Cumulative summation of a numpy array by index
If I understand the question correctly, there is a fast function for this (as long as the data array is 1d)
>>> i = np.array([0,0,1,2,2])>>> d = np.array([0,1,2,3,4])>>> np.bincount(i, weights=d)array([ 1., 2., 7.])np.bincount returns an array for all integers range(max(i)), even if some counts are zero
This solution should be more efficient for large arrays (it iterates over the possible index values instead of the individual entries of i):
import numpy as npi = np.array([0,0,1,2,2])d = np.array([0,1,2,3,4])i_max = i.max()c = np.empty(i_max+1)for j in range(i_max+1): c[j] = d[i==j].sum()print c[1. 2. 7.]