Adding through an array with np.where function Numpy Python

Question

I am trying to write a function where it adds the Sequence one at a time until the Number is reached. So since the the sum of the Sequence array is 21 and not 45 it will add the first element of the Sequence 3 to the Sequence so it becomes [3, 7, 11, 3]. Since [3, 7, 11, 3] is equal to 24 and is lower than 45 the next element in the Sequence is going to be added which is 7, the Sequence is updated to be [3, 7, 11, 3, 7] and so on until Number> np.sum([Sequence] is does not return True. The np.where function below is faulty how can I fix it?

Code:

Number = 45
Number2= 46
Sequence = np.array([3, 7, 11])
p = 0
np.where(Number> np.sum([Sequence]),np.append(Sequence,Sequence[p], p+= 1))
np.where(Number2> np.sum([Sequence]),np.append(Sequence,Sequence[p], p+= 1))

Expected Output

Number = [3,7,11,3,7,11,3]
Number2 = [3,7,11,3,7,11,3,7]

Python evaluates function arguments first, and then passes in the results. where is a function, not an iterator. Practice with where in an interactive session before trying to do something fancy like this. — hpaulj
– hpaulj, Commented Mar 5, 2021 at 6:16
Except for functions like np.cumsum most numpy functions operate on their inputs 'in-parallel', as whole arrays.. They do not operate sequentially. Lists are better for sequential tasks like yours. — hpaulj
– hpaulj, Commented Mar 5, 2021 at 6:25
Is there anyway I could implant what I am trying to do with a pandas module or np.cumsum — ege Selcuk
– ege Selcuk, Commented Mar 5, 2021 at 21:51

Tim Roberts · Accepted Answer · 2021-03-05 05:26:59Z

1

I'm not convinced this can be done as a one-liner. The second and third parameters to np.where are supposed to be sequences. It's easy as a loop:

seq45 = []
for n in itertools.cycle(Sequence):
    seq45.append(n)
    if sum(seq45) >= 45: break

answered Mar 5, 2021 at 5:26

Tim Roberts

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2 Comments

ege Selcuk Over a year ago

I am trying to use numpy functions since its more optimized but thanks anyways.

Tim Roberts Over a year ago

Confucious say, a working non-optimal solution is better than a non-working optimized solution.... You can of course make seq45 an np.array.

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