Increment Numpy multi-d array with repeated indices

Question

I'm interested in the multi-dimensional case of Increment Numpy array with repeated indices.

I have an N-dimensional array and a set N index arrays, who's values I want to increment. The index arrays might have have repeated entries.

Without repeats, the solution is

a = arange(24).reshape(2,3,4)
i = array([0,0,1])
j = array([0,1,1])
k = array([0,0,3])
a[i,j,k] += 1

With repeats, (ex. j=array([0,0,2]) ), I'm unable to make numpy increment the replicates.

JoshAdel · Accepted Answer · 2011-09-15 17:40:07Z

4

How about this:

import numpy as np
a = np.zeros((2,3,4))
i = np.array([0,0,1])
j = np.array([0,0,1])
k = np.array([0,0,3])

ijk = np.vstack((i,j,k)).T
H,edge = np.histogramdd(ijk,bins=a.shape)
a += H

answered Sep 15, 2011 at 17:40

JoshAdel

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1 Comment

ajwood Over a year ago

I'm using this with cubic bins and flatten cubes of the same size for i,j and k. Any idea why it starts to break down on arrays larger than 27x27x27?

steabert · Accepted Answer · 2011-09-15 15:50:31Z

0

I don't know if there is an easier solution with direct array indexing, but this works:

for x,y,z in zip(i,j,k):
    a[x,y,z] +=1

answered Sep 15, 2011 at 15:50

steabert

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