o ñ h…ã@s`ddlZddlmZgd¢Zeddd„ƒZdd„Zeddd „ƒZedd d „ƒZ edd d „ƒZ dS)éN)Ú decorator)Údelaunay_plot_2dÚconvex_hull_plot_2dÚvoronoi_plot_2dc Ksšddlm}|dur| ¡}| ¡}||fd|i|¤ŽSt|ddd„ƒƒ}|r1||fd|i|¤ŽSz| d¡||fd|i|¤ŽW| |¡S| |¡w)NrÚaxÚisholdcSsdS)NT©rrrúL/var/www/vscode/kcb/lib/python3.10/site-packages/scipy/spatial/_plotutils.pyÚsz_held_figure..T)Úmatplotlib.pyplotÚpyplotÚfigureÚgcaÚgetattrÚhold)ÚfuncÚobjrÚkwÚpltÚfigÚwas_heldrrr Ú _held_figures  rcCs^dtj|dd}|jdd|}|jdd|}| |d|d¡| |d|d¡dS)Ngš™™™™™¹?r©Úaxisé)ÚnpÚptpÚminÚmaxÚset_xlimÚset_ylim)rÚpointsÚmarginÚxy_minÚxy_maxrrr Ú_adjust_boundss r%cCsX|jjddkr tdƒ‚|jj\}}| ||d¡| |||j ¡¡t||jƒ|j S)aB Plot the given Delaunay triangulation in 2-D Parameters ---------- tri : scipy.spatial.Delaunay instance Triangulation to plot ax : matplotlib.axes.Axes instance, optional Axes to plot on Returns ------- fig : matplotlib.figure.Figure instance Figure for the plot See Also -------- Delaunay matplotlib.pyplot.triplot Notes ----- Requires Matplotlib. Examples -------- >>> import numpy as np >>> import matplotlib.pyplot as plt >>> from scipy.spatial import Delaunay, delaunay_plot_2d The Delaunay triangulation of a set of random points: >>> rng = np.random.default_rng() >>> points = rng.random((30, 2)) >>> tri = Delaunay(points) Plot it: >>> _ = delaunay_plot_2d(tri) >>> plt.show() réz!Delaunay triangulation is not 2-DÚo) r!ÚshapeÚ ValueErrorÚTÚplotÚtriplotÚ simplicesÚcopyr%r )ÚtrirÚxÚyrrr r$s-  rcsˆddlm}ˆjjddkrtdƒ‚| ˆjdd…dfˆjdd…dfd¡‡fdd „ˆjDƒ}| ||d d d ¡t|ˆjƒ|j S) a& Plot the given convex hull diagram in 2-D Parameters ---------- hull : scipy.spatial.ConvexHull instance Convex hull to plot ax : matplotlib.axes.Axes instance, optional Axes to plot on Returns ------- fig : matplotlib.figure.Figure instance Figure for the plot See Also -------- ConvexHull Notes ----- Requires Matplotlib. Examples -------- >>> import numpy as np >>> import matplotlib.pyplot as plt >>> from scipy.spatial import ConvexHull, convex_hull_plot_2d The convex hull of a random set of points: >>> rng = np.random.default_rng() >>> points = rng.random((30, 2)) >>> hull = ConvexHull(points) Plot it: >>> _ = convex_hull_plot_2d(hull) >>> plt.show() r©ÚLineCollectionrr&zConvex hull is not 2-DNr'csg|]}ˆj|‘qSr)r!)Ú.0Úsimplex©Úhullrr Ú sz'convex_hull_plot_2d..ÚkÚsolid)ÚcolorsÚ linestyle) Úmatplotlib.collectionsr3r!r(r)r+r-Úadd_collectionr%r )r7rr3Ú line_segmentsrr6r r]s -*þ rc Ks<ddlm}|jjddkrtdƒ‚| dd¡r5| dd ¡}|j|jd d …df|jd d …dfd |d | d d¡rP| |jd d …df|jd d …dfd ¡| dd¡}| dd¡}| dd¡}|jjdd}t j |jdd} g} g} t |j |j ƒD]€\} } t  | ¡} t  | dk¡r•|  |j| ¡q|| | dkd}|j| d|j| d}|t j |¡}t  |d |dg¡}|j| jdd}t  t  |||¡¡|}|jrÛ| }t|  ¡|  ¡ƒ}|j|||  ¡|}|  |j||g¡q|| || |||dd¡| || |||dd¡t||jƒ|jS)ae Plot the given Voronoi diagram in 2-D Parameters ---------- vor : scipy.spatial.Voronoi instance Diagram to plot ax : matplotlib.axes.Axes instance, optional Axes to plot on show_points : bool, optional Add the Voronoi points to the plot. show_vertices : bool, optional Add the Voronoi vertices to the plot. line_colors : string, optional Specifies the line color for polygon boundaries line_width : float, optional Specifies the line width for polygon boundaries line_alpha : float, optional Specifies the line alpha for polygon boundaries point_size : float, optional Specifies the size of points Returns ------- fig : matplotlib.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 -------- >>> 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() rr2rr&zVoronoi diagram is not 2-DÚ show_pointsTÚ point_sizeNÚ.)Ú markersizeÚ show_verticesr'Ú line_colorsr9Ú line_widthgð?Ú line_alpharr:)r;ÚlwÚalphar<Údashed)r=r3r!r(r)Úgetr+ÚverticesÚmeanrrÚzipÚ ridge_pointsÚridge_verticesÚasarrayÚallÚappendÚlinalgÚnormÚarrayÚsignÚdotÚ furthest_siteÚabsrrr>r%r )Úvorrrr3rArErFrGÚcenterÚ ptp_boundÚfinite_segmentsÚinfinite_segmentsÚpointidxr5ÚiÚtÚnÚmidpointÚ directionÚ aspect_factorÚ far_pointrrr r™sX D  . *    üü r)N) ÚnumpyrÚscipy._lib.decoratorrÚ _decoratorÚ__all__rr%rrrrrrr Ús   8 ;