Numpy array - change the next element based on a change on previous

Question

Let's say I have two numpy arrays:

import numpy as np
a = np.ones(5)
b = np.array([1.0, 1.1, 1.05, 1.2, 1.25])

I'd like that element a[1]=a[0]*b[1], lets call this a[1] a new_a, then a[2]=new_a*b[2]. Can this be done without using a loop in numpy? With a loop code looks like this:

for i in range(len(a)-1):
    a[i+1] = a[i]*b[i+1]
print (a)

prints:

[ 1.      1.1     1.155   1.386   1.7325]

kennytm · Accepted Answer · 2012-10-26 16:54:17Z

4

This is called "cumulative product". There is already a built-in function cumprod for this.

>>> numpy.cumprod([1.0, 1.1, 1.05, 1.2, 1.25])
array([ 1.    ,  1.1   ,  1.155 ,  1.386 ,  1.7325])

answered Oct 26, 2012 at 16:54

kennytm

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2 Comments

enedene Over a year ago

You did solve my particular problem, but what about a general case where you can't ignore the value of a?

kennytm Over a year ago

@enedene: You could do b[0] *= a[0] before calling cumprod if you could modify b, or multiply the whole result by a[0] (i.e. cumprod(...) * a[0].

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