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
<https://github.com/mbarbry/numpy/tree/looking_around> (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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