Speed up for-loop in Cython

Question

I am still at the beginning to understand how Cython works. This snippet shows one of the slow parts of my program and I am wondering whether this for loop can be improved. It still pretty much looks like the original Numpy version, but I added the cdef's and int-conversion.

cdef Py_ssize_t i, j
cdef double ii, jj

for ii in np.arange(startx, endx+1, 0.1):
    for jj in np.arange(starty, endy+1, 0.1):
        if my_condition(ii, jj):
            i = <int>ii
            j = <int>jj
            data[i, j] += 1

Do you have any recommendations?

Answer 1

Study the cython example in

https://docs.scipy.org/doc/numpy/reference/arrays.nditer.html

That uses nditer to hand out the array elements.

And

https://cython.readthedocs.io/en/stable/src/userguide/memoryviews.html

which demonstrates the use of memoryviews (and C arrays) to rapidly iterate over the values.

Either way your goal is to let cython access the databuffer directly rather than by way of the numpy functions.

Answer 2

I had the same problem and found this simple solution.

https://github.com/cython/cython/issues/3310#issuecomment-707252866

for i in range(start, stop, step):
    ...

to this:

i = start - step
for _ in range(((stop - start) + (step - 1))//step):
    i += step
    ...