colour.XYZ_to_LLAB#

colour.XYZ_to_LLAB(XYZ: Domain100, XYZ_0: Domain100, Y_b: ArrayLike, L: ArrayLike, surround: InductionFactors_LLAB = VIEWING_CONDITIONS_LLAB['Reference Samples & Images, Average Surround, Subtending < 4']) → Annotated[CAM_Specification_LLAB, 360][source]#

Compute the :math:`LLAB(l:c)` colour appearance model correlates from the specified CIE XYZ tristimulus values.

Parameters:

  • XYZ (Domain100) – CIE XYZ tristimulus values of test sample / stimulus.

  • XYZ_0 (Domain100) – CIE XYZ tristimulus values of reference white.

  • Y_b (ArrayLike) – Luminance factor of the background in \(cd/m^2\).

  • L (ArrayLike) – 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

100

1

XYZ_0

100

1

Range

Scale - Reference

Scale - 1

specification.h

360

1

References

[Fai13h], [LLK96], [LM96]

Examples

Fairchild (2013) Table 14.3 Case 4 (chromatic stimulus under illuminant A reference white, mesopic luminance):

>>> XYZ = np.array([19.01, 20.00, 21.78])
>>> XYZ_0 = np.array([109.85, 100.00, 35.58])
>>> Y_b = 20.0
>>> L = 31.83
>>> surround = VIEWING_CONDITIONS_LLAB["ref_average_4_minus"]
>>> XYZ_to_LLAB(XYZ, XYZ_0, Y_b, L, surround)
CAM_Specification_LLAB(J=np.float64(39.81475...), C=np.float64(29.345046...), h=np.float64(271.852666...), s=np.float64(0.737039...), M=np.float64(54.593098...), HC=None, a=np.float64(1.764967...), b=np.float64(-54.564560...))
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