Compare adjacent values in numpy array

Question

I have a Numpy one-dimensional array of data, something like this

a = [1.9, 2.3, 2.1, 2.5, 2.7, 3.0, 3.3, 3.2, 3.1]

I want to create a new array, where the values are composed of the greater of the adjacent values. For the above example, the output would be:

b = [2.3, 2.3, 2.5, 2.7, 3.0, 3.3, 3.3, 3.2]

I can do this by looping through the input array, comparing the neighbouring values, eg:

import numpy as np

a = np.array([1.9, 2.3, 2.1, 2.5, 2.7, 3.0, 3.3, 3.2, 3.1])
b = np.zeros(len(a)-1)

for i in range(len(a)-1):
    if (a[i] > a[i+1]):
        b[i] = a[i]
    else:
        b[i] = a[i+1]

but I'd like to do this in a more elegant "pythonic" vectorised fashion. I've searched and read about np.zip, np.where, np.diff etc but haven't yet found a way to do this (or more likely, I haven't understood what is possible). Any suggestions ?

Alok Singhal · Accepted Answer · 2016-07-19 04:40:48Z

6

You want element-wise maximum of a[1:] and a[:-1]:

>>> a
array([ 1.9,  2.3,  2.1,  2.5,  2.7,  3. ,  3.3,  3.2,  3.1])
>>> a[1:]
array([ 2.3,  2.1,  2.5,  2.7,  3. ,  3.3,  3.2,  3.1])
>>> a[:-1]
array([ 1.9,  2.3,  2.1,  2.5,  2.7,  3. ,  3.3,  3.2])
>>> np.maximum(a[1:], a[:-1])
array([ 2.3,  2.3,  2.5,  2.7,  3. ,  3.3,  3.3,  3.2])

answered Jul 19, 2016 at 4:40

Alok Singhal

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1 Comment

Geoff S Over a year ago

Brilliant, thanks ! That was just what I was looking for. Simple once you see it :)

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