colour.colorimetry.correction Module

Spectral Bandpass Dependence Correction

Defines objects to perform spectral bandpass dependence correction.

The following correction methods are available:

colour.colorimetry.correction.bandpass_correction_stearns1988(spd)[source]

Implements spectral bandpass dependence correction on given spectral power distribution using Stearns and Stearns (1988) method.

References

[1]Stephen Westland, Caterina Ripamonti, Vien Cheung, Computational Colour Science Using MATLAB, 2nd Edition, The Wiley-IS&T Series in Imaging Science and Technology, published July 2012, ISBN-13: 978-0-470-66569-5, page 38.
Parameters:spd (SpectralPowerDistribution) – Spectral power distribution.
Returns:Spectral bandpass dependence corrected spectral power distribution.
Return type:SpectralPowerDistribution

Examples

>>> from colour import SpectralPowerDistribution
>>> data = {510: 49.67, 520: 69.59, 530: 81.73, 540: 88.19}
>>> spd = SpectralPowerDistribution('Spd', data)
>>> corrected_spd = bandpass_correction_stearns1988(spd)
>>> corrected_spd.values  
array([ 48.01664   ,  70.3729688...,  82.0919506...,  88.72618   ])
colour.colorimetry.correction.BANDPASS_CORRECTION_METHODS = CaseInsensitiveMapping({u'Stearns 1988': <function bandpass_correction_stearns1988 at 0x102e036e0>})

Supported spectral bandpass dependence correction methods.

BANDPASS_CORRECTION_METHODS : dict
(‘Stearns 1988’,)
colour.colorimetry.correction.bandpass_correction(spd, method=u'Stearns 1988')[source]

Implements spectral bandpass dependence correction on given spectral power distribution using given method.

Parameters:
  • spd (SpectralPowerDistribution) – Spectral power distribution.
  • method (unicode) – (‘Stearns 1988’,) Correction method.
Returns:

Spectral bandpass dependence corrected spectral power distribution.

Return type:

SpectralPowerDistribution