def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1, **kwargs):
"""
Returns the corresponding chromaticities prediction for CMCCAT2000
chromatic adaptation model.
Parameters
----------
experiment : integer, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
Breneman (1987) experiment number.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
tuple
Corresponding chromaticities prediction.
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.20832101929657834, 0.47271680534693694)),
((0.449, 0.511), (0.44592707020371486, 0.50777351504395707)),
((0.263, 0.505), (0.26402624712986333, 0.4955361681706304)),
((0.322, 0.545), (0.33168840090358015, 0.54315801981008516)),
((0.316, 0.537), (0.32226245779851387, 0.53576245377085929)),
((0.265, 0.553), (0.27107058097430181, 0.5501997842556422)),
((0.221, 0.538), (0.22618269421847523, 0.52947407170848704)),
((0.135, 0.532), (0.14396930475660724, 0.51909841743126817)),
((0.145, 0.472), (0.14948357434418671, 0.45567605010224305)),
((0.163, 0.331), (0.15631720730028753, 0.31641514460738623)),
((0.176, 0.431), (0.17631993066748047, 0.41275893424542082)),
((0.244, 0.349), (0.22876382018951744, 0.3499324084859976))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
XYZ_w = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_t)) * 100
XYZ_wr = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_m)) * 100
xy_wr = XYZ_to_xy(XYZ_wr)
L_A1 = L_A2 = BRENEMAN_EXPERIMENTS_PRIMARIES_CHROMATICITIES.get(
experiment).Y
prediction = []
for result in experiment_results:
XYZ_1 = xy_to_XYZ(Luv_uv_to_xy(result.uvp_t)) * 100
XYZ_2 = chromatic_adaptation_CMCCAT2000(
XYZ_1, XYZ_w, XYZ_wr, L_A1, L_A2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)
def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1, **kwargs):
"""
Returns the corresponding chromaticities prediction for CMCCAT2000
chromatic adaptation model.
Parameters
----------
experiment : integer, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
Breneman (1987) experiment number.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
tuple
Corresponding chromaticities prediction.
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.20832101929657834, 0.47271680534693694)),
((0.449, 0.511), (0.44592707020371486, 0.50777351504395707)),
((0.263, 0.505), (0.26402624712986333, 0.4955361681706304)),
((0.322, 0.545), (0.33168840090358015, 0.54315801981008516)),
((0.316, 0.537), (0.32226245779851387, 0.53576245377085929)),
((0.265, 0.553), (0.27107058097430181, 0.5501997842556422)),
((0.221, 0.538), (0.22618269421847523, 0.52947407170848704)),
((0.135, 0.532), (0.14396930475660724, 0.51909841743126817)),
((0.145, 0.472), (0.14948357434418671, 0.45567605010224305)),
((0.163, 0.331), (0.15631720730028753, 0.31641514460738623)),
((0.176, 0.431), (0.17631993066748047, 0.41275893424542082)),
((0.244, 0.349), (0.22876382018951744, 0.3499324084859976))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
XYZ_w = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_t)) * 100
XYZ_wr = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_m)) * 100
xy_wr = XYZ_to_xy(XYZ_wr)
L_A1 = L_A2 = BRENEMAN_EXPERIMENTS_PRIMARIES_CHROMATICITIES.get(
experiment).Y
prediction = []
for result in experiment_results:
XYZ_1 = xy_to_XYZ(Luv_uv_to_xy(result.uvp_t)) * 100
XYZ_2 = chromatic_adaptation_CMCCAT2000(
XYZ_1, XYZ_w, XYZ_wr, L_A1, L_A2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)
def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1):
"""
Returns the corresponding chromaticities prediction for CMCCAT2000
chromatic adaptation model.
Parameters
----------
experiment : integer, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
Breneman (1987) experiment number.
Returns
-------
tuple
Corresponding chromaticities prediction.
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.2083210..., 0.4727168...)),
((0.449, 0.511), (0.4459270..., 0.5077735...)),
((0.263, 0.505), (0.2640262..., 0.4955361...)),
((0.322, 0.545), (0.3316884..., 0.5431580...)),
((0.316, 0.537), (0.3222624..., 0.5357624...)),
((0.265, 0.553), (0.2710705..., 0.5501997...)),
((0.221, 0.538), (0.2261826..., 0.5294740...)),
((0.135, 0.532), (0.1439693..., 0.5190984...)),
((0.145, 0.472), (0.1494835..., 0.4556760...)),
((0.163, 0.331), (0.1563172..., 0.3164151...)),
((0.176, 0.431), (0.1763199..., 0.4127589...)),
((0.244, 0.349), (0.2287638..., 0.3499324...))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
XYZ_w = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_t)) * 100
XYZ_wr = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_m)) * 100
xy_wr = XYZ_to_xy(XYZ_wr)
L_A1 = L_A2 = BRENEMAN_EXPERIMENTS_PRIMARIES_CHROMATICITIES.get(
experiment).Y
prediction = []
for result in experiment_results:
XYZ_1 = xy_to_XYZ(Luv_uv_to_xy(result.uvp_t)) * 100
XYZ_2 = chromatic_adaptation_CMCCAT2000(
XYZ_1, XYZ_w, XYZ_wr, L_A1, L_A2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)
def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1):
"""
Returns the corresponding chromaticities prediction for CMCCAT2000
chromatic adaptation model.
Parameters
----------
experiment : integer, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
Breneman (1987) experiment number.
Returns
-------
tuple
Corresponding chromaticities prediction.
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.2083210..., 0.4727168...)),
((0.449, 0.511), (0.4459270..., 0.5077735...)),
((0.263, 0.505), (0.2640262..., 0.4955361...)),
((0.322, 0.545), (0.3316884..., 0.5431580...)),
((0.316, 0.537), (0.3222624..., 0.5357624...)),
((0.265, 0.553), (0.2710705..., 0.5501997...)),
((0.221, 0.538), (0.2261826..., 0.5294740...)),
((0.135, 0.532), (0.1439693..., 0.5190984...)),
((0.145, 0.472), (0.1494835..., 0.4556760...)),
((0.163, 0.331), (0.1563172..., 0.3164151...)),
((0.176, 0.431), (0.1763199..., 0.4127589...)),
((0.244, 0.349), (0.2287638..., 0.3499324...))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
XYZ_w = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_t)) * 100
XYZ_wr = xy_to_XYZ(Luv_uv_to_xy(illuminants.uvp_m)) * 100
xy_wr = XYZ_to_xy(XYZ_wr)
L_A1 = L_A2 = BRENEMAN_EXPERIMENTS_PRIMARIES_CHROMATICITIES.get(
experiment).Y
prediction = []
for result in experiment_results:
XYZ_1 = xy_to_XYZ(Luv_uv_to_xy(result.uvp_t)) * 100
XYZ_2 = chromatic_adaptation_CMCCAT2000(XYZ_1, XYZ_w, XYZ_wr, L_A1,
L_A2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
prediction.append(
CorrespondingChromaticitiesPrediction(result.name, result.uvp_t,
result.uvp_m, uvp))
return tuple(prediction)
def corresponding_chromaticities_prediction_CMCCAT2000(experiment=1):
"""
Returns the corresponding chromaticities prediction for *CMCCAT2000*
chromatic adaptation model.
Parameters
----------
experiment : integer or CorrespondingColourDataset, optional
{1, 2, 3, 4, 6, 8, 9, 11, 12}
*Breneman (1987)* experiment number or
:class:`colour.CorrespondingColourDataset` class instance.
Returns
-------
tuple
Corresponding chromaticities prediction.
References
----------
:cite:`Breneman1987b`, :cite:`Li2002a`, :cite:`Westland2012k`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CMCCAT2000(2)
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2083210..., 0.4727168...])),
(array([ 0.449, 0.511]), array([ 0.4459270..., 0.5077735...])),
(array([ 0.263, 0.505]), array([ 0.2640262..., 0.4955361...])),
(array([ 0.322, 0.545]), array([ 0.3316884..., 0.5431580...])),
(array([ 0.316, 0.537]), array([ 0.3222624..., 0.5357624...])),
(array([ 0.265, 0.553]), array([ 0.2710705..., 0.5501997...])),
(array([ 0.221, 0.538]), array([ 0.2261826..., 0.5294740...])),
(array([ 0.135, 0.532]), array([ 0.1439693..., 0.5190984...])),
(array([ 0.145, 0.472]), array([ 0.1494835..., 0.4556760...])),
(array([ 0.163, 0.331]), array([ 0.1563172..., 0.3164151...])),
(array([ 0.176, 0.431]), array([ 0.1763199..., 0.4127589...])),
(array([ 0.244, 0.349]), array([ 0.2287638..., 0.3499324...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_w, XYZ_wr = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_w, xy_wr = XYZ_to_xy([XYZ_w, XYZ_wr])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_w), xy_w)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_wr), xy_wr)
L_A1 = experiment_results.Y_t
L_A2 = experiment_results.Y_r
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_CMCCAT2000(XYZ_1, XYZ_w, XYZ_wr, L_A1,
L_A2)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_wr), xy_wr)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])