In NumPy how do I get the maximum of subsets Python

Question

8down votefavorite

I have an array of values, said v, (e.g. v=[1,2,3,4,5,6,7,8,9,10]) and an array of indexes, say g(e.g. g=[0,0,0,0,1,1,1,1,2,2]).

I know, for instance, how to take the first element of each group, in a very numpythonic way, doing:

import numpy as np
v=np.array([1,2,3,4,74,73,72,71,9,10])
g=np.array([0,0,0,0,1,1,1,1,2,2])
mask=np.concatenate(([True],np.diff(g)!=0))
v[mask]

returns:

array([1, 74, 9])

Is there any numpythonic way (avoiding explicit loops) to get the maximum of each subset?

Answer 1

You can use np.maximum.reduceat:

>>> _, idx = np.unique(g, return_index=True)
>>> np.maximum.reduceat(v, idx)
array([ 4, 74, 10])