Plot specific data sets from arrays - Python

Question

Question

I am a physicist with data that consists of 4 numpy.ndarrays, with equal lengths (the data I have is huge, with len ~75k). I am looking for a way to sort and plot data from the arrays.

Let's say I have arrays similar to A,B,C,D below:

A = [1,2,3,1,2,3,1,2,3,1,2,3]
B = [1,1,1,2,2,2,1,1,1,2,2]
C = [1,1,1,1,1,1,2,2,2,2,2]
D = [5,6,3,6,3,5,2,4,6,8,7,9]

Let's now say I would like to do a 3D plot of A,D,B' for each value ofC`. How could I automate this?

Chosen solution

With lots of help from RickardSjogren I wrote the following code to plot and save each of the data series for each value of C.

fig = plt.figure()
C_unique = np.unique(C)

for c in zip(C_unique):
    ax = axes(projection='3d')    
    ax.scatter(A[C == c], D[C == c], B[C == c])
    ax.set_xlabel('A')
    ax.set_ylabel('D')
    ax.set_zlabel('B')
    ax.set_title('C = '+str(c))
    savefig(saveDirectory+'/'+str(c))
    clf()

Can you explain more that what you mean by 3D plot of A,D,B' for each value ofC? — Kasravnd
– Kasravnd, Commented Apr 28, 2015 at 10:53
Plot A,D,B as a x,y,z 3D projection plot, for each value of C. In the case of the arrays shown there, that would mean plot 2 plots of A,D,B, one where C=1, another where C=2. — 8765674
– 8765674, Commented Apr 28, 2015 at 11:03
So is this question related to those tags? if you are looking for a plotting answer you need to mention it! or maybe you want an array? anyway you need to add the code that you have been tried so far! — Kasravnd
– Kasravnd, Commented Apr 28, 2015 at 11:10

RickardSjogren · Accepted Answer · 2015-04-28 11:27:21Z

2

You can do 3D-plots using Matplotlib. From the documentation you simply do:

import matplotlib.pyplot as plt
from mpl_toolkits.mplot3d import Axes3D
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1, projection='3d')

And use the plotting methods of the Axes3D-object referenced by ax.

An example using your data for arbitrary number of C-values:

import numpy as np

A = [1,2,3,1,2,3,1,2,3,1,2]
B = [1,1,1,2,2,2,1,1,1,2,2]
C = [1,1,1,1,1,1,2,2,2,2,2]
D = [5,6,3,6,3,5,2,4,6,8,7]
A, B, C, D = map(np.array, [A, B, C, D])

fig = plt.figure()
c_unique = np.unique(C)
fig.set_size_inches(4 * len(c_unique), 4)

# Add axis for each unique C-value.
axes = [fig.add_subplot(1, len(c_unique), i + 1, projection='3d') for i, _ in enumerate(c_unique)]

for c, ax in zip(c_unique, axes):
    # Use boolean indexing of numpy-arrays to plot values for current C.
    ax.scatter(A[C == c], B[C == c], D[C == c])

    ax.set_xlabel('A')
    ax.set_ylabel('B')
    ax.set_zlabel('D')
    ax.set_title('C = {}'.format(c))

fig.tight_layout()

Result:

3D plot

answered Apr 28, 2015 at 11:27

RickardSjogren

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1 Comment

8765674 Over a year ago

Thanks, I've managed to tweak your code for my purposes. This helped a lot.

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