Moving Window Average Convolution with different Radii - Python
Since you are attempting a rather customized moving window average convolution, it is unlikely that you will find it in an existing library. 
Instead you can implement this in a straightforward way with loops. Then use Cython, f2py or numba, etc to speed this up to a level comparable with a native C/Fortran implementation, while still using numpy to access and store data in memory.
I would like to perform a basic moving average convolution of an array where each pixel is replaced by the average of its surrounding pixels. 
But my problem scenario goes like this : 

I have two arrays valueArray and radiiArray. Both the arrays have the same shape. 
I need to apply the moving average to the valueArray but instead of having a constant radius to get my neighboring pixels, I want each pixel's average be calculated with a different radii - values of which are stored in the radiiArray 

I could implement it using for loops but that would be time consuming since the arrays are too large. Is this possible using the numpy library?