Matplotlib displaying uneven data in a 3D surface

Question

I have simple code for plotting points in 3D for Matplotlib, as shown below -

from mpl_toolkits.mplot3d import axes3d import matplotlib.pyplot as plt import numpy as np from numpy import genfromtxt import csv fig = plt.figure() ax = fig.add_subplot(111, projection='3d') my_data = genfromtxt('points1.csv', delimiter=',') points1X = my_data[:,0] points1Y = my_data[:,1] points1Z = my_data[:,2] ## I remove the header of the CSV File. points1X = np.delete(points1X, 0) points1Y = np.delete(points1Y, 0) points1Z = np.delete(points1Z, 0) # Convert the array to 1D array points1X = np.reshape(points1X,points1X.size) points1Y = np.reshape(points1Y,points1Y.size) points1Z = np.reshape(points1Z,points1Z.size) my_data = genfromtxt('points2.csv', delimiter=',') points2X = my_data[:,0] points2Y = my_data[:,1] points2Z = my_data[:,2] ## I remove the header of the CSV File. points2X = np.delete(points2X, 0) points2Y = np.delete(points2Y, 0) points2Z = np.delete(points2Z, 0) # Convert the array to 1D array points2X = np.reshape(points2X,points2X.size) points2Y = np.reshape(points2Y,points2Y.size) points2Z = np.reshape(points2Z,points2Z.size) ax.plot(points1X, points1Y, points1Z, 'd', markersize=8, markerfacecolor='red', label='points1') ax.plot(points2X, points2Y, points2Z, 'd', markersize=8, markerfacecolor='blue', label='points2') plt.show() 

My problem is that I tried to make a decent surface graph from the data that I have. I already tried to use the ax.plot_surface() function to make it beautiful. To do this, I eliminated some points and recounted the matrix form of input required by this function. However, the graph I constructed is much more difficult to interpret and understand. Thus, there may be two possibilities: either I am not using the function correctly, or otherwise, the data I am trying to build is not suitable for a surface graph.

What I was expecting is a 3D plot that will have an effect similar to the one we have on the 3D pie chart. We see that one part (what is extracted) is part of another part. I did not expect it to be exactly the same as this, but some kind of effect is.

I would like to ask:

• Do you think it will be possible to make such a 3D graph?
• Is there a better way, could I express my data in 3 dimensions?

Here are 2 files -

points1.csv

 Dim1,Dim2,Dim3 3,8,1 3,8,2 3,8,3 3,8,4 3,8,5 3,9,1 3,9,2 3,9,3 3,9,4 3,9,5 3,10,1 3,10,2 3,10,3 3,10,4 3,10,5 3,11,1 3,11,2 3,11,3 3,11,4 3,11,5 3,12,1 3,12,2 3,13,1 3,13,2 3,14,1 3,14,2 3,15,1 3,15,2 3,16,1 3,16,2 3,17,1 3,17,2 3,18,1 3,18,2 4,8,1 4,8,2 4,8,3 4,8,4 4,8,5 4,9,1 4,9,2 4,9,3 4,9,4 4,9,5 4,10,1 4,10,2 4,10,3 4,10,4 4,10,5 4,11,1 4,11,2 4,11,3 4,11,4 4,11,5 4,12,1 4,13,1 4,14,1 4,15,1 4,16,1 4,17,1 4,18,1 5,8,1 5,8,2 5,8,3 5,8,4 5,8,5 5,9,1 5,9,2 5,9,3 5,9,4 5,9,5 5,10,1 5,10,2 5,10,3 5,10,4 5,10,5 5,11,1 5,11,2 5,11,3 5,11,4 5,11,5 5,12,1 5,13,1 5,14,1 5,15,1 5,16,1 5,17,1 5,18,1 6,8,1 6,8,2 6,8,3 6,8,4 6,8,5 6,9,1 6,9,2 6,9,3 6,9,4 6,9,5 6,10,1 6,11,1 6,12,1 6,13,1 6,14,1 6,15,1 6,16,1 6,17,1 6,18,1 7,8,1 7,8,2 7,8,3 7,8,4 7,8,5 7,9,1 7,9,2 7,9,3 7,9,4 7,9,5 

and points2.csv

 Dim1,Dim2,Dim3 3,12,3 3,12,4 3,12,5 3,13,3 3,13,4 3,13,5 3,14,3 3,14,4 3,14,5 3,15,3 3,15,4 3,15,5 3,16,3 3,16,4 3,16,5 3,17,3 3,17,4 3,17,5 3,18,3 3,18,4 3,18,5 4,12,2 4,12,3 4,12,4 4,12,5 4,13,2 4,13,3 4,13,4 4,13,5 4,14,2 4,14,3 4,14,4 4,14,5 4,15,2 4,15,3 4,15,4 4,15,5 4,16,2 4,16,3 4,16,4 4,16,5 4,17,2 4,17,3 4,17,4 4,17,5 4,18,2 4,18,3 4,18,4 4,18,5 5,12,2 5,12,3 5,12,4 5,12,5 5,13,2 5,13,3 5,13,4 5,13,5 5,14,2 5,14,3 5,14,4 5,14,5 5,15,2 5,15,3 5,15,4 5,15,5 5,16,2 5,16,3 5,16,4 5,16,5 5,17,2 5,17,3 5,17,4 5,17,5 5,18,2 5,18,3 5,18,4 5,18,5 6,10,2 6,10,3 6,10,4 6,10,5 6,11,2 6,11,3 6,11,4 6,11,5 6,12,2 6,12,3 6,12,4 6,12,5 6,13,2 6,13,3 6,13,4 6,13,5 6,14,2 6,14,3 6,14,4 6,14,5 6,15,2 6,15,3 6,15,4 6,15,5 6,16,2 6,16,3 6,16,4 6,16,5 6,17,2 6,17,3 6,17,4 6,17,5 6,18,2 6,18,3 6,18,4 6,18,5 7,10,1 7,10,2 7,10,3 7,10,4 7,10,5 7,11,1 7,11,2 7,11,3 7,11,4 7,11,5 7,12,1 7,12,2 7,12,3 7,12,4 7,12,5 7,13,1 7,13,2 7,13,3 7,13,4 7,13,5 7,14,1 7,14,2 7,14,3 7,14,4 7,14,5 7,15,1 7,15,2 7,15,3 7,15,4 7,15,5 7,16,1 7,16,2 7,16,3 7,16,4 7,16,5 7,17,1 7,17,2 7,17,3 7,17,4 7,17,5 7,18,1 7,18,2 7,18,3 7,18,4 7,18,5 

Answer 1

I don’t see where your problem is, besides, you need to focus your data. Here is what your data from points1.csv :

 import numpy as np from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from scipy.interpolate import griddata fig = plt.figure(figsize=plt.figaspect(0.5)) ax = fig.add_subplot(1, 2, 1, projection='3d') # note this: you can skip rows! my_data = np.genfromtxt('file1.csv', delimiter=',',skiprows=1) X = my_data[:,0] Y = my_data[:,1] Z = my_data[:,2] xi = np.linspace(X.min(),X.max(),100) yi = np.linspace(Y.min(),Y.max(),100) # VERY IMPORTANT, to tell matplotlib how is your data organized zi = griddata((X, Y), Z, (xi[None,:], yi[:,None]), method='cubic') CS = plt.contour(xi,yi,zi,15,linewidths=0.5,color='k') ax = fig.add_subplot(1, 2, 2, projection='3d') xig, yig = np.meshgrid(xi, yi) surf = ax.plot_surface(xig, yig, zi, linewidth=0) plt.show() 

Hope this helps.