How do I get indices of N maximum values in a NumPy array? How do I get indices of N maximum values in a NumPy array? python python

# How do I get indices of N maximum values in a NumPy array?

Newer NumPy versions (1.8 and up) have a function called `argpartition` for this. To get the indices of the four largest elements, do

``>>> a = np.array([9, 4, 4, 3, 3, 9, 0, 4, 6, 0])>>> aarray([9, 4, 4, 3, 3, 9, 0, 4, 6, 0])>>> ind = np.argpartition(a, -4)[-4:]>>> indarray([1, 5, 8, 0])>>> a[ind]array([4, 9, 6, 9])``

Unlike `argsort`, this function runs in linear time in the worst case, but the returned indices are not sorted, as can be seen from the result of evaluating `a[ind]`. If you need that too, sort them afterwards:

``>>> ind[np.argsort(a[ind])]array([1, 8, 5, 0])``

To get the top-k elements in sorted order in this way takes O(n + k log k) time.

The simplest I've been able to come up with is:

``In : import numpy as npIn : arr = np.array([1, 3, 2, 4, 5])In : arr.argsort()[-3:][::-1]Out: array([4, 3, 1])``

This involves a complete sort of the array. I wonder if `numpy` provides a built-in way to do a partial sort; so far I haven't been able to find one.

If this solution turns out to be too slow (especially for small `n`), it may be worth looking at coding something up in Cython.

Simpler yet:

``idx = (-arr).argsort()[:n]``

where n is the number of maximum values.