Matplotlib是Python中令人惊叹的可视化库，用于数组的二维图。 Matplotlib是一个基于NumPy数组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
这个 matplotlib.patches.Wedge类用于在图中添加wedge-shaped个色块。楔子居中xy = (x, y)半径为r时，它将theta1扫描到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。
用法： class matplotlib.patches.Wedge(center, r, theta1, theta2, width=None, **kwargs)
参数：
- centre:楔形的中心点。
- r:楔形的半径。
- theta1:第一扫角。
- theta2:第二扫描角。
- width:扫描宽度
下表提供了kwargs属性：
| PROPERTY | DESCRIPTION |
|---|---|
| agg_filter | 一个过滤器函数，它接受一个(m，n，3)浮点数组，一个dpi值返回一个(m，n，3)数组 |
| alpha | 浮点数或无 |
| animated | bool |
| 抗锯齿或抗锯齿 | unknown |
| capstyle | {‘butt’，“回合”，‘projecting’} |
| clip_box | Bbox |
| clip_on | bool |
| clip_path | [(Path，Transform)|补丁|无] |
| color | rgba元组的颜色或顺序 |
| contains | callable |
| edgecolor或ec或edgecolors | 颜色或无或‘auto’ |
| facecolor或fc或facecolors | 颜色或无 |
| figure | figure |
| fill | bool |
| gid | str |
| hatch | {‘/’、‘\’、‘|’、‘-’、‘+’、‘x’, ‘o’、‘O’、‘.’、‘*’} |
| in_layout | bool |
| joinstyle | {‘miter’，“回合”，‘bevel’} |
| 线型或ls | {“-”，“-”，“-。”，“：”，“，(偏移量，on-off-seq)，...} |
| 线宽或线宽或lw | 浮点数或无 |
| path_effects | AbstractPathEffect |
| picker | 无或布尔或浮点数或可赎回 |
| path_effects | AbstractPathEffect |
| picker | float或callable [[Artist，Event]，Tuple [bool，dict]] |
| rasterized | 布尔还是无 |
| sketch_params | (比例：浮点数，长度：浮点数，随机性：浮点数) |
| snap | 布尔还是无 |
| transform | matplotlib.transforms.Transform |
| url | str |
| visible | bool |
| zorder | float |
范例1：
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：
范例2：
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("Recipie for a pie")
plt.show()输出：
注：本文由纯净天空筛选整理自GeeksforGeeks大神的英文原创作品 Matplotlib.patches.Wedge class in Python。非经特殊声明，原始代码版权归原作者所有，本译文未经允许或授权，请勿转载或复制。