colour.XYZ_to_LLAB

colour.XYZ_to_LLAB(XYZ, XYZ_0, Y_b, L, surround=LLAB_InductionFactors(D=1, F_S=3, F_L=1, F_C=1))[source]

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

Parameters:
  • XYZ (array_like) – CIE XYZ tristimulus values of test sample / stimulus.
  • XYZ_0 (array_like) – CIE XYZ tristimulus values of reference white.
  • Y_b (numeric or array_like) – Luminance factor of the background in \(cd/m^2\).
  • L (numeric or array_like) – Absolute luminance \(L\) of reference white in \(cd/m^2\).
  • surround (LLAB_InductionFactors, optional) – Surround viewing conditions induction factors.
Returns:

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

Return type:

LLAB_Specification

Notes

Domain Scale - Reference Scale - 1
XYZ [0, 100] [0, 1]
XYZ_0 [0, 100] [0, 1]
Range Scale - Reference Scale - 1
LLAB_Specification.h [0, 360] [0, 1]

References

[Fairchild2013x], [Luo1996b], [Luo1996c]

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 = LLAB_VIEWING_CONDITIONS['ref_average_4_minus']
>>> XYZ_to_LLAB(XYZ, XYZ_0, Y_b, L, surround)  # doctest: +ELLIPSIS
LLAB_Specification(J=37.3668650..., C=0.0089496..., h=270..., s=0.0002395..., M=0.0190185..., HC=None, a=..., b=-0.0190185...)