CODEWITHSUNDEEP
pythonnumpy
Paul T.
Paul T.

Reputation: 326

never allocate an output of numpy.ufunc

This question has info on using an input as an output to compute something in place with a numpy.ufunc:

Is it possible to avoid allocating space for an unwanted output of a numpy.ufunc? For example, say I only want one of the two outputs from modf. Can I ensure that the other, unwanted array is never allocated at all?

I thought passing _ to out might do it, but it throws an error:

import numpy as np
ar = np.arange(6)/3
np.modf(ar, out=(ar, _))    

TypeError: return arrays must be of ArrayType

As it says in the docs, passing None means that the output array is allocated in the function and returned. I can ignore the returned values, but it still has to be allocated and populated inside the function.

Upvotes: 2

Views: 287

Answers (1)

ZisIsNotZis
ZisIsNotZis

Reputation: 1740

You can minimize allocation by passing a "fake" array:

ar = np.arange(6) / 3
np.modf(ar, ar, np.broadcast_arrays(ar.dtype.type(0), ar)[0])

This dummy array is as big as a single double, and modf will not do allocation internally.

EDIT According to suggestions from @Eric and @hpaulj, a more general and long-term solution would be

np.lib.stride_tricks._broadcast_to(np.empty(1, ar.dtype), ar.shape, False, False)

Upvotes: 4

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