colour.XYZ_to_CAM16¶
-
colour.
XYZ_to_CAM16
(XYZ, XYZ_w, L_A, Y_b, surround=CIECAM02_InductionFactors(F=1, c=0.69, N_c=1), discount_illuminant=False)[source]¶ Computes the CAM16 colour appearance model correlates from given CIE XYZ tristimulus values.
This is the forward implementation.
- Parameters
XYZ (array_like) – CIE XYZ tristimulus values of test sample / stimulus.
XYZ_w (array_like) – CIE XYZ tristimulus values of reference white.
L_A (numeric or array_like) – Adapting field luminance \(L_A\) in \(cd/m^2\), (often taken to be 20% of the luminance of a white object in the scene).
Y_b (numeric or array_like) – Relative luminance of background \(Y_b\) in \(cd/m^2\).
surround (CAM16_InductionFactors, optional) – Surround viewing conditions induction factors.
discount_illuminant (bool, optional) – Truth value indicating if the illuminant should be discounted.
- Returns
CAM16 colour appearance model specification.
- Return type
Notes
Domain
Scale - Reference
Scale - 1
XYZ
[0, 100]
[0, 1]
XYZ_w
[0, 100]
[0, 1]
Range
Scale - Reference
Scale - 1
CAM16_specification.J
[0, 100]
[0, 1]
CAM16_specification.C
[0, 100]
[0, 1]
CAM16_specification.h
[0, 360]
[0, 1]
CAM16_specification.s
[0, 100]
[0, 1]
CAM16_specification.Q
[0, 100]
[0, 1]
CAM16_specification.M
[0, 100]
[0, 1]
CAM16_specification.H
[0, 360]
[0, 1]
References
Examples
>>> XYZ = np.array([19.01, 20.00, 21.78]) >>> XYZ_w = np.array([95.05, 100.00, 108.88]) >>> L_A = 318.31 >>> Y_b = 20.0 >>> surround = CAM16_VIEWING_CONDITIONS['Average'] >>> XYZ_to_CAM16(XYZ, XYZ_w, L_A, Y_b, surround) CAM16_Specification(J=41.7312079..., C=0.1033557..., h=217.0679597..., s=2.3450150..., Q=195.3717089..., M=0.1074367..., H=275.5949861..., HC=None)