def test_domain_range_scale_CIECAM02_to_XYZ(self):
"""
Tests :func:`colour.appearance.cam16.CIECAM02_to_XYZ` definition domain
and range scale support.
"""
XYZ_i = np.array([19.01, 20.00, 21.78])
XYZ_w = np.array([95.05, 100.00, 108.88])
L_A = 318.31
Y_b = 20.0
surround = VIEWING_CONDITIONS_CIECAM02['Average']
specification = XYZ_to_CIECAM02(XYZ_i, XYZ_w, L_A, Y_b, surround)
XYZ = CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround)
d_r = (
('reference', 1, 1, 1),
(1,
np.array([
1 / 100, 1 / 100, 1 / 360, 1 / 100, 1 / 100, 1 / 100, 1 / 360
]), 0.01, 0.01),
(100, np.array([1, 1, 100 / 360, 1, 1, 1, 100 / 360]), 1, 1),
)
for scale, factor_a, factor_b, factor_c in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(CIECAM02_to_XYZ(
specification[:-1] * factor_a, XYZ_w * factor_b, L_A, Y_b,
surround),
XYZ * factor_c,
decimal=7)
def test_domain_range_scale_CIECAM02_to_XYZ(self):
"""
Test :func:`colour.appearance.ciecam02.CIECAM02_to_XYZ` definition
domain and range scale support.
"""
XYZ_i = np.array([19.01, 20.00, 21.78])
XYZ_w = np.array([95.05, 100.00, 108.88])
L_A = 318.31
Y_b = 20
surround = VIEWING_CONDITIONS_CIECAM02["Average"]
specification = XYZ_to_CIECAM02(XYZ_i, XYZ_w, L_A, Y_b, surround)
XYZ = CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround)
d_r = (
("reference", 1, 1),
(
"1",
np.array([
1 / 100,
1 / 100,
1 / 360,
1 / 100,
1 / 100,
1 / 100,
1 / 400,
np.nan,
]),
0.01,
),
(
"100",
np.array([1, 1, 100 / 360, 1, 1, 1, 100 / 400, np.nan]),
1,
),
)
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
CIECAM02_to_XYZ(
specification * factor_a,
XYZ_w * factor_b,
L_A,
Y_b,
surround,
),
XYZ * factor_b,
decimal=7,
)
def _XYZ_from_data(self, data, correlates):
"""
Returns the *CIE XYZ* tristimulus values from given *CIECAM02* colour
appearance model input data.
Parameters
----------
data : list
Fixture data.
correlates : array_like
Correlates used to build the input *CIECAM02* colour appearance
model specification.
Returns
-------
array_like
*CIE XYZ* tristimulus values
"""
XYZ_w = tstack([data['X_w'], data['Y_w'], data['Z_w']])
i, j, k = correlates
specification = as_namedtuple({
i: data[i],
j: data[j],
k: data[k]
}, CAM_Specification_CIECAM02)
XYZ = CIECAM02_to_XYZ(
specification, XYZ_w, data['L_A'], data['Y_b'],
InductionFactors_CIECAM02(data['F'], data['c'], data['N_c']))
return XYZ
def get_output_specification_from_data(self, data):
"""
Returns the *CIECAM02* colour appearance model output specification
from given data.
Parameters
----------
data : list
Fixture data.
Returns
-------
CIECAM02_Specification
*CIECAM02* colour appearance model specification.
"""
XYZ_w = np.array([data['X_w'], data['Y_w'], data['Z_w']])
specification = CIECAM02_to_XYZ(data['J'], data['C'], data['h'],
XYZ_w,
data['L_A'],
data['Y_b'],
CIECAM02_InductionFactors(data['F'],
data['c'],
data['N_c']))
return specification
def test_n_dimensional_CIECAM02_to_XYZ(self):
"""
Test :func:`colour.appearance.ciecam02.CIECAM02_to_XYZ` definition
n-dimensional support.
"""
XYZ = np.array([19.01, 20.00, 21.78])
XYZ_w = np.array([95.05, 100.00, 108.88])
L_A = 318.31
Y_b = 20
surround = VIEWING_CONDITIONS_CIECAM02["Average"]
specification = XYZ_to_CIECAM02(XYZ, XYZ_w, L_A, Y_b, surround)
XYZ = CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround)
specification = CAM_Specification_CIECAM02(
*np.transpose(np.tile(tsplit(specification), (6, 1))).tolist())
XYZ = np.tile(XYZ, (6, 1))
np.testing.assert_almost_equal(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
XYZ,
decimal=7,
)
XYZ_w = np.tile(XYZ_w, (6, 1))
np.testing.assert_almost_equal(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
XYZ,
decimal=7,
)
specification = CAM_Specification_CIECAM02(
*tsplit(np.reshape(specification, (2, 3, 8))).tolist())
XYZ_w = np.reshape(XYZ_w, (2, 3, 3))
XYZ = np.reshape(XYZ, (2, 3, 3))
np.testing.assert_almost_equal(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
XYZ,
decimal=7,
)
def test_nan_CIECAM02_to_XYZ(self):
"""
Tests :func:`colour.appearance.ciecam02.CIECAM02_to_XYZ` 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:
J = case[0]
C = case[0]
h = case[0]
XYZ_w = np.array(case)
L_A = case[0]
Y_b = case[0]
surround = CIECAM02_InductionFactors(case[0], case[0], case[0])
CIECAM02_to_XYZ(J, C, h, XYZ_w, L_A, Y_b, surround)
def test_raise_exception_CIECAM02_to_XYZ(self):
"""
Tests :func:`colour.appearance.cam16.CIECAM02_to_XYZ` definition raised
exception.
"""
try:
CIECAM02_to_XYZ(
CAM_Specification_CIECAM02(
41.731091132513917,
None,
219.04843265831178,
),
np.array([95.05, 100.00, 108.88]),
318.31,
20.0,
VIEWING_CONDITIONS_CIECAM02['Average'],
)
except ValueError:
pass
def UCS_Luo2006_to_XYZ(Jpapbp: ArrayLike, coefficients: ArrayLike,
**kwargs: Any) -> NDArray:
"""
Convert from one of the *Luo et al. (2006)* *CAM02-LCD*, *CAM02-SCD*, or
*CAM02-UCS* colourspaces :math:`J'a'b'` array to *CIE XYZ* tristimulus
values.
Parameters
----------
Jpapbp
*Luo et al. (2006)* *CAM02-LCD*, *CAM02-SCD*, or *CAM02-UCS*
colourspaces :math:`J'a'b'` array.
coefficients
Coefficients of one of the *Luo et al. (2006)* *CAM02-LCD*,
*CAM02-SCD*, or *CAM02-UCS* colourspaces.
Other Parameters
----------------
kwargs
{:func:`colour.CIECAM02_to_XYZ`},
See the documentation of the previously listed definition. The default
viewing conditions are that of *IEC 61966-2-1:1999*, i.e. *sRGB* 64 Lux
ambient illumination, 80 :math:`cd/m^2`, adapting field luminance about
20% of a white object in the scene.
Returns
-------
:class:`numpy.ndarray`
*CIE XYZ* tristimulus values.
Warnings
--------
The ``XYZ_w`` parameter for :func:`colour.XYZ_to_CAM16` definition must be
given in the same domain-range scale than the ``XYZ`` parameter.
Notes
-----
+------------+------------------------+------------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+============+========================+==================+
| ``Jpapbp`` | ``Jp`` : [0, 100] | ``Jp`` : [0, 1] |
| | | |
| | ``ap`` : [-100, 100] | ``ap`` : [-1, 1] |
| | | |
| | ``bp`` : [-100, 100] | ``bp`` : [-1, 1] |
+------------+------------------------+------------------+
+------------+------------------------+------------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+============+========================+==================+
| ``XYZ`` | [0, 1] | [0, 1] |
+------------+------------------------+------------------+
Examples
--------
>>> Jpapbp = np.array([46.61386154, 39.35760236, 15.96730435])
>>> UCS_Luo2006_to_XYZ(
... Jpapbp, COEFFICIENTS_UCS_LUO2006['CAM02-LCD'])
... # doctest: +ELLIPSIS
array([ 0.2065400..., 0.1219722..., 0.0513695...])
"""
from colour.appearance import (
CAM_KWARGS_CIECAM02_sRGB,
CAM_Specification_CIECAM02,
CIECAM02_to_XYZ,
)
domain_range_reference = get_domain_range_scale() == "reference"
settings = CAM_KWARGS_CIECAM02_sRGB.copy()
settings.update(**kwargs)
XYZ_w = kwargs.get("XYZ_w")
if XYZ_w is not None and domain_range_reference:
settings["XYZ_w"] = XYZ_w * 100
J, M, h = tsplit(UCS_Luo2006_to_JMh_CIECAM02(Jpapbp, coefficients))
specification = CAM_Specification_CIECAM02(J=J, M=M, h=h)
XYZ = CIECAM02_to_XYZ(specification, **settings)
if domain_range_reference:
XYZ /= 100
return XYZ
def test_CIECAM02_to_XYZ(self):
"""Test :func:`colour.appearance.ciecam02.CIECAM02_to_XYZ` definition."""
specification = CAM_Specification_CIECAM02(41.73, 0.1, 219, 2.36,
195.37, 0.11, 278.1)
XYZ_w = np.array([95.05, 100.00, 108.88])
L_A = 318.31
Y_b = 20
surround = InductionFactors_CIECAM02(1, 0.69, 1)
np.testing.assert_allclose(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
np.array([19.01, 20.00, 21.78]),
rtol=0.01,
atol=0.01,
)
specification = CAM_Specification_CIECAM02(65.96, 48.57, 19.6, 52.25,
152.67, 41.67, 399.6,
np.nan)
L_A = 31.83
np.testing.assert_allclose(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
np.array([57.06, 43.06, 31.96]),
rtol=0.01,
atol=0.01,
)
specification = CAM_Specification_CIECAM02(21.79, 46.94, 177.1, 58.79,
141.17, 48.8, 220.4, np.nan)
XYZ_w = np.array([109.85, 100.00, 35.58])
L_A = 318.31
np.testing.assert_allclose(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
np.array([3.53, 6.56, 2.14]),
rtol=0.01,
atol=0.01,
)
specification = CAM_Specification_CIECAM02(42.53, 51.92, 248.9, 60.22,
122.83, 44.54, 305.8,
np.nan)
L_A = 31.83
np.testing.assert_allclose(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
np.array([19.01, 20.00, 21.78]),
rtol=0.01,
atol=0.01,
)
specification = CAM_Specification_CIECAM02(
21.72630603341673,
411.5190338631848,
349.12875710099053,
227.15081998415593,
57.657243286322725,
297.49693233026602,
375.5788601911363,
np.nan,
)
XYZ_w = np.array([95.05, 100, 108.88])
L_A = 4.074366543152521
np.testing.assert_allclose(
CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b, surround),
np.array([61.45276998, 7.00421901, 82.24067384]),
rtol=0.01,
atol=0.01,
)
