Visualising 2 Parameters And Their Results

There's 2 parameters where I want to try different values for: a = [0.0, 0.5, 0.6] # len == 3 b = [0.0, 0.02 , 0.05, 0.1] # len == 4 For each value of a, try each value of b. Th

Solution 1:

There are many different options. The first step in any case needs to be to convert your res list into a numpy array.

For many plots like imshow, pcolor(mesh) or contourf, you need to have three 2D arrays, which you can obtain via reshaping of your input array (given that it is ordered correctly).

The following shows some options you have:

res = [(0.0, 0.0, 0.5), (0.0, 0.02, 0.7), (0.0, 0.05, 0.6), (0.0, 0.10, 0.8),
       (0.5, 0.0, 0.4), (0.5, 0.02, 0.6), (0.5, 0.05, 0.5), (0.5, 0.10, 0.7),
       (0.6, 0.0, 0.3), (0.6, 0.02, 0.5), (0.6, 0.05, 0.4), (0.6, 0.10, 0.6)]

import matplotlib.pyplot as plt
import numpy as np

res = np.array(res)
A = res[:,0].reshape(3,4) #A in y direction
B = res[:,1].reshape(3,4)
Z = res[:,2].reshape(3,4)

fig, ((ax, ax2), (ax3, ax4)) = plt.subplots(2,2)
#imshow
im = ax.imshow(Z, origin="lower")
ax.set_xticks(range(len(Z[0,:])))ax.set_yticks(range(len(Z[:,0])))ax.set_xticklabels(B[0,:])ax.set_yticklabels(A[:,0])#pcolormesh, first need to extend the grid
bp = np.append(B[0,:], [0.15])
ap = np.append(A[:,0], [0.7])
Bp, Ap = np.meshgrid(bp, ap)
ax2.pcolormesh(Bp, Ap, Z)

#contour
ax3.contourf(B, A, Z, levels=np.linspace(Z.min(), Z.max(),5))
#scatterax4.scatter(res[:,1], res[:,0], c=res[:,2], s=121)

ax.set_title("imshow")
ax2.set_title("pcolormesh")
ax3.set_title("contourf")
ax4.set_title("scatter")
plt.tight_layout()
fig.colorbar(im, ax=fig.axes, pad=0.05)
plt.show()