That sounds like a good idea! I didn't see any real good examples of usage
after some googling. Giving more examples of effective usage could also clear
more things up regarding design decisions. Additionally I'm always interested
in learning some new tricks :)
Cheers,
Stefan
Gesendet:
Ok that are indeed some good reasons to keep the status quo, especially since performance is crucial for numpy.
It's a dillemma: Using the matrix class for linear algebra would be the correct way for such thing,
but the matrix API is not that powerful and beautiful as the one of arrays.
On t
On 08/02/15 23:17, Stefan Reiterer wrote:
> Actually I use numpy for several years now, and I love it.
> The reason that I think silent broadcasting of sums is bad
> comes simply from the fact, that I had more trouble with it, than it
> helped me.
In Fortran 90, broadcasting allows us to write co
Simon Wood wrote:
> Not quite the same. This is not so much about language semantics as
> mathematical definitions. You (the Numpy community) have decided to
> overload certain mathematical operators to act in a way that is not
> consistent with linear algebra teachings.
We have overloaded the o
Matthew Brett wrote:
> I agree. I knew about broadcasting as soon as I started using numpy,
> so I can honestly say this has never surprised me.
Fortran 90 has broadcasting too. NumPy's broadcasting was inspired by
Fortran 90, which was the lingua franca of scientific computing in the
1990s. Li
On Sun, Feb 8, 2015 at 7:12 PM, Eric Firing wrote:
> On 2015/02/08 12:43 PM, josef.p...@gmail.com wrote:
>
>>
>> For me the main behavior I had to adjust to was loosing a dimension in
>> any reduce operation, mean, sum, ...
>>
>> if x is 2d
>> x - x.mean(1)
>> we loose a dimension, and it doesn't
On 2015/02/08 12:43 PM, josef.p...@gmail.com wrote:
>
> For me the main behavior I had to adjust to was loosing a dimension in
> any reduce operation, mean, sum, ...
>
> if x is 2d
> x - x.mean(1)
> we loose a dimension, and it doesn't broadcast in the right direction
Though you can use:
x_demea
Yeah, its all about the preferred semantics.
Indeed if you want to use LA semantics, ndarray semantics are somewhat of a
disappointment; though I would argue they do have a very well design
internal logic of their own.
Much moreso than LA semantics in the first place; LA semantics fail to
general
At 02:47 PM 2/8/2015, Simon Wood wrote:
>Not quite the same. This is not so much about language semantics as
>mathematical definitions. You (the Numpy community) have decided to
>overload certain mathematical operators to act in a way that is not
>consistent with linear algebra teachings. This c
On 08-Feb-15 5:47 PM, Nathaniel Smith
wrote:
On 8 Feb 2015 13:39, "Simon Wood" wrote:
I find the broadcasting aspect of Numpy a turn off. If I go to add a 1x3
vector to a 3x1 vector, I want the program to warn me or error out. I
On 8 Feb 2015 13:04, "Stefan Reiterer" wrote:
>
> So I suggest that the best would be to throw warnings when arrays get
Broadcasted like
> Octave do. Python warnings can be catched and handled, that would be a
great benefit.
>
> Another idea would to provide warning levels for braodcasting, e.g
>
On Sun, Feb 8, 2015 at 5:28 PM, wrote:
> On Sun, Feb 8, 2015 at 4:56 PM, Matthew Brett
> wrote:
> > Hi,
> >
> > On Sun, Feb 8, 2015 at 1:39 PM, Simon Wood wrote:
> >>
> >>
> >> On Sun, Feb 8, 2015 at 4:24 PM, Stefan Reiterer wrote:
> >>>
> >>> I don't think this is a good comparison, especiall
On 8 Feb 2015 13:39, "Simon Wood" wrote:
>
> I find the broadcasting aspect of Numpy a turn off. If I go to add a 1x3
vector to a 3x1 vector, I want the program to warn me or error out. I don't
want it to do something under the covers that has no mathematical basis or
definition. Also, Octave may
On Sun, Feb 8, 2015 at 5:17 PM, Stefan Reiterer wrote:
> Actually I use numpy for several years now, and I love it.
> The reason that I think silent broadcasting of sums is bad
> comes simply from the fact, that I had more trouble with it, than it helped
> me.
>
> I won't stop using numpy because
On Sun, Feb 8, 2015 at 4:56 PM, Matthew Brett wrote:
> Hi,
>
> On Sun, Feb 8, 2015 at 1:39 PM, Simon Wood wrote:
>>
>>
>> On Sun, Feb 8, 2015 at 4:24 PM, Stefan Reiterer wrote:
>>>
>>> I don't think this is a good comparison, especially since broadcasting is
>>> a feature not a necessity ...
>>>
Actually I use numpy for several years now, and I love it.
The reason that I think silent broadcasting of sums is bad
comes simply from the fact, that I had more trouble with it, than it helped me.
I won't stop using numpy because of that, but I think this behavior may backfire,
and thats t
numpy is like Tesla. Everybody else has been doing it wrong...
Ben Root
On Sun, Feb 8, 2015 at 4:39 PM, Simon Wood wrote:
>
>
> On Sun, Feb 8, 2015 at 4:24 PM, Stefan Reiterer wrote:
>
>> I don't think this is a good comparison, especially since broadcasting is
>> a feature not a necessity ...
This. (nd)arrays are a far more widespread concept than linear algebraic
operations. If you want LA semantics, use the matrix subclass. Or don't,
since simply sticking to the much more pervasive and general ndarray
semantics is usually simpler and less confusing.
On Sun, Feb 8, 2015 at 10:54 PM, W
Hi,
On Sun, Feb 8, 2015 at 1:39 PM, Simon Wood wrote:
>
>
> On Sun, Feb 8, 2015 at 4:24 PM, Stefan Reiterer wrote:
>>
>> I don't think this is a good comparison, especially since broadcasting is
>> a feature not a necessity ...
>> It's more like turning off/on driving assistance.
>>
>> And as al
On Sun, 8 Feb 2015, Stefan Reiterer wrote:
> And as already mentioned: other matrix languages also allow it, but they warn
> about it's usage.
> This has indeed it's merits.
numpy isn't a matrix language. They're arrays. Storing numbers that you are
thinking of as a vector in an array doesn't t
On Sun, Feb 8, 2015 at 4:24 PM, Stefan Reiterer wrote:
> I don't think this is a good comparison, especially since broadcasting is
> a feature not a necessity ...
> It's more like turning off/on driving assistance.
>
> And as already mentioned: other matrix languages also allow it, but they
> war
Hi,
On Sun, Feb 8, 2015 at 1:24 PM, Stefan Reiterer wrote:
> I don't think this is a good comparison, especially since broadcasting is a
> feature not a necessity ...
> It's more like turning off/on driving assistance.
>
> And as already mentioned: other matrix languages also allow it, but they
>
I don't think this is a good comparison, especially since broadcasting is a feature not a necessity ...
It's more like turning off/on driving assistance.
And as already mentioned: other matrix languages also allow it, but they warn about it's usage.
This has indeed it's merits.
Gesendet: S
On Sun, Feb 8, 2015 at 2:14 PM, Stefan Reiterer wrote:
> Yeah I'm aware of that, that's the reason why I suggested a warning level
> as an alternative.
> Setting no warnings as default would avoid breaking existing code.
> *Gesendet:* Sonntag, 08. Februar 2015 um 22:08 Uhr
> *Von:* "Eelco Hoogen
On Sun, Feb 8, 2015 at 4:08 PM, Eelco Hoogendoorn
wrote:
>> I personally use Octave and/or Numpy for several years now and never ever
>> needed braodcasting.
> But since it is still there there will be many users who need it, there will
> be some use for it.
>
> Uhm, yeah, there is some use for i
Yeah I'm aware of that, that's the reason why I suggested a warning level as an alternative.
Setting no warnings as default would avoid breaking existing code.
Gesendet: Sonntag, 08. Februar 2015 um 22:08 Uhr
Von: "Eelco Hoogendoorn"
An: "Discussion of Numerical Python"
Betreff: Re: [Numpy-di
> I personally use Octave and/or Numpy for several years now and never
ever needed braodcasting.
But since it is still there there will be many users who need it, there
will be some use for it.
Uhm, yeah, there is some use for it. Im all for explicit over implicit, but
personally current broadcas
Hi!
As shortly discussed on github:
https://github.com/numpy/numpy/issues/5541
I personally think that silent Broadcasting is not a good thing. I had recently a lot
of trouble with row and column vectors which got bradcastet toghether altough it was
more annoying than useful, especially
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