NumPy selecting specific column index per row by using a list of indexes

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If you’ve got a boolean array you can do direct selection based on that like so:

>>> a = np.array([True, True, True, False, False])
>>> b = np.array([1,2,3,4,5])
>>> b[a]
array([1, 2, 3])

To go along with your initial example you could do the following:

>>> a = np.array([[1,2,3], [4,5,6], [7,8,9]])
>>> b = np.array([[False,True,False],[True,False,False],[False,False,True]])
>>> a[b]
array([2, 4, 9])

You can also add in an arange and do direct selection on that, though depending on how you’re generating your boolean array and what your code looks like YMMV.

>>> a = np.array([[1,2,3], [4,5,6], [7,8,9]])
>>> a[np.arange(len(a)), [1,0,2]]
array([2, 4, 9])

Hope that helps, let me know if you’ve got any more questions.

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