+------------+------------------------+--------------------+
+------------+------------------------+--------------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+========================+====================+
| ``R_d_ab`` | ``R_d`` : [0, 100] | ``R_d`` : [0, 1] |
| | | |
| | ``a_Rd`` : [-100, 100] | ``a_Rd`` : [-1, 1] |
| | | |
| | ``b_Rd`` : [-100, 100] | ``b_Rd`` : [-1, 1] |
+------------+------------------------+--------------------+
References
----------
:cite:`HunterLab2012a`
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) * 100
>>> D65 = TVS_ILLUMINANTS_HUNTERLAB[
... 'CIE 1931 2 Degree Standard Observer']['D65']
>>> XYZ_to_Hunter_Rdab(XYZ, D65.XYZ_n, D65.K_ab)
... # doctest: +ELLIPSIS
array([ 12.197225 ..., 57.1253787..., 17.4624134...])
"""
X, Y, Z = tsplit(to_domain_100(XYZ))
X_n, Y_n, Z_n = tsplit(to_domain_100(XYZ_n))
K_a, K_b = (tsplit(XYZ_to_K_ab_HunterLab1966(XYZ_n))
if K_ab is None else tsplit(K_ab))
f = 0.51 * ((21 + 0.2 * Y) / (1 + 0.2 * Y))
Y_Yn = Y / Y_n
R_d = Y
a_Rd = K_a * f * (X / X_n - Y_Yn)
b_Rd = K_b * f * (Y_Yn - Z / Z_n)
R_d_ab = tstack([R_d, a_Rd, b_Rd])
return from_range_100(R_d_ab)
def Hunter_Rdab_to_XYZ(
R_d_ab: ArrayLike,
XYZ_n: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB[
"CIE 1931 2 Degree Standard Observer"]["D65"].XYZ_n,
K_ab: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB[
"CIE 1931 2 Degree Standard Observer"]["D65"].K_ab,
) -> NDArray:
"""
Convert from *Hunter Rd,a,b* colour scale to *CIE XYZ* tristimulus values.
Parameters
----------
R_d_ab
*Hunter Rd,a,b* colour scale array.
XYZ_n
Reference *illuminant* tristimulus values.
K_ab
Reference *illuminant* chromaticity coefficients, if ``K_ab`` is set to
*None* it will be computed using
:func:`colour.XYZ_to_K_ab_HunterLab1966`.
Returns
-------
:class:`numpy.ndarray`
*CIE XYZ* tristimulus values.
Notes
-----
+------------+------------------------+--------------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+========================+====================+
| ``R_d_ab`` | ``R_d`` : [0, 100] | ``R_d`` : [0, 1] |
| | | |
| | ``a_Rd`` : [-100, 100] | ``a_Rd`` : [-1, 1] |
| | | |
| | ``b_Rd`` : [-100, 100] | ``b_Rd`` : [-1, 1] |
+------------+------------------------+--------------------+
| ``XYZ_n`` | [0, 100] | [0, 1] |
+------------+------------------------+--------------------+
+------------+------------------------+--------------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+========================+====================+
| ``XYZ`` | [0, 100] | [0, 1] |
+------------+------------------------+--------------------+
References
----------
:cite:`HunterLab2012a`
Examples
--------
>>> import numpy as np
>>> R_d_ab = np.array([12.19722500, 57.12537874, 17.46241341])
>>> D65 = TVS_ILLUMINANTS_HUNTERLAB[
... 'CIE 1931 2 Degree Standard Observer']['D65']
>>> Hunter_Rdab_to_XYZ(R_d_ab, D65.XYZ_n, D65.K_ab)
array([ 20.654008, 12.197225, 5.136952])
"""
R_d, a_Rd, b_Rd = tsplit(to_domain_100(R_d_ab))
X_n, Y_n, Z_n = tsplit(to_domain_100(XYZ_n))
K_a, K_b = (tsplit(XYZ_to_K_ab_HunterLab1966(XYZ_n))
if K_ab is None else tsplit(K_ab))
f = 0.51 * ((21 + 0.2 * R_d) / (1 + 0.2 * R_d))
Rd_Yn = R_d / Y_n
X = (a_Rd / (K_a * f) + Rd_Yn) * X_n
Z = -(b_Rd / (K_b * f) - Rd_Yn) * Z_n
XYZ = tstack([X, R_d, Z])
return from_range_100(XYZ)