colour.adaptation.chromatic_adaptation_CIE1994#
- colour.adaptation.chromatic_adaptation_CIE1994(XYZ_1: ArrayLike, xy_o1: ArrayLike, xy_o2: ArrayLike, Y_o: ArrayLike, E_o1: ArrayLike, E_o2: ArrayLike, n: ArrayLike = 1) NDArrayFloat [source]#
Adapt given stimulus CIE XYZ_1 tristimulus values from test viewing conditions to reference viewing conditions using CIE 1994 chromatic adaptation model.
- Parameters
XYZ_1 (ArrayLike) – CIE XYZ tristimulus values of test sample / stimulus.
xy_o1 (ArrayLike) – Chromaticity coordinates \(x_{o1}\) and \(y_{o1}\) of test illuminant and background.
xy_o2 (ArrayLike) – Chromaticity coordinates \(x_{o2}\) and \(y_{o2}\) of reference illuminant and background.
Y_o (ArrayLike) – Luminance factor \(Y_o\) of achromatic background as percentage normalised to domain [18, 100] in ‘Reference’ domain-range scale.
E_o1 (ArrayLike) – Test illuminance \(E_{o1}\) in \(cd/m^2\).
E_o2 (ArrayLike) – Reference illuminance \(E_{o2}\) in \(cd/m^2\).
n (ArrayLike) – Noise component in fundamental primary system.
- Returns
Adapted CIE XYZ_2 tristimulus values of test stimulus.
- Return type
Notes
Domain
Scale - Reference
Scale - 1
XYZ_1
[0, 100]
[0, 1]
Y_o
[0, 100]
[0, 1]
Range
Scale - Reference
Scale - 1
XYZ_2
[0, 100]
[0, 1]
References
Examples
>>> XYZ_1 = np.array([28.00, 21.26, 5.27]) >>> xy_o1 = np.array([0.4476, 0.4074]) >>> xy_o2 = np.array([0.3127, 0.3290]) >>> Y_o = 20 >>> E_o1 = 1000 >>> E_o2 = 1000 >>> chromatic_adaptation_CIE1994(XYZ_1, xy_o1, xy_o2, Y_o, E_o1, E_o2) ... array([ 24.0337952..., 21.1562121..., 17.6430119...])