# colour.colorimetry.illuminants Module¶

## Illuminants¶

Defines CIE illuminants computation related objects:

Illuminants Jupyter Notebook colour.colorimetry.dataset.illuminants.d_illuminants_s_spds, colour.colorimetry.spectrum.SpectralPowerDistribution

colour.colorimetry.illuminants.D_illuminant_relative_spd(xy)[source]

Returns the relative spectral power distribution of given CIE Standard Illuminant D Series using given xy chromaticity coordinates.

References

 [1] Wyszecki, G., & Stiles, W. S. (2000). CIE Method of Calculating D-Illuminants. In Color Science: Concepts and Methods, Quantitative Data and Formulae (pp. 145–146). Wiley. ISBN:978-0471399186
 [2] Lindbloom, B. (2007). Spectral Power Distribution of a CIE D-Illuminant. Retrieved April 05, 2014, from http://www.brucelindbloom.com/Eqn_DIlluminant.html
Parameters: xy (array_like) – xy chromaticity coordinates. CIE Standard Illuminant D Series relative spectral power distribution. SpectralPowerDistribution

Examples

>>> xy = np.array([0.34570, 0.35850])
>>> print(D_illuminant_relative_spd(xy))
SpectralPowerDistribution('CIE Standard Illuminant D Series', (300.0, 830.0, 10.0))

colour.colorimetry.illuminants.CIE_standard_illuminant_A_function(wl)[source]

CIE Standard Illuminant A is intended to represent typical, domestic, tungsten-filament lighting. Its relative spectral power distribution is that of a Planckian radiator at a temperature of approximately 2856 K. CIE Standard Illuminant A should be used in all applications of colorimetry involving the use of incandescent lighting, unless there are specific reasons for using a different illuminant.

Parameters: wl (array_like) – Wavelength to evaluate the function at. CIE Standard Illuminant A value at given wavelength. ndarray

References

 [1] CIE TC 1-48. (2004). 3.1 Recommendations concerning standard physical data of illuminants. In CIE 015:2004 Colorimetry, 3rd Edition (pp. 12–13). ISBN:978-3-901-90633-6

Examples

>>> wl = np.array([560, 580, 581.5])
>>> CIE_standard_illuminant_A_function(wl)
array([ 100.        ,  114.4363383...,  115.5285063...])