Matplotlib.patches.Circle 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.Circle

The matplotlib.patches.Circle class is used to create a circular patch at a given center xy = (x, y) with a given radius. It uses Bezier splines and is much closer to a scale-free circle.

Syntax: class matplotlib.patches.Circle(xy, radius=5, **kwargs)

parameters:

  • xy: It is the center of the circle.
  • radius: It sets the radius of the circle to be drawn. Its default value is 5 units and is optional.

Below table provides with the optional valid 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

Example 1:

filter_none

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code

import numpy as np
from matplotlib.patches import Circle
from matplotlib.collections import PatchCollection
import matplotlib.pyplot as plt
from matplotlib import cm
from matplotlib import animation
  
  
fig, ax = plt.subplots()
  
patches = []
# create circles with random sizes 
# and locations
N = 12 # number of circles
x = np.random.rand(N)
y = np.random.rand(N)
radii = 0.1 * np.random.rand(N)
for x1, y1, r in zip(x, y, radii):
    circle = Circle((x1, y1), r)
    patches.append(circle)
  
# add these circles to a collection
p = PatchCollection(patches, cmap = cm.prism, alpha = 0.4)
ax.add_collection(p)
  
def animate(i):
      
    # random index to color map
    colors = 100 * np.random.rand(len(patches))
      
    # set new color colors
    p.set_array(np.array(colors))
    return p,
  
ani = animation.FuncAnimation(fig, animate,
                              frames = 50, interval = 50)
  
plt.show()

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Output:

Example 2:

filter_none

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code

import numpy as np
import matplotlib
from matplotlib.patches import Circle, Wedge, Polygon, Ellipse
from matplotlib.collections import PatchCollection
import matplotlib.pyplot as plt
import matplotlib.patches as matpatches
  
  
fig, ax = plt.subplots(figsize =(8, 8))
patches = []
  
  
circle = Circle((2, 2), 2)
patches.append(circle)
  
polygon = matpatches.PathPatch(patches[0].get_path())
patches.append(polygon)
  
  
colors = 2 * np.random.rand(len(patches))
p = PatchCollection(patches,
                    cmap = matplotlib.cm.jet,
                    alpha = 0.4)
  
p.set_array(np.array(colors))
ax.add_collection(p)
  
plt.axis([-10, 10, -10, 10])
  
plt.show()
  
  
contain2 = patches[0].get_path().contains_points([[0.5, 0.5], 
                                                  [1.0, 1.0]])
contain3 = patches[0].contains_point([0.5, 0.5])
contain4 = patches[0].contains_point([1.0, 1.0])

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Output:




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