colour.temperature.uv_to_CCT_Ohno2013#

colour.temperature.uv_to_CCT_Ohno2013(uv: ArrayLike, cmfs: Optional[MultiSpectralDistributions] = None, start: Optional[float] = None, end: Optional[float] = None, count: Optional[int] = None, iterations: Optional[int] = None) → ndarray[source]#

Return the correlated colour temperature \(T_{cp}\) and \(\Delta_{uv}\) from given CIE UCS colourspace uv chromaticity coordinates, colour matching functions and temperature range using Ohno (2013) method.

The iterations parameter defines the calculations’ precision: The higher its value, the more planckian tables will be generated through cascade expansion in order to converge to the exact solution.

Parameters:

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

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

  • start (Optional[float]) – Temperature range start in kelvin degrees, default to 1000.

  • end (Optional[float]) – Temperature range end in kelvin degrees, default to 100000.

  • count (Optional[int]) – Temperatures count/samples in the planckian tables, default to 10.

  • iterations (Optional[int]) – Number of planckian tables to generate, default to 6.

Returns:

Correlated colour temperature \(T_{cp}\), \(\Delta_{uv}\).

Return type:

numpy.ndarray

References

[Ohn14]

Examples

>>> from pprint import pprint
>>> from colour import MSDS_CMFS, SPECTRAL_SHAPE_DEFAULT
>>> cmfs = (
...     MSDS_CMFS["CIE 1931 2 Degree Standard Observer"]
...     .copy()
...     .align(SPECTRAL_SHAPE_DEFAULT)
... )
>>> uv = np.array([0.1978, 0.3122])
>>> uv_to_CCT_Ohno2013(uv, cmfs)  
array([  6.50747...e+03,   3.22334...e-03])