> From: T J gmail.com>
> Is there a better way to achieve the following, perhaps without the
> python for loop?
>
> >>> x.shape
> (1,3)
> >>> y.shape
> (1,3)
> >>> z = empty(len(x))
> >>> for i in range(1):
> ...z[i] = dot(x[i], y[i])
> ...
> __
Robert Kern gmail.com> writes:
> On Sat, Mar 28, 2009 at 23:15, Anne Archibald gmail.com>
wrote:
> > 2009/3/28 Geoffrey Irving naml.us>:
> >> On Sat, Mar 28, 2009 at 12:47 AM, Robert Kern gmail.com>
wrote:
> >>> 2009/3/27 Charles R Harris gmail.com>:
>
> On Fri, Mar 27, 2009 at 4:43
> Essentially, you want to operate on a stack of two dimensional arrays,
> correct?
Yes, this is correct -- and I also think that one should be able to provide a
list of axes to be ignored.
> I'd be mildly supportive of something like this for tensordot; I'd prefer
> more descriptive name for k
Dear all:
After using numpy for several weeks, I am very happy about it and
deeply impressed about the performance improvements it brings in my
python code. Now I have stumbled upon a problem, where I cannot use
numpy to eliminate all my loops in python.
Currently the return value of inner(a, b)
