colour.temperature.xy_to_CCT_CIE_D

colour.temperature.xy_to_CCT_CIE_D(xy: ArrayLike, optimisation_kwargs: dict | None = None) → NDArrayFloat

Compute the correlated colour temperature \(T_{cp}\) of a CIE Illuminant D Series from the specified CIE xy chromaticity coordinates.

Parameters:

• xy (ArrayLike) – CIE xy chromaticity coordinates.

• optimisation_kwargs (dict | None) – Inversion parameters forwarded to colour.temperature.x0_CCT_grid() and colour.temperature.solve_CCT_Newton(). Accepted keys are samples (grid density for the initial guess, default colour.temperature.CCT_INVERSION_GRID_SAMPLES), newton_iterations, backtrack_iterations and tolerance (forwarded to solve_CCT_Newton()).

Returns:

Correlated colour temperature \(T_{cp}\).

Return type:

numpy.ndarray

Warning

The CIE Illuminant D Series method does not provide an analytical inverse transformation to compute the correlated colour temperature \(T_{cp}\) from the specified CIE xy chromaticity coordinates. The current implementation seeds a damped Gauss-Newton iteration with a nearest-neighbour lookup against a coarse grid sampled from the analytical forward, vectorised across all input samples.

References

[WS00k]

Examples

>>> xy_to_CCT_CIE_D([0.31270775, 0.32911283])
np.float64(6504.389564...)