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From: Oscar Benjamin <oscar.j.benjamin@gmail.com>
Date: Sun, 19 Jan 2014 15:46:43 +0000
Subject: Re: Need help vectorizing code
To: Kevin K <richyokevin@gmail.com>
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Xref: csiph.com comp.lang.python:64295

On 18 January 2014 20:51, Kevin K <richyokevin@gmail.com> wrote:
> I have some code that I need help vectorizing.
> I want to convert the following to vector form, how can I? I want to get rid of the inner loop - apparently, it's possible to do so.
> X is an NxD matrix. y is a 1xD vector.
>
> def foo(X, y, mylambda, N, D, epsilon):
> ...
>         for j in xrange(D):
>             aj = 0
>             cj = 0
>             for i in xrange(N):
>                 aj += 2 * (X[i,j] ** 2)
>                 cj += 2 * (X[i,j] * (y[i] - w.transpose()*X[i].transpose() + w[j]*X[i,j]))

As Peter said the y[i] above suggests that y has the shape (1, N) or
(N, 1) or (N,) but not (1, D). Is that an error? Should it actually be
y[j]?

You don't give the shape of w but I guess that it is (1, D) since you
index it with j. That means that w.transpose() is (D, 1). But then
X[i] has the shape (D,). Broadcasting those two shapes gives a shape
of (D, D) for cj. OTOH if w has the shape (D, 1) then cj has the shape
(1, D).

Basically your description is insufficient for me to know what your
code is doing in terms of all the array shapes. So I can't really
offer a vectorisation of it.

>
> ...
>
> If I call numpy.vectorize() on the function, it throws an error at runtime.

You've misunderstood what the numpy.vectorize function is for. The
vectorize function is a convenient way of generating a function that
can operate on arrays of arbitrary shape out of a function that
operates only on scalar values.


Oscar