def test_n_dimensional_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition n-dimensions
support.
"""
xyY = np.array([0.26414772, 0.37770001, 1.])
xy = np.array([0.26414772236966133, 0.37770000704815188])
np.testing.assert_almost_equal(
xyY_to_xy(xyY),
xy,
decimal=7)
xyY = np.tile(xyY, (6, 1))
xy = np.tile(xy, (6, 1))
np.testing.assert_almost_equal(
xyY_to_xy(xyY),
xy,
decimal=7)
xyY = np.reshape(xyY, (2, 3, 3))
xy = np.reshape(xy, (2, 3, 2))
np.testing.assert_almost_equal(
xyY_to_xy(xyY),
xy,
decimal=7)
def test_xyY_to_xy(self):
"""Test :func:`colour.models.cie_xyy.xyY_to_xy` definition."""
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.54369557, 0.32107944, 0.12197225])),
np.array([0.54369557, 0.32107944]),
decimal=7,
)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.29777735, 0.48246446, 0.23042768])),
np.array([0.29777735, 0.48246446]),
decimal=7,
)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.18582823, 0.14633764, 0.06157201])),
np.array([0.18582823, 0.14633764]),
decimal=7,
)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.31270, 0.32900])),
np.array([0.31270000, 0.32900000]),
decimal=7,
)
def test_nan_xyY_to_xy(self):
"""Test :func:`colour.models.cie_xyy.xyY_to_xy` definition nan support."""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=2))
for case in cases:
xyY = np.array(case)
xyY_to_xy(xyY)
def test_nan_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition nan support.
"""
cases = [-1.0, 0.0, 1.0, -np.inf, np.inf, np.nan]
cases = set(permutations(cases * 3, r=2))
for case in cases:
xyY = np.array(case)
xyY_to_xy(xyY)
def test_domain_range_scale_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition domain and
range scale support.
"""
xyY = np.array([0.54369557, 0.32107944, 0.12197225])
xy = xyY_to_xy(xyY)
xyY = np.tile(xyY, (6, 1)).reshape(2, 3, 3)
xy = np.tile(xy, (6, 1)).reshape(2, 3, 2)
d_r = (('reference', 1, 1), (1, 1, 1), (100, np.array([1, 1, 100]), 1))
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
xyY_to_xy(xyY * factor_a), xy * factor_b, decimal=7)
def test_n_dimensional_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition n-dimensional
support.
"""
xyY = np.array([0.54369557, 0.32107944, 0.12197225])
xy = xyY_to_xy(xyY)
xyY = np.tile(xyY, (6, 1))
xy = np.tile(xy, (6, 1))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
xyY = np.reshape(xyY, (2, 3, 3))
xy = np.reshape(xy, (2, 3, 2))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
def test_domain_range_scale_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition domain and
range scale support.
"""
xyY = np.array([0.54369557, 0.32107944, 0.12197225])
xy = xyY_to_xy(xyY)
xyY = np.tile(xyY, (6, 1)).reshape(2, 3, 3)
xy = np.tile(xy, (6, 1)).reshape(2, 3, 2)
d_r = (('reference', 1, 1), (1, 1, 1), (100, np.array([1, 1, 100]), 1))
for scale, factor_a, factor_b in d_r:
with domain_range_scale(scale):
np.testing.assert_almost_equal(
xyY_to_xy(xyY * factor_a), xy * factor_b, decimal=7)
def test_n_dimensional_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition n-dimensional
support.
"""
xyY = np.array([0.54369557, 0.32107944, 0.12197225])
xy = xyY_to_xy(xyY)
xyY = np.tile(xyY, (6, 1))
xy = np.tile(xy, (6, 1))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
xyY = np.reshape(xyY, (2, 3, 3))
xy = np.reshape(xy, (2, 3, 2))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
def test_n_dimensional_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition n-dimensions
support.
"""
xyY = np.array([0.26414772, 0.37770001, 1.0])
xy = np.array([0.26414772236966133, 0.37770000704815188])
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
xyY = np.tile(xyY, (6, 1))
xy = np.tile(xy, (6, 1))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
xyY = np.reshape(xyY, (2, 3, 3))
xy = np.reshape(xy, (2, 3, 2))
np.testing.assert_almost_equal(xyY_to_xy(xyY), xy, decimal=7)
def test_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition.
"""
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.26414772, 0.37770001, 1.00000000])), np.array([0.26414772, 0.37770001]), decimal=7
)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.50453169, 0.37440000, 1.00000000])), np.array([0.50453169, 0.3744]), decimal=7
)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.47670437, 0.35790000, 1.00000000])), np.array([0.47670437, 0.3579]), decimal=7
)
np.testing.assert_almost_equal(xyY_to_xy(np.array([0.34567, 0.35850])), np.array([0.34567, 0.3585]), decimal=7)
def XYZ_to_UVW(
XYZ,
illuminant=ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D50']):
"""
Converts from *CIE XYZ* tristimulus values to *CIE 1964 U\*V\*W\**
colourspace.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE 1964 U\*V\*W\** colourspace array.
Warning
-------
The input domain and output range of that definition are non standard!
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *CIE 1964 U\*V\*W\** colourspace array is in range [0, 100].
References
----------
- :cite:`Wikipediacj`
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313]) * 100
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([-28.0579733..., -0.8819449..., 37.0041149...])
"""
xyY = XYZ_to_xyY(XYZ, xyY_to_xy(illuminant))
_x, _y, Y = tsplit(xyY)
u, v = tsplit(UCS_to_uv(XYZ_to_UCS(XYZ)))
u_0, v_0 = tsplit(UCS_to_uv(XYZ_to_UCS(xyY_to_XYZ(xy_to_xyY(illuminant)))))
W = 25 * Y**(1 / 3) - 17
U = 13 * W * (u - u_0)
V = 13 * W * (v - v_0)
UVW = tstack((U, V, W))
return UVW
def XYZ_to_UVW(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE 1964 U\*V\*W\**
colourspace.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE 1964 U\*V\*W\** colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *CIE UVW* colourspace array is in range [0, 100].
Warning
-------
The input / output domains of that definition are non standard!
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313]) * 100
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([-28.0579733..., -0.8819449..., 37.0041149...])
"""
xyY = XYZ_to_xyY(XYZ, xyY_to_xy(illuminant))
_x, _y, Y = tsplit(xyY)
u, v = tsplit(UCS_to_uv(XYZ_to_UCS(XYZ)))
u_0, v_0 = tsplit(
UCS_to_uv(XYZ_to_UCS(xyY_to_XYZ(xy_to_xyY(illuminant)))))
W = 25 * Y ** (1 / 3) - 17
U = 13 * W * (u - u_0)
V = 13 * W * (v - v_0)
UVW = tstack((U, V, W))
return UVW
def test_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition.
"""
np.testing.assert_almost_equal(xyY_to_xy(
np.array([0.26414772, 0.37770001, 1.00000000])),
np.array([0.26414772, 0.37770001]),
decimal=7)
np.testing.assert_almost_equal(xyY_to_xy(
np.array([0.50453169, 0.37440000, 1.00000000])),
np.array([0.50453169, 0.37440000]),
decimal=7)
np.testing.assert_almost_equal(xyY_to_xy(
np.array([0.47670437, 0.35790000, 1.00000000])),
np.array([0.47670437, 0.35790000]),
decimal=7)
np.testing.assert_almost_equal(xyY_to_xy(np.array([0.34570, 0.35850])),
np.array([0.34570000, 0.35850000]),
decimal=7)
def test_xyY_to_xy(self):
"""
Tests :func:`colour.models.cie_xyy.xyY_to_xy` definition.
"""
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.54369557, 0.32107944, 0.12197225])),
np.array([0.54369557, 0.32107944]),
decimal=7)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.29777735, 0.48246446, 0.23042768])),
np.array([0.29777735, 0.48246446]),
decimal=7)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.18582823, 0.14633764, 0.06157201])),
np.array([0.18582823, 0.14633764]),
decimal=7)
np.testing.assert_almost_equal(
xyY_to_xy(np.array([0.31270, 0.32900])),
np.array([0.31270000, 0.32900000]),
decimal=7)
def UVW_to_XYZ(
UVW,
illuminant=ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']):
"""
Converts *CIE 1964 U\\*V\\*W\\** colourspace to *CIE XYZ* tristimulus
values.
Parameters
----------
UVW : array_like
*CIE 1964 U\\*V\\*W\\** colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE XYZ* tristimulus values.
Warning
-------
The input domain and output range of that definition are non standard!
Notes
-----
+----------------+-----------------------+-----------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``UVW`` | ``U`` : [-100, 100] | ``U`` : [-1, 1] |
| | | |
| | ``V`` : [-100, 100] | ``V`` : [-1, 1] |
| | | |
| | ``W`` : [0, 100] | ``W`` : [0, 1] |
+----------------+-----------------------+-----------------+
| ``illuminant`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
+----------------+-----------------------+-----------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``XYZ`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
References
----------
:cite:`Wikipedia2008a`
Examples
--------
>>> import numpy as np
>>> UVW = np.array([94.55035725, 11.55536523, 40.54757405])
>>> UVW_to_XYZ(UVW)
array([ 20.654008, 12.197225, 5.136952])
"""
U, V, W = tsplit(to_domain_100(UVW))
u_0, v_0 = tsplit(xy_to_UCS_uv(xyY_to_xy(illuminant)))
Y = ((W + 17) / 25) ** 3
u = U / (13 * W) + u_0
v = V / (13 * W) + v_0
x, y = tsplit(UCS_uv_to_xy(tstack([u, v])))
XYZ = xyY_to_XYZ(tstack([x, y, Y]))
return from_range_100(XYZ)
def UVW_to_XYZ(
UVW,
illuminant=ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']):
"""
Converts *CIE 1964 U\\*V\\*W\\** colourspace to *CIE XYZ* tristimulus
values.
Parameters
----------
UVW : array_like
*CIE 1964 U\\*V\\*W\\** colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE XYZ* tristimulus values.
Warning
-------
The input domain and output range of that definition are non standard!
Notes
-----
+----------------+-----------------------+-----------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``UVW`` | ``U`` : [-100, 100] | ``U`` : [-1, 1] |
| | | |
| | ``V`` : [-100, 100] | ``V`` : [-1, 1] |
| | | |
| | ``W`` : [0, 100] | ``W`` : [0, 1] |
+----------------+-----------------------+-----------------+
| ``illuminant`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
+----------------+-----------------------+-----------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``XYZ`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
References
----------
:cite:`Wikipedia2008a`
Examples
--------
>>> import numpy as np
>>> UVW = np.array([94.55035725, 11.55536523, 40.54757405])
>>> UVW_to_XYZ(UVW)
array([ 20.654008, 12.197225, 5.136952])
"""
U, V, W = tsplit(to_domain_100(UVW))
u_0, v_0 = tsplit(xy_to_UCS_uv(xyY_to_xy(illuminant)))
Y = ((W + 17) / 25)**3
u = U / (13 * W) + u_0
v = V / (13 * W) + v_0
x, y = tsplit(UCS_uv_to_xy(tstack([u, v])))
XYZ = xyY_to_XYZ(tstack([x, y, Y]))
return from_range_100(XYZ)
def XYZ_to_UVW(
XYZ,
illuminant=ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']):
"""
Converts from *CIE XYZ* tristimulus values to *CIE 1964 U\\*V\\*W\\**
colourspace.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE 1964 U\\*V\\*W\\** colourspace array.
Warning
-------
The input domain and output range of that definition are non standard!
Notes
-----
+----------------+-----------------------+-----------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``XYZ`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
| ``illuminant`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
+----------------+-----------------------+-----------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``UVW`` | ``U`` : [-100, 100] | ``U`` : [-1, 1] |
| | | |
| | ``V`` : [-100, 100] | ``V`` : [-1, 1] |
| | | |
| | ``W`` : [0, 100] | ``W`` : [0, 1] |
+----------------+-----------------------+-----------------+
References
----------
:cite:`Wikipedia2008a`
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) * 100
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([ 94.5503572..., 11.5553652..., 40.5475740...])
"""
XYZ = to_domain_100(XYZ)
xy = xyY_to_xy(illuminant)
xyY = XYZ_to_xyY(XYZ, xy)
_x, _y, Y = tsplit(xyY)
u, v = tsplit(UCS_to_uv(XYZ_to_UCS(XYZ)))
u_0, v_0 = tsplit(xy_to_UCS_uv(xy))
W = 25 * spow(Y, 1 / 3) - 17
U = 13 * W * (u - u_0)
V = 13 * W * (v - v_0)
UVW = tstack([U, V, W])
return from_range_100(UVW)
def XYZ_to_UVW(
XYZ,
illuminant=ILLUMINANTS['CIE 1931 2 Degree Standard Observer']['D65']):
"""
Converts from *CIE XYZ* tristimulus values to *CIE 1964 U\\*V\\*W\\**
colourspace.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE 1964 U\\*V\\*W\\** colourspace array.
Warning
-------
The input domain and output range of that definition are non standard!
Notes
-----
+----------------+-----------------------+-----------------+
| **Domain** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``XYZ`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
| ``illuminant`` | [0, 1] | [0, 1] |
+----------------+-----------------------+-----------------+
+----------------+-----------------------+-----------------+
| **Range** | **Scale - Reference** | **Scale - 1** |
+================+=======================+=================+
| ``UVW`` | ``U`` : [-100, 100] | ``U`` : [-1, 1] |
| | | |
| | ``V`` : [-100, 100] | ``V`` : [-1, 1] |
| | | |
| | ``W`` : [0, 100] | ``W`` : [0, 1] |
+----------------+-----------------------+-----------------+
References
----------
:cite:`Wikipedia2008a`
Examples
--------
>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) * 100
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([ 94.5503572..., 11.5553652..., 40.5475740...])
"""
XYZ = to_domain_100(XYZ)
xy = xyY_to_xy(illuminant)
xyY = XYZ_to_xyY(XYZ, xy)
_x, _y, Y = tsplit(xyY)
u, v = tsplit(UCS_to_uv(XYZ_to_UCS(XYZ)))
u_0, v_0 = tsplit(xy_to_UCS_uv(xy))
W = 25 * spow(Y, 1 / 3) - 17
U = 13 * W * (u - u_0)
V = 13 * W * (v - v_0)
UVW = tstack([U, V, W])
return from_range_100(UVW)