colour.colorimetry.whiteness_CIE2004¶
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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.
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
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...])