colour.XYZ_to_ATD95#
- colour.XYZ_to_ATD95(XYZ: ArrayLike, XYZ_0: ArrayLike, Y_0: FloatingOrArrayLike, k_1: FloatingOrArrayLike, k_2: FloatingOrArrayLike, sigma: FloatingOrArrayLike = 300) CAM_Specification_ATD95 [source]#
Compute the ATD (1995) colour vision model correlates.
- Parameters:
XYZ (ArrayLike) – CIE XYZ tristimulus values of test sample / stimulus.
XYZ_0 (ArrayLike) – CIE XYZ tristimulus values of reference white.
Y_0 (FloatingOrArrayLike) – Absolute adapting field luminance in \(cd/m^2\).
k_1 (FloatingOrArrayLike) – Application specific weight \(k_1\).
k_2 (FloatingOrArrayLike) – Application specific weight \(k_2\).
sigma (FloatingOrArrayLike) – Constant \(\sigma\) varied to predict different types of data.
- Returns:
ATD (1995) colour vision model specification.
- Return type:
Notes
Domain
Scale - Reference
Scale - 1
XYZ
[0, 100]
[0, 1]
XYZ_0
[0, 100]
[0, 1]
Range
Scale - Reference
Scale - 1
CAM_Specification_ATD95.h
[0, 360]
[0, 1]
For unrelated colors, there is only self-adaptation and \(k_1\) is set to 1.0 while \(k_2\) is set to 0.0. For related colors such as typical colorimetric applications, \(k_1\) is set to 0.0 and \(k_2\) is set to a value between 15 and 50 (Guth, 1995).
References
Examples
>>> XYZ = np.array([19.01, 20.00, 21.78]) >>> XYZ_0 = np.array([95.05, 100.00, 108.88]) >>> Y_0 = 318.31 >>> k_1 = 0.0 >>> k_2 = 50.0 >>> XYZ_to_ATD95(XYZ, XYZ_0, Y_0, k_1, k_2) CAM_Specification_ATD95(h=1.9089869..., C=1.2064060..., Q=0.1814003..., A_1=0.1787931... T_1=0.0286942..., D_1=0.0107584..., A_2=0.0192182..., T_2=0.0205377..., D_2=0.0107584...)