How to get the cumulative sum of numpy array in-place

Question

I want to compute the integral image. for example

a=array([(1,2,3),(4,5,6)])
b = a.cumsum(axis=0)

This will generate another array b.Can I execute the cumsum in-place. If not . Are there any other methods to do that

Hippocrene

I am not sure what output value you expect if not an array. Could you please precise? – Shira

Answer 1

You have to pass the argument out:

np.cumsum(a, axis=1, out=a)

OBS: your array is actually a 2-D array, so you can use axis=0 to sum along the rows and axis=1 to sum along the columns.

Cosmetician

Is this the same to a=np.cumsum(a,axis=1). How can I confirm the a is the original one – Hippocrene

@Hippocrene in the documentation it states that this function returns a new array, but I don't know how to check if it is the same object, for other objects we could use hash(), but np.ndarrays are unhashable... – Cosmetician

It can be confirmed by the address of a.data. I have confirmed that it's in-place in your way thanks – Hippocrene

@Hippocrene good to know this... I've been using .data in Cython but I never thought of using it for other purposes – Cosmetician

@Hippocrene - Don't use a.data for this. It will only work in a very limited number of cases (e.g. what you're doing where the same array is returned, instead of a new array that shares the same data). Use numpy.may_share_memory instead. – Hearten

Answer 2

Try this using numpy directly numpy.cumsum(a) :

a=array([(1,2,3)])
b = np.cumsum(a)
print b
>>array([1,3,6]) 

Sudatorium