Can I cleanse a numpy array without a loop?

Question

Perhaps not such a big deal, but it breaks my heart to follow this:

deltas = data[1:] - data[:-1]

with this:

for i in range(len(deltas)):
        if deltas[i] < 0: deltas[i] = 0
        if deltas[i] > 100: deltas[i] = 0

For this particular example...is there a better way to do the cleansing part?

Question part two: What if the cleansing rules are more complicated, or less complicated than this example. For example, we might just want to change all negative numbers to zero. Or, we might be doing a more complicated mapping.

unutbu · Accepted Answer · 2010-12-02 23:44:33Z

9

import numpy as np
deltas=np.diff(data)
deltas[deltas<0]=0
deltas[deltas>100]=0

Also possible, and a bit quicker is

deltas[(deltas<0) | (deltas>100)]=0

edited Dec 2, 2010 at 23:44

answered Dec 2, 2010 at 20:05

unutbu

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Karl Knechtel · Accepted Answer · 2010-12-02 20:08:03Z

1

Try using numpy.vectorize to apply a function to each element of the numpy array.

answered Dec 2, 2010 at 20:08

Karl Knechtel

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