Numpy vs Cython speed

Question

I have an analysis code that does some heavy numerical operations using numpy. Just for curiosity, tried to compile it with cython with little changes and then I rewrote it

Answer 1

I'd guess the main overhead you are saving is the temporary arrays created. You create a great big array array - array[row, :], then reduce it into a smaller array using sum. But building that big temporary array won't be free, especially if you need to allocate memory.