How do I sum only certain elements from an array?

Question

I want to sum only the elements from the array out that have a value less than 0.49, but I'm not sure how to implement a filter for that criteria. Here is what I have so far:

def outcome(surveys,voters):
    out = np.random.random((surveys,voters))
    rep = [0]*surveys
    for i in range(0,surveys):
        rep[i] = sum(out[i,:])
    return rep

Any help is greatly appreciated, Thanks in advance!

numpy.random.random((x,y)) returns an x by y array of random numbers from 0 to 1. — pauld
– pauld, Commented Jul 23, 2014 at 13:48

deinonychusaur · Accepted Answer · 2014-07-23 13:49:30Z

3

I would use masked arrays and then just sum along the axis:

out = np.ma.masked_greater_equal(np.random.random((surveys,voters)), 0.49)
rep = out.sum(axis=1)

answered Jul 23, 2014 at 13:49

deinonychusaur

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Cory Kramer · Accepted Answer · 2014-07-23 13:45:31Z

2

>>> l = [0.25, 0.1, 0.5, 0.75, 0.1, 0.9]
>>> sum(i for i in l if i < 0.49)
0.44999999999999996

Alternatively

>>> l = [0.25, 0.1, 0.5, 0.75, 0.1, 0.9]
>>> sum(filter(lambda x: x < 0.49, l))
0.44999999999999996

answered Jul 23, 2014 at 13:45

Cory Kramer

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Comments

toine · Accepted Answer · 2014-07-23 14:05:20Z

0

you can use comparison directly on the array, that will return a boolean or mask array useful to access the interesting part of the array, see http://docs.scipy.org/doc/numpy/user/basics.indexing.html.

in other words,

def outcome(surveys,voters):
    out = np.random.random((surveys,voters))
    rep = [0]*surveys
    for i in range(0,surveys):
        rep[i] = sum(out[i,out[i,:]<0.49])
    return rep

edited Jul 23, 2014 at 14:05

answered Jul 23, 2014 at 13:51

toine

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1 Comment

deinonychusaur Over a year ago

This will sum only those larger than 0.49 rather than only those less. And while it works in principle, iterating out in python is unneccesary and by far slower than using the built in functionality of numpy

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