colour.characterisation.training_data_sds_to_XYZ#

colour.characterisation.training_data_sds_to_XYZ(training_data: colour.colorimetry.spectrum.MultiSpectralDistributions, cmfs: colour.colorimetry.spectrum.MultiSpectralDistributions, illuminant: colour.colorimetry.spectrum.SpectralDistribution, chromatic_adaptation_transform: Optional[Union[Literal['Bianco 2010', 'Bianco PC 2010', 'Bradford', 'CAT02 Brill 2008', 'CAT02', 'CAT16', 'CMCCAT2000', 'CMCCAT97', 'Fairchild', 'Sharp', 'Von Kries', 'XYZ Scaling'], str]] = 'CAT02') numpy.ndarray[source]#

Convert given training data to CIE XYZ tristimulus values using given illuminant and given standard observer colour matching functions.

Parameters
Returns

Training data CIE XYZ tristimulus values.

Return type

numpy.ndarray

Examples

>>> from colour import MSDS_CMFS
>>> path = os.path.join(
...     RESOURCES_DIRECTORY_RAWTOACES,
...     'CANON_EOS_5DMark_II_RGB_Sensitivities.csv')
>>> cmfs = MSDS_CMFS['CIE 1931 2 Degree Standard Observer']
>>> 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()
>>> training_data_sds_to_XYZ(training_data, cmfs, illuminant)[:5]
... 
array([[ 0.0174353...,  0.0179504...,  0.0196109...],
       [ 0.0855607...,  0.0895735...,  0.0901703...],
       [ 0.7455880...,  0.7817549...,  0.7834356...],
       [ 0.1900528...,  0.1995   ...,  0.2012606...],
       [ 0.5626319...,  0.5914544...,  0.5894500...]])