colour.XYZ_to_Hunter_Rdab#

colour.XYZ_to_Hunter_Rdab(XYZ: ArrayLike, XYZ_n: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB['CIE 1931 2 Degree Standard Observer']['D65'].XYZ_n, K_ab: ArrayLike = TVS_ILLUMINANTS_HUNTERLAB['CIE 1931 2 Degree Standard Observer']['D65'].K_ab) → NDArrayFloat[source]#

Convert from CIE XYZ tristimulus values to Hunter Rd,a,b colour scale.

Parameters:

XYZ (ArrayLike) – CIE XYZ tristimulus values.
XYZ_n (ArrayLike) – Reference illuminant tristimulus values.
K_ab (ArrayLike) – Reference illuminant chromaticity coefficients, if K_ab is set to None it will be computed using colour.XYZ_to_K_ab_HunterLab1966().

Returns:

Hunter Rd,a,b colour scale array.

Return type:

numpy.ndarray

Notes

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

Range	Scale - Reference	Scale - 1
`R_d_ab`	`R_d` : [0, 100] `a_Rd` : [-100, 100] `b_Rd` : [-100, 100]	`R_d` : [0, 1] `a_Rd` : [-1, 1] `b_Rd` : [-1, 1]

Range

Scale - Reference

Scale - 1

R_d_ab

R_d : [0, 100]

a_Rd : [-100, 100]

b_Rd : [-100, 100]

R_d : [0, 1]

a_Rd : [-1, 1]

b_Rd : [-1, 1]

References

[HunterLab12]

Examples

>>> import numpy as np
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952]) * 100
>>> D65 = TVS_ILLUMINANTS_HUNTERLAB["CIE 1931 2 Degree Standard Observer"]["D65"]
>>> XYZ_to_Hunter_Rdab(XYZ, D65.XYZ_n, D65.K_ab)
... 
array([ 12.197225 ...,  57.1253787...,  17.4624134...])