compare consecutive values of an array numpy

Question

I have a vector A and I want to find all the "i" values of the array which are bigger than the neighboring values, i.e. right before (i-1) and right after (i+1). I wrote a simple code (surely with mistakes) that should print the array (y_maxtab) containing the "i" values. I try to run and It gets stacked. Could you help me on that?

import numpy as np

y_maxtab = []


A=np.array([2.0,2.5,1.7,5,7,8,9,3,5,3,7,8])

i=1

while i <= len(A):
   if A[i] > A[i-1] and a[i] > A[i+1]:
         y_maxtab.append(A[i])
         i=i+1
print y_maxtab

wflynny · Accepted Answer · 2014-07-10 20:12:01Z

1

Well, your code as is has some problems.

If the first if statement fails, you will never increment i, and will be stuck in an infinite loop.
The second clause of the if statement has an undefined reference (a).
The while statement will allow values of i which will cause IndexErrors with A[i] and A[i+1].

If you are committed to keeping the code in the same form, you could change it so that it looks like

i = 1
while i < len(A)-1:
    if A[i] > A[i-1] and a[i] > A[i+1]:
        y_maxtab.append(A[i])
    i=i+1
print y_maxtab
# [2.5, 9.0, 5.0]

However, a more pythonic way would be something like

for first, middle, last in zip(A[:], A[1:], A[2:]):
    if first < middle > last:
        y_maxtab.append(middle)
print y_maxtab
# [2.5, 9.0, 5.0]

edited Jul 10, 2014 at 20:12

answered Jul 10, 2014 at 14:59

wflynny

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5 Comments

user2379410 Over a year ago

+1 for pointing out and fixing the errors. But the indexing in the zip() is a bit inconsistent.

wflynny Over a year ago

Since zip stops once the shortest iterable is exhausted, I wasn't careful. To me, it makes the most sense as I've edited it, although the way it's written in @Eelco's answer may be preferable to some.

user2379410 Over a year ago

I agree, this behavior of zip is well known and it looks nicer

wflynny Over a year ago

Perhaps the downvote is due to not utilizing the power of numpy, but it doesn't seem that OP grasps when one should use numpy.array over list.

diegus Over a year ago

My corrected code works fine and also the more pythonic version, thanks a lot!!

Eelco Hoogendoorn · Accepted Answer · 2014-07-10 16:00:43Z

1

Here is a solution that uses numpy directly. Far faster and cleaner than a python loop, and moreover, it does what you intend it to.

local_maximum = (A[:-2]<A[1:-1]) & (A[2:]<A[1:-1])
print A[1:-1][local_maximum]

Or slightly more verbose, but perhaps more readable:

left, mid, right = A[:-2], A[1:-1], A[2:]
local_maximum = (left<mid) & (right<mid)
print mid[local_maximum]

answered Jul 10, 2014 at 16:00

Eelco Hoogendoorn

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