colour.XYZ_to_LLAB#

Compute the :math:`LLAB(l:c)` colour appearance model correlates.

Parameters:

XYZ (_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) – CIE XYZ tristimulus values of test sample / stimulus.
XYZ_0 (_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) – CIE XYZ tristimulus values of reference white.
Y_b (_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) – Luminance factor of the background in \(cd/m^2\).
L (_SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | bool | int | float | complex | str | bytes | _NestedSequence[bool | int | float | complex | str | bytes]) – Absolute luminance \(L\) of reference white in \(cd/m^2\).
surround (InductionFactors_LLAB) – Surround viewing conditions induction factors.

Returns:

:math:`LLAB(l:c)` colour appearance model specification.

Return type:

colour.CAM_Specification_LLAB

Notes

Domain	Scale - Reference	Scale - 1
`XYZ`	[0, 100]	[0, 1]
`XYZ_0`	[0, 100]	[0, 1]

Range	Scale - Reference	Scale - 1
`CAM_Specification_LLAB.h`	[0, 360]	[0, 1]

References

[Fai13h], [LLK96], [LM96]

Examples

>>> XYZ = np.array([19.01, 20.00, 21.78])
>>> XYZ_0 = np.array([95.05, 100.00, 108.88])
>>> Y_b = 20.0
>>> L = 318.31
>>> surround = VIEWING_CONDITIONS_LLAB["ref_average_4_minus"]
>>> XYZ_to_LLAB(XYZ, XYZ_0, Y_b, L, surround)  
CAM_Specification_LLAB(J=37.3668650..., C=0.0089496..., h=270..., s=0.0002395..., M=0.0190185..., HC=None, a=..., b=-0.0190185...)