Or just with a dot:
===
In [17]: np.tensordot(weights, matrices, (0,0))
Out[17]:
array([[ 5., 5., 5.],
[ 5., 5., 5.]])
In [18]: np.dot(matrices.T,weights).T
Out[18]:
array([[ 5., 5., 5.],
[ 5., 5., 5.]])
==
make matrices.T C_CONTIGUOUS for maximum speed.
-n
On Mon, Mar 7, 2011 at 6:03 PM, shu wei <mailshu...@gmail.com> wrote:
> Thanks very much. It works.
>
> On Mon, Mar 7, 2011 at 11:53 AM, <qu...@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
>>
>> > _______________________________________________
>> > NumPy-Discussion mailing list
>> > NumPy-Discussion@scipy.org
>> > http://mail.scipy.org/mailman/listinfo/numpy-discussion
>>
>>
>> --
>> There are two things children should get
>> from their parents: roots and wings.
>>
>> The king who needs to remind his people of his rank, is no king.
>>
>> A beggar's mistake harms no one but the beggar. A king's mistake,
>> however, harms everyone but the king. Too often, the measure of
>> power lies not in the number who obey your will, but in the number
>> who suffer your stupidity.
>> _______________________________________________
>> NumPy-Discussion mailing list
>> NumPy-Discussion@scipy.org
>> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
> _______________________________________________
> NumPy-Discussion mailing list
> NumPy-Discussion@scipy.org
> http://mail.scipy.org/mailman/listinfo/numpy-discussion
>
>
_______________________________________________
NumPy-Discussion mailing list
NumPy-Discussion@scipy.org
http://mail.scipy.org/mailman/listinfo/numpy-discussion
