[python] plot a circle with pyplot

surprisingly I didn't find a straight-forward description on how to draw a circle with matplotlib.pyplot (please no pylab) taking as input center (x,y) and radius r. I tried some variants of this:

import matplotlib.pyplot as plt
circle=plt.Circle((0,0),2)
# here must be something like circle.plot() or not?
plt.show()

... but still didn't get it working.

This question is related to python matplotlib

The answer is


#!/usr/bin/python
import matplotlib.pyplot as plt
import numpy as np

def xy(r,phi):
  return r*np.cos(phi), r*np.sin(phi)

fig = plt.figure()
ax = fig.add_subplot(111,aspect='equal')  

phis=np.arange(0,6.28,0.01)
r =1.
ax.plot( *xy(r,phis), c='r',ls='-' )
plt.show()

Or, if you prefer, look at the paths, http://matplotlib.sourceforge.net/users/path_tutorial.html


Similarly to scatter plot you can also use normal plot with circle line style. Using markersize parameter you can adjust radius of a circle:

import matplotlib.pyplot as plt

plt.plot(200, 2, 'o', markersize=7)

If you aim to have the "circle" maintain a visual aspect ratio of 1 no matter what the data coordinates are, you could use the scatter() method. http://matplotlib.org/1.3.1/api/pyplot_api.html#matplotlib.pyplot.scatter

import matplotlib.pyplot as plt
x = [1, 2, 3, 4, 5]
y = [10, 20, 30, 40, 50]
r = [100, 80, 60, 40, 20] # in points, not data units
fig, ax = plt.subplots(1, 1)
ax.scatter(x, y, s=r)
fig.show()

Image is a scatter plot. Five circles along the line y=10x have decreasing radii from bottom left to top right. Although the graph is square-shaped, the y-axis has 10 times the range of the x-axis. Even so, the aspect ratio of the circles is 1 on the screen.


Hello I have written a code for drawing a circle. It will help for drawing all kind of circles. The image shows the circle with radius 1 and center at 0,0 The center and radius can be edited of any choice.

## Draw a circle with center and radius defined
## Also enable the coordinate axes
import matplotlib.pyplot as plt
import numpy as np
# Define limits of coordinate system
x1 = -1.5
x2 = 1.5
y1 = -1.5
y2 = 1.5

circle1 = plt.Circle((0,0),1, color = 'k', fill = False, clip_on = False)
fig, ax = plt.subplots()
ax.add_artist(circle1)
plt.axis("equal")
ax.spines['left'].set_position('zero')
ax.spines['bottom'].set_position('zero')
ax.spines['right'].set_color('none')
ax.spines['top'].set_color('none')
ax.xaxis.set_ticks_position('bottom')
ax.yaxis.set_ticks_position('left')
plt.xlim(left=x1)
plt.xlim(right=x2)
plt.ylim(bottom=y1)
plt.ylim(top=y2)
plt.axhline(linewidth=2, color='k')
plt.axvline(linewidth=2, color='k')

##plt.grid(True)
plt.grid(color='k', linestyle='-.', linewidth=0.5)
plt.show()

Good luck


Extending the accepted answer for a common usecase. In particular:

  1. View the circles at a natural aspect ratio.

  2. Automatically extend the axes limits to include the newly plotted circles.

Self-contained example:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.add_patch(plt.Circle((0, 0), 0.2, color='r', alpha=0.5))
ax.add_patch(plt.Circle((1, 1), 0.5, color='#00ffff', alpha=0.5))
ax.add_artist(plt.Circle((1, 0), 0.5, color='#000033', alpha=0.5))

#Use adjustable='box-forced' to make the plot area square-shaped as well.
ax.set_aspect('equal', adjustable='datalim')
ax.plot()   #Causes an autoscale update.
plt.show()

Note the difference between ax.add_patch(..) and ax.add_artist(..): of the two, only the former makes autoscaling machinery take the circle into account (reference: discussion), so after running the above code we get:

add_patch(..) vs add_artist(..)

See also: set_aspect(..) documentation.


import matplotlib.pyplot as plt

circle1 = plt.Circle((0, 0), 0.2, color='r')
plt.gca().add_patch(circle1)

A quick condensed version of the accepted answer, to quickly plug a circle into an existing plot. Refer to the accepted answer and other answers to understand the details.

By the way:

  • gca() means Get Current Axis

I see plots with the use of (.circle) but based on what you might want to do you can also try this out:

import matplotlib.pyplot as plt
import numpy as np

x = list(range(1,6))
y = list(range(10, 20, 2))

print(x, y)

for i, data in enumerate(zip(x,y)):
    j, k = data
    plt.scatter(j,k, marker = "o", s = ((i+1)**4)*50, alpha = 0.3)

Simple concentric circle plot using linear progressing points

centers = np.array([[5,18], [3,14], [7,6]])
m, n = make_blobs(n_samples=20, centers=[[5,18], [3,14], [7,6]], n_features=2, 
cluster_std = 0.4)
colors = ['g', 'b', 'r', 'm']

plt.figure(num=None, figsize=(7,6), facecolor='w', edgecolor='k')
plt.scatter(m[:,0], m[:,1])

for i in range(len(centers)):

    plt.scatter(centers[i,0], centers[i,1], color = colors[i], marker = 'o', s = 13000, alpha = 0.2)
    plt.scatter(centers[i,0], centers[i,1], color = 'k', marker = 'x', s = 50)

plt.savefig('plot.png')

Circled points of a classification problem.


If you want to plot a set of circles, you might want to see this post or this gist(a bit newer). The post offered a function named circles.

The function circles works like scatter, but the sizes of plotted circles are in data unit.

Here's an example:

from pylab import *
figure(figsize=(8,8))
ax=subplot(aspect='equal')

#plot one circle (the biggest one on bottom-right)
circles(1, 0, 0.5, 'r', alpha=0.2, lw=5, edgecolor='b', transform=ax.transAxes)

#plot a set of circles (circles in diagonal)
a=arange(11)
out = circles(a, a, a*0.2, c=a, alpha=0.5, edgecolor='none')
colorbar(out)

xlim(0,10)
ylim(0,10)

enter image description here