What would be the most efficient way to compute:

c[j] = \sum_i (a[i] * b[i,j])

where a[i] is a 1-d vector, b[i,j] is a 2-d array?

This seems to be one way:

import numpy as np
a = np.arange (3)
b = np.arange (12).reshape (3,4)
c = np.dot (a, b).sum()

but np.dot returns a vector, which then needs further reduction.  Don't know if 
there's a better way.

-- 
-- Those who don't understand recursion are doomed to repeat it

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