> Could you please offer some code or math notation to help communicate this?
> I am forced to guess at the need.
>
> The words "matrix" and "vector" are ambiguous.
> After all, matrices (of given shape) are a type of vector (i.e., can be added
> and scaled.)
> So if by "matrix" you mean "2d
> FWIW, +1 for matvec & vecmat to complement matmat (erm, matmul). Having a
> binop where one argument is a matrix and the other is a
> stack/batch of vectors is indeed awkward otherwise, and a dedicated function
> to clearly distinguish "two matrices" from "a matrix and a
> batch of vectors"
On Wed, Jan 24, 2024 at 2:27 PM Marten van Kerkwijk
wrote:
> > Why do these belong in NumPy? What is the broad field of application of
> these functions? And,
> > does a more general concept underpin them?
>
> Multiplication of a matrix with a vector is about as common as matrix
> with matrix or
On Wed, 24 Jan 2024 at 19:29, Marten van Kerkwijk
wrote:
>
> > Why do these belong in NumPy? What is the broad field of application of
> > these functions? And,
> > does a more general concept underpin them?
>
> Multiplication of a matrix with a vector is about as common as matrix
> with matrix
FWIW, +1 for matvec & vecmat to complement matmat (erm, matmul). Having a
binop where one argument is a matrix and the other is a stack/batch of
vectors is indeed awkward otherwise, and a dedicated function to clearly
distinguish "two matrices" from "a matrix and a batch of vectors" sounds
great
> Why do these belong in NumPy? What is the broad field of application of these
> functions? And,
> does a more general concept underpin them?
Multiplication of a matrix with a vector is about as common as matrix
with matrix or vector with vector, and not currently easy to do for
stacks of
Why do these belong in NumPy? What is the broad field of application of
these functions? And, does a more general concept underpin them?
Thanks, Alan Isaac
On Tue, Jan 23, 2024 at 5:17 PM Marten van Kerkwijk
wrote:
> Hi All,
>
> I have a PR [1] that adds `np.matvec` and `np.vecmat` gufuncs for
On Wed, Jan 24, 2024 at 10:43 AM Sebastian Berg
wrote:
> On Mon, 2024-01-22 at 17:08 -0700, Nathan wrote:
> > Hi all,
> >
> > I propose we accept NEP 55 and merge PR #25347 implementing the NEP
> > in time
> > for the NumPy 2.0 RC:
>
>
> I really like this work and I think it is a big
On Wed, Jan 24, 2024 at 6:29 AM Fabio Matti
wrote:
> Hi,
>
> In the `numpy.polynomial.chebyshev` module, the function for raising a
> Chebyshev polynomial to a power, `chebpow` [1], is essentially implemented
> in the following way:
>
> {{{#!highlight python
> def chebpow(c, pow):
> """Raise
Hi,
In the `numpy.polynomial.chebyshev` module, the function for raising a
Chebyshev polynomial to a power, `chebpow` [1], is essentially implemented in
the following way:
{{{#!highlight python
def chebpow(c, pow):
"""Raise a Chebyshev series to a power."""
zs =
On Mon, 2024-01-22 at 17:08 -0700, Nathan wrote:
> Hi all,
>
> I propose we accept NEP 55 and merge PR #25347 implementing the NEP
> in time
> for the NumPy 2.0 RC:
I really like this work and I think it is a big improvement! At this
point we probably have to expect some things to be still
11 matches
Mail list logo
