Matplotlib.patches.Wedge class in Python

Matplotlib is an amazing visualization library in Python for 2D plots of arrays. Matplotlib is a multi-platform data visualization library built on NumPy arrays and designed to work with the broader SciPy stack.

matplotlib.patches.Wedge

The matplotlib.patches.Wedge class is used to add wedge-shaped patches in the plot. The wedge is centered at xy = (x, y) with a radius r and it sweeps theta1 to theta2 (in degrees). The partial wedge is drawn from inner radius r – width to outer radius r if width is given.

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

Parameters:

centre: The centre point of the the wedge.
r: Radius of the wedge.
theta1: First angle of sweep.
theta2: Second angle of sweep.
width: Width of the sweep

The kwargs attributes are given in the table below:

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

Example 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() 

Output:

Example 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() 

Output:

My Personal Notes

matplotlib.patches.Wedge

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