def XYZ_to_xy(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the *xy* chromaticity coordinates from given *CIE XYZ* tristimulus
values.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*xy* chromaticity coordinates.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Output *xy* chromaticity coordinates are in range [0, 1].
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_xy(XYZ) # doctest: +ELLIPSIS
array([ 0.2641477..., 0.3777000...])
"""
xy = xyY_to_xy(XYZ_to_xyY(XYZ, illuminant))
return xy
def XYZ_to_xy(XYZ, illuminant=ILLUMINANTS.get("CIE 1931 2 Degree Standard Observer").get("D50")):
"""
Returns the *xy* chromaticity coordinates from given *CIE XYZ* tristimulus
values.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*xy* chromaticity coordinates.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Output *xy* chromaticity coordinates are in domain [0, 1].
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_xy(XYZ) # doctest: +ELLIPSIS
array([ 0.2641477..., 0.3777000...])
"""
xy = xyY_to_xy(XYZ_to_xyY(XYZ, illuminant))
return xy
def RGB_to_Lab(RGB, colourspace):
"""
Converts given *RGB* value from given colourspace to *CIE Lab* colourspace.
Parameters
----------
RGB : array_like
*RGB* value.
colourspace : RGB_Colourspace
*RGB* colourspace.
Returns
-------
bool
Definition success.
"""
return XYZ_to_Lab(
RGB_to_XYZ(np.array(RGB),
colourspace.whitepoint,
ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('E'),
colourspace.to_XYZ,
'Bradford',
colourspace.decoding_cctf),
colourspace.whitepoint)
def XYZ_to_xy(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the *xy* chromaticity coordinates from given *CIE XYZ* colourspace
matrix.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
tuple
*xy* chromaticity coordinates.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *xy* chromaticity coordinates are in domain [0, 1].
Examples
--------
>>> XYZ_to_xy(np.array([0.97137399, 1, 1.04462134])) # doctest: +ELLIPSIS
(0.3220741..., 0.3315655...)
>>> XYZ_to_xy((0.97137399, 1, 1.04462134)) # doctest: +ELLIPSIS
(0.3220741..., 0.3315655...)
"""
xyY = np.ravel(XYZ_to_xyY(XYZ, illuminant))
return xyY[0], xyY[1]
def XYZ_to_xy(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the *xy* chromaticity coordinates from given *CIE XYZ* colourspace
matrix.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
tuple
*xy* chromaticity coordinates.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *xy* chromaticity coordinates are in domain [0, 1].
Examples
--------
>>> XYZ = np.array([0.07049534, 0.1008, 0.09558313])
>>> XYZ_to_xy(XYZ) # doctest: +ELLIPSIS
(0.2641477..., 0.3777000...)
"""
xyY = np.ravel(XYZ_to_xyY(XYZ, illuminant))
return xyY[0], xyY[1]
def XYZ_to_xy(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the *xy* chromaticity coordinates from given *CIE XYZ* colourspace
matrix.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
tuple
*xy* chromaticity coordinates.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *xy* chromaticity coordinates are in domain [0, 1].
Examples
--------
>>> XYZ_to_xy(np.array([0.97137399, 1, 1.04462134])) # doctest: +ELLIPSIS
(0.3220741..., 0.3315655...)
>>> XYZ_to_xy((0.97137399, 1, 1.04462134)) # doctest: +ELLIPSIS
(0.3220741..., 0.3315655...)
"""
xyY = np.ravel(XYZ_to_xyY(XYZ, illuminant))
return xyY[0], xyY[1]
def Luv_to_XYZ(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Luv* colourspace to *CIE XYZ* tristimulus values.
Parameters
----------
Luv : array_like
*CIE Luv* colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE XYZ* tristimulus values.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *CIE XYZ* tristimulus values are in range [0, 1].
References
----------
.. [3] Lindbloom, B. (2003). Luv to XYZ. Retrieved February 24, 2014,
from http://brucelindbloom.com/Eqn_Luv_to_XYZ.html
Examples
--------
>>> Luv = np.array([37.9856291 , -28.80219593, -1.35800706])
>>> Luv_to_XYZ(Luv) # doctest: +ELLIPSIS
array([ 0.0704953..., 0.1008 , 0.0955831...])
"""
L, u, v = tsplit(Luv)
X_r, Y_r, Z_r = tsplit(xyY_to_XYZ(xy_to_xyY(illuminant)))
Y = np.where(L > CIE_E * CIE_K, ((L + 16) / 116) ** 3, L / CIE_K)
a = 1 / 3 * ((52 * L / (u + 13 * L *
(4 * X_r / (X_r + 15 * Y_r + 3 * Z_r)))) - 1)
b = -5 * Y
c = -1 / 3.0
d = Y * (39 * L / (v + 13 * L *
(9 * Y_r / (X_r + 15 * Y_r + 3 * Z_r))) - 5)
X = (d - b) / (a - c)
Z = X * a + b
XYZ = tstack((X, Y, Z))
return XYZ
def XYZ_to_Lab(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE Lab* 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 Lab* colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *Lightness* :math:`L^*` is in range [0, 100].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to Lab. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_XYZ_to_Lab.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_Lab(XYZ) # doctest: +ELLIPSIS
array([ 37.9856291..., -23.6290768..., -4.4174661...])
"""
XYZ = np.asarray(XYZ)
XYZ_r = xyY_to_XYZ(xy_to_xyY(illuminant))
XYZ_f = XYZ / XYZ_r
XYZ_f = np.where(XYZ_f > CIE_E,
np.power(XYZ_f, 1 / 3),
(CIE_K * XYZ_f + 16) / 116)
X_f, Y_f, Z_f = tsplit(XYZ_f)
L = 116 * Y_f - 16
a = 500 * (X_f - Y_f)
b = 200 * (Y_f - Z_f)
Lab = tstack((L, a, b))
return Lab
def XYZ_to_Lab(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE Lab* 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 Lab* colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *Lightness* :math:`L^*` is in domain [0, 100].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to Lab. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_XYZ_to_Lab.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_Lab(XYZ) # doctest: +ELLIPSIS
array([ 37.9856291..., -23.6230288..., -4.4141703...])
"""
XYZ = np.asarray(XYZ)
XYZ_r = xyY_to_XYZ(xy_to_xyY(illuminant))
XYZ_f = XYZ / XYZ_r
XYZ_f = np.where(XYZ_f > CIE_E,
np.power(XYZ_f, 1 / 3),
(CIE_K * XYZ_f + 16) / 116)
X_f, Y_f, Z_f = tsplit(XYZ_f)
L = 116 * Y_f - 16
a = 500 * (X_f - Y_f)
b = 200 * (Y_f - Z_f)
Lab = tstack((L, a, b))
return Lab
def XYZ_to_Luv(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE Luv* 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 Luv* colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output :math:`L^*` is in range [0, 100].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to Luv. Retrieved February 24, 2014,
from http://brucelindbloom.com/Eqn_XYZ_to_Luv.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_Luv(XYZ) # doctest: +ELLIPSIS
array([ 37.9856291..., -28.8021959..., -1.3580070...])
"""
X, Y, Z = tsplit(XYZ)
X_r, Y_r, Z_r = tsplit(xyY_to_XYZ(xy_to_xyY(illuminant)))
y_r = Y / Y_r
L = np.where(y_r > CIE_E, 116 * y_r ** (1 / 3) - 16, CIE_K * y_r)
u = (13 * L * ((4 * X / (X + 15 * Y + 3 * Z)) -
(4 * X_r / (X_r + 15 * Y_r + 3 * Z_r))))
v = (13 * L * ((9 * Y / (X + 15 * Y + 3 * Z)) -
(9 * Y_r / (X_r + 15 * Y_r + 3 * Z_r))))
Luv = tstack((L, u, v))
return Luv
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 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 domain [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([-28.0483277..., -0.8805242..., 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 Lab_to_XYZ(Lab,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Lab* colourspace to *CIE XYZ* tristimulus values.
Parameters
----------
Lab : array_like
*CIE Lab* colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE XYZ* tristimulus values.
Notes
-----
- Input *Lightness* :math:`L^*` is in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *CIE XYZ* tristimulus values are in domain [0, 1].
References
----------
.. [3] Lindbloom, B. (2008). Lab to XYZ. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_Lab_to_XYZ.html
Examples
--------
>>> Lab = np.array([37.98562910, -23.62302887, -4.41417036])
>>> Lab_to_XYZ(Lab) # doctest: +ELLIPSIS
array([ 0.0704953..., 0.1008 , 0.0955831...])
"""
L, a, b = tsplit(Lab)
XYZ_r = xyY_to_XYZ(xy_to_xyY(illuminant))
f_y = (L + 16) / 116
f_x = a / 500 + f_y
f_z = f_y - b / 200
x_r = np.where(f_x**3 > CIE_E, f_x**3, (116 * f_x - 16) / CIE_K)
y_r = np.where(L > CIE_K * CIE_E, ((L + 16) / 116)**3, L / CIE_K)
z_r = np.where(f_z**3 > CIE_E, f_z**3, (116 * f_z - 16) / CIE_K)
XYZ = tstack((x_r, y_r, z_r)) * XYZ_r
return XYZ
def Lab_to_XYZ(Lab,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Lab* colourspace to *CIE XYZ* colourspace.
Parameters
----------
Lab : array_like, (3,)
*CIE Lab* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE XYZ* colourspace matrix.
Notes
-----
- Input *Lightness* :math:`L^*` is in domain [0, 100].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *CIE XYZ* colourspace matrix is in domain [0, 1].
References
----------
.. [3] http://www.brucelindbloom.com/Eqn_Lab_to_XYZ.html
(Last accessed 24 February 2014)
Examples
--------
>>> Lab = np.array([100, -7.41787844, -15.85742105])
>>> Lab_to_XYZ(Lab) # doctest: +ELLIPSIS
array([ 0.9219310..., 1. , 1.0374424...])
"""
L, a, b = np.ravel(Lab)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
fy = (L + 16) / 116
fx = a / 500 + fy
fz = fy - b / 200
xr = fx ** 3 if fx ** 3 > CIE_E else (116 * fx - 16) / CIE_K
yr = ((L + 16) / 116) ** 3 if L > CIE_K * CIE_E else L / CIE_K
zr = fz ** 3 if fz ** 3 > CIE_E else (116 * fz - 16) / CIE_K
X = xr * Xr
Y = yr * Yr
Z = zr * Zr
return np.array([X, Y, Z])
def Luv_to_XYZ(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Luv* colourspace to *CIE XYZ* colourspace.
Parameters
----------
Luv : array_like, (3,)
*CIE Luv* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE XYZ* colourspace matrix.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *CIE XYZ* colourspace matrix is in domain [0, 1].
References
----------
.. [3] http://brucelindbloom.com/Eqn_Luv_to_XYZ.html
(Last accessed 24 February 2014)
Examples
--------
>>> Luv = np.array([100, -20.04304247, -19.81676035])
>>> Luv_to_XYZ(Luv) # doctest: +ELLIPSIS
array([ 0.9219310..., 1. , 1.0374424...])
"""
L, u, v = np.ravel(Luv)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
Y = ((L + 16) / 116) ** 3 if L > CIE_E * CIE_K else L / CIE_K
a = 1 / 3 * ((52 * L / (u + 13 * L *
(4 * Xr / (Xr + 15 * Yr + 3 * Zr)))) - 1)
b = -5 * Y
c = -1 / 3.0
d = Y * (39 * L / (v + 13 * L *
(9 * Yr / (Xr + 15 * Yr + 3 * Zr))) - 5)
X = (d - b) / (a - c)
Z = X * a + b
return np.array([X, Y, Z])
def Lab_to_XYZ(Lab,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Lab* colourspace to *CIE XYZ* tristimulus values.
Parameters
----------
Lab : array_like
*CIE Lab* colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
*CIE XYZ* tristimulus values.
Notes
-----
- Input *Lightness* :math:`L^*` is in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output *CIE XYZ* tristimulus values are in domain [0, 1].
References
----------
.. [3] Lindbloom, B. (2008). Lab to XYZ. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_Lab_to_XYZ.html
Examples
--------
>>> Lab = np.array([37.98562910, -23.62302887, -4.41417036])
>>> Lab_to_XYZ(Lab) # doctest: +ELLIPSIS
array([ 0.0704953..., 0.1008 , 0.0955831...])
"""
L, a, b = tsplit(Lab)
XYZ_r = xyY_to_XYZ(xy_to_xyY(illuminant))
f_y = (L + 16) / 116
f_x = a / 500 + f_y
f_z = f_y - b / 200
x_r = np.where(f_x ** 3 > CIE_E, f_x ** 3, (116 * f_x - 16) / CIE_K)
y_r = np.where(L > CIE_K * CIE_E, ((L + 16) / 116) ** 3, L / CIE_K)
z_r = np.where(f_z ** 3 > CIE_E, f_z ** 3, (116 * f_z - 16) / CIE_K)
XYZ = tstack((x_r, y_r, z_r)) * XYZ_r
return XYZ
def Lab_to_XYZ(Lab,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Lab* colourspace to *CIE XYZ* colourspace.
Parameters
----------
Lab : array_like, (3,)
*CIE Lab* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE XYZ* colourspace matrix.
Notes
-----
- Input *Lightness* :math:`L^*` is in domain [0, 100].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *CIE XYZ* colourspace matrix is in domain [0, 1].
References
----------
.. [3] http://www.brucelindbloom.com/Eqn_Lab_to_XYZ.html
(Last accessed 24 February 2014)
Examples
--------
>>> Lab = np.array([100, -7.41787844, -15.85742105])
>>> Lab_to_XYZ(Lab) # doctest: +ELLIPSIS
array([ 0.9219310..., 1. , 1.0374424...])
"""
L, a, b = np.ravel(Lab)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
fy = (L + 16) / 116
fx = a / 500 + fy
fz = fy - b / 200
xr = fx**3 if fx**3 > CIE_E else (116 * fx - 16) / CIE_K
yr = ((L + 16) / 116)**3 if L > CIE_K * CIE_E else L / CIE_K
zr = fz**3 if fz**3 > CIE_E else (116 * fz - 16) / CIE_K
X = xr * Xr
Y = yr * Yr
Z = zr * Zr
return np.array([X, Y, Z])
def Luv_to_XYZ(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE Luv* colourspace to *CIE XYZ* colourspace.
Parameters
----------
Luv : array_like, (3,)
*CIE Luv* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE XYZ* colourspace matrix.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *CIE XYZ* colourspace matrix is in domain [0, 1].
References
----------
.. [3] Lindbloom, B. (2003). Luv to XYZ. Retrieved February 24, 2014,
from http://brucelindbloom.com/Eqn_Luv_to_XYZ.html
Examples
--------
>>> Luv = np.array([37.9856291, -28.79229446, -1.3558195])
>>> Luv_to_XYZ(Luv) # doctest: +ELLIPSIS
array([ 0.0704953..., 0.1008 , 0.0955831...])
"""
L, u, v = np.ravel(Luv)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
Y = ((L + 16) / 116) ** 3 if L > CIE_E * CIE_K else L / CIE_K
a = 1 / 3 * ((52 * L / (u + 13 * L *
(4 * Xr / (Xr + 15 * Yr + 3 * Zr)))) - 1)
b = -5 * Y
c = -1 / 3.0
d = Y * (39 * L / (v + 13 * L *
(9 * Yr / (Xr + 15 * Yr + 3 * Zr))) - 5)
X = (d - b) / (a - c)
Z = X * a + b
return np.array([X, Y, Z])
def XYZ_to_Lab(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE Lab* colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE Lab* colourspace matrix.
Notes
-----
- Input *CIE XYZ* is in domain [0, 1].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *Lightness* :math:`L^*` is in domain [0, 100].
References
----------
.. [2] http://www.brucelindbloom.com/Eqn_XYZ_to_Lab.html
(Last accessed 24 February 2014)
Examples
--------
>>> XYZ_to_Lab(np.array([0.92193107, 1, 1.03744246])) # doctest: +ELLIPSIS
array([ 100. , -7.4178784..., -15.8574210...])
"""
X, Y, Z = np.ravel(XYZ)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
xr = X / Xr
yr = Y / Yr
zr = Z / Zr
fx = xr ** (1 / 3) if xr > CIE_E else (CIE_K * xr + 16) / 116
fy = yr ** (1 / 3) if yr > CIE_E else (CIE_K * yr + 16) / 116
fz = zr ** (1 / 3) if zr > CIE_E else (CIE_K * zr + 16) / 116
L = 116 * fy - 16
a = 500 * (fx - fy)
b = 200 * (fy - fz)
return np.array([L, a, b])
def XYZ_to_Lab(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE Lab* colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE Lab* colourspace matrix.
Notes
-----
- Input *CIE XYZ* is in domain [0, 1].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output *Lightness* :math:`L^*` is in domain [0, 100].
References
----------
.. [2] http://www.brucelindbloom.com/Eqn_XYZ_to_Lab.html
(Last accessed 24 February 2014)
Examples
--------
>>> XYZ_to_Lab(np.array([0.92193107, 1, 1.03744246])) # doctest: +ELLIPSIS
array([ 100. , -7.4178784..., -15.8574210...])
"""
X, Y, Z = np.ravel(XYZ)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
xr = X / Xr
yr = Y / Yr
zr = Z / Zr
fx = xr**(1 / 3) if xr > CIE_E else (CIE_K * xr + 16) / 116
fy = yr**(1 / 3) if yr > CIE_E else (CIE_K * yr + 16) / 116
fz = zr**(1 / 3) if zr > CIE_E else (CIE_K * zr + 16) / 116
L = 116 * fy - 16
a = 500 * (fx - fy)
b = 200 * (fy - fz)
return np.array([L, a, b])
def XYZ_to_xyY(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE xyY* colourspace and
reference *illuminant*.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*CIE xyY* colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Output *CIE xyY* colourspace array is in range [0, 1].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to xyY. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_XYZ_to_xyY.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_xyY(XYZ) # doctest: +ELLIPSIS
array([ 0.2641477..., 0.3777000..., 0.1008 ])
"""
XYZ = np.asarray(XYZ)
X, Y, Z = tsplit(XYZ)
xy_w = np.asarray(illuminant)
XYZ_n = np.zeros(XYZ.shape)
XYZ_n[..., 0:2] = xy_w
xyY = np.where(
np.all(XYZ == 0, axis=-1)[..., np.newaxis],
XYZ_n,
tstack((X / (X + Y + Z), Y / (X + Y + Z), Y)))
return xyY
def XYZ_to_xyY(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* tristimulus values to *CIE xyY* colourspace and
reference *illuminant*.
Parameters
----------
XYZ : array_like
*CIE XYZ* tristimulus values.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*CIE xyY* colourspace array.
Notes
-----
- Input *CIE XYZ* tristimulus values are in domain [0, 1].
- Output *CIE xyY* colourspace array is in range [0, 1].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to xyY. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_XYZ_to_xyY.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.10080000, 0.09558313])
>>> XYZ_to_xyY(XYZ) # doctest: +ELLIPSIS
array([ 0.2641477..., 0.3777000..., 0.1008 ])
"""
XYZ = np.asarray(XYZ)
X, Y, Z = tsplit(XYZ)
xy_w = np.asarray(illuminant)
XYZ_n = np.zeros(XYZ.shape)
XYZ_n[..., 0:2] = xy_w
xyY = np.where(
np.all(XYZ == 0, axis=-1)[..., np.newaxis], XYZ_n,
tstack((X / (X + Y + Z), Y / (X + Y + Z), Y)))
return xyY
def XYZ_to_Luv(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE Luv* colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE Luv* colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output :math:`L^*` is in domain [0, 100].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to Luv. Retrieved February 24, 2014,
from http://brucelindbloom.com/Eqn_XYZ_to_Luv.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.1008, 0.09558313])
>>> XYZ_to_Luv(XYZ) # doctest: +ELLIPSIS
array([ 37.9856291..., -28.7922944..., -1.3558195...])
"""
X, Y, Z = np.ravel(XYZ)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
yr = Y / Yr
L = 116 * yr ** (1 / 3) - 16 if yr > CIE_E else CIE_K * yr
u = (13 * L * ((4 * X / (X + 15 * Y + 3 * Z)) -
(4 * Xr / (Xr + 15 * Yr + 3 * Zr))))
v = (13 * L * ((9 * Y / (X + 15 * Y + 3 * Z)) -
(9 * Yr / (Xr + 15 * Yr + 3 * Zr))))
return np.array([L, u, v])
def XYZ_to_Luv(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE Luv* colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE Luv* colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Input *illuminant* chromaticity coordinates are in domain [0, 1].
- Output :math:`L^*` is in domain [0, 100].
References
----------
.. [2] http://brucelindbloom.com/Eqn_XYZ_to_Luv.html
(Last accessed 24 February 2014)
Examples
--------
>>> XYZ_to_Luv(np.array([0.92193107, 1, 1.03744246])) # doctest: +ELLIPSIS
array([ 100. , -20.0430424..., -19.8167603...])
"""
X, Y, Z = np.ravel(XYZ)
Xr, Yr, Zr = np.ravel(xy_to_XYZ(illuminant))
yr = Y / Yr
L = 116 * yr ** (1 / 3) - 16 if yr > CIE_E else CIE_K * yr
u = (13 * L * ((4 * X / (X + 15 * Y + 3 * Z)) -
(4 * Xr / (Xr + 15 * Yr + 3 * Zr))))
v = (13 * L * ((9 * Y / (X + 15 * Y + 3 * Z)) -
(9 * Yr / (Xr + 15 * Yr + 3 * Zr))))
return np.array([L, u, v])
def Luv_to_uv(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the :math:`uv^p` chromaticity coordinates from given *CIE Luv*
colourspace array.
Parameters
----------
Luv : array_like
*CIE Luv* colourspace array.
illuminant : array_like, optional
Reference *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array.
Returns
-------
ndarray
:math:`uv^p` chromaticity coordinates.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Input *illuminant* *xy* chromaticity coordinates or *CIE xyY*
colourspace array are in domain [0, :math:`\infty`].
- Output :math:`uv^p` chromaticity coordinates are in range [0, 1].
References
----------
.. [4] Wikipedia. (n.d.). The forward transformation. Retrieved February
24, 2014, from
http://en.wikipedia.org/wiki/CIELUV#The_forward_transformation
Examples
--------
>>> Luv = np.array([37.9856291 , -28.80219593, -1.35800706])
>>> Luv_to_uv(Luv) # doctest: +ELLIPSIS
array([ 0.1508531..., 0.4853297...])
"""
X, Y, Z = tsplit(Luv_to_XYZ(Luv, illuminant))
uv = tstack((4 * X / (X + 15 * Y + 3 * Z),
9 * Y / (X + 15 * Y + 3 * Z)))
return uv
def XYZ_to_UVW(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE 1964 U\*V\*W\** colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE 1964 U\*V\*W\** colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 100].
- Output *CIE UVW* colourspace matrix is in domain [0, 100].
Warning
-------
The input / output domains of that definition are non standard!
Examples
--------
>>> XYZ = np.array([0.07049534, 0.1008, 0.09558313]) * 100
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([-28.0483277..., -0.8805242..., 37.0041149...])
"""
x, y, Y = np.ravel(XYZ_to_xyY(XYZ, illuminant))
u, v = np.ravel(UCS_to_uv(XYZ_to_UCS(XYZ)))
u0, v0 = np.ravel(UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(illuminant))))
W = 25 * Y ** (1 / 3) - 17
U = 13 * W * (u - u0)
V = 13 * W * (v - v0)
return np.array([U, V, W])
def XYZ_to_UVW(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE 1964 U\*V*\W\** colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE 1964 U\*V*\W\** colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 100].
- Output *CIE UVW* colourspace matrix is in domain [0, 100].
Warning
-------
The input / output domains of that definition are non standard!
Examples
--------
>>> XYZ = np.array([11.80583421, 10.34, 5.15089229])
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([ 24.2543371..., 7.2205484..., 37.4645000...])
"""
x, y, Y = np.ravel(XYZ_to_xyY(XYZ, illuminant))
u, v = np.ravel(UCS_to_uv(XYZ_to_UCS(XYZ)))
u0, v0 = np.ravel(UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(illuminant))))
W = 25 * Y ** (1 / 3) - 17
U = 13 * W * (u - u0)
V = 13 * W * (v - v0)
return np.array([U, V, W])
def XYZ_to_UVW(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE 1964 U\*V*\W\** colourspace.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE 1964 U\*V*\W\** colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 100].
- Output *CIE UVW* colourspace matrix is in domain [0, 100].
Warning
-------
The input / output domains of that definition are non standard!
Examples
--------
>>> XYZ = np.array([11.80583421, 10.34, 5.15089229])
>>> XYZ_to_UVW(XYZ) # doctest: +ELLIPSIS
array([ 24.2543371..., 7.2205484..., 37.4645000...])
"""
x, y, Y = np.ravel(XYZ_to_xyY(XYZ, illuminant))
u, v = np.ravel(UCS_to_uv(XYZ_to_UCS(XYZ)))
u0, v0 = np.ravel(UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(illuminant))))
W = 25 * Y**(1 / 3) - 17
U = 13 * W * (u - u0)
V = 13 * W * (v - v0)
return np.array([U, V, W])
def XYZ_to_xyY(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE xyY* colourspace and reference
*illuminant*.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE xyY* colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *CIE xyY* colourspace matrix is in domain [0, 1].
References
----------
.. [2] Lindbloom, B. (2003). XYZ to xyY. Retrieved February 24, 2014,
from http://www.brucelindbloom.com/Eqn_XYZ_to_xyY.html
Examples
--------
>>> XYZ = np.array([0.07049534, 0.1008, 0.09558313])
>>> XYZ_to_xyY(XYZ) # doctest: +ELLIPSIS
array([ 0.2641477..., 0.3777000..., 0.1008 ])
"""
X, Y, Z = np.ravel(XYZ)
if X == 0 and Y == 0 and Z == 0:
return np.array([illuminant[0], illuminant[1], Y])
else:
return np.array([X / (X + Y + Z), Y / (X + Y + Z), Y])
def CCT_factor(reference_data, XYZ_r):
xy_w = ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get('D65')
XYZ_w = xy_to_XYZ(xy_w)
Labs = []
for vs_colorimetry_data_ in reference_data:
_name, XYZ, _Lab, _C = vs_colorimetry_data_
XYZ_a = chromatic_adaptation_VonKries(XYZ,
XYZ_r,
XYZ_w,
transform='CMCCAT2000')
Lab = XYZ_to_Lab(XYZ_a, illuminant=xy_w)
Labs.append(Lab)
G_r = gamut_area(Labs) / D65_GAMUT_AREA
CCT_f = 1 if G_r > 1 else G_r
return CCT_f
def RGB_colourspace_limits(colourspace,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(
'D50')):
"""
Computes given *RGB* colourspace volume limits in *Lab* colourspace.
Parameters
----------
colourspace : RGB_Colourspace
*RGB* colourspace to compute the volume of.
illuminant : array_like, optional
*Lab* colourspace *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*RGB* colourspace volume limits.
Examples
--------
>>> from colour import sRGB_COLOURSPACE as sRGB
>>> RGB_colourspace_limits(sRGB) # doctest: +ELLIPSIS
array([[ 0... , 100.0000848...],
[ -79.2197012..., 94.6760011...],
[-114.7814393..., 96.7261797...]])
"""
Lab = []
for combination in list(itertools.product([0, 1], repeat=3)):
Lab.append(XYZ_to_Lab(RGB_to_XYZ(combination,
colourspace.whitepoint,
illuminant,
colourspace.RGB_to_XYZ_matrix)))
Lab = np.array(Lab)
limits = []
for i in np.arange(3):
limits.append((np.min(Lab[..., i]), np.max(Lab[..., i])))
return np.array(limits)
def RGB_colourspace_limits(
colourspace,
illuminant=ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get(
'D50')):
"""
Computes given *RGB* colourspace volume limits in *Lab* colourspace.
Parameters
----------
colourspace : RGB_Colourspace
*RGB* colourspace to compute the volume of.
illuminant : array_like, optional
*Lab* colourspace *illuminant* chromaticity coordinates.
Returns
-------
ndarray
*RGB* colourspace volume limits.
Examples
--------
>>> from colour import sRGB_COLOURSPACE as sRGB
>>> RGB_colourspace_limits(sRGB) # doctest: +ELLIPSIS
array([[ 0... , 100... ],
[ -79.2263741..., 94.6657491...],
[-114.7846271..., 96.7135199...]])
"""
Lab = []
for combination in list(itertools.product([0, 1], repeat=3)):
Lab.append(
XYZ_to_Lab(
RGB_to_XYZ(combination, colourspace.whitepoint, illuminant,
colourspace.RGB_to_XYZ_matrix)))
Lab = np.array(Lab)
limits = []
for i in np.arange(3):
limits.append((np.min(Lab[..., i]), np.max(Lab[..., i])))
return np.array(limits)
def XYZ_to_xyY(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE xyY* colourspace and reference
*illuminant*.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE xyY* colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *CIE xyY* colourspace matrix is in domain [0, 1].
References
----------
.. [2] http://www.brucelindbloom.com/Eqn_XYZ_to_xyY.html
(Last accessed 24 February 2014)
Examples
--------
>>> XYZ_to_xyY(np.array([0.1180583421, 0.1034, 0.0515089229]))
array([ 0.4325, 0.3788, 0.1034])
"""
X, Y, Z = np.ravel(XYZ)
if X == 0 and Y == 0 and Z == 0:
return np.array([illuminant[0], illuminant[1], Y])
else:
return np.array([X / (X + Y + Z), Y / (X + Y + Z), Y])
def XYZ_to_xyY(XYZ,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Converts from *CIE XYZ* colourspace to *CIE xyY* colourspace and reference
*illuminant*.
Parameters
----------
XYZ : array_like, (3,)
*CIE XYZ* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
ndarray, (3,)
*CIE xyY* colourspace matrix.
Notes
-----
- Input *CIE XYZ* colourspace matrix is in domain [0, 1].
- Output *CIE xyY* colourspace matrix is in domain [0, 1].
References
----------
.. [2] http://www.brucelindbloom.com/Eqn_XYZ_to_xyY.html
(Last accessed 24 February 2014)
Examples
--------
>>> XYZ_to_xyY(np.array([0.1180583421, 0.1034, 0.0515089229]))
array([ 0.4325, 0.3788, 0.1034])
"""
X, Y, Z = np.ravel(XYZ)
if X == 0 and Y == 0 and Z == 0:
return np.array([illuminant[0], illuminant[1], Y])
else:
return np.array([X / (X + Y + Z), Y / (X + Y + Z), Y])
def Luv_to_uv(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the :math:`uv^p` chromaticity coordinates from given *CIE Luv*
colourspace matrix.
Parameters
----------
Luv : array_like, (3,)
*CIE Luv* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
tuple
:math:`uv^p` chromaticity coordinates.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Output :math:`uv^p` chromaticity coordinates are in domain [0, 1].
References
----------
.. [4] Wikipedia. (n.d.). The forward transformation. Retrieved February
24, 2014, from
http://en.wikipedia.org/wiki/CIELUV#The_forward_transformation
Examples
--------
>>> Luv = np.array([37.9856291, -28.79229446, -1.3558195])
>>> Luv_to_uv(Luv) # doctest: +ELLIPSIS
(0.1508530..., 0.4853297...)
"""
X, Y, Z = np.ravel(Luv_to_XYZ(Luv, illuminant))
return 4 * X / (X + 15 * Y + 3 * Z), 9 * Y / (X + 15 * Y + 3 * Z)
def Luv_to_uv(Luv,
illuminant=ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')):
"""
Returns the *u"v"* chromaticity coordinates from given *CIE Luv*
colourspace matrix.
Parameters
----------
Luv : array_like, (3,)
*CIE Luv* colourspace matrix.
illuminant : array_like, optional
Reference *illuminant* chromaticity coordinates.
Returns
-------
tuple
*u"v"* chromaticity coordinates.
Notes
-----
- Input :math:`L^*` is in domain [0, 100].
- Output *u"v"* chromaticity coordinates are in domain [0, 1].
References
----------
.. [4] http://en.wikipedia.org/wiki/CIELUV#The_forward_transformation
(Last accessed 24 February 2014)
Examples
--------
>>> Luv = np.array([100, -20.04304247, -19.81676035])
>>> Luv_to_uv(Luv) # doctest: +ELLIPSIS
(0.1937414..., 0.4728316...)
"""
X, Y, Z = np.ravel(Luv_to_XYZ(Luv, illuminant))
return 4 * X / (X + 15 * Y + 3 * Z), 9 * Y / (X + 15 * Y + 3 * Z)
def RGB_to_Lab(RGB, colourspace):
"""
Converts given *RGB* value from given colourspace to *CIE Lab* colourspace.
Parameters
----------
RGB : array_like
*RGB* value.
colourspace : RGB_Colourspace
*RGB* colourspace.
Returns
-------
bool
Definition success.
"""
return XYZ_to_Lab(
RGB_to_XYZ(
np.array(RGB), colourspace.whitepoint,
ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get('E'),
colourspace.to_XYZ, 'Bradford', colourspace.cctf_decoding),
colourspace.whitepoint)
def CCT_factor(reference_data, XYZ_r):
"""
Returns the correlated colour temperature factor penalizing lamps with
extremely low correlated colour temperatures.
Parameters
----------
reference_data : VS_ColorimetryData
Reference colorimetry data.
XYZ_r : array_like
*CIE XYZ* tristimulus values for reference.
Returns
-------
numeric
Correlated colour temperature factor.
"""
xy_w = ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get('D65')
XYZ_w = xy_to_XYZ(xy_w)
Labs = []
for vs_colorimetry_data_ in reference_data:
_name, XYZ, _Lab, _C = vs_colorimetry_data_
XYZ_a = chromatic_adaptation_VonKries(XYZ,
XYZ_r,
XYZ_w,
transform='CMCCAT2000')
Lab = XYZ_to_Lab(XYZ_a, illuminant=xy_w)
Labs.append(Lab)
G_r = gamut_area(Labs) / D65_GAMUT_AREA
CCT_f = 1 if G_r > 1 else G_r
return CCT_f
def CCT_factor(reference_data, XYZ_r):
"""
Returns the correlated colour temperature factor penalizing lamps with
extremely low correlated colour temperatures.
Parameters
----------
reference_data : VS_ColorimetryData
Reference colorimetry data.
XYZ_r : array_like
*CIE XYZ* tristimulus values for reference.
Returns
-------
numeric
Correlated colour temperature factor.
"""
xy_w = ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get('D65')
XYZ_w = xy_to_XYZ(xy_w)
Labs = []
for vs_colorimetry_data_ in reference_data:
_name, XYZ, _Lab, _C = vs_colorimetry_data_
XYZ_a = chromatic_adaptation_VonKries(XYZ,
XYZ_r,
XYZ_w,
transform='CMCCAT2000')
Lab = XYZ_to_Lab(XYZ_a, illuminant=xy_w)
Labs.append(Lab)
G_r = gamut_area(Labs) / D65_GAMUT_AREA
CCT_f = 1 if G_r > 1 else G_r
return CCT_f
[0.29, 0.60],
[0.15, 0.06]])
"""
*Pal/Secam RGB* colourspace primaries.
PAL_SECAM_RGB_PRIMARIES : ndarray, (3, 2)
"""
PAL_SECAM_RGB_ILLUMINANT = 'D65'
"""
*Pal/Secam RGB* colourspace whitepoint name as illuminant.
PAL_SECAM_RGB_ILLUMINANT : unicode
"""
PAL_SECAM_RGB_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(PAL_SECAM_RGB_ILLUMINANT)
"""
*Pal/Secam RGB* colourspace whitepoint.
PAL_SECAM_RGB_WHITEPOINT : tuple
"""
PAL_SECAM_RGB_TO_XYZ_MATRIX = normalised_primary_matrix(
PAL_SECAM_RGB_PRIMARIES, PAL_SECAM_RGB_WHITEPOINT)
"""
*Pal/Secam RGB* colourspace to *CIE XYZ* tristimulus values matrix.
PAL_SECAM_RGB_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_PAL_SECAM_RGB_MATRIX = np.linalg.inv(PAL_SECAM_RGB_TO_XYZ_MATRIX)
DCI_P3_P_PRIMARIES : ndarray, (3, 2)
"""
DCI_P3_ILLUMINANT = 'D63'
"""
*DCI-P3* colourspace whitepoint name as illuminant.
DCI_P3_ILLUMINANT : unicode
Notes
-----
*CIE Illuminant D Series* *D63* illuminant is used for *DCI-P3* whitepoint at
48 :math:`cd/m^2`.
"""
DCI_P3_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(DCI_P3_ILLUMINANT)
"""
*DCI-P3* colourspace whitepoint.
DCI_P3_WHITEPOINT : tuple
"""
DCI_P3_TO_XYZ_MATRIX = normalised_primary_matrix(
DCI_P3_PRIMARIES,
DCI_P3_WHITEPOINT)
"""
*DCI-P3* colourspace to *CIE XYZ* tristimulus values matrix.
DCI_P3_TO_XYZ_MATRIX : array_like, (3, 3)
"""
__all__ = [
'SMPTE_C_RGB_PRIMARIES', 'SMPTE_C_RGB_WHITEPOINT',
'SMPTE_C_RGB_TO_XYZ_MATRIX', 'XYZ_TO_SMPTE_C_RGB_MATRIX',
'SMPTE_C_RGB_TRANSFER_FUNCTION', 'SMPTE_C_RGB_INVERSE_TRANSFER_FUNCTION',
'SMPTE_C_RGB_COLOURSPACE'
]
SMPTE_C_RGB_PRIMARIES = np.array([[0.630, 0.340], [0.310, 0.595],
[0.155, 0.070]])
"""
*SMPTE-C RGB* colourspace primaries.
SMPTE_C_RGB_PRIMARIES : ndarray, (3, 2)
"""
SMPTE_C_RGB_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D65')
"""
*SMPTE-C RGB* colourspace whitepoint.
SMPTE_C_RGB_WHITEPOINT : tuple
"""
SMPTE_C_RGB_TO_XYZ_MATRIX = normalised_primary_matrix(SMPTE_C_RGB_PRIMARIES,
SMPTE_C_RGB_WHITEPOINT)
"""
*SMPTE-C RGB* colourspace to *CIE XYZ* colourspace matrix.
SMPTE_C_RGB_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_SMPTE_C_RGB_MATRIX = np.linalg.inv(SMPTE_C_RGB_TO_XYZ_MATRIX)
def planckian_locus_CIE_1931_chromaticity_diagram_plot(
illuminants=None,
**kwargs):
"""
Plots the planckian locus and given illuminants in
*CIE 1931 Chromaticity Diagram*.
Parameters
----------
illuminants : array_like, optional
Factory illuminants to plot.
\**kwargs : dict, optional
Keywords arguments.
Returns
-------
Figure
Current figure or None.
Raises
------
KeyError
If one of the given illuminant is not found in the factory illuminants.
Examples
--------
>>> ils = ['A', 'B', 'C']
>>> planckian_locus_CIE_1931_chromaticity_diagram_plot(
... ils) # doctest: +SKIP
"""
if illuminants is None:
illuminants = ('A', 'B', 'C')
cmfs = CMFS.get('CIE 1931 2 Degree Standard Observer')
settings = {
'title': ('{0} Illuminants - Planckian Locus\n'
'CIE 1931 Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer').format(
', '.join(illuminants))
if illuminants else
('Planckian Locus\nCIE 1931 Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'),
'standalone': False}
settings.update(kwargs)
CIE_1931_chromaticity_diagram_plot(**settings)
start, end = 1667, 100000
xy = np.array([UCS_uv_to_xy(CCT_to_uv(x, 0, method='Robertson 1968'))
for x in np.arange(start, end + 250, 250)])
pylab.plot(xy[..., 0], xy[..., 1], color='black', linewidth=2)
for i in (1667, 2000, 2500, 3000, 4000, 6000, 10000):
x0, y0 = UCS_uv_to_xy(CCT_to_uv(i, -0.025, method='Robertson 1968'))
x1, y1 = UCS_uv_to_xy(CCT_to_uv(i, 0.025, method='Robertson 1968'))
pylab.plot((x0, x1), (y0, y1), color='black', linewidth=2)
pylab.annotate('{0}K'.format(i),
xy=(x0, y0),
xytext=(0, -10),
color='black',
textcoords='offset points',
size='x-small')
for illuminant in illuminants:
xy = ILLUMINANTS.get(cmfs.name).get(illuminant)
if xy is None:
raise KeyError(
('Illuminant "{0}" not found in factory illuminants: '
'"{1}".').format(illuminant,
sorted(ILLUMINANTS.get(cmfs.name).keys())))
pylab.plot(xy[0], xy[1], 'o', color='white', linewidth=2)
pylab.annotate(illuminant,
xy=(xy[0], xy[1]),
xytext=(-50, 30),
color='black',
textcoords='offset points',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3, rad=-0.2'))
settings.update({
'x_tighten': True,
'y_tighten': True,
'limits': (-0.1, 0.9, -0.1, 0.9),
'standalone': True})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def planckian_locus_CIE_1960_UCS_chromaticity_diagram_plot(
illuminants=None,
**kwargs):
"""
Plots the planckian locus and given illuminants in
*CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
illuminants : array_like, optional
Factory illuminants to plot.
\*\*kwargs : \*\*
Keywords arguments.
Returns
-------
bool
Definition success.
Raises
------
KeyError
If one of the given illuminant is not found in the factory illuminants.
Examples
--------
>>> ils = ['A', 'C', 'E']
>>> planckian_locus_CIE_1960_UCS_chromaticity_diagram_plot(ils) # noqa # doctest: +SKIP
True
"""
if illuminants is None:
illuminants = ('A', 'C', 'E')
cmfs = CMFS.get('CIE 1931 2 Degree Standard Observer')
settings = {
'title': ('{0} Illuminants - Planckian Locus\n'
'CIE 1960 UCS Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer').format(
', '.join(illuminants))
if illuminants else
('Planckian Locus\nCIE 1960 UCS Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'),
'standalone': False}
settings.update(kwargs)
if not CIE_1960_UCS_chromaticity_diagram_plot(**settings):
return
xy_to_uv = lambda x: UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(x)))
start, end = 1667, 100000
uv = np.array([CCT_to_uv(x, 0, cmfs=cmfs)
for x in np.arange(start, end + 250, 250)])
pylab.plot(uv[:, 0], uv[:, 1], color='black', linewidth=2)
for i in [1667, 2000, 2500, 3000, 4000, 6000, 10000]:
u0, v0 = CCT_to_uv(i, -0.05)
u1, v1 = CCT_to_uv(i, 0.05)
pylab.plot([u0, u1], [v0, v1], color='black', linewidth=2)
pylab.annotate('{0}K'.format(i),
xy=(u0, v0),
xytext=(0, -10),
textcoords='offset points',
size='x-small')
for illuminant in illuminants:
uv = xy_to_uv(ILLUMINANTS.get(cmfs.name).get(illuminant))
if uv is None:
raise KeyError(
('Illuminant "{0}" not found in factory illuminants: '
'"{1}".').format(illuminant,
sorted(ILLUMINANTS.get(cmfs.name).keys())))
pylab.plot(uv[0], uv[1], 'o', color='white', linewidth=2)
pylab.annotate(illuminant,
xy=(uv[0], uv[1]),
xytext=(-50, 30),
textcoords='offset points',
arrowprops=dict(arrowstyle='->',
connectionstyle='arc3, rad=-0.2'))
settings.update({'standalone': True})
settings.update(kwargs)
return display(**settings)
__status__ = 'Production'
__all__ = [
'SMITS1999_PRIMARIES', 'SMITS1999_WHITEPOINT',
'SMITS1999_XYZ_TO_RGB_MATRIX', 'XYZ_to_RGB_Smits1999',
'RGB_to_spectral_Smits1999'
]
SMITS1999_PRIMARIES = sRGB_COLOURSPACE.primaries
"""
Current Smits (1999) method implementation colourspace primaries.
SMITS1999_PRIMARIES : ndarray, (3, 2)
"""
SMITS1999_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('E')
"""
Current Smits (1999) method implementation colourspace whitepoint.
SMITS1999_WHITEPOINT : tuple
"""
SMITS1999_XYZ_TO_RGB_MATRIX = np.linalg.inv(
normalised_primary_matrix(SMITS1999_PRIMARIES, SMITS1999_WHITEPOINT))
"""
Current Smits (1999) method implementation *RGB* colourspace to
*CIE XYZ* tristimulus values matrix.
SMITS1999_XYZ_TO_RGB_MATRIX : array_like, (3, 3)
"""
0.26586621], [0.10039113, 0.89960887],
[0.03621495, 0.00000000]])
"""
*Max RGB* colourspace primaries.
MAX_RGB_PRIMARIES : ndarray, (3, 2)
"""
MAX_RGB_ILLUMINANT = 'D50'
"""
*Max RGB* colourspace whitepoint name as illuminant.
MAX_RGB_ILLUMINANT : unicode
"""
MAX_RGB_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(MAX_RGB_ILLUMINANT)
"""
*Max RGB* colourspace whitepoint.
MAX_RGB_WHITEPOINT : tuple
"""
MAX_RGB_TO_XYZ_MATRIX = normalised_primary_matrix(MAX_RGB_PRIMARIES,
MAX_RGB_WHITEPOINT)
"""
*Max RGB* colourspace to *CIE XYZ* tristimulus values matrix.
MAX_RGB_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_MAX_RGB_MATRIX = np.linalg.inv(MAX_RGB_TO_XYZ_MATRIX)
[0.209905660377358, 0.709905660377358],
[0.140061791967044, 0.080329557157570]])
"""
*ECI RGB v2* colourspace primaries.
ECI_RGB_V2_PRIMARIES : ndarray, (3, 2)
"""
ECI_RGB_V_ILLUMINANT = 'D50'
"""
*ECI RGB v2* colourspace whitepoint name as illuminant.
ECI_RGB_V_ILLUMINANT : unicode
"""
ECI_RGB_V2_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(ECI_RGB_V_ILLUMINANT)
"""
*ECI RGB v2* colourspace whitepoint.
ECI_RGB_V2_WHITEPOINT : tuple
"""
ECI_RGB_V2_TO_XYZ_MATRIX = normalised_primary_matrix(ECI_RGB_V2_PRIMARIES,
ECI_RGB_V2_WHITEPOINT)
"""
*ECI RGB v2* colourspace to *CIE XYZ* tristimulus values matrix.
ECI_RGB_V2_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_ECI_RGB_V2_MATRIX = np.linalg.inv(ECI_RGB_V2_TO_XYZ_MATRIX)
(15, 'red', 0.5709, 0.3298,
0.1268), (16, 'yellow', 0.4694, 0.4732,
0.6081), (17, 'magenta', 0.4177, 0.2704,
0.2007), (18, 'cyan', 0.2151,
0.3037, 0.1903),
(19, 'white 9.5 (.05 D)', 0.3488, 0.3628,
0.9129), (20, 'neutral 8 (.23 D)', 0.3451, 0.3596,
0.5885), (21, 'neutral 6.5 (.44 D)',
0.3446, 0.3590, 0.3595),
(22, 'neutral 5 (.70 D)', 0.3438, 0.3589,
0.1912), (23, 'neutral 3.5 (1.05 D)', 0.3423,
0.3576, 0.0893), (24, 'black 2 (1.5 D)',
0.3439, 0.3565,
0.0320))
BABELCOLOR_AVERAGE_ILLUMINANT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D50')
"""
*BabelColor Average* illuminant.
BABELCOLOR_AVERAGE_ILLUMINANT : tuple
"""
BABELCOLOR_AVERAGE = [
ColourChecker_Specification(*x) for x in BABELCOLOR_AVERAGE_DATA
]
"""
Average data derived from measurements of 30 *ColourChecker* charts.
BABELCOLOR_AVERAGE : list
"""
[0.260000000000000010, 0.699999999999999960],
[0.109728506787330320, 0.004524886877828055]])
"""
*Ekta Space PS 5* colourspace primaries.
EKTA_SPACE_PS_5_PRIMARIES : ndarray, (3, 2)
"""
EKTA_SPACE_PS_5_V_ILLUMINANT = 'D50'
"""
*Ekta Space PS 5* colourspace whitepoint name as illuminant.
EKTA_SPACE_PS_5_V_ILLUMINANT : unicode
"""
EKTA_SPACE_PS_5_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(EKTA_SPACE_PS_5_V_ILLUMINANT)
"""
*Ekta Space PS 5* colourspace whitepoint.
EKTA_SPACE_PS_5_WHITEPOINT : tuple
"""
EKTA_SPACE_PS_5_TO_XYZ_MATRIX = normalised_primary_matrix(
EKTA_SPACE_PS_5_PRIMARIES, EKTA_SPACE_PS_5_WHITEPOINT)
"""
*Ekta Space PS 5* colourspace to *CIE XYZ* tristimulus values matrix.
EKTA_SPACE_PS_5_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_EKTA_SPACE_PS_5_MATRIX = np.linalg.inv(EKTA_SPACE_PS_5_TO_XYZ_MATRIX)
def planckian_locus_CIE_1960_UCS_chromaticity_diagram_plot(
illuminants=None, **kwargs):
"""
Plots the planckian locus and given illuminants in
*CIE 1960 UCS Chromaticity Diagram*.
Parameters
----------
illuminants : array_like, optional
Factory illuminants to plot.
Other Parameters
----------------
\**kwargs : dict, optional
{:func:`boundaries`, :func:`canvas`, :func:`decorate`,
:func:`display`},
Please refer to the documentation of the previously listed definitions.
show_diagram_colours : bool, optional
{:func:`CIE_1960_UCS_chromaticity_diagram_plot`},
Whether to display the chromaticity diagram background colours.
Returns
-------
Figure
Current figure or None.
Raises
------
KeyError
If one of the given illuminant is not found in the factory illuminants.
Examples
--------
>>> ils = ['A', 'C', 'E']
>>> planckian_locus_CIE_1960_UCS_chromaticity_diagram_plot(
... ils) # doctest: +SKIP
"""
if illuminants is None:
illuminants = ('A', 'C', 'E')
cmfs = CMFS['CIE 1931 2 Degree Standard Observer']
settings = {
'title': ('{0} Illuminants - Planckian Locus\n'
'CIE 1960 UCS Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'
).format(', '.join(illuminants)) if illuminants else
('Planckian Locus\nCIE 1960 UCS Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'),
'standalone':
False
}
settings.update(kwargs)
CIE_1960_UCS_chromaticity_diagram_plot(**settings)
start, end = 1667, 100000
uv = np.array(
[CCT_to_uv(x, 'Robertson 1968', D_uv=0)
for x in np.arange(start, end + 250, 250)]) # yapf: disable
pylab.plot(uv[..., 0], uv[..., 1], color='black', linewidth=2)
for i in (1667, 2000, 2500, 3000, 4000, 6000, 10000):
u0, v0 = CCT_to_uv(i, 'Robertson 1968', D_uv=-0.05)
u1, v1 = CCT_to_uv(i, 'Robertson 1968', D_uv=0.05)
pylab.plot((u0, u1), (v0, v1), color='black', linewidth=2)
pylab.annotate(
'{0}K'.format(i),
xy=(u0, v0),
xytext=(0, -10),
color='black',
textcoords='offset points',
size='x-small')
for illuminant in illuminants:
xy = ILLUMINANTS.get(cmfs.name).get(illuminant)
if xy is None:
raise KeyError(
('Illuminant "{0}" not found in factory illuminants: '
'"{1}".').format(illuminant,
sorted(ILLUMINANTS[cmfs.name].keys())))
uv = UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(xy)))
pylab.plot(uv[0], uv[1], 'o', color='white', linewidth=2)
pylab.annotate(
illuminant,
xy=(uv[0], uv[1]),
xytext=(-50, 30),
color='black',
textcoords='offset points',
arrowprops=dict(arrowstyle='->', connectionstyle='arc3, rad=-0.2'))
settings.update({
'x_tighten': True,
'y_tighten': True,
'limits': (-0.1, 0.7, -0.2, 0.6),
'standalone': True
})
settings.update(kwargs)
boundaries(**settings)
decorate(**settings)
return display(**settings)
def plot_planckian_locus_in_chromaticity_diagram(
illuminants=None,
annotate_parameters=None,
chromaticity_diagram_callable=plot_chromaticity_diagram,
planckian_locus_callable=plot_planckian_locus,
method='CIE 1931',
**kwargs):
"""
Plots the *Planckian Locus* and given illuminants in the
*Chromaticity Diagram* according to given method.
Parameters
----------
illuminants : array_like, optional
Factory illuminants to plot.
annotate_parameters : dict or array_like, optional
Parameters for the :func:`plt.annotate` definition, used to annotate
the resulting chromaticity coordinates with their respective illuminant
names if ``annotate`` is set to *True*. ``annotate_parameters`` can be
either a single dictionary applied to all the arrows with same settings
or a sequence of dictionaries with different settings for each
illuminant.
chromaticity_diagram_callable : callable, optional
Callable responsible for drawing the *Chromaticity Diagram*.
planckian_locus_callable : callable, optional
Callable responsible for drawing the *Planckian Locus*.
method : unicode, optional
**{'CIE 1931', 'CIE 1960 UCS', 'CIE 1976 UCS'}**,
*Chromaticity Diagram* method.
Other Parameters
----------------
\\**kwargs : dict, optional
{:func:`colour.plotting.artist`,
:func:`colour.plotting.diagrams.plot_chromaticity_diagram`,
:func:`colour.plotting.temperature.plot_planckian_locus`,
:func:`colour.plotting.render`},
Please refer to the documentation of the previously listed definitions.
Returns
-------
tuple
Current figure and axes.
Examples
--------
>>> plot_planckian_locus_in_chromaticity_diagram(['A', 'B', 'C'])
... # doctest: +ELLIPSIS
(<Figure size ... with 1 Axes>, \
<matplotlib.axes._subplots.AxesSubplot object at 0x...>)
.. image:: ../_static/Plotting_\
Plot_Planckian_Locus_In_Chromaticity_Diagram.png
:align: center
:alt: plot_planckian_locus_in_chromaticity_diagram
"""
cmfs = CMFS['CIE 1931 2 Degree Standard Observer']
if illuminants is None:
illuminants = ('A', 'B', 'C')
illuminants = filter_passthrough(ILLUMINANTS.get(cmfs.name), illuminants)
settings = {'uniform': True}
settings.update(kwargs)
_figure, axes = artist(**settings)
method = method.upper()
settings = {'axes': axes, 'method': method}
settings.update(kwargs)
settings['standalone'] = False
chromaticity_diagram_callable(**settings)
planckian_locus_callable(**settings)
if method == 'CIE 1931':
def xy_to_ij(xy):
"""
Converts given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return xy
bounding_box = (-0.1, 0.9, -0.1, 0.9)
elif method == 'CIE 1960 UCS':
def xy_to_ij(xy):
"""
Converts given *CIE xy* chromaticity coordinates to *ij*
chromaticity coordinates.
"""
return UCS_to_uv(XYZ_to_UCS(xy_to_XYZ(xy)))
bounding_box = (-0.1, 0.7, -0.2, 0.6)
else:
raise ValueError('Invalid method: "{0}", must be one of '
'{{\'CIE 1931\', \'CIE 1960 UCS\'}}'.format(method))
annotate_settings_collection = [{
'annotate': True,
'xytext': (-50, 30),
'textcoords': 'offset points',
'arrowprops': COLOUR_ARROW_STYLE,
} for _ in range(len(illuminants))]
if annotate_parameters is not None:
if not isinstance(annotate_parameters, dict):
assert len(annotate_parameters) == len(illuminants), (
'Multiple annotate parameters defined, but they do not match '
'the illuminants count!')
for i, annotate_settings in enumerate(annotate_settings_collection):
if isinstance(annotate_parameters, dict):
annotate_settings.update(annotate_parameters)
else:
annotate_settings.update(annotate_parameters[i])
for i, (illuminant, xy) in enumerate(illuminants.items()):
ij = xy_to_ij(xy)
axes.plot(ij[0],
ij[1],
'o',
color=COLOUR_STYLE_CONSTANTS.colour.brightest,
markeredgecolor=COLOUR_STYLE_CONSTANTS.colour.dark,
markersize=(COLOUR_STYLE_CONSTANTS.geometry.short * 6 +
COLOUR_STYLE_CONSTANTS.geometry.short * 0.75),
markeredgewidth=COLOUR_STYLE_CONSTANTS.geometry.short * 0.75,
label=illuminant)
if annotate_settings_collection[i]['annotate']:
annotate_settings = annotate_settings_collection[i]
annotate_settings.pop('annotate')
axes.annotate(illuminant, xy=ij, **annotate_settings)
title = (('{0} Illuminants - Planckian Locus\n'
'{1} Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer').format(
', '.join(illuminants), method) if illuminants else
('Planckian Locus\n{0} Chromaticity Diagram - '
'CIE 1931 2 Degree Standard Observer'.format(method)))
settings.update({
'axes': axes,
'standalone': True,
'bounding_box': bounding_box,
'title': title,
})
settings.update(kwargs)
return render(**settings)
REC_709_PRIMARIES = np.array([[0.6400, 0.3300], [0.3000, 0.6000],
[0.1500, 0.0600]])
"""
*Rec. 709* colourspace primaries.
REC_709_PRIMARIES : ndarray, (3, 2)
"""
REC_709_ILLUMINANT = 'D65'
"""
*Rec. 709* colourspace whitepoint name as illuminant.
REC_709_ILLUMINANT : unicode
"""
REC_709_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(REC_709_ILLUMINANT)
"""
*Rec. 709* colourspace whitepoint.
REC_709_WHITEPOINT : tuple
"""
REC_709_TO_XYZ_MATRIX = np.array([[0.41238656, 0.35759149, 0.18045049],
[0.21263682, 0.71518298, 0.0721802],
[0.01933062, 0.11919716, 0.95037259]])
"""
*Rec. 709* colourspace to *CIE XYZ* tristimulus values matrix.
REC_709_TO_XYZ_MATRIX : array_like, (3, 3)
"""
[0.2210, 0.8480],
[0.0861, -0.1020]])
"""
*ALEXA Wide Gamut RGB* colourspace primaries.
ALEXA_WIDE_GAMUT_RGB_PRIMARIES : ndarray, (3, 2)
"""
ALEXA_WIDE_GAMUT_RGB_ILLUMINANT = 'D65'
"""
*ALEXA Wide Gamut RGB* colourspace whitepoint name as illuminant.
ALEXA_WIDE_GAMUT_RGB_WHITEPOINT : unicode
"""
ALEXA_WIDE_GAMUT_RGB_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get(ALEXA_WIDE_GAMUT_RGB_ILLUMINANT)
"""
*ALEXA Wide Gamut RGB* colourspace whitepoint.
ALEXA_WIDE_GAMUT_RGB_WHITEPOINT : tuple
"""
ALEXA_WIDE_GAMUT_RGB_TO_XYZ_MATRIX = np.array(
[[0.638008, 0.214704, 0.097744],
[0.291954, 0.823841, -0.115795],
[0.002798, -0.067034, 1.153294]])
"""
*ALEXA Wide Gamut RGB* colourspace to *CIE XYZ* tristimulus values matrix.
ALEXA_WIDE_GAMUT_RGB_TO_XYZ_MATRIX : array_like, (3, 3)
"""
__all__ = [
'ADOBE_RGB_1998_PRIMARIES', 'ADOBE_RGB_1998_WHITEPOINT',
'ADOBE_RGB_1998_TO_XYZ_MATRIX', 'XYZ_TO_ADOBE_RGB_1998_MATRIX',
'ADOBE_RGB_1998_TRANSFER_FUNCTION',
'ADOBE_RGB_1998_INVERSE_TRANSFER_FUNCTION', 'ADOBE_RGB_1998_COLOURSPACE'
]
ADOBE_RGB_1998_PRIMARIES = np.array([[0.6400, 0.3300], [0.2100, 0.7100],
[0.1500, 0.0600]])
"""
*Adobe RGB 1998* colourspace primaries.
ADOBE_RGB_1998_PRIMARIES : ndarray, (3, 2)
"""
ADOBE_RGB_1998_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('D65')
"""
*Adobe RGB 1998* colourspace whitepoint.
ADOBE_RGB_1998_WHITEPOINT : tuple
"""
ADOBE_RGB_1998_TO_XYZ_MATRIX = np.array([[0.57666809, 0.18556195, 0.1881985],
[0.29734449, 0.62737611, 0.0752794],
[0.02703132, 0.07069027, 0.99117879]])
"""
*Adobe RGB 1998* colourspace to *CIE XYZ* colourspace matrix.
ADOBE_RGB_1998_TO_XYZ_MATRIX : array_like, (3, 3)
References
__status__ = 'Production'
__all__ = ['SMITS1999_PRIMARIES',
'SMITS1999_WHITEPOINT',
'SMITS1999_XYZ_TO_RGB_MATRIX',
'XYZ_to_RGB_smits1999',
'RGB_to_spectral_Smits1999']
SMITS1999_PRIMARIES = sRGB_COLOURSPACE.primaries
"""
Current Smits (1999) method implementation colourspace primaries.
SMITS1999_PRIMARIES : ndarray, (3, 2)
"""
SMITS1999_WHITEPOINT = ILLUMINANTS.get(
'CIE 1931 2 Degree Standard Observer').get('E')
"""
Current Smits (1999) method implementation colourspace whitepoint.
SMITS1999_WHITEPOINT : tuple
"""
SMITS1999_XYZ_TO_RGB_MATRIX = np.linalg.inv(
normalised_primary_matrix(SMITS1999_PRIMARIES, SMITS1999_WHITEPOINT))
"""
Current Smits (1999) method implementation *RGB* colourspace to
*CIE XYZ* colourspace matrix.
SMITS1999_XYZ_TO_RGB_MATRIX : array_like, (3, 3)
"""
AP1 = np.array([[0.71300, 0.29300], [0.16500, 0.83000], [0.12800, 0.04400]])
"""
*ACES Primaries 1* or *AP1* primaries (known as *Rec. 2020+* primaries prior
to *ACES* 1.0 release).
AP1 : ndarray, (3, 2)
"""
ACES_ILLUMINANT = 'D60'
"""
*ACES2065-1* colourspace whitepoint name as illuminant.
ACES_ILLUMINANT : unicode
"""
ACES_WHITEPOINT = ILLUMINANTS.get('CIE 1931 2 Degree Standard Observer').get(
ACES_ILLUMINANT)
"""
*ACES2065-1* colourspace whitepoint.
ACES_WHITEPOINT : tuple
"""
AP0_TO_XYZ_MATRIX = np.array([[0.9525523959, 0.0000000000, 0.0000936786],
[0.3439664498, 0.7281660966, -0.0721325464],
[0.0000000000, 0.0000000000, 1.0088251844]])
"""
*ACES Primaries 0* to *CIE XYZ* tristimulus values matrix defined as per [2].
AP0_TO_XYZ_MATRIX : array_like, (3, 3)
"""
XYZ_TO_AP0_MATRIX = np.linalg.inv(AP0_TO_XYZ_MATRIX)
