def test_nan_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition nan support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=3))
for case in cases:
XYZ_1 = np.array(case)
xy_o1 = np.array(case[0:2])
xy_o2 = np.array(case[0:2])
Y_o = case[0]
E_o1 = case[0]
E_o2 = case[0]
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)
def test_nan_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition nan support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=3))
for case in cases:
XYZ_1 = np.array(case)
xy_o1 = np.array(case[0:2])
xy_o2 = np.array(case[0:2])
Y_o = case[0]
E_o1 = case[0]
E_o2 = case[0]
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)
def corresponding_chromaticities_prediction_CIE1994(experiment=1):
"""
Returns the corresponding chromaticities prediction for CIE 1994
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_CIE1994(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.2133909..., 0.4939794...)),
((0.449, 0.511), (0.4450345..., 0.5120939...)),
((0.263, 0.505), (0.2693262..., 0.5083212...)),
((0.322, 0.545), (0.3308593..., 0.5443940...)),
((0.316, 0.537), (0.3225195..., 0.5377826...)),
((0.265, 0.553), (0.2709737..., 0.5513666...)),
((0.221, 0.538), (0.2280786..., 0.5351592...)),
((0.135, 0.532), (0.1439436..., 0.5303576...)),
((0.145, 0.472), (0.1500743..., 0.4842895...)),
((0.163, 0.331), (0.1559955..., 0.3772379...)),
((0.176, 0.431), (0.1806318..., 0.4518475...)),
((0.244, 0.349), (0.2454445..., 0.4018004...))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
xy_o1 = Luv_uv_to_xy(illuminants.uvp_t)
xy_o2 = Luv_uv_to_xy(illuminants.uvp_m)
# :math:`Y_o` is set to an arbitrary value in domain [18, 100].
Y_o = 18
E_o1 = E_o2 = 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_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)
def test_n_dimensional_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition n-dimensional arrays support.
"""
XYZ_1 = np.array([28.00, 21.26, 5.27])
xy_o1 = np.array([0.4476, 0.4074])
xy_o2 = np.array([0.3127, 0.3290])
Y_o = 20
E_o1 = 1000
E_o2 = 1000
XYZ_2 = np.array([24.03379521, 21.15621214, 17.64301199])
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
XYZ_1 = np.tile(XYZ_1, (6, 1))
XYZ_2 = np.tile(XYZ_2, (6, 1))
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
xy_o1 = np.tile(xy_o1, (6, 1))
xy_o2 = np.tile(xy_o2, (6, 1))
Y_o = np.tile(Y_o, 6)
E_o1 = np.tile(E_o1, 6)
E_o2 = np.tile(E_o2, 6)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
XYZ_1 = np.reshape(XYZ_1, (2, 3, 3))
xy_o1 = np.reshape(xy_o1, (2, 3, 2))
xy_o2 = np.reshape(xy_o2, (2, 3, 2))
Y_o = np.reshape(Y_o, (2, 3))
E_o1 = np.reshape(E_o1, (2, 3))
E_o2 = np.reshape(E_o2, (2, 3))
XYZ_2 = np.reshape(XYZ_2, (2, 3, 3))
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
def test_n_dimensional_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition n-dimensional arrays support.
"""
XYZ_1 = np.array([28.00, 21.26, 5.27])
xy_o1 = np.array([0.44760, 0.40740])
xy_o2 = np.array([0.31270, 0.32900])
Y_o = 20
E_o1 = 1000
E_o2 = 1000
XYZ_2 = np.array([24.03379521, 21.15621214, 17.64301199])
np.testing.assert_almost_equal(chromatic_adaptation_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
XYZ_1 = np.tile(XYZ_1, (6, 1))
XYZ_2 = np.tile(XYZ_2, (6, 1))
np.testing.assert_almost_equal(chromatic_adaptation_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
xy_o1 = np.tile(xy_o1, (6, 1))
xy_o2 = np.tile(xy_o2, (6, 1))
Y_o = np.tile(Y_o, 6)
E_o1 = np.tile(E_o1, 6)
E_o2 = np.tile(E_o2, 6)
np.testing.assert_almost_equal(chromatic_adaptation_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
XYZ_1 = np.reshape(XYZ_1, (2, 3, 3))
xy_o1 = np.reshape(xy_o1, (2, 3, 2))
xy_o2 = np.reshape(xy_o2, (2, 3, 2))
Y_o = np.reshape(Y_o, (2, 3))
E_o1 = np.reshape(E_o1, (2, 3))
E_o2 = np.reshape(E_o2, (2, 3))
XYZ_2 = np.reshape(XYZ_2, (2, 3, 3))
np.testing.assert_almost_equal(chromatic_adaptation_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2),
XYZ_2,
decimal=7)
def corresponding_chromaticities_prediction_CIE1994(experiment=1):
"""
Returns the corresponding chromaticities prediction for CIE 1994
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_CIE1994(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.2133909..., 0.4939794...)),
((0.449, 0.511), (0.4450345..., 0.5120939...)),
((0.263, 0.505), (0.2693262..., 0.5083212...)),
((0.322, 0.545), (0.3308593..., 0.5443940...)),
((0.316, 0.537), (0.3225195..., 0.5377826...)),
((0.265, 0.553), (0.2709737..., 0.5513666...)),
((0.221, 0.538), (0.2280786..., 0.5351592...)),
((0.135, 0.532), (0.1439436..., 0.5303576...)),
((0.145, 0.472), (0.1500743..., 0.4842895...)),
((0.163, 0.331), (0.1559955..., 0.3772379...)),
((0.176, 0.431), (0.1806318..., 0.4518475...)),
((0.244, 0.349), (0.2454445..., 0.4018004...))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
xy_o1 = Luv_uv_to_xy(illuminants.uvp_t)
xy_o2 = Luv_uv_to_xy(illuminants.uvp_m)
# :math:`Y_o` is set to an arbitrary value in domain [18, 100].
Y_o = 18
E_o1 = E_o2 = 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_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1,
E_o2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
prediction.append(
CorrespondingChromaticitiesPrediction(result.name, result.uvp_t,
result.uvp_m, uvp))
return tuple(prediction)
def test_chromatic_adaptation_CIE1994(self):
"""
Test :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition.
"""
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([28.00, 21.26, 5.27]),
xy_o1=np.array([0.44760, 0.40740]),
xy_o2=np.array([0.31270, 0.32900]),
Y_o=20,
E_o1=1000,
E_o2=1000,
),
np.array([24.03379521, 21.15621214, 17.64301199]),
decimal=7,
)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([21.77, 19.18, 16.73]),
xy_o1=np.array([0.31270, 0.32900]),
xy_o2=np.array([0.31270, 0.32900]),
Y_o=50,
E_o1=100,
E_o2=1000,
),
np.array([21.12891746, 19.42980532, 19.49577765]),
decimal=7,
)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([0.07818780, 0.06157201, 0.28099326]) * 100,
xy_o1=np.array([0.31270, 0.32900]),
xy_o2=np.array([0.37208, 0.37529]),
Y_o=20,
E_o1=100,
E_o2=1000,
),
np.array([9.14287406, 9.35843355, 15.95753504]),
decimal=7,
)
def test_domain_range_scale_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition domain and range scale support.
"""
XYZ_1 = np.array([28.00, 21.26, 5.27])
xy_o1 = np.array([0.44760, 0.40740])
xy_o2 = np.array([0.31270, 0.32900])
Y_o = 20
E_o1 = 1000
E_o2 = 1000
XYZ_2 = chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1,
E_o2)
d_r = (('reference', 1), (1, 0.01), (100, 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(chromatic_adaptation_CIE1994(
XYZ_1 * factor, xy_o1, xy_o2, Y_o * factor, E_o1, E_o2),
XYZ_2 * factor,
decimal=7)
def test_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition.
"""
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([28.00, 21.26, 5.27]),
xy_o1=np.array([0.4476, 0.4074]),
xy_o2=np.array([0.3127, 0.3290]),
Y_o=20,
E_o1=1000,
E_o2=1000),
np.array([24.03379521, 21.15621214, 17.64301199]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([21.77, 19.18, 16.73]),
xy_o1=np.array([0.3127, 0.3290]),
xy_o2=np.array([0.3127, 0.3290]),
Y_o=50,
E_o1=100,
E_o2=1000),
np.array([21.12891746, 19.42980532, 19.49577765]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([0.47097710, 0.34950000, 0.11301649]) * 100,
xy_o1=np.array([0.3127, 0.3290]),
xy_o2=np.array([0.4476, 0.4074]),
Y_o=20,
E_o1=100,
E_o2=1000),
np.array([40.55293261, 28.95161939, 4.09480293]),
decimal=7)
def test_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition.
"""
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([28.00, 21.26, 5.27]),
xy_o1=np.array([0.44760, 0.40740]),
xy_o2=np.array([0.31270, 0.32900]),
Y_o=20,
E_o1=1000,
E_o2=1000),
np.array([24.03379521, 21.15621214, 17.64301199]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([21.77, 19.18, 16.73]),
xy_o1=np.array([0.31270, 0.32900]),
xy_o2=np.array([0.31270, 0.32900]),
Y_o=50,
E_o1=100,
E_o2=1000),
np.array([21.12891746, 19.42980532, 19.49577765]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([0.07818780, 0.06157201, 0.28099326]) * 100,
xy_o1=np.array([0.31270, 0.32900]),
xy_o2=np.array([0.37208, 0.37529]),
Y_o=20,
E_o1=100,
E_o2=1000),
np.array([9.14287406, 9.35843355, 15.95753504]),
decimal=7)
def test_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition.
"""
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([28.00, 21.26, 5.27]),
xy_o1=np.array([0.4476, 0.4074]),
xy_o2=np.array([0.3127, 0.3290]),
Y_o=20,
E_o1=1000,
E_o2=1000),
np.array([24.03379521, 21.15621214, 17.64301199]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([21.77, 19.18, 16.73]),
xy_o1=np.array([0.3127, 0.3290]),
xy_o2=np.array([0.3127, 0.3290]),
Y_o=50,
E_o1=100,
E_o2=1000),
np.array([21.12891746, 19.42980532, 19.49577765]),
decimal=7)
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(
XYZ_1=np.array([0.47097710, 0.34950000, 0.11301649]) * 100,
xy_o1=np.array([0.3127, 0.3290]),
xy_o2=np.array([0.4476, 0.4074]),
Y_o=20,
E_o1=100,
E_o2=1000),
np.array([40.55293261, 28.95161939, 4.09480293]),
decimal=7)
def test_domain_range_scale_chromatic_adaptation_CIE1994(self):
"""
Tests :func:`colour.adaptation.cie1994.chromatic_adaptation_CIE1994`
definition domain and range scale support.
"""
XYZ_1 = np.array([28.00, 21.26, 5.27])
xy_o1 = np.array([0.44760, 0.40740])
xy_o2 = np.array([0.31270, 0.32900])
Y_o = 20
E_o1 = 1000
E_o2 = 1000
XYZ_2 = chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1,
E_o2)
d_r = (('reference', 1), (1, 0.01), (100, 1))
for scale, factor in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
chromatic_adaptation_CIE1994(XYZ_1 * factor, xy_o1, xy_o2,
Y_o * factor, E_o1, E_o2),
XYZ_2 * factor,
decimal=7)
def corresponding_chromaticities_prediction_CIE1994(experiment=1):
"""
Returns the corresponding chromaticities prediction for *CIE 1994*
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:`CIETC1-321994b`
Examples
--------
>>> from pprint import pprint
>>> pr = corresponding_chromaticities_prediction_CIE1994(2)
>>> pr = [(p.uv_m, p.uv_p) for p in pr]
>>> pprint(pr) # doctest: +ELLIPSIS
[(array([ 0.207, 0.486]), array([ 0.2273130..., 0.5267609...])),
(array([ 0.449, 0.511]), array([ 0.4612181..., 0.5191849...])),
(array([ 0.263, 0.505]), array([ 0.2872404..., 0.5306938...])),
(array([ 0.322, 0.545]), array([ 0.3489822..., 0.5454398...])),
(array([ 0.316, 0.537]), array([ 0.3371612..., 0.5421567...])),
(array([ 0.265, 0.553]), array([ 0.2889416..., 0.5534074...])),
(array([ 0.221, 0.538]), array([ 0.2412195..., 0.5464301...])),
(array([ 0.135, 0.532]), array([ 0.1530344..., 0.5488239...])),
(array([ 0.145, 0.472]), array([ 0.1568709..., 0.5258835...])),
(array([ 0.163, 0.331]), array([ 0.1499762..., 0.4401747...])),
(array([ 0.176, 0.431]), array([ 0.1876711..., 0.5039627...])),
(array([ 0.244, 0.349]), array([ 0.2560012..., 0.4546263...]))]
"""
experiment_results = (convert_experiment_results_Breneman1987(experiment)
if is_numeric(experiment) else experiment)
with domain_range_scale(1):
XYZ_t, XYZ_r = experiment_results.XYZ_t, experiment_results.XYZ_r
xy_o1, xy_o2 = XYZ_to_xy([XYZ_t, XYZ_r])
uv_t = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_ct, xy_o1), xy_o1)
uv_m = Luv_to_uv(XYZ_to_Luv(experiment_results.XYZ_cr, xy_o2), xy_o2)
Y_r = experiment_results.B_r
E_o1, E_o2 = experiment_results.Y_t, experiment_results.Y_r
XYZ_1 = experiment_results.XYZ_ct
XYZ_2 = chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_r, E_o1,
E_o2)
uv_p = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
return tuple([
CorrespondingChromaticitiesPrediction(experiment_results.name,
uv_t[i], uv_m[i], uv_p[i])
for i in range(len(uv_t))
])
def corresponding_chromaticities_prediction_CIE1994(experiment=1, **kwargs):
"""
Returns the corresponding chromaticities prediction for CIE 1994
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_CIE1994(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.21339093279517196, 0.49397945742298016)),
((0.449, 0.511), (0.4450345313098153, 0.5120939085633327)),
((0.263, 0.505), (0.26932620724691858, 0.50832124608390727)),
((0.322, 0.545), (0.33085939370840811, 0.54439408389253441)),
((0.316, 0.537), (0.3225195584183046, 0.53778269440789594)),
((0.265, 0.553), (0.2709737181087471, 0.5513666373694861)),
((0.221, 0.538), (0.22807869730753863, 0.53515923458385406)),
((0.135, 0.532), (0.14394366662060523, 0.53035769204585748)),
((0.145, 0.472), (0.15007438031976222, 0.48428958620888679)),
((0.163, 0.331), (0.15599555781959967, 0.37723798698131394)),
((0.176, 0.431), (0.18063180902005657, 0.45184759430042898)),
((0.244, 0.349), (0.24544456656434688, 0.40180048388092021))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
xy_o1 = Luv_uv_to_xy(illuminants.uvp_t)
xy_o2 = Luv_uv_to_xy(illuminants.uvp_m)
# :math:`Y_o` is set to an arbitrary value in domain [18, 100].
Y_o = 18
E_o1 = E_o2 = 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_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)
def corresponding_chromaticities_prediction_CIE1994(experiment=1, **kwargs):
"""
Returns the corresponding chromaticities prediction for CIE 1994
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_CIE1994(2)
>>> pr = [(p.uvp_m, p.uvp_p) for p in pr]
>>> pprint(pr) # doctest: +SKIP
[((0.207, 0.486), (0.21339093279517196, 0.49397945742298016)),
((0.449, 0.511), (0.4450345313098153, 0.5120939085633327)),
((0.263, 0.505), (0.26932620724691858, 0.50832124608390727)),
((0.322, 0.545), (0.33085939370840811, 0.54439408389253441)),
((0.316, 0.537), (0.3225195584183046, 0.53778269440789594)),
((0.265, 0.553), (0.2709737181087471, 0.5513666373694861)),
((0.221, 0.538), (0.22807869730753863, 0.53515923458385406)),
((0.135, 0.532), (0.14394366662060523, 0.53035769204585748)),
((0.145, 0.472), (0.15007438031976222, 0.48428958620888679)),
((0.163, 0.331), (0.15599555781959967, 0.37723798698131394)),
((0.176, 0.431), (0.18063180902005657, 0.45184759430042898)),
((0.244, 0.349), (0.24544456656434688, 0.40180048388092021))]
"""
experiment_results = list(BRENEMAN_EXPERIMENTS.get(experiment))
illuminants = experiment_results.pop(0)
xy_o1 = Luv_uv_to_xy(illuminants.uvp_t)
xy_o2 = Luv_uv_to_xy(illuminants.uvp_m)
# :math:`Y_o` is set to an arbitrary value in domain [18, 100].
Y_o = 18
E_o1 = E_o2 = 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_CIE1994(
XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2)
uvp = Luv_to_uv(XYZ_to_Luv(XYZ_2, xy_o2), xy_o2)
prediction.append(CorrespondingChromaticitiesPrediction(
result.name,
result.uvp_t,
result.uvp_m,
uvp))
return tuple(prediction)