I have a lot of data for a simulation. I would like to represent it in a 3D plot. Lets say i have 10 points representing 10 seconds. For each second i have a list with ~millions of energy values (the length of the list is constant for each second). I would like to plot it as a surface, where distribution of the points in the third dimension should be constant (like 1,2,3,4 ...).
I read about the tutorial on surfaces, but the example lists are nested in a way i dont understand it.
What i tried so far:
import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import axes3d
fig = plt.figure()
ax = fig.add_subplot(111, projection='3d')
X, Y, Z = axes3d.get_test_data(0.05)
print(X)
ax.plot_wireframe([1,2,3,4,2,4,6,8], [1,2,3,4,1,2,3,4], [1,1,1,1,2,2,2,2])
plt.show()
Here i assume that on the first seconds the energies are 1,2,3,4 and for the second second they are 2,4,6,8. I tried to manually add the distribution for the third axis (hence 1,2,3,4,1,2,3,4 for the two points).
The code above produces no output.
Can this be done somehow?