graph the contents of a matrix in python (using matplotlib)

Question

Hi I need to graph the contents of a matrix where each row represents a different feature and each column is a different time point. In other words, I want to see the change in features over time and I have stacked each feature in the form of a matrix. C is the matrix

A=C.tolist() #convert matrix to list. R=[] for i in xrange(len(A[0])): R+=[[i]*len(A[i])] for j in xrange(len(A[0])): S=[] S=C[0:len(C)][j] pylab.plot(R[j],S,'r*') pylab.show()

Is this right/is there a more efficient way of doing this? Thanks!

Avaris · Accepted Answer · 2012-08-24 01:16:01Z

From the docs:

matplotlib.pyplot.plot(*args, **kwargs): 
[...]
plot(y) # plot y using x as index array 0..N-1 plot(y, 'r+') # ditto, but with red plusses 
If x and/or y is 2-dimensional, then the corresponding columns will be plotted.

So if A has the values in columns, it is as simple as:

pylab.plot(A, 'r*') # making all red might be confusing, '*-' might be better

If your data is in rows, then plot the transpose of it:

pylab.plot(A.T, 'r*')

aaren · Accepted Answer · 2012-08-24 00:34:25Z

You can extract column i of a matrix M with M[:,i] and the number of columns in M is given by M.shape[1].

import matplotlib.pyplot as plt T = range(M.shape[0]) for i in range(M.shape[1]): plt.plot(T, M[:,i]) plt.show()

This assumes that the rows represent equally spaced timeslices.

Actually, you can do it a lot easier with plt.plot(M.T) - as in the answer below.

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