[Numpy-discussion] failed to add routine to the core module

[Sebastian Berg]

On Thu, 2017-05-18 at 15:04 +0200, marc wrote:
> Dear Numpy developers,
> I'm trying to add a routine to calculate the sum of a product of two
> arrays (a dot product). But that would not increase the memory (from
> what I saw np.dot is increasing the memory while it should not be
> necessary). The idea is to avoid the use of the temporary array in
> the calculation of the variance ( numpy/numpy/core/_methods.py line
> 112).

np.dot should only increase memory in some cases (such as non-
contiguous arrays) and be much faster in most cases (unless e.g. you do
not have a BLAS compatible type). You might also want to check out
np.einsum, which is pretty slick and can handle these kind of
operations as well. Note that `np.dot` calls into BLAS so that it is in
general much faster then np.einsum.

- Sebastian

> The routine that I want to implement look like this in python,
> arr = np.random.rand(100000)
> mean = arr.mean()
> var = 0.0
> for ai in arr: var += (ai-mean)**2
> I would like to implement it in the umath module. As a first step, I
> tried to reproduce the divmod function of umath, but I did not manage
> to do it, you can find my fork here (the branch with the changes is
> call looking_around). During compilation I get the following error,
> gcc: numpy/core/src/multiarray/number.c 
> In file included from numpy/core/src/multiarray/number.c:17:0:
> numpy/core/src/multiarray/number.c: In function
> ‘array_sum_multiply’: 
> numpy/core/src/private/binop_override.h:176:39: error:
> ‘PyNumberMethods {aka struct <anonymous>}’ has no member named
> ‘nb_sum_multiply’ (void*)(Py_TYPE(m2)->tp_as_number->SLOT_NAME) !=
> (void*)(test_func)) 
>                             ^ 
> numpy/core/src/private/binop_override.h:180:13: note: in expansion of
> macro ‘BINOP_IS_FORWARD’ if (BINOP_IS_FORWARD(m1, m2, slot_expr,
> test_func) && \
>         ^ 
> numpy/core/src/multiarray/number.c:363:5: note: in expansion of macro
> ‘BINOP_GIVE_UP_IF_NEEDED’ BINOP_GIVE_UP_IF_NEEDED(m1, m2,
> nb_sum_multiply, array_sum_multiply);
> Sorry if my question seems basic, but I'm new in Numpy development.
> Any help?
> Thank you in advance,
> Marc Barbry
> 
> PS: I opened an issues as well on the github repository
> https://github.com/numpy/numpy/issues/9130 
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