# colour.dominant_wavelength#

colour.dominant_wavelength(xy: ArrayLike, xy_n: ArrayLike, cmfs: = None, inverse: bool = False) [source]#

Return 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 (ArrayLike) – Colour stimulus CIE xy chromaticity coordinates.

• xy_n (ArrayLike) – Achromatic stimulus CIE xy chromaticity coordinates.

• cmfs (Optional[colour.colorimetry.spectrum.MultiSpectralDistributions]) – Standard observer colour matching functions, default to the CIE 1931 2 Degree Standard Observer.

• inverse (bool) – Inverse the computation direction to retrieve the complementary wavelength.

Returns

Dominant wavelength, first intersection point CIE xy chromaticity coordinates, second intersection point CIE xy chromaticity coordinates.

Return type

tuple

References

, [Erdb]

Examples

Dominant wavelength computation:

>>> from colour.colorimetry import MSDS_CMFS
>>> from pprint import pprint
>>> cmfs = MSDS_CMFS['CIE 1931 2 Degree Standard Observer']
>>> xy = np.array([0.54369557, 0.32107944])
>>> xy_n = np.array([0.31270000, 0.32900000])
>>> pprint(dominant_wavelength(xy, xy_n, cmfs))
(array(616...),
array([ 0.6835474...,  0.3162840...]),
array([ 0.6835474...,  0.3162840...]))

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

>>> xy = np.array([0.37605506, 0.24452225])
>>> pprint(dominant_wavelength(xy, xy_n))
(array(-509.0),
array([ 0.4572314...,  0.1362814...]),
array([ 0.0104096...,  0.7320745...]))