如何有效地排序一个numpy矩阵

Question

I have this numpy array

matrix = np.array([[ 0.8,  0.2,  0.1],
   [ 1. ,  0. ,  0. ],
   [ 0. ,  0. ,  1. ]])

and I would like to filter to return, for each row of matrix the indices in decreasing value order.

For example, this would be

np.array([[0, 1, 2], [0, 1, 2], [2, 0, 1]])

I know I could use np.argsort , but this doesn't seem to be returning the right output. I tried changing the axis to different values, but that doesn't help either.

Answer 1

Probably the easiest way to get your desired output would be:

(-matrix).argsort(axis=1)
# array([[0, 1, 2],
#        [0, 1, 2],
#        [2, 0, 1]])

Answer 2

I think np.argsort does seem to do the trick, you just need to make sure to flip the matrix horizontally to make it decreasing order:

>>>matrix = np.array(
[[ 0.8,  0.2,  0.1],
[ 1. ,  0. ,  0. ],
[ 0. ,  0. ,  1. ]])

>>> np.fliplr(np.argsort(matrix))
array([[0, 1, 2],
       [0, 2, 1],
       [2, 1, 0]])

This should be the right output unless you have any requirements for sorting ties. Right now the flipping would make the rightmost tie the first index. If you wanted to match your exact output, where the leftmost index is first you could do a bit of juggling:

# Flip the array first and get the indices
>>> flipped = np.argsort(np.fliplr(matrix))

# Subtract the width of your array to reverse the indices
# Flip the array to be in descending order
>>> np.fliplr(abs(flipped - flipped.shape[1]))
array([[0, 1, 2],
       [0, 1, 2],
       [2, 0, 1]])