def test_as_namedtuple(self):
"""
Tests :func:`colour.utilities.array.as_namedtuple` definition.
"""
NamedTuple = namedtuple('NamedTuple', 'a b c')
a_a = np.ones(3)
a_b = np.ones(3) + 1
a_c = np.ones(3) + 2
named_tuple = NamedTuple(a_a, a_b, a_c)
self.assertEqual(named_tuple, as_namedtuple(named_tuple, NamedTuple))
self.assertEqual(
named_tuple,
as_namedtuple({
'a': a_a,
'b': a_b,
'c': a_c
}, NamedTuple))
self.assertEqual(named_tuple, as_namedtuple([a_a, a_b, a_c],
NamedTuple))
a_r = np.array(
[tuple(a) for a in np.transpose((a_a, a_b, a_c)).tolist()],
dtype=[(str('a'), str('f8')),
(str('b'), str('f8')),
(str('c'), str('f8'))]) # yapf: disable
np.testing.assert_array_equal(
np.array(named_tuple), np.array(as_namedtuple(a_r, NamedTuple)))
def test_as_namedtuple(self):
"""
Tests :func:`colour.utilities.array.as_namedtuple` definition.
"""
NamedTuple = namedtuple('NamedTuple', 'a b c')
a_a = np.ones(3)
a_b = np.ones(3) + 1
a_c = np.ones(3) + 2
named_tuple = NamedTuple(a_a, a_b, a_c)
self.assertEqual(named_tuple, as_namedtuple(named_tuple, NamedTuple))
self.assertEqual(
named_tuple,
as_namedtuple({
'a': a_a,
'b': a_b,
'c': a_c
}, NamedTuple))
self.assertEqual(named_tuple, as_namedtuple([a_a, a_b, a_c],
NamedTuple))
a_r = np.array(
[tuple(a) for a in np.transpose((a_a, a_b, a_c)).tolist()],
dtype=[(str('a'), str('f8')),
(str('b'), str('f8')),
(str('c'), str('f8'))]) # yapf: disable
np.testing.assert_array_equal(np.array(named_tuple),
np.array(as_namedtuple(a_r, NamedTuple)))
def _XYZ_from_data(self, data, correlates):
"""
Returns the *CIE XYZ* tristimulus values from given *CAM16* colour
appearance model input data.
Parameters
----------
data : list
Fixture data.
correlates : array_like
Correlates used to build the input *CAM16* 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
CAM16_specification = as_namedtuple(
{
i: data[i],
j: data[j],
k: data[k]
}, CAM16_Specification)
XYZ = CAM16_to_XYZ(
CAM16_specification, XYZ_w, data['L_A'], data['Y_b'],
CAM16_InductionFactors(data['F'], data['c'], data['N_c']))
return XYZ
def _XYZ_from_data(self, data, correlates):
"""
Returns the *CIE XYZ* tristimulus values from given *CAM16* colour
appearance model input data.
Parameters
----------
data : list
Fixture data.
correlates : array_like
Correlates used to build the input *CAM16* 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
CAM16_specification = as_namedtuple({
i: data[i],
j: data[j],
k: data[k]
}, CAM16_Specification)
XYZ = CAM16_to_XYZ(
CAM16_specification, XYZ_w, data['L_A'], data['Y_b'],
CAM16_InductionFactors(data['F'], data['c'], data['N_c']))
return XYZ
def CIECAM02_to_XYZ(CIECAM02_specification,
XYZ_w,
L_A,
Y_b,
surround=CIECAM02_VIEWING_CONDITIONS['Average'],
discount_illuminant=False):
"""
Converts *CIECAM02* specification to *CIE XYZ* tristimulus values.
This is the *reverse* implementation.
Parameters
----------
CIECAM02_specification : CIECAM02_Specification
*CIECAM02* colour appearance model specification. Correlate of
*Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of
*colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be
specified, e.g. :math:`JCh` or :math:`JMh`.
XYZ_w : array_like
*CIE XYZ* tristimulus values of reference white.
L_A : numeric or array_like
Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken
to be 20% of the luminance of a white object in the scene).
Y_b : numeric or array_like
Relative luminance of background :math:`Y_b` in :math:`cd/m^2`.
surround : CIECAM02_InductionFactors, optional
Surround viewing conditions.
discount_illuminant : bool, optional
Discount the illuminant.
Returns
-------
XYZ : ndarray
*CIE XYZ* tristimulus values.
Raises
------
ValueError
If neither *C* or *M* correlates have been defined in the
``CIECAM02_specification`` argument.
Warning
-------
The output range of that definition is non standard!
Notes
-----
+------------------------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+==============================+=======================+===============+
| ``CIECAM02_specification.h`` | [0, 360] | [0, 1] |
+------------------------------+-----------------------+---------------+
| ``CIECAM02_specification.H`` | [0, 360] | [0, 1] |
+------------------------------+-----------------------+---------------+
| ``XYZ_w`` | [0, 100] | [0, 1] |
+------------------------------+-----------------------+---------------+
+------------------------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+==============================+=======================+===============+
| ``XYZ`` | [0, 100] | [0, 1] |
+------------------------------+-----------------------+---------------+
- ``CIECAM02_specification`` can also be passed as a compatible argument
to :func:`colour.utilities.as_namedtuple` definition.
References
----------
:cite:`Fairchild2004c`, :cite:`Luo2013`, :cite:`Moroneya`,
:cite:`Wikipedia2007a`
Examples
--------
>>> specification = CIECAM02_Specification(J=41.731091132513917,
... C=0.104707757171031,
... h=219.048432658311780)
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS
array([ 19.01..., 20... , 21.78...])
"""
J, C, h, _s, _Q, M, _H, _HC = as_namedtuple(CIECAM02_specification,
CIECAM02_Specification)
L_A = as_float_array(L_A)
h = to_domain_degrees(h)
XYZ_w = to_domain_100(XYZ_w)
_X_w, Y_w, _Z_w = tsplit(XYZ_w)
n, F_L, N_bb, N_cb, z = tsplit(
viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
if C is None and M is not None:
C = M / spow(F_L, 0.25)
elif C is None:
raise ValueError('Either "C" or "M" correlate must be defined in '
'the "CIECAM02_specification" argument!')
# Converting *CIE XYZ* tristimulus values to *CMCCAT2000* transform
# sharpened *RGB* values.
RGB_w = dot_vector(CAT02_CAT, XYZ_w)
# Computing degree of adaptation :math:`D`.
D = (degree_of_adaptation(surround.F, L_A)
if not discount_illuminant else np.ones(L_A.shape))
# Computing full chromatic adaptation.
RGB_wc = full_chromatic_adaptation_forward(RGB_w, RGB_w, Y_w, D)
# Converting to *Hunt-Pointer-Estevez* colourspace.
RGB_pw = RGB_to_rgb(RGB_wc)
# Applying post-adaptation non linear response compression.
RGB_aw = post_adaptation_non_linear_response_compression_forward(
RGB_pw, F_L)
# Computing achromatic response for the whitepoint.
A_w = achromatic_response_forward(RGB_aw, N_bb)
# Computing temporary magnitude quantity :math:`t`.
t = temporary_magnitude_quantity_reverse(C, J, n)
# Computing eccentricity factor *e_t*.
e_t = eccentricity_factor(h)
# Computing achromatic response :math:`A` for the stimulus.
A = achromatic_response_reverse(A_w, J, surround.c, z)
# Computing *P_1* to *P_3*.
P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb)
_P_1, P_2, _P_3 = tsplit(P_n)
# Computing opponent colour dimensions :math:`a` and :math:`b`.
a, b = tsplit(opponent_colour_dimensions_reverse(P_n, h))
# Computing post-adaptation non linear response compression matrix.
RGB_a = post_adaptation_non_linear_response_compression_matrix(P_2, a, b)
# Applying reverse post-adaptation non linear response compression.
RGB_p = post_adaptation_non_linear_response_compression_reverse(RGB_a, F_L)
# Converting to *Hunt-Pointer-Estevez* colourspace.
RGB_c = rgb_to_RGB(RGB_p)
# Applying reverse full chromatic adaptation.
RGB = full_chromatic_adaptation_reverse(RGB_c, RGB_w, Y_w, D)
# Converting *CMCCAT2000* transform sharpened *RGB* values to *CIE XYZ*
# tristimulus values.
XYZ = dot_vector(CAT02_INVERSE_CAT, RGB)
return from_range_100(XYZ)
def CAM16_to_XYZ(CAM16_specification,
XYZ_w,
L_A,
Y_b,
surround=CAM16_VIEWING_CONDITIONS['Average'],
discount_illuminant=False):
"""
Converts from *CAM16* specification to *CIE XYZ* tristimulus values.
This is the *inverse* implementation.
Parameters
----------
CAM16_specification : CAM16_Specification
*CAM16* colour appearance model specification. Correlate of
*Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of
*colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be
specified, e.g. :math:`JCh` or :math:`JMh`.
XYZ_w : array_like
*CIE XYZ* tristimulus values of reference white.
L_A : numeric or array_like
Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken
to be 20% of the luminance of a white object in the scene).
Y_b : numeric or array_like
Relative luminance of background :math:`Y_b` in :math:`cd/m^2`.
surround : CAM16_InductionFactors, optional
Surround viewing conditions.
discount_illuminant : bool, optional
Discount the illuminant.
Returns
-------
XYZ : ndarray
*CIE XYZ* tristimulus values.
Raises
------
ValueError
If neither *C* or *M* correlates have been defined in the
``CAM16_specification`` argument.
Notes
-----
+---------------------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+===========================+=======================+===============+
| ``CAM16_specification.J`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.C`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.h`` | [0, 360] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.s`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.Q`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.M`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.H`` | [0, 360] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``XYZ_w`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
+---------------------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+===========================+=======================+===============+
| ``XYZ`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
- ``CAM16_specification`` can also be passed as a compatible argument
to :func:`colour.utilities.as_namedtuple` definition.
References
----------
:cite:`Li2017`
Examples
--------
>>> specification = CAM16_Specification(J=41.731207905126638,
... C=0.103355738709070,
... h=217.067959767393010)
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> CAM16_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS
array([ 19.01..., 20... , 21.78...])
"""
J, C, h, _s, _Q, M, _H, _HC = as_namedtuple(CAM16_specification,
CAM16_Specification)
J = to_domain_100(J)
C = to_domain_100(C) if C is not None else C
h = to_domain_degrees(h)
M = to_domain_100(M) if M is not None else M
L_A = as_float_array(L_A)
XYZ_w = to_domain_100(XYZ_w)
_X_w, Y_w, _Z_w = tsplit(XYZ_w)
# Step 0
# Converting *CIE XYZ* tristimulus values to sharpened *RGB* values.
RGB_w = dot_vector(M_16, XYZ_w)
# Computing degree of adaptation :math:`D`.
D = (np.clip(degree_of_adaptation(surround.F, L_A), 0, 1)
if not discount_illuminant else np.ones(L_A.shape))
n, F_L, N_bb, N_cb, z = tsplit(
viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
D_RGB = (D[..., np.newaxis] * Y_w[..., np.newaxis] / RGB_w + 1 -
D[..., np.newaxis])
RGB_wc = D_RGB * RGB_w
# Applying forward post-adaptation non linear response compression.
RGB_aw = post_adaptation_non_linear_response_compression_forward(
RGB_wc, F_L)
# Computing achromatic responses for the whitepoint.
A_w = achromatic_response_forward(RGB_aw, N_bb)
# Step 1
if C is None and M is not None:
C = M / spow(F_L, 0.25)
elif C is None:
raise ValueError('Either "C" or "M" correlate must be defined in '
'the "CAM16_specification" argument!')
# Step 2
# Computing temporary magnitude quantity :math:`t`.
t = temporary_magnitude_quantity_inverse(C, J, n)
# Computing eccentricity factor *e_t*.
e_t = eccentricity_factor(h)
# Computing achromatic response :math:`A` for the stimulus.
A = achromatic_response_inverse(A_w, J, surround.c, z)
# Computing *P_1* to *P_3*.
P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb)
_P_1, P_2, _P_3 = tsplit(P_n)
# Step 3
# Computing opponent colour dimensions :math:`a` and :math:`b`.
a, b = tsplit(opponent_colour_dimensions_inverse(P_n, h))
# Step 4
# Computing post-adaptation non linear response compression matrix.
RGB_a = post_adaptation_non_linear_response_compression_matrix(P_2, a, b)
# Step 5
# Applying inverse post-adaptation non linear response compression.
RGB_c = post_adaptation_non_linear_response_compression_inverse(RGB_a, F_L)
# Step 6
RGB = RGB_c / D_RGB
# Step 7
XYZ = dot_vector(M_16_INVERSE, RGB)
return from_range_100(XYZ)
def CAM16_to_XYZ(CAM16_specification,
XYZ_w,
L_A,
Y_b,
surround=CAM16_VIEWING_CONDITIONS['Average'],
discount_illuminant=False):
"""
Converts *CAM16* specification to *CIE XYZ* tristimulus values.
This is the *reverse* implementation.
Parameters
----------
CAM16_specification : CAM16_Specification
*CAM16* colour appearance model specification. Correlate of
*Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of
*colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be
specified, e.g. :math:`JCh` or :math:`JMh`.
XYZ_w : array_like
*CIE XYZ* tristimulus values of reference white.
L_A : numeric or array_like
Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken
to be 20% of the luminance of a white object in the scene).
Y_b : numeric or array_like
Relative luminance of background :math:`Y_b` in :math:`cd/m^2`.
surround : CAM16_InductionFactors, optional
Surround viewing conditions.
discount_illuminant : bool, optional
Discount the illuminant.
Returns
-------
XYZ : ndarray
*CIE XYZ* tristimulus values.
Raises
------
ValueError
If neither *C* or *M* correlates have been defined in the
``CAM16_specification`` argument.
Notes
-----
+---------------------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+===========================+=======================+===============+
| ``CAM16_specification.h`` | [0, 360] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``CAM16_specification.H`` | [0, 360] | [0, 1] |
+---------------------------+-----------------------+---------------+
| ``XYZ_w`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
+---------------------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+===========================+=======================+===============+
| ``XYZ`` | [0, 100] | [0, 1] |
+---------------------------+-----------------------+---------------+
- ``CAM16_specification`` can also be passed as a compatible argument
to :func:`colour.utilities.as_namedtuple` definition.
References
----------
:cite:`Li2017`
Examples
--------
>>> specification = CAM16_Specification(J=41.731207905126638,
... C=0.103355738709070,
... h=217.067959767393010)
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> CAM16_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS
array([ 19.01..., 20... , 21.78...])
"""
J, C, h, _s, _Q, M, _H, _HC = as_namedtuple(CAM16_specification,
CAM16_Specification)
L_A = as_float_array(L_A)
h = to_domain_degrees(h)
XYZ_w = to_domain_100(XYZ_w)
_X_w, Y_w, _Z_w = tsplit(XYZ_w)
# Step 0
# Converting *CIE XYZ* tristimulus values to sharpened *RGB* values.
RGB_w = dot_vector(M_16, XYZ_w)
# Computing degree of adaptation :math:`D`.
D = (np.clip(degree_of_adaptation(surround.F, L_A), 0, 1)
if not discount_illuminant else np.ones(L_A.shape))
n, F_L, N_bb, N_cb, z = tsplit(
viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
D_RGB = (D[..., np.newaxis] * Y_w[..., np.newaxis] / RGB_w + 1 -
D[..., np.newaxis])
RGB_wc = D_RGB * RGB_w
# Applying forward post-adaptation non linear response compression.
RGB_aw = post_adaptation_non_linear_response_compression_forward(
RGB_wc, F_L)
# Computing achromatic responses for the whitepoint.
A_w = achromatic_response_forward(RGB_aw, N_bb)
# Step 1
if C is None and M is not None:
C = M / spow(F_L, 0.25)
elif C is None:
raise ValueError('Either "C" or "M" correlate must be defined in '
'the "CAM16_specification" argument!')
# Step 2
# Computing temporary magnitude quantity :math:`t`.
t = temporary_magnitude_quantity_reverse(C, J, n)
# Computing eccentricity factor *e_t*.
e_t = eccentricity_factor(h)
# Computing achromatic response :math:`A` for the stimulus.
A = achromatic_response_reverse(A_w, J, surround.c, z)
# Computing *P_1* to *P_3*.
P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb)
_P_1, P_2, _P_3 = tsplit(P_n)
# Step 3
# Computing opponent colour dimensions :math:`a` and :math:`b`.
a, b = tsplit(opponent_colour_dimensions_reverse(P_n, h))
# Step 4
# Computing post-adaptation non linear response compression matrix.
RGB_a = post_adaptation_non_linear_response_compression_matrix(P_2, a, b)
# Step 5
# Applying reverse post-adaptation non linear response compression.
RGB_c = post_adaptation_non_linear_response_compression_reverse(RGB_a, F_L)
# Step 6
RGB = RGB_c / D_RGB
# Step 7
XYZ = dot_vector(M_16_INVERSE, RGB)
return from_range_100(XYZ)
def CAM16_to_XYZ(CAM16_specification,
XYZ_w,
L_A,
Y_b,
surround=CAM16_VIEWING_CONDITIONS['Average'],
discount_illuminant=False):
"""
Converts *CAM16* specification to *CIE XYZ* tristimulus values.
This is the *reverse* implementation.
Parameters
----------
CAM16_specification : CAM16_Specification
*CAM16* colour appearance model specification. Correlate of
*Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of
*colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be
specified, e.g. :math:`JCh` or :math:`JMh`.
XYZ_w : array_like
*CIE XYZ* tristimulus values of reference white.
L_A : numeric or array_like
Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken
to be 20% of the luminance of a white object in the scene).
Y_b : numeric or array_like
Relative luminance of background :math:`Y_b` in :math:`cd/m^2`.
surround : CAM16_InductionFactors, optional
Surround viewing conditions.
discount_illuminant : bool, optional
Discount the illuminant.
Returns
-------
XYZ : ndarray
*CIE XYZ* tristimulus values.
Raises
------
ValueError
If neither *C* or *M* correlates have been defined in the
``CAM16_specification`` argument.
Warning
-------
The output range of that definition is non standard!
Notes
-----
- ``CAM16_specification`` can also be passed as a compatible argument
:func:`colour.utilities.as_namedtuple` definition.
- Input *CIE XYZ_w* tristimulus values are in domain [0, 100].
- Output *CIE XYZ* tristimulus values are in range [0, 100].
References
----------
- :cite:`Li2017`
Examples
--------
>>> specification = CAM16_Specification(J=41.718025051415616,
... C=11.941344635245843,
... h=210.38389558131118)
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> CAM16_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS
array([ 19.01..., 20... , 21.78...])
"""
J, C, h, _s, _Q, M, _H, _HC = as_namedtuple(CAM16_specification,
CAM16_Specification)
_X_w, Y_w, _Zw = tsplit(XYZ_w)
# Step 0
# Converting *CIE XYZ* tristimulus values to sharpened *RGB* values.
RGB_w = dot_vector(M_16, XYZ_w)
# Computing degree of adaptation :math:`D`.
D = (np.clip(degree_of_adaptation(surround.F, L_A), 0, 1)
if not discount_illuminant else 1)
n, F_L, N_bb, N_cb, z = tsplit(
viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
D_RGB = D[..., np.newaxis] * XYZ_w / RGB_w + 1 - D[..., np.newaxis]
RGB_wc = D_RGB * RGB_w
# Applying forward post-adaptation non linear response compression.
RGB_aw = post_adaptation_non_linear_response_compression_forward(
RGB_wc, F_L)
# Computing achromatic responses for the whitepoint.
A_w = achromatic_response_forward(RGB_aw, N_bb)
# Step 1
if C is None and M is not None:
C = M / F_L**0.25
elif C is None:
raise ValueError('Either "C" or "M" correlate must be defined in '
'the "CAM16_specification" argument!')
# Step 2
# Computing temporary magnitude quantity :math:`t`.
t = temporary_magnitude_quantity_reverse(C, J, n)
# Computing eccentricity factor *e_t*.
e_t = eccentricity_factor(h)
# Computing achromatic response :math:`A` for the stimulus.
A = achromatic_response_reverse(A_w, J, surround.c, z)
# Computing *P_1* to *P_3*.
P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb)
_P_1, P_2, _P_3 = tsplit(P_n)
# Step 3
# Computing opponent colour dimensions :math:`a` and :math:`b`.
a, b = tsplit(opponent_colour_dimensions_reverse(P_n, h))
# Step 4
# Computing post-adaptation non linear response compression matrix.
RGB_a = post_adaptation_non_linear_response_compression_matrix(P_2, a, b)
# Step 5
# Applying reverse post-adaptation non linear response compression.
RGB_c = post_adaptation_non_linear_response_compression_reverse(RGB_a, F_L)
# Step 6
RGB = RGB_c / D_RGB
# Step 7
XYZ = dot_vector(M_16_INVERSE, RGB)
return XYZ
def CIECAM02_to_XYZ(CIECAM02_specification,
XYZ_w,
L_A,
Y_b,
surround=CIECAM02_VIEWING_CONDITIONS['Average'],
discount_illuminant=False):
"""
Converts *CIECAM02* specification to *CIE XYZ* tristimulus values.
This is the *reverse* implementation.
Parameters
----------
CIECAM02_specification : CIECAM02_Specification
*CIECAM02* colour appearance model specification. Correlate of
*Lightness* :math:`J`, correlate of *chroma* :math:`C` or correlate of
*colourfulness* :math:`M` and *hue* angle :math:`h` in degrees must be
specified, e.g. :math:`JCh` or :math:`JMh`.
XYZ_w : array_like
*CIE XYZ* tristimulus values of reference white.
L_A : numeric or array_like
Adapting field *luminance* :math:`L_A` in :math:`cd/m^2`, (often taken
to be 20% of the luminance of a white object in the scene).
Y_b : numeric or array_like
Relative luminance of background :math:`Y_b` in :math:`cd/m^2`.
surround : CIECAM02_InductionFactors, optional
Surround viewing conditions.
discount_illuminant : bool, optional
Discount the illuminant.
Returns
-------
XYZ : ndarray
*CIE XYZ* tristimulus values.
Raises
------
ValueError
If neither *C* or *M* correlates have been defined in the
``CIECAM02_specification`` argument.
Warning
-------
The output range of that definition is non standard!
Notes
-----
+------------------------------+-----------------------+---------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+==============================+=======================+===============+
| ``CIECAM02_specification.h`` | [0, 360] | [0, 1] |
+------------------------------+-----------------------+---------------+
| ``CIECAM02_specification.H`` | [0, 360] | [0, 1] |
+------------------------------+-----------------------+---------------+
| ``XYZ_w`` | [0, 100] | [0, 1] |
+------------------------------+-----------------------+---------------+
+------------------------------+-----------------------+---------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+==============================+=======================+===============+
| ``XYZ`` | [0, 100] | [0, 1] |
+------------------------------+-----------------------+---------------+
- ``CIECAM02_specification`` can also be passed as a compatible argument
to :func:`colour.utilities.as_namedtuple` definition.
References
----------
:cite:`Fairchild2004c`, :cite:`Luo2013`, :cite:`Moroneya`,
:cite:`Wikipedia2007a`
Examples
--------
>>> specification = CIECAM02_Specification(J=41.731091132513917,
... C=0.104707757171031,
... h=219.048432658311780)
>>> XYZ_w = np.array([95.05, 100.00, 108.88])
>>> L_A = 318.31
>>> Y_b = 20.0
>>> CIECAM02_to_XYZ(specification, XYZ_w, L_A, Y_b) # doctest: +ELLIPSIS
array([ 19.01..., 20... , 21.78...])
"""
J, C, h, _s, _Q, M, _H, _HC = as_namedtuple(CIECAM02_specification,
CIECAM02_Specification)
L_A = as_float_array(L_A)
h = to_domain_degrees(h)
XYZ_w = to_domain_100(XYZ_w)
_X_w, Y_w, _Z_w = tsplit(XYZ_w)
n, F_L, N_bb, N_cb, z = tsplit(
viewing_condition_dependent_parameters(Y_b, Y_w, L_A))
if C is None and M is not None:
C = M / spow(F_L, 0.25)
elif C is None:
raise ValueError('Either "C" or "M" correlate must be defined in '
'the "CIECAM02_specification" argument!')
# Converting *CIE XYZ* tristimulus values to *CMCCAT2000* transform
# sharpened *RGB* values.
RGB_w = dot_vector(CAT02_CAT, XYZ_w)
# Computing degree of adaptation :math:`D`.
D = (degree_of_adaptation(surround.F, L_A)
if not discount_illuminant else np.ones(L_A.shape))
# Computing full chromatic adaptation.
RGB_wc = full_chromatic_adaptation_forward(RGB_w, RGB_w, Y_w, D)
# Converting to *Hunt-Pointer-Estevez* colourspace.
RGB_pw = RGB_to_rgb(RGB_wc)
# Applying post-adaptation non linear response compression.
RGB_aw = post_adaptation_non_linear_response_compression_forward(
RGB_pw, F_L)
# Computing achromatic response for the whitepoint.
A_w = achromatic_response_forward(RGB_aw, N_bb)
# Computing temporary magnitude quantity :math:`t`.
t = temporary_magnitude_quantity_reverse(C, J, n)
# Computing eccentricity factor *e_t*.
e_t = eccentricity_factor(h)
# Computing achromatic response :math:`A` for the stimulus.
A = achromatic_response_reverse(A_w, J, surround.c, z)
# Computing *P_1* to *P_3*.
P_n = P(surround.N_c, N_cb, e_t, t, A, N_bb)
_P_1, P_2, _P_3 = tsplit(P_n)
# Computing opponent colour dimensions :math:`a` and :math:`b`.
a, b = tsplit(opponent_colour_dimensions_reverse(P_n, h))
# Computing post-adaptation non linear response compression matrix.
RGB_a = post_adaptation_non_linear_response_compression_matrix(P_2, a, b)
# Applying reverse post-adaptation non linear response compression.
RGB_p = post_adaptation_non_linear_response_compression_reverse(RGB_a, F_L)
# Converting to *Hunt-Pointer-Estevez* colourspace.
RGB_c = rgb_to_RGB(RGB_p)
# Applying reverse full chromatic adaptation.
RGB = full_chromatic_adaptation_reverse(RGB_c, RGB_w, Y_w, D)
# Converting *CMCCAT2000* transform sharpened *RGB* values to *CIE XYZ*
# tristimulus values.
XYZ = dot_vector(CAT02_INVERSE_CAT, RGB)
return from_range_100(XYZ)
