colour.colorimetry.whiteness_Berger1959#

colour.colorimetry.whiteness_Berger1959(XYZ: ArrayLike, XYZ_0: ArrayLike) → NDArrayFloat[source]#

Return the whiteness index \(WI\) of given sample CIE XYZ tristimulus values using Berger (1959) method.

Parameters:

XYZ (ArrayLike) – CIE XYZ tristimulus values of the sample.
XYZ_0 (ArrayLike) – CIE XYZ tristimulus values of the reference white.

Returns:

Whiteness \(WI\).

Return type:

np.float or numpy.ndarray

Notes

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

Range	Scale - Reference	Scale - 1
`WI`	[0, 100]	[0, 1]

Whiteness \(WI\) values larger than 33.33 indicate a bluish white and values smaller than 33.33 indicate a yellowish white.

References

[XRitePantone12]

Examples

>>> import numpy as np
>>> XYZ = np.array([95.00000000, 100.00000000, 105.00000000])
>>> XYZ_0 = np.array([94.80966767, 100.00000000, 107.30513595])
>>> whiteness_Berger1959(XYZ, XYZ_0)  
30.3638017...