colour.recovery.RGB_to_sd_Smits1999#

colour.recovery.RGB_to_sd_Smits1999(RGB: ArrayLike) → SpectralDistribution[source]#

Recover the spectral distribution of given RGB colourspace array using Smits (1999) method.

Parameters:: RGB (ArrayLike) – RGB colourspace array to recover the spectral distribution from.
Returns:: Recovered spectral distribution.
Return type:: colour.SpectralDistribution

Notes

Domain	Scale - Reference	Scale - 1
`RGB`	[0, 1]	[0, 1]

References

[Smi99]

Examples

>>> import numpy as np
>>> from colour import MSDS_CMFS, SDS_ILLUMINANTS, SpectralShape
>>> from colour.colorimetry import sd_to_XYZ_integration
>>> from colour.utilities import numpy_print_options
>>> XYZ = np.array([0.20654008, 0.12197225, 0.05136952])
>>> RGB = XYZ_to_RGB_Smits1999(XYZ)
>>> cmfs = (
...     MSDS_CMFS["CIE 1931 2 Degree Standard Observer"]
...     .copy()
...     .align(SpectralShape(360, 780, 10))
... )
>>> illuminant = SDS_ILLUMINANTS["E"].copy().align(cmfs.shape)
>>> sd = RGB_to_sd_Smits1999(RGB)
>>> with numpy_print_options(suppress=True):
...     sd  
...
SpectralDistribution([[ 380.        ,    0.0787830...],
                      [ 417.7778    ,    0.0622018...],
                      [ 455.5556    ,    0.0446206...],
                      [ 493.3333    ,    0.0352220...],
                      [ 531.1111    ,    0.0324149...],
                      [ 568.8889    ,    0.0330105...],
                      [ 606.6667    ,    0.3207115...],
                      [ 644.4444    ,    0.3836164...],
                      [ 682.2222    ,    0.3836164...],
                      [ 720.        ,    0.3835649...]],
                     LinearInterpolator,
                     {},
                     Extrapolator,
                     {'method': 'Constant', 'left': None, 'right': None})
>>> sd_to_XYZ_integration(sd, cmfs, illuminant) / 100  
array([ 0.1894770...,  0.1126470...,  0.0474420...])