Python中的 Matplotlib.patches.RegularPolygon 类

Matplotlib是Python中用于数组二维图的惊人可视化库。 Matplotlib 是一个基于 NumPy 数组构建的多平台数据可视化库，旨在与更广泛的 SciPy 堆栈配合使用。

matplotlib.patches.RegularPolygon

matplotlib.patches.RegularPolygon 类用于添加正多边形补丁。

Syntax: class matplotlib.patches.RegularPolygon(xy, numVertices, radius=5, orientation=0, **kwargs)
Parameters:  

• xy: A length 2 tuple (x, y) of the center.
   
• numVertices: It represents the number of vertices.
   
• radius: The distance from the center to each of the vertices.
   
• orientation: It is used to rotate the polygon (in radians). 

下表列出了有效的 kwargs；

PROPERTY	DESCRIPTION
agg_filter	a filter function that takes a (m, n, 3) float array and a dpi value that returns a (m, n, 3) array
alpha	float or None
animated	bool
antialiased or aa	unknown
capstyle	{‘butt’, ’round’, ‘projecting’}
clip_box	Bbox
clip_on	bool
clip_path	[(Path, Transform)|Patch|None]
color	color or sequence of rgba tuples
contains	callable
edgecolor or ec or edgecolors	color or None or ‘auto’
facecolor or fc or facecolors	color or None
figure	figure
fill	bool
gid	str
hatch	{‘/’, ‘\’, ‘|’, ‘-‘, ‘+’, ‘x’, ‘o’, ‘O’, ‘.’, ‘*’}
in_layout	bool
joinstyle	{‘miter’, ’round’, ‘bevel’}
linestyle or ls	{‘-‘, ‘–‘, ‘-.’, ‘:’, ”, (offset, on-off-seq), …}
linewidth or linewidths or lw	float or None
path_effects	AbstractPathEffect
picker	None or bool or float or callable
path_effects	AbstractPathEffect
picker	float or callable[[Artist, Event], Tuple[bool, dict]]
rasterized	bool or None
sketch_params	(scale: float, length: float, randomness: float)
snap	bool or None
transform	matplotlib.transforms.Transform
url	str
visible	bool
zorder	float

示例 1：

Python3

import matplotlib.pyplot as plt
from matplotlib.patches import RegularPolygon
import numpy as np
 
 
coord = [[0, 0, 0],
         [0, 1, -1],
         [-1, 1, 0],
         [-1, 0, 1],
         [0, -1, 1],
         [1, -1, 0],
         [1, 0, -1]]
 
colors = [["Green"],
          ["Green"],
          ["Green"],
          ["Green"],
          ["Green"],
          ["Green"],
          ["Green"]]
 
labels = [['1'], ['2'],
          ['3'], ['4'],
          ['5'], ['6'],
          ['7']]
 
# Horizontal cartesian coords
hcoord = for c in coord]
 
# Vertical cartersian coords
vcoord = [2. * np.sin(np.radians(60)) * (c[1] - c[2]) /3.
          for c in coord]
 
fig, ax = plt.subplots(1)
ax.set_aspect('equal')
 
# Add some coloured hexagons
for x, y, c, l in zip(hcoord, vcoord, colors, labels):
     
    # matplotlib understands lower
    # case words for colours
    color = c[0].lower()
    hex = RegularPolygon((x, y),
                         numVertices = 6,
                         radius = 2. / 3.,
                         orientation = np.radians(30),
                         facecolor = color,
                         alpha = 0.2,
                         edgecolor ='k')
     
    ax.add_patch(hex)
     
    # Also add a text label
    ax.text(x, y + 0.2, l[0], ha ='center',
            va ='center', size = 20)
 
# add scatter points in hexagon centers
ax.scatter(hcoord, vcoord, c =.lower()
                               for c in colors],
           alpha = 0.5)
 
plt.show()

输出：

示例 2：

Python3

import matplotlib.pyplot as plt
from matplotlib.patches import RegularPolygon
from matplotlib.collections import PatchCollection
import numpy as np
 
 
xy = np.random.random((10, 2))
z = np.random.random(10)
 
patches = [RegularPolygon((x, y),
                          5, 0.1)
           for x, y in xy]
 
collection = PatchCollection(patches,
                             array = z,
                             edgecolors ='brown',
                             lw = 2)
 
fig, ax = plt.subplots()
 
ax.patch.set(facecolor ='green')
ax.add_collection(collection)
ax.autoscale()
 
plt.show()

输出：