Drawing circle hand drawn style by matplotlib in Python

Question

I'm new to matprotlib. After plotting a graph I would like to mark a point. I do this with the following code:

import matplotlib.pyplot as plt

fig, ax = plt.subplots()
ax.scatter(3, 2, s=500, edgecolor='#ff575a', lw=2, facecolor='none', alpha=0.5, zorder=1) #6.5-row['mag']
ax.plot([1, 2, 3, 4], [1, 4, 2, 3])

The output:

Instead of the symmetric red circle is it possible to make a custom shape handwriting style? Something like this one:

I have tried to use the AnnotationBbox insted of ax.scatter:

ab = AnnotationBbox(OffsetImage(plt.imread('circle.png'), 
    zoom=0.2), (3, 2), frameon=False)

But that make the picture bad with some pixels of the circle missing, so it is not that sharp as the original png:

Store it as a png with transparency and plot it over your curve? — Mr. T
– Mr. T, Commented Jan 28, 2022 at 19:02
@Mr.T That could work, yes. Do you think programming way is too complicated? Or it is not possible with matplotlib? — user164863
– user164863, Commented Jan 28, 2022 at 19:06
Or perhaps save the graph plot in pdf/png and then with another software (e.g.: inkscape) you could add it manually and adjust it in and easier way — fgoudra
– fgoudra, Commented Jan 28, 2022 at 19:10
You could use the with construction: with plt.xkcd(scale=10): ax.add_patch(Arc((3, 2), 0.3, 0.3, 0, 271, 270, edgecolor='#ff575a', lw=2, facecolor='none', alpha=0.5, zorder=1)) — JohanC
– JohanC, Commented Jan 28, 2022 at 20:19

JohanC · Accepted Answer · 2022-02-03 20:11:51Z

1

The following example code uses the xkcd style to draw a wiggly arc. You might need to experiment with the parameters for the best fit with your plot.

import matplotlib.pyplot as plt
from matplotlib.patches import Arc

fig, ax = plt.subplots()
ax.scatter(3, 2, s=500, edgecolor='#ff575a', lw=2, facecolor='none', alpha=0.5, zorder=1)  #
ax.plot([1, 2, 3, 4], [1, 4, 2, 3])
with plt.xkcd(scale=10):
    ax.add_patch(Arc((3, 2), 0.3, 0.3, angle=275, theta1=0, theta2=350,
                     edgecolor='#ff575a', lw=2, facecolor='none', alpha=0.5, zorder=1))
plt.show()

answered Feb 3, 2022 at 20:11

JohanC

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