colour.XYZ_to_LLAB

colour.XYZ_to_LLAB(XYZ, XYZ_0, Y_b, L, surround=InductionFactors_LLAB(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 (InductionFactors_LLAB, optional) – Surround viewing conditions induction factors.

Returns

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

Return type

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

[Fai13e], [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...)