colour.dominant_wavelength

colour.dominant_wavelength(xy, xy_n, cmfs=XYZ_ColourMatchingFunctions(name='CIE 1931 2 Degree Standard Observer', ...), reverse=False)[source]

Returns the dominant wavelength \(\lambda_d\) for given colour stimulus \(xy\) and the related \(xy_wl\) first and \(xy_{cw}\) second intersection coordinates with the spectral locus.

In the eventuality where the \(xy_wl\) first intersection coordinates are on the line of purples, the complementary wavelength will be computed in lieu.

The complementary wavelength is indicated by a negative sign and the \(xy_{cw}\) second intersection coordinates which are set by default to the same value than \(xy_wl\) first intersection coordinates will be set to the complementary dominant wavelength intersection coordinates with the spectral locus.

Parameters:
  • xy (array_like) – Colour stimulus xy chromaticity coordinates.
  • xy_n (array_like) – Achromatic stimulus xy chromaticity coordinates.
  • cmfs (XYZ_ColourMatchingFunctions, optional) – Standard observer colour matching functions.
  • reverse (bool, optional) – Reverse the computation direction to retrieve the complementary wavelength.
Returns:

Dominant wavelength, first intersection point xy chromaticity coordinates, second intersection point xy chromaticity coordinates.
Return type:

tuple

References

Examples

Dominant wavelength computation:

>>> from pprint import pprint
>>> xy = np.array([0.26415, 0.37770])
>>> xy_n = np.array([0.31270, 0.32900])
>>> cmfs = CMFS['CIE 1931 2 Degree Standard Observer']
>>> pprint(dominant_wavelength(xy, xy_n, cmfs))  
(array(504...),
 array([ 0.0036969...,  0.6389577...]),
 array([ 0.0036969...,  0.6389577...]))

Complementary dominant wavelength is returned if the first intersection is located on the line of purples:

>>> xy = np.array([0.35000, 0.25000])
>>> pprint(dominant_wavelength(xy, xy_n, cmfs))  
(array(-520...),
 array([ 0.4133314...,  0.1158663...]),
 array([ 0.0743553...,  0.8338050...]))