[Numpy-discussion] A basic question on the dot function
Tue Oct 16 15:08:30 CDT 2007
On 10/16/07, Julien Hillairet <firstname.lastname@example.org> wrote:
> 2007/10/16, Bill Baxter <email@example.com>:
> > dot() also serves as Numpy's matrix multiply function. So it's trying
> > to interpret that as a (3,N) matrix times a (3,N) matrix.
> > See examples here:
> > http://www.scipy.org/Numpy_Example_List_With_Doc#head-2a810f7dccd3f7c700d1076f15078ad1fe3c6d0d
> > --bb
> 2007/10/16, Charles R Harris < firstname.lastname@example.org>:
> > Dot is matrix multiplication, not the "dot" product you were expecting.
> > It is also a bit ambiguous, as you see with the 1-D vectors, where you got
> > what you expected.
> > Chuck
> 2007/10/16, Robert Kern <email@example.com>:
> > When given two 2-D arrays, dot() essentially does matrix multiplication.
> > The
> > last dimension of the first argument is matched with the next-to-last
> > dimension
> > of the second argument.
> > --
> > Robert Kern
> Thank you for your answers. So, is there a "proper" solution to do the dot
> product as I had expected it ?
You might try tensordot. Without thinking it through too much:
numpy.tensordot(a0, a1, axes=[-1,-1])
seems to do what you want.
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