colour.temperature.uv_to_CCT_Planck1900

colour.temperature.uv_to_CCT_Planck1900(uv: ArrayLike, cmfs: MultiSpectralDistributions | None = None, optimisation_kwargs: dict | None = None) → NDArrayFloat

Compute the correlated colour temperature \(T_{cp}\) of a blackbody from specified CIE UCS colourspace uv chromaticity coordinates using colour matching functions.

Parameters:

• uv (ArrayLike) – CIE UCS colourspace uv chromaticity coordinates.

• cmfs (MultiSpectralDistributions | None) – Standard observer colour matching functions, default to the CIE 1931 2 Degree Standard Observer.

• 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 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

[CIET14804e]

Examples

>>> uv_to_CCT_Planck1900([0.20042808, 0.31033343])
np.float64(6504.000071...)