Source code for colour.adaptation

# -*- coding: utf-8 -*-
"""
References
----------
-   :cite:`CIETC1-321994b` : CIE TC 1-32. (1994). CIE 109-1994 A Method of
    Predicting Corresponding Colours under Different Chromatic and Illuminance
    Adaptations. ISBN:978-3-900734-51-0
-   :cite:`Fairchild1991a` : Fairchild, M. D. (1991). Formulation and testing
    of an incomplete-chromatic-adaptation model. Color Research & Application,
    16(4), 243-250. doi:10.1002/col.5080160406
-   :cite:`Fairchild2013s` : Fairchild, M. D. (2013). FAIRCHILD'S 1990 MODEL.
    In Color Appearance Models (3rd ed., pp. 4418-4495). Wiley. ISBN:B00DAYO8E2
-   :cite:`Fairchild2013t` : Fairchild, M. D. (2013). Chromatic Adaptation
    Models. In Color Appearance Models (3rd ed., pp. 4179-4252). Wiley.
    ISBN:B00DAYO8E2
-   :cite:`Li2002a` : Li, C., Luo, M. R., Rigg, B., & Hunt, R. W. G. (2002).
    CMC 2000 chromatic adaptation transform: CMCCAT2000. Color Research &
    Application, 27(1), 49-58. doi:10.1002/col.10005
-   :cite:`Westland2012k` : Westland, S., Ripamonti, C., & Cheung, V. (2012).
    CMCCAT2000. In Computational Colour Science Using MATLAB
    (2nd ed., pp. 83-86). ISBN:978-0-470-66569-5
"""

from __future__ import absolute_import

import numpy as np

from colour.utilities import CaseInsensitiveMapping, filter_kwargs

from .dataset import *  # noqa
from . import dataset
from .vonkries import (chromatic_adaptation_matrix_VonKries,
                       chromatic_adaptation_VonKries)
from .fairchild1990 import chromatic_adaptation_Fairchild1990
from .cmccat2000 import (
    CMCCAT2000_InductionFactors, CMCCAT2000_VIEWING_CONDITIONS,
    chromatic_adaptation_forward_CMCCAT2000,
    chromatic_adaptation_reverse_CMCCAT2000, chromatic_adaptation_CMCCAT2000)
from .cie1994 import chromatic_adaptation_CIE1994

__all__ = []
__all__ += dataset.__all__
__all__ += [
    'chromatic_adaptation_matrix_VonKries', 'chromatic_adaptation_VonKries'
]
__all__ += ['chromatic_adaptation_Fairchild1990']
__all__ += [
    'CMCCAT2000_InductionFactors', 'CMCCAT2000_VIEWING_CONDITIONS',
    'chromatic_adaptation_forward_CMCCAT2000',
    'chromatic_adaptation_reverse_CMCCAT2000',
    'chromatic_adaptation_CMCCAT2000'
]
__all__ += ['chromatic_adaptation_CIE1994']

CHROMATIC_ADAPTATION_METHODS = CaseInsensitiveMapping({
    'CIE 1994': chromatic_adaptation_CIE1994,
    'CMCCAT2000': chromatic_adaptation_CMCCAT2000,
    'Fairchild 1990': chromatic_adaptation_Fairchild1990,
    'Von Kries': chromatic_adaptation_VonKries,
})
CHROMATIC_ADAPTATION_METHODS.__doc__ = """
Supported chromatic adaptation methods.

References
----------
-   :cite:`CIETC1-321994b`
-   :cite:`Fairchild1991a`
-   :cite:`Fairchild2013s`
-   :cite:`Fairchild2013t`
-   :cite:`Li2002a`
-   :cite:`Westland2012k`

CHROMATIC_ADAPTATION_METHODS : CaseInsensitiveMapping
    **{'CIE 1994', 'CMCCAT2000', 'Fairchild 1990', 'Von Kries'}**
"""


[docs]def chromatic_adaptation(XYZ, XYZ_w, XYZ_wr, method='Von Kries', **kwargs): """ 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 the whitepoint. XYZ_wr : array_like Reference viewing condition *CIE XYZ* tristimulus values of the whitepoint. method : unicode, optional **{'Von Kries', 'CIE 1994', 'CMCCAT2000', 'Fairchild 1990'}**, Computation method. Other Parameters ---------------- E_o1 : numeric {:func:`colour.adaptation.chromatic_adaptation_CIE1994`}, Test illuminance :math:`E_{o1}` in :math:`cd/m^2`. E_o2 : numeric {:func:`colour.adaptation.chromatic_adaptation_CIE1994`}, Reference illuminance :math:`E_{o2}` in :math:`cd/m^2`. L_A1 : numeric or array_like {:func:`colour.adaptation.chromatic_adaptation_CMCCAT2000`}, Luminance of test adapting field :math:`L_{A1}` in :math:`cd/m^2`. L_A2 : numeric or array_like {:func:`colour.adaptation.chromatic_adaptation_CMCCAT2000`}, Luminance of reference adapting field :math:`L_{A2}` in :math:`cd/m^2`. Y_n : numeric or array_like {:func:`colour.adaptation.chromatic_adaptation_Fairchild1990`}, Luminance :math:`Y_n` of test adapting stimulus in :math:`cd/m^2`. Y_o : numeric {:func:`colour.adaptation.chromatic_adaptation_CIE1994`}, Luminance factor :math:`Y_o` of achromatic background as percentage in domain [18, 100]. direction : unicode, optional {:func:`colour.adaptation.chromatic_adaptation_CMCCAT2000`}, **{'Forward', 'Reverse'}**, Chromatic adaptation direction. discount_illuminant : bool, optional {:func:`colour.adaptation.chromatic_adaptation_Fairchild1990`}, Truth value indicating if the illuminant should be discounted. n : numeric, optional {:func:`colour.adaptation.chromatic_adaptation_CIE1994`}, Noise component in fundamental primary system. surround : CMCCAT2000_InductionFactors, optional {:func:`colour.adaptation.chromatic_adaptation_CMCCAT2000`}, Surround viewing conditions induction factors. transform : unicode, optional {:func:`colour.adaptation.chromatic_adaptation_VonKries`}, **{'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. References ---------- - :cite:`CIETC1-321994b` - :cite:`Fairchild1991a` - :cite:`Fairchild2013s` - :cite:`Fairchild2013t` - :cite:`Li2002a` - :cite:`Westland2012k` Examples -------- *Von Kries* chromatic adaptation: >>> import numpy as np >>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313]) >>> XYZ_w = np.array([1.09846607, 1.00000000, 0.35582280]) >>> XYZ_wr = np.array([0.95042855, 1.00000000, 1.08890037]) >>> chromatic_adaptation(XYZ, XYZ_w, XYZ_wr) ... # doctest: +ELLIPSIS array([ 0.0839746..., 0.1141321..., 0.2862554...]) *CIE 1994* chromatic adaptation, requires extra *kwargs*: >>> XYZ = np.array([0.2800, 0.2126, 0.0527]) >>> XYZ_w = np.array([1.09867452, 1.00000000, 0.35591556]) >>> XYZ_wr = np.array([0.95045593, 1.00000000, 1.08905775]) >>> Y_o = 20 >>> E_o = 1000 >>> chromatic_adaptation( ... XYZ, XYZ_w, XYZ_wr, method='CIE 1994', Y_o=Y_o, E_o1=E_o, E_o2=E_o) ... # doctest: +ELLIPSIS array([ 0.2403379..., 0.2115621..., 0.1764301...]) *CMCCAT2000* chromatic adaptation, requires extra *kwargs*: >>> XYZ = np.array([0.2248, 0.2274, 0.0854]) >>> XYZ_w = np.array([1.1115, 1.0000, 0.3520]) >>> XYZ_wr = np.array([0.9481, 1.0000, 1.0730]) >>> L_A = 200 >>> chromatic_adaptation( ... XYZ, XYZ_w, XYZ_wr, method='CMCCAT2000', L_A1=L_A, L_A2=L_A) ... # doctest: +ELLIPSIS array([ 0.1952698..., 0.2306834..., 0.2497175...]) *Fairchild (1990)* chromatic adaptation, requires extra *kwargs*: >>> XYZ = np.array([0.1953, 0.2307, 0.2497]) >>> Y_n = 200 >>> chromatic_adaptation( ... XYZ, XYZ_w, XYZ_wr, method='Fairchild 1990', Y_n=Y_n) ... # doctest: +ELLIPSIS array([ 0.2332526..., 0.2332455..., 0.7611593...]) """ XYZ = np.asarray(XYZ) XYZ_w = np.asarray(XYZ_w) XYZ_wr = np.asarray(XYZ_wr) function = CHROMATIC_ADAPTATION_METHODS[method] # Callables with percentage domain. # TODO: Handle scaling with metadata. percentage_domain = (chromatic_adaptation_CIE1994, chromatic_adaptation_CMCCAT2000, chromatic_adaptation_Fairchild1990) if function in percentage_domain: XYZ = XYZ * 100 XYZ_w = XYZ_w * 100 XYZ_wr = XYZ_wr * 100 kwargs.update({'XYZ_w': XYZ_w, 'XYZ_wr': XYZ_wr}) if function is chromatic_adaptation_CIE1994: from colour import XYZ_to_xy kwargs.update({'xy_o1': XYZ_to_xy(XYZ_w), 'xy_o2': XYZ_to_xy(XYZ_wr)}) elif function is chromatic_adaptation_Fairchild1990: kwargs.update({'XYZ_n': XYZ_w, 'XYZ_r': XYZ_wr}) XYZ_c = function(XYZ, **filter_kwargs(function, **kwargs)) if function in percentage_domain: XYZ_c /= 100 return XYZ_c
__all__ += ['CHROMATIC_ADAPTATION_METHODS', 'chromatic_adaptation']