Ah OK. I was just wondering if there are recommended values to start with
in case below some values are reserved for NumPy/SciPy internals. I'll just
go with the ufunc path just in case.
This really looks like TeX overful/underful badness value adjustment. As
long as the journal accepts don't ment
Coming up with a single number for a sane "array priority" is basically an
impossible task :). If you only need compatibility with the latest version
of NumPy, this is one good reason to set __array_ufunc__ instead, even if
only to write __array_ufunc__ = None.
On Mon, Jun 19, 2017 at 9:14 AM, Nat
I don't think there's any real standard here. Just doing a github search
reveals many different choices people have used:
https://github.com/search?l=Python&q=__array_priority__&type=Code&utf8=%E2%9C%93
On Mon, Jun 19, 2017 at 11:07 AM, Ilhan Polat wrote:
> Thank you. I didn't know that it exis
Thank you. I didn't know that it existed. Is there any place where I can
get a feeling for a sane priority number compared to what's being done in
production? Just to make sure I'm not stepping on any toes.
On Mon, Jun 19, 2017 at 5:36 PM, Stephan Hoyer wrote:
> I answered your question on Stack
I answered your question on StackOverflow:
https://stackoverflow.com/questions/40694380/forcing-multiplication-to-use-rmul-instead-of-numpy-array-mul-or-byp/44634634#44634634
In brief, you need to set __array_priority__ or __array_ufunc__ on your
object.
On Mon, Jun 19, 2017 at 5:27 AM, Ilhan Pol
I will assume some simple linear systems knowledge but the question can be
generalized to any operator that implements __mul__ and __rmul__ methods.
Motivation:
I am trying to implement a gain matrix, say 3x3 identity matrix, for time
being with a single input single output (SISO) system that I h