Source code for colour.quality.cri

# -*- coding: utf-8 -*-
"""
Colour Rendering Index
======================

Defines *Colour Rendering Index* (CRI) computation objects:

-   :class:`colour.quality.CRI_Specification`
-   :func:`colour.colour_rendering_index`

References
----------
-   :cite:`Ohno2008a` : Ohno, Yoshiro, & Davis, W. (2008). NIST CQS simulation
    (Version 7.4) [Computer software].
    https://drive.google.com/file/d/1PsuU6QjUJjCX6tQyCud6ul2Tbs8rYWW9/view?\
usp=sharing
"""

from __future__ import division, unicode_literals

import numpy as np
from collections import namedtuple

from colour.algebra import euclidean_distance, spow
from colour.colorimetry import (
    DEFAULT_SPECTRAL_SHAPE, sd_CIE_illuminant_D_series, STANDARD_OBSERVER_CMFS,
    sd_blackbody, sd_to_XYZ)
from colour.quality.datasets.tcs import TCS_INDEXES_TO_NAMES, TCS_SDS
from colour.models import UCS_to_uv, XYZ_to_UCS, XYZ_to_xyY
from colour.temperature import CCT_to_xy_CIE_D, uv_to_CCT_Robertson1968
from colour.utilities import domain_range_scale

__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__ = [
    'TCS_ColorimetryData', 'TCS_ColourQualityScaleData', 'CRI_Specification',
    'colour_rendering_index', 'tcs_colorimetry_data',
    'colour_rendering_indexes'
]


class TCS_ColorimetryData(
        namedtuple('TCS_ColorimetryData', ('name', 'XYZ', 'uv', 'UVW'))):
    """
    Defines the the class storing *test colour samples* colorimetry data.
    """


class TCS_ColourQualityScaleData(
        namedtuple('TCS_ColourQualityScaleData', ('name', 'Q_a'))):
    """
    Defines the the class storing *test colour samples* colour rendering
    index data.
    """


[docs]class CRI_Specification( namedtuple('CRI_Specification', ('name', 'Q_a', 'Q_as', 'colorimetry_data'))): """ Defines the *Colour Rendering Index* (CRI) colour quality specification. Parameters ---------- name : unicode Name of the test spectral distribution. Q_a : numeric *Colour Rendering Index* (CRI) :math:`Q_a`. Q_as : dict Individual *colour rendering indexes* data for each sample. colorimetry_data : tuple Colorimetry data for the test and reference computations. References ---------- :cite:`Ohno2008a` """
[docs]def colour_rendering_index(sd_test, additional_data=False): """ Returns the *Colour Rendering Index* (CRI) :math:`Q_a` of given spectral distribution. Parameters ---------- sd_test : SpectralDistribution Test spectral distribution. additional_data : bool, optional Whether to output additional data. Returns ------- numeric or CRI_Specification *Colour Rendering Index* (CRI). References ---------- :cite:`Ohno2008a` Examples -------- >>> from colour import ILLUMINANT_SDS >>> sd = ILLUMINANT_SDS['FL2'] >>> colour_rendering_index(sd) # doctest: +ELLIPSIS 64.2337241... """ cmfs = STANDARD_OBSERVER_CMFS['CIE 1931 2 Degree Standard Observer'].copy( ).trim(DEFAULT_SPECTRAL_SHAPE) shape = cmfs.shape sd_test = sd_test.copy().align(shape) tcs_sds = {sd.name: sd.copy().align(shape) for sd in TCS_SDS.values()} with domain_range_scale('1'): XYZ = sd_to_XYZ(sd_test, cmfs) uv = UCS_to_uv(XYZ_to_UCS(XYZ)) CCT, _D_uv = uv_to_CCT_Robertson1968(uv) if CCT < 5000: sd_reference = sd_blackbody(CCT, shape) else: xy = CCT_to_xy_CIE_D(CCT) sd_reference = sd_CIE_illuminant_D_series(xy) sd_reference.align(shape) test_tcs_colorimetry_data = tcs_colorimetry_data( sd_test, sd_reference, tcs_sds, cmfs, chromatic_adaptation=True) reference_tcs_colorimetry_data = tcs_colorimetry_data( sd_reference, sd_reference, tcs_sds, cmfs) Q_as = colour_rendering_indexes(test_tcs_colorimetry_data, reference_tcs_colorimetry_data) Q_a = np.average( [v.Q_a for k, v in Q_as.items() if k in (1, 2, 3, 4, 5, 6, 7, 8)]) if additional_data: return CRI_Specification( sd_test.name, Q_a, Q_as, (test_tcs_colorimetry_data, reference_tcs_colorimetry_data)) else: return Q_a
def tcs_colorimetry_data(sd_t, sd_r, sds_tcs, cmfs, chromatic_adaptation=False): """ Returns the *test colour samples* colorimetry data. Parameters ---------- sd_t : SpectralDistribution Test spectral distribution. sd_r : SpectralDistribution Reference spectral distribution. sds_tcs : dict *Test colour samples* spectral distributions. cmfs : XYZ_ColourMatchingFunctions Standard observer colour matching functions. chromatic_adaptation : bool, optional Perform chromatic adaptation. Returns ------- list *Test colour samples* colorimetry data. """ XYZ_t = sd_to_XYZ(sd_t, cmfs) uv_t = UCS_to_uv(XYZ_to_UCS(XYZ_t)) u_t, v_t = uv_t[0], uv_t[1] XYZ_r = sd_to_XYZ(sd_r, cmfs) uv_r = UCS_to_uv(XYZ_to_UCS(XYZ_r)) u_r, v_r = uv_r[0], uv_r[1] tcs_data = [] for _key, value in sorted(TCS_INDEXES_TO_NAMES.items()): sd_tcs = sds_tcs[value] XYZ_tcs = sd_to_XYZ(sd_tcs, cmfs, sd_t) xyY_tcs = XYZ_to_xyY(XYZ_tcs) uv_tcs = UCS_to_uv(XYZ_to_UCS(XYZ_tcs)) u_tcs, v_tcs = uv_tcs[0], uv_tcs[1] if chromatic_adaptation: def c(x, y): """ Computes the :math:`c` term. """ return (4 - x - 10 * y) / y def d(x, y): """ Computes the :math:`d` term. """ return (1.708 * y + 0.404 - 1.481 * x) / y c_t, d_t = c(u_t, v_t), d(u_t, v_t) c_r, d_r = c(u_r, v_r), d(u_r, v_r) tcs_c, tcs_d = c(u_tcs, v_tcs), d(u_tcs, v_tcs) u_tcs = ( (10.872 + 0.404 * c_r / c_t * tcs_c - 4 * d_r / d_t * tcs_d) / (16.518 + 1.481 * c_r / c_t * tcs_c - d_r / d_t * tcs_d)) v_tcs = (5.52 / (16.518 + 1.481 * c_r / c_t * tcs_c - d_r / d_t * tcs_d)) W_tcs = 25 * spow(xyY_tcs[-1], 1 / 3) - 17 U_tcs = 13 * W_tcs * (u_tcs - u_r) V_tcs = 13 * W_tcs * (v_tcs - v_r) tcs_data.append( TCS_ColorimetryData(sd_tcs.name, XYZ_tcs, uv_tcs, np.array([U_tcs, V_tcs, W_tcs]))) return tcs_data def colour_rendering_indexes(test_data, reference_data): """ Returns the *test colour samples* rendering indexes :math:`Q_a`. Parameters ---------- test_data : list Test data. reference_data : list Reference data. Returns ------- dict *Test colour samples* *Colour Rendering Index* (CRI). """ Q_as = {} for i, _ in enumerate(test_data): Q_as[i + 1] = TCS_ColourQualityScaleData( test_data[i].name, 100 - 4.6 * euclidean_distance(reference_data[i].UVW, test_data[i].UVW)) return Q_as