Awesome. I just added rollaxis(c,0,3) and was done.
Cheers mate.
On Fri, Jul 4, 2008 at 2:38 AM, lorenzo bolla <[EMAIL PROTECTED]> wrote:
> If a and b are 2d arrays, you can use numpy.dot:
>
> In [36]: a
> Out[36]:
> array([[1, 2],
>[3, 4]])
> In [37]: b
> Out[37]:
> array([[5, 6],
>
If a and b are 2d arrays, you can use numpy.dot:
In [36]: a
Out[36]:
array([[1, 2],
[3, 4]])
In [37]: b
Out[37]:
array([[5, 6],
[7, 8]])
In [38]: numpy.dot(a,b)
Out[38]:
array([[19, 22],
[43, 50]])
If a and b are 3d arrays of shape 2x2xN, you can use something like that:
In [
I have two 2d arrays a & b for example:
a=array([c,d],[e,f])
b=array([g,h],[i,j])
Each of the elements of a & b are actually 1d arrays of length N so I
guess technically a & b have shape (2,2,N).
However I want to matrix multiply a & b to create a 2d array x, where
the elements of x are created wit
