Hello Marten,
Thank you for your help, effectively, the example that you propose is
much easier to imitate, I can now continue further.
Thanks,
Marc
On 05/18/2017 04:32 PM, Marten van Kerkwijk wrote:
Hi Marc,
ufuncs are quite tricky to compile. Part of your problem is that, I
think, you started a bit too high up: `divmod` is also a binary
operation, so that part you do not need at all. It may be an idea to
start instead with a PR that implemented a new ufunc, e.g.,
https://github.com/numpy/numpy/pull/8795, so that you can see what is
involved.
All the best,
Marten
On Thu, May 18, 2017 at 9:04 AM, marc <marc.bar...@mailoo.org> 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).
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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