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:

  1. centre: The centre 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

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:

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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()

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Output:

Example 2:

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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()

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Output:




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