Charles R Harris wrote:
>1. Integers to negative integer powers raise an error.
>2. Integers to integer powers always results in floats.
2
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On Sun, Jun 5, 2016 at 6:41 PM, Stephan Hoyer wrote:
> If possible, I'd love to add new functions for "generalized ufunc" linear
> algebra, and then deprecate (or at least discourage) using the older
> versions with inferior broadcasting rules. Adding a new keyword arg means
> we'll be stuck with
A simple workaround gets the speed back:
In [11]: %timeit (X.T * A.dot(X.T)).sum(axis=0)
1 loop, best of 3: 612 ms per loop
In [12]: %timeit np.einsum('ij,ji->j', A.dot(X.T), X)
1 loop, best of 3: 414 ms per loop
If working as advertised, the code in gh-5488 will convert the
three-argument ein
On Sun, Jun 5, 2016 at 8:41 PM, Stephan Hoyer wrote:
> If possible, I'd love to add new functions for "generalized ufunc" linear
> algebra, and then deprecate (or at least discourage) using the older
> versions with inferior broadcasting rules. Adding a new keyword arg means
> we'll be stuck with
On Sun, Jun 5, 2016 at 5:08 PM, Mark Daoust wrote:
> Here's the einsum version:
>
> `es = np.einsum('Na,ab,Nb->N',X,A,X)`
>
> But that's running ~45x slower than your version.
>
> OT: anyone know why einsum is so bad for this one?
>
I think einsum can create some large intermediate arrays. It c
If possible, I'd love to add new functions for "generalized ufunc" linear
algebra, and then deprecate (or at least discourage) using the older
versions with inferior broadcasting rules. Adding a new keyword arg means
we'll be stuck with an awkward API for a long time to come.
There are three types
Here's the einsum version:
`es = np.einsum('Na,ab,Nb->N',X,A,X)`
But that's running ~45x slower than your version.
OT: anyone know why einsum is so bad for this one?
Mark Daoust
On Sat, May 28, 2016 at 11:53 PM, Scott Sievert
wrote:
> I recently ran into an application where I had to comput
On 6/4/2016 10:23 PM, Charles R Harris wrote:
From my point of view, backwards compatibility is the main reason for
choosing 1, otherwise I'd pick 2. If it weren't so easy to get
floating point by using floating exponents I'd probably choose
differently.
As an interested user, I offer a summary
