You need to add it to an axes. A Circle
is a subclass of an Patch
, and an axes
has an add_patch
method. (You can also use add_artist
but it's not recommended.)
Here's an example of doing this:
import matplotlib.pyplot as plt
circle1 = plt.Circle((0, 0), 0.2, color='r')
circle2 = plt.Circle((0.5, 0.5), 0.2, color='blue')
circle3 = plt.Circle((1, 1), 0.2, color='g', clip_on=False)
fig, ax = plt.subplots() # note we must use plt.subplots, not plt.subplot
# (or if you have an existing figure)
# fig = plt.gcf()
# ax = fig.gca()
ax.add_patch(circle1)
ax.add_patch(circle2)
ax.add_patch(circle3)
fig.savefig('plotcircles.png')
This results in the following figure:
The first circle is at the origin, but by default clip_on
is True
, so the circle is clipped when ever it extends beyond the axes
. The third (green) circle shows what happens when you don't clip the Artist
. It extends beyond the axes (but not beyond the figure, ie the figure size is not automatically adjusted to plot all of your artists).
The units for x, y and radius correspond to data units by default. In this case, I didn't plot anything on my axes (fig.gca()
returns the current axes), and since the limits have never been set, they defaults to an x and y range from 0 to 1.
Here's a continuation of the example, showing how units matter:
circle1 = plt.Circle((0, 0), 2, color='r')
# now make a circle with no fill, which is good for hi-lighting key results
circle2 = plt.Circle((5, 5), 0.5, color='b', fill=False)
circle3 = plt.Circle((10, 10), 2, color='g', clip_on=False)
ax = plt.gca()
ax.cla() # clear things for fresh plot
# change default range so that new circles will work
ax.set_xlim((0, 10))
ax.set_ylim((0, 10))
# some data
ax.plot(range(11), 'o', color='black')
# key data point that we are encircling
ax.plot((5), (5), 'o', color='y')
ax.add_patch(circle1)
ax.add_patch(circle2)
ax.add_patch(circle3)
fig.savefig('plotcircles2.png')
which results in:
You can see how I set the fill of the 2nd circle to False
, which is useful for encircling key results (like my yellow data point).