How to filter numpy array by list of indices?

It looks like you just need a basic integer array indexing:

filter_indices = [1,3,5]np.array([11,13,155,22,0xff,32,56,88])[filter_indices] 

numpy.take can be useful and works well for multimensional arrays.

import numpy as npfilter_indices = [1, 2]axis = 0array = np.array([[1, 2, 3, 4, 5],                   [10, 20, 30, 40, 50],                   [100, 200, 300, 400, 500]])print(np.take(array, filter_indices, axis))# [[ 10  20  30  40  50]#  [100 200 300 400 500]]axis = 1print(np.take(array, filter_indices, axis))# [[  2   3]#  [ 20  30]# [200 300]]

Using Docs: https://docs.scipy.org/doc/numpy-1.13.0/user/basics.indexing.htmlThe following implementation should work for arbitrary number of dimensions/shapes for some numpy ndarray.

First we need a multi-dimensional set of indexes and some example data:

import numpy as npy = np.arange(35).reshape(5,7)print(y) indexlist = [[0,1], [0,2], [3,3]]print ('indexlist:', indexlist)

To actually extract the intuitive result the trick is to use a Transpose:

indexlisttranspose = np.array(indexlist).T.tolist()print ('indexlist.T:', indexlisttranspose)print ('y[indexlist.T]:', y[ tuple(indexlisttranspose) ])

Makes the following terminal output:

y: [[ 0  1  2  3  4  5  6] [ 7  8  9 10 11 12 13] [14 15 16 17 18 19 20] [21 22 23 24 25 26 27] [28 29 30 31 32 33 34]]indexlist: [[0, 1], [0, 2], [3, 3]]indexlist.T: [[0, 0, 3], [1, 2, 3]]y[indexlist.T]: [ 1  2 24]

The tuple... fixes a future warning which we can cause like so:

print ('y[indexlist.T]:', y[ indexlisttranspose ])

FutureWarning: Using a non-tuple sequence for multidimensional indexing is deprecated; use `arr[tuple(seq)]` instead of `arr[seq]`.In the future this will be interpreted as an array index,`arr[np.array(seq)]`, which will result either in an error or adifferent result.    print ('y[indexlist.T]:', y[ indexlisttranspose ])y[indexlist.T]: [ 1  2 24]