Python - Multi processing to mount an array

Question

I m using griddata to \"mount\" array with a great number of shapes and i would like to know if i can calculate functions (on each slice) on each my 4 cores in order to accelera

Answer 1

Three things:

1. The most important question is why are you doing this?.
2. Your NumPy build may already be making use of multiple cores. I am not sure off the top of my head how to check, see questions like this or if absolutely necessary take a look at the Numexpr library https://github.com/pydata/numexpr
3. About the "Y" in your likely XY problem - you are re-calculating data that you can instead re-use:

.

import numpy

size = 8
Y=(arange(2000))
X=(arange(2000))
(xx,yy)=meshgrid(X,Y)

array = zeros((Y.shape[0], X.shape[0], size))

array[..., 0] = 0    
for i in range(1, size):
    array[..., 1] = X ** i + Y ** i + array[..., i - 1]