No speed gains from Cython

Question

I am trying to define a function that contains an inner loop for simulating an integral.

The problem is speed. Evaluating the function once can take up to 30 seconds on

Answer 1

You could definitely speed up your code by using more of Numpy's capabilities.

For instance:

cdef np.ndarray[double, ndim=1] S = np.zeros(dtype = "d", shape = J)
cdef int j
for j in xrange(ns):
    S += P_i[:,j]

would be much faster and legible as

S = P_i.sum(axis=1)

You also repeat some calculations, which thus take twice more time than necessary. For instance

np.where(data[:,1]==(yr + 72))

could be calculated only once and stored in a variable that you could reuse.

You also perform a lot of reshaping and slicing: it could help to have your variables be in a simpler format from the beginning on. If possible, your code would be much clearer, and optimizations could be much more obvious.