How can divide every element of an array by the sum of the array?

Question

I have the following array:

propensity = [32.  0.  0.]

I've calculated the sum of the array as follows:

a0 = sum(propensity)

I'm trying to calculate a fraction for every element of the array over the sum of the array and have written the following function:

def prob_rxn_fires(propensity, a0):
for x in propensity:
    print("propensity:\n", x)  
    prob = x/a0  
print("Prob reaction fires:\n", prob)      
return prob

I want the function to return three fractions for each array element, at the moment it only returns 0. I think that's because when it iterates through the array and reaches the return statement it returns only the last value it computed which is 0/32 = 0.0. I need to return the first 2 values as well but am unsure how to fix this?

Cheers

s3dev · Accepted Answer · 2020-05-04 08:44:52Z

1

What about using numpy?

import numpy as np

propensity = np.array([32.0,  0.0,  0.0])
propensity/sum(propensity)

Output:

array([1., 0., 0.])

answered May 4, 2020 at 8:44

s3dev

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Comments

Adnan · Accepted Answer · 2020-05-04 08:52:17Z

1

You can do simply as

propensity = [32.,  0.0,  0.0]
a0 = sum(propensity)
propensity = [x/a0 for x in propensity]
print(propensity)

Output

[1.0, 0.0, 0.0]

answered May 4, 2020 at 8:52

Adnan

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3 Comments

s3dev Over a year ago

This technique might run into low-level issues as the propensity iterable is being iterated and written in parallel. Consider revising.

Adnan Over a year ago

What sort of low level issues ? ,I think only checkfor division by zero needs to be added , and also for your solution why to import numpy for such simple task

s3dev Over a year ago

TBH I cannot remember all the details. From what I remember, when Python assigns an iterable to a hash table, sometimes the loop will not continue as it considers the next value as already seen, so exits prematurely - due to the order in which hash values are stored. Suggestion: Just assign your list comp output to another variable.

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