voronoi_plot_2d#
- scipy.spatial.voronoi_plot_2d(vor, ax=None, **kw)[source]#
- 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 - 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 - QJfor random joggling, or- Qtto enforce triangulated output. Otherwise, some Voronoi regions may not be visible.- Examples - >>> 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_2dto plot the diagram:- >>> fig = voronoi_plot_2d(vor) - Use - voronoi_plot_2dto 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()   