Python中的 Matplotlib.patches.Wedge 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.Wedge

matplotlib.patches.Wedge 类用于在图中添加楔形补丁。楔形以 xy = (x, y) 为中心，半径为 r，它扫过 theta1 到 theta2（以度为单位）。如果给定宽度，则从内半径 r - 宽度到外半径 r 绘制部分楔形。

Syntax: class matplotlib.patches.Wedge(center, r, theta1, theta2, width=None, **kwargs)
Parameters: 
 

1. center: The center point of the the wedge.
    
2. r: Radius of the wedge.
    
3. theta1: First angle of sweep.
    
4. theta2: Second angle of sweep.
    
5. width: Width of the sweep
    

kwargs 属性如下表所示：

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 numpy as np
from matplotlib.patches import Circle, Wedge, Polygon
from matplotlib.collections import PatchCollection
import matplotlib.pyplot as plt
 
 
# Fixing random state for reproducibility
np.random.seed(19680801)
 
fig, ax = plt.subplots()
 
resolution = 50  # the number of vertices
N = 3
x = np.random.rand(N)
y = np.random.rand(N)
radii = 0.1 * np.random.rand(N)
patches = []
 
for x1, y1, r in zip(x, y, radii):
    circle = Circle((x1, y1), r)
    patches.append(circle)
 
x = np.random.rand(N)
y = np.random.rand(N)
radii = 0.1 * np.random.rand(N)
theta1 = 360.0 * np.random.rand(N)
theta2 = 360.0 * np.random.rand(N)
 
for x1, y1, r, t1, t2 in zip(x, y, radii,
                             theta1, theta2):
    wedge = Wedge((x1, y1), r, t1, t2)
    patches.append(wedge)
 
# Some limiting conditions on Wedge
patches += [
    Wedge((.3, .7), .1, 0, 360),             # Full circle
    Wedge((.7, .8), .2, 0, 360, width = 0.05),  # Full ring
    Wedge((.8, .3), .2, 0, 45),              # Full sector
    Wedge((.8, .3), .2, 45, 90, width = 0.10),  # Ring sector
]
 
for i in range(N):
    polygon = Polygon(np.random.rand(N, 2), True)
    patches.append(polygon)
 
colors = 100 * np.random.rand(len(patches))
p = PatchCollection(patches, alpha = 0.4)
p.set_array(np.array(colors))
ax.add_collection(p)
fig.colorbar(p, ax = ax)
 
plt.show()

输出：

示例 2：

Python3

import numpy as np
import matplotlib.pyplot as plt
 
 
fig, ax = plt.subplots(figsize =(6, 3),
                       subplot_kw = dict(aspect ="equal"))
 
recipe = ["375 g flour",
          "75 g sugar",
          "250 g butter",
          "300 g berries"]
 
data = [float(x.split()[0]) for x in recipe]
ingredients = [x.split()[-1] for x in recipe]
 
 
def func(pct, allvals):
    absolute = int(pct / 100.*np.sum(allvals))
     
    return "{:.1f}%\n({:d} g)".format(pct, absolute)
 
 
wedges, texts, autotexts = ax.pie(data,
                                  autopct = lambda pct: func(pct, data),
                                  textprops = dict(color ="w"))
 
ax.legend(wedges, ingredients,
          title ="Ingredients",
          loc ="center left",
          bbox_to_anchor =(1, 0, 0.5, 1))
 
plt.setp(autotexts, size = 8, weight ="bold")
 
ax.set_title("Recipe for a pie")
 
plt.show()

输出：