[Numpy-discussion] How to sum weighted matrices

shu wei mailshuwei@gmail....
Mon Mar 7 20:03:53 CST 2011

```Thanks very much. It works.

On Mon, Mar 7, 2011 at 11:53 AM, <qubax@gmx.at> wrote:

> for your problem, you can do:
>
> ----------------------------
>
> import numpy as np
>
> weights = np.array([1,2])
>
> matrix1 = np.ones((2,3))
> matrix2 = 2*np.ones((2,3))
>
> matrices = np.array([matrix1,matrix2])
>
> weighted_sum = np.tensordot(weights, matrices, (0,0))
>
> --------------------------
>
> On Mon, Mar 07, 2011 at 06:16:15AM -0600, shu wei wrote:
> >    Hello all,
> >
> >    I am new to python and numpy.
> >    My question is how to sum up N weighted matrices.
> >    For example w=[1,2] (N=2 case)
> >    m1=[1 2 3,
> >           3 4 5]
> >
> >    m2=[3 4 5,
> >           4 5 6]
> >    I want to get a matrix Y=w[1]*m1+w[2]*m2 by using a loop.
> >
> >    My original problem is like this
> >    X=[1 2 3,
> >         3 4 5,
> >         4 5 6]
> >
> >    a1=[1 2 3]  1st row of X
> >    m1=a1'*a1 a matirx
> >    a2=[3 4 5] 2nd row of X
> >    m2=a2'*a2
> >    a3=[ 4 5 6] 3rd row of X
> >    m3=a3'*a3
> >
> >    I want to get Y1=w[1]*m1+w[2]*m2
> >                          Y2=w[1]*m2+w[2]*m3
> >    So basically it is rolling and to sum up the weighted matries
> >    I have a big X, the rolling window is relatively small.
> >
> >    I tried to use
> >
> >    sq=np.array([x[i].reshape(-1,1)*x[i] for i in np.arange(0,len(x)]) #
> >    s=len(x)
> >    m=np.array([sq[i:i+t] for i in np.arange(0,s-t+1)]) # t is the len(w)
> >
> >    then I was stuck, I tried to use a loop somethig like
> >    Y=np.array([np.sum(w[i]*m[j,i],axis=0) for i in np.arange(0,t)] )
> >    Any suggestion is welcome.
> >
> >    sue
>
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>
>
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