logically adding in numpy

Question

I want to do the following operation. But It likes the histogram operation.

maxIndex = 6    
dst  =zeros((1,6))
a    =array([1,2,3,4,7,0,3,4,5,7])
index=array([1,1,1,3,3,4,4,5,5,5])

a's length == index's length,

for i in (a.size):
    dst[index[i]] = dst[index[i]] + a[i]

How can I do this more pythonic. and more efficiently

possible duplicate of Assigning identical array indices at once in Python/Numpy — Daniel
– Daniel, Commented Aug 30, 2013 at 12:54
This question appears to belong on codereview.stackexchange.org — David Pope
– David Pope, Commented Mar 2, 2014 at 0:10

Alok Singhal · Accepted Answer · 2013-08-30 08:03:38Z

4

If I understand correctly, I think you are looking for numpy.bincount:

dst = numpy.bincount(index, weights=a, minlength=maxIndex)

This give me array([ 0., 6., 0., 11., 3., 16.]) as the output. If you don't want to calculate maxIndex by hand, you can omit minlength parameter from the function call and numpy will return an appropriately-sized array for you.

answered Aug 30, 2013 at 8:03

Alok Singhal

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3 Comments

kennytm Over a year ago

minlength should be set to maxIndex to match OP's output.

Alok Singhal Over a year ago

@KennyTM I think you're right. I wasn't sure what maxIndex was doing in his question. What the OP probably really wants is the default behavior, without the minlength parameter since that will return an array with a non-zero last element...

Samuel Over a year ago

very nice. That's what i want

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