Utility of parameter 'out' in numpy functions

Question

What is the utility of the out parameter in certain numpy functions such as cumsum or cumprod or other mathematical functions?

If the result is huge in size does it help to use the out parameter to improve computational time or memory efficiency?

This thread gives some information about how to use it. But I want to know when should I use it and what could the benefits be?

Did you read the answers? E.g. "Controlling the dtype is one reason to use out. Another is to conserve memory by 'reusing' an array that already exists." — jonrsharpe
– jonrsharpe, Commented Dec 4, 2014 at 12:26
@jonrsharpe yes I did my dear. But I was looking for a bit more explanation. — Sounak
– Sounak, Commented Dec 4, 2014 at 12:38
Then mention that in your question. What did you understand from that, and what was unclear about it? Try to be specific when asking questions. — jonrsharpe
– jonrsharpe, Commented Dec 4, 2014 at 12:39
@jonrsharpe can you make your comment an answer. The dtype issue is what I came to this post looking for and it isn't addressed in the other answer. — zozo
– zozo, Commented Mar 18, 2020 at 17:14

cel · Accepted Answer · 2014-12-04 12:39:43Z

27

Functions that take the out parameter create new objects. This is usually what you would expect from the function: Give some array and get a new one with the transformed data.

However, imagine you want to call this function several thousand times in a row. Each function call will create a new array, which of course takes a lot of time.

In this case you may want to create an output array out and let the function fill the array with the output. After processing the data you can reuse out and let the function overwrite its values. This way you won't allocate or free any memory, which can save you a lot of time.

edited Dec 4, 2014 at 12:39

answered Dec 4, 2014 at 12:31

cel

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2 Comments

Sounak Over a year ago

array.cumsum(0,out=array) array.cumsum(1,out=array) array.cumsum(2,out=array) is better than array.cumsum(0).cumsum(1).cumsum(2)

Jaime Over a year ago

I think you should still be able to do array.cumsum(0, out=array).cumsum(1, out=array).cumsum(2, out=array) if you want to keep it a one-liner.

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