colour.characterisation.training_data_sds_to_RGB#

colour.characterisation.training_data_sds_to_RGB(training_data: colour.colorimetry.spectrum.MultiSpectralDistributions, sensitivities: colour.characterisation.cameras.RGB_CameraSensitivities, illuminant: colour.colorimetry.spectrum.SpectralDistribution) → Tuple[numpy.ndarray, numpy.ndarray][source]#

Convert given training data to RGB tristimulus values using given illuminant and given camera RGB spectral sensitivities.

Parameters

training_data (colour.colorimetry.spectrum.MultiSpectralDistributions) – Training data multi-spectral distributions.
sensitivities (colour.characterisation.cameras.RGB_CameraSensitivities) – Camera RGB spectral sensitivities.
illuminant (colour.colorimetry.spectrum.SpectralDistribution) – Illuminant spectral distribution.

Returns

Tuple of training data RGB tristimulus values and white balance multipliers.

Return type

tuple

Examples

>>> path = os.path.join(
...     RESOURCES_DIRECTORY_RAWTOACES,
...     'CANON_EOS_5DMark_II_RGB_Sensitivities.csv')
>>> sensitivities = sds_and_msds_to_msds(
...     read_sds_from_csv_file(path).values())
>>> illuminant = normalise_illuminant(
...     SDS_ILLUMINANTS['D55'], sensitivities)
>>> training_data = read_training_data_rawtoaces_v1()
>>> RGB, RGB_w = training_data_sds_to_RGB(
...     training_data, sensitivities, illuminant)
>>> RGB[:5]  
array([[ 0.0207582...,  0.0196857...,  0.0213935...],
       [ 0.0895775...,  0.0891922...,  0.0891091...],
       [ 0.7810230...,  0.7801938...,  0.7764302...],
       [ 0.1995   ...,  0.1995   ...,  0.1995   ...],
       [ 0.5898478...,  0.5904015...,  0.5851076...]])
>>> RGB_w  
array([ 2.3414154...,  1.        ,  1.5163375...])

colour.characterisation.normalise_illuminant

colour.characterisation.training_data_sds_to_XYZ