colour.adaptation.chromatic_adaptation_inverse_CMCCAT2000#
- colour.adaptation.chromatic_adaptation_inverse_CMCCAT2000(XYZ_c: ArrayLike, XYZ_w: ArrayLike, XYZ_wr: ArrayLike, L_A1: ArrayLike, L_A2: ArrayLike, surround: InductionFactors_CMCCAT2000 = VIEWING_CONDITIONS_CMCCAT2000['Average']) NDArrayFloat [source]#
Adapt given stimulus corresponding colour CIE XYZ tristimulus values from reference viewing conditions to test viewing conditions using CMCCAT2000 inverse chromatic adaptation model.
- Parameters:
XYZ_c (ArrayLike) – CIE XYZ tristimulus values of the stimulus to adapt.
XYZ_w (ArrayLike) – Test viewing condition CIE XYZ tristimulus values of the whitepoint.
XYZ_wr (ArrayLike) – Reference viewing condition CIE XYZ tristimulus values of the whitepoint.
L_A1 (ArrayLike) – Luminance of test adapting field \(L_{A1}\) in \(cd/m^2\).
L_A2 (ArrayLike) – Luminance of reference adapting field \(L_{A2}\) in \(cd/m^2\).
surround (InductionFactors_CMCCAT2000) – Surround viewing conditions induction factors.
- Returns:
CIE XYZ_c tristimulus values of the adapted stimulus.
- Return type:
Notes
Domain
Scale - Reference
Scale - 1
XYZ_c
[0, 100]
[0, 1]
XYZ_w
[0, 100]
[0, 1]
XYZ_wr
[0, 100]
[0, 1]
Range
Scale - Reference
Scale - 1
XYZ
[0, 100]
[0, 1]
References
Examples
>>> XYZ_c = np.array([19.53, 23.07, 24.97]) >>> XYZ_w = np.array([111.15, 100.00, 35.20]) >>> XYZ_wr = np.array([94.81, 100.00, 107.30]) >>> L_A1 = 200 >>> L_A2 = 200 >>> chromatic_adaptation_inverse_CMCCAT2000(XYZ_c, XYZ_w, XYZ_wr, L_A1, L_A2) ... array([ 22.4839876..., 22.7419485..., 8.5393392...])