On Tue, May 29, 2018 at 2:21 PM, Jonathan Tammo Siebert <
jotasi_numpy_sc...@posteo.de> wrote:
> On Tue, 2018-05-29 at 10:47 -0400, josef.p...@gmail.com wrote:
> > On Tue, May 29, 2018 at 9:14 AM, Jonathan Tammo Siebert <
> > jotasi_numpy_sc...@posteo.de> wrote:
> >
> > > Hi,
> > >
> > > I hope th
On Tue, 2018-05-29 at 10:47 -0400, josef.p...@gmail.com wrote:
> On Tue, May 29, 2018 at 9:14 AM, Jonathan Tammo Siebert <
> jotasi_numpy_sc...@posteo.de> wrote:
>
> > Hi,
> >
> > I hope this is the appropriate place to ask something like
> > this, otherwise please let me know (or feel free to ig
On Mon, May 28, 2018, 20:41 Stephan Hoyer wrote:
> On Mon, May 28, 2018 at 7:36 PM Eric Wieser
> wrote:
>
>> which ensure that it is still well defined (as the identity) on 1d
>> arrays.
>>
>> This strikes me as a bad idea. There’s already enough confusion from
>> beginners that array_1d.T is a
On Tue, May 29, 2018 at 9:46 AM, Stephan Hoyer wrote:
> Reviving this discussion --
> I don't really care what our policy is, but can we make a decision one way
> or the other about where we discuss NEPs? We've had a revival of NEP
> writing recently, so this is very timely.
>
> Previously, I was
Reviving this discussion --
I don't really care what our policy is, but can we make a decision one way
or the other about where we discuss NEPs? We've had a revival of NEP
writing recently, so this is very timely.
Previously, I was in slight favor of doing discussion on GitHub. Now that
I've start
On Tue, May 29, 2018 at 9:14 AM, Jonathan Tammo Siebert <
jotasi_numpy_sc...@posteo.de> wrote:
> Hi,
>
> I hope this is the appropriate place to ask something like
> this, otherwise please let me know (or feel free to ignore
> this). Also I hope that I do not misunderstood something or
> did some
Hi,
I hope this is the appropriate place to ask something like
this, otherwise please let me know (or feel free to ignore
this). Also I hope that I do not misunderstood something or
did some silly mistake. If so, please let me know as well!
TLDR:
When scaling the covariance matrix based on the re
Apart from the math-validity discussion, in my experience errors are used a
bit too generously in the not-allowed ops. No ops are fine once you learn
more about them such as transpose on 1D arrays (good or bad is another
discussion). But raising errors bloat the computational code too much. "Is
it
On Tue, May 29, 2018 at 12:16 PM, Daπid wrote:
> Right now, np.int(8).T throws an error, but np.transpose(np.int(8)) gives a
> 0-d array. On one hand, it is nice to be able to use the same code for
`np.int` is just python `int`! What you mean is `np.int64(8).T` which
works fine, so does `np.array
On 29 May 2018 at 05:40, Stephan Hoyer wrote:
> But given that idiomatic NumPy code uses 1D arrays in favor of explicit
> row/column vectors with shapes (1,n) and (n,1), I do think it does make
> sense for matrix transpose on 1D arrays to be the identity, because matrix
> transpose should convert
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Dear Colleagues,
We are delighted to invite you to join us for the
**11th European Conference on Python in Science**.
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On Tue, May 29, 2018 at 5:40 AM, Stephan Hoyer wrote:
> But given that idiomatic NumPy code uses 1D arrays in favor of explicit
> row/column vectors with shapes (1,n) and (n,1), I do think it does make
> sense for matrix transpose on 1D arrays to be the identity, because matrix
> transpose should
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