scipy.spatial.

voronoi_plot_2d

scipy.spatial.voronoi_plot_2d(vor, ax=None, **kw)

Plot the given Voronoi diagram in 2-D

Parameters:

vorscipy.spatial.Voronoi instance

Diagram to plot

axmatplotlib.axes.Axes instance, optional

Axes to plot on

show_pointsbool, optional

Add the Voronoi points to the plot.

show_verticesbool, optional

Add the Voronoi vertices to the plot.

line_colorsstring, optional

Specifies the line color for polygon boundaries

line_widthfloat, optional

Specifies the line width for polygon boundaries

line_alphafloat, optional

Specifies the line alpha for polygon boundaries

point_sizefloat, optional

Specifies the size of points

Returns:

figmatplotlib.figure.Figure instance

Figure for the plot

See also

Voronoi

Notes

Requires Matplotlib. For degenerate input, including collinearity and other violations of general position, it may be preferable to calculate the Voronoi diagram with Qhull options QJ for random joggling, or Qt to enforce triangulated output. Otherwise, some Voronoi regions may not be visible.

Examples

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>>> import numpy as np
>>> import matplotlib.pyplot as plt
>>> from scipy.spatial import Voronoi, voronoi_plot_2d

Create a set of points for the example:

>>> rng = np.random.default_rng()
>>> points = rng.random((10,2))

Generate the Voronoi diagram for the points:

>>> vor = Voronoi(points)

Use voronoi_plot_2d to plot the diagram:

>>> fig = voronoi_plot_2d(vor)

Use voronoi_plot_2d to plot the diagram again, with some settings customized:

>>> fig = voronoi_plot_2d(vor, show_vertices=False, line_colors='orange',
...                       line_width=2, line_alpha=0.6, point_size=2)
>>> plt.show()

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