colour.plotting.plot_cvd_simulation_Machado2009#
- colour.plotting.plot_cvd_simulation_Machado2009(RGB: ArrayLike, deficiency: Literal['Deuteranomaly', 'Protanomaly', 'Tritanomaly'] | str = 'Protanomaly', severity: float = 0.5, M_a: ArrayLike | None = None, **kwargs: Any) Tuple[plt.Figure, plt.Axes] [source]#
Perform colour vision deficiency simulation on given RGB colourspace array using Machado et al. (2009) model.
- Parameters:
RGB (ArrayLike) – RGB colourspace array.
deficiency (Literal['Deuteranomaly', 'Protanomaly', 'Tritanomaly'] | str) – Colour blindness / vision deficiency type.
severity (float) – Severity of the colour vision deficiency in domain [0, 1].
M_a (ArrayLike | None) – Anomalous trichromacy matrix to use instead of Machado (2010) pre-computed matrix.
kwargs (Any) – {
colour.plotting.artist()
,colour.plotting.plot_image()
,colour.plotting.render()
}, See the documentation of the previously listed definitions.
- Return type:
Tuple[plt.Figure, plt.Axes]
Notes
Input RGB array is expected to be linearly encoded.
- Returns:
Current figure and axes.
- Return type:
- Parameters:
Examples
>>> import numpy as np >>> RGB = np.random.rand(32, 32, 3) >>> plot_cvd_simulation_Machado2009(RGB) (<Figure size ... with 1 Axes>, <...Axes...>)