Shuffling non-zero elements of each row in an array - Python / NumPy

Question

I have a an array that is relatively sparse, and I would like to go through each row and shuffle only the non-zero elements.

Example Input:

[2,3,1,0] [0,0,2,1] 

Example Output:

[2,1,3,0] [0,0,1,2] 

Note how the zeros have not changed position.

To shuffle all elements in each row (including zeros) I can do this:

for i in range(len(X)):     np.random.shuffle(X[i, :]) 

What I tried to do then is this:

for i in range(len(X)):     np.random.shuffle(X[i, np.nonzero(X[i, :])]) 

But it has no effect. I've noticed that the return type of X[i, np.nonzero(X[i, :])] is different from X[i, :] which might be the cause.

In[30]: X[i, np.nonzero(X[i, :])] Out[30]: array([[23,  5, 29, 11, 17]])  In[31]: X[i, :] Out[31]: array([23,  5, 29, 11, 17]) 

Answer 1

You could use the non-inplace numpy.random.permutation with explicit non-zero indexing:

>>> X = np.array([[2,3,1,0], [0,0,2,1]]) >>> for i in range(len(X)): ...     idx = np.nonzero(X[i]) ...     X[i][idx] = np.random.permutation(X[i][idx]) ...  >>> X array([[3, 2, 1, 0],        [0, 0, 2, 1]])