Is there any way I can improve the Python code I attached below? It seems too slow for me now.
C_abs = abs(C)
_, n = C_abs.shape
G = np.zeros((n, n))
for i in xrange(n):
for j in xrange(n):
G[i,j] = C_abs[i,j]+C_abs[j,i]
Just add C_abs with its transposed version -
G = C_abs + C_abs.T
To understand, look at the computation part of the code :
G[i,j] = C_abs[i,j]+C_abs[j,i]
The first input on the right side is C_abs[i,j], which has the same iterators involved as on the left side of the assignment - G[i,j]. So, for a vectorized solution, we will use it without change as the first input. The second input on the right side is C_abs[j,i] and its iterators are flipped version of the iterators on the left side - G[i,j]. This flipping in the entire array context would be the transpose of C_abs. Therefore, put together, we will add C_abs with its own transposed version to get the desired output in a vectorized manner.
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