colour.colorimetry.whiteness_CIE2004

colour.colorimetry.whiteness_CIE2004(xy, Y, xy_n, observer='CIE 1931 2 Degree Standard Observer')[source]

Returns the whiteness \(W\) or \(W_{10}\) and tint \(T\) or \(T_{10}\) of given sample CIE xy chromaticity coordinates using CIE 2004 method.

Parameters:
  • xy (array_like) – Chromaticity coordinates CIE xy of sample.
  • Y (numeric or array_like) – Tristimulus \(Y\) value of sample.
  • xy_n (array_like) – Chromaticity coordinates xy_n of perfect diffuser.
  • observer (unicode, optional) – {‘CIE 1931 2 Degree Standard Observer’, ‘CIE 1964 10 Degree Standard Observer’}, CIE Standard Observer used for computations, tint \(T\) or \(T_{10}\) value is dependent on viewing field angular subtense.
Returns:

Whiteness \(W\) or \(W_{10}\) and tint \(T\) or \(T_{10}\) of given sample.

Return type:

ndarray

Notes

Domain Scale - Reference Scale - 1
Y [0, 100] [0, 1]
Range Scale - Reference Scale - 1
WT [0, 100] [0, 1]
  • This method may be used only for samples whose values of \(W\) or \(W_{10}\) lie within the following limits: greater than 40 and less than 5Y - 280, or 5Y10 - 280.
  • This method may be used only for samples whose values of \(T\) or \(T_{10}\) lie within the following limits: greater than -4 and less than +2.
  • Output whiteness \(W\) or \(W_{10}\) values larger than 100 indicate a bluish white while values smaller than 100 indicate a yellowish white.
  • Positive output tint \(T\) or \(T_{10}\) values indicate a greener tint while negative values indicate a redder tint.

References

[CIETC1-482004k]

Examples

>>> import numpy as np
>>> xy = np.array([0.3167, 0.3334])
>>> xy_n = np.array([0.3139, 0.3311])
>>> whiteness_CIE2004(xy, 100, xy_n)  # doctest: +ELLIPSIS
array([ 93.85...,  -1.305...])