Matplotlib custom marker/symbol

The most flexible option for matplotlib is marker paths.

I used Inkscape to convert Smiley face svg into a single SVG path. Inkscape also has options to trace path in raster images. The I used svg path to convert it to matplotlib.path.Path using svgpath2mpl.

!pip install svgpath2mpl matplotlib
from svgpath2mpl import parse_path

import matplotlib.pyplot as plt      
import numpy as np                   
# Use Inkscape to edit SVG, 
# Path -> Combine to convert multiple paths into a single path
# Use Path -> Object to path to convert objects to SVG path
smiley = parse_path("""m 739.01202,391.98936 c 13,26 13,57 9,85 -6,27 -18,52 -35,68 -21,20 -50,23 -77,18 -15,-4 -28,-12 -39,-23 -18,-17 -30,-40 -36,-67 -4,-20 -4,-41 0,-60 l 6,-21 z m -302,-1 c 2,3 6,20 7,29 5,28 1,57 -11,83 -15,30 -41,52 -72,60 -29,7 -57,0 -82,-15 -26,-17 -45,-49 -50,-82 -2,-12 -2,-33 0,-45 1,-10 5,-26 8,-30 z M 487.15488,66.132209 c 121,21 194,115.000001 212,233.000001 l 0,8 25,1 1,18 -481,0 c -6,-13 -10,-27 -13,-41 -13,-94 38,-146 114,-193.000001 45,-23 93,-29 142,-26 z m -47,18 c -52,6 -98,28.000001 -138,62.000001 -28,25 -46,56 -51,87 -4,20 -1,57 5,70 l 423,1 c 2,-56 -39,-118 -74,-157 -31,-34 -72,-54.000001 -116,-63.000001 -11,-2 -38,-2 -49,0 z m 138,324.000001 c -5,6 -6,40 -2,58 3,16 4,16 10,10 14,-14 38,-14 52,0 15,18 12,41 -6,55 -3,3 -5,5 -5,6 1,4 22,8 34,7 42,-4 57.6,-40 66.2,-77 3,-17 1,-53 -4,-59 l -145.2,0 z m -331,-1 c -4,5 -5,34 -4,50 2,14 6,24 8,24 1,0 3,-2 6,-5 17,-17 47,-13 58,9 7,16 4,31 -8,43 -4,4 -7,8 -7,9 0,0 4,2 8,3 51,17 105,-20 115,-80 3,-15 0,-43 -3,-53 z m 61,-266 c 0,0 46,-40 105,-53.000001 66,-15 114,7 114,7 0,0 -14,76.000001 -93,95.000001 -76,18 -126,-49 -126,-49 z""")
smiley.vertices -= smiley.vertices.mean(axis=0)
x = np.linspace(-3, 3, 20)          
plt.plot(x, np.sin(x), marker=smiley, markersize=20, color='c')
plt.show()

Google Colab Link

So found out that it was just using mathtext symbols and not referring to any special vector based marker stored in the matplotlib module...

from matplotlib import pyplot as plt
import numpy as np
from numpy.random import randint
import matplotlib

x = np.arange(0.0, 100.0, 2.0)
y = x ** 1.3 + np.random.rand(*x.shape) * 30.0
s = np.random.rand(*x.shape) * 800 + 500

markers = ['\\alpha', '\\beta', '\gamma', '\sigma','\infty', \
            '\spadesuit', '\heartsuit', '\diamondsuit', '\clubsuit', \
            '\\bigodot', '\\bigotimes', '\\bigoplus', '\imath', '\\bowtie', \
            '\\bigtriangleup', '\\bigtriangledown', '\oslash' \
           '\ast', '\\times', '\circ', '\\bullet', '\star', '+', \
            '\Theta', '\Xi', '\Phi', \
            '\$', '\#', '\%', '\S']

def getRandomMarker():
    return "$"+markers[randint(0,len(markers),1)]+"$"

def getMarker(i):
    # Use modulus in order not to have the index exceeding the lenght of the list (markers)
    return "$"+markers[i % len(markers)]+"$"

for i, mi in enumerate(markers):
    plt.plot(x[i], y[i], "b", alpha=0.5, marker=getRandomMarker(), markersize=randint(16,26,1))
    plt.plot(x[i], y[i]+50, "m", alpha=0.5, marker=getMarker(i), markersize=randint(16,26,1))
    # Let's see if their "center" is located where we expect them to be...
    plt.plot(x[i], y[i]+100, "y", alpha=0.5, marker=getMarker(i), markersize=24)
    plt.plot(x[i], y[i]+100, "k+", markersize=12, markeredgewidth=2)

plt.xlabel("x-axis")
plt.ylabel("y-axis")
plt.xlim( -5, plt.xlim()[1]+5 )
plt.ylim( 0, plt.ylim()[1]*1.1 )
plt.gcf().set_size_inches(12,6)
plt.show()