Is there an easy way to divide each matrix element by the column sum? For example:
input:
1 4
4 10
output:
1/5 4/14
4/5 10/14
Couldn't resist trying a list comprehension. If this matrix was represented in a row-major list of lists, try this:
>>> A = [[1,4],[4,10]]
>>> [[float(i)/j for i,j in zip(a,map(sum,zip(*A)))] for a in A]
[[0.20000000000000001, 0.2857142857142857], [0.80000000000000004, 0.7142857142857143]]
Yes, I know that this is not super-efficient, as we compute the column sums once per row. Saving this in a variable named colsums looks like:
>>> colsums = map(sum,zip(*A))
>>> [[float(i)/j for i,j in zip(a,colsums)] for a in A]
[[0.20000000000000001, 0.2857142857142857], [0.80000000000000004, 0.7142857142857143]]
Note that zip(*A) gives transpose(A).