[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.

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)

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

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)

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()

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

#!/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

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:

See also: set_aspect(..) documentation.

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)

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')