# -*- coding: utf-8 -*-
"""
Von Kries Chromatic Adaptation Model
====================================
Defines *Von Kries* chromatic adaptation model objects:
- :func:`colour.adaptation.chromatic_adaptation_matrix_VonKries`
- :func:`colour.adaptation.chromatic_adaptation_VonKries`
See Also
--------
`Chromatic Adaptation Jupyter Notebook
<http://nbviewer.jupyter.org/github/colour-science/colour-notebooks/\
blob/master/notebooks/adaptation/vonkries.ipynb>`_
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 division, unicode_literals
import numpy as np
from colour.adaptation import CHROMATIC_ADAPTATION_TRANSFORMS
from colour.utilities import (dot_matrix, dot_vector, from_range_1,
row_as_diagonal, to_domain_1)
__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2019 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-science@googlegroups.com'
__status__ = 'Production'
__all__ = [
'chromatic_adaptation_matrix_VonKries', 'chromatic_adaptation_VonKries'
]
[docs]def chromatic_adaptation_matrix_VonKries(XYZ_w, XYZ_wr, transform='CAT02'):
"""
Computes the *chromatic adaptation* matrix from test viewing conditions
to reference viewing conditions.
Parameters
----------
XYZ_w : array_like
Test viewing condition *CIE XYZ* tristimulus values of whitepoint.
XYZ_wr : array_like
Reference viewing condition *CIE XYZ* tristimulus values of whitepoint.
transform : unicode, optional
**{'CAT02', 'XYZ Scaling', 'Von Kries', 'Bradford', 'Sharp',
'Fairchild', 'CMCCAT97', 'CMCCAT2000', 'CAT02_BRILL_CAT', 'Bianco',
'Bianco PC'}**,
Chromatic adaptation transform.
Returns
-------
ndarray
Chromatic adaptation matrix :math:`M_{cat}`.
Raises
------
KeyError
If chromatic adaptation method is not defined.
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])
>>> chromatic_adaptation_matrix_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'
>>> chromatic_adaptation_matrix_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)
M = CHROMATIC_ADAPTATION_TRANSFORMS.get(transform)
if M is None:
raise KeyError(
'"{0}" chromatic adaptation transform is not defined! Supported '
'methods: "{1}".'.format(transform,
CHROMATIC_ADAPTATION_TRANSFORMS.keys()))
rgb_w = np.einsum('...i,...ij->...j', XYZ_w, np.transpose(M))
rgb_wr = np.einsum('...i,...ij->...j', XYZ_wr, np.transpose(M))
D = rgb_wr / rgb_w
D = row_as_diagonal(D)
M_CAT = dot_matrix(np.linalg.inv(M), D)
M_CAT = dot_matrix(M_CAT, M)
return M_CAT
[docs]def chromatic_adaptation_VonKries(XYZ, XYZ_w, XYZ_wr, transform='CAT02'):
"""
Adapts given stimulus from test viewing conditions to reference viewing
conditions.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values of stimulus to adapt.
XYZ_w : array_like
Test viewing condition *CIE XYZ* tristimulus values of whitepoint.
XYZ_wr : array_like
Reference viewing condition *CIE XYZ* tristimulus values of whitepoint.
transform : unicode, optional
**{'CAT02', 'XYZ Scaling', 'Von Kries', 'Bradford', 'Sharp',
'Fairchild', 'CMCCAT97', 'CMCCAT2000', 'CAT02_BRILL_CAT', 'Bianco',
'Bianco PC'}**,
Chromatic adaptation transform.
Returns
-------
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 = chromatic_adaptation_matrix_VonKries(XYZ_w, XYZ_wr, transform)
XYZ_a = dot_vector(M_CAT, XYZ)
return from_range_1(XYZ_a)