Given an index array idx that only contains 0 and 1 elements, and 1s represent the sample indices of interest, and a sample array A (A.shape[0] = idx.shape[0]). The objective here is to extract a subset of samples based on the index vector.
In matlab, it is trivial to do:
B = A(idx,:) %assuming A is 2D matrix and idx is a logical vector
How to achieve this in Python in a simple manner?
If your mask array idx has the same shape as your array A, then you should be able to extract elements specified by the mask if you convert idx to a boolean array, using astype.
Demo -
>>> A
array([[ 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]])
>>> idx
array([[1, 0, 0, 1, 1],
[0, 0, 0, 1, 0],
[1, 0, 0, 1, 1],
[1, 0, 0, 1, 1],
[0, 1, 1, 1, 1]])
>>> A[idx.astype(bool)]
array([ 0, 3, 4, 8, 10, 13, 14, 15, 18, 19, 21, 22, 23, 24])
A[idx.astype(bool)]I suppose?