colour.XYZ_to_sCAM

colour.XYZ_to_sCAM(XYZ: Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100], XYZ_w: Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100], L_A: ArrayLike, Y_b: ArrayLike, surround: InductionFactors_sCAM = VIEWING_CONDITIONS_sCAM['Average'], discount_illuminant: bool = False) → Annotated[CAM_Specification_sCAM, 100, 100, 360, 100, 100, 400, 100, 100, 100, 100]

Compute the sCAM colour appearance model correlates from the specified CIE XYZ tristimulus values.

Parameters:

• XYZ (Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100]) – CIE XYZ tristimulus values of test sample / stimulus.

• XYZ_w (Annotated[_Buffer | _SupportsArray[dtype[Any]] | _NestedSequence[_SupportsArray[dtype[Any]]] | complex | bytes | str | _NestedSequence[complex | bytes | str], 100]) – CIE XYZ tristimulus values of reference white.

• L_A (ArrayLike) – 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 (ArrayLike) – Luminous factor of background \(Y_b\) such as \(Y_b = 100 \times L_b / L_w\) where \(L_w\) is the luminance of the light source and \(L_b\) is the luminance of the background. For viewing images, \(Y_b\) can be the average \(Y\) value for the pixels in the entire image, or frequently, a \(Y\) value of 20, approximating an \(L^*\) of 50 is used.

• surround (InductionFactors_sCAM) – Surround viewing conditions induction factors.

• discount_illuminant (bool) – Truth value indicating if the illuminant should be discounted.

Returns:

sCAM colour appearance model specification.

Return type:

colour.CAM_Specification_sCAM

Notes

Domain	Scale - Reference	Scale - 1
XYZ	100	1
XYZ_w	100	1

Range	Scale - Reference	Scale - 1
specification.J	100	1
specification.C	100	1
specification.h	360	1
specification.Q	100	1
specification.M	100	1
specification.H	400	1
specification.HC	None	None
specification.V	100	1
specification.K	100	1
specification.W	100	1
specification.D	100	1

References

[LL24]

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 = VIEWING_CONDITIONS_sCAM["Average"]
>>> XYZ_to_sCAM(XYZ, XYZ_w, L_A, Y_b, surround)
CAM_Specification_sCAM(J=49.9795668..., C=0.0140531..., h=328.2724924..., Q=195.23024234..., M=0.0050244..., H=363.6013437..., HC=None, V=49.9795727..., K=50.0204272..., W=34.9734327..., D=65.0265672...)