How to use matplotlib PATH to draw a polygon

Question

I have a problem when using matplotlib python PATH modules I want to draw a close poly like this:

but I definitely don’t know the sequence of connected points, and it turned out that the images of the results cannot satisfy my needs. How to draw a polygon correctly, without defining a sequence yourself, but with code?

here is my code:

import matplotlib
import matplotlib.pyplot as plt
import pandas
from matplotlib.path import Path
import matplotlib.patches as patches
#read data
info = pandas.read_csv('/Users/james/Desktop/nba.csv')
info.columns = ['number', 'team_id', 'player_id', 'x_loc', 'y_loc', 
'radius', 'moment', 'game_clock', 'shot_clock', 'player_name', 
'player_jersey']

#first_team_info
x_1 = info.x_loc[1:6]
y_1 = info.y_loc[1:6]
matrix= [x_1,y_1]
z_1 = list(zip(*matrix))
z_1.append(z_1[4])
n_1 = info.player_jersey[1:6]
verts = z_1
codes = [Path.MOVETO,
     Path.LINETO,
     Path.LINETO,
     Path.LINETO,
     Path.LINETO,
     Path.CLOSEPOLY,
     ]
     path = Path(verts, codes)
     fig = plt.figure()
     ax = fig.add_subplot(111)
     patch = patches.PathPatch(path, facecolor='orange', lw=2)
     ax.add_patch(patch)
     ax.set_xlim(0, 100)
     ax.set_ylim(0, 55)
     plt.show()

and I got the following:

Answer 1

Matplotlib displays the waypoints so that they are fixed. This can lead to undesirable results if there is no control over the order, as is the case with the question.

So the solution could be

• (A) . Scipy scipy.spatial.ConvexHull , . , . , , .
• (B) , . . . , . , . , , , .

import numpy as np
import matplotlib.pyplot as plt
from scipy.spatial import ConvexHull

p = [(1,1), (2,1.6), (0.8,2.7), (1.7,3.2)]
p2 = [(0.7,1.3),(2,0.9),(1.4,1.5),(1.9,3.1),(0.6,2.5),(1.4,2.3)]

def convexhull(p):
    p = np.array(p)
    hull = ConvexHull(p)
    return p[hull.vertices,:]

def ccw_sort(p):
    p = np.array(p)
    mean = np.mean(p,axis=0)
    d = p-mean
    s = np.arctan2(d[:,0], d[:,1])
    return p[np.argsort(s),:]

fig, axes = plt.subplots(ncols=3, nrows=2, sharex=True, sharey=True)

axes[0,0].set_title("original")
poly = plt.Polygon(p, ec="k")
axes[0,0].add_patch(poly)

poly2 = plt.Polygon(p2, ec="k")
axes[1,0].add_patch(poly2)

axes[0,1].set_title("convex hull")
poly = plt.Polygon(convexhull(p), ec="k")
axes[0,1].add_patch(poly)

poly2 = plt.Polygon(convexhull(p2), ec="k")
axes[1,1].add_patch(poly2)

axes[0,2].set_title("ccw sort")
poly = plt.Polygon(ccw_sort(p), ec="k")
axes[0,2].add_patch(poly)

poly2 = plt.Polygon(ccw_sort(p2), ec="k")
axes[1,2].add_patch(poly2)


for ax in axes[0,:]:
    x,y = zip(*p)
    ax.scatter(x,y, color="k", alpha=0.6, zorder=3)
for ax in axes[1,:]:
    x,y = zip(*p2)
    ax.scatter(x,y, color="k", alpha=0.6, zorder=3)


axes[0,0].margins(0.1)
axes[0,0].relim()
axes[0,0].autoscale_view()
plt.show()