My aim with matplotlib is to create a scatter plot where both markers and colors vary.
import matplotlib.pyplot as plt
import numpy as np
markers = np.array(["1","2","3","4","+",">"])
# Sample Data
x = np.array([0, 2, 3, 4, 0, 1, 5, 6, 7, 8])
y = np.array([0, 1, 0, 2, 3, 4, 5, 6, 7, 8])
c = np.array([0, 0.4, 0, 0.2, 1, 0.9, 1, 1, 1])
m = np.array([0, 0, 0, 1, 1, 1, 2, 3, 3])
# Figure
fig, ax = plt.subplots(figsize=(8,7))
# Scatter
ax.scatter(x=x, y=y, c=c, marker=markers[m], cmap = 'summer') # Not possible
Unfortunately, matplotlib doesn't currently support using an array of markers.
As a workaround, I have resorted to iterating over points, but the color remains unchanged.
# Works well for markers but all points have the same color.
for i in range(x.shape[0]):
ax.scatter(x=x[i], y=y[i], c=c[i], marker=markers[m[i]], cmap = 'summer')
I am not experienced in manipulating ColorMap instances and couldn't find suitable examples for my specific needs.
If feasible, having a colormap would be beneficial.