# 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 xy chromaticity coordinates using CIE 2004 method.

Parameters: xy (array_like) – Chromaticity coordinates 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. Whiteness $$W$$ or $$W_{10}$$ and tint $$T$$ or $$T_{10}$$ of given sample. 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

[CIET14804i]

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...])