def colour_quality_scale(spd_test, T, additional_data=False):
cmfs = STANDARD_OBSERVERS_CMFS.get('CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
CCT, _D_uv = T
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_vs_colorimetry_data = vs_colorimetry_data(spd_test,
spd_reference,
VS_SPDS,
cmfs,
chromatic_adaptation=True)
reference_vs_colorimetry_data = vs_colorimetry_data(
spd_reference, spd_reference, VS_SPDS, cmfs)
XYZ_r = spectral_to_XYZ(spd_reference, cmfs)
XYZ_r /= XYZ_r[1]
CCT_f = CCT_factor(reference_vs_colorimetry_data, XYZ_r)
Q_as = colour_quality_scales(test_vs_colorimetry_data,
reference_vs_colorimetry_data, CCT_f)
D_E_RMS = delta_E_RMS(Q_as, 'D_E_ab')
D_Ep_RMS = delta_E_RMS(Q_as, 'D_Ep_ab')
Q_a = scale_conversion(D_Ep_RMS, CCT_f)
Q_f = scale_conversion(D_E_RMS, CCT_f, 2.928)
p_delta_C = np.average([
sample_data.D_C_ab if sample_data.D_C_ab > 0 else 0
for sample_data in Q_as.values()
])
Q_p = 100 - 3.6 * (D_Ep_RMS - p_delta_C)
G_t = gamut_area(
[vs_CQS_data.Lab for vs_CQS_data in test_vs_colorimetry_data])
G_r = gamut_area(
[vs_CQS_data.Lab for vs_CQS_data in reference_vs_colorimetry_data])
Q_g = G_t / D65_GAMUT_AREA * 100
Q_d = G_t / G_r * CCT_f * 100
if additional_data:
return CQS_Specification(
spd_test.name, Q_a, Q_f, Q_p, Q_g, Q_d, Q_as,
(test_vs_colorimetry_data, reference_vs_colorimetry_data))
else:
return Q_a
def test_D_illuminant_relative_spd(self):
"""
Tests :func:`colour.colorimetry.illuminants.D_illuminant_relative_spd`
definition.
"""
spd = D_illuminant_relative_spd(np.array([0.32168, 0.33767]))
np.testing.assert_almost_equal(sorted(spd.data.values()),
sorted(D60_SPD_DATA.values()),
decimal=7)
def test_D_illuminant_relative_spd(self):
"""
Tests :func:`colour.colorimetry.illuminants.D_illuminant_relative_spd`
definition.
"""
spd_r = SpectralPowerDistribution(D60_SPD_DATA)
spd_t = D_illuminant_relative_spd(np.array([0.32168, 0.33767]))
np.testing.assert_array_equal(spd_r.domain, spd_t.domain)
np.testing.assert_almost_equal(spd_r.values, spd_t.values, decimal=7)
def colour_rendering_index(spd_test, additional_data=False):
"""
Returns the *colour rendering index* :math:`Q_a` of given spectral power
distribution.
Parameters
----------
spd_test : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or CRI_Specification
Colour rendering index.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_rendering_index(spd) # doctest: +ELLIPSIS
64.1507331...
"""
cmfs = STANDARD_OBSERVERS_CMFS.get('CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
spd_test = spd_test.clone().align(shape)
tcs_spds = {}
for index, tcs_spd in TCS_SPDS.items():
tcs_spds[index] = tcs_spd.clone().align(shape)
XYZ = spectral_to_XYZ(spd_test, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, _D_uv = uv_to_CCT_Robertson1968(uv)
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_tcs_colorimetry_data = tcs_colorimetry_data(
spd_test,
spd_reference,
tcs_spds,
cmfs,
chromatic_adaptation=True)
reference_tcs_colorimetry_data = tcs_colorimetry_data(
spd_reference,
spd_reference,
tcs_spds,
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(spd_test.name,
Q_a,
Q_as,
(test_tcs_colorimetry_data,
reference_tcs_colorimetry_data))
else:
return Q_a
def colour_rendering_index(spd_test, additional_data=False):
"""
Returns the *Colour Rendering Index* (CRI) :math:`Q_a` of given spectral
power distribution.
Parameters
----------
spd_test : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or CRI_Specification
*Colour Rendering Index* (CRI).
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS['F2']
>>> colour_rendering_index(spd) # doctest: +ELLIPSIS
64.1515202...
"""
cmfs = STANDARD_OBSERVERS_CMFS[
'CIE 1931 2 Degree Standard Observer'].clone().trim_wavelengths(
ASTME30815_PRACTISE_SHAPE)
shape = cmfs.shape
spd_test = spd_test.clone().align(shape)
tcs_spds = {
spd.name: spd.clone().align(shape)
for spd in TCS_SPDS.values()
}
XYZ = spectral_to_XYZ(spd_test, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, _D_uv = uv_to_CCT_Robertson1968(uv)
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_tcs_colorimetry_data = tcs_colorimetry_data(
spd_test, spd_reference, tcs_spds, cmfs, chromatic_adaptation=True)
reference_tcs_colorimetry_data = tcs_colorimetry_data(
spd_reference, spd_reference, tcs_spds, 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(spd_test.name, Q_a, Q_as,
(test_tcs_colorimetry_data,
reference_tcs_colorimetry_data))
else:
return Q_a
def colour_quality_scale(spd_test, additional_data=False):
"""
Returns the *colour quality scale* of given spectral power distribution.
Parameters
----------
spd_test : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or CQS_Specification
Color quality scale.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_quality_scale(spd) # doctest: +ELLIPSIS
64.6781117...
"""
cmfs = STANDARD_OBSERVERS_CMFS.get(
'CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
XYZ = spectral_to_XYZ(spd_test, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, _D_uv = uv_to_CCT_Ohno2013(uv)
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_vs_colorimetry_data = vs_colorimetry_data(
spd_test,
spd_reference,
VS_SPDS,
cmfs,
chromatic_adaptation=True)
reference_vs_colorimetry_data = vs_colorimetry_data(
spd_reference,
spd_reference,
VS_SPDS,
cmfs)
XYZ_r = spectral_to_XYZ(spd_reference, cmfs)
XYZ_r /= XYZ_r[1]
CCT_f = CCT_factor(reference_vs_colorimetry_data, XYZ_r)
Q_as = colour_quality_scales(
test_vs_colorimetry_data, reference_vs_colorimetry_data, CCT_f)
D_E_RMS = delta_E_RMS(Q_as, 'D_E_ab')
D_Ep_RMS = delta_E_RMS(Q_as, 'D_Ep_ab')
Q_a = scale_conversion(D_Ep_RMS, CCT_f)
Q_f = scale_conversion(D_E_RMS, CCT_f, 2.928)
p_delta_C = np.average(
[sample_data.D_C_ab if sample_data.D_C_ab > 0 else 0
for sample_data in
Q_as.values()])
Q_p = 100 - 3.6 * (D_Ep_RMS - p_delta_C)
G_t = gamut_area([vs_CQS_data.Lab
for vs_CQS_data in test_vs_colorimetry_data])
G_r = gamut_area([vs_CQS_data.Lab
for vs_CQS_data in reference_vs_colorimetry_data])
Q_g = G_t / D65_GAMUT_AREA * 100
Q_d = G_t / G_r * CCT_f * 100
if additional_data:
return CQS_Specification(spd_test.name,
Q_a,
Q_f,
Q_p,
Q_g,
Q_d,
Q_as,
(test_vs_colorimetry_data,
reference_vs_colorimetry_data))
else:
return Q_a
def colour_quality_scale(spd_test, additional_data=False):
"""
Returns the *Colour Quality Scale* (CQS) of given spectral power
distribution.
Parameters
----------
spd_test : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or CQS_Specification
Color quality scale.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS['F2']
>>> colour_quality_scale(spd) # doctest: +ELLIPSIS
64.6864169...
"""
cmfs = STANDARD_OBSERVERS_CMFS[
'CIE 1931 2 Degree Standard Observer'].clone().trim_wavelengths(
ASTME30815_PRACTISE_SHAPE)
shape = cmfs.shape
spd_test = spd_test.clone().align(shape)
vs_spds = {spd.name: spd.clone().align(shape) for spd in VS_SPDS.values()}
XYZ = spectral_to_XYZ(spd_test, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, _D_uv = uv_to_CCT_Ohno2013(uv)
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_vs_colorimetry_data = vs_colorimetry_data(spd_test,
spd_reference,
vs_spds,
cmfs,
chromatic_adaptation=True)
reference_vs_colorimetry_data = vs_colorimetry_data(
spd_reference, spd_reference, vs_spds, cmfs)
XYZ_r = spectral_to_XYZ(spd_reference, cmfs)
XYZ_r /= XYZ_r[1]
CCT_f = CCT_factor(reference_vs_colorimetry_data, XYZ_r)
Q_as = colour_quality_scales(test_vs_colorimetry_data,
reference_vs_colorimetry_data, CCT_f)
D_E_RMS = delta_E_RMS(Q_as, 'D_E_ab')
D_Ep_RMS = delta_E_RMS(Q_as, 'D_Ep_ab')
Q_a = scale_conversion(D_Ep_RMS, CCT_f)
Q_f = scale_conversion(D_E_RMS, CCT_f, 2.928)
p_delta_C = np.average(
[sample_data.D_C_ab if sample_data.D_C_ab > 0 else 0
for sample_data in Q_as.values()]) # yapf: disable
Q_p = 100 - 3.6 * (D_Ep_RMS - p_delta_C)
G_t = gamut_area(
[vs_CQS_data.Lab for vs_CQS_data in test_vs_colorimetry_data])
G_r = gamut_area(
[vs_CQS_data.Lab for vs_CQS_data in reference_vs_colorimetry_data])
Q_g = G_t / D65_GAMUT_AREA * 100
Q_d = G_t / G_r * CCT_f * 100
if additional_data:
return CQS_Specification(
spd_test.name, Q_a, Q_f, Q_p, Q_g, Q_d, Q_as,
(test_vs_colorimetry_data, reference_vs_colorimetry_data))
else:
return Q_a
def colour_rendering_index(test_spd, additional_data=False):
"""
Returns the *colour rendering index* of given spectral power distribution.
Parameters
----------
test_spd : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or (numeric, dict)
Colour rendering index, Tsc data.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_rendering_index(spd) # doctest: +ELLIPSIS
64.1507331...
"""
cmfs = STANDARD_OBSERVERS_CMFS.get('CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
test_spd = test_spd.clone().align(shape)
tcs_spds = {}
for index, tcs_spd in sorted(TCS_SPDS.items()):
tcs_spds[index] = tcs_spd.clone().align(shape)
XYZ = spectral_to_XYZ(test_spd, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, Duv = uv_to_CCT_robertson1968(uv)
if CCT < 5000:
reference_spd = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_illuminant_D(CCT)
reference_spd = D_illuminant_relative_spd(xy)
reference_spd.align(shape)
test_tcs_colorimetry_data = _tcs_colorimetry_data(
test_spd,
reference_spd,
tcs_spds,
cmfs,
chromatic_adaptation=True)
reference_tcs_colorimetry_data = _tcs_colorimetry_data(
reference_spd,
reference_spd,
tcs_spds, cmfs)
colour_rendering_indexes = _colour_rendering_indexes(
test_tcs_colorimetry_data, reference_tcs_colorimetry_data)
colour_rendering_index = np.average(
[v for k, v in colour_rendering_indexes.items()
if k in (1, 2, 3, 4, 5, 6, 7, 8)])
if additional_data:
return (colour_rendering_index,
colour_rendering_indexes,
[test_tcs_colorimetry_data, reference_tcs_colorimetry_data])
else:
return colour_rendering_index
def colour_rendering_index(test_spd, additional_data=False):
"""
Returns the *colour rendering index* of given spectral power distribution.
Parameters
----------
test_spd : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or (numeric, dict)
Colour rendering index, Tsc data.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_rendering_index(spd) # doctest: +ELLIPSIS
64.1507331...
"""
cmfs = STANDARD_OBSERVERS_CMFS.get('CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
test_spd = test_spd.clone().align(shape)
tcs_spds = {}
for index, tcs_spd in sorted(TCS_SPDS.items()):
tcs_spds[index] = tcs_spd.clone().align(shape)
XYZ = spectral_to_XYZ(test_spd, cmfs)
uv = UCS_to_uv(XYZ_to_UCS(XYZ))
CCT, Duv = uv_to_CCT_robertson1968(uv)
if CCT < 5000:
reference_spd = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_illuminant_D(CCT)
reference_spd = D_illuminant_relative_spd(xy)
reference_spd.align(shape)
test_tcs_colorimetry_data = _tcs_colorimetry_data(
test_spd, reference_spd, tcs_spds, cmfs, chromatic_adaptation=True)
reference_tcs_colorimetry_data = _tcs_colorimetry_data(
reference_spd, reference_spd, tcs_spds, cmfs)
colour_rendering_indexes = _colour_rendering_indexes(
test_tcs_colorimetry_data, reference_tcs_colorimetry_data)
colour_rendering_index = np.average([
v for k, v in colour_rendering_indexes.items()
if k in (1, 2, 3, 4, 5, 6, 7, 8)
])
if additional_data:
return (colour_rendering_index, colour_rendering_indexes,
[test_tcs_colorimetry_data, reference_tcs_colorimetry_data])
else:
return colour_rendering_index
def colour_rendering_index(spd_test,T, additional_data=False):
"""
Returns the *colour rendering index* :math:`Q_a` of given spectral power
distribution.
Parameters
----------
spd_test : SpectralPowerDistribution
Test spectral power distribution.
additional_data : bool, optional
Output additional data.
Returns
-------
numeric or CRI_Specification
Colour rendering index.
Examples
--------
>>> from colour import ILLUMINANTS_RELATIVE_SPDS
>>> spd = ILLUMINANTS_RELATIVE_SPDS.get('F2')
>>> colour_rendering_index(spd) # doctest: +ELLIPSIS
64.1495478...
"""
cmfs = STANDARD_OBSERVERS_CMFS.get('CIE 1931 2 Degree Standard Observer')
shape = cmfs.shape
CCT, _D_uv = T[0],T[1]
if CCT < 5000:
spd_reference = blackbody_spd(CCT, shape)
else:
xy = CCT_to_xy_CIE_D(CCT)
spd_reference = D_illuminant_relative_spd(xy)
spd_reference.align(shape)
test_tcs_colorimetry_data = tcs_colorimetry_data(
spd_test,
spd_reference,
TCS_SPDS,
cmfs,
chromatic_adaptation=True)
reference_tcs_colorimetry_data = tcs_colorimetry_data(
spd_reference,
spd_reference,
TCS_SPDS,
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(spd_test.name,
Q_a,
Q_as,
(test_tcs_colorimetry_data,
reference_tcs_colorimetry_data))
else:
return Q_a
