"""
Von Kries Chromatic Adaptation Model
====================================
Defines the *Von Kries* chromatic adaptation model objects:
- :func:`colour.adaptation.matrix_chromatic_adaptation_VonKries`
- :func:`colour.adaptation.chromatic_adaptation_VonKries`
References
----------
- :cite:`Fairchild2013t` : Fairchild, M. D. (2013). Chromatic Adaptation
Models. In Color Appearance Models (3rd ed., pp. 4179-4252). Wiley.
ISBN:B00DAYO8E2
"""
from __future__ import annotations
import numpy as np
from colour.adaptation import CHROMATIC_ADAPTATION_TRANSFORMS
from colour.algebra import matrix_dot, sdiv, sdiv_mode, vector_dot
from colour.hints import (
ArrayLike,
LiteralChromaticAdaptationTransform,
NDArrayFloat,
)
from colour.utilities import (
from_range_1,
row_as_diagonal,
to_domain_1,
validate_method,
)
__author__ = "Colour Developers"
__copyright__ = "Copyright 2013 Colour Developers"
__license__ = "BSD-3-Clause - https://opensource.org/licenses/BSD-3-Clause"
__maintainer__ = "Colour Developers"
__email__ = "colour-developers@colour-science.org"
__status__ = "Production"
__all__ = [
"matrix_chromatic_adaptation_VonKries",
"chromatic_adaptation_VonKries",
]
[docs]
def matrix_chromatic_adaptation_VonKries(
XYZ_w: ArrayLike,
XYZ_wr: ArrayLike,
transform: LiteralChromaticAdaptationTransform | str = "CAT02",
) -> NDArrayFloat:
"""
Compute the *chromatic adaptation* matrix from test viewing conditions
to reference viewing conditions.
Parameters
----------
XYZ_w
Test viewing conditions *CIE XYZ* tristimulus values of whitepoint.
XYZ_wr
Reference viewing conditions *CIE XYZ* tristimulus values of
whitepoint.
transform
Chromatic adaptation transform.
Returns
-------
:class:`numpy.ndarray`
Chromatic adaptation matrix :math:`M_{cat}`.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ_w`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
| ``XYZ_wr`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
References
----------
:cite:`Fairchild2013t`
Examples
--------
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> matrix_chromatic_adaptation_VonKries(XYZ_w, XYZ_wr)
... # doctest: +ELLIPSIS
array([[ 1.0425738..., 0.0308910..., -0.0528125...],
[ 0.0221934..., 1.0018566..., -0.0210737...],
[-0.0011648..., -0.0034205..., 0.7617890...]])
Using Bradford method:
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> method = "Bradford"
>>> matrix_chromatic_adaptation_VonKries(XYZ_w, XYZ_wr, method)
... # doctest: +ELLIPSIS
array([[ 1.0479297..., 0.0229468..., -0.0501922...],
[ 0.0296278..., 0.9904344..., -0.0170738...],
[-0.0092430..., 0.0150551..., 0.7518742...]])
"""
XYZ_w = to_domain_1(XYZ_w)
XYZ_wr = to_domain_1(XYZ_wr)
transform = validate_method(
transform,
tuple(CHROMATIC_ADAPTATION_TRANSFORMS),
'"{0}" chromatic adaptation transform is invalid, '
"it must be one of {1}!",
)
M = CHROMATIC_ADAPTATION_TRANSFORMS[transform]
RGB_w = np.einsum("...i,...ij->...j", XYZ_w, np.transpose(M))
RGB_wr = np.einsum("...i,...ij->...j", XYZ_wr, np.transpose(M))
with sdiv_mode():
D = sdiv(RGB_wr, RGB_w)
D = row_as_diagonal(D)
M_CAT = matrix_dot(np.linalg.inv(M), D)
M_CAT = matrix_dot(M_CAT, M)
return M_CAT
[docs]
def chromatic_adaptation_VonKries(
XYZ: ArrayLike,
XYZ_w: ArrayLike,
XYZ_wr: ArrayLike,
transform: LiteralChromaticAdaptationTransform | str = "CAT02",
) -> NDArrayFloat:
"""
Adapt given stimulus from test viewing conditions to reference viewing
conditions.
Parameters
----------
XYZ
*CIE XYZ* tristimulus values of stimulus to adapt.
XYZ_w
Test viewing conditions *CIE XYZ* tristimulus values of whitepoint.
XYZ_wr
Reference viewing conditions *CIE XYZ* tristimulus values of
whitepoint.
transform
Chromatic adaptation transform.
Returns
-------
:class:`numpy.ndarray`
*CIE XYZ_c* tristimulus values of the stimulus corresponding colour.
Notes
-----
+------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
| ``XYZ_n`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
| ``XYZ_r`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
+------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+=======================+===============+
| ``XYZ_c`` | [0, 1] | [0, 1] |
+------------+-----------------------+---------------+
References
----------
:cite:`Fairchild2013t`
Examples
--------
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr) # doctest: +ELLIPSIS
array([ 0.2163881..., 0.1257 , 0.0384749...])
Using Bradford method:
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> XYZ_w = np.array([0.95045593, 1.00000000, 1.08905775])
>>> XYZ_wr = np.array([0.96429568, 1.00000000, 0.82510460])
>>> transform = "Bradford"
>>> chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr, transform)
... # doctest: +ELLIPSIS
array([ 0.2166600..., 0.1260477..., 0.0385506...])
"""
XYZ = to_domain_1(XYZ)
M_CAT = matrix_chromatic_adaptation_VonKries(XYZ_w, XYZ_wr, transform)
XYZ_a = vector_dot(M_CAT, XYZ)
return from_range_1(XYZ_a)