I have created the following three example heat maps:
import numpy as np
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(15, 10))
img1 = np.array([[1.23,2.12,3.11],[0.99,1.44,1.04],[1.1,2.1,1.5]])
ax1 = fig.add_subplot(1, 3, 1)
im = ax1.imshow(img1, origin='lower', cmap='Blues')
img2 = np.array([[1.12,2.0,3.02],[0.3,1.23,0.2],[1.0,1.1,0.3]])
ax1 = fig.add_subplot(1, 3, 2)
im2 = ax1.imshow(img2, origin='lower', cmap='Blues')
img3 = np.array([[0.9,1.44,1.9],[0.1,1.1,0.19],[0.9,1.0,0.2]])
ax1 = fig.add_subplot(1, 3, 3)
im3 = ax1.imshow(img3, origin='lower', cmap='Blues')
plt.tight_layout()
plt.show()
Now I would like to merge these three heat maps (images) into one heat map (one image) using barycentric coordinates and normalizing (range 0 to 1) per heat map (dimension).
As far as I know barycentric coordinates could look as follows:
How can I create this color triangle (colormap) in python and how can I then use this to create a heat map?