[Numpy-discussion] Returning numpy scalars in cython functions

Keith Goodman kwgoodman@gmail....
Thu Nov 18 11:51:04 CST 2010


The cython function below returns a long int:

    @cython.boundscheck(False)
    def mysum(np.ndarray[np.int64_t, ndim=1] a):
        "sum of 1d numpy array with dtype=np.int64."
        cdef Py_ssize_t i
        cdef int asize = a.shape[0]
        cdef np.int64_t asum = 0
        for i in range(asize):
            asum += a[i]
        return asum

What's the best way to make it return a numpy long int, or whatever it
is called, that has dtype, ndim, size, etc. class methods? The only
thing I could come up with is changing the last line to

    return np.array(asum)[()]

It works. And adds some overhead:

>> a = np.arange(10)
>> timeit mysum(a)
10000000 loops, best of 3: 167 ns per loop
>> timeit mysum2(a)
1000000 loops, best of 3: 984 ns per loop

And for scale:

>> timeit np.sum(a)
100000 loops, best of 3: 3.3 us per loop

I'm new to cython. Did I miss any optimizations in the mysum function above?


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