colour.models Package¶

Sub-Packages¶

Sub-Modules¶

Module Contents¶

class colour.models.RGB_Colourspace(name, primaries, whitepoint, to_XYZ=None, to_RGB=None, transfer_function=None, inverse_transfer_function=None)¶

Bases: object

Implements support for the RGB colourspaces dataset from colour.models.dataset.aces_rgb, etc....

Parameters:

name (str or unicode) – RGB Colourspace name. primaries (array_like) – RGB Colourspace primaries. whitepoint (array_like) – RGB Colourspace whitepoint. to_XYZ (array_like) – Transformation matrix from colourspace to CIE XYZ colourspace. to_RGB (array_like) – Transformation matrix from CIE XYZ colourspace to colourspace. transfer_function (object) – RGB Colourspace transfer function from linear to colourspace. inverse_transfer_function (object) – RGB Colourspace inverse transfer function from colourspace to linear.

inverse_transfer_function¶

Property for self.__inverse_transfer_function private attribute.

Returns:	self.__inverse_transfer_function.
Return type:	object

name¶

Property for self.__name private attribute.

Returns:	self.__name.
Return type:	str or unicode

primaries¶

Property for self.__primaries private attribute.

Returns:	self.__primaries.
Return type:	array_like, (3, 2)

to_RGB¶

Property for self.__to_RGB private attribute.

Returns:	self.__to_RGB.
Return type:	array_like, (3, 3)

to_XYZ¶

Property for self.__to_XYZ private attribute.

Returns:	self.__to_XYZ.
Return type:	array_like, (3, 3)

transfer_function¶

Property for self.__transfer_function private attribute.

Returns:	self.__transfer_function.
Return type:	object

whitepoint¶

Property for self.__whitepoint private attribute.

Returns:	self.__whitepoint.
Return type:	array_like

colour.models.normalised_primary_matrix(primaries, whitepoint)¶

Returns the normalised primary matrix using given primaries and whitepoint matrices.

Parameters:	primaries (array_like) – Primaries chromaticity coordinate matrix, (3, 2). whitepoint (array_like) – Illuminant / whitepoint chromaticity coordinates.
Returns:	Normalised primary matrix.
Return type:	ndarray, (3, 3)

References

[3]	RP 177-1993 SMPTE RECOMMENDED PRACTICE - Television Color Equations: 3.3.2 - 3.3.6

Examples

>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = (0.32168, 0.33767)
>>> normalised_primary_matrix(pms, whitepoint)  
array([[  9.5255239...e-01,   0.0000000...e+00,   9.3678631...e-05],
       [  3.4396645...e-01,   7.2816609...e-01,  -7.2132546...e-02],
       [  0.0000000...e+00,   0.0000000...e+00,   1.0088251...e+00]])

colour.models.RGB_luminance_equation(primaries, whitepoint)¶

Returns the luminance equation from given primaries and whitepoint matrices.

Parameters:	primaries (array_like, (3, 2)) – Primaries chromaticity coordinate matrix. whitepoint (array_like) – Illuminant / whitepoint chromaticity coordinates.
Returns:	Luminance equation.
Return type:	unicode

References

[4]	RP 177-1993 SMPTE RECOMMENDED PRACTICE - Television Color Equations: 3.3.8

Examples

>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = (0.32168, 0.33767)
>>> # Doctests skip for Python 2.x compatibility.
>>> RGB_luminance_equation(pms, whitepoint)  
'Y = 0.3439664...(R) + 0.7281660...(G) + -0.0721325...(B)'

colour.models.RGB_luminance(RGB, primaries, whitepoint)¶

Returns the luminance \(y\) of given RGB components from given primaries and whitepoint matrices.

Parameters:	RGB (array_like, (3,)) – RGB chromaticity coordinate matrix. primaries (array_like, (3, 2)) – Primaries chromaticity coordinate matrix. whitepoint (array_like) – Illuminant / whitepoint chromaticity coordinates.
Returns:	Luminance \(y\).
Return type:	numeric

References

[5]	RP 177-1993 SMPTE RECOMMENDED PRACTICE - Television Color Equations: 3.3.3 - 3.3.6

Examples

>>> RGB = np.array([40.6, 4.2, 67.4])
>>> pms = np.array([0.73470, 0.26530, 0.00000, 1.00000, 0.00010, -0.07700])
>>> whitepoint = (0.32168, 0.33767)
>>> RGB_luminance(RGB, pms, whitepoint)  
12.1616018...

colour.models.XYZ_to_xyY(XYZ, illuminant=(0.34567, 0.3585))¶

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:	CIE xyY colourspace matrix.
Return type:	ndarray, (3,)

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])

colour.models.xyY_to_XYZ(xyY)¶

Converts from CIE xyY colourspace to CIE XYZ colourspace.

Parameters:	xyY (array_like, (3,)) – CIE xyY colourspace matrix.
Returns:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE xyY colourspace matrix is in domain [0, 1].
• Output CIE XYZ colourspace matrix is in domain [0, 1].

References

[3]	http://www.brucelindbloom.com/Eqn_xyY_to_XYZ.html (Last accessed 24 February 2014)

Examples

>>> xyY_to_XYZ(np.array([0.4325, 0.3788, 0.1034]))  
array([ 0.1180583...,  0.1034    ,  0.0515089...])

colour.models.xy_to_XYZ(xy)¶

Returns the CIE XYZ colourspace matrix from given xy chromaticity coordinates.

Parameters:	xy (array_like) – xy chromaticity coordinates.
Returns:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input xy chromaticity coordinates are in domain [0, 1].
• Output CIE XYZ colourspace matrix is in domain [0, 1].

Examples

>>> xy_to_XYZ((0.25, 0.25))
array([ 1.,  1.,  2.])

colour.models.XYZ_to_xy(XYZ, illuminant=(0.34567, 0.3585))¶

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:	xy chromaticity coordinates.
Return type:	tuple

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]))  
(0.3220741..., 0.3315655...)
>>> XYZ_to_xy((0.97137399, 1, 1.04462134))  
(0.3220741..., 0.3315655...)

colour.models.XYZ_to_Lab(XYZ, illuminant=(0.34567, 0.3585))¶

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:	CIE Lab colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE XYZ is in domain [0, 1].
• Input illuminant chromaticity coordinates are in domain [0, 1].
• Output Lightness \(L^*\) 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]))  
array([ 100.        ,   -7.4178784...,  -15.8574210...])

colour.models.Lab_to_XYZ(Lab, illuminant=(0.34567, 0.3585))¶

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:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input Lightness \(L^*\) 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)  
array([ 0.9219310...,  1.        ,  1.0374424...])

colour.models.Lab_to_LCHab(Lab)¶

Converts from CIE Lab colourspace to CIE LCHab colourspace.

Parameters:	Lab (array_like, (3,)) – CIE Lab colourspace matrix.
Returns:	CIE LCHab colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Lightness \(L^*\) is in domain [0, 100].

References

[4]	http://www.brucelindbloom.com/Eqn_Lab_to_LCH.html (Last accessed 24 February 2014)

Examples

>>> Lab = np.array([100, -7.41787844, -15.85742105])
>>> Lab_to_LCHab(Lab)  
array([ 100.        ,   17.5066479...,  244.9304684...])

colour.models.LCHab_to_Lab(LCHab)¶

Converts from CIE LCHab colourspace to CIE Lab colourspace.

Parameters:	LCHab (array_like, (3,)) – CIE LCHab colourspace matrix.
Returns:	CIE Lab colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Lightness \(L^*\) is in domain [0, 100].

References

[5]	http://www.brucelindbloom.com/Eqn_LCH_to_Lab.html (Last accessed 24 February 2014)

Examples

>>> LCHab = np.array([100, 17.50664796, 244.93046842])
>>> LCHab_to_Lab(LCHab)  
array([ 100.        ,   -7.4178784...,  -15.8574210...])

colour.models.XYZ_to_Luv(XYZ, illuminant=(0.34567, 0.3585))¶

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:	CIE Luv colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE XYZ colourspace matrix is in domain [0, 1].
• Input illuminant chromaticity coordinates are in domain [0, 1].
• Output \(L^*\) 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]))  
array([ 100.        ,  -20.0430424...,  -19.8167603...])

colour.models.Luv_to_XYZ(Luv, illuminant=(0.34567, 0.3585))¶

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:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input \(L^*\) 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)  
array([ 0.9219310...,  1.        ,  1.0374424...])

colour.models.Luv_to_uv(Luv, illuminant=(0.34567, 0.3585))¶

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:	u”v” chromaticity coordinates.
Return type:	tuple

Notes

• Input \(L^*\) 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)  
(0.1937414..., 0.4728316...)

colour.models.Luv_uv_to_xy(uv)¶

Returns the xy chromaticity coordinates from given CIE Luv colourspace u”v” chromaticity coordinates.

Parameters:	uv (array_like) – CIE Luv u”v” chromaticity coordinates.
Returns:	xy chromaticity coordinates.
Return type:	tuple

Notes

• Input u”v” chromaticity coordinates are in domain [0, 1].
• Output xy is in domain [0, 1].

References

[5]	http://en.wikipedia.org/wiki/CIELUV#The_reverse_transformation (Last accessed 24 February 2014)

Examples

>>> uv = (0.2033733344733139, 0.3140500001549052)
>>> Luv_uv_to_xy(uv)  
(0.2233388..., 0.1532803...)

colour.models.Luv_to_LCHuv(Luv)¶

Converts from CIE Luv colourspace to CIE LCHuv colourspace.

Parameters:	Luv (array_like, (3,)) – CIE Luv colourspace matrix.
Returns:	CIE LCHuv colourspace matrix.
Return type:	ndarray, (3,)

Notes

• \(L^*\) is in domain [0, 100].

References

[6]	http://www.brucelindbloom.com/Eqn_Luv_to_LCH.html (Last accessed 24 February 2014)

Examples

>>> Luv = np.array([100, -20.04304247, -19.81676035])
>>> Luv_to_LCHuv(Luv)  
array([ 100.        ,   28.1855910...,  224.6747382...])

colour.models.LCHuv_to_Luv(LCHuv)¶

Converts from CIE LCHuv colourspace to CIE Luv colourspace.

Parameters:	LCHuv (array_like, (3,)) – CIE LCHuv colourspace matrix.
Returns:	CIE Luv colourspace matrix.
Return type:	ndarray, (3,)

Notes

• \(L^*\) is in domain [0, 100].

References

[7]	http://www.brucelindbloom.com/Eqn_LCH_to_Luv.html (Last accessed 24 February 2014)

Examples

>>> LCHuv = np.array([100, 28.18559104, 224.6747382])
>>> LCHuv_to_Luv(LCHuv)  
array([ 100.        ,  -20.0430424...,  -19.8167603...])

colour.models.XYZ_to_UCS(XYZ)¶

Converts from CIE XYZ colourspace to CIE UCS colourspace.

Parameters:	XYZ (array_like, (3,)) – CIE XYZ colourspace matrix.
Returns:	CIE UCS colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE XYZ colourspace matrix is in domain [0, 1].
• Output CIE UCS colourspace matrix is in domain [0, 1].

References

[2]	http://en.wikipedia.org/wiki/CIE_1960_color_space#Relation_to_CIEXYZ (Last accessed 24 February 2014)

Examples

>>> XYZ = np.array([0.1180583421, 0.1034, 0.0515089229])
>>> XYZ_to_UCS(XYZ)  
array([ 0.0787055...,  0.1034    ,  0.1218252...])

colour.models.UCS_to_XYZ(UVW)¶

Converts from CIE UCS colourspace to CIE XYZ colourspace.

Parameters:	UVW (array_like, (3,)) – CIE UCS colourspace matrix.
Returns:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE UCS colourspace matrix is in domain [0, 1].
• Output CIE XYZ colourspace matrix is in domain [0, 1].

References

[3]	http://en.wikipedia.org/wiki/CIE_1960_color_space#Relation_to_CIEXYZ (Last accessed 24 February 2014)

Examples

>>> UCS = np.array([0.07870556, 0.1034, 0.12182529])
>>> UCS_to_XYZ(UCS)  
array([ 0.1180583...,  0.1034    ,  0.0515089...])

colour.models.UCS_to_uv(UVW)¶

Returns the uv chromaticity coordinates from given CIE UCS colourspace matrix.

Parameters:	UVW (array_like, (3,)) – CIE UCS colourspace matrix.
Returns:	uv chromaticity coordinates.
Return type:	tuple

Notes

• Input CIE UCS colourspace matrix is in domain [0, 1].
• Output uv chromaticity coordinates are in domain [0, 1].

References

[4]	http://en.wikipedia.org/wiki/CIE_1960_color_space#Relation_to_CIEXYZ (Last accessed 24 February 2014)

Examples

>>> UCS = np.array([0.1180583421, 0.1034, 0.0515089229])
>>> UCS_to_uv(UCS)  
(0.4324999..., 0.3788000...)

colour.models.UCS_uv_to_xy(uv)¶

Returns the xy chromaticity coordinates from given CIE UCS colourspace uv chromaticity coordinates.

Parameters:	uv (array_like) – CIE UCS uv chromaticity coordinates.
Returns:	xy chromaticity coordinates.
Return type:	tuple

Notes

• Input uv chromaticity coordinates are in domain [0, 1].
• Output xy chromaticity coordinates are in domain [0, 1].

References

[5]	http://en.wikipedia.org/wiki/CIE_1960_color_space#Relation_to_CIEXYZ (Last accessed 24 February 2014)

Examples

>>> uv = (0.43249999995420696, 0.378800000065942)
>>> UCS_uv_to_xy(uv)  
(0.7072386..., 0.4129510...)

colour.models.XYZ_to_UVW(XYZ, illuminant=(0.34567, 0.3585))¶

Converts from CIE XYZ colourspace to CIE 1964 U*VW** colourspace.

Parameters:	XYZ (array_like, (3,)) – CIE XYZ colourspace matrix. illuminant (array_like, optional) – Reference illuminant chromaticity coordinates.
Returns:	CIE 1964 U*VW** colourspace matrix.
Return type:	ndarray, (3,)

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)  
array([ 24.2543371...,   7.2205484...,  37.4645000...])

colour.models.XYZ_to_RGB(XYZ, illuminant_XYZ, illuminant_RGB, to_RGB, chromatic_adaptation_method=u'CAT02', transfer_function=None)¶

Converts from CIE XYZ colourspace to RGB colourspace using given CIE XYZ colourspace matrix, illuminants, chromatic adaptation method, normalised primary matrix and transfer function.

Parameters:	XYZ (array_like, (3,)) – CIE XYZ colourspace matrix. illuminant_XYZ (array_like) – CIE XYZ colourspace illuminant xy chromaticity coordinates. illuminant_RGB (array_like) – RGB colourspace illuminant xy chromaticity coordinates. to_RGB (array_like, (3, 3)) – Normalised primary matrix. chromatic_adaptation_method (unicode, optional) – (‘XYZ Scaling’, ‘Bradford’, ‘Von Kries’, ‘Fairchild’, ‘CAT02’) Chromatic adaptation method. transfer_function (object, optional) – Transfer function.
Returns:	RGB colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE XYZ colourspace matrix is in domain [0, 1].
• Input illuminant_XYZ xy chromaticity coordinates are in domain [0, 1].
• Input illuminant_RGB xy chromaticity coordinates are in domain [0, 1].
• Output RGB colourspace matrix is in domain [0, 1].

Examples

>>> XYZ = np.array([0.1151847498, 0.1008, 0.0508937252])
>>> illuminant_XYZ = (0.34567, 0.35850)
>>> illuminant_RGB = (0.31271, 0.32902)
>>> chromatic_adaptation_method =  'Bradford'
>>> to_RGB = np.array([
...     [3.24100326, -1.53739899, -0.49861587],
...     [-0.96922426, 1.87592999, 0.04155422],
...     [0.05563942, -0.2040112, 1.05714897]])
>>> XYZ_to_RGB(
...     XYZ,
...     illuminant_XYZ,
...     illuminant_RGB,
...     to_RGB,
...     chromatic_adaptation_method)  
array([ 0.1730350...,  0.0821103...,  0.0567249...])

colour.models.RGB_to_XYZ(RGB, illuminant_RGB, illuminant_XYZ, to_XYZ, chromatic_adaptation_method=u'CAT02', inverse_transfer_function=None)¶

Converts from RGB colourspace to CIE XYZ colourspace using given RGB colourspace matrix, illuminants, chromatic adaptation method, normalised primary matrix and transfer function.

Parameters:	RGB (array_like, (3,)) – RGB colourspace matrix. illuminant_RGB (array_like) – RGB colourspace illuminant chromaticity coordinates. illuminant_XYZ (array_like) – CIE XYZ colourspace illuminant chromaticity coordinates. to_XYZ (array_like, (3, 3)) – Normalised primary matrix. chromatic_adaptation_method (unicode, optional) – (‘XYZ Scaling’, ‘Bradford’, ‘Von Kries’, ‘Fairchild’, ‘CAT02’) Chromatic adaptation method. inverse_transfer_function (object, optional) – Inverse transfer function.
Returns:	CIE XYZ colourspace matrix.
Return type:	ndarray, (3,)

Notes

• Input RGB colourspace matrix is in domain [0, 1].
• Input illuminant_RGB xy chromaticity coordinates are in domain [0, 1].
• Input illuminant_XYZ xy chromaticity coordinates are in domain [0, 1].
• Output CIE XYZ colourspace matrix is in domain [0, 1].

Examples

>>> RGB = np.array([0.17303501, 0.08211033, 0.05672498])
>>> illuminant_RGB = (0.31271, 0.32902)
>>> illuminant_XYZ = (0.34567, 0.35850)
>>> chromatic_adaptation_method = 'Bradford'
>>> to_XYZ = np.array([
...     [0.41238656, 0.35759149, 0.18045049],
...     [0.21263682, 0.71518298, 0.0721802],
...     [0.01933062, 0.11919716, 0.95037259]])
>>> RGB_to_XYZ(
...     RGB,
...     illuminant_RGB,
...     illuminant_XYZ,
...     to_XYZ,
...     chromatic_adaptation_method)  
array([ 0.1151847...,  0.1008    ,  0.0508937...])

colour.models.RGB_to_RGB(RGB, input_colourspace, output_colourspace, chromatic_adaptation_method=u'CAT02')¶

Converts from given input RGB colourspace to output RGB colourspace using given chromatic adaptation method.

Parameters:	RGB (array_like, (3,)) – RGB colourspace matrix. input_colourspace (RGB_Colourspace) – RGB input colourspace. output_colourspace (RGB_Colourspace) – RGB output colourspace. chromatic_adaptation_method (unicode, optional) – (‘XYZ Scaling’, ‘Bradford’, ‘Von Kries’, ‘Fairchild’, ‘CAT02’) Chromatic adaptation method. (3,) (ndarray,) – RGB colourspace matrix.

Notes

• RGB colourspace matrices are in domain [0, 1].

Examples

>>> from colour import sRGB_COLOURSPACE, PROPHOTO_RGB_COLOURSPACE
>>> RGB = np.array([0.35521588, 0.41, 0.24177934])
>>> RGB_to_RGB(
...     RGB,
...     sRGB_COLOURSPACE,
...     PROPHOTO_RGB_COLOURSPACE)  
array([ 0.3579334...,  0.4007138...,  0.2615704...])

colour.models.XYZ_to_sRGB(XYZ, illuminant=(0.31271, 0.32902), chromatic_adaptation_method=u'CAT02', transfer_function=True)¶

Converts from CIE XYZ colourspace to sRGB colourspace.

Parameters:	XYZ (array_like, (3,)) – CIE XYZ colourspace matrix. illuminant (array_like, optional) – Source illuminant chromaticity coordinates. chromatic_adaptation_method (unicode, optional) – (‘XYZ Scaling’, ‘Bradford’, ‘Von Kries’, ‘Fairchild’, ‘CAT02’) Chromatic adaptation method. transfer_function (bool, optional) – Apply sRGB transfer function.
Returns:	sRGB colour matrix.
Return type:	ndarray, (3,)

Notes

• Input CIE XYZ colourspace matrix is in domain [0, 1].

Examples

>>> XYZ = np.array([0.1180583421, 0.1034, 0.0515089229])
>>> XYZ_to_sRGB(XYZ)  
array([ 0.4822488...,  0.3165197...,  0.2207051...])

colour.models.spectral_to_aces_relative_exposure_values(spd, illuminant=<colour.colorimetry.spectrum.SpectralPowerDistribution object at 0x102cf8610>)¶

Converts given spectral power distribution to ACES RGB colourspace relative exposure values.

Parameters:	spd (SpectralPowerDistribution) – Spectral power distribution. illuminant (SpectralPowerDistribution, optional) – Illuminant spectral power distribution.
Returns:	ACES RGB colourspace relative exposure values matrix.
Return type:	ndarray, (3,)

Notes

• Output ACES RGB colourspace relative exposure values matrix is in domain [0, 1].

See also

colour.colorimetry.tristimulus.spectral_to_XYZ()

References

Examples

>>> from colour import COLOURCHECKERS_SPDS
>>> spd = COLOURCHECKERS_SPDS['ColorChecker N Ohta']['dark skin']
>>> spectral_to_aces_relative_exposure_values(spd)  
array([ 0.1187697...,  0.0870866...,  0.0589442...])