Source code for colour.adaptation.cmccat2000

# -*- coding: utf-8 -*-
"""
CMCCAT2000 Chromatic Adaptation Model
=====================================

Defines *CMCCAT2000* chromatic adaptation model objects:

-   :class:`colour.adaptation.CMCCAT2000_InductionFactors`
-   :class:`colour.CMCCAT2000_VIEWING_CONDITIONS`
-   :func:`colour.adaptation.chromatic_adaptation_forward_CMCCAT2000`
-   :func:`colour.adaptation.chromatic_adaptation_inverse_CMCCAT2000`
-   :func:`colour.adaptation.chromatic_adaptation_CMCCAT2000`

References
----------
-   :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 division, unicode_literals

import numpy as np
from collections import namedtuple

from colour.adaptation import CMCCAT2000_CAT
from colour.utilities import (CaseInsensitiveMapping, as_float_array,
                              dot_vector, from_range_100, to_domain_100)

__author__ = 'Colour Developers'
__copyright__ = 'Copyright (C) 2013-2020 - Colour Developers'
__license__ = 'New BSD License - https://opensource.org/licenses/BSD-3-Clause'
__maintainer__ = 'Colour Developers'
__email__ = 'colour-developers@colour-science.org'
__status__ = 'Production'

__all__ = [
    'CMCCAT2000_INVERSE_CAT', 'CMCCAT2000_InductionFactors',
    'CMCCAT2000_VIEWING_CONDITIONS', 'chromatic_adaptation_forward_CMCCAT2000',
    'chromatic_adaptation_inverse_CMCCAT2000',
    'chromatic_adaptation_CMCCAT2000'
]

CMCCAT2000_INVERSE_CAT = np.linalg.inv(CMCCAT2000_CAT)
"""
Inverse *CMCCAT2000* chromatic adaptation transform.

CMCCAT2000_INVERSE_CAT : array_like, (3, 3)
"""


[docs]class CMCCAT2000_InductionFactors( namedtuple('CMCCAT2000_InductionFactors', ('F', ))): """ *CMCCAT2000* chromatic adaptation model induction factors. Parameters ---------- F : numeric or array_like :math:`F` surround condition. References ---------- :cite:`Li2002a`, :cite:`Westland2012k` """
CMCCAT2000_VIEWING_CONDITIONS = CaseInsensitiveMapping({ 'Average': CMCCAT2000_InductionFactors(1), 'Dim': CMCCAT2000_InductionFactors(0.8), 'Dark': CMCCAT2000_InductionFactors(0.8) }) CMCCAT2000_VIEWING_CONDITIONS.__doc__ = """ Reference *CMCCAT2000* chromatic adaptation model viewing conditions. References ---------- :cite:`Li2002a`, :cite:`Westland2012k` CMCCAT2000_VIEWING_CONDITIONS : CaseInsensitiveMapping ('Average', 'Dim', 'Dark') """
[docs]def chromatic_adaptation_forward_CMCCAT2000( XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, surround=CMCCAT2000_VIEWING_CONDITIONS['Average']): """ Adapts given stimulus *CIE XYZ* tristimulus values from test viewing conditions to reference viewing conditions using *CMCCAT2000* forward chromatic adaptation model. Parameters ---------- XYZ : array_like *CIE XYZ* tristimulus values of the 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. L_A1 : numeric or array_like Luminance of test adapting field :math:`L_{A1}` in :math:`cd/m^2`. L_A2 : numeric or array_like Luminance of reference adapting field :math:`L_{A2}` in :math:`cd/m^2`. surround : CMCCAT2000_InductionFactors, optional Surround viewing conditions induction factors. Returns ------- ndarray *CIE XYZ_c* tristimulus values of the stimulus corresponding colour. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_w`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_wr`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ_c`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`Li2002a`, :cite:`Westland2012k` Examples -------- >>> XYZ = np.array([22.48, 22.74, 8.54]) >>> XYZ_w = np.array([111.15, 100.00, 35.20]) >>> XYZ_wr = np.array([94.81, 100.00, 107.30]) >>> L_A1 = 200 >>> L_A2 = 200 >>> chromatic_adaptation_forward_CMCCAT2000(XYZ, XYZ_w, XYZ_wr, L_A1, L_A2) ... # doctest: +ELLIPSIS array([ 19.5269832..., 23.0683396..., 24.9717522...]) """ XYZ = to_domain_100(XYZ) XYZ_w = to_domain_100(XYZ_w) XYZ_wr = to_domain_100(XYZ_wr) L_A1 = as_float_array(L_A1) L_A2 = as_float_array(L_A2) RGB = dot_vector(CMCCAT2000_CAT, XYZ) RGB_w = dot_vector(CMCCAT2000_CAT, XYZ_w) RGB_wr = dot_vector(CMCCAT2000_CAT, XYZ_wr) D = (surround.F * (0.08 * np.log10(0.5 * (L_A1 + L_A2)) + 0.76 - 0.45 * (L_A1 - L_A2) / (L_A1 + L_A2))) D = np.clip(D, 0, 1) a = D * XYZ_w[..., 1] / XYZ_wr[..., 1] RGB_c = ( RGB * (a[..., np.newaxis] * (RGB_wr / RGB_w) + 1 - D[..., np.newaxis])) XYZ_c = dot_vector(CMCCAT2000_INVERSE_CAT, RGB_c) return from_range_100(XYZ_c)
[docs]def chromatic_adaptation_inverse_CMCCAT2000( XYZ_c, XYZ_w, XYZ_wr, L_A1, L_A2, surround=CMCCAT2000_VIEWING_CONDITIONS['Average']): """ Adapts given stimulus corresponding colour *CIE XYZ* tristimulus values from reference viewing conditions to test viewing conditions using *CMCCAT2000* inverse chromatic adaptation model. Parameters ---------- XYZ_c : array_like *CIE XYZ* tristimulus values of the 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. L_A1 : numeric or array_like Luminance of test adapting field :math:`L_{A1}` in :math:`cd/m^2`. L_A2 : numeric or array_like Luminance of reference adapting field :math:`L_{A2}` in :math:`cd/m^2`. surround : CMCCAT2000_InductionFactors, optional Surround viewing conditions induction factors. Returns ------- ndarray *CIE XYZ_c* tristimulus values of the adapted stimulus. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ_c`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_w`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_wr`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`Li2002a`, :cite:`Westland2012k` Examples -------- >>> XYZ_c = np.array([19.53, 23.07, 24.97]) >>> XYZ_w = np.array([111.15, 100.00, 35.20]) >>> XYZ_wr = np.array([94.81, 100.00, 107.30]) >>> L_A1 = 200 >>> L_A2 = 200 >>> chromatic_adaptation_inverse_CMCCAT2000(XYZ_c, XYZ_w, XYZ_wr, L_A1, ... L_A2) ... # doctest: +ELLIPSIS array([ 22.4839876..., 22.7419485..., 8.5393392...]) """ XYZ_c = to_domain_100(XYZ_c) XYZ_w = to_domain_100(XYZ_w) XYZ_wr = to_domain_100(XYZ_wr) L_A1 = as_float_array(L_A1) L_A2 = as_float_array(L_A2) RGB_c = dot_vector(CMCCAT2000_CAT, XYZ_c) RGB_w = dot_vector(CMCCAT2000_CAT, XYZ_w) RGB_wr = dot_vector(CMCCAT2000_CAT, XYZ_wr) D = (surround.F * (0.08 * np.log10(0.5 * (L_A1 + L_A2)) + 0.76 - 0.45 * (L_A1 - L_A2) / (L_A1 + L_A2))) D = np.clip(D, 0, 1) a = D * XYZ_w[..., 1] / XYZ_wr[..., 1] RGB = (RGB_c / (a[..., np.newaxis] * (RGB_wr / RGB_w) + 1 - D[..., np.newaxis])) XYZ = dot_vector(CMCCAT2000_INVERSE_CAT, RGB) return from_range_100(XYZ)
[docs]def chromatic_adaptation_CMCCAT2000( XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, surround=CMCCAT2000_VIEWING_CONDITIONS['Average'], direction='Forward'): """ Adapts given stimulus *CIE XYZ* tristimulus values using given viewing conditions. This definition is a convenient wrapper around :func:`colour.adaptation.chromatic_adaptation_forward_CMCCAT2000` and :func:`colour.adaptation.chromatic_adaptation_inverse_CMCCAT2000`. Parameters ---------- XYZ : array_like *CIE XYZ* tristimulus values of the stimulus to adapt. XYZ_w : array_like Source viewing condition *CIE XYZ* tristimulus values of the whitepoint. XYZ_wr : array_like Target viewing condition *CIE XYZ* tristimulus values of the whitepoint. L_A1 : numeric or array_like Luminance of test adapting field :math:`L_{A1}` in :math:`cd/m^2`. L_A2 : numeric or array_like Luminance of reference adapting field :math:`L_{A2}` in :math:`cd/m^2`. surround : CMCCAT2000_InductionFactors, optional Surround viewing conditions induction factors. direction : unicode, optional **{'Forward', 'Inverse'}**, Chromatic adaptation direction. Returns ------- ndarray Adapted stimulus *CIE XYZ* tristimulus values. Notes ----- +------------+-----------------------+---------------+ | **Domain** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_w`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ | ``XYZ_wr`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ +------------+-----------------------+---------------+ | **Range** | **Scale - Reference** | **Scale - 1** | +============+=======================+===============+ | ``XYZ`` | [0, 100] | [0, 1] | +------------+-----------------------+---------------+ References ---------- :cite:`Li2002a`, :cite:`Westland2012k` Examples -------- >>> XYZ = np.array([22.48, 22.74, 8.54]) >>> XYZ_w = np.array([111.15, 100.00, 35.20]) >>> XYZ_wr = np.array([94.81, 100.00, 107.30]) >>> L_A1 = 200 >>> L_A2 = 200 >>> chromatic_adaptation_CMCCAT2000( ... XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, direction='Forward') ... # doctest: +ELLIPSIS array([ 19.5269832..., 23.0683396..., 24.9717522...]) Using the *CMCCAT2000* inverse model: >>> XYZ = np.array([19.52698326, 23.06833960, 24.97175229]) >>> XYZ_w = np.array([111.15, 100.00, 35.20]) >>> XYZ_wr = np.array([94.81, 100.00, 107.30]) >>> L_A1 = 200 >>> L_A2 = 200 >>> chromatic_adaptation_CMCCAT2000( ... XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, direction='Inverse') ... # doctest: +ELLIPSIS array([ 22.48, 22.74, 8.54]) """ if direction.lower() == 'forward': return chromatic_adaptation_forward_CMCCAT2000(XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, surround) else: return chromatic_adaptation_inverse_CMCCAT2000(XYZ, XYZ_w, XYZ_wr, L_A1, L_A2, surround)