Bivariate colourplot edit

bivariate.py

import numpy as np
import matplotlib.pyplot as plt

def colorFromBivariateData(Z1,Z2,cmap1 = plt.cm.Blues, cmap2 = plt.cm.Reds, preset = False):

    if preset:
        z1mn = 0.
        z2mn = 0.
        z1mx = 1.
        z2mx = 1.
    else:
        z1mn = Z1.min()
        z2mn = Z2.min()
        z1mx = Z1.max()
        z2mx = Z2.max()        

    # Rescale values to fit into colormap range (0->255)
    Z1_plot = np.array(255*(Z1-z1mn)/(z1mx-z1mn), dtype=np.int)
    Z2_plot = np.array(255*(Z2-z2mn)/(z2mx-z2mn), dtype=np.int)

    Z1_color = cmap1(Z1_plot)
    Z2_color = cmap2(Z2_plot)

    # Color for each point
    Z_color = np.sum([Z1_color, Z2_color], axis=0)/2.0

    return Z_color

xx, yy = np.mgrid[0:50,0:50]
C_map = colorFromBivariateData(xx,yy)

fig = plt.figure(figsize=(10,5))

ax1 = fig.add_subplot(1,2,1)
x = xx.flatten()
y = yy.flatten()
cflat = C_map.reshape((len(x),4))  
plt.scatter(x,y,c = cflat,s=8)

ax1.set_title('Data')

xx, yy = np.mgrid[0:9,0:9]
C_map = colorFromBivariateData(xx,yy)

ax2 = fig.add_subplot(1,2,2)
ax2.imshow(C_map)
ax2.set_title('Bivariate Color Map')
ax2.set_xlabel('Variable 1')
ax2.set_ylabel('Variable 2')
ax2.set_ylim((-0.5,0.5+(yy.max()-yy.min())))     

fig.tight_layout()
fig.show()