colour.adaptation.chromatic_adaptation_reverse_CMCCAT2000¶

colour.adaptation.chromatic_adaptation_reverse_CMCCAT2000(XYZ_c, XYZ_w, XYZ_wr, L_A1, L_A2, surround=CMCCAT2000_InductionFactors(F=1))[source]¶

Adapts given stimulus corresponding colour CIE XYZ tristimulus values from reference viewing conditions to test viewing conditions using CMCCAT2000 reverse chromatic adaptation model.

Parameters:	XYZ_c (array_like) – CIE XYZ tristimulus values of the stimulus to adapt. XYZ_w (array_like) – Test viewing condition CIE XYZ tristimulus values of the whitepoint. XYZ_wr (array_like) – Reference viewing condition CIE XYZ tristimulus values of the whitepoint. L_A1 (numeric or array_like) – Luminance of test adapting field \(L_{A1}\) in \(cd/m^2\). L_A2 (numeric or array_like) – Luminance of reference adapting field \(L_{A2}\) in \(cd/m^2\). surround (CMCCAT2000_InductionFactors, optional) – Surround viewing conditions induction factors.
Returns:	CIE XYZ_c tristimulus values of the adapted stimulus.
Return type:	ndarray

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

[LLRH02], [WRC12a]

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_reverse_CMCCAT2000(XYZ_c, XYZ_w, XYZ_wr, L_A1,
...                                         L_A2)
... # doctest: +ELLIPSIS
array([ 22.4839876...,  22.7419485...,   8.5393392...])