Thanks for your reply! I managed to open a ticket,
http://projects.scipy.org/numpy/ticket/1834
You are actually right, you can also just use zeros instead of random.
Maybe I can test a bit more tomorrow... but its 4am in the morning now ;-).
Thanks for your help and kindness!
Wieland
On Tue, May 17, 2011 at 8:09 PM, Wieland Brendel wrote:
> It also fails for
>
> T = random.random((2,d,d))
> W = random.random((2,d,d,i))
>
> and d > 2. For d = 3 it fails for i = 911...1365.
>
> Should I submit this as a bug (if so, how do I do that?) and/or contact the
> author Mark Wiebe?
>
>
It also fails for
T = random.random((2,d,d))
W = random.random((2,d,d,i))
and d > 2. For d = 3 it fails for i = 911...1365.
Should I submit this as a bug (if so, how do I do that?) and/or
contact the author Mark Wiebe?
Wieland
PS: How
On Tue, May 17, 2011 at 7:46 PM, Wieland Brendel wrote:
> > The equality being that the expression should be ~0?
>
> Exactly.
>
> > I see the problem when the last index is in the range 235 - 390.
>
> Good to see I am not the only one - I was getting crazy. Same range for me by
> the way.**> Out
On Tue, May 17, 2011 at 7:32 PM, Charles R Harris wrote:
>
>
> On Tue, May 17, 2011 at 6:47 PM, Wieland Brendel
> wrote:
>
>>
>> Hello,
>> I am encountering a very strange behaviour of einsum on my machine. I
>> tracked the problem down to the following test code:
>>
>> from numpy import *
>>
>>
> The equality being that the _expression_ should be ~0?
Exactly.
> I see the problem when the last index is in the range 235 - 390.
Good to see I am not the only one - I was getting crazy. Same range for me by the way.
> Out of curiosity, which machine/OS are you using? I'm
> The equality being that the _expression_ should be ~0?
Exactly.
> I see the problem when the last index is in the range 235 - 390.
Good to see I am not the only one - I was getting crazy. Same range for me by the way.
> Out of curiosity, which machine/OS are you using? I'm on 64 b
On Tue, May 17, 2011 at 6:47 PM, Wieland Brendel wrote:
>
> Hello,
> I am encountering a very strange behaviour of einsum on my machine. I
> tracked the problem down to the following test code:
>
> from numpy import *
>
> T = random.random((3,10,10))
> W = random.random((3,10,7,275))
>
> print all
Hello,
I am encountering a very strange behaviour of einsum on my machine. I
tracked the problem down to the following test code:
from numpy import *
T = random.random((3,10,10))
W = random.random((3,10,7,275))
print all(einsum('ij...,j...->i...',T[0],W[0]) +
einsum('ij...,j...->i...',T[1],W[1
Dear Numpy users,
I've been trying to compile Scikits ANN
(http://projects.scipy.org/scikits/wiki/AnnWrapper) with Python 2.7.1,
numpy 1.6.0, and SWIG 2.0.3 but the compilation breaks down down with
this error:
running install
running bdist_egg
running egg_info
running build_src
build_src
buil
On Tue, May 17, 2011 at 12:55:39PM -0500, Benjamin Root wrote:
>Is this hungarian method in an official scikits package, or is this just
>your own thing?
Right now we are playing with the idea of integrating it in the scikits
learn, as it would be useful in a couple of places. I don't know
On Tue, May 17, 2011 at 12:49 PM, Gael Varoquaux <
gael.varoqu...@normalesup.org> wrote:
> On Tue, May 17, 2011 at 09:36:40AM -0700, Hoyt Koepke wrote:
> > > OK, your input is making my motivation to fight with Jonker-Volgenant
> go
> > > down. I'll see with the other people involved if we still t
On Tue, May 17, 2011 at 09:36:40AM -0700, Hoyt Koepke wrote:
> > OK, your input is making my motivation to fight with Jonker-Volgenant go
> > down. I'll see with the other people involved if we still target
> > Jonger-Volgenant, or if we stick with the hungarian algorithm, in which
> > case the pro
>> Well, the hungarian algorithm has a theoretical upper bound of O(n^3),
>> with n being the number of nodes, which is pretty much the best you
>> can do if you have a dense graph and make no assumptions on
>> capacities.
>
> OK, your input is making my motivation to fight with Jonker-Volgenant go
On Tue, May 17, 2011 at 8:03 AM, Wolfgang Kerzendorf <
wkerzend...@googlemail.com> wrote:
> Hello,
>
> The science package I'm using fits legendre polynomials to data. I heard
> it is more stable than the normal polynomials for a fit. Is there a
> polyfit for legendre polynomials? How do I do that
Hello,
The science package I'm using fits legendre polynomials to data. I heard
it is more stable than the normal polynomials for a fit. Is there a
polyfit for legendre polynomials? How do I do that with the new legendre
polynomials module?
Thanks
Wolfgang
_
On Fri, May 13, 2011 at 21:15, Ondrej Marsalek
wrote:
> On Fri, May 13, 2011 at 18:54, Pauli Virtanen wrote:
>> Fri, 13 May 2011 17:39:26 +0200, Ondrej Marsalek wrote:
>> [clip]
>>> while this does not (i.e. still produces just a warning):
>>>
>>> $ python -W error -c 'import numpy; x=numpy.ones(
On Mon, May 16, 2011 at 10:03:09AM -0700, Hoyt Koepke wrote:
> > I might go that way: I already have pure-Python code that implements it
> > and that I have been using for a year or so.
> Fair enough -- though you'd probably get a big speed up moving to cython.
Indeed. If this is needed, we'll co
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