On 27 Feb 2013 12:57, "Jorge Scandaliaris" wrote:
>
> Hi,
> First of all excuse me if this is a trivial question. I have the feeling
it is,
> but searching and looking through the docs has proven unsuccesful so far.
>
> I have an ndarray A of shape (M,2,2) representing M 2 x 2 matrices. Now I
want
Jaime Fernández del Río gmail.com> writes:
> np.einsum makes a lot of these easier to figure out:
> In [7]: np.einsum('ijk, kl', A, T)
> Out[7]:
> array([[[ 7, 10],
> [15, 22]],
>
> [[23, 34],
> [31, 46]],
>
> [[39, 58],
> [47, 70]]])
>
Thanks, I will h
On Wed, Feb 27, 2013 at 5:41 AM, Jorge Scandaliaris
wrote:
> Jorge Scandaliaris yahoo.es> writes:
> > I have an ndarray A of shape (M,2,2) representing M 2 x 2 matrices.
> > Now I want to apply a transform T of shape (2,2) to each of matrix.
>
np.einsum makes a lot of these easier to figure out:
Jorge Scandaliaris yahoo.es> writes:
<...>
> I have an ndarray A of shape (M,2,2) representing M 2 x 2 matrices.
> Now I want to apply a transform T of shape (2,2) to each of matrix.
> The way I do this now is by iterating over all rows of A
> multiplying the matrices using numpy.dot():
>
> for
Hi,
First of all excuse me if this is a trivial question. I have the feeling it is,
but searching and looking through the docs has proven unsuccesful so far.
I have an ndarray A of shape (M,2,2) representing M 2 x 2 matrices. Now I want
to apply a transform T of shape (2,2) to each of matrix. The
