colour.plotting.plot_sds_in_chromaticity_diagram_CIE1960UCS

colour.plotting.plot_sds_in_chromaticity_diagram_CIE1960UCS(sds: Union[Sequence[Union[colour.colorimetry.spectrum.SpectralDistribution, colour.colorimetry.spectrum.MultiSpectralDistributions]], colour.colorimetry.spectrum.MultiSpectralDistributions], cmfs: Union[colour.colorimetry.spectrum.MultiSpectralDistributions, str, Sequence[Union[colour.colorimetry.spectrum.MultiSpectralDistributions, str]]] = 'CIE 1931 2 Degree Standard Observer', chromaticity_diagram_callable_CIE1960UCS: Callable = plot_chromaticity_diagram_CIE1960UCS, annotate_kwargs: Optional[Union[Dict, List[Dict]]] = None, plot_kwargs: Optional[Union[Dict, List[Dict]]] = None, **kwargs: Any) → Tuple[matplotlib.figure.Figure, matplotlib.axes._axes.Axes]

Plot given spectral distribution chromaticity coordinates into the CIE 1960 UCS Chromaticity Diagram.

Parameters

• sds (Union[Sequence[Union[colour.colorimetry.spectrum.SpectralDistribution, colour.colorimetry.spectrum.MultiSpectralDistributions]], colour.colorimetry.spectrum.MultiSpectralDistributions]) – Spectral distributions or multi-spectral distributions to plot. sds can be a single colour.MultiSpectralDistributions class instance, a list of colour.MultiSpectralDistributions class instances or a list of colour.SpectralDistribution class instances.

• cmfs (Union[colour.colorimetry.spectrum.MultiSpectralDistributions, str, Sequence[Union[colour.colorimetry.spectrum.MultiSpectralDistributions, str]]]) – Standard observer colour matching functions used for computing the spectral locus boundaries. cmfs can be of any type or form supported by the colour.plotting.filter_cmfs() definition.

• chromaticity_diagram_callable_CIE1960UCS (Callable) – Callable responsible for drawing the CIE 1960 UCS Chromaticity Diagram.

• annotate_kwargs (Optional[Union[Dict, List[Dict]]]) –

  Keyword arguments for the matplotlib.pyplot.annotate() definition, used to annotate the resulting chromaticity coordinates with their respective spectral distribution names. annotate_kwargs can be either a single dictionary applied to all the arrows with same settings or a sequence of dictionaries with different settings for each spectral distribution. The following special keyword arguments can also be used:

  • annotate : Whether to annotate the spectral distributions.

• plot_kwargs (Optional[Union[Dict, List[Dict]]]) –

  Keyword arguments for the matplotlib.pyplot.plot() definition, used to control the style of the plotted spectral distributions. plot_kwargs` can be either a single dictionary applied to all the plotted spectral distributions with the same settings or a sequence of dictionaries with different settings for each plotted spectral distributions. The following special keyword arguments can also be used:

  • illuminant : The illuminant used to compute the spectral distributions colours. The default is the illuminant associated with the whitepoint of the default plotting colourspace. illuminant can be of any type or form supported by the colour.plotting.filter_cmfs() definition.

  • cmfs : The standard observer colour matching functions used for computing the spectral distributions colours. cmfs can be of any type or form supported by the colour.plotting.filter_cmfs() definition.

  • normalise_sd_colours : Whether to normalise the computed spectral distributions colours. The default is True.

  • use_sd_colours : Whether to use the computed spectral distributions colours under the plotting colourspace illuminant. Alternatively, it is possible to use the matplotlib.pyplot.plot() definition color argument with pre-computed values. The default is True.

• kwargs (Any) – {colour.plotting.artist(), colour.plotting.diagrams.plot_chromaticity_diagram(), colour.plotting.render()}, See the documentation of the previously listed definitions.

Returns

Current figure and axes.

Return type

tuple

Examples

>>> A = SDS_ILLUMINANTS['A']
>>> D65 = SDS_ILLUMINANTS['D65']
>>> plot_sds_in_chromaticity_diagram_CIE1960UCS([A, D65])
... 
(<Figure size ... with 1 Axes>, <...AxesSubplot...>)

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