From f.braennstroem at gmx.de  Sun Oct  1 05:15:29 2006
From: f.braennstroem at gmx.de (Fabian Braennstroem)
Date: Sun, 1 Oct 2006 11:15:29 +0200
Subject: [SciPy-user] Pros and Cons of Python verses other
	array	environments
References: <fc.3b9aca00738a08413b9aca0041088a73.2b780992@umit.maine.edu>
	<db6b5ecc0609281337s48a0d40kd63b2d2d06a55a9e@mail.gmail.com>
	<loom.20060929T141725-390@post.gmane.org>
	<200609291458.34486.thyreau@shfj.cea.fr>
Message-ID: <efo0vd$4cp$1@sea.gmane.org>

Hi,

* Benjamin THYREAU <thyreau at shfj.cea.fr> wrote:
> (...)
>>
>> When it comes to the distribution, I like Enthought's Python package, but
>> it is only for Windows.  What I have done for Linux is set up a gar make
>> system (also used by konstruct and gargnome) to build everything anyone
>> needs to get a python system up and running.  The download is quite small
>> (1 makefile per package to be built).  The makefile tells the system the
>> name and location of the download. When make is run it automatically goes
>> to the web, gets the source, builds and installs it.  All the user has to
>> do is type 'make install' and they have a full scientific python
>> environment waiting for them.  Right now I have it set up to build blas,
>> lapack, numpy, scipy, pygtk, matplotlib, ipython and python2.4 (if it is
>> not already there).  I also add a little script in their path that can be
>> run to set the correct environment variables, launch ipython and import
>> scipy and mpl.
>>
>> Perhaps this is a way to easily get Linux users up and running.
>>
>> s.
>>
>>
> Sounds interesting. I remember having mostly good experience with Konstrut.
> Is there some publicy available location where i could find your script ?

I would like to see your script too! Sounds really nice :-)

Greetings!
 Fabian



From peridot.faceted at gmail.com  Sun Oct  1 10:35:58 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Sun, 1 Oct 2006 10:35:58 -0400
Subject: [SciPy-user] Running mean: numpy or pyrex?
In-Reply-To: <be6d1720609300053q2ae1c79bl4d1d8b18d6c9ad37@mail.gmail.com>
References: <be6d1720609300053q2ae1c79bl4d1d8b18d6c9ad37@mail.gmail.com>
Message-ID: <ce557a360610010735y64f79f95x9838dc51823f4b4f@mail.gmail.com>

On 30/09/06, David Finlayson <david.p.finlayson at gmail.com> wrote:

> I was fairly impressed with the filter performance using psyco until I met
> some truly huge files. Now I am wondering if I would get any speed benefit
> from using numpy (for the 2D array access) or would I be better off trying
> pyrex for the running mean loops? One of the issues I am facing is the
> possibility that very large files may need to be read from the disk as
> needed instead of holding the whole thing in ram. I also need to distrubute
> this code to my team, so minimizing the pain of installing numeric and other
> packages would be an issue. Should I expect significant speed benefits from
> a numy version of this type of code?

Numpy is designed for exactly this kind of computation. It will almost
certainly be simpler to express your calculation in numpy, and it may
be faster (as the internal loops are written in C). Numpy is also
capable of operating on on-disk arrays by mmap()ing them (so that
pages are loaded and unloaded as needed). Once in numpy, there are
also tools such as weave which should allow you to accelerate
calculations further (by running more code in C).

On the other hand, depending what you're doing, psyco may accelerate
your program, and it is certainly easy to add (two lines: import
psyco; psyco.full() ) though it has never actually accelerated any
computation that I tried it on.

If you don't care about linear algebra speed, I think numpy is
relatively easy to install. (For me it was just a question of clicking
on a checkbox as iti is packaged for my distribution of Linux.) If
you're doing major calculations, you may need to ensure that your
favourite fast linear algebra package gets detected.

If you do end up trying it, please report on your experiences.
Performance is not always what we expect. (For example, I tried
converting a number of examples from the Great Computer Language
Shootout to use Numeric only to discover that they ran more slowly.)

A. M. Archibald


From jstano at interchange.ubc.ca  Sun Oct  1 15:00:58 2006
From: jstano at interchange.ubc.ca (joe stano)
Date: Sun, 01 Oct 2006 12:00:58 -0700
Subject: [SciPy-user] Cobyla Help part 2
Message-ID: <0J6H00HLR0TIEE@smtp.interchange.ubc.ca>

Thanks for the advice.

Although reshape would not work because the size was larger then 32, I am
still able to reshape the array with loops.

The script now runs, however, the constraints do not seem to be working
(i.e., I get answers that I should not).  I have made sure that each
constraint returns a single value (+ if constraint is met and - if not) and
each constraint takes in the decision variable.

I have attached a portion of the script (I know it is not pretty but I am
just starting out), so that maybe someone can see if I have incorrectly
called something?

 

Thanks for any help,

 

joe

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From skokot at po.opole.pl  Sun Oct  1 16:08:31 2006
From: skokot at po.opole.pl (Seweryn Kokot)
Date: Sun, 01 Oct 2006 22:08:31 +0200
Subject: [SciPy-user] matplotlib, numpy and scipy
Message-ID: <8764f3u7cw.fsf@poczta.po.opole.pl>

As I remember some time ago matplotlib required scipy and now requires
numpy. Any explaination?

I read somewhere that scipy may conflict with numpy... is it true?

Regards,
Seweryn Kokot



From robert.kern at gmail.com  Sun Oct  1 16:30:38 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Sun, 01 Oct 2006 15:30:38 -0500
Subject: [SciPy-user] matplotlib, numpy and scipy
In-Reply-To: <8764f3u7cw.fsf@poczta.po.opole.pl>
References: <8764f3u7cw.fsf@poczta.po.opole.pl>
Message-ID: <4520256E.7000001@gmail.com>

Seweryn Kokot wrote:
> As I remember some time ago matplotlib required scipy and now requires
> numpy. Any explaination?

numpy used to be called "scipy core" and was renamed because people got confused 
and thought that implied they had to install all of scipy.

> I read somewhere that scipy may conflict with numpy... is it true?

No, scipy builds on top of numpy.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From fullung at gmail.com  Sun Oct  1 17:07:13 2006
From: fullung at gmail.com (Albert Strasheim)
Date: Sun, 1 Oct 2006 23:07:13 +0200
Subject: [SciPy-user] Q: Building SciPy for Windows without
	Cygwindependency?
In-Reply-To: <451EF0C5.1010308@cox.net>
Message-ID: <E1GU8Wj-0005sj-1n@mail2.sun.ac.za>

Hello all

> -----Original Message-----
> From: scipy-user-bounces at scipy.org [mailto:scipy-user-bounces at scipy.org]
> On Behalf Of Kyle Ferrio
> Sent: 01 October 2006 00:34
> To: SciPy Users
> Subject: [SciPy-user] Q: Building SciPy for Windows without
> Cygwindependency?
> 
> I want to build a full-up SciPy for MS Windows in line with the Python
> and SciPy licenses.

Are you planning to do this with MinGW or with the Microsoft compiler?

> I noticed the following text in the excellent installation instructions,
> regarding the choice of compiler:
> 
>    "Cygwin is required if you want to build ATLAS yourself."
> 
> Well, I often build ATLAS myself.  And now (implicitly) I want to build
> ATLAS in a way that is available to SciPy.
> 
> So I have two questions:
> 
> 1. Must ATLAS -- to be used with SciPy -- be built with a dependence on
> the GPL'ed Cygwin runtime library?
>    (I can't imagine why this would be the case, but I want to test my
> understanding.)

I've built ATLAS 3.7.11 under Cygwin, AFAIR, this produced a static library
that is not linked to the Cygwin runtime.

> 2. Is the "need" for Cygwin actually just a way to get (extremely
> convenient) tools like 'ar' which do not infect the ATLAS lib with the
> GPL?

The need for Cygwin is a requirement of ATLAS's build system, parts of which
are written in C and have a very Unix-centric view of the world.

Regards,

Albert



From ckkart at hoc.net  Sun Oct  1 19:13:47 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Mon, 02 Oct 2006 08:13:47 +0900
Subject: [SciPy-user] Cobyla Help part 2
In-Reply-To: <0J6H00HLR0TIEE@smtp.interchange.ubc.ca>
References: <0J6H00HLR0TIEE@smtp.interchange.ubc.ca>
Message-ID: <45204BAB.9000704@hoc.net>

joe stano wrote:
> Thanks for the advice.
> 
> Although reshape would not work because the size was larger then 32, I am
> still able to reshape the array with loops.

? Why that? Why can't you reshape an array larger than 32 (elements, I guess) ?
If you have an NxN array with N=32 you can call
numpy.ravel(data)
to get a 1D-arrayu and
numpy.reshape(data, (N,N)
to get its original shape back.

> The script now runs, however, the constraints do not seem to be working
> (i.e., I get answers that I should not).  I have made sure that each
> constraint returns a single value (+ if constraint is met and - if not) and
> each constraint takes in the decision variable.

I think the constraints should return a continous functions, not just -1 and +1,
so the minimizer knows where to go to improve the result. I might be wrong here.

> I have attached a portion of the script (I know it is not pretty but I am
> just starting out), so that maybe someone can see if I have incorrectly
> called something?

Please send a complete example, including your input data, otherwise it is
difficult to find out what's happening.

Christain



From ckkart at hoc.net  Sun Oct  1 22:22:42 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Mon, 02 Oct 2006 11:22:42 +0900
Subject: [SciPy-user] does scipy have a function... partII
Message-ID: <452077F2.5060001@hoc.net>

Hi,
concerning the discussions about finding the upper/lower limit of some data some
days ago (http://article.gmane.org/gmane.comp.python.scientific.user/8926), I've
enhanced my script and added constraints to the 2nd derivative of the function.
This gives much smoother results, at least for that special type of data Bill
has to deal with. That additional constraint seems to help the minimizer find a
solution and the number of function evaluations goes down significantly.
I'm really impressed how well fmin_cobyla works.

Regards, Christian
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From johnlichtenstein at mac.com  Mon Oct  2 01:03:34 2006
From: johnlichtenstein at mac.com (John Lichtenstein)
Date: Sun, 1 Oct 2006 22:03:34 -0700
Subject: [SciPy-user] matplotlib on osx
In-Reply-To: <20061001023457.GA14026@clipper.ens.fr>
References: <mailman.23104.1159600993.2761.scipy-user@scipy.org>
	<C7304513-E5E5-4055-AA1C-7FD8161F5048@unsw.edu.au>
	<20061001023457.GA14026@clipper.ens.fr>
Message-ID: <FC16047E-8419-496E-8939-DBD3258873FD@mac.com>

Has anyone gotten matplotlib running on OSX recently? I tried  
upgrading to 10.4.8, and building Python 2.5, numpy, scipy, libpng,  
and freetype from source. Everything went fine, even matplotlib  
installed without an error. But when I import matplotlib I get

21:49:24: Debug: ../src/common/object.cpp(224): assert "sm_classTable- 
 >Get(m_className) == NULL" failed: class already in RTTI table -  
have you used IMPLEMENT_DYNAMIC_CLASS() twice (may be by linking some  
object module(s) twice)?
../src/common/object.cpp(224): assert "sm_classTable->Get 
(m_className) == NULL" failed: class already in RTTI table - have you  
used IMPLEMENT_DYNAMIC_CLASS() twice (may be by linking some object  
module(s) twice)?
Trace/BPT trap

What's the clean way to uninstall Python? I used to have a working  
matplotlib using the pythonmac distribution. Maybe I can get back to  
that. 


From willemjagter at gmail.com  Mon Oct  2 04:30:59 2006
From: willemjagter at gmail.com (William Hunter)
Date: Mon, 2 Oct 2006 10:30:59 +0200
Subject: [SciPy-user] Sparse: Efficient metod to convert to CSC format
Message-ID: <8b3894bc0610020130n48bf6029sb8122ed92ecf2c5d@mail.gmail.com>

I've been bugging Robert C. and Ed S. (thanks guys) for a while about
this now, but I think it might be good if I share my experiences with
other users.

When converting a sparse matrix to CSC format, one of the quickest
ways to get there is to give <sparse.csc_matrix> three vectors
containing;

(1) [values]: the values,
(2) [rowind]: the row indices and
(3) [colptr]: the column pointer.

If one times how long it takes to get your CSC matrix by doing
sparse.csc_matrix((values, rowind, colptr)) compared to the other ways
to get it, e.g., csc_matrix(dense_mtx), I've found that the first
method is faster (enough to be significant for me).

One can solve a sparse system with <linsolve.spsolve>, if your matrix
is in CSC format. And here's my question: Let's say I have a way (and
I might :-)) to construct those 3 vectors very quickly, how can I use
them directly as arguments in <linsolve.spsolve>? For example:

solution = linsolve.spsolve([values],[rowind],[colptr],[RHS])

This way I can skip the conversion to CSC format since it's already in
that form, albeit 'decomposed'.
--
William


From willemjagter at gmail.com  Mon Oct  2 07:14:39 2006
From: willemjagter at gmail.com (William Hunter)
Date: Mon, 2 Oct 2006 13:14:39 +0200
Subject: [SciPy-user] error building pyopengl...
In-Reply-To: <451DB1D8.8000707@gmail.com>
References: <451DB1D8.8000707@gmail.com>
Message-ID: <8b3894bc0610020414q3b396436wdaa9e906c7939536@mail.gmail.com>

Can't you make use of a deb or rpm instead of building it yourself, perhaps?

On 30/09/06, fred <fredmfp at gmail.com> wrote:
> Hi the list,
>
> Yes, I know it's a little bit OT, but I saw on Wilna DuToit Scipy
> webpage his mat3d.py and thus
> I need to build PyOpenGL (2.0.2.01).
>
> I can't build it because gcc failed with exit status 1...
>
> What do I need to build it ?
>
> PyOpenGL seems to be quite old on sourceforge and not to be still
> maintained.
>
>
> Cheers,
>
>
> PS : python2.4, swig 1.3.23
>
> --
> ? Python, c'est un peu comme la ba?onnette en 14, faut toujours sortir avec,
> et pas h?siter d'en mettre un coup en cas de besoin. ?
> J.-Ph. D.
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>

From fredmfp at gmail.com  Mon Oct  2 07:24:55 2006
From: fredmfp at gmail.com (fred)
Date: Mon, 02 Oct 2006 13:24:55 +0200
Subject: [SciPy-user] error building pyopengl...
In-Reply-To: <8b3894bc0610020414q3b396436wdaa9e906c7939536@mail.gmail.com>
References: <451DB1D8.8000707@gmail.com>
	<8b3894bc0610020414q3b396436wdaa9e906c7939536@mail.gmail.com>
Message-ID: <4520F707.9030002@gmail.com>

William Hunter a ?crit :

>Can't you make use of a deb or rpm instead of building it yourself, perhaps?
>  
>

1) I build all my own python (2.4) stuff in /usr/local.
2) There is no python2.4-opengl deb package (or source) for my sarge.

-- 
? Python, c'est un peu comme la ba?onnette en 14, faut toujours sortir avec,
et pas h?siter d'en mettre un coup en cas de besoin. ?
J.-Ph. D.




From cimrman3 at ntc.zcu.cz  Mon Oct  2 09:13:05 2006
From: cimrman3 at ntc.zcu.cz (Robert Cimrman)
Date: Mon, 02 Oct 2006 15:13:05 +0200
Subject: [SciPy-user] Sparse: Efficient metod to convert to CSC format
In-Reply-To: <8b3894bc0610020130n48bf6029sb8122ed92ecf2c5d@mail.gmail.com>
References: <8b3894bc0610020130n48bf6029sb8122ed92ecf2c5d@mail.gmail.com>
Message-ID: <45211061.8050806@ntc.zcu.cz>

William Hunter wrote:
> I've been bugging Robert C. and Ed S. (thanks guys) for a while about
> this now, but I think it might be good if I share my experiences with
> other users.
> 
> When converting a sparse matrix to CSC format, one of the quickest
> ways to get there is to give <sparse.csc_matrix> three vectors
> containing;
> 
> (1) [values]: the values,
> (2) [rowind]: the row indices and
> (3) [colptr]: the column pointer.
> 
> If one times how long it takes to get your CSC matrix by doing
> sparse.csc_matrix((values, rowind, colptr)) compared to the other ways
> to get it, e.g., csc_matrix(dense_mtx), I've found that the first
> method is faster (enough to be significant for me).
> 
> One can solve a sparse system with <linsolve.spsolve>, if your matrix
> is in CSC format. And here's my question: Let's say I have a way (and
> I might :-)) to construct those 3 vectors very quickly, how can I use
> them directly as arguments in <linsolve.spsolve>? For example:
> 
> solution = linsolve.spsolve([values],[rowind],[colptr],[RHS])

If you have already (values, rowind, colptr) triplet, creating a CSC 
matrix is virtually a no-operation (besides some sanity checks).

Is it really so inconvenient to write:
solution = linsolve.spsolve( csc_matrix( (values, rowind, colptr), shape 
),[RHS])?

On the other hand, the syntax
solution = linsolve.spsolve( (values,rowind,colptr,'csc'), [RHS])
might be useful as a syntactic sugar, so I am not against adding it. 
Note however, that you must indicate somehow if your triplet is CSR or 
CSC or ... - it is not much shorter then writing the full CSC constructor.

r.


From lists.steve at arachnedesign.net  Mon Oct  2 09:40:54 2006
From: lists.steve at arachnedesign.net (Steve Lianoglou)
Date: Mon, 2 Oct 2006 09:40:54 -0400
Subject: [SciPy-user] matplotlib on osx
In-Reply-To: <FC16047E-8419-496E-8939-DBD3258873FD@mac.com>
References: <mailman.23104.1159600993.2761.scipy-user@scipy.org>
	<C7304513-E5E5-4055-AA1C-7FD8161F5048@unsw.edu.au>
	<20061001023457.GA14026@clipper.ens.fr>
	<FC16047E-8419-496E-8939-DBD3258873FD@mac.com>
Message-ID: <184E8FF9-36DC-413C-A565-EA904256F79B@arachnedesign.net>

Hi John,

> Has anyone gotten matplotlib running on OSX recently? I tried
> upgrading to 10.4.8, and building Python 2.5, numpy, scipy, libpng,
> and freetype from source. Everything went fine, even matplotlib
> installed without an error. But when I import matplotlib I get

Mine seems to be working well.

I've installed python and the various dependencies of matplotplib via  
MacPorts.

The dependencies for py-matplotlib are:
python24, freetype, libpng, antigraingeometry, py-numarray, py- 
numeric, py-dateutil, py-tz

I then reinstalled matplotlib myself via recent svn checkouts since I  
wanted it to be working with the latest svn numpy as well. So I have  
some extra stuff lying around since the ports installations depend on  
them, but it all seems to work fine for me.

If you want to use python 2.5, however, MacPorts won't do you any good.

HTH,
-steve




From willemjagter at gmail.com  Mon Oct  2 10:15:33 2006
From: willemjagter at gmail.com (William Hunter)
Date: Mon, 2 Oct 2006 16:15:33 +0200
Subject: [SciPy-user] Sparse: Efficient method to convert to CSC format
Message-ID: <8b3894bc0610020715m4efd4565m7c36a1c040f390a9@mail.gmail.com>

On 02/10/06, Robert Cimrman <cimrman3 at ntc.zcu.cz> wrote:
> William Hunter wrote:
> > I've been bugging Robert C. and Ed S. (thanks guys) for a while about
> > this now, but I think it might be good if I share my experiences with
> > other users.
> >
> > When converting a sparse matrix to CSC format, one of the quickest
> > ways to get there is to give <sparse.csc_matrix> three vectors
> > containing;
> >
> > (1) [values]: the values,
> > (2) [rowind]: the row indices and
> > (3) [colptr]: the column pointer.
> >
> > If one times how long it takes to get your CSC matrix by doing
> > sparse.csc_matrix((values, rowind, colptr)) compared to the other ways
> > to get it, e.g., csc_matrix(dense_mtx), I've found that the first
> > method is faster (enough to be significant for me).
> >
> > One can solve a sparse system with <linsolve.spsolve>, if your matrix
> > is in CSC format. And here's my question: Let's say I have a way (and
> > I might :-)) to construct those 3 vectors very quickly, how can I use
> > them directly as arguments in <linsolve.spsolve>? For example:
> >
> > solution = linsolve.spsolve([values],[rowind],[colptr],[RHS])
>
> If you have already (values, rowind, colptr) triplet, creating a CSC
> matrix is virtually a no-operation (besides some sanity checks).

I suppose I'm really interested (curious) to know what happens behind
the scenes and why (except for the checks). I had a look at the
source, but gave up after a while. There's a method that creates an
instance (?) and I think I understand why it is useful to group the
vectors, but I can't see how this is done, so perhaps I shouldn't be
reading there in any case, but I'd still like to know what happens if
it doesn't require a lot of explanation. I know I shouldn't worry
about it, but I just can't help myself...

> Is it really so inconvenient to write:
> solution = linsolve.spsolve( csc_matrix( (values, rowind, colptr), shape
> ),[RHS])?
>
> On the other hand, the syntax
> solution = linsolve.spsolve( (values,rowind,colptr,'csc'), [RHS])
> might be useful as a syntactic sugar, so I am not against adding it.

No need, that's just syntax.

> Note however, that you must indicate somehow if your triplet is CSR or
> CSC or ... - it is not much shorter then writing the full CSC constructor.
>
> r.
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From bhendrix at enthought.com  Mon Oct  2 11:29:01 2006
From: bhendrix at enthought.com (Bryce Hendrix)
Date: Mon, 02 Oct 2006 10:29:01 -0500
Subject: [SciPy-user] Pros and Cons of Python verses other
	array	environments
In-Reply-To: <20061001023457.GA14026@clipper.ens.fr>
References: <mailman.23104.1159600993.2761.scipy-user@scipy.org>	<C7304513-E5E5-4055-AA1C-7FD8161F5048@unsw.edu.au>
	<20061001023457.GA14026@clipper.ens.fr>
Message-ID: <4521303D.6030405@enthought.com>

I've kept quite about this because I'm trying to solidify all the eggs 
for the next release. Now that the cat is out of the bag, you can find 
nightly builds of scipy and numpy, continuous builds of ETS, and lots of 
other eggs here:

http://code.enthought.com/enstaller/eggs.

The next release is very close, I'm just trying to hammer out the last 
critical bugs for the enstaller application.

Bryce

Gael Varoquaux wrote:
> As for packages repository and dead-easy install for windows there is
> light at the end of the tunnel. Eggs are starting to appear as a package
> standard, and enthought in working on a installer for windows capable of
> download egg from repositories (see
> http://code.enthought.com/enthon/enstaller.shtml for an alpha version).
>
> Ga?l
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>   



From david at ar.media.kyoto-u.ac.jp  Tue Oct  3 01:52:19 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Tue, 03 Oct 2006 14:52:19 +0900
Subject: [SciPy-user] Pros and Cons of
	Python	verses	other	array	environments
In-Reply-To: <451ECCB1.4070301@gmail.com>
References: <451BFBD7.4080701@ieee.org>	<51f97e530609281704n522fa5c8ge00571acec53162e@mail.gmail.com>	<e86a5fd00609281805o44d4b12duf296f766f57a359f@mail.gmail.com>	<451CD238.3040509@ar.media.kyoto-u.ac.jp>	<451DE807.1010602@bigpond.net.au>	<451E5ADE.3050404@ar.media.kyoto-u.ac.jp>
	<451ECCB1.4070301@gmail.com>
Message-ID: <4521FA93.2080905@ar.media.kyoto-u.ac.jp>

Robert Kern wrote:
> David Cournapeau wrote:
>
>   
>> You have first an index on all top level functions, and you can dig it 
>> through as deep as you want. Notice how you know for a given function 
>> which call are called when and how often. I have no idea how difficult 
>> this would be to implement in python. I was told some months ago on the 
>> main python list that hotshot can give a per line profiling of python 
>> code, but this is not documented; also, it looks like it is possible to 
>> get the source code at runtime without too much difficulty in python. I 
>> would be really surprised if nobody tried to do something similar for 
>> python in general, because this is really useful. I have never found 
>> anything for python, but it may be just because I don't know the name 
>> for this kind of tools (I tried googling with terms such as "source 
>> profiling", without much success).
>>     
>
> One excellent tool for drilling through these results is a KDE application 
> called kcachegrind. It was written to visualize valgrind profiling results, but 
> the file format is generic enough that someone wrote a script hotshot2calltree 
> that converts hotshot results to it. I believe it comes with kcachegrind.
>
>    http://kcachegrind.sourceforge.net/cgi-bin/show.cgi
>
> There is a new profiler the comes with 2.5 (but I believe is compatible with at 
> least 2.4) called cProfile (available separately as lsprof). It too has a 
> converter for kcachegrind.
>
>    http://codespeak.net/svn/user/arigo/hack/misc/lsprof/
>    http://www.gnome.org/~johan/lsprofcalltree.py
>
>   

Thanks for the tip: it looks like lsprof can gives you the information 
per child functions, which is the main weakness of previous python 
profilers IMHO. I cannot make it work right now on python2.4, will try 
at home with python 2.5

David


From coatimundi at cox.net  Tue Oct  3 01:59:59 2006
From: coatimundi at cox.net (Coatimundi)
Date: Mon, 02 Oct 2006 22:59:59 -0700
Subject: [SciPy-user] Building Numpy with Visual Studio?
Message-ID: <efsu96$2qf$1@sea.gmane.org>


As I read the build guidelines for Numpy at 
www.scipy.org/Installing_SciPy/Windows I see that the instructions 
suggest that Numpy can be built with the MSVC tools against an ATLAS lib 
built with Cygwin tools.

At this point I am perplexed.  I thought that Cygwin used ELF and that 
Windows used COFF (actually PE) for static libs.

So it is not obvious to me why setup.py should be able to build with the 
  MSVC tools if the atlas and lapack libs are built with Cygwin tools.

Maybe the Microsoft linker understands both ELF and COFF?
Or maybe Cygwin actually uses PE?

Can someone help me understand this?

Thanks.



From fperez.net at gmail.com  Tue Oct  3 03:43:56 2006
From: fperez.net at gmail.com (Fernando Perez)
Date: Tue, 3 Oct 2006 01:43:56 -0600
Subject: [SciPy-user] access to wavelets.scipy.org/svn/
In-Reply-To: <20060929194828.GB13399@swri16wm.electro.swri.edu>
References: <20060929194828.GB13399@swri16wm.electro.swri.edu>
Message-ID: <db6b5ecc0610030043k701e545epe33c2d81e142d0f7@mail.gmail.com>

Hi Glen,

On 9/29/06, Glen W. Mabey <Glen.Mabey at swri.org> wrote:
> Hello,
>
> I don't know of a better place to post than this for a question
> regarding pywt.
>
> Following the instructions found at http://wavelets.scipy.org/index.html for
> checking out the development version:
>
>     $$ svn co http://wavelets.scipy.org/svn/multiresolution/wavelets/trunk wavelets
>     svn: REPORT request failed on '/svn/multiresolution/!svn/vcc/default'
>     svn: REPORT of '/svn/multiresolution/!svn/vcc/default': 400 Bad Request (http://wavelets.scipy.org)
>
>
> and the indicated path in
> http://wavelets.scipy.org/svn/multiresolution/pywt/trunk/README.txt
> yields a similar error.
>
> However, trying:
>     $$ svn co https://wavelets.scipy.org/svn/multiresolution/pywt/trunk/
> at least asks for a password.  However, shouldn't there be (or, could
> there please be) anonymous access to this tree?

As others have pointed, this is an issue with your local proxy config.
 If you're still having problems, please let us know.

Also, note that the brief history provided by Jarrod is correct.
Filip's code has been moved over to the scipy site, and Filip has SVN
commit access to it.

I just did a quick update of the site to better reflect this, and
turned it into a Moin wiki completely.  This will remove me as the
bottleneck for site handling, and Filip (or anyone else) can now
contribute more up to date info.

A pywavelets project is one of those things that everyone seems to
need but nobody has the time to fully develop.  Currently at least
Filip is making progress, but my understanding is that his time is
also limited for this project.  If more users with expertise in this
area and some time to spare are willing to help, there's plenty to
do...

Cheers,

f


From robert.kern at gmail.com  Tue Oct  3 03:56:41 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 03 Oct 2006 02:56:41 -0500
Subject: [SciPy-user] Building Numpy with Visual Studio?
In-Reply-To: <efsu96$2qf$1@sea.gmane.org>
References: <efsu96$2qf$1@sea.gmane.org>
Message-ID: <452217B9.1030607@gmail.com>

Coatimundi wrote:
> As I read the build guidelines for Numpy at 
> www.scipy.org/Installing_SciPy/Windows I see that the instructions 
> suggest that Numpy can be built with the MSVC tools against an ATLAS lib 
> built with Cygwin tools.
> 
> At this point I am perplexed.  I thought that Cygwin used ELF and that 
> Windows used COFF (actually PE) for static libs.
> 
> So it is not obvious to me why setup.py should be able to build with the 
>   MSVC tools if the atlas and lapack libs are built with Cygwin tools.
> 
> Maybe the Microsoft linker understands both ELF and COFF?
> Or maybe Cygwin actually uses PE?

The latter.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From hetland at tamu.edu  Tue Oct  3 09:56:12 2006
From: hetland at tamu.edu (Rob Hetland)
Date: Tue, 3 Oct 2006 08:56:12 -0500
Subject: [SciPy-user] matplotlib on osx
In-Reply-To: <184E8FF9-36DC-413C-A565-EA904256F79B@arachnedesign.net>
References: <mailman.23104.1159600993.2761.scipy-user@scipy.org>
	<C7304513-E5E5-4055-AA1C-7FD8161F5048@unsw.edu.au>
	<20061001023457.GA14026@clipper.ens.fr>
	<FC16047E-8419-496E-8939-DBD3258873FD@mac.com>
	<184E8FF9-36DC-413C-A565-EA904256F79B@arachnedesign.net>
Message-ID: <D8ECF6F1-624C-4EE3-8FEC-4BB11728E99D@tamu.edu>


I also got mpl to work using the i-Installer to install Freetype2 and  
libpng (they are both available as universal binaries).

I have installed on my macbook pro and a number of student macbooks  
with no issues using this method,

-Rob

On Oct 2, 2006, at 8:40 AM, Steve Lianoglou wrote:

> Hi John,
>
>> Has anyone gotten matplotlib running on OSX recently? I tried
>> upgrading to 10.4.8, and building Python 2.5, numpy, scipy, libpng,
>> and freetype from source. Everything went fine, even matplotlib
>> installed without an error. But when I import matplotlib I get
>
> Mine seems to be working well.
>
> I've installed python and the various dependencies of matplotplib via
> MacPorts.
>
> The dependencies for py-matplotlib are:
> python24, freetype, libpng, antigraingeometry, py-numarray, py-
> numeric, py-dateutil, py-tz
>
> I then reinstalled matplotlib myself via recent svn checkouts since I
> wanted it to be working with the latest svn numpy as well. So I have
> some extra stuff lying around since the ports installations depend on
> them, but it all seems to work fine for me.
>
> If you want to use python 2.5, however, MacPorts won't do you any  
> good.
>
> HTH,
> -steve
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

----
Rob Hetland, Associate Professor
Dept. of Oceanography, Texas A&M University
http://pong.tamu.edu/~rob
phone: 979-458-0096, fax: 979-845-6331




From coatimundi at cox.net  Tue Oct  3 10:03:00 2006
From: coatimundi at cox.net (Coatimundi)
Date: Tue, 03 Oct 2006 07:03:00 -0700
Subject: [SciPy-user] Building Numpy with Visual Studio?
In-Reply-To: <452217B9.1030607@gmail.com>
References: <efsu96$2qf$1@sea.gmane.org> <452217B9.1030607@gmail.com>
Message-ID: <eftqis$sd9$1@sea.gmane.org>

Robert Kern wrote:
> Coatimundi wrote:
>> As I read the build guidelines for Numpy at 
>> www.scipy.org/Installing_SciPy/Windows I see that the instructions 
>> suggest that Numpy can be built with the MSVC tools against an ATLAS lib 
>> built with Cygwin tools.
>>
>> At this point I am perplexed.  I thought that Cygwin used ELF and that 
>> Windows used COFF (actually PE) for static libs.
>>
>> So it is not obvious to me why setup.py should be able to build with the 
>>   MSVC tools if the atlas and lapack libs are built with Cygwin tools.
>>
>> Maybe the Microsoft linker understands both ELF and COFF?
>> Or maybe Cygwin actually uses PE?
> 
> The latter.
> 

Thanks.  I scoured the Cygwin site and finally found a strong clue to 
this in the Cygwin entry at wikipedia: 
http://en.wikipedia.org/wiki/Cygwin#History



From fccoelho at gmail.com  Tue Oct  3 14:46:40 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Tue, 3 Oct 2006 15:46:40 -0300
Subject: [SciPy-user] gaussian_kde broken?
Message-ID: <d9af7a880610031146y5d6a42edq85dc230526e029c6@mail.gmail.com>

Hi,

I noticed a new bug in the combination Numpy1.0rc1/Scipy0.5.1:

#generate a sample from a normal distribution:
a=normal(0,1,10000)
from scipy.stats.kde import gaussian_kde as kde
d=kde(a)
d.evaluate(arange(-1,1,0.1))
---------------------------------------------------------------------------
exceptions.TypeError                                 Traceback (most recent
call last)

/home/fccoelho/Documents/Papers/YFgame/<console>

/usr/lib/python2.4/site-packages/scipy/stats/kde.py in evaluate(self,
points)
    116                 diff = self.dataset - points[:,i,newaxis]
    117                 tdiff = dot(self.inv_cov, diff)
--> 118                 energy = sum(diff*tdiff,axis=0)/2.0
    119                 result[i] = sum(exp(-energy),axis=0)
    120

TypeError: sum() takes no keyword arguments

Are there any fixes available for this?

thanks

-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismar
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From robert.kern at gmail.com  Tue Oct  3 14:51:23 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 03 Oct 2006 13:51:23 -0500
Subject: [SciPy-user] gaussian_kde broken?
In-Reply-To: <d9af7a880610031146y5d6a42edq85dc230526e029c6@mail.gmail.com>
References: <d9af7a880610031146y5d6a42edq85dc230526e029c6@mail.gmail.com>
Message-ID: <4522B12B.70305@gmail.com>

Flavio Coelho wrote:
> Hi,
> 
> I noticed a new bug in the combination Numpy1.0rc1/Scipy0.5.1:
> 
> #generate a sample from a normal distribution:
> a=normal(0,1,10000)
> from scipy.stats.kde import gaussian_kde as kde
> d=kde(a)
> d.evaluate (arange(-1,1,0.1))
> ---------------------------------------------------------------------------
> exceptions.TypeError                                 Traceback (most 
> recent call last)
> 
> /home/fccoelho/Documents/Papers/YFgame/<console>
> 
> /usr/lib/python2.4/site-packages/scipy/stats/kde.py in evaluate(self, 
> points)
>     116                 diff = self.dataset - points[:,i,newaxis]
>     117                 tdiff = dot(self.inv_cov, diff)
> --> 118                 energy = sum(diff*tdiff,axis=0)/2.0
>     119                 result[i] = sum(exp(-energy),axis=0)
>     120
> 
> TypeError: sum() takes no keyword arguments
> 
> Are there any fixes available for this?

It's been fixed in SVN for a while now.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From fccoelho at gmail.com  Tue Oct  3 14:59:07 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Tue, 3 Oct 2006 15:59:07 -0300
Subject: [SciPy-user] gaussian_kde broken?
In-Reply-To: <4522B12B.70305@gmail.com>
References: <d9af7a880610031146y5d6a42edq85dc230526e029c6@mail.gmail.com>
	<4522B12B.70305@gmail.com>
Message-ID: <d9af7a880610031159s2c1437a4qfc38a17c04c2ef3c@mail.gmail.com>

Thanks Robert!!

Now, which one should I update to SVN numpy or scipy?

Thanks again!

Fl?vio

On 10/3/06, Robert Kern <robert.kern at gmail.com> wrote:
>
> Flavio Coelho wrote:
> > Hi,
> >
> > I noticed a new bug in the combination Numpy1.0rc1/Scipy0.5.1:
> >
> > #generate a sample from a normal distribution:
> > a=normal(0,1,10000)
> > from scipy.stats.kde import gaussian_kde as kde
> > d=kde(a)
> > d.evaluate (arange(-1,1,0.1))
> >
> ---------------------------------------------------------------------------
> > exceptions.TypeError                                 Traceback (most
> > recent call last)
> >
> > /home/fccoelho/Documents/Papers/YFgame/<console>
> >
> > /usr/lib/python2.4/site-packages/scipy/stats/kde.py in evaluate(self,
> > points)
> >     116                 diff = self.dataset - points[:,i,newaxis]
> >     117                 tdiff = dot(self.inv_cov, diff)
> > --> 118                 energy = sum(diff*tdiff,axis=0)/2.0
> >     119                 result[i] = sum(exp(-energy),axis=0)
> >     120
> >
> > TypeError: sum() takes no keyword arguments
> >
> > Are there any fixes available for this?
>
> It's been fixed in SVN for a while now.
>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma
>   that is made terrible by our own mad attempt to interpret it as though
> it had
>   an underlying truth."
>    -- Umberto Eco
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismark
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From robert.kern at gmail.com  Tue Oct  3 15:23:42 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 03 Oct 2006 14:23:42 -0500
Subject: [SciPy-user] gaussian_kde broken?
In-Reply-To: <d9af7a880610031159s2c1437a4qfc38a17c04c2ef3c@mail.gmail.com>
References: <d9af7a880610031146y5d6a42edq85dc230526e029c6@mail.gmail.com>	<4522B12B.70305@gmail.com>
	<d9af7a880610031159s2c1437a4qfc38a17c04c2ef3c@mail.gmail.com>
Message-ID: <4522B8BE.2080705@gmail.com>

Flavio Coelho wrote:
> Thanks Robert!!
> 
> Now, which one should I update to SVN numpy or scipy?

You might probably need to do both just to keep versions in sync, but the 
problem was in scipy, and so is the fix.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From fredmfp at gmail.com  Wed Oct  4 03:05:01 2006
From: fredmfp at gmail.com (fred)
Date: Wed, 04 Oct 2006 09:05:01 +0200
Subject: [SciPy-user] [OT] displaying pictures on the wiki...
Message-ID: <45235D1D.10106@gmail.com>

Hi the list,

Is it possible to displays pictures in a "array" (side-by-side) as this,
on the wiki ?



some text...

---------
| x | x |
---------

some text...

---------
| x | x |
---------

some text...

...


Cheers,


-- 
http://scipy.org/FredericPetit



From david at ar.media.kyoto-u.ac.jp  Wed Oct  4 04:34:20 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Wed, 04 Oct 2006 17:34:20 +0900
Subject: [SciPy-user] Is anybody working on a toolbox for
 Kalman	filtering and derivative ?
In-Reply-To: <D1ACB40F-9581-446C-99E5-853D33944108@eecs.berkeley.edu>
References: <451D36C7.6080507@ar.media.kyoto-u.ac.jp>
	<D1ACB40F-9581-446C-99E5-853D33944108@eecs.berkeley.edu>
Message-ID: <4523720C.1090509@ar.media.kyoto-u.ac.jp>

Aaron Hoover wrote:
> Hi David,
>
> Though it's not just a Kalman filtering toolbox, the open source  
> computer vision library, OpenCV contains implementations of Kalman  
> filtering. I've had good success using OpenCV's Python wrappers to do  
> a lot of
> 2D vision and image processing very quickly with Python. If nothing  
> else, you could use their source as a point of comparison for your  
> implementation.
>
>   
Thanks for the tip, but I am mainly interested in non visual related 
problems, and I wish to be more general. Could be nice to have 
comparison, though, I agree,

David


From arserlom at gmail.com  Wed Oct  4 07:18:48 2006
From: arserlom at gmail.com (Armando Serrano Lombillo)
Date: Wed, 4 Oct 2006 13:18:48 +0200
Subject: [SciPy-user] Problems building numpy from SVN
Message-ID: <d7ab268c0610040418i29fce6fepc0468623666505de@mail.gmail.com>

I've checked out numpy's source code from
http://svn.scipy.org/svn/numpy/trunk/ and have tried to build it but it's
giving me this error:

error: Command "C:\MinGW\bin\g77.exe -g -Wall -mno-cygwin -shared
build\temp.win
32-2.5\Release\numpy\linalg\lapack_litemodule.o "-LC:\Archivos de
programa\Atlas
" -LC:\MinGW\lib -LC:\MinGW\lib\gcc\mingw32\3.4.2 -LC:\Python25\libs
-LC:\Python
25\PCBuild -llapack -llapack -lf77blas -lcblas -latlas -lpython25 -lg2c
-lgcc -l
msvcr71 -o build\lib.win32-2.5\numpy\linalg\lapack_lite.pyd" failed with
exit st
atus 1

I'm on Windows XP, python 2.5 and I'm using mingw 5.0.3 and these atlas
files: "Pentium 4 /
SSE2".<http://www.scipy.org/Installing_SciPy/Windows?action=AttachFile&do=get&target=atlas3.6.0_WinNT_P4SSE2.zip>

The command I used to build numpy was:
setup.py config --compiler=mingw32 build --compiler=mingw32 bdist_wininst

Can anybody help?
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From skokot at po.opole.pl  Wed Oct  4 09:16:01 2006
From: skokot at po.opole.pl (Seweryn Kokot)
Date: Wed, 04 Oct 2006 15:16:01 +0200
Subject: [SciPy-user] problem with unicode in matplotlib
Message-ID: <874pukgr1q.fsf@poczta.po.opole.pl>

Hello,

I'm using python-matplotlib from debian unstable (vers. 0.87.5) 
and the plots doesn't display properly polish fonts, 
instead I get squares on graphs.
Simple example

#!/usr/bin/python
# -*- coding: iso-8859-2 -*-
from pylab import *
plot([1, 2, 3], [1, 4, 2])
xlabel(unicode('Miesi?c maj','iso-8859-2'))
ylabel(unicode('??????','iso-8859-2'))
show()

Any idea?
Regards,
Seweryn Kokot



From djf at pdx.edu  Wed Oct  4 10:20:55 2006
From: djf at pdx.edu (Daniel Fish)
Date: Wed, 4 Oct 2006 07:20:55 -0700
Subject: [SciPy-user] leastsquare N>M ?
Message-ID: <002701c6e7c0$4e831b70$6401a8c0@Fish>

I receive the following error from scipy.optimize.leastsq() (in scipy version 0.5.0.2033, python 2.4 (windows)):

# CODE--------------------------------------
1. from scipy.optimize import *
2. def func(x):
3.     return x[0]**2
4. x0=[1,0]
5. (y,msg)=leastsq(func,x0)
6. print y

# OUTPUT----------------------------------------------------------------------------------------------------
File "C:/cygwin/Ksim/PythonCode/Database/test.py", line 5, in ?
(y,msg)=leastsq(func,x0)
File "C:\Python24\lib\site-packages\scipy\optimize\minpack.py", line 257, in leastsq raise errors[info][1], errors[info][0]
TypeError: Improper input parameters.
2 1 1 0.000000 0.000000 0.000000 600 100.000000
# -----------------------------------------------------------------------------------------------------------------

But have no problem if I let x0=[1]. Does leastsq not work with more unknowns than equations, or am I doing something wrong?

thanks,

djoefish






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From stefan at sun.ac.za  Wed Oct  4 11:23:34 2006
From: stefan at sun.ac.za (Stefan van der Walt)
Date: Wed, 4 Oct 2006 17:23:34 +0200
Subject: [SciPy-user] leastsquare N>M ?
In-Reply-To: <002701c6e7c0$4e831b70$6401a8c0@Fish>
References: <002701c6e7c0$4e831b70$6401a8c0@Fish>
Message-ID: <20061004152334.GO26999@mentat.za.net>

On Wed, Oct 04, 2006 at 07:20:55AM -0700, Daniel Fish wrote:
> I receive the following error from scipy.optimize.leastsq() (in scipy version
> 0.5.0.2033, python 2.4 (windows)):
>  
> # CODE--------------------------------------
> 1. from scipy.optimize import *
> 2. def func(x):
> 3.     return x[0]**2
> 4. x0=[1,0]
> 5. (y,msg)=leastsq(func,x0)
> 6. print y
>  
> #
> OUTPUT----------------------------------------------------------------------------------------------------
> File "C:/cygwin/Ksim/PythonCode/Database/test.py", line 5, in ?
> (y,msg)=leastsq(func,x0)
> File "C:\Python24\lib\site-packages\scipy\optimize\minpack.py", line 257, in
> leastsq raise errors[info][1], errors[info][0]
> TypeError: Improper input parameters.
> 2 1 1 0.000000 0.000000 0.000000 600 100.000000
> #
> -----------------------------------------------------------------------------------------------------------------
>  
> But have no problem if I let x0=[1]. Does leastsq not work with more unknowns
> than equations, or am I doing something wrong?

Leastsq is used when you have more equations than unknowns, to provide
you with an answer that minimises some norm.  In your case, rather use
'fmin', i.e.

y,msg = fmin(func,x0)

to produce y = 6.22301527786e-61

Regards
St?fan


From jstano at interchange.ubc.ca  Wed Oct  4 13:02:16 2006
From: jstano at interchange.ubc.ca (joe stano)
Date: Wed, 04 Oct 2006 10:02:16 -0700
Subject: [SciPy-user] Scipy Minimizer
Message-ID: <0J6M004HNFBS8Y@smtp.interchange.ubc.ca>

Hi

Does anyone know what the best scipy minimizer to use would be if I need to
have upper and lower bounds on my list of decision variables, along with
separate constraint functions?  I have tried fmin_cobyla and fmin_lbfgsb but
no luck.  Currently I can solve my function using Excel Solver, but would
rather implement in Python.

 

Thanks for any help.

 

joe

 

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From wangxj.uc at gmail.com  Wed Oct  4 13:16:49 2006
From: wangxj.uc at gmail.com (Xiaojian Wang)
Date: Wed, 4 Oct 2006 10:16:49 -0700
Subject: [SciPy-user] Scipy Minimizer
In-Reply-To: <0J6M004HNFBS8Y@smtp.interchange.ubc.ca>
References: <0J6M004HNFBS8Y@smtp.interchange.ubc.ca>
Message-ID: <d23aa0180610041016u7b00cd8bvc0ec61e14fd256aa@mail.gmail.com>

joe
I used fmin_cobyla, it works on my problem, what is the difference between
Excel Solver and fmin_cobyla/fmin_lbfgsb ??, there is no general best
minimizer,
you may try different methods on your specific problem.
xiaojian





On 10/4/06, joe stano <jstano at interchange.ubc.ca> wrote:
>
>  Hi
>
> Does anyone know what the best scipy minimizer to use would be if I need
> to have upper and lower bounds on my list of decision variables, along with
> separate constraint functions?  I have tried fmin_cobyla and fmin_lbfgsb but
> no luck.  Currently I can solve my function using Excel Solver, but would
> rather implement in Python.
>
>
>
> Thanks for any help.
>
>
>
> joe
>
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
>
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From jstano at interchange.ubc.ca  Wed Oct  4 13:26:34 2006
From: jstano at interchange.ubc.ca (joe stano)
Date: Wed, 04 Oct 2006 10:26:34 -0700
Subject: [SciPy-user] Scipy Minimizer
Message-ID: <0J6M004J7GGANS@smtp.interchange.ubc.ca>

Thanks xiaojian

I think solver uses a generalized reduced gradient optimization.  My biggest
problem is that the scipy optimizer constraint functions require the
constraint to return a single number, whereas I need to return a list of
numbers, all meeting the constraint (non negative).  Maybe it is just my
implementation but I am not sure.  

 

joe

 

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From hetland at tamu.edu  Wed Oct  4 15:01:46 2006
From: hetland at tamu.edu (Rob Hetland)
Date: Wed, 4 Oct 2006 14:01:46 -0500
Subject: [SciPy-user] matplotlib on osx
In-Reply-To: <D8ECF6F1-624C-4EE3-8FEC-4BB11728E99D@tamu.edu>
References: <mailman.23104.1159600993.2761.scipy-user@scipy.org>
	<C7304513-E5E5-4055-AA1C-7FD8161F5048@unsw.edu.au>
	<20061001023457.GA14026@clipper.ens.fr>
	<FC16047E-8419-496E-8939-DBD3258873FD@mac.com>
	<184E8FF9-36DC-413C-A565-EA904256F79B@arachnedesign.net>
	<D8ECF6F1-624C-4EE3-8FEC-4BB11728E99D@tamu.edu>
Message-ID: <3B22122A-7D99-4115-A5B9-098553131E6C@tamu.edu>


OK.  I would like to change my answer.

I was just installing MPL on a student's new MacBook.  He had  
installed Python 2.5 (only), and we tried to get the svn version of  
MPL working after a successful install of numpy.  MPL segfaulted.

Then we installed python 2.4.3, and the numpy and mpl packages  
available from macpython.  These worked -- and also fixed the mpl  
that was installed in python 2.5!

I didn't have time to dig around to see what was actually changed,  
but I thought this was strange, and interesting enough to report,

-Rob

On Oct 3, 2006, at 8:56 AM, Rob Hetland wrote:

>
> I also got mpl to work using the i-Installer to install Freetype2 and
> libpng (they are both available as universal binaries).
>
> I have installed on my macbook pro and a number of student macbooks
> with no issues using this method,
>
> -Rob
>
> On Oct 2, 2006, at 8:40 AM, Steve Lianoglou wrote:
>
>> Hi John,
>>
>>> Has anyone gotten matplotlib running on OSX recently? I tried
>>> upgrading to 10.4.8, and building Python 2.5, numpy, scipy, libpng,
>>> and freetype from source. Everything went fine, even matplotlib
>>> installed without an error. But when I import matplotlib I get
>>
>> Mine seems to be working well.
>>
>> I've installed python and the various dependencies of matplotplib via
>> MacPorts.
>>
>> The dependencies for py-matplotlib are:
>> python24, freetype, libpng, antigraingeometry, py-numarray, py-
>> numeric, py-dateutil, py-tz
>>
>> I then reinstalled matplotlib myself via recent svn checkouts since I
>> wanted it to be working with the latest svn numpy as well. So I have
>> some extra stuff lying around since the ports installations depend on
>> them, but it all seems to work fine for me.
>>
>> If you want to use python 2.5, however, MacPorts won't do you any
>> good.
>>
>> HTH,
>> -steve
>>
>>
>> _______________________________________________
>> SciPy-user mailing list
>> SciPy-user at scipy.org
>> http://projects.scipy.org/mailman/listinfo/scipy-user
>
> ----
> Rob Hetland, Associate Professor
> Dept. of Oceanography, Texas A&M University
> http://pong.tamu.edu/~rob
> phone: 979-458-0096, fax: 979-845-6331
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

----
Rob Hetland, Associate Professor
Dept. of Oceanography, Texas A&M University
http://pong.tamu.edu/~rob
phone: 979-458-0096, fax: 979-845-6331




From robert.kern at gmail.com  Wed Oct  4 15:48:47 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Wed, 04 Oct 2006 14:48:47 -0500
Subject: [SciPy-user] Scipy Minimizer
In-Reply-To: <0J6M004J7GGANS@smtp.interchange.ubc.ca>
References: <0J6M004J7GGANS@smtp.interchange.ubc.ca>
Message-ID: <4524101F.2010304@gmail.com>

joe stano wrote:
> Thanks xiaojian
> 
> I think solver uses a generalized reduced gradient optimization.  My 
> biggest problem is that the scipy optimizer constraint functions require 
> the constraint to return a single number, whereas I need to return a 
> list of numbers, all meeting the constraint (non negative).  Maybe it is 
> just my implementation but I am not sure. 

fmin_cobyla takes a list of constraint functions. Take your single function that 
returns multiple numbers and make separate functions each returning one number.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From davidlinke at tiscali.de  Wed Oct  4 19:38:11 2006
From: davidlinke at tiscali.de (David Linke)
Date: Thu, 05 Oct 2006 01:38:11 +0200
Subject: [SciPy-user] [OT] displaying pictures on the wiki...
In-Reply-To: <45235D1D.10106@gmail.com>
References: <45235D1D.10106@gmail.com>
Message-ID: <452445E3.4090500@tiscali.de>

fred wrote:

> Hi the list,
> 
> Is it possible to displays pictures in a "array" (side-by-side) as this,
> on the wiki ?
> 
> some text...
> 
> ---------
> | x | x |
> ---------
> 
(...)

Hi Fred,

see my change on your page http://scipy.org/FredericPetit

If anybody else is interested in the answer: To solve this use a table 
for side-by-side arrangement and the ImageLink-macro for adjusting the 
size. ImageLink is installed in the scipy wiki (see 
http://moinmoin.wikiwikiweb.de/MacroMarket/ImageLink for options of the 
macro).

Regards,
David


From fredmfp at gmail.com  Thu Oct  5 02:37:57 2006
From: fredmfp at gmail.com (fred)
Date: Thu, 05 Oct 2006 08:37:57 +0200
Subject: [SciPy-user] [OT] displaying pictures on the wiki...
In-Reply-To: <452445E3.4090500@tiscali.de>
References: <45235D1D.10106@gmail.com> <452445E3.4090500@tiscali.de>
Message-ID: <4524A845.1070300@gmail.com>

David Linke a ?crit :

>
>Hi Fred,
>
>see my change on your page http://scipy.org/FredericPetit
>  
>
Eh, that's great ! :-)

Thanks a lot.

-- 
http://scipy.org/FredericPetit



From mjakubik at ta3.sk  Thu Oct  5 05:20:59 2006
From: mjakubik at ta3.sk (Marian Jakubik)
Date: Thu, 5 Oct 2006 11:20:59 +0200
Subject: [SciPy-user] SuSE 10.1 installation problem
Message-ID: <20061005112059.7513cfa5@jakubik.ta3.sk>

Hi everyone,

I'm a SciPy newbie and have problem with installing it on SuSE 10.1.

I installed numpy-1.0rc1, then blas-3.0-926.i586.rpm &
lapack-3.0-926.i586.rpm and then scipy-0.5.1...

I tried to run this very simple script:
...
from scipy import *
p = poly1d([3,4,5])
print p
...

and I've got this error:

Traceback (most recent call last):
  File "1.py", line 1, in ?
    from scipy import *
  File
"/usr/local/lib/python2.4/site-packages/scipy/signal/__init__.py", line
9, in ? from bsplines import * File
"/usr/local/lib/python2.4/site-packages/scipy/signal/bsplines.py", line
3, in ? import scipy.special File
"/usr/local/lib/python2.4/site-packages/scipy/special/__init__.py",
line 10, in ? import orthogonal File
"/usr/local/lib/python2.4/site-packages/scipy/special/orthogonal.py",
line 67, in ? from scipy.linalg import eig File
"/usr/local/lib/python2.4/site-packages/scipy/linalg/__init__.py", line
8, in ? from basic import * File
"/usr/local/lib/python2.4/site-packages/scipy/linalg/basic.py", line
17, in ? from lapack import get_lapack_funcs File
"/usr/local/lib/python2.4/site-packages/scipy/linalg/lapack.py", line
17, in ? from scipy.linalg import flapack
ImportError: /usr/lib/libblas.so.3: undefined symbol: _gfortran_filename

I think the problem is in "from scipy import *" statement and is linked to blas & lapack...

Can anyone help me, pls?


Best regards,
Marian Jakubik


From ckkart at hoc.net  Thu Oct  5 05:21:49 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Thu, 05 Oct 2006 18:21:49 +0900
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <20061005112059.7513cfa5@jakubik.ta3.sk>
References: <20061005112059.7513cfa5@jakubik.ta3.sk>
Message-ID: <4524CEAD.2020804@hoc.net>

Marian Jakubik wrote:
> Hi everyone,
> 
> I'm a SciPy newbie and have problem with installing it on SuSE 10.1.
> 
> I installed numpy-1.0rc1, then blas-3.0-926.i586.rpm &
> lapack-3.0-926.i586.rpm and then scipy-0.5.1...
> 
> I tried to run this very simple script:
> ...
> from scipy import *
> p = poly1d([3,4,5])
> print p
> ...
> 
> and I've got this error:
> 
> Traceback (most recent call last):
>   File "1.py", line 1, in ?
>     from scipy import *
>   File
> "/usr/local/lib/python2.4/site-packages/scipy/signal/__init__.py", line
> 9, in ? from bsplines import * File
> "/usr/local/lib/python2.4/site-packages/scipy/signal/bsplines.py", line
> 3, in ? import scipy.special File
> "/usr/local/lib/python2.4/site-packages/scipy/special/__init__.py",
> line 10, in ? import orthogonal File
> "/usr/local/lib/python2.4/site-packages/scipy/special/orthogonal.py",
> line 67, in ? from scipy.linalg import eig File
> "/usr/local/lib/python2.4/site-packages/scipy/linalg/__init__.py", line
> 8, in ? from basic import * File
> "/usr/local/lib/python2.4/site-packages/scipy/linalg/basic.py", line
> 17, in ? from lapack import get_lapack_funcs File
> "/usr/local/lib/python2.4/site-packages/scipy/linalg/lapack.py", line
> 17, in ? from scipy.linalg import flapack
> ImportError: /usr/lib/libblas.so.3: undefined symbol: _gfortran_filename
> 
> I think the problem is in "from scipy import *" statement and is linked to blas & lapack...
> 

SuSE blas and lapack rpms are buggy.
You have to build them yourself.
Christian


From mjakubik at ta3.sk  Thu Oct  5 06:21:33 2006
From: mjakubik at ta3.sk (Marian Jakubik)
Date: Thu, 5 Oct 2006 12:21:33 +0200
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <4524CEAD.2020804@hoc.net>
References: <20061005112059.7513cfa5@jakubik.ta3.sk> <4524CEAD.2020804@hoc.net>
Message-ID: <20061005122133.6319c3da@jakubik.ta3.sk>

Could you help me with "building them myself"???

I tried to do this, but an error occured during the building from source codes.

Could you post me some hints for building it?

Best regards,

Marian Jakubik





On Thu, 05 Oct 2006 18:21:49 +0900
Christian Kristukat <ckkart at hoc.net> wrote:

> Marian Jakubik wrote:
> > Hi everyone,
> > 
> > I'm a SciPy newbie and have problem with installing it on SuSE 10.1.
> > 
> > I installed numpy-1.0rc1, then blas-3.0-926.i586.rpm &
> > lapack-3.0-926.i586.rpm and then scipy-0.5.1...
> > 
> > I tried to run this very simple script:
> > ...
> > from scipy import *
> > p = poly1d([3,4,5])
> > print p
> > ...
> > 
> > and I've got this error:
> > 
> > Traceback (most recent call last):
> >   File "1.py", line 1, in ?
> >     from scipy import *
> >   File
> > "/usr/local/lib/python2.4/site-packages/scipy/signal/__init__.py", line
> > 9, in ? from bsplines import * File
> > "/usr/local/lib/python2.4/site-packages/scipy/signal/bsplines.py", line
> > 3, in ? import scipy.special File
> > "/usr/local/lib/python2.4/site-packages/scipy/special/__init__.py",
> > line 10, in ? import orthogonal File
> > "/usr/local/lib/python2.4/site-packages/scipy/special/orthogonal.py",
> > line 67, in ? from scipy.linalg import eig File
> > "/usr/local/lib/python2.4/site-packages/scipy/linalg/__init__.py", line
> > 8, in ? from basic import * File
> > "/usr/local/lib/python2.4/site-packages/scipy/linalg/basic.py", line
> > 17, in ? from lapack import get_lapack_funcs File
> > "/usr/local/lib/python2.4/site-packages/scipy/linalg/lapack.py", line
> > 17, in ? from scipy.linalg import flapack
> > ImportError: /usr/lib/libblas.so.3: undefined symbol: _gfortran_filename
> > 
> > I think the problem is in "from scipy import *" statement and is linked to blas & lapack...
> > 
> 
> SuSE blas and lapack rpms are buggy.
> You have to build them yourself.
> Christian
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user


From ckkart at hoc.net  Thu Oct  5 06:28:25 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Thu, 05 Oct 2006 19:28:25 +0900
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <20061005122133.6319c3da@jakubik.ta3.sk>
References: <20061005112059.7513cfa5@jakubik.ta3.sk> <4524CEAD.2020804@hoc.net>
	<20061005122133.6319c3da@jakubik.ta3.sk>
Message-ID: <4524DE49.9040105@hoc.net>

Marian Jakubik wrote:
> Could you help me with "building them myself"???
> 
> I tried to do this, but an error occured during the building from source codes.
> 
> Could you post me some hints for building it?
> 

http://pong.tamu.edu/tiki/tiki-view_blog_post.php?blogId=6&postId=97

Following these instructions worked for me on SuSE 10.1 using gcc4/gfortran to
build lapack and blas. I remember that the lapack tests failed but the lib was
built anyway.

Christian





From nwagner at iam.uni-stuttgart.de  Thu Oct  5 06:44:25 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Thu, 05 Oct 2006 12:44:25 +0200
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <4524DE49.9040105@hoc.net>
References: <20061005112059.7513cfa5@jakubik.ta3.sk>
	<4524CEAD.2020804@hoc.net>	<20061005122133.6319c3da@jakubik.ta3.sk>
	<4524DE49.9040105@hoc.net>
Message-ID: <4524E209.404@iam.uni-stuttgart.de>

Christian Kristukat wrote:
> Marian Jakubik wrote:
>   
>> Could you help me with "building them myself"???
>>
>> I tried to do this, but an error occured during the building from source codes.
>>
>> Could you post me some hints for building it?
>>
>>     
>
> http://pong.tamu.edu/tiki/tiki-view_blog_post.php?blogId=6&postId=97
>
> Following these instructions worked for me on SuSE 10.1 using gcc4/gfortran to
> build lapack and blas. I remember that the lapack tests failed but the lib was
> built anyway.
>
> Christian
>
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   
Is gfortran really stable/reliable ?

Nils
 


From mjakubik at ta3.sk  Thu Oct  5 07:09:15 2006
From: mjakubik at ta3.sk (Marian Jakubik)
Date: Thu, 5 Oct 2006 13:09:15 +0200
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <4524E209.404@iam.uni-stuttgart.de>
References: <20061005112059.7513cfa5@jakubik.ta3.sk> <4524CEAD.2020804@hoc.net>
	<20061005122133.6319c3da@jakubik.ta3.sk> <4524DE49.9040105@hoc.net>
	<4524E209.404@iam.uni-stuttgart.de>
Message-ID: <20061005130915.02134612@jakubik.ta3.sk>

Christian,

thanks a lot.. It works...!!!

Marian

On Thu, 05 Oct 2006 12:44:25 +0200
Nils Wagner <nwagner at iam.uni-stuttgart.de> wrote:

> Christian Kristukat wrote:
> > Marian Jakubik wrote:
> >   
> >> Could you help me with "building them myself"???
> >>
> >> I tried to do this, but an error occured during the building from source codes.
> >>
> >> Could you post me some hints for building it?
> >>
> >>     
> >
> > http://pong.tamu.edu/tiki/tiki-view_blog_post.php?blogId=6&postId=97
> >
> > Following these instructions worked for me on SuSE 10.1 using gcc4/gfortran to
> > build lapack and blas. I remember that the lapack tests failed but the lib was
> > built anyway.
> >
> > Christian
> >
> >
> >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >   
> Is gfortran really stable/reliable ?
> 
> Nils
>  
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user


From jbednar at inf.ed.ac.uk  Thu Oct  5 09:37:18 2006
From: jbednar at inf.ed.ac.uk (James A. Bednar)
Date: Thu, 5 Oct 2006 14:37:18 +0100
Subject: [SciPy-user] weave broken with GCC 4.1.x
Message-ID: <17701.2702.582663.583713@lodestar.inf.ed.ac.uk>

Hi all,

I've looked in the mailing-list archives and Trac for an answer to
this question, but couldn't find anything relevant:

- Is there a standalone version of weave (not requiring the rest of
  SciPy) that works with GCC 4.1.x?

We've been using weave happily for our Topographica simulator
(www.topographica.org) for a couple of years now, and it's been very
helpful.  However, we are not currently interested in using the rest
of SciPy, because SciPy has so many external dependencies on libraries
that we would not be able to supply with our code.  Instead, we just
installed Scipy_core-0.3.0_108.1820, which provides weave by itself.
This has been working fine with GCC 3.x, 4.0.3, and 4.04.

However, this version of weave doesn't work anymore with GCC 4.1.1 --
apparently GCC has added even more checks that find errors in the
weave code, such as:

  /disk/scratch/topographica-0.9.1/lib/python2.4/site-packages/weave/scxx/object.h:600: error: extra qualification ?py::object::? on member 

I tried upgrading Scipy_core to 0.3.2, the last release where I could
find a separate weave distribution, but now I just get coredumps
whenever weave tries to compile and run something, which is even
worse.

I could certainly generate extensive bug reports for these two cases,
but I suspect that weave has since been updated in many ways, so that
such an effort might not be worthwhile.  So I'd like to use the latest
weave distribution, but there doesn't seem to be a separate package
anymore.  I did try using the weave subdirectory of the current
package, as suggested in some of the documentation, but that results
in 'ImportError: No module named numpy.distutils.core'.  So it doesn't
look like weave can be used without the rest of SciPy right now.  (As
a side note, I'm reluctant to replace Numeric with NumPy in my
simulator, because the restricted license for the documentation, means
that I can't provide documentation of the array operations for my own
simulator!).

So, is it possible to use the latest version of weave without the rest
of SciPy?  weave seems very useful to the entire Python community,
regardless of whether they are doing scientific computing, so it seems
tragic if its use is limited because it cannot be extricated from
unrelated requirements for NumPy, LAPACK, ATLAS, etc.

Alternatively, is there some older version of a standalone weave that
at least works with GCC 4.1.x?  That's all we really need for right
now; without it our simulator won't work on recent Linux
distributions!

Thanks,

Jim








From oliphant at ee.byu.edu  Thu Oct  5 09:41:41 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Thu, 05 Oct 2006 07:41:41 -0600
Subject: [SciPy-user] weave broken with GCC 4.1.x
In-Reply-To: <17701.2702.582663.583713@lodestar.inf.ed.ac.uk>
References: <17701.2702.582663.583713@lodestar.inf.ed.ac.uk>
Message-ID: <45250B95.1020908@ee.byu.edu>

James A. Bednar wrote:

>Hi all,
>
>I've looked in the mailing-list archives and Trac for an answer to
>this question, but couldn't find anything relevant:
>
>- Is there a standalone version of weave (not requiring the rest of
>  SciPy) that works with GCC 4.1.x?
>  
>

Just check weave out from svn by itself and install it using

python setup.py install

This should work.

-Travis



From jbednar at inf.ed.ac.uk  Thu Oct  5 09:48:42 2006
From: jbednar at inf.ed.ac.uk (James A. Bednar)
Date: Thu, 5 Oct 2006 14:48:42 +0100
Subject: [SciPy-user] weave broken with GCC 4.1.x
In-Reply-To: <45250B95.1020908@ee.byu.edu>
References: <17701.2702.582663.583713@lodestar.inf.ed.ac.uk>
	<45250B95.1020908@ee.byu.edu>
Message-ID: <17701.3386.777308.640011@lodestar.inf.ed.ac.uk>

|  From: Travis Oliphant
|  Date: Oct  5 07:41:41 2006 -0600
|  
|  James A. Bednar wrote:
|  
|  >Hi all,
|  >
|  >I've looked in the mailing-list archives and Trac for an answer to
|  >this question, but couldn't find anything relevant:
|  >
|  >- Is there a standalone version of weave (not requiring the rest of
|  >  SciPy) that works with GCC 4.1.x?
|  >  
|  >
|  
|  Just check weave out from svn by itself and install it using
|  
|  python setup.py install
|  
|  This should work.

Thanks for the quick reply!  However, that won't work unless you have
numpy installed already:

  $ svn co http://svn.scipy.org/svn/scipy/trunk/Lib/weave weave
  A    weave/converters.py

  ...

  A    weave/examples/vq.py
  Checked out revision 2241.
  $ cd weave/
  $/weave> named numpy.distutils.core
  $/weave> python setup.py install
  Traceback (most recent call last):
    File "setup.py", line 14, in ?
      from numpy.distutils.core import setup
  ImportError: No module named numpy.distutils.core
  $

Jim


From ckkart at hoc.net  Thu Oct  5 11:03:33 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Fri, 06 Oct 2006 00:03:33 +0900
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <4524E209.404@iam.uni-stuttgart.de>
References: <20061005112059.7513cfa5@jakubik.ta3.sk>	<4524CEAD.2020804@hoc.net>	<20061005122133.6319c3da@jakubik.ta3.sk>	<4524DE49.9040105@hoc.net>
	<4524E209.404@iam.uni-stuttgart.de>
Message-ID: <45251EC5.3070107@hoc.net>

Nils Wagner wrote:
>> http://projects.scipy.org/mailman/listinfo/scipy-user
>>   
> Is gfortran really stable/reliable ?

I don't know. I once experienced some weirdness with gfortran 4.0.x but none so
far with 4.1.0, which ships with SuSE 10.1.
Christian


From coughlan at ski.org  Thu Oct  5 16:34:35 2006
From: coughlan at ski.org (James Coughlan)
Date: Thu, 05 Oct 2006 13:34:35 -0700
Subject: [SciPy-user] can't get weave to run
Message-ID: <45256C5B.6080803@ski.org>

When I try to run a simple weave example:

from scipy import weave
a=1
weave.inline('printf("%d",a);',['a'])

I get this error message:

Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "C:\PYTHON24\lib\site-packages\scipy\weave\inline_tools.py", line 
325, in inline
    results = attempt_function_call(code,local_dict,global_dict)
  File "C:\PYTHON24\lib\site-packages\scipy\weave\inline_tools.py", line 
375, in attempt_function_call
    function_list = function_catalog.get_functions(code,module_dir)
  File "C:\PYTHON24\lib\site-packages\scipy\weave\catalog.py", line 593, 
in get_functions
    function_list = self.get_cataloged_functions(code)
  File "C:\PYTHON24\lib\site-packages\scipy\weave\catalog.py", line 506, 
in get_cataloged_functions
    cat = get_catalog(path,mode)
  File "C:\PYTHON24\lib\site-packages\scipy\weave\catalog.py", line 275, 
in get_catalog
    if (dumb and os.path.exists(catalog_file+'.dat')) \
  File "C:\Python24\lib\ntpath.py", line 256, in exists
    st = os.stat(path)
TypeError: coercing to Unicode: need string or buffer, NoneType found

I am running Python Enthought Edition--Python 2.4.3 for Windows Enhanced 
Python Distribution, which includes SciPy version 0.5.0.2033. (Weave 
used to work on my computer, back when I was using Python 2.3.)

Does anybody have some suggestions?

Thanks,
James

PS When I run weave.test() I get some successes and some error messages:

  Found 16 tests for scipy.weave.slice_handler
  Found 0 tests for scipy.weave.c_spec
  Found 2 tests for scipy.weave.blitz_tools
building extensions here: 
c:\docume~1\james\locals~1\temp\James\python24_compiled\m0
  Found 1 tests for scipy.weave.ext_tools
  Found 74 tests for scipy.weave.size_check
  Found 9 tests for scipy.weave.build_tools
  Found 0 tests for scipy.weave.inline_tools
  Found 1 tests for scipy.weave.ast_tools
  Found 0 tests for scipy.weave.wx_spec
  Found 3 tests for scipy.weave.standard_array_spec
  Found 26 tests for scipy.weave.catalog
  Found 0 tests for __main__
.............................................................................................warning: 
specified build_dir '_bad_pa
th_' does not exist or is not writable. Trying default locations
.....warning: specified build_dir '_bad_path_' does not exist or is not 
writable. Trying default locations
................................removing 
'c:\docume~1\james\locals~1\temp\tmpgr3vnecat_test' (and everything 
under it)
error removing c:\docume~1\james\locals~1\temp\tmpgr3vnecat_test: 
c:\docume~1\james\locals~1\temp\tmpgr3vnecat_test\win3224compile
d_catalog: Permission denied
error removing c:\docume~1\james\locals~1\temp\tmpgr3vnecat_test: 
c:\docume~1\james\locals~1\temp\tmpgr3vnecat_test: Directory not
 empty
.removing 'c:\docume~1\james\locals~1\temp\tmpfw6kvscat_test' (and 
everything under it)
.
----------------------------------------------------------------------
Ran 132 tests in 3.264s

OK
<unittest.TextTestRunner object at 0x0116DBF0>



From ckkart at hoc.net  Fri Oct  6 00:39:01 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Fri, 06 Oct 2006 13:39:01 +0900
Subject: [SciPy-user] SuSE 10.1 installation problem
In-Reply-To: <20061005130915.02134612@jakubik.ta3.sk>
References: <20061005112059.7513cfa5@jakubik.ta3.sk>
	<4524CEAD.2020804@hoc.net>	<20061005122133.6319c3da@jakubik.ta3.sk>
	<4524DE49.9040105@hoc.net>	<4524E209.404@iam.uni-stuttgart.de>
	<20061005130915.02134612@jakubik.ta3.sk>
Message-ID: <4525DDE5.8010209@hoc.net>

Marian Jakubik wrote:
> Christian,
> 
> thanks a lot.. It works...!!!

Great.
Just in case: I've put latest numpy/scipy rpms, built on SuSE10.1, Intel Celeron
with blas/lapack here:
http://rosa.physik.tu-berlin.de/~semmel/suse10.1

Christian



From willemjagter at gmail.com  Fri Oct  6 03:22:22 2006
From: willemjagter at gmail.com (William Hunter)
Date: Fri, 6 Oct 2006 09:22:22 +0200
Subject: [SciPy-user] matplotlib: pylab doesn't import (backends problem)
Message-ID: <8b3894bc0610060022u4584a855q5798c08b6473b20d@mail.gmail.com>

These are installed:
scipy.__version__ = '0.5.1'
numpy.__version__  = '1.0rc1'
matplotlib.__version__ = '0.87.6'

My options in setup.py for matplotlib is set to build Agg and
GTKAgg ( = 1), the others all = 0. If I leave them at 'auto' as per
default, matplotlib doesn't build (?). I use Ubuntu Dapper - AMD64.

Here's what happens if I try to import pylab (in a new terminal):


In [1]: import pylab
---------------------------------------------------------------------------
exceptions.ImportError                               Traceback (most
recent call last)

/home/william/<ipython console>

/usr/lib/python2.4/site-packages/pylab.py
----> 1 from matplotlib.pylab import *

/usr/lib/python2.4/site-packages/matplotlib/pylab.py
    200
    201 from axes import Axes, PolarAxes
--> 202 import backends
    203 from cbook import flatten, is_string_like, exception_to_str, popd, \
    204      silent_list, iterable, enumerate

/usr/lib/python2.4/site-packages/matplotlib/backends/__init__.py
     52 # a hack to keep old versions of ipython working with mpl after bug
     53 # fix #1209354
     54 if 'IPython.Shell' in  sys.modules:
---> 55     new_figure_manager, draw_if_interactive, show = pylab_setup()
     56

/usr/lib/python2.4/site-packages/matplotlib/backends/__init__.py in
pylab_setup()
     21     backend_name = 'backend_'+backend.lower()
     22     backend_mod = __import__('matplotlib.backends.'+backend_name,
---> 23                              globals(),locals(),[backend_name])
     24
     25     # Things we pull in from all backends

/usr/lib/python2.4/site-packages/matplotlib/backends/backend_gtkagg.py
      8 from matplotlib.figure import Figure
      9 from backend_agg import FigureCanvasAgg
---> 10 from backend_gtk import gtk, FigureManagerGTK, FigureCanvasGTK,\
     11      show, draw_if_interactive,\
     12      error_msg_gtk, NavigationToolbar, PIXELS_PER_INCH,
backend_version, \

/usr/lib/python2.4/site-packages/matplotlib/backends/backend_gtk.py
     19 from matplotlib.backend_bases import RendererBase,
GraphicsContextBase, \
     20      FigureManagerBase, FigureCanvasBase, NavigationToolbar2, cursors
---> 21 from matplotlib.backends.backend_gdk import RendererGDK, FigureCanvasGDK
     22 from matplotlib.cbook import is_string_like, enumerate
     23 from matplotlib.colors import colorConverter

/usr/lib/python2.4/site-packages/matplotlib/backends/backend_gdk.py
     33     from matplotlib.backends._nc_backend_gdk import
pixbuf_get_pixels_array
     34 else:
---> 35     from matplotlib.backends._ns_backend_gdk import
pixbuf_get_pixels_array
     36
     37

ImportError: No module named _ns_backend_gdk


I had matplotlib 0.87.4 running like a brand new Mercedes-Benz
previously, with older numpy/scipy. Any ideas how to fix this?
--
wh


From lorrmann at physik.uni-wuerzburg.de  Fri Oct  6 03:47:09 2006
From: lorrmann at physik.uni-wuerzburg.de (Volker Lorrmann)
Date: Fri, 06 Oct 2006 09:47:09 +0200
Subject: [SciPy-user] Solving Two boundary value problems with Python/Scipy
In-Reply-To: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
Message-ID: <452609FD.4080702@physik.uni-wuerzburg.de>

Hi list,

i?m going to write a simulation, in which it would be neccessary to 
solve an boundary value ode.
My question is, would it be possible to solve such ode?s with any solver 
in scipy? Otherwise i have to choose another language for this 
simulation (scilab,rlab).

Many thanks

Volker

-- 
-----------------------
Volker Lorrmann
Universit?t W?rzburg
Experimentelle Physik 6
Am Hubland
97074 Wuerzburg
Germany
Tel: +49 931 888 5770
volker.lorrmann at physik.uni-wuerzburg.de




From hasslerjc at adelphia.net  Fri Oct  6 09:32:36 2006
From: hasslerjc at adelphia.net (John Hassler)
Date: Fri, 06 Oct 2006 09:32:36 -0400
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <452609FD.4080702@physik.uni-wuerzburg.de>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
Message-ID: <45265AF4.5030200@adelphia.net>

I don't think that there's a function specifically for boundary value 
ode problems in SciPy, but it is pretty simple to combine an ode solver 
with a zero finder to use the "shooting method."  I'm not familiar with 
how rlab or Matlab does it, but the Scilab "bvode" uses a finite 
difference method.  If the problem isn't too complex, the shooting 
method is easy to set up, and works as well as the finite difference 
method.  (In my vast experience ... well, ok, two applications ... the 
shooting method was more forgiving and less brittle than the finite 
difference method.)

What sort of bvp do you have?

john

Volker Lorrmann wrote:
> Hi list,
>
> i?m going to write a simulation, in which it would be neccessary to 
> solve an boundary value ode.
> My question is, would it be possible to solve such ode?s with any solver 
> in scipy? Otherwise i have to choose another language for this 
> simulation (scilab,rlab).
>
> Many thanks
>
> Volker
>
>   


From jdhunter at ace.bsd.uchicago.edu  Fri Oct  6 09:56:34 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Fri, 06 Oct 2006 08:56:34 -0500
Subject: [SciPy-user] matplotlib: pylab doesn't import (backends problem)
In-Reply-To: <8b3894bc0610060022u4584a855q5798c08b6473b20d@mail.gmail.com>
	("William Hunter"'s message of "Fri, 6 Oct 2006 09:22:22 +0200")
References: <8b3894bc0610060022u4584a855q5798c08b6473b20d@mail.gmail.com>
Message-ID: <87r6xl1ral.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "William" == William Hunter <willemjagter at gmail.com> writes:

    William> These are installed: scipy.__version__ = '0.5.1'
    William> numpy.__version__ = '1.0rc1' matplotlib.__version__ =
    William> '0.87.6'

    William> My options in setup.py for matplotlib is set to build Agg
    William> and GTKAgg ( = 1), the others all = 0. If I leave them at
    William> 'auto' as per default, matplotlib doesn't build (?). I
    William> use Ubuntu Dapper - AMD64.

    William> Here's what happens if I try to import pylab (in a new
    William> terminal):


    William> /usr/lib/python2.4/site-packages/matplotlib/backends/backend_gdk.py
    William> 33 from matplotlib.backends._nc_backend_gdk import
    William> pixbuf_get_pixels_array 34 else:
    ---> 35 from matplotlib.backends._ns_backend_gdk import
    William> pixbuf_get_pixels_array 36 37

    William> ImportError: No module named _ns_backend_gdk


This question is better addressed on matplotlib-users....

It looks like either you do not have numpy or pygtk properly
installed.  Note also you need to eh gtk-devel packages to compile the
gtk extensions, as described at

   http://matplotlib.sourceforge.net/installing.html

As a quick check for numpy and pygtk, you can do

>>> import numpy
>>> import gtk

but you'll still need the gtk-devel packages

If it still doesn't work, 

> rm -rf build
> python setup.py build >& build.out

and post output to the matplotlib-devel list.


JDH


From willemjagter at gmail.com  Fri Oct  6 10:03:57 2006
From: willemjagter at gmail.com (William Hunter)
Date: Fri, 6 Oct 2006 16:03:57 +0200
Subject: [SciPy-user] matplotlib: pylab doesn't import (backends problem)
In-Reply-To: <87r6xl1ral.fsf@peds-pc311.bsd.uchicago.edu>
References: <8b3894bc0610060022u4584a855q5798c08b6473b20d@mail.gmail.com>
	<87r6xl1ral.fsf@peds-pc311.bsd.uchicago.edu>
Message-ID: <8b3894bc0610060703m2d3c1136g60c918644c706685@mail.gmail.com>

> This question is better addressed on matplotlib-users....

OK, I'll post there, thanks.


From peridot.faceted at gmail.com  Fri Oct  6 11:12:55 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Fri, 6 Oct 2006 11:12:55 -0400
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <45265AF4.5030200@adelphia.net>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
	<45265AF4.5030200@adelphia.net>
Message-ID: <ce557a360610060812t1d36c5edvd73f6acaf8059408@mail.gmail.com>

On 06/10/06, John Hassler <hasslerjc at adelphia.net> wrote:
> I don't think that there's a function specifically for boundary value
> ode problems in SciPy, but it is pretty simple to combine an ode solver
> with a zero finder to use the "shooting method."  I'm not familiar with
> how rlab or Matlab does it, but the Scilab "bvode" uses a finite
> difference method.  If the problem isn't too complex, the shooting
> method is easy to set up, and works as well as the finite difference
> method.  (In my vast experience ... well, ok, two applications ... the
> shooting method was more forgiving and less brittle than the finite
> difference method.)
>
> What sort of bvp do you have?
>
> john

It seems to me it would be useful for scipy to have an "odetools"
package, providing convenience features on top of our existing ODE
solvers (as well as a better fortran ODE solver, namely lsodar, but
that's beside the point).

Features could include:
* Implementation of the shooting method
* class ODESolution, which provides an interpolated function object
* An implementation (necessarily slow and limited) of the finite
difference method
* Tools for working with linear ODEs (generate a complete set of solutions, say)
* Tools for solving eigenvalue problems

Any other suggestions?

I've started thinking about how to do this, and written some prototype
code, but it would be a moderately big project. It should probably
mostly in python, because I imagine people will need to extend and
modify all the classes for their particular problems.

A. M. Archibald


From rclewley at cam.cornell.edu  Fri Oct  6 12:19:18 2006
From: rclewley at cam.cornell.edu (Robert Clewley)
Date: Fri, 6 Oct 2006 12:19:18 -0400 (EDT)
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <ce557a360610060812t1d36c5edvd73f6acaf8059408@mail.gmail.com>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
	<45265AF4.5030200@adelphia.net>
	<ce557a360610060812t1d36c5edvd73f6acaf8059408@mail.gmail.com>
Message-ID: <Pine.LNX.4.64.0610061206371.31682@kilburn.cam.cornell.edu>

> It seems to me it would be useful for scipy to have an "odetools"
> package, providing convenience features on top of our existing ODE
> solvers (as well as a better fortran ODE solver, namely lsodar, but
> that's beside the point).

Sure, and I've said before that the SciPy powers-that-be are welcome to 
use any parts of our PyDSTool package as the basis of such a package. 
e.g., our SWIG-based interfaces to two great integrators (Dopri and 
Radau). Our interface includes events at the C-level and external inputs 
interpolated from arrays. Our ODEGenerator classes provide a lot of 
convenience features on top of the solvers (including the existing Scipy 
VODE solver).

>
> Features could include:
> * Implementation of the shooting method

Yes, that would be useful.

> * class ODESolution, which provides an interpolated function object

That's exactly what our Variable and Trajectory classes do, built over
scipy's interp1d.


> * An implementation (necessarily slow and limited) of the finite
> difference method

Our diff function provides that with various options for 
functions from R^N -> R^M. Here's the signature and docstring
from PyDSTool/common.py:


def diff(func, x0, vars=None, axes=None, dir=1, dx=None):
     """Numerical 1st derivative of R^N -> R^M function about x0 by finite
     differences.

     dir=1 uses finite forward difference.
     dir=-1 uses finite backward difference.
     List valued dx rescales finite differencing in each axis separately.
     vars argument specifies which elements of x0 are to be treated as
       variables for the purposes of taking the Jacobian.
     If axes argument is unused or set to be all axes, the Jacobian of the
       function evaluated at x0 with respect to the variables is returned,
       otherwise a sub-matrix of it is returned.
     If dx is not given an appropriate step size is chosen (proportional to
       sqrt(machine precision)).
     """


> * Tools for working with linear ODEs (generate a complete set of solutions, say)
> * Tools for solving eigenvalue problems
>
> Any other suggestions?

A set of phase plane tools, like finding nullclines, fixed points, 
stability.... I have a whole bunch of code working for this 
that will end up in the next release of PyDSTool (for Scipy 0.5.1, 
finally) and I'll be adding a few additional features like calculating 
stability of fixed points.

The port to Numpy and new Scipy is will be done in the next few weeks so 
code will be available for people to clean up to their liking for use in 
SciPy.

-Rob


From peridot.faceted at gmail.com  Fri Oct  6 16:20:55 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Fri, 6 Oct 2006 16:20:55 -0400
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <Pine.LNX.4.64.0610061206371.31682@kilburn.cam.cornell.edu>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
	<45265AF4.5030200@adelphia.net>
	<ce557a360610060812t1d36c5edvd73f6acaf8059408@mail.gmail.com>
	<Pine.LNX.4.64.0610061206371.31682@kilburn.cam.cornell.edu>
Message-ID: <ce557a360610061320s5e804e0ax87a3eb4af93c02ba@mail.gmail.com>

On 06/10/06, Robert Clewley <rclewley at cam.cornell.edu> wrote:
> > It seems to me it would be useful for scipy to have an "odetools"
> > package, providing convenience features on top of our existing ODE
> > solvers (as well as a better fortran ODE solver, namely lsodar, but
> > that's beside the point).
>
> Sure, and I've said before that the SciPy powers-that-be are welcome to
> use any parts of our PyDSTool package as the basis of such a package.
> e.g., our SWIG-based interfaces to two great integrators (Dopri and
> Radau). Our interface includes events at the C-level and external inputs
> interpolated from arrays. Our ODEGenerator classes provide a lot of
> convenience features on top of the solvers (including the existing Scipy
> VODE solver).

I confess I hadn't really examined PyDSTool very closely; it sounds
like it addresses exactly what I was suggesting. Perhaps there's no
need for such a scipy package, if people can just use PyDSTool. Do you
think there is any point in moving some generic functionality into
scipy? I'd at least like to have an ODE solver that can handle
constraints on the dependent variable.

> > * class ODESolution, which provides an interpolated function object
>
> That's exactly what our Variable and Trajectory classes do, built over
> scipy's interp1d.

Wait, interp1d is linear-interpolation-only! I had in mind a
higher-order spline that took into account not the bending energy at
each knot but the known derivatives at each point (and possibly the
order used internally by the integrator) to obtain a solution that
followed the real solution even more closely at little extra cost.

> > * An implementation (necessarily slow and limited) of the finite
> > difference method
>
> Our diff function provides that with various options for
> functions from R^N -> R^M. Here's the signature and docstring
> from PyDSTool/common.py:

Er, I suppose I meant the relaxation method of solving boundary-value problems.

> A set of phase plane tools, like finding nullclines, fixed points,
> stability.... I have a whole bunch of code working for this
> that will end up in the next release of PyDSTool (for Scipy 0.5.1,
> finally) and I'll be adding a few additional features like calculating
> stability of fixed points.

These more advanced applications, particularly if you've got code in
progress, maybe do belong in PyDSTool; I had in mind just some
relatively basic things (that I have needed).

> The port to Numpy and new Scipy is will be done in the next few weeks so
> code will be available for people to clean up to their liking for use in
> SciPy.

I'll take a closer look at what PyDSTool can do.

Thanks, and I apologize for not having taken a closer look at it
before making my suggestions,

A. M. Archibald


From rclewley at cam.cornell.edu  Fri Oct  6 16:42:35 2006
From: rclewley at cam.cornell.edu (Robert Clewley)
Date: Fri, 6 Oct 2006 16:42:35 -0400 (EDT)
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <ce557a360610061320s5e804e0ax87a3eb4af93c02ba@mail.gmail.com>
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
	<45265AF4.5030200@adelphia.net>
	<ce557a360610060812t1d36c5edvd73f6acaf8059408@mail.gmail.com>
	<Pine.LNX.4.64.0610061206371.31682@kilburn.cam.cornell.edu>
	<ce557a360610061320s5e804e0ax87a3eb4af93c02ba@mail.gmail.com>
Message-ID: <Pine.LNX.4.64.0610061622540.28686@moose.cam.cornell.edu>

> I confess I hadn't really examined PyDSTool very closely; it sounds
> like it addresses exactly what I was suggesting. Perhaps there's no
> need for such a scipy package, if people can just use PyDSTool. Do you
> think there is any point in moving some generic functionality into
> scipy?

Not necessarily, and besides I don't know that my code is really of
high enough quality for it to belong in there. I don't have the
time to completely rewrite it with unit tests, etc., although it *does*
work reliably on the tests for which we can compare output from 
other packages, for instance.

However, my guess is that there's sufficient general applicability of
our numeric Interval, Point and Pointset classes (and possibly our Curve 
a.k.a. Trajectory classes) for other scientific applications that might
make it worthwhile for those to be incorporated, at least.

> I'd at least like to have an ODE solver that can handle
> constraints on the dependent variable.

Indeed, that's what drove us to interfacing with Radau, which does that 
nicely.

> Wait, interp1d is linear-interpolation-only! I had in mind a
> higher-order spline that took into account not the bending energy at
> each knot but the known derivatives at each point (and possibly the
> order used internally by the integrator) to obtain a solution that
> followed the real solution even more closely at little extra cost.

Absolutely. From what I remember, at the time that I wrote those classes I 
there was only that 1d interpolator around in scipy that suited our needs. 
Well, anyway, the classes are not really hardwired to it and other 
interpolators could be put in very easily. I plan to make the option more 
accessible with our Numpy-based release. For everyday "normal" purposes 
just using small enough time steps in the integration makes linear 
interpolation fine. Plus there's already a "refine" option in the C 
integrators which uses high-order interpolation to provide a fine mesh
before it reaches the interpolator.

>> Our diff function provides that with various options for
>> functions from R^N -> R^M. Here's the signature and docstring
>> from PyDSTool/common.py:
>
> Er, I suppose I meant the relaxation method of solving boundary-value problems.

Ah, right... yes. Sorry, I was asleep at the wheel when I included that!

> Thanks, and I apologize for not having taken a closer look at it
> before making my suggestions,

No need to apologise. Exploring the vast range of what's out there and
discussing your ideas for new features is what these lists are for.
You've encouraged me to write some classes to help PyDSTool users do BVPs!

-Rob


From pav at iki.fi  Fri Oct  6 19:55:53 2006
From: pav at iki.fi (Pauli Virtanen)
Date: Sat, 07 Oct 2006 02:55:53 +0300
Subject: [SciPy-user] COLNEW the BVP solver for scipy [Was: Solving Two
	boundary value problems ...]
References: <mailman.24999.1160039953.2761.scipy-user@scipy.org>
	<452609FD.4080702@physik.uni-wuerzburg.de>
	<45265AF4.5030200@adelphia.net>
Message-ID: <eg6qe9$c9t$1@sea.gmane.org>

John Hassler wrote:
> I don't think that there's a function specifically for boundary value
> ode problems in SciPy, but it is pretty simple to combine an ode solver
> with a zero finder to use the "shooting method."  I'm not familiar with
> how rlab or Matlab does it, but the Scilab "bvode" uses a finite
> difference method.  If the problem isn't too complex, the shooting
> method is easy to set up, and works as well as the finite difference
> method.  (In my vast experience ... well, ok, two applications ... the
> shooting method was more forgiving and less brittle than the finite
> difference method.)

Hi all,

I've recently written a Python wrapper for a modified version of the COLNEW
bvp solver (Scilab's bvode is also based on COLNEW). The code can be found
from::

    http://www.elisanet.fi/ptvirtan/bvp/

In addition to wrapping COLNEW, the package has the following features

* I vectorized COLNEW over mesh points. (Vectorized code is approx 10x
  faster than non-vectorized, at least in my small tests.)
* There are simple estimators for the Jacobians so that they need not be
  explicitly provided. They appear to work well despite their simplicity.

This is still in development -- the code has so far not been in real use.
However, I made a test suite of the test problems for COLSYS, COLNEW and
MUS plus some others, and the code solves them correctly.

About usage and syntax: For example solving Bessel's equation plus another
one with some boundary conditions,

    u''(x) = -u'(x) / x + (nu**2/x**2 - 1) * u(x)        for 1 <= x <= 10
    v'(x) = x**(nu+1) * u(x)                             for 1 <= x <= 10

    u(1)  = J_{nu}(1)
    u(10) = J_{nu}(10)
    v(5)  = 5**(nu+1) * J_{nu+1}(5)

looks like this (yes, it is vectorized)

    import scipy as N
    N.pkgload('special')
    import bvp

    nu = 3.4123
    degrees = [2, 1]

    def fsub(x, z):
        """The equations"""
        u, du, v = z     # it's neat to name the variables
        return N.array([-du/x + (nu**2/x**2 - 1)*u, x**(nu+1) * u])

    def gsub(z):
        """The boundary conditions"""
        u, du, v = z
        return N.array([u[0] - N.special.jv(nu,   1),
                        v[1] - 5**(nu+1) * N.special.jv(nu+1, 5),
                        u[2] - N.special.jv(nu,   10)])

    boundary_points = [1, 5, 10]
    tol = [1e-5, 0, 1e-5]

    solution = bvp.colnew.solve(
        boundary_points, degrees, fsub, gsub,
        is_linear=True, tolerances=tol,
        vectorized=True, maximum_mesh_size=300)

    solution_values = solution([2,3,4,5,6])

I hope this package will be of some use to people. I'd be interested to hear
if it proves (un)useful or any other suggestions the people on the list
might have.

        Pauli Virtanen




From R.Springuel at umit.maine.edu  Fri Oct  6 20:21:23 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Fri, 06 Oct 2006 20:21:23 -0400
Subject: [SciPy-user] Installation problems on Mac OS X
Message-ID: <4526F303.6000301@umit.maine.edu>

I just migrated to a Mac OS X environment and am trying to install numpy 
from the source files (a first for this former Windows user).  However, 
when I do so, I get the following error:

Running from numpy source directory.
F2PY Version 2_3198
blas_opt_info:
  FOUND:
    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
    define_macros = [('NO_ATLAS_INFO', 3)]
    extra_compile_args = ['-faltivec', 
'-I/System/Library/Frameworks/vecLib.framework/Headers']

lapack_opt_info:
  FOUND:
    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
    define_macros = [('NO_ATLAS_INFO', 3)]
    extra_compile_args = ['-faltivec']

running install
running build
running config_fc
running build_src
building py_modules sources
building extension "numpy.core.multiarray" sources
Generating build/src.macosx-10.3-fat-2.5/numpy/core/config.h
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable g77
Could not locate executable f77
Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize Gnu95FCompiler
customize G95FCompiler
customize GnuFCompiler
customize Gnu95FCompiler
customize NAGFCompiler
customize NAGFCompiler using config
C compiler: gcc -arch ppc -arch i386 -isysroot 
/Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double 
-no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: 
'-I/Library/Frameworks/Python.framework/Versions/2.5/include/python2.5 
-Inumpy/core/src -Inumpy/core/include 
-I/Library/Frameworks/Python.framework/Versions/2.5/include/python2.5 -c'
gcc: _configtest.c
sh: line 1: gcc: command not found
sh: line 1: gcc: command not found
failure.
removing: _configtest.c _configtest.o
numpy/core/setup.py:50: DeprecationWarning: raising a string exception 
is deprecated
  raise "ERROR: Failed to test configuration"
Traceback (most recent call last):
  File "setup.py", line 89, in <module>
    setup_package()
  File "setup.py", line 82, in setup_package
    configuration=configuration )
  File "/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/core.py", line 
174, in setup
    return old_setup(**new_attr)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/core.py", 
line 151, in setup
    dist.run_commands()
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/dist.py", 
line 974, in run_commands
    self.run_command(cmd)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/dist.py", 
line 994, in run_command
    cmd_obj.run()
  File 
"/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/command/install.py", 
line 16, in run
    r = old_install.run(self)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/command/install.py", 
line 506, in run
    self.run_command('build')
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/cmd.py", 
line 333, in run_command
    self.distribution.run_command(command)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/dist.py", 
line 994, in run_command
    cmd_obj.run()
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/command/build.py", 
line 112, in run
    self.run_command(cmd_name)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/cmd.py", 
line 333, in run_command
    self.distribution.run_command(command)
  File 
"/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/distutils/dist.py", 
line 994, in run_command
    cmd_obj.run()
  File 
"/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/command/build_src.py", 
line 87, in run
    self.build_sources()
  File 
"/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/command/build_src.py", 
line 106, in build_sources
    self.build_extension_sources(ext)
  File 
"/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/command/build_src.py", 
line 212, in build_extension_sources
    sources = self.generate_sources(sources, ext)
  File 
"/Users/RPS/Desktop/numpy-1.0rc1/numpy/distutils/command/build_src.py", 
line 270, in generate_sources
    source = func(extension, build_dir)
  File "numpy/core/setup.py", line 50, in generate_config_h
    raise "ERROR: Failed to test configuration"
ERROR: Failed to test configuration

Having not done a source file installation before, I don't know what to 
make of this.  Can anybody help me out?

-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm



From oliphant at ee.byu.edu  Fri Oct  6 21:24:51 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Fri, 06 Oct 2006 19:24:51 -0600
Subject: [SciPy-user] Installation problems on Mac OS X
In-Reply-To: <4526F303.6000301@umit.maine.edu>
References: <4526F303.6000301@umit.maine.edu>
Message-ID: <452701E3.8090403@ee.byu.edu>

R. Padraic Springuel wrote:

>I just migrated to a Mac OS X environment and am trying to install numpy 
>from the source files (a first for this former Windows user).  However, 
>when I do so, I get the following error:
>
>Running from numpy source directory.
>F2PY Version 2_3198
>blas_opt_info:
>  FOUND:
>    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
>    define_macros = [('NO_ATLAS_INFO', 3)]
>    extra_compile_args = ['-faltivec', 
>'-I/System/Library/Frameworks/vecLib.framework/Headers']
>
>lapack_opt_info:
>  FOUND:
>    extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
>    define_macros = [('NO_ATLAS_INFO', 3)]
>    extra_compile_args = ['-faltivec']
>
>running install
>running build
>running config_fc
>running build_src
>building py_modules sources
>building extension "numpy.core.multiarray" sources
>Generating build/src.macosx-10.3-fat-2.5/numpy/core/config.h
>customize NAGFCompiler
>customize AbsoftFCompiler
>customize IbmFCompiler
>Could not locate executable g77
>Could not locate executable f77
>Could not locate executable gfortran
>Could not locate executable f95
>customize GnuFCompiler
>customize Gnu95FCompiler
>customize G95FCompiler
>customize GnuFCompiler
>customize Gnu95FCompiler
>customize NAGFCompiler
>customize NAGFCompiler using config
>C compiler: gcc -arch ppc -arch i386 -isysroot 
>/Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double 
>-no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3
>
>compile options: 
>'-I/Library/Frameworks/Python.framework/Versions/2.5/include/python2.5 
>-Inumpy/core/src -Inumpy/core/include 
>-I/Library/Frameworks/Python.framework/Versions/2.5/include/python2.5 -c'
>gcc: _configtest.c
>sh: line 1: gcc: command not found
>sh: line 1: gcc: command not found
>failure.
>
>  
>

[snip]

>Having not done a source file installation before, I don't know what to 
>make of this.  Can anybody help me out?
>
>  
>
The important information of the error is just above the [snip].  Do you 
have a compiler installed?

-Travis






From lorrmann at physik.uni-wuerzburg.de  Sat Oct  7 07:12:18 2006
From: lorrmann at physik.uni-wuerzburg.de (Volker Lorrmann)
Date: Sat, 07 Oct 2006 13:12:18 +0200
Subject: [SciPy-user] Solving Two boundary value problems with
	Python/Scipy
In-Reply-To: <mailman.12.1160154005.6128.scipy-user@scipy.org>
References: <mailman.12.1160154005.6128.scipy-user@scipy.org>
Message-ID: <45278B92.40801@physik.uni-wuerzburg.de>

Hi John,

i?ve already found less information about the shooting method. Do you 
have some more informations for me? Than i think i?ll give it a try.
I?ll try now to describe the bvp. The ode describes  "electrone/hole 
density" in the conducting and  valence band of a polymer thin film. The 
boundary values are, that the density on the front and back have to be 
zero.

Volker
>
>
> I don't think that there's a function specifically for boundary value 
> ode problems in SciPy, but it is pretty simple to combine an ode 
> solver with a zero finder to use the "shooting method."  I'm not 
> familiar with how rlab or Matlab does it, but the Scilab "bvode" uses 
> a finite difference method.  If the problem isn't too complex, the 
> shooting method is easy to set up, and works as well as the finite 
> difference method.  (In my vast experience ... well, ok, two 
> applications ... the shooting method was more forgiving and less 
> brittle than the finite difference method.)
>
> What sort of bvp do you have?
>
> john
>
> Volker Lorrmann wrote:
>> Hi list,
>>
>> i?m going to write a simulation, in which it would be neccessary to 
>> solve an boundary value ode.
>> My question is, would it be possible to solve such ode?s with any 
>> solver in scipy? Otherwise i have to choose another language for this 
>> simulation (scilab,rlab).
>>
>> Many thanks
>>
>> Volker
>>
>>   



From hasslerjc at adelphia.net  Sat Oct  7 08:59:40 2006
From: hasslerjc at adelphia.net (John Hassler)
Date: Sat, 07 Oct 2006 08:59:40 -0400
Subject: [SciPy-user] Solving Two boundary value problems
	with	Python/Scipy
In-Reply-To: <45278B92.40801@physik.uni-wuerzburg.de>
References: <mailman.12.1160154005.6128.scipy-user@scipy.org>
	<45278B92.40801@physik.uni-wuerzburg.de>
Message-ID: <4527A4BC.2030305@adelphia.net>

An HTML attachment was scrubbed...
URL: <http://mail.scipy.org/pipermail/scipy-user/attachments/20061007/de98c680/attachment.html>

From lorrmann at physik.uni-wuerzburg.de  Sat Oct  7 10:04:00 2006
From: lorrmann at physik.uni-wuerzburg.de (Volker Lorrmann)
Date: Sat, 07 Oct 2006 16:04:00 +0200
Subject: [SciPy-user] COLNEW the BVP solver for scipy [Was: Solving Two
 boundary value problems ...]
In-Reply-To: <mailman.25970.1160225998.2761.scipy-user@scipy.org>
References: <mailman.25970.1160225998.2761.scipy-user@scipy.org>
Message-ID: <4527B3D0.6090401@physik.uni-wuerzburg.de>

That looks really amazing. Exactly what i?ve been looking for. Thanks!!

Volker
> Hi all,
>
> I've recently written a Python wrapper for a modified version of the COLNEW
> bvp solver (Scilab's bvode is also based on COLNEW). The code can be found
> from::
>
>     http://www.elisanet.fi/ptvirtan/bvp/
>
> In addition to wrapping COLNEW, the package has the following features
>
> * I vectorized COLNEW over mesh points. (Vectorized code is approx 10x
>   faster than non-vectorized, at least in my small tests.)
> * There are simple estimators for the Jacobians so that they need not be
>   explicitly provided. They appear to work well despite their simplicity.
>
> This is still in development -- the code has so far not been in real use.
> However, I made a test suite of the test problems for COLSYS, COLNEW and
> MUS plus some others, and the code solves them correctly.
>
> About usage and syntax: For example solving Bessel's equation plus another
> one with some boundary conditions,
>
>     u''(x) = -u'(x) / x + (nu**2/x**2 - 1) * u(x)        for 1 <= x <= 10
>     v'(x) = x**(nu+1) * u(x)                             for 1 <= x <= 10
>
>     u(1)  = J_{nu}(1)
>     u(10) = J_{nu}(10)
>     v(5)  = 5**(nu+1) * J_{nu+1}(5)
>
> looks like this (yes, it is vectorized)
>
>     import scipy as N
>     N.pkgload('special')
>     import bvp
>
>     nu = 3.4123
>     degrees = [2, 1]
>
>     def fsub(x, z):
>         """The equations"""
>         u, du, v = z     # it's neat to name the variables
>         return N.array([-du/x + (nu**2/x**2 - 1)*u, x**(nu+1) * u])
>
>     def gsub(z):
>         """The boundary conditions"""
>         u, du, v = z
>         return N.array([u[0] - N.special.jv(nu,   1),
>                         v[1] - 5**(nu+1) * N.special.jv(nu+1, 5),
>                         u[2] - N.special.jv(nu,   10)])
>
>     boundary_points = [1, 5, 10]
>     tol = [1e-5, 0, 1e-5]
>
>     solution = bvp.colnew.solve(
>         boundary_points, degrees, fsub, gsub,
>         is_linear=True, tolerances=tol,
>         vectorized=True, maximum_mesh_size=300)
>
>     solution_values = solution([2,3,4,5,6])
>
> I hope this package will be of some use to people. I'd be interested to hear
> if it proves (un)useful or any other suggestions the people on the list
> might have.
>
>         Pauli Virtanen



From nicolist at limare.net  Sat Oct  7 13:20:15 2006
From: nicolist at limare.net (Nicolas Limare)
Date: Sat, 07 Oct 2006 19:20:15 +0200
Subject: [SciPy-user] the scipy roundup bug tracker should be closed
Message-ID: <eg8nkf$u01$1@sea.gmane.org>

Hi,

The scipy tracker for the roundup bts on scipy.net is only used by
spammers. As all the bugs are now handled through trac, this tracker
should be closed.

http://www.scipy.net/roundup/scipy/

-- 
Nico



From R.Springuel at umit.maine.edu  Sat Oct  7 17:24:36 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Sat, 07 Oct 2006 17:24:36 -0400
Subject: [SciPy-user] Installation problems on Mac OS X
In-Reply-To: <fc.3b9aca00637c4c4b3b9aca004b4c7c63.2c794417@umit.maine.edu>
References: <fc.3b9aca00637c4c4b3b9aca004b4c7c63.2c794417@umit.maine.edu>
Message-ID: <45281B14.6050706@umit.maine.edu>

It's a brand new MacBook, so I'd only have a compiler if it came with 
one preinstalled.  Given the error, I'm guessing that it didn't.  So 
what kind of compiler should I be looking to get and where from?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From lists.steve at arachnedesign.net  Sat Oct  7 18:53:24 2006
From: lists.steve at arachnedesign.net (Steve Lianoglou)
Date: Sat, 7 Oct 2006 18:53:24 -0400
Subject: [SciPy-user] Installation problems on Mac OS X
In-Reply-To: <45281B14.6050706@umit.maine.edu>
References: <fc.3b9aca00637c4c4b3b9aca004b4c7c63.2c794417@umit.maine.edu>
	<45281B14.6050706@umit.maine.edu>
Message-ID: <7CAC9179-1263-494E-BE15-72A4F012ACD0@arachnedesign.net>

Hi,


> It's a brand new MacBook, so I'd only have a compiler if it came with
> one preinstalled.  Given the error, I'm guessing that it didn't.  So
> what kind of compiler should I be looking to get and where from?
>

In the install discs, you should be able to find a way to install  
XCode/Developer Tools.

If you can't find the installer, you can d/l it from here.
http://developer.apple.com/tools/xcode/

Install those and you'll get gcc, etc. You may be able to install gcc  
w/o XCode, but I'm not sure.

Or .. you can install MacPorts (http://macports.org) and then install  
gcc from there.

-steve


ps - I had mistakenly sent this email earlier from the wrong email  
address, so it didn't get through, sorry to list mods :-)



From gnchen at cortechs.net  Sat Oct  7 20:37:23 2006
From: gnchen at cortechs.net (Gennan Chen)
Date: Sat, 7 Oct 2006 17:37:23 -0700
Subject: [SciPy-user] matplotlib and python 2.5 on Intel OS X
Message-ID: <B415F8F2-2CDC-47A0-A343-0515B2B4A62C@cortechs.net>

Hi!

I am like to compile matplotlib for ython 2.5 on Intel OSX.  
Compilation went fine. But I got segmented faults when I tried to run  
some test scripts. Anyone ever successfully built it on python 2.5??  
If did, can you give me some hints on setup.py?

Gen


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From cygnusx1 at mac.com  Sat Oct  7 23:31:11 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Sat, 7 Oct 2006 23:31:11 -0400
Subject: [SciPy-user] Building scipy 0.5.1 on Mac OS 10.4.7
Message-ID: <3F5A6101-0BE1-4D9B-97C7-46BC26226886@mac.com>

I've finally achieved a successful build of scipy 0.5.1 &  
numpy-1.0rc1 on Mac OS 10.4.7 PPC.  I was guided by the instructions at

http://www.scipy.org/Installing_SciPy/Mac_OS_X

However, there were some confusing parts in the description, for  
example:

- I switched to gcc 3.3 to build fftw but had to switch back to gcc  
4.0 to build numpy and later.
- I had to set the link to libgcc.a just prior to the actual scipy  
build.
- All numpy tests passed, but two scipy tests failed.

Everything built okay, but when I tried to run a program that called  
scipy.integrate, it failed with:

     import scipy.integrate
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/integrate/__init__.py", line 9, in ?
     from quadrature import *
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/integrate/quadrature.py", line 8, in ?
     from scipy.special.orthogonal import p_roots
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/special/__init__.py", line 8, in ?
     from basic import *
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/special/basic.py", line 8, in ?
     from _cephes import *
ImportError: Failure linking new module: /Library/Frameworks/ 
Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/ 
special/_cephes.so: Symbol not found: _printf$LDBLStub
   Referenced from: /Library/Frameworks/Python.framework/Versions/2.4/ 
lib/python2.4/site-packages/scipy/special/_cephes.so
   Expected in: dynamic lookup

Suggestions?

Tom
========
GCC/G77
% sudo tar -xvf g77v3.4-bin.tar -C /
% sudo gcc_select 3.3

FFTW Libraries
% gnutar -xvzf fftw-3.1.2.tar.gz
% cd fftw-3.1.2
% ./configure
% make
% sudo make install
% sudo ln -s /usr/local/lib/libfftw3.a /usr/local/lib/libfftw.a
% sudo     ln -s /usr/local/lib/libfftw3.la /usr/local/lib/libfftw.la
% sudo    ln -s /usr/local/include/fftw3.h /usr/local/include/fftw.h

numpy
% sudo gcc_select 4.0
% gnutar xzf numpy-1.0rc1.tar.gz
% sudo python setup.py install
% python
import numpy
numpy.test(1,1)
(ALL PASSED)

% gnutar xzf scipy-0.5.1.tar.gz
% cd scipy-0.5.1
sudo ln -s /usr/lib/gcc/powerpc-apple-darwin8/4.0.1/libgcc.a /usr/ 
local/lib/libcc_dynamic.a

Some may encounter a linking error when building fftpack, which  
mentions something about undefined symbols from /usr/lib/ld. If so,  
you need to edit 'Lib/fftpack/setup.py' by changing:

     config.add_extension('_fftpack',
       sources=sources,
       libraries=['dfftpack'],
       extra_info = extra_info
     )

     config.add_extension('convolve',
       sources = ['convolve.pyf','src/convolve.c'],
       libraries = ['dfftpack'],
       extra_info = extra_info
     )

to:

     config.add_extension('_fftpack',
       sources=sources,
       libraries=['dfftpack'],
       extra_info = extra_info,
       extra_link_args = ['-lSystemStubs']
     )

     config.add_extension('convolve',
       sources = ['convolve.pyf','src/convolve.c'],
       libraries = ['dfftpack'],
       extra_info = extra_info,
       extra_link_args = ['-lSystemStubs']
     )


% python setup.py build
% sudo python setup.py install
% python
 >>> import scipy
 >>> scipy.test(level=1)
ERROR: check_integer (scipy.io.tests.test_array_import.test_read_array)
ERROR: check_simple_todense  
(scipy.io.tests.test_mmio.test_mmio_coordinate)


--
W.T. Bridgman, Ph.D.
Physics & Astronomy



From koara at atlas.cz  Mon Oct  9 05:39:24 2006
From: koara at atlas.cz (koara at atlas.cz)
Date: Mon, 09 Oct 2006 11:39:24 +0200
Subject: [SciPy-user] sparse behaviour?
Message-ID: <9b88f1713e4d4a18b400c72d5f0726e3@atlas.cz>

Hello all,

i decided to represent some of my large matrices as sparse matrices. My initial assumption was that the exposed operations and interfaces are the same (only the inner representation changes), so that my code would require no changes. However my code broke down immediately; is this how things are and my assumtpion was incorrect, or is something wrong?

an example (getting covariance matrix) of code that didn't make it:

n1 = matrix([[0,0,1,0],[0,0,0,2]])
s1 = sparse.lil_matrix(n1)
cov(n1) # OK
cov(s1) # shape mismatch exception---------------------------------------
Nov? spoty P. ?tvrni?ka najdete na www.neuservis.cz. Prav? dnes!




From jdhunter at ace.bsd.uchicago.edu  Mon Oct  9 10:01:56 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Mon, 09 Oct 2006 09:01:56 -0500
Subject: [SciPy-user] matplotlib and python 2.5 on Intel OS X
In-Reply-To: <B415F8F2-2CDC-47A0-A343-0515B2B4A62C@cortechs.net> (Gennan
	Chen's message of "Sat, 7 Oct 2006 17:37:23 -0700")
References: <B415F8F2-2CDC-47A0-A343-0515B2B4A62C@cortechs.net>
Message-ID: <87slhxoaej.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "Gennan" == Gennan Chen <gnchen at cortechs.net> writes:

    Gennan> Hi!  I am like to compile matplotlib for ython 2.5 on
    Gennan> Intel OSX.  Compilation went fine. But I got segmented
    Gennan> faults when I tried to run some test scripts. Anyone ever
    Gennan> successfully built it on python 2.5??  If did, can you
    Gennan> give me some hints on setup.py?

matplotlib questions should be directed to matplotlib-users or
matplotlib-devel.  In the mean time, please take a look at the
attached instructions for debugging segfaults.  Once you've
collected some of this, please post to the devel list.

# How to diagnose where a segfault is occurring

First thing to try is simply rm -rf the site-packages/matplotlib and
build subdirs and get a clean install.  Installing a new version over
a pretty old version has been known to cause trouble, segfault, etc.

Try importing these packages individually

  import matplotlib._image
  import matplotlib._transforms

  #one of these three depending on which numerix package you are using
  import matplotlib.backends._na_backend_agg # for numarray
  import matplotlib.backends._nc_backend_agg # for Numeric
  import matplotlib.backends._ns_backend_agg # for numpy

  import matplotlib.backends._tkagg
  import matplotlib._agg


If the last two work and the others don't, it is likely you need to
upgrade your gcc, because on some platforms (OS X for sure) old
versions of gcc cannot compile new versions of pycxx, which matplotlib
uses for building some but not all of it's extensions.  Report back
which if any work or segfault or raise tracebacks,

If that shed additional light, again flush the build and install dirs,
and try setting VERBOSE=True in setup.py before doing a clean install.
The VERBOSE setting will generate lots of extra output and may help
indicate where the segfault is occurring 


From jdhunter at ace.bsd.uchicago.edu  Mon Oct  9 10:01:56 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Mon, 09 Oct 2006 09:01:56 -0500
Subject: [SciPy-user] matplotlib and python 2.5 on Intel OS X
In-Reply-To: <B415F8F2-2CDC-47A0-A343-0515B2B4A62C@cortechs.net> (Gennan
	Chen's message of "Sat, 7 Oct 2006 17:37:23 -0700")
References: <B415F8F2-2CDC-47A0-A343-0515B2B4A62C@cortechs.net>
Message-ID: <87slhxoaej.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "Gennan" == Gennan Chen <gnchen at cortechs.net> writes:

    Gennan> Hi!  I am like to compile matplotlib for ython 2.5 on
    Gennan> Intel OSX.  Compilation went fine. But I got segmented
    Gennan> faults when I tried to run some test scripts. Anyone ever
    Gennan> successfully built it on python 2.5??  If did, can you
    Gennan> give me some hints on setup.py?

matplotlib questions should be directed to matplotlib-users or
matplotlib-devel.  In the mean time, please take a look at the
attached instructions for debugging segfaults.  Once you've
collected some of this, please post to the devel list.

# How to diagnose where a segfault is occurring

First thing to try is simply rm -rf the site-packages/matplotlib and
build subdirs and get a clean install.  Installing a new version over
a pretty old version has been known to cause trouble, segfault, etc.

Try importing these packages individually

  import matplotlib._image
  import matplotlib._transforms

  #one of these three depending on which numerix package you are using
  import matplotlib.backends._na_backend_agg # for numarray
  import matplotlib.backends._nc_backend_agg # for Numeric
  import matplotlib.backends._ns_backend_agg # for numpy

  import matplotlib.backends._tkagg
  import matplotlib._agg


If the last two work and the others don't, it is likely you need to
upgrade your gcc, because on some platforms (OS X for sure) old
versions of gcc cannot compile new versions of pycxx, which matplotlib
uses for building some but not all of it's extensions.  Report back
which if any work or segfault or raise tracebacks,

If that shed additional light, again flush the build and install dirs,
and try setting VERBOSE=True in setup.py before doing a clean install.
The VERBOSE setting will generate lots of extra output and may help
indicate where the segfault is occurring 


From R.Springuel at umit.maine.edu  Mon Oct  9 10:42:53 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Mon, 09 Oct 2006 10:42:53 -0400
Subject: [SciPy-user] Installation Problems on Mac OS X
Message-ID: <452A5FED.3090504@umit.maine.edu>

Okay.  I got numpy to install okay, but now I'm having a problem with 
scipy.  Now, the full output of the install command is really long by 
the time it hits the error, but I believe that these lines at the end 
specify what the error is:

sh: line 1: f95: command not found
sh: line 1: f95: command not found
error: Command "f95 -fixed -O4 -target=native -c -c 
Lib/fftpack/dfftpack/dcosqb.f -o 
build/temp.macosx-10.3-fat-2.5/Lib/fftpack/dfftpack/dcosqb.o" failed 
with exit status 127

Can some one explain to me what this error means and how to go about 
correcting it?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From ahoover at eecs.berkeley.edu  Mon Oct  9 11:14:33 2006
From: ahoover at eecs.berkeley.edu (Aaron Hoover)
Date: Mon, 9 Oct 2006 08:14:33 -0700
Subject: [SciPy-user] Installation Problems on Mac OS X
In-Reply-To: <452A5FED.3090504@umit.maine.edu>
References: <452A5FED.3090504@umit.maine.edu>
Message-ID: <1B99FD32-54D6-484E-91EB-CECBC9803478@eecs.berkeley.edu>

>
> sh: line 1: f95: command not found
> sh: line 1: f95: command not found
> error: Command "f95 -fixed -O4 -target=native -c -c
> Lib/fftpack/dfftpack/dcosqb.f -o
> build/temp.macosx-10.3-fat-2.5/Lib/fftpack/dfftpack/dcosqb.o" failed
> with exit status 127

You are missing a Fortran 95 compiler. There is a binary version of  
the compiler here: http://prdownloads.sourceforge.net/hpc/gcc-intel- 
bin.tar.gz?download. Also, you can find a nice guide to setting up  
SciPy on OS X on the
SciPy wiki here: http://www.scipy.org/Installing_SciPy/Mac_OS_X.


Cheers,
Aaron


From pspuhler at ball.com  Mon Oct  9 12:17:28 2006
From: pspuhler at ball.com (Spuhler, Peter)
Date: Mon, 9 Oct 2006 10:17:28 -0600
Subject: [SciPy-user] howto call optimize.brute()
Message-ID: <7575324F915A05448800386F6CEAF3670454C604@AEROMSG2.AERO.BALL.COM>

I can't seem to get optimize.brute working

The following error function works for optimize.fmin_powell for example
Def _error(x,offset):
	Error = x[0]**2 + x[1]**2 + offset
	Return error
Optimize.fmin(_error,x0=[1,1],args=(10,))

But if I now try to use optimize.brute
Bounds = ((-10,10,0.1),(-10,10,0.1))
Optimize.brute(_error,ranges=bounds,args=(10,))
I get the following error. What am I missing?

C:\Python24\lib\site-packages\scipy\optimize\optimize.py in brute(func,
ranges,
args, Ns, full_output, finish)
   1577     if (N==1):
   1578         grid = (grid,)
-> 1579     Jout = vecfunc(*grid)
   1580     Nshape = shape(Jout)
   1581     indx = argmin(Jout.ravel())

C:\Python24\lib\site-packages\numpy\lib\function_base.py in
__call__(self, *args
)
    619         nargs = len(args)
    620         if (nargs > self.nin) or (nargs < self.nin_wo_defaults):
--> 621             raise ValueError, "mismatch between python function
inputs"\

    622                   " and received arguments"
    623         if self.nout is None or self.otypes == '':

ValueError: mismatch between python function inputs and received
arguments

Thanks
-Peter




From nwagner at iam.uni-stuttgart.de  Mon Oct  9 13:30:47 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Mon, 09 Oct 2006 19:30:47 +0200
Subject: [SciPy-user] howto call optimize.brute()
In-Reply-To: <7575324F915A05448800386F6CEAF3670454C604@AEROMSG2.AERO.BALL.COM>
References: <7575324F915A05448800386F6CEAF3670454C604@AEROMSG2.AERO.BALL.COM>
Message-ID: <web-59552525@uni-stuttgart.de>

On Mon, 9 Oct 2006 10:17:28 -0600
  "Spuhler, Peter" <pspuhler at ball.com> wrote:
> I can't seem to get optimize.brute working
> 
> The following error function works for 
>optimize.fmin_powell for example
> Def _error(x,offset):
> 	Error = x[0]**2 + x[1]**2 + offset
> 	Return error
> Optimize.fmin(_error,x0=[1,1],args=(10,))
> 
> But if I now try to use optimize.brute
> Bounds = ((-10,10,0.1),(-10,10,0.1))
> Optimize.brute(_error,ranges=bounds,args=(10,))
> I get the following error. What am I missing?
> 
> C:\Python24\lib\site-packages\scipy\optimize\optimize.py 
>in brute(func,
> ranges,
> args, Ns, full_output, finish)
>   1577     if (N==1):
>   1578         grid = (grid,)
> -> 1579     Jout = vecfunc(*grid)
>   1580     Nshape = shape(Jout)
>   1581     indx = argmin(Jout.ravel())
> 
> C:\Python24\lib\site-packages\numpy\lib\function_base.py 
>in
> __call__(self, *args
> )
>    619         nargs = len(args)
>    620         if (nargs > self.nin) or (nargs < 
>self.nin_wo_defaults):
> --> 621             raise ValueError, "mismatch between 
>python function
> inputs"\
> 
>    622                   " and received arguments"
>    623         if self.nout is None or self.otypes == 
>'':
> 
> ValueError: mismatch between python function inputs and 
>received
> arguments
> 
> Thanks
> -Peter
> 
> 
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

I cannot reproduce your problem.
I am using
>>> scipy.__version__
'0.5.2.dev2247'
>>> import numpy
>>> numpy.__version__
'1.0.dev3292'


Nils
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From andrew.young at sri.com  Mon Oct  9 13:39:25 2006
From: andrew.young at sri.com (Andrew B. Young)
Date: Mon, 09 Oct 2006 10:39:25 -0700
Subject: [SciPy-user] Problem installing scipy-0.5.1 on FC5
Message-ID: <452A894D.4000407@sri.com>

I would like to use splrep() splev() for matplotlib plot smoothing 
similar to gnuplot smoothing 
(http://mail.python.org/pipermail/python-list/2005-April/275568.html) 
but the install fails.  I followed the instructions for FC5 on 
http://www.scipy.org/Installing_SciPy/Linux?highlight=%28%28----%28-%2A%29%28%5Cr%29%3F%5Cn%29%28.%2A%29CategoryInstallation%5Cb%29

sudo yum install numpy
  Installed: numpy.i386 0:0.9.8-1.fc5
  Dependency Installed: atlas.i386 0:3.6.0-10.fc5
sudo yum install lapack-devel blas-devel
  Installed: blas-devel.i386 0:3.0-37.fc5 lapack-devel.i386 0:3.0-37.fc5
  Dependency Installed: blas.i386 0:3.0-37.fc5 lapack.i386 0:3.0-37.fc5

Downloaded scipy-0.5.1
cd /usr/src/scipy-0.5.1
python setup.py install, and...
    File 
"/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
655, in _get_configuration_from_setup_py
    ('.py', 'U', 1))
  File "Lib/ndimage/setup.py", line 3, in ?
    from numpy.numarray import get_numarray_include_dirs

Then in installed numarray-1.5.2, but that went into site-packages/numarray.
Then I tried a symlink from numpy/numarray -> ../numarry, but more errors

Any help?
Thanks,
Andre


From pecora at anvil.nrl.navy.mil  Mon Oct  9 13:45:46 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Mon, 09 Oct 2006 13:45:46 -0400
Subject: [SciPy-user] Problem loading Scipy on MacOS X, missing module.
Message-ID: <452A8ACA.8020205@anvil.nrl.navy.mil>

I recently loaded the SuperPack for Scipy 0.5.1 on the MacOS 10.4 which 
included MacPython 2.4.  All packages were loaded:

scipy-0.5.0.2095-py2.4-macosx10.4.mpkg
PyMC-1.0_beta-py2.4-macosx10.4.mpkg
numpy-1.1.2881-py2.4-macosx10.4.mpkg
matplotlib-0.87.4_r2592-py2.4-macosx10.4.mpkg
ipython-0.7.2-py2.4-macosx10.4.mpkg


My problem.  When I run pythonw in the Terminal and import scipy I get 
the following error message:

 >>> import scipy
import linsolve.umfpack -> failed: Failure linking new module: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so: 
Library not loaded: /usr/local/lib/libg2c.0.dylib
  Referenced from: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so
  Reason: image not found

So, I guess it can't find a module (so it says), but I'm a bit lost in 
the verbosity of the error message.  Can anyone tell me what the problem 
is? 

Thanks for any help.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From R.Springuel at umit.maine.edu  Mon Oct  9 13:53:18 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Mon, 09 Oct 2006 13:53:18 -0400
Subject: [SciPy-user] Installation problems on Mac OS X
Message-ID: <452A8C8E.4000601@umit.maine.edu>

Okay, so I installed the Fortran compiler using the directions and link 
on the wiki, but I'm still getting the same error.  Now what?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From oliphant.travis at ieee.org  Mon Oct  9 14:15:56 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Mon, 09 Oct 2006 12:15:56 -0600
Subject: [SciPy-user] Problem installing scipy-0.5.1 on FC5
In-Reply-To: <452A894D.4000407@sri.com>
References: <452A894D.4000407@sri.com>
Message-ID: <452A91DC.1050604@ieee.org>

Andrew B. Young wrote:
> I would like to use splrep() splev() for matplotlib plot smoothing 
> similar to gnuplot smoothing 
> (http://mail.python.org/pipermail/python-list/2005-April/275568.html) 
> but the install fails.  I followed the instructions for FC5 on 
> http://www.scipy.org/Installing_SciPy/Linux?highlight=%28%28----%28-%2A%29%28%5Cr%29%3F%5Cn%29%28.%2A%29CategoryInstallation%5Cb%29
>
> sudo yum install numpy
>   Installed: numpy.i386 0:0.9.8-1.fc5
>   Dependency Installed: atlas.i386 0:3.6.0-10.fc5
> sudo yum install lapack-devel blas-devel
>   Installed: blas-devel.i386 0:3.0-37.fc5 lapack-devel.i386 0:3.0-37.fc5
>   Dependency Installed: blas.i386 0:3.0-37.fc5 lapack.i386 0:3.0-37.fc5
>
> Downloaded scipy-0.5.1
> cd /usr/src/scipy-0.5.1
> python setup.py install, and...
>     File 
> "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
> 655, in _get_configuration_from_setup_py
>     ('.py', 'U', 1))
>   File "Lib/ndimage/setup.py", line 3, in ?
>     from numpy.numarray import get_numarray_include_dirs
>
>   
The dependencies are wrong.  SciPy 0.5.1 requires numpy 1.0  not 
numpy-0.9.8.

The required numarray compatibility layer is in numpy 1.0 not in 
numarray.  You don't need to install numarray at all.

Install numpy 1.0

-Travis



From pspuhler at ball.com  Mon Oct  9 15:00:13 2006
From: pspuhler at ball.com (Spuhler, Peter)
Date: Mon, 9 Oct 2006 13:00:13 -0600
Subject: [SciPy-user] howto call optimize.brute()
Message-ID: <7575324F915A05448800386F6CEAF3670454C60C@AEROMSG2.AERO.BALL.COM>

On Mon, 9 Oct 2006 10:17:28 -0600
  "Spuhler, Peter" <pspuhler <at> ball.com> wrote:
> I can't seem to get optimize.brute working
> 
> The following error function works for 
>optimize.fmin_powell for example
> Def _error(x,offset):
> 	Error = x[0]**2 + x[1]**2 + offset
> 	Return error
> Optimize.fmin(_error,x0=[1,1],args=(10,))
> 
> But if I now try to use optimize.brute
> Bounds = ((-10,10,0.1),(-10,10,0.1))
> Optimize.brute(_error,ranges=bounds,args=(10,))
> I get the following error. What am I missing?
> 
> C:\Python24\lib\site-packages\scipy\optimize\optimize.py 
>in brute(func,
> ranges,
> args, Ns, full_output, finish)
>   1577     if (N==1):
>   1578         grid = (grid,)
> -> 1579     Jout = vecfunc(*grid)
>   1580     Nshape = shape(Jout)
>   1581     indx = argmin(Jout.ravel())
> 
> C:\Python24\lib\site-packages\numpy\lib\function_base.py 
>in
> __call__(self, *args
> )
>    619         nargs = len(args)
>    620         if (nargs > self.nin) or (nargs < 
>self.nin_wo_defaults):
> --> 621             raise ValueError, "mismatch between 
>python function
> inputs"\
> 
>    622                   " and received arguments"
>    623         if self.nout is None or self.otypes == 
>'':
> 
> ValueError: mismatch between python function inputs and 
>received
> arguments
> 
> Thanks
> -Peter
> 
> 
> _______________________________________________
> SciPy-user mailing list
> SciPy-user <at> scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

I cannot reproduce your problem.
I am using
>>> scipy.__version__
'0.5.2.dev2247'
>>> import numpy
>>> numpy.__version__
'1.0.dev3292'

Nils

I'm using enthought python dist
Numpy 0.9.9.2706
Scipy 0.5.0.2033
Is this a bug in this version of scipy?





From andrew.young at sri.com  Mon Oct  9 17:11:06 2006
From: andrew.young at sri.com (Andrew B. Young)
Date: Mon, 09 Oct 2006 14:11:06 -0700
Subject: [SciPy-user] Problem installing scipy-0.5.1 on FC5
In-Reply-To: <452A91DC.1050604@ieee.org>
References: <452A894D.4000407@sri.com> <452A91DC.1050604@ieee.org>
Message-ID: <452ABAEA.6080204@sri.com>

That did it!
Thanks Travis.

Travis Oliphant wrote:
> Andrew B. Young wrote:
>   
>> I would like to use splrep() splev() for matplotlib plot smoothing 
>> similar to gnuplot smoothing 
>> (http://mail.python.org/pipermail/python-list/2005-April/275568.html) 
>> but the install fails.  I followed the instructions for FC5 on 
>> http://www.scipy.org/Installing_SciPy/Linux?highlight=%28%28----%28-%2A%29%28%5Cr%29%3F%5Cn%29%28.%2A%29CategoryInstallation%5Cb%29
>>
>> sudo yum install numpy
>>   Installed: numpy.i386 0:0.9.8-1.fc5
>>   Dependency Installed: atlas.i386 0:3.6.0-10.fc5
>> sudo yum install lapack-devel blas-devel
>>   Installed: blas-devel.i386 0:3.0-37.fc5 lapack-devel.i386 0:3.0-37.fc5
>>   Dependency Installed: blas.i386 0:3.0-37.fc5 lapack.i386 0:3.0-37.fc5
>>
>> Downloaded scipy-0.5.1
>> cd /usr/src/scipy-0.5.1
>> python setup.py install, and...
>>     File 
>> "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
>> 655, in _get_configuration_from_setup_py
>>     ('.py', 'U', 1))
>>   File "Lib/ndimage/setup.py", line 3, in ?
>>     from numpy.numarray import get_numarray_include_dirs
>>
>>   
>>     
> The dependencies are wrong.  SciPy 0.5.1 requires numpy 1.0  not 
> numpy-0.9.8.
>
> The required numarray compatibility layer is in numpy 1.0 not in 
> numarray.  You don't need to install numarray at all.
>
> Install numpy 1.0
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   



From stefan at sun.ac.za  Mon Oct  9 19:48:53 2006
From: stefan at sun.ac.za (Stefan van der Walt)
Date: Tue, 10 Oct 2006 01:48:53 +0200
Subject: [SciPy-user] sparse behaviour?
In-Reply-To: <9b88f1713e4d4a18b400c72d5f0726e3@atlas.cz>
References: <9b88f1713e4d4a18b400c72d5f0726e3@atlas.cz>
Message-ID: <20061009234853.GF4215@mentat.za.net>

On Mon, Oct 09, 2006 at 11:39:24AM +0200, koara at atlas.cz wrote:
> i decided to represent some of my large matrices as sparse matrices. My initial assumption was that the exposed operations and interfaces are the same (only the inner representation changes), so that my code would require no changes. However my code broke down immediately; is this how things are and my assumtpion was incorrect, or is something wrong?
> 
> an example (getting covariance matrix) of code that didn't make it:
> 
> n1 = matrix([[0,0,1,0],[0,0,0,2]])
> s1 = sparse.lil_matrix(n1)
> cov(n1) # OK
> cov(s1) # shape mismatch
> exception---------------------------------------

Currently, scipy.cov calls numpy.cov, which knows nothing about sparse
matrices.  I don't think there is any reason why it can't be done,
it's just that no one has taken the time to implement it.

Regards
St?fan


From peridot.faceted at gmail.com  Mon Oct  9 23:29:32 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Mon, 9 Oct 2006 23:29:32 -0400
Subject: [SciPy-user] sparse behaviour?
In-Reply-To: <20061009234853.GF4215@mentat.za.net>
References: <9b88f1713e4d4a18b400c72d5f0726e3@atlas.cz>
	<20061009234853.GF4215@mentat.za.net>
Message-ID: <ce557a360610092029v42388086t7ff35680e6b0091f@mail.gmail.com>

On 09/10/06, Stefan van der Walt <stefan at sun.ac.za> wrote:

> Currently, scipy.cov calls numpy.cov, which knows nothing about sparse
> matrices.  I don't think there is any reason why it can't be done,
> it's just that no one has taken the time to implement it.

There are two ways to fix this: just convert the matrix into a dense
matrix and call numpy.cov, or actually implement a covariance-matrix
algorithm for sparse matrices. I would argue *against* doing the
first: if a user is using sparse matrices, they have a reason, whether
because dense matrices would overload memory, or because sparse
algorithms are vastly faster, and secretly exploding their matrix to a
dense one is likely to be confusing and unwanted.

A. M. Archibald


From ryanlists at gmail.com  Tue Oct 10 02:26:50 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 01:26:50 -0500
Subject: [SciPy-user] where bug
Message-ID: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>

I am having a problem running some slightly older code under a fairly
new Scipy for the first time.  The code uses where and something like
this:
In [23]: t=arange(0,1,0.01)

In [24]: where(t>0.5)
Out[24]:
(array([51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
       68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
       85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]),)

used to return just the array instead of the tuple with the array in
it.  Is this a feature or a bug?  Can you get this behavior from a
stray comma in the return line?

Thanks,

Ryan


From a.u.r.e.l.i.a.n at gmx.net  Tue Oct 10 02:36:47 2006
From: a.u.r.e.l.i.a.n at gmx.net (Johannes Loehnert)
Date: Tue, 10 Oct 2006 08:36:47 +0200
Subject: [SciPy-user] where bug
In-Reply-To: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>
References: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>
Message-ID: <200610100836.47965.a.u.r.e.l.i.a.n@gmx.net>

Am Dienstag, 10. Oktober 2006 08:26 schrieb Ryan Krauss:
> I am having a problem running some slightly older code under a fairly
> new Scipy for the first time.  The code uses where and something like
> this:
> In [23]: t=arange(0,1,0.01)
>
> In [24]: where(t>0.5)
> Out[24]:
> (array([51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
>        68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
>        85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]),)
>
> used to return just the array instead of the tuple with the array in
> it.  Is this a feature or a bug?  

Feature. If you use n-d arrays, you will get back a tuple of size n, one index 
array for each axis. You ran into the special case n=1.

AFAIK, nonzero returns just the array in 1d case. Though I would recommend to 
use fancy indexing (i.e. t[t>0.5] ) whenever possible, it is way faster.

HTH,
Johannes


From oliphant.travis at ieee.org  Tue Oct 10 02:55:37 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Tue, 10 Oct 2006 00:55:37 -0600
Subject: [SciPy-user] where bug
In-Reply-To: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>
References: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>
Message-ID: <452B43E9.9080005@ieee.org>

Ryan Krauss wrote:
> I am having a problem running some slightly older code under a fairly
> new Scipy for the first time.  The code uses where and something like
> this:
> In [23]: t=arange(0,1,0.01)
>
> In [24]: where(t>0.5)
> Out[24]:
> (array([51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
>        68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
>        85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]),)
>
> used to return just the array instead of the tuple with the array in
> it.  Is this a feature or a bug? 
It's a feature (the old behavior was a bug...).  The functionality of 
where is actually from NumPy and has changed to be consistent with 
Numarray.    You can get the old behavior with flatnonzero(...) or of 
course where(...)[0].

-Travis



From koara at atlas.cz  Tue Oct 10 04:39:34 2006
From: koara at atlas.cz (koara at atlas.cz)
Date: Tue, 10 Oct 2006 10:39:34 +0200
Subject: [SciPy-user] sparse behaviour?
Message-ID: <aa0adb4872f84dee9009cd7beb26ae10@atlas.cz>

>-----Puvodni zprava-----
>Od: Stefan van der Walt [mailto:stefan at sun.ac.za]
>Odesl?no: 9. r?jna 2006 23:48
>Komu: scipy-user at scipy.org
>Predmet: Re: [SciPy-user] sparse behaviour?
> ...
>Currently, scipy.cov calls numpy.cov, which knows nothing about sparse
>matrices.  I don't think there is any reason why it can't be done,
>it's just that no one has taken the time to implement it.


Thank you Stefan!

So indeed my assumption was wrong. Is there a user-friendly list of which things work the same for both dense/sparse matrices without any additional code, so that i do not re-invent the wheel? Since indexing syntax is the same, I imagine some things might work even with a simple call to numpy, no?  Just like i assumed cov() would... :>

Well i guess there's a lot of debugging ahead either way. Cheers
---------------------------------------
Nov? spoty P. Ctvrnicka najdete na www.neuservis.cz. Prave dnes!




From cimrman3 at ntc.zcu.cz  Tue Oct 10 06:06:09 2006
From: cimrman3 at ntc.zcu.cz (Robert Cimrman)
Date: Tue, 10 Oct 2006 12:06:09 +0200
Subject: [SciPy-user] sparse behaviour?
In-Reply-To: <aa0adb4872f84dee9009cd7beb26ae10@atlas.cz>
References: <aa0adb4872f84dee9009cd7beb26ae10@atlas.cz>
Message-ID: <452B7091.9080308@ntc.zcu.cz>

koara at atlas.cz wrote:
>> -----Puvodni zprava----- Od: Stefan van der Walt
>> [mailto:stefan at sun.ac.za] Odesl?no: 9. r?jna 2006 23:48 Komu:
>> scipy-user at scipy.org Predmet: Re: [SciPy-user] sparse behaviour? 
>> ... Currently, scipy.cov calls numpy.cov, which knows nothing about
>> sparse matrices.  I don't think there is any reason why it can't be
>> done, it's just that no one has taken the time to implement it.
> 
> 
> Thank you Stefan!
> 
> So indeed my assumption was wrong. Is there a user-friendly list of
> which things work the same for both dense/sparse matrices without any
> additional code, so that i do not re-invent the wheel? Since indexing
> syntax is the same, I imagine some things might work even with a
> simple call to numpy, no?  Just like i assumed cov() would... :>

The short answer (and current status) is:
1. all functions in scipy.sparse and scipy.linsolve work with sparse
matrices and expect sparse matrices (they were written for them)
2. all other functions do not understand sparse matrices.

IMHO the problem here is that the sparse matrix class is not a subclass
of numpy.ndarray. So far, asarray and friends - when used on a sparse
matrix - make an object array with one item - the sparse matrix object.
I would prefer this behaviour changed to:
a) raise exception
b) call .todense() method of the sparse matrix
- here I am more for a) since using a dense-array algorithm on a sparse
matrix will not work well - b) would cause many out-of-memory errors.

And then, of course, sparse matrix algorithms should be continuously
added to reflect the dense ones. (Here, for example, the CSparse library
could help, if wrapped properly to Python.)

cheers,
r.


From andrew.young at sri.com  Tue Oct 10 11:13:03 2006
From: andrew.young at sri.com (Andrew B. Young)
Date: Tue, 10 Oct 2006 08:13:03 -0700
Subject: [SciPy-user] Plotting an array
Message-ID: <452BB87F.8000601@sri.com>

I believe this is a rookie question but the I've not discovered the
answer so easily.  The code below, copied from a posting I found,
produces a graph with a straight line across zero.  Plotting just t,
plot(t), produces a line either zero or one.  I am sure it has
something to do with plotting an array versus plotting a python list.
I would be happy for a pointer to the reference material for me to
read.  http://www.scipy.org/Documentation has not yet lead me to the
answer.


  t = arange(0, 2.0, 0.1)
  y = sin(2*pi*t)
  tck = interpolate.splrep(t, y, s=0)
  tnew = arange(0, 2.0, 0.01)
  ynew = interpolate.splev(tnew, tck, der=0)
  plot(t, y, 'o', tnew, ynew)
  show()

Thanks,
Andrew Young

Python 2.4.3 (#1, Jun 13 2006, 11:46:08), [GCC 4.1.1 20060525 (Red Hat 4.1.1-1)] on linux2
numpy-1.0rc1
scipy-0.5.1
matplotlib-0.85



From elcorto at gmx.net  Tue Oct 10 11:56:14 2006
From: elcorto at gmx.net (Steve Schmerler)
Date: Tue, 10 Oct 2006 17:56:14 +0200
Subject: [SciPy-user] import speed in a script
Message-ID: <452BC29E.2070400@gmx.net>

Hi

This may be a dumb and/or more general Python question, but:

What is more advisable in terms of speed:
Say I call a script many times and inside I do nothing but

from numpy import <name>

or

import numpy as nu


I tried both and found no speed difference (e.g. calling the script 500 
times). I just wondered about this since there is scipy.pkgload(). In an 
interactive session "import scipy" doesn't import the whole scipy with 
all packages. Is this also true for an import statement in a script?

-- 
cheers,
steve

Random number generation is the art of producing pure gibberish as 
quickly as possible.


From arserlom at gmail.com  Tue Oct 10 12:01:33 2006
From: arserlom at gmail.com (Armando Serrano Lombillo)
Date: Tue, 10 Oct 2006 18:01:33 +0200
Subject: [SciPy-user] How to calculate minors.
Message-ID: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>

Hello, is there any way to easily calculate minors of matrixes with
scipy/numpy.

For example if we have matrix a:
[[1 2 3]
 [4 5 6]
 [7 8 9]]

then minor(a,0) should be the same as det([[5,6],[8,9]]) and minor (a,1)
should be the same as det([[1,3],[7,9]]).

Armando.
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From elcorto at gmx.net  Tue Oct 10 12:15:21 2006
From: elcorto at gmx.net (Steve Schmerler)
Date: Tue, 10 Oct 2006 18:15:21 +0200
Subject: [SciPy-user] Plotting an array
In-Reply-To: <452BB87F.8000601@sri.com>
References: <452BB87F.8000601@sri.com>
Message-ID: <452BC719.2030103@gmx.net>

Andrew B. Young wrote:
> I believe this is a rookie question but the I've not discovered the
> answer so easily.  The code below, copied from a posting I found,
> produces a graph with a straight line across zero.  Plotting just t,
> plot(t), produces a line either zero or one.  I am sure it has
> something to do with plotting an array versus plotting a python list.

Hmmm, t, y, tnew and ynew are <type 'numpy.ndarray'> in my case (try 
type(t) etc. to find out).
The only list is tck, but is not plotted (it contains infos about the 
spline and is passed to splev).

numpy 1.0rc1.dev3144
scipy 0.5.2.dev2197
matplotlib 0.87.5 Rev 2761

> I would be happy for a pointer to the reference material for me to
> read.  http://www.scipy.org/Documentation has not yet lead me to the
> answer.
> 
> 
>   t = arange(0, 2.0, 0.1)
>   y = sin(2*pi*t)
>   tck = interpolate.splrep(t, y, s=0)
>   tnew = arange(0, 2.0, 0.01)
>   ynew = interpolate.splev(tnew, tck, der=0)
>   plot(t, y, 'o', tnew, ynew)
>   show()
> 

PS: Rather unimportant note to the scipy guys:

In [27]: len(tck)
Out[27]: 3
In [28]: type(tck)
Out[28]: <type 'list'>

The splrep docstring says tck is a len 3 tuple, not a list ...

-- 
cheers,
steve

Random number generation is the art of producing pure gibberish as 
quickly as possible.


From gael.varoquaux at normalesup.org  Tue Oct 10 12:19:50 2006
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Tue, 10 Oct 2006 18:19:50 +0200
Subject: [SciPy-user] Plotting an array
In-Reply-To: <452BB87F.8000601@sri.com>
References: <452BB87F.8000601@sri.com>
Message-ID: <20061010161945.GA7916@clipper.ens.fr>

    Hi,

Can you give a complete minimum example that does not work. If I put the
following code in a file and run python on it, I get the expected result.

from scipy import *
from pylab import *
t = arange(0, 2.0, 0.1)
y = sin(2*pi*t)
tck = interpolate.splrep(t, y, s=0)
tnew = arange(0, 2.0, 0.01)
ynew = interpolate.splev(tnew, tck, der=0)
plot(t, y, 'o', tnew, ynew)
show()


Ga?l


From ryanlists at gmail.com  Tue Oct 10 12:23:00 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 11:23:00 -0500
Subject: [SciPy-user] where bug
In-Reply-To: <452B43E9.9080005@ieee.org>
References: <c5b438120610092326h5f75636cha56843b427dd4e37@mail.gmail.com>
	<452B43E9.9080005@ieee.org>
Message-ID: <c5b438120610100923l7f5efd1fr5dfe315be858bac7@mail.gmail.com>

Thanks to Travis and Johannes.  As long as I know its a feature, I
will adjust my code accordingly.

Ryan

On 10/10/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> Ryan Krauss wrote:
> > I am having a problem running some slightly older code under a fairly
> > new Scipy for the first time.  The code uses where and something like
> > this:
> > In [23]: t=arange(0,1,0.01)
> >
> > In [24]: where(t>0.5)
> > Out[24]:
> > (array([51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65, 66, 67,
> >        68, 69, 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
> >        85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, 97, 98, 99]),)
> >
> > used to return just the array instead of the tuple with the array in
> > it.  Is this a feature or a bug?
> It's a feature (the old behavior was a bug...).  The functionality of
> where is actually from NumPy and has changed to be consistent with
> Numarray.    You can get the old behavior with flatnonzero(...) or of
> course where(...)[0].
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From andrew.young at sri.com  Tue Oct 10 13:30:59 2006
From: andrew.young at sri.com (Andrew B. Young)
Date: Tue, 10 Oct 2006 10:30:59 -0700
Subject: [SciPy-user] Plotting an array
In-Reply-To: <20061010161945.GA7916@clipper.ens.fr>
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
Message-ID: <452BD8D3.2010500@sri.com>

Gael,

The following little program--
-- test.py ----------------------
| from scipy import arange, sin, pi, interpolate
| from pylab import plot, show, savefig
| t = arange(0, 2.0, 0.1)
| plot(t)
| savefig('test.png')

Produces the plot at http://polar.sri.com/~ayoung/test.png

Why does the plot "turn on" at one?  If I,
  plot( [ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9,  1. 
, 1.1,  1.2,  1.3,  1.4,  1.5,  1.6,  1.7,  1.8,  1.9] )
I get what I would expect:  http://polar.sri.com/~ayoung/test2.png

Thanks for you help.
-andyy

Gael Varoquaux wrote:
>     Hi,
>
> Can you give a complete minimum example that does not work. If I put the
> following code in a file and run python on it, I get the expected result.
>
> from scipy import *
> from pylab import *
> t = arange(0, 2.0, 0.1)
> y = sin(2*pi*t)
> tck = interpolate.splrep(t, y, s=0)
> tnew = arange(0, 2.0, 0.01)
> ynew = interpolate.splev(tnew, tck, der=0)
> plot(t, y, 'o', tnew, ynew)
> show()
>
>
> Ga?l
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   




From ryanlists at gmail.com  Tue Oct 10 13:32:24 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 12:32:24 -0500
Subject: [SciPy-user] phase wrapping algorithm
Message-ID: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>

I am rethinking an algorithm for unwrapping phase data from arctan2
for a vector of complex numbers (coming from lti models of feedback
control systems).  I had written something a while ago using weave,
but my old code causes seg faults with a recent scipy update.  So, I
am rethinking the algorithm.

The problem occurs when either because of noise or just the definition
of the inverse tangent, their are discontinuities in the phase (which
is coming from arctan2(imag(vector), real(vector)).  For example, in
the attached plot and data file, there is a point where the phase
passes through -180 degrees.  arctan2 jumps to returning +180, +175
etc, when it makes a pretty plot and makes more sense to me to convert
+175 to -185.  What I had done previously is write a for loop that
compares the current value of the phase to the value at the previous
index (i.e. if phase[i]-phase[-1]>300 or if phase[i]-phase[i-1]<-300)
to find the discontinuities.  Is there a cleaner/faster way to do
this?  (I had done it in weave and will probably now do it in f2py for
comparison on speeds).  I have attached/included a first attempt at an
algorithm that is more vectorized.  But is there a fast, easy way to
compare a vector to the same vector shift one element up or down?
Right now I am doing this

phase2=r_[phase[0:1],phase[0:-1]]

to shift the vector (and reuse the first element so there isn't a jump
from phase[-1] to phase[0] which may legitimately be far apart).

Has anyone else already done this?  Are there obvious bottlenecks with
the algorithm?

Thanks for your thoughts,

Ryan

=====================================
from scipy import arange, io, r_
from pylab import show, figure, subplot, clf, cla, semilogx, xlabel,
ylabel, legend, xlim

import copy

data=io.read_array('phase_data.txt')
f=data[:,0]
phase=data[:,1]
figure(1)
clf()
startphase=copy.copy(phase)
semilogx(f,startphase)

keepgoing=1

inds=arange(0,len(phase))

while keepgoing:
    phase2=r_[phase[0:1],phase[0:-1]]#artificially repeat the first element
    diff=phase-phase2
    jumps=inds[abs(diff)>250]
    keepgoing=jumps.any()
    if not keepgoing:
        break
    ind=jumps.min()
    if diff[ind]>0:
        phase[ind:]-=360
    else:
        phase[ind:]+=360


semilogx(f,phase,'r--')

legend(['Before unwrapping','after unwrapping'],2)

xlim([1,30])

show()
-------------- next part --------------
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From ryanlists at gmail.com  Tue Oct 10 13:35:50 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 12:35:50 -0500
Subject: [SciPy-user] Plotting an array
In-Reply-To: <452BD8D3.2010500@sri.com>
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
	<452BD8D3.2010500@sri.com>
Message-ID: <c5b438120610101035r2c4c919ct92cad1828640fca8@mail.gmail.com>

It seems like you are somehow plotting t as an integer.  print t to
your command window and check it out.

If I just do t=arange(0,2.0,0.1) and plot(t) I get a plot that looks
like your test2.png and my t is:
t = arange(0, 2.0, 0.1)

Ryan

On 10/10/06, Andrew B. Young <andrew.young at sri.com> wrote:
> Gael,
>
> The following little program--
> -- test.py ----------------------
> | from scipy import arange, sin, pi, interpolate
> | from pylab import plot, show, savefig
> | t = arange(0, 2.0, 0.1)
> | plot(t)
> | savefig('test.png')
>
> Produces the plot at http://polar.sri.com/~ayoung/test.png
>
> Why does the plot "turn on" at one?  If I,
>   plot( [ 0. ,  0.1,  0.2,  0.3,  0.4,  0.5,  0.6,  0.7,  0.8,  0.9,  1.
> , 1.1,  1.2,  1.3,  1.4,  1.5,  1.6,  1.7,  1.8,  1.9] )
> I get what I would expect:  http://polar.sri.com/~ayoung/test2.png
>
> Thanks for you help.
> -andyy
>
> Gael Varoquaux wrote:
> >     Hi,
> >
> > Can you give a complete minimum example that does not work. If I put the
> > following code in a file and run python on it, I get the expected result.
> >
> > from scipy import *
> > from pylab import *
> > t = arange(0, 2.0, 0.1)
> > y = sin(2*pi*t)
> > tck = interpolate.splrep(t, y, s=0)
> > tnew = arange(0, 2.0, 0.01)
> > ynew = interpolate.splev(tnew, tck, der=0)
> > plot(t, y, 'o', tnew, ynew)
> > show()
> >
> >
> > Ga?l
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From stefan at sun.ac.za  Tue Oct 10 13:39:13 2006
From: stefan at sun.ac.za (Stefan van der Walt)
Date: Tue, 10 Oct 2006 19:39:13 +0200
Subject: [SciPy-user] Plotting an array
In-Reply-To: <452BC719.2030103@gmx.net>
References: <452BB87F.8000601@sri.com> <452BC719.2030103@gmx.net>
Message-ID: <20061010173913.GA13457@mentat.za.net>

On Tue, Oct 10, 2006 at 06:15:21PM +0200, Steve Schmerler wrote:
> >   t = arange(0, 2.0, 0.1)
> >   y = sin(2*pi*t)
> >   tck = interpolate.splrep(t, y, s=0)
> >   tnew = arange(0, 2.0, 0.01)
> >   ynew = interpolate.splev(tnew, tck, der=0)
> >   plot(t, y, 'o', tnew, ynew)
> >   show()
> > 
> 
> PS: Rather unimportant note to the scipy guys:
> 
> In [27]: len(tck)
> Out[27]: 3
> In [28]: type(tck)
> Out[28]: <type 'list'>
> 
> The splrep docstring says tck is a len 3 tuple, not a list ...

Fixed in SVN.

Cheers
St?fan


From jdhunter at ace.bsd.uchicago.edu  Tue Oct 10 13:48:47 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Tue, 10 Oct 2006 12:48:47 -0500
Subject: [SciPy-user] Plotting an array
In-Reply-To: <452BD8D3.2010500@sri.com> ("Andrew B. Young"'s message of
	"Tue, 10 Oct 2006 10:30:59 -0700")
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
	<452BD8D3.2010500@sri.com>
Message-ID: <87slhwcb9c.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "Andrew" == Andrew B Young <andrew.young at sri.com> writes:

    Andrew> Gael, The following little program-- -- test.py
    Andrew> ---------------------- | from scipy import arange, sin,
    Andrew> pi, interpolate | from pylab import plot, show, savefig |
    Andrew> t = arange(0, 2.0, 0.1) | plot(t) | savefig('test.png')

    Andrew> Produces the plot at http://polar.sri.com/~ayoung/test.png

    Andrew> Why does the plot "turn on" at one?  If I, plot( [ 0. ,
    Andrew> 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.  , 1.1,
    Andrew> 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9] ) I get what I
    Andrew> would expect: http://polar.sri.com/~ayoung/test2.png

This looks odd; one possibility is that you are mixing your numerix
packages.  Check you matplotlib rc setting.  If you are using a recent
scipy built on top of a recent numpy, you should setting you numerix
setting to numpy -- see http://matplotlib.sf.net/matplotlibrc

Alternatively, just use the matplotlib numerix namespace to insure
consistency

  from pylab import plot, show, savefig, nx
  t = nx.arange(0, 2.0, 0.1)
  plot(t)
  savefig('test.png')


JDH


From jdhunter at ace.bsd.uchicago.edu  Tue Oct 10 13:59:29 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Tue, 10 Oct 2006 12:59:29 -0500
Subject: [SciPy-user] Plotting an array
In-Reply-To: <87slhwcb9c.fsf@peds-pc311.bsd.uchicago.edu> (John Hunter's
	message of "Tue, 10 Oct 2006 12:48:47 -0500")
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
	<452BD8D3.2010500@sri.com>
	<87slhwcb9c.fsf@peds-pc311.bsd.uchicago.edu>
Message-ID: <87u02caw72.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "John" == John Hunter <jdhunter at ace.bsd.uchicago.edu> writes:

>>>>> "Andrew" == Andrew B Young <andrew.young at sri.com> writes:
    Andrew> Gael, The following little program-- -- test.py
    Andrew> ---------------------- | from scipy import arange, sin,
    Andrew> pi, interpolate | from pylab import plot, show, savefig |
    Andrew> t = arange(0, 2.0, 0.1) | plot(t) | savefig('test.png')

    Andrew> Produces the plot at http://polar.sri.com/~ayoung/test.png

    Andrew> Why does the plot "turn on" at one?  If I, plot( [ 0. ,
    Andrew> 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.  , 1.1,
    Andrew> 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9] ) I get what I
    Andrew> would expect: http://polar.sri.com/~ayoung/test2.png

    John> This looks odd; one possibility is that you are mixing your
    John> numerix packages.  Check you matplotlib rc setting.  If you

Yep, that's it.  I can reproduce it with an old Numeric and a newish
numpy/scipy.  The combination of versions below exposes the problem if
your rc setting is Numeric.  Either of the suggested changes I made in
my last post will fix your problem.

In [5]: import numpy; numpy.__version__ Out[5]: '0.9.6.2138'

In [6]: import scipy; scipy.__version__
Out[6]: '0.4.7.1617'

In [7]: import Numeric; Numeric.__version__
Out[7]: '23.1'


JDH


From pecora at anvil.nrl.navy.mil  Tue Oct 10 14:17:45 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Tue, 10 Oct 2006 14:17:45 -0400
Subject: [SciPy-user] Plotting an array
In-Reply-To: <20061010161945.GA7916@clipper.ens.fr>
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
Message-ID: <452BE3C9.9020109@anvil.nrl.navy.mil>

Gael Varoquaux wrote:
>     Hi,
>
> Can you give a complete minimum example that does not work. If I put the
> following code in a file and run python on it, I get the expected result.
>
> from scipy import *
> from pylab import *
> t = arange(0, 2.0, 0.1)
> y = sin(2*pi*t)
> tck = interpolate.splrep(t, y, s=0)
> tnew = arange(0, 2.0, 0.01)
> ynew = interpolate.splev(tnew, tck, der=0)
> plot(t, y, 'o', tnew, ynew)
> show()
>
>
> Ga?l
>   

When I do the above I get:

Traceback (most recent call last):
  File "/Users/louispecora/Code/python/test_folder/junk.py", line 18, in ?
    from scipy import *
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/linsolve/__init__.py", 
line 5, in ?
    from linsolve import *
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/linsolve/linsolve.py", 
line 1, in ?
    from scipy.sparse import isspmatrix_csc, isspmatrix_csr, isspmatrix, 
spdiags
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/__init__.py", 
line 5, in ?
    from sparse import *
  File 
"/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparse.py", 
line 12, in ?
    import sparsetools
ImportError: Failure linking new module: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so: 
Library not loaded: /usr/local/lib/libg2c.0.dylib
  Referenced from: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so
  Reason: image not found


I am missing sparsetools.so.   But I installed the SciPy superpack.  Is 
sparsetools.so not in that?

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From steveire at gmail.com  Tue Oct 10 14:33:19 2006
From: steveire at gmail.com (Stephen Kelly)
Date: Tue, 10 Oct 2006 19:33:19 +0100
Subject: [SciPy-user] How to calculate minors.
In-Reply-To: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>
References: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>
Message-ID: <18fbbe5a0610101133u4aa733c8h873704e0d59d0f01@mail.gmail.com>

I was looking for a way to do this a while ago too. I got it working by
multiplying the inverse of the matrix by the determinant, which gave me the
adjoint of the original matrix.

>>> from numpy import *
>>> from numpy.linalg import *
>>> a = array([[1, 2, 3],[4, 5, 6],[7, 8, 9]])
>>> adj = det(a) * inv(a)
>>> print adj
array([[ -3.,   6.,  -3.],
       [  6., -12.,   6.],
       [ -3.,   6.,  -3.]])

So you can access the diagonal elements now to get the minors. It's a work
around, and I think it should be built in to scipy properly.

Steve.

On 10/10/06, Armando Serrano Lombillo <arserlom at gmail.com> wrote:
>
> Hello, is there any way to easily calculate minors of matrixes with
> scipy/numpy.
>
> For example if we have matrix a:
> [[1 2 3]
>  [4 5 6]
>  [7 8 9]]
>
> then minor(a,0) should be the same as det([[5,6],[8,9]]) and minor (a,1)
> should be the same as det([[1,3],[7,9]]).
>
> Armando.
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
>
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From oliphant.travis at ieee.org  Tue Oct 10 14:35:39 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Tue, 10 Oct 2006 12:35:39 -0600
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
Message-ID: <452BE7FB.7000509@ieee.org>

Ryan Krauss wrote:
> I am rethinking an algorithm for unwrapping phase data from arctan2
> for a vector of complex numbers (coming from lti models of feedback
> control systems).  I had written something a while ago using weave,
> but my old code causes seg faults with a recent scipy update.  So, I
> am rethinking the algorithm.

There is already a phase unwrapping algorithm in NumPy for 1-d data 
called unwrap.

numpy.unwrap(b) seems to work fine on the second column of the data you 
posted.

Best,

-Travis



From ryanlists at gmail.com  Tue Oct 10 14:43:31 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 13:43:31 -0500
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <452BE7FB.7000509@ieee.org>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
	<452BE7FB.7000509@ieee.org>
Message-ID: <c5b438120610101143i53c6ef6n1d72ff0becd40b59@mail.gmail.com>

Thanks Travis.

I looked in scipy.signal and when I didn't see, I just assumed it didn't exist.

I was just starting to make good progess on my FORTRAN version too.....

I may need to revisit this when I need more control over messy
experimental data.  Is there a tricky in-place way to calculate the
difference between a vector and itself shift by 1 or more elements?

Thanks,

Ryan

On 10/10/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> Ryan Krauss wrote:
> > I am rethinking an algorithm for unwrapping phase data from arctan2
> > for a vector of complex numbers (coming from lti models of feedback
> > control systems).  I had written something a while ago using weave,
> > but my old code causes seg faults with a recent scipy update.  So, I
> > am rethinking the algorithm.
>
> There is already a phase unwrapping algorithm in NumPy for 1-d data
> called unwrap.
>
> numpy.unwrap(b) seems to work fine on the second column of the data you
> posted.
>
> Best,
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From oliphant.travis at ieee.org  Tue Oct 10 14:52:49 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Tue, 10 Oct 2006 12:52:49 -0600
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <c5b438120610101143i53c6ef6n1d72ff0becd40b59@mail.gmail.com>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>	<452BE7FB.7000509@ieee.org>
	<c5b438120610101143i53c6ef6n1d72ff0becd40b59@mail.gmail.com>
Message-ID: <452BEC01.1000804@ieee.org>

Ryan Krauss wrote:
> Thanks Travis.
>
> I looked in scipy.signal and when I didn't see, I just assumed it didn't exist.
>
> I was just starting to make good progess on my FORTRAN version too.....
>
>   
The FORTRAN version would be faster and not require memory use.  The 
NumPy version creates the difference vector, finds discontinuites and 
forms a correction vector that is cumsummed and added to the original.
> I may need to revisit this when I need more control over messy
> experimental data.  Is there a tricky in-place way to calculate the
>   
> difference between a vector and itself shift by 1 or more elements?
>   

c[:-1] -= c[1:]  # shift-by-one
c[:-2] -= c[2:]  # shift-by-two

etc.

This will leave un-changed the last elements of the array.

-Travis



From ryanlists at gmail.com  Tue Oct 10 14:57:09 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 13:57:09 -0500
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <452BEC01.1000804@ieee.org>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
	<452BE7FB.7000509@ieee.org>
	<c5b438120610101143i53c6ef6n1d72ff0becd40b59@mail.gmail.com>
	<452BEC01.1000804@ieee.org>
Message-ID: <c5b438120610101157r188a53f9yb0c39d87157aad41@mail.gmail.com>

For this simple problem, my FORTRAN version is running about 30 times
faster, but neither takes very long:

Python vector time=0.000700950622559
FORTRAN time=2.09808349609e-05
ratio=33.4090909091
Numpy.unwrap time=0.000639915466309
Numpy ratio=30.5

I will probably finish the FORTRAN version since it is almost done.

Ryan

On 10/10/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> Ryan Krauss wrote:
> > Thanks Travis.
> >
> > I looked in scipy.signal and when I didn't see, I just assumed it didn't exist.
> >
> > I was just starting to make good progess on my FORTRAN version too.....
> >
> >
> The FORTRAN version would be faster and not require memory use.  The
> NumPy version creates the difference vector, finds discontinuites and
> forms a correction vector that is cumsummed and added to the original.
> > I may need to revisit this when I need more control over messy
> > experimental data.  Is there a tricky in-place way to calculate the
> >
> > difference between a vector and itself shift by 1 or more elements?
> >
>
> c[:-1] -= c[1:]  # shift-by-one
> c[:-2] -= c[2:]  # shift-by-two
>
> etc.
>
> This will leave un-changed the last elements of the array.
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From jorgen.stenarson at bostream.nu  Tue Oct 10 16:27:31 2006
From: jorgen.stenarson at bostream.nu (=?ISO-8859-1?Q?J=F6rgen_Stenarson?=)
Date: Tue, 10 Oct 2006 22:27:31 +0200
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
Message-ID: <452C0233.3070600@bostream.nu>

Ryan,

I don't have any tested code on this computer but here is pseudo code of 
how I remember doing it:

phasestep=arg(data[1:]/data[:-1])
totalphase=arg(data[0])+accumulate(phasestep)

where accumulate should give [0, phasestep[0], 
phasestep[0]+phasestep[1], ...]
this will of course only work as long as the phase difference between 
neighbouring points is small enough, but that is probably true for any 
algorithm.

/J?rgen Stenarson

Ryan Krauss skrev:
> I am rethinking an algorithm for unwrapping phase data from arctan2
> for a vector of complex numbers (coming from lti models of feedback
> control systems).  I had written something a while ago using weave,
> but my old code causes seg faults with a recent scipy update.  So, I
> am rethinking the algorithm.
> 
> The problem occurs when either because of noise or just the definition
> of the inverse tangent, their are discontinuities in the phase (which
> is coming from arctan2(imag(vector), real(vector)).  For example, in
> the attached plot and data file, there is a point where the phase
> passes through -180 degrees.  arctan2 jumps to returning +180, +175
> etc, when it makes a pretty plot and makes more sense to me to convert
> +175 to -185.  What I had done previously is write a for loop that
> compares the current value of the phase to the value at the previous
> index (i.e. if phase[i]-phase[-1]>300 or if phase[i]-phase[i-1]<-300)
> to find the discontinuities.  Is there a cleaner/faster way to do
> this?  (I had done it in weave and will probably now do it in f2py for
> comparison on speeds).  I have attached/included a first attempt at an
> algorithm that is more vectorized.  But is there a fast, easy way to
> compare a vector to the same vector shift one element up or down?
> Right now I am doing this
> 
> phase2=r_[phase[0:1],phase[0:-1]]
> 
> to shift the vector (and reuse the first element so there isn't a jump
> from phase[-1] to phase[0] which may legitimately be far apart).
> 
> Has anyone else already done this?  Are there obvious bottlenecks with
> the algorithm?
> 
> Thanks for your thoughts,
> 
> Ryan
> 
> =====================================
> from scipy import arange, io, r_
> from pylab import show, figure, subplot, clf, cla, semilogx, xlabel,
> ylabel, legend, xlim
> 
> import copy
> 
> data=io.read_array('phase_data.txt')
> f=data[:,0]
> phase=data[:,1]
> figure(1)
> clf()
> startphase=copy.copy(phase)
> semilogx(f,startphase)
> 
> keepgoing=1
> 
> inds=arange(0,len(phase))
> 
> while keepgoing:
>    phase2=r_[phase[0:1],phase[0:-1]]#artificially repeat the first element
>    diff=phase-phase2
>    jumps=inds[abs(diff)>250]
>    keepgoing=jumps.any()
>    if not keepgoing:
>        break
>    ind=jumps.min()
>    if diff[ind]>0:
>        phase[ind:]-=360
>    else:
>        phase[ind:]+=360
> 
> 
> semilogx(f,phase,'r--')
> 
> legend(['Before unwrapping','after unwrapping'],2)
> 
> xlim([1,30])
> 
> show()
> 
> 
> ------------------------------------------------------------------------
> 
> 1.30952e+00 -9.60103e+01
> 1.33333e+00 -9.61655e+01
> 1.35714e+00 -9.63309e+01
> 1.38095e+00 -9.65099e+01
> 1.40476e+00 -9.67070e+01
> 1.42857e+00 -9.69287e+01
> 1.45238e+00 -9.71850e+01
> 1.47619e+00 -9.74911e+01
> 1.50000e+00 -9.78711e+01
> 1.52381e+00 -9.83629e+01
> 1.54762e+00 -9.90266e+01
> 1.57143e+00 -9.99476e+01
> 1.59524e+00 -1.01203e+02
> 1.61905e+00 -1.02674e+02
> 1.64286e+00 -1.03685e+02
> 1.66667e+00 -1.03370e+02
> 1.69048e+00 -1.02078e+02
> 1.71429e+00 -1.00795e+02
> 1.73810e+00 -9.98998e+01
> 1.76190e+00 -9.93507e+01
> 1.78571e+00 -9.90331e+01
> 1.80952e+00 -9.88608e+01
> 1.83333e+00 -9.87801e+01
> 1.85714e+00 -9.87585e+01
> 1.88095e+00 -9.87760e+01
> 1.90476e+00 -9.88203e+01
> 1.92857e+00 -9.88835e+01
> 1.95238e+00 -9.89604e+01
> 1.97619e+00 -9.90475e+01
> 2.00000e+00 -9.91423e+01
> 2.02381e+00 -9.92431e+01
> 2.04762e+00 -9.93486e+01
> 2.07143e+00 -9.94580e+01
> 2.09524e+00 -9.95705e+01
> 2.11905e+00 -9.96857e+01
> 2.14286e+00 -9.98032e+01
> 2.16667e+00 -9.99227e+01
> 2.19048e+00 -1.00044e+02
> 2.21429e+00 -1.00167e+02
> 2.23810e+00 -1.00291e+02
> 2.26190e+00 -1.00416e+02
> 2.28571e+00 -1.00543e+02
> 2.30952e+00 -1.00671e+02
> 2.33333e+00 -1.00800e+02
> 2.35714e+00 -1.00930e+02
> 2.38095e+00 -1.01061e+02
> 2.40476e+00 -1.01193e+02
> 2.42857e+00 -1.01326e+02
> 2.45238e+00 -1.01460e+02
> 2.47619e+00 -1.01595e+02
> 2.50000e+00 -1.01731e+02
> 2.52381e+00 -1.01867e+02
> 2.54762e+00 -1.02005e+02
> 2.57143e+00 -1.02143e+02
> 2.59524e+00 -1.02283e+02
> 2.61905e+00 -1.02423e+02
> 2.64286e+00 -1.02564e+02
> 2.66667e+00 -1.02706e+02
> 2.69048e+00 -1.02849e+02
> 2.71429e+00 -1.02993e+02
> 2.73810e+00 -1.03138e+02
> 2.76190e+00 -1.03284e+02
> 2.78571e+00 -1.03431e+02
> 2.80952e+00 -1.03579e+02
> 2.83333e+00 -1.03728e+02
> 2.85714e+00 -1.03877e+02
> 2.88095e+00 -1.04028e+02
> 2.90476e+00 -1.04180e+02
> 2.92857e+00 -1.04333e+02
> 2.95238e+00 -1.04487e+02
> 2.97619e+00 -1.04642e+02
> 3.00000e+00 -1.04798e+02
> 3.02381e+00 -1.04955e+02
> 3.04762e+00 -1.05113e+02
> 3.07143e+00 -1.05272e+02
> 3.09524e+00 -1.05433e+02
> 3.11905e+00 -1.05595e+02
> 3.14286e+00 -1.05758e+02
> 3.16667e+00 -1.05922e+02
> 3.19048e+00 -1.06087e+02
> 3.21429e+00 -1.06253e+02
> 3.23810e+00 -1.06421e+02
> 3.26190e+00 -1.06590e+02
> 3.28571e+00 -1.06761e+02
> 3.30952e+00 -1.06932e+02
> 3.33333e+00 -1.07105e+02
> 3.35714e+00 -1.07280e+02
> 3.38095e+00 -1.07456e+02
> 3.40476e+00 -1.07633e+02
> 3.42857e+00 -1.07812e+02
> 3.45238e+00 -1.07992e+02
> 3.47619e+00 -1.08173e+02
> 3.50000e+00 -1.08357e+02
> 3.52381e+00 -1.08541e+02
> 3.54762e+00 -1.08728e+02
> 3.57143e+00 -1.08916e+02
> 3.59524e+00 -1.09105e+02
> 3.61905e+00 -1.09297e+02
> 3.64286e+00 -1.09490e+02
> 3.66667e+00 -1.09684e+02
> 3.69048e+00 -1.09881e+02
> 3.71429e+00 -1.10079e+02
> 3.73810e+00 -1.10280e+02
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> 1.44762e+01 -1.31009e+02
> 1.45000e+01 -1.31086e+02
> 1.45238e+01 -1.31164e+02
> 1.45476e+01 -1.31241e+02
> 1.45714e+01 -1.31319e+02
> 1.45952e+01 -1.31396e+02
> 1.46190e+01 -1.31473e+02
> 1.46429e+01 -1.31550e+02
> 1.46667e+01 -1.31627e+02
> 1.46905e+01 -1.31704e+02
> 1.47143e+01 -1.31780e+02
> 1.47381e+01 -1.31857e+02
> 1.47619e+01 -1.31933e+02
> 1.47857e+01 -1.32009e+02
> 1.48095e+01 -1.32085e+02
> 1.48333e+01 -1.32161e+02
> 1.48571e+01 -1.32237e+02
> 1.48810e+01 -1.32312e+02
> 1.49048e+01 -1.32388e+02
> 1.49286e+01 -1.32463e+02
> 1.49524e+01 -1.32538e+02
> 1.49762e+01 -1.32613e+02
> 1.50000e+01 -1.32688e+02
> 1.50238e+01 -1.32763e+02
> 1.50476e+01 -1.32838e+02
> 1.50714e+01 -1.32912e+02
> 1.50952e+01 -1.32987e+02
> 1.51190e+01 -1.33061e+02
> 1.51429e+01 -1.33135e+02
> 1.51667e+01 -1.33209e+02
> 1.51905e+01 -1.33283e+02
> 1.52143e+01 -1.33357e+02
> 1.52381e+01 -1.33431e+02
> 1.52619e+01 -1.33504e+02
> 1.52857e+01 -1.33578e+02
> 1.53095e+01 -1.33651e+02
> 1.53333e+01 -1.33724e+02
> 1.53571e+01 -1.33797e+02
> 1.53810e+01 -1.33870e+02
> 1.54048e+01 -1.33943e+02
> 1.54286e+01 -1.34016e+02
> 1.54524e+01 -1.34088e+02
> 1.54762e+01 -1.34161e+02
> 1.55000e+01 -1.34233e+02
> 1.55238e+01 -1.34306e+02
> 1.55476e+01 -1.34378e+02
> 1.55714e+01 -1.34450e+02
> 1.55952e+01 -1.34521e+02
> 1.56190e+01 -1.34593e+02
> 1.56429e+01 -1.34665e+02
> 1.56667e+01 -1.34736e+02
> 1.56905e+01 -1.34808e+02
> 1.57143e+01 -1.34879e+02
> 1.57381e+01 -1.34950e+02
> 1.57619e+01 -1.35021e+02
> 1.57857e+01 -1.35092e+02
> 1.58095e+01 -1.35163e+02
> 1.58333e+01 -1.35234e+02
> 1.58571e+01 -1.35305e+02
> 1.58810e+01 -1.35375e+02
> 1.59048e+01 -1.35445e+02
> 1.59286e+01 -1.35516e+02
> 1.59524e+01 -1.35586e+02
> 1.59762e+01 -1.35656e+02
> 1.60000e+01 -1.35726e+02
> 1.60238e+01 -1.35796e+02
> 1.60476e+01 -1.35865e+02
> 1.60714e+01 -1.35935e+02
> 1.60952e+01 -1.36005e+02
> 1.61190e+01 -1.36074e+02
> 1.61429e+01 -1.36143e+02
> 1.61667e+01 -1.36213e+02
> 1.61905e+01 -1.36282e+02
> 1.62143e+01 -1.36351e+02
> 1.62381e+01 -1.36419e+02
> 1.62619e+01 -1.36488e+02
> 1.62857e+01 -1.36557e+02
> 1.63095e+01 -1.36626e+02
> 1.63333e+01 -1.36694e+02
> 1.63571e+01 -1.36762e+02
> 1.63810e+01 -1.36831e+02
> 1.64048e+01 -1.36899e+02
> 1.64286e+01 -1.36967e+02
> 1.64524e+01 -1.37035e+02
> 1.64762e+01 -1.37103e+02
> 1.65000e+01 -1.37170e+02
> 1.65238e+01 -1.37238e+02
> 1.65476e+01 -1.37306e+02
> 1.65714e+01 -1.37373e+02
> 1.65952e+01 -1.37440e+02
> 1.66190e+01 -1.37508e+02
> 1.66429e+01 -1.37575e+02
> 1.66667e+01 -1.37642e+02
> 1.66905e+01 -1.37709e+02
> 1.67143e+01 -1.37776e+02
> 1.67381e+01 -1.37842e+02
> 1.67619e+01 -1.37909e+02
> 1.67857e+01 -1.37976e+02
> 1.68095e+01 -1.38042e+02
> 1.68333e+01 -1.38108e+02
> 1.68571e+01 -1.38175e+02
> 1.68810e+01 -1.38241e+02
> 1.69048e+01 -1.38307e+02
> 1.69286e+01 -1.38373e+02
> 1.69524e+01 -1.38439e+02
> 1.69762e+01 -1.38505e+02
> 1.70000e+01 -1.38570e+02
> 1.70238e+01 -1.38636e+02
> 1.70476e+01 -1.38701e+02
> 1.70714e+01 -1.38767e+02
> 1.70952e+01 -1.38832e+02
> 1.71190e+01 -1.38898e+02
> 1.71429e+01 -1.38963e+02
> 1.71667e+01 -1.39028e+02
> 1.71905e+01 -1.39093e+02
> 1.72143e+01 -1.39158e+02
> 1.72381e+01 -1.39222e+02
> 1.72619e+01 -1.39287e+02
> 1.72857e+01 -1.39352e+02
> 1.73095e+01 -1.39416e+02
> 1.73333e+01 -1.39481e+02
> 1.73571e+01 -1.39545e+02
> 1.73810e+01 -1.39609e+02
> 1.74048e+01 -1.39673e+02
> 1.74286e+01 -1.39737e+02
> 1.74524e+01 -1.39801e+02
> 1.74762e+01 -1.39865e+02
> 1.75000e+01 -1.39929e+02
> 1.75238e+01 -1.39993e+02
> 1.75476e+01 -1.40056e+02
> 1.75714e+01 -1.40120e+02
> 1.75952e+01 -1.40183e+02
> 1.76190e+01 -1.40247e+02
> 1.76429e+01 -1.40310e+02
> 1.76667e+01 -1.40373e+02
> 1.76905e+01 -1.40436e+02
> 1.77143e+01 -1.40499e+02
> 1.77381e+01 -1.40562e+02
> 1.77619e+01 -1.40625e+02
> 1.77857e+01 -1.40688e+02
> 1.78095e+01 -1.40751e+02
> 1.78333e+01 -1.40813e+02
> 1.78571e+01 -1.40876e+02
> 1.78810e+01 -1.40938e+02
> 1.79048e+01 -1.41001e+02
> 1.79286e+01 -1.41063e+02
> 1.79524e+01 -1.41125e+02
> 1.79762e+01 -1.41187e+02
> 1.80000e+01 -1.41249e+02
> 1.80238e+01 -1.41311e+02
> 1.80476e+01 -1.41373e+02
> 1.80714e+01 -1.41435e+02
> 1.80952e+01 -1.41496e+02
> 1.81190e+01 -1.41558e+02
> 1.81429e+01 -1.41619e+02
> 1.81667e+01 -1.41681e+02
> 1.81905e+01 -1.41742e+02
> 1.82143e+01 -1.41803e+02
> 1.82381e+01 -1.41864e+02
> 1.82619e+01 -1.41926e+02
> 1.82857e+01 -1.41987e+02
> 1.83095e+01 -1.42047e+02
> 1.83333e+01 -1.42108e+02
> 1.83571e+01 -1.42169e+02
> 1.83810e+01 -1.42230e+02
> 1.84048e+01 -1.42290e+02
> 1.84286e+01 -1.42351e+02
> 1.84524e+01 -1.42411e+02
> 1.84762e+01 -1.42471e+02
> 1.85000e+01 -1.42532e+02
> 1.85238e+01 -1.42592e+02
> 1.85476e+01 -1.42652e+02
> 1.85714e+01 -1.42712e+02
> 1.85952e+01 -1.42771e+02
> 1.86190e+01 -1.42831e+02
> 1.86429e+01 -1.42891e+02
> 1.86667e+01 -1.42951e+02
> 1.86905e+01 -1.43010e+02
> 1.87143e+01 -1.43069e+02
> 1.87381e+01 -1.43129e+02
> 1.87619e+01 -1.43188e+02
> 1.87857e+01 -1.43247e+02
> 1.88095e+01 -1.43306e+02
> 1.88333e+01 -1.43365e+02
> 1.88571e+01 -1.43424e+02
> 1.88810e+01 -1.43483e+02
> 1.89048e+01 -1.43542e+02
> 1.89286e+01 -1.43600e+02
> 1.89524e+01 -1.43659e+02
> 1.89762e+01 -1.43717e+02
> 1.90000e+01 -1.43776e+02
> 1.90238e+01 -1.43834e+02
> 1.90476e+01 -1.43892e+02
> 1.90714e+01 -1.43950e+02
> 1.90952e+01 -1.44008e+02
> 1.91190e+01 -1.44066e+02
> 1.91429e+01 -1.44123e+02
> 1.91667e+01 -1.44181e+02
> 1.91905e+01 -1.44239e+02
> 1.92143e+01 -1.44296e+02
> 1.92381e+01 -1.44353e+02
> 1.92619e+01 -1.44411e+02
> 1.92857e+01 -1.44468e+02
> 1.93095e+01 -1.44525e+02
> 1.93333e+01 -1.44582e+02
> 1.93571e+01 -1.44639e+02
> 1.93810e+01 -1.44695e+02
> 1.94048e+01 -1.44752e+02
> 1.94286e+01 -1.44808e+02
> 1.94524e+01 -1.44865e+02
> 1.94762e+01 -1.44921e+02
> 1.95000e+01 -1.44977e+02
> 1.95238e+01 -1.45033e+02
> 1.95476e+01 -1.45089e+02
> 1.95714e+01 -1.45145e+02
> 1.95952e+01 -1.45201e+02
> 1.96190e+01 -1.45256e+02
> 1.96429e+01 -1.45312e+02
> 1.96667e+01 -1.45367e+02
> 1.96905e+01 -1.45422e+02
> 1.97143e+01 -1.45477e+02
> 1.97381e+01 -1.45532e+02
> 1.97619e+01 -1.45587e+02
> 1.97857e+01 -1.45642e+02
> 1.98095e+01 -1.45696e+02
> 1.98333e+01 -1.45751e+02
> 1.98571e+01 -1.45805e+02
> 1.98810e+01 -1.45859e+02
> 1.99048e+01 -1.45913e+02
> 1.99286e+01 -1.45967e+02
> 1.99524e+01 -1.46021e+02
> 1.99762e+01 -1.46075e+02
> 2.00000e+01 -1.46128e+02
> 2.00238e+01 -1.46181e+02
> 2.00476e+01 -1.46235e+02
> 2.00714e+01 -1.46288e+02
> 2.00952e+01 -1.46341e+02
> 2.01190e+01 -1.46393e+02
> 2.01429e+01 -1.46446e+02
> 2.01667e+01 -1.46498e+02
> 2.01905e+01 -1.46551e+02
> 2.02143e+01 -1.46603e+02
> 2.02381e+01 -1.46655e+02
> 2.02619e+01 -1.46706e+02
> 2.02857e+01 -1.46758e+02
> 2.03095e+01 -1.46810e+02
> 2.03333e+01 -1.46861e+02
> 2.03571e+01 -1.46912e+02
> 2.03810e+01 -1.46963e+02
> 2.04048e+01 -1.47014e+02
> 2.04286e+01 -1.47064e+02
> 2.04524e+01 -1.47115e+02
> 2.04762e+01 -1.47165e+02
> 2.05000e+01 -1.47215e+02
> 2.05238e+01 -1.47265e+02
> 2.05476e+01 -1.47315e+02
> 2.05714e+01 -1.47364e+02
> 2.05952e+01 -1.47414e+02
> 2.06190e+01 -1.47463e+02
> 2.06429e+01 -1.47512e+02
> 2.06667e+01 -1.47560e+02
> 2.06905e+01 -1.47609e+02
> 2.07143e+01 -1.47657e+02
> 2.07381e+01 -1.47706e+02
> 2.07619e+01 -1.47754e+02
> 2.07857e+01 -1.47801e+02
> 2.08095e+01 -1.47849e+02
> 2.08333e+01 -1.47896e+02
> 2.08571e+01 -1.47944e+02
> 2.08810e+01 -1.47991e+02
> 2.09048e+01 -1.48037e+02
> 2.09286e+01 -1.48084e+02
> 2.09524e+01 -1.48130e+02
> 2.09762e+01 -1.48176e+02
> 2.10000e+01 -1.48222e+02
> 2.10238e+01 -1.48268e+02
> 2.10476e+01 -1.48314e+02
> 2.10714e+01 -1.48359e+02
> 2.10952e+01 -1.48404e+02
> 2.11190e+01 -1.48449e+02
> 2.11429e+01 -1.48494e+02
> 2.11667e+01 -1.48538e+02
> 2.11905e+01 -1.48583e+02
> 2.12143e+01 -1.48627e+02
> 2.12381e+01 -1.48671e+02
> 2.12619e+01 -1.48714e+02
> 2.12857e+01 -1.48758e+02
> 2.13095e+01 -1.48801e+02
> 2.13333e+01 -1.48844e+02
> 2.13571e+01 -1.48887e+02
> 2.13810e+01 -1.48930e+02
> 2.14048e+01 -1.48972e+02
> 2.14286e+01 -1.49014e+02
> 2.14524e+01 -1.49056e+02
> 2.14762e+01 -1.49098e+02
> 2.15000e+01 -1.49140e+02
> 2.15238e+01 -1.49181e+02
> 
> 
> ------------------------------------------------------------------------
> 
> 
> ------------------------------------------------------------------------
> 
> from scipy import arange, io, r_
> from pylab import show, figure, subplot, clf, cla, semilogx, xlabel, ylabel, legend, xlim
> 
> import copy
> 
> data=io.read_array('phase_data.txt')
> f=data[:,0]
> phase=data[:,1]
> figure(1)
> clf()
> startphase=copy.copy(phase)
> semilogx(f,startphase)
> 
> keepgoing=1
> 
> inds=arange(0,len(phase))
>     
> while keepgoing:
>     phase2=r_[phase[0:1],phase[0:-1]]#artificially repeat the first element
>     diff=phase-phase2
>     jumps=inds[abs(diff)>250]
>     keepgoing=jumps.any()
>     if not keepgoing:
>         break
>     ind=jumps.min()
>     if diff[ind]>0:
>         phase[ind:]-=360
>     else:
>         phase[ind:]+=360
>     
> 
> semilogx(f,phase,'r--')
> 
> legend(['Before unwrapping','after unwrapping'],2)
> 
> xlim([1,30])
> 
> show()
> 
> 
> ------------------------------------------------------------------------
> 
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user



From bryan at cole.uklinux.net  Tue Oct 10 16:55:49 2006
From: bryan at cole.uklinux.net (Bryan Cole)
Date: Tue, 10 Oct 2006 21:55:49 +0100
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
Message-ID: <1160513747.8450.167.camel@pc1.cole.uklinux.net>

I do this quite a lot in the context of FFTs.
try:

def unwrap(thetaArray):
    """takes an array of theta values in degrees
    returns the data in unwrapped form"""
    diff = zeros_like(thetaArray)
    diff[1:] = thetaArray[1:] - thetaArray[:-1]
    upSteps = diff > 180
    downSteps = diff < -180
    shift = cumsum(upSteps) - cumsum(downSteps)
    return thetaArray - 360*shift

Obviously, a Weave version will be a lot faster, but this is at least 
fully vectorised, so it's not bad.

BC

On Tue, 2006-10-10 at 12:32 -0500, Ryan Krauss wrote:
> I am rethinking an algorithm for unwrapping phase data from arctan2
> for a vector of complex numbers (coming from lti models of feedback
> control systems).  I had written something a while ago using weave,
> but my old code causes seg faults with a recent scipy update.  So, I
> am rethinking the algorithm.
> 
> The problem occurs when either because of noise or just the definition
> of the inverse tangent, their are discontinuities in the phase (which
> is coming from arctan2(imag(vector), real(vector)).  For example, in
> the attached plot and data file, there is a point where the phase
> passes through -180 degrees.  arctan2 jumps to returning +180, +175
> etc, when it makes a pretty plot and makes more sense to me to convert
> +175 to -185.  What I had done previously is write a for loop that
> compares the current value of the phase to the value at the previous
> index (i.e. if phase[i]-phase[-1]>300 or if phase[i]-phase[i-1]<-300)
> to find the discontinuities.  Is there a cleaner/faster way to do
> this?  (I had done it in weave and will probably now do it in f2py for
> comparison on speeds).  I have attached/included a first attempt at an
> algorithm that is more vectorized.  But is there a fast, easy way to
> compare a vector to the same vector shift one element up or down?
> Right now I am doing this
> 
> phase2=r_[phase[0:1],phase[0:-1]]
> 
> to shift the vector (and reuse the first element so there isn't a jump
> from phase[-1] to phase[0] which may legitimately be far apart).
> 
> Has anyone else already done this?  Are there obvious bottlenecks with
> the algorithm?
> 
> Thanks for your thoughts,
> 
> Ryan
> 
> =====================================
> from scipy import arange, io, r_
> from pylab import show, figure, subplot, clf, cla, semilogx, xlabel,
> ylabel, legend, xlim
> 
> import copy
> 
> data=io.read_array('phase_data.txt')
> f=data[:,0]
> phase=data[:,1]
> figure(1)
> clf()
> startphase=copy.copy(phase)
> semilogx(f,startphase)
> 
> keepgoing=1
> 
> inds=arange(0,len(phase))
> 
> while keepgoing:
>     phase2=r_[phase[0:1],phase[0:-1]]#artificially repeat the first element
>     diff=phase-phase2
>     jumps=inds[abs(diff)>250]
>     keepgoing=jumps.any()
>     if not keepgoing:
>         break
>     ind=jumps.min()
>     if diff[ind]>0:
>         phase[ind:]-=360
>     else:
>         phase[ind:]+=360
> 
> 
> semilogx(f,phase,'r--')
> 
> legend(['Before unwrapping','after unwrapping'],2)
> 
> xlim([1,30])
> 
> show()
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user




From andrew.young at sri.com  Tue Oct 10 16:58:54 2006
From: andrew.young at sri.com (Andrew B. Young)
Date: Tue, 10 Oct 2006 13:58:54 -0700
Subject: [SciPy-user] Plotting an array
In-Reply-To: <87u02caw72.fsf@peds-pc311.bsd.uchicago.edu>
References: <452BB87F.8000601@sri.com> <20061010161945.GA7916@clipper.ens.fr>
	<452BD8D3.2010500@sri.com>
	<87slhwcb9c.fsf@peds-pc311.bsd.uchicago.edu>
	<87u02caw72.fsf@peds-pc311.bsd.uchicago.edu>
Message-ID: <452C098E.5090500@sri.com>

Thanks John!
-andyy

John Hunter wrote:
>>>>>> "John" == John Hunter <jdhunter at ace.bsd.uchicago.edu> writes:
>>>>>>             
>
>   
>>>>>> "Andrew" == Andrew B Young <andrew.young at sri.com> writes:
>>>>>>             
>     Andrew> Gael, The following little program-- -- test.py
>     Andrew> ---------------------- | from scipy import arange, sin,
>     Andrew> pi, interpolate | from pylab import plot, show, savefig |
>     Andrew> t = arange(0, 2.0, 0.1) | plot(t) | savefig('test.png')
>
>     Andrew> Produces the plot at http://polar.sri.com/~ayoung/test.png
>
>     Andrew> Why does the plot "turn on" at one?  If I, plot( [ 0. ,
>     Andrew> 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1.  , 1.1,
>     Andrew> 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9] ) I get what I
>     Andrew> would expect: http://polar.sri.com/~ayoung/test2.png
>
>     John> This looks odd; one possibility is that you are mixing your
>     John> numerix packages.  Check you matplotlib rc setting.  If you
>
> Yep, that's it.  I can reproduce it with an old Numeric and a newish
> numpy/scipy.  The combination of versions below exposes the problem if
> your rc setting is Numeric.  Either of the suggested changes I made in
> my last post will fix your problem.
>
> In [5]: import numpy; numpy.__version__ Out[5]: '0.9.6.2138'
>
> In [6]: import scipy; scipy.__version__
> Out[6]: '0.4.7.1617'
>
> In [7]: import Numeric; Numeric.__version__
> Out[7]: '23.1'
>
>
> JDH
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   



From pecora at anvil.nrl.navy.mil  Tue Oct 10 17:14:07 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Tue, 10 Oct 2006 17:14:07 -0400
Subject: [SciPy-user]  Missing library will not allow SciPy to load.
Message-ID: <452C0D1F.9060301@anvil.nrl.navy.mil>

When I do

from scipy import *

I get the following error:

ImportError: Failure linking new module: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so: 
Library not loaded: /usr/local/lib/libg2c.0.dylib
  Referenced from: 
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so
  Reason: image not found


It seems I'm missing  libg2c.0.dylib.  I just installed the SciPy 
SuperPack.  I guess it wasn't in there or was supposed to be installed 
from some other package.  Does anyone know about this? 


-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From peridot.faceted at gmail.com  Tue Oct 10 17:14:07 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Tue, 10 Oct 2006 17:14:07 -0400
Subject: [SciPy-user] How to calculate minors.
In-Reply-To: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>
References: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>
Message-ID: <ce557a360610101414u7c8319a7r7a305b5e0b2ffca1@mail.gmail.com>

On 10/10/06, Armando Serrano Lombillo <arserlom at gmail.com> wrote:
> Hello, is there any way to easily calculate minors of matrixes with
> scipy/numpy.
>
> For example if we have matrix a:
> [[1 2 3]
>  [4 5 6]
>  [7 8 9]]
>
> then minor(a,0) should be the same as det([[5,6],[8,9]]) and minor (a,1)
> should be the same as det([[1,3],[7,9]]).
>
> Armando.

You can always you fancy indexing to chop out the row and column you
are not interested in and take the determinant (with appropriate
signs).

Maybe a bit complicated, but if you want a single minor it's good
enough to implement minor() in pure python.

A. M. Archibald


From ryanlists at gmail.com  Tue Oct 10 17:58:13 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Tue, 10 Oct 2006 16:58:13 -0500
Subject: [SciPy-user] phase wrapping algorithm
In-Reply-To: <1160513747.8450.167.camel@pc1.cole.uklinux.net>
References: <c5b438120610101032j297f2499sa1b086856d0ca12a@mail.gmail.com>
	<1160513747.8450.167.camel@pc1.cole.uklinux.net>
Message-ID: <c5b438120610101458y6809715bh9f013b816ad50853@mail.gmail.com>

This probably wasn't worth the ammount of time I spent on it, but I'll
submit it to the list in case anyone else is curious or can learn from
it.  This is a bit of a contrived example, but I often find with
experimental data that I have significant noise at high and low
frequncies, so I want to start the phase wrapping in the middle at a
known good point.  So I wrote a phase wrapping algorithm that breaks
the data into two vectors, phase wraps the one above the middle
frequency in the normal way, but needs to step through the one below
the middle frequency in reverse.  The FORTRAN and Python versions are
attached.  phasewrap.py contains the Python implementation and
includes a function to compare the two.  Typical output includes the
attached plot and these times:

FORTRAN time=0.00100302696228
Numpy.unwrap time=0.00893402099609
Numpy/FORTRAN time ratio=8.90705966247
Bryan Cole time=0.00318098068237
Bryan/FORTRAN time ratio=3.17138103161


Bryan's algorithm is exactly the kind of vectorized thinking that I
need to learn how to do.  I think in for loops; I don't know why.

Thanks to everyone who contributed to this,

Ryan

On 10/10/06, Bryan Cole <bryan at cole.uklinux.net> wrote:
> I do this quite a lot in the context of FFTs.
> try:
>
> def unwrap(thetaArray):
>     """takes an array of theta values in degrees
>     returns the data in unwrapped form"""
>     diff = zeros_like(thetaArray)
>     diff[1:] = thetaArray[1:] - thetaArray[:-1]
>     upSteps = diff > 180
>     downSteps = diff < -180
>     shift = cumsum(upSteps) - cumsum(downSteps)
>     return thetaArray - 360*shift
>
> Obviously, a Weave version will be a lot faster, but this is at least
> fully vectorised, so it's not bad.
>
> BC
>
> On Tue, 2006-10-10 at 12:32 -0500, Ryan Krauss wrote:
> > I am rethinking an algorithm for unwrapping phase data from arctan2
> > for a vector of complex numbers (coming from lti models of feedback
> > control systems).  I had written something a while ago using weave,
> > but my old code causes seg faults with a recent scipy update.  So, I
> > am rethinking the algorithm.
> >
> > The problem occurs when either because of noise or just the definition
> > of the inverse tangent, their are discontinuities in the phase (which
> > is coming from arctan2(imag(vector), real(vector)).  For example, in
> > the attached plot and data file, there is a point where the phase
> > passes through -180 degrees.  arctan2 jumps to returning +180, +175
> > etc, when it makes a pretty plot and makes more sense to me to convert
> > +175 to -185.  What I had done previously is write a for loop that
> > compares the current value of the phase to the value at the previous
> > index (i.e. if phase[i]-phase[-1]>300 or if phase[i]-phase[i-1]<-300)
> > to find the discontinuities.  Is there a cleaner/faster way to do
> > this?  (I had done it in weave and will probably now do it in f2py for
> > comparison on speeds).  I have attached/included a first attempt at an
> > algorithm that is more vectorized.  But is there a fast, easy way to
> > compare a vector to the same vector shift one element up or down?
> > Right now I am doing this
> >
> > phase2=r_[phase[0:1],phase[0:-1]]
> >
> > to shift the vector (and reuse the first element so there isn't a jump
> > from phase[-1] to phase[0] which may legitimately be far apart).
> >
> > Has anyone else already done this?  Are there obvious bottlenecks with
> > the algorithm?
> >
> > Thanks for your thoughts,
> >
> > Ryan
> >
> > =====================================
> > from scipy import arange, io, r_
> > from pylab import show, figure, subplot, clf, cla, semilogx, xlabel,
> > ylabel, legend, xlim
> >
> > import copy
> >
> > data=io.read_array('phase_data.txt')
> > f=data[:,0]
> > phase=data[:,1]
> > figure(1)
> > clf()
> > startphase=copy.copy(phase)
> > semilogx(f,startphase)
> >
> > keepgoing=1
> >
> > inds=arange(0,len(phase))
> >
> > while keepgoing:
> >     phase2=r_[phase[0:1],phase[0:-1]]#artificially repeat the first element
> >     diff=phase-phase2
> >     jumps=inds[abs(diff)>250]
> >     keepgoing=jumps.any()
> >     if not keepgoing:
> >         break
> >     ind=jumps.min()
> >     if diff[ind]>0:
> >         phase[ind:]-=360
> >     else:
> >         phase[ind:]+=360
> >
> >
> > semilogx(f,phase,'r--')
> >
> > legend(['Before unwrapping','after unwrapping'],2)
> >
> > xlim([1,30])
> >
> > show()
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
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2.05238e+01 -1.47265e+02
2.05476e+01 -1.47315e+02
2.05714e+01 -1.47364e+02
2.05952e+01 -1.47414e+02
2.06190e+01 -1.47463e+02
2.06429e+01 -1.47512e+02
2.06667e+01 -1.47560e+02
2.06905e+01 -1.47609e+02
2.07143e+01 -1.47657e+02
2.07381e+01 -1.47706e+02
2.07619e+01 -1.47754e+02
2.07857e+01 -1.47801e+02
2.08095e+01 -1.47849e+02
2.08333e+01 -1.47896e+02
2.08571e+01 -1.47944e+02
2.08810e+01 -1.47991e+02
2.09048e+01 -1.48037e+02
2.09286e+01 -1.48084e+02
2.09524e+01 -1.48130e+02
2.09762e+01 -1.48176e+02
2.10000e+01 -1.48222e+02
2.10238e+01 -1.48268e+02
2.10476e+01 -1.48314e+02
2.10714e+01 -1.48359e+02
2.10952e+01 -1.48404e+02
2.11190e+01 -1.48449e+02
2.11429e+01 -1.48494e+02
2.11667e+01 -1.48538e+02
2.11905e+01 -1.48583e+02
2.12143e+01 -1.48627e+02
2.12381e+01 -1.48671e+02
2.12619e+01 -1.48714e+02
2.12857e+01 -1.48758e+02
2.13095e+01 -1.48801e+02
2.13333e+01 -1.48844e+02
2.13571e+01 -1.48887e+02
2.13810e+01 -1.48930e+02
2.14048e+01 -1.48972e+02
2.14286e+01 -1.49014e+02
2.14524e+01 -1.49056e+02
2.14762e+01 -1.49098e+02
2.15000e+01 -1.49140e+02
2.15238e+01 -1.49181e+02
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From cygnusx1 at mac.com  Tue Oct 10 22:21:28 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Tue, 10 Oct 2006 22:21:28 -0400
Subject: [SciPy-user]   Missing library will not allow SciPy to load.
Message-ID: <7D612544-6319-457E-B27F-90F734F0BA69@mac.com>

> When I do
>
> from scipy import *
>
> I get the following error:
>
> ImportError: Failure linking new module:
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
> site-packages/scipy/sparse/sparsetools.so:
> Library not loaded: /usr/local/lib/libg2c.0.dylib
>   Referenced from:
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
> site-packages/scipy/sparse/sparsetools.so
>   Reason: image not found
>
>
> It seems I'm missing  libg2c.0.dylib.  I just installed the SciPy
> SuperPack.  I guess it wasn't in there or was supposed to be installed
> from some other package.  Does anyone know about this?
>
I believe this is installed as part of the g77 package (g77v3.4- 
bin.tar.gz).

Tom
--
W.T. Bridgman, Ph.D.
Physics & Astronomy



From w.richert at gmx.net  Wed Oct 11 06:34:35 2006
From: w.richert at gmx.net (Willi Richert)
Date: Wed, 11 Oct 2006 12:34:35 +0200
Subject: [SciPy-user] Pickling poly1d()
Message-ID: <200610111234.36223.w.richert@gmx.net>

Hi,

to be able to pickle poly1d instances I had to add __set/getstate__ and remove 
__setattr__ from it. It works now, however, I think there were some good 
reasons for the current version to not provide those methods. Do I now 
involve other problems / side effects with the attached version?

I diff'ed against numpy-0.9.8, but polynomial.py in the newest version 
(1.0rc2) has the same problem.

Regards,
wr

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From pecora at anvil.nrl.navy.mil  Wed Oct 11 06:53:50 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Wed, 11 Oct 2006 06:53:50 -0400
Subject: [SciPy-user] Missing library will not allow SciPy to load.
In-Reply-To: <7D612544-6319-457E-B27F-90F734F0BA69@mac.com>
References: <7D612544-6319-457E-B27F-90F734F0BA69@mac.com>
Message-ID: <452CCD3E.3060706@anvil.nrl.navy.mil>

Tom Bridgman wrote:
>> When I do
>>
>> from scipy import *
>>
>> I get the following error:
>>
>> ImportError: Failure linking new module:
>> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
>> site-packages/scipy/sparse/sparsetools.so:
>> Library not loaded: /usr/local/lib/libg2c.0.dylib
>>   Referenced from:
>> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
>> site-packages/scipy/sparse/sparsetools.so
>>   Reason: image not found
>>
>>
>> It seems I'm missing  libg2c.0.dylib.  I just installed the SciPy
>> SuperPack.  I guess it wasn't in there or was supposed to be installed
>> from some other package.  Does anyone know about this?
>>
>>     
> I believe this is installed as part of the g77 package (g77v3.4- 
> bin.tar.gz).
>
> Tom
> --
>   

Thanks.  You know, I think I didn't install g77 thinking I would never 
need it since I don't use Fortran anymore.  But I didn't think about 
dependencies within SciPy.  I'll install it. 

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From ryanlists at gmail.com  Wed Oct 11 10:55:43 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Wed, 11 Oct 2006 09:55:43 -0500
Subject: [SciPy-user] SciPy Ubuntu Dapper installation using Andrew Straw's
	packages
Message-ID: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>

I have a dumb apt question.  I have added
deb http://debs.astraw.com/ dapper/
deb-src http://debs.astraw.com/ dapper/

to my sources.list.  What at the names of the actual packages I need to install?

I searched using synaptic for numpy and found one called
python-scientific but didn't actually see anything called numpy or
scipy.

Thanks,

Ryan


From gael.varoquaux at normalesup.org  Wed Oct 11 11:02:09 2006
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Wed, 11 Oct 2006 17:02:09 +0200
Subject: [SciPy-user] SciPy Ubuntu Dapper installation using Andrew
	Straw's packages
In-Reply-To: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>
References: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>
Message-ID: <20061011150208.GH19992@clipper.ens.fr>

On Wed, Oct 11, 2006 at 09:55:43AM -0500, Ryan Krauss wrote:
> I have a dumb apt question.  I have added
> deb http://debs.astraw.com/ dapper/
> deb-src http://debs.astraw.com/ dapper/

> to my sources.list.  What at the names of the actual packages I need to install?

Did you update your packages. Searching for numpy with updated package
list gives:

python-numeric-tutorial - Tutorial for the Numerical Python Library
python-scientific - Python modules useful for scientific computing
python-numarray - An array processing package modelled after Python-Numeric
python-numeric - Numerical (matrix-oriented) Mathematics for Python
python-scientific-doc - Python modules useful for scientific computing
python2.4-numarray - An array processing package modelled after Python-Numeric
python2.4-numeric - Numerical (matrix-oriented) Mathematics for Python
python-numpy - NumPy: array processing for numbers, strings, records,...


I suggest you first remove all the matlplotib and scipy packages, then
install python-matplotlib, python-numpy and python-scipy.

Ga?l



From R.Springuel at umit.maine.edu  Wed Oct 11 17:23:46 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Wed, 11 Oct 2006 17:23:46 -0400
Subject: [SciPy-user] Installation Problems on Mac OS X
Message-ID: <452D60E2.70400@umit.maine.edu>

Okay, I've followed the instructions in the Wiki, but I'm still unable 
to install scipy-0.5.1 on my new Mac.  I've included the full output of 
what happens when I try below.  Can anyone tell me what I'm doing wrong?

$ python setup.py install

fft_opt_info:
fftw3_info:
   libraries fftw3 not found in 
/Library/Frameworks/Python.framework/Versions/2.5/lib
   FOUND:
     libraries = ['fftw3']
     library_dirs = ['/usr/local/lib']
     define_macros = [('SCIPY_FFTW3_H', None)]
     include_dirs = ['/usr/local/include']

djbfft_info:
   NOT AVAILABLE

   FOUND:
     libraries = ['fftw3']
     library_dirs = ['/usr/local/lib']
     define_macros = [('SCIPY_FFTW3_H', None)]
     include_dirs = ['/usr/local/include']

blas_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec', 
'-I/System/Library/Frameworks/vecLib.framework/Headers']

lapack_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec']

non-existing path in 'Lib/linsolve': 'tests'
umfpack_info:
   libraries umfpack not found in 
/Library/Frameworks/Python.framework/Versions/2.5/lib
   libraries umfpack not found in /usr/local/lib
   libraries umfpack not found in /usr/lib
/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/numpy/distutils/system_info.py:401: 
UserWarning:
     UMFPACK sparse solver 
(http://www.cise.ufl.edu/research/sparse/umfpack/)
     not found. Directories to search for the libraries can be specified 
in the
     numpy/distutils/site.cfg file (section [umfpack]) or by setting
     the UMFPACK environment variable.
   warnings.warn(self.notfounderror.__doc__)
   NOT AVAILABLE

non-existing path in 'Lib/maxentropy': 'doc'
Warning: Subpackage 'Lib' configuration returned as 'scipy'
running install
running build
running config_fc
running build_src
building py_modules sources
building library "dfftpack" sources
building library "linpack_lite" sources
building library "mach" sources
building library "quadpack" sources
building library "odepack" sources
building library "fitpack" sources
building library "superlu_src" sources
building library "minpack" sources
building library "rootfind" sources
building library "c_misc" sources
building library "cephes" sources
building library "mach" sources
building library "toms" sources
building library "amos" sources
building library "cdf" sources
building library "specfun" sources
building library "statlib" sources
building extension "scipy.cluster._vq" sources
building extension "scipy.fftpack._fftpack" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.fftpack.convolve" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.integrate._quadpack" sources
building extension "scipy.integrate._odepack" sources
building extension "scipy.integrate.vode" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.interpolate._fitpack" sources
building extension "scipy.interpolate.dfitpack" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
   adding 
'build/src.macosx-10.3-fat-2.5/Lib/interpolate/dfitpack-f2pywrappers.f' 
to sources.
building extension "scipy.io.numpyio" sources
building extension "scipy.lib.blas.fblas" sources
f2py options: ['skip:', ':']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
   adding 
'build/src.macosx-10.3-fat-2.5/build/src.macosx-10.3-fat-2.5/Lib/lib/blas/fblas-f2pywrappers.f' 
to sources.
building extension "scipy.lib.blas.cblas" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/lib/blas/cblas.pyf' to 
sources.
f2py options: ['skip:', ':']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.lib.lapack.flapack" sources
f2py options: ['skip:', ':']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.lib.lapack.clapack" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/lib/lapack/clapack.pyf' 
to sources.
f2py options: ['skip:', ':']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.lib.lapack.calc_lwork" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.lib.lapack.atlas_version" sources
building extension "scipy.linalg.fblas" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/linalg/fblas.pyf' to sources.
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
   adding 
'build/src.macosx-10.3-fat-2.5/build/src.macosx-10.3-fat-2.5/scipy/linalg/fblas-f2pywrappers.f' 
to sources.
building extension "scipy.linalg.cblas" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/linalg/cblas.pyf' to sources.
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.linalg.flapack" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/linalg/flapack.pyf' to 
sources.
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
   adding 
'build/src.macosx-10.3-fat-2.5/build/src.macosx-10.3-fat-2.5/scipy/linalg/flapack-f2pywrappers.f' 
to sources.
building extension "scipy.linalg.clapack" sources
   adding 'build/src.macosx-10.3-fat-2.5/scipy/linalg/clapack.pyf' to 
sources.
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.linalg._flinalg" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.linalg.calc_lwork" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.linalg.atlas_version" sources
building extension "scipy.linalg._iterative" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.linsolve._zsuperlu" sources
building extension "scipy.linsolve._dsuperlu" sources
building extension "scipy.linsolve._csuperlu" sources
building extension "scipy.linsolve._ssuperlu" sources
building extension "scipy.linsolve.umfpack.__umfpack" sources
building extension "scipy.optimize._minpack" sources
building extension "scipy.optimize._zeros" sources
building extension "scipy.optimize._lbfgsb" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.optimize.moduleTNC" sources
building extension "scipy.optimize._cobyla" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.optimize.minpack2" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.signal.sigtools" sources
building extension "scipy.signal.spline" sources
building extension "scipy.sparse.sparsetools" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.special._cephes" sources
building extension "scipy.special.specfun" sources
f2py options: ['--no-wrap-functions']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.stats.statlib" sources
f2py options: ['--no-wrap-functions']
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.stats.futil" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
building extension "scipy.stats.mvn" sources
f2py options: []
   adding 'build/src.macosx-10.3-fat-2.5/fortranobject.c' to sources.
   adding 'build/src.macosx-10.3-fat-2.5' to include_dirs.
   adding 'build/src.macosx-10.3-fat-2.5/Lib/stats/mvn-f2pywrappers.f' 
to sources.
building extension "scipy.ndimage._nd_image" sources
building data_files sources
running build_py
copying build/src.macosx-10.3-fat-2.5/scipy/__config__.py -> 
build/lib.macosx-10.3-fat-2.5/scipy
running build_clib
customize UnixCCompiler
customize UnixCCompiler using build_clib
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable g77
Could not locate executable f77
Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize Gnu95FCompiler
customize G95FCompiler
customize GnuFCompiler
customize Gnu95FCompiler
customize NAGFCompiler
customize NAGFCompiler using build_clib
building 'dfftpack' library
compiling Fortran sources
Fortran f77 compiler: f95 -fixed -O4 -target=native
Fortran f90 compiler: f95 -O4 -target=native
Fortran fix compiler: f95 -fixed -O4 -target=native
compile options: '-c'
f95:f77: Lib/fftpack/dfftpack/dcosqb.f
sh: line 1: f95: command not found
sh: line 1: f95: command not found
error: Command "f95 -fixed -O4 -target=native -c -c 
Lib/fftpack/dfftpack/dcosqb.f -o 
build/temp.macosx-10.3-fat-2.5/Lib/fftpack/dfftpack/dcosqb.o" failed 
with exit status 127
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From lists.steve at arachnedesign.net  Wed Oct 11 17:39:11 2006
From: lists.steve at arachnedesign.net (Steve Lianoglou)
Date: Wed, 11 Oct 2006 17:39:11 -0400
Subject: [SciPy-user] Installation Problems on Mac OS X
In-Reply-To: <452D60E2.70400@umit.maine.edu>
References: <452D60E2.70400@umit.maine.edu>
Message-ID: <1D67DE63-896A-4359-830C-B1DDF605F163@arachnedesign.net>

Just a stab in the dark, but it still looks like you don't have a  
fortran compiler that scipy can find.

Look in your output here:

> Could not locate executable g77
> Could not locate executable f77
> Could not locate executable gfortran
> Could not locate executable f95
  ... and ...
> compiling Fortran sources
> Fortran f77 compiler: f95 -fixed -O4 -target=native
> Fortran f90 compiler: f95 -O4 -target=native
> Fortran fix compiler: f95 -fixed -O4 -target=native
> compile options: '-c'
> f95:f77: Lib/fftpack/dfftpack/dcosqb.f
> sh: line 1: f95: command not found
> sh: line 1: f95: command not found
> error: Command "f95 -fixed -O4 -target=native -c -c
> Lib/fftpack/dfftpack/dcosqb.f -o


It says it can't find any fortran compiler (including f95), then it  
tries to use "f95" .. so ... that's what looks fishy to me.

Can you find f95 in your path? Maybe it's installed in /usr/local/bin  
and  you need to add that (but maybe scipy will find it by some other  
means(?))

-steve





From lists.steve at arachnedesign.net  Wed Oct 11 17:39:11 2006
From: lists.steve at arachnedesign.net (Steve Lianoglou)
Date: Wed, 11 Oct 2006 17:39:11 -0400
Subject: [SciPy-user] Installation Problems on Mac OS X
In-Reply-To: <452D60E2.70400@umit.maine.edu>
References: <452D60E2.70400@umit.maine.edu>
Message-ID: <1D67DE63-896A-4359-830C-B1DDF605F163@arachnedesign.net>

Just a stab in the dark, but it still looks like you don't have a  
fortran compiler that scipy can find.

Look in your output here:

> Could not locate executable g77
> Could not locate executable f77
> Could not locate executable gfortran
> Could not locate executable f95
  ... and ...
> compiling Fortran sources
> Fortran f77 compiler: f95 -fixed -O4 -target=native
> Fortran f90 compiler: f95 -O4 -target=native
> Fortran fix compiler: f95 -fixed -O4 -target=native
> compile options: '-c'
> f95:f77: Lib/fftpack/dfftpack/dcosqb.f
> sh: line 1: f95: command not found
> sh: line 1: f95: command not found
> error: Command "f95 -fixed -O4 -target=native -c -c
> Lib/fftpack/dfftpack/dcosqb.f -o


It says it can't find any fortran compiler (including f95), then it  
tries to use "f95" .. so ... that's what looks fishy to me.

Can you find f95 in your path? Maybe it's installed in /usr/local/bin  
and  you need to add that (but maybe scipy will find it by some other  
means(?))

-steve





From strang at nmr.mgh.harvard.edu  Wed Oct 11 21:28:17 2006
From: strang at nmr.mgh.harvard.edu (Gary Strangman)
Date: Wed, 11 Oct 2006 21:28:17 -0400 (EDT)
Subject: [SciPy-user] scipy build problem, linux centos4 (fwd)
Message-ID: <Pine.LNX.4.62.0610112127350.9917@guppy.nmr.mgh.harvard.edu>


Hi,

I appear to have a compile problem similar to those reported by OS/X 
users, but this is on a Linux CentOS4 platform and I've been unable to 
find a solution in the list archives. The tail end of my "python setup.py 
install" command is shown below, followed by a the items requested by the 
scipy.org FAQ. I didn't have trouble compiling on my FedoraCore2 box but 
was forced to upgrade by my sysadmins (grrrr) and now I've hit a brick 
wall. It was (at least originally) an out-of-the-box installation attempt.

Any suggestions/help would be most appreciated.

Gary

build/temp.linux-i686-2.4/build/src.linux-i686-2.4/fortranobject.o(.text+0x1abf):build/src.linux-i686-2.4/fortranobject.c:267: 
undefined reference to `PyExc_AttributeError'
build/temp.linux-i686-2.4/build/src.linux-i686-2.4/fortranobject.o(.text+0x1ac6):build/src.linux-i686-2.4/fortranobject.c:267: 
undefined reference to `PyErr_SetString'
build/temp.linux-i686-2.4/build/src.linux-i686-2.4/fortranobject.o(.text+0x1adf):build/src.linux-i686-2.4/fortranobject.c:218: 
undefined reference to `PyExc_AttributeError'
build/temp.linux-i686-2.4/build/src.linux-i686-2.4/fortranobject.o(.text+0x1ae7):build/src.linux-i686-2.4/fortranobject.c:218: 
undefined reference to `PyErr_SetString'
/usr/lib/gcc/i386-redhat-linux/3.4.5/libfrtbegin.a(frtbegin.o)(.text+0x35): In 
function `main':
: undefined reference to `MAIN__'
collect2: ld returned 1 exit status
error: Command "/usr/bin/g77 -L/usr/X11R6/lib 
build/temp.linux-i686-2.4/build/src.linux-i686-2.4/Lib/fftpack/_fftpackmodule.o 
build/temp.linux-i686-2.4/Lib/fftpack/src/zfft.o 
build/temp.linux-i686-2.4/Lib/fftpack/src/drfft.o 
build/temp.linux-i686-2.4/Lib/fftpack/src/zrfft.o 
build/temp.linux-i686-2.4/Lib/fftpack/src/zfftnd.o 
build/temp.linux-i686-2.4/build/src.linux-i686-2.4/fortranobject.o 
-L/usr/local/lib -Lbuild/temp.linux-i686-2.4 -ldfftpack -lfftw3 -lg2c -o 
build/lib.linux-i686-2.4/scipy/fftpack/_fftpack.so" failed with exit status 1
/space/nsg/8/users/scipy-0.5.1>

-------------------------------------------

Linux guppy 2.6.9-42.0.2.ELsmp #1 SMP Wed Aug 23 00:17:26 CDT 2006 i686 i686 
i386 GNU/Linux

sys.platform = linux2
sys.version = '2.4.3 (#1, Oct  6 2006, 15:32:21) \n[GCC 3.4.5 20051201 (Red Hat 
3.4.5-2)]'
numpy.__version__ = '1.0b5'

/space/nsg/8/users> python -c 'from numpy.f2py.diagnose import run; run()'
------
os.name='posix'
------
sys.platform='linux2'
------
sys.version:
2.4.3 (#1, Oct  6 2006, 15:32:21)
[GCC 3.4.5 20051201 (Red Hat 3.4.5-2)]
------
sys.prefix:
/space/nsg/8/users
------
sys.path=':/homes/3/strang/python:/space/nsg/8/users/numpy-1.0b5/numpy/lib:/space/nsg/8/users/include/python2.3:/space/nsg/8/users/lib/python2.3:/usr/include:/usr/lib:/space/nsg/8/users/lib/R/lib:/space/nsg/8/users/lib/python24.zip:/space/nsg/8/users/lib/python2.4:/space/nsg/8/users/lib/python2.4/plat-linux2:/space/nsg/8/users/lib/python2.4/lib-tk:/space/nsg/8/users/lib/python2.4/lib-dynload:/space/nsg/8/users/lib/python2.4/site-packages:/space/nsg/8/users/lib/python2.4/site-packages/Numeric:/space/nsg/8/users/lib/python2.4/site-packages/PIL'
------
Failed to import numarray: No module named numarray
Found Numeric version '24.2' in 
/space/nsg/8/users/lib/python2.4/site-packages/Numeric/Numeric.pyc
Found new numpy version '1.0b5' in 
/space/nsg/8/users/lib/python2.4/site-packages/numpy/__init__.pyc
Found f2py2e version '2_3118' in 
/space/nsg/8/users/lib/python2.4/site-packages/numpy/f2py/f2py2e.pyc
Found numpy.distutils version '0.4.0' in 
'/space/nsg/8/users/lib/python2.4/site-packages/numpy/distutils/__init__.pyc'
------
Importing numpy.distutils.fcompiler ... ok
------
Checking availability of supported Fortran compilers:
customize CompaqFCompiler
customize NoneFCompiler
customize AbsoftFCompiler
Could not locate executable ifort
Could not locate executable ifc
Could not locate executable ifort
Could not locate executable efort
Could not locate executable efc
Could not locate executable ifort
Could not locate executable efort
Could not locate executable efc
customize IntelFCompiler
Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize SunFCompiler
customize NAGFCompiler
customize VastFCompiler
customize GnuFCompiler
customize IbmFCompiler
customize Gnu95FCompiler
customize IntelVisualFCompiler
customize G95FCompiler
customize IntelItaniumFCompiler
customize PGroupFCompiler
customize LaheyFCompiler
customize CompaqVisualFCompiler
customize MipsFCompiler
customize HPUXFCompiler
customize IntelItaniumVisualFCompiler
customize IntelEM64TFCompiler
List of available Fortran compilers:
   --fcompiler=gnu  GNU Fortran Compiler (3.4.5)
List of unavailable Fortran compilers:
   --fcompiler=absoft   Absoft Corp Fortran Compiler
   --fcompiler=compaq   Compaq Fortran Compiler
   --fcompiler=compaqv  DIGITAL|Compaq Visual Fortran Compiler
   --fcompiler=g95      G95 Fortran Compiler
   --fcompiler=gnu95    GNU 95 Fortran Compiler
   --fcompiler=hpux     HP Fortran 90 Compiler
   --fcompiler=ibm      IBM XL Fortran Compiler
   --fcompiler=intel    Intel Fortran Compiler for 32-bit apps
   --fcompiler=intele   Intel Fortran Compiler for Itanium apps
   --fcompiler=intelem  Intel Fortran Compiler for EM64T-based apps
   --fcompiler=intelev  Intel Visual Fortran Compiler for Itanium apps
   --fcompiler=intelv   Intel Visual Fortran Compiler for 32-bit apps
   --fcompiler=lahey    Lahey/Fujitsu Fortran 95 Compiler
   --fcompiler=mips     MIPSpro Fortran Compiler
   --fcompiler=nag      NAGWare Fortran 95 Compiler
   --fcompiler=none     Fake Fortran compiler
   --fcompiler=pg       Portland Group Fortran Compiler
   --fcompiler=sun      Sun|Forte Fortran 95 Compiler
   --fcompiler=vast     Pacific-Sierra Research Fortran 90 Compiler
List of unimplemented Fortran compilers:
   --fcompiler=f  Fortran Company/NAG F Compiler
For compiler details, run 'config_fc --verbose' setup command.
------
Importing numpy.distutils.cpuinfo ... ok
------
CPU information: getNCPUs has_mmx has_sse has_sse2 is_32bit is_Intel is_XEON 
is_Xeon ------
/space/nsg/8/users> python -c 'from numpy import show_config as s;s()'
atlas_threads_info:
     libraries = ['lapack', 'lapack', 'blas']
     library_dirs = ['/usr/lib']
     language = c

blas_opt_info:
     libraries = ['lapack', 'blas']
     library_dirs = ['/usr/lib']
     define_macros = [('NO_ATLAS_INFO', 2)]
     language = c

atlas_blas_threads_info:
     libraries = ['lapack', 'blas']
     library_dirs = ['/usr/lib']
     language = c

lapack_opt_info:
     libraries = ['lapack', 'lapack', 'blas']
     library_dirs = ['/usr/lib']
     define_macros = [('NO_ATLAS_INFO', 2)]
     language = c

lapack_mkl_info:
   NOT AVAILABLE

blas_mkl_info:
   NOT AVAILABLE

mkl_info:
   NOT AVAILABLE




From ryanlists at gmail.com  Wed Oct 11 22:40:27 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Wed, 11 Oct 2006 21:40:27 -0500
Subject: [SciPy-user] SciPy Ubuntu Dapper installation using Andrew
	Straw's packages
In-Reply-To: <20061011150208.GH19992@clipper.ens.fr>
References: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>
	<20061011150208.GH19992@clipper.ens.fr>
Message-ID: <c5b438120610111940x4f9c15f0q75d8c1d96b29e085@mail.gmail.com>

So, Andrew's packages worked beautifully.  The information I was
looking for is actually on
http://scipy.org/Installing_SciPy/Linux .  I kept searching the list
for the instructions but it is on the website (in case anyone else is
ever looking here and finds this message).

Are the packages using optimized Atlas and Lapack if I have them
installed specific to my processor (sse2)?  Would I see any
performance increases if I built from source?

Thanks,

Ryan

On 10/11/06, Gael Varoquaux <gael.varoquaux at normalesup.org> wrote:
> On Wed, Oct 11, 2006 at 09:55:43AM -0500, Ryan Krauss wrote:
> > I have a dumb apt question.  I have added
> > deb http://debs.astraw.com/ dapper/
> > deb-src http://debs.astraw.com/ dapper/
>
> > to my sources.list.  What at the names of the actual packages I need to install?
>
> Did you update your packages. Searching for numpy with updated package
> list gives:
>
> python-numeric-tutorial - Tutorial for the Numerical Python Library
> python-scientific - Python modules useful for scientific computing
> python-numarray - An array processing package modelled after Python-Numeric
> python-numeric - Numerical (matrix-oriented) Mathematics for Python
> python-scientific-doc - Python modules useful for scientific computing
> python2.4-numarray - An array processing package modelled after Python-Numeric
> python2.4-numeric - Numerical (matrix-oriented) Mathematics for Python
> python-numpy - NumPy: array processing for numbers, strings, records,...
>
>
> I suggest you first remove all the matlplotib and scipy packages, then
> install python-matplotlib, python-numpy and python-scipy.
>
> Ga?l
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From david at ar.media.kyoto-u.ac.jp  Thu Oct 12 00:03:43 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Thu, 12 Oct 2006 13:03:43 +0900
Subject: [SciPy-user] SciPy Ubuntu Dapper installation using
 Andrew	Straw's packages
In-Reply-To: <c5b438120610111940x4f9c15f0q75d8c1d96b29e085@mail.gmail.com>
References: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>	<20061011150208.GH19992@clipper.ens.fr>
	<c5b438120610111940x4f9c15f0q75d8c1d96b29e085@mail.gmail.com>
Message-ID: <452DBE9F.3020902@ar.media.kyoto-u.ac.jp>

Ryan Krauss wrote:
> So, Andrew's packages worked beautifully.  The information I was
> looking for is actually on
> http://scipy.org/Installing_SciPy/Linux .  I kept searching the list
> for the instructions but it is on the website (in case anyone else is
> ever looking here and finds this message).
>
> Are the packages using optimized Atlas and Lapack if I have them
> installed specific to my processor (sse2)?
An 'easy' way to check if you are using sse2 optimized atlas is to check 
which libraries the loader loads when loading numpy and scipy libraries. 
For example, for numpy:

ldd /usr/lib/python2.4/site-packages/numpy/core/_dotblas.so  | grep blas 
returns the atlas enabled libblas (in the /usr/lib/sse2 directory, but 
this is distribution dependent, I think)

>   Would I see any
> performance increases if I built from source?
>   
Only if your atlas is faster than the shipped one (stating the obvious:) 
). Concretely, this means that you are able to compile a faster atlas, 
with the correct extended lapack, and this is not trivial, specially if 
your cpu is not in the default. Recent (after 3.7.14, I think) atlas 
have a much easier to use configuration.

If you have a new intel core 2 duo, last atlas give outstanding results 
according to the main developer of Atlas:

http://sourceforge.net/mailarchive/forum.php?thread_id=30384800&forum_id=426

David


From ndbecker2 at gmail.com  Thu Oct 12 14:49:17 2006
From: ndbecker2 at gmail.com (Neal Becker)
Date: Thu, 12 Oct 2006 14:49:17 -0400
Subject: [SciPy-user] Prob with romberg integration?
Message-ID: <egm2pb$6rs$1@sea.gmane.org>

This is scipy-0.5.1:
---------------------------
from scipy.integrate import romberg
from math import sqrt, log, exp

def F (x):
    return x


def G (v):
    return exp (v) * F (exp (v))

gain = 1/sqrt (2*romberg (G, log (1e-7), log (0.5)))
------------------------
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "/usr/tmp/python-MSHhoK.py", line 11, in ?
    gain = 1/sqrt (2*romberg (G, log (1e-7), log (0.5)))
  File "/usr/lib64/python2.4/site-packages/scipy/integrate/quadrature.py", line 377, in romberg
    ordsum = ordsum + _difftrap(vfunc, interval, n)
  File "/usr/lib64/python2.4/site-packages/scipy/integrate/quadrature.py", line 326, in _difftrap
    s = sum(function(points),0)
  File "/usr/lib64/python2.4/site-packages/scipy/integrate/quadrature.py", line 54, in vfunc
    output = empty((n,), dtype=y0.dtype)
AttributeError: 'float' object has no attribute 'dtype'




From peridot.faceted at gmail.com  Thu Oct 12 17:14:28 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Thu, 12 Oct 2006 17:14:28 -0400
Subject: [SciPy-user] Prob with romberg integration?
In-Reply-To: <egm2pb$6rs$1@sea.gmane.org>
References: <egm2pb$6rs$1@sea.gmane.org>
Message-ID: <ce557a360610121414h714865a9ya4adc7e126742556@mail.gmail.com>

On 12/10/06, Neal Becker <ndbecker2 at gmail.com> wrote:

> AttributeError: 'float' object has no attribute 'dtype'

Looks like things are not getting converted to Numeric data types. A
bug, but easy to work around; just wrap the arguments in array()
calls.

A. M. Archibald


From pecora at anvil.nrl.navy.mil  Thu Oct 12 17:17:04 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Thu, 12 Oct 2006 17:17:04 -0400
Subject: [SciPy-user] Missing library will not allow SciPy to load.
In-Reply-To: <7D612544-6319-457E-B27F-90F734F0BA69@mac.com>
References: <7D612544-6319-457E-B27F-90F734F0BA69@mac.com>
Message-ID: <452EB0D0.6020807@anvil.nrl.navy.mil>

Tom Bridgman wrote:
>> When I do
>>
>> from scipy import *
>>
>> I get the following error:
>>
>> ImportError: Failure linking new module:
>> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
>> site-packages/scipy/sparse/sparsetools.so:
>> Library not loaded: /usr/local/lib/libg2c.0.dylib
>>   Referenced from:
>> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/ 
>> site-packages/scipy/sparse/sparsetools.so
>>   Reason: image not found
>>
>>
>> It seems I'm missing  libg2c.0.dylib.  I just installed the SciPy
>> SuperPack.  I guess it wasn't in there or was supposed to be installed
>> from some other package.  Does anyone know about this?
>>
>>     
> I believe this is installed as part of the g77 package (g77v3.4- 
> bin.tar.gz).
>
> Tom
>   

Yes, this seemed to do it.  But I did have to use Terminal to manually 
transfer those files into /usr/local and sub directories.  Unlike the 
packages, this one is back up to the user.

Thanks.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From ryanlists at gmail.com  Thu Oct 12 17:22:49 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Thu, 12 Oct 2006 16:22:49 -0500
Subject: [SciPy-user] SciPy Ubuntu Dapper installation using Andrew
	Straw's packages
In-Reply-To: <452DBE9F.3020902@ar.media.kyoto-u.ac.jp>
References: <c5b438120610110755s60fedc08jc01adb0b5e75a6e6@mail.gmail.com>
	<20061011150208.GH19992@clipper.ens.fr>
	<c5b438120610111940x4f9c15f0q75d8c1d96b29e085@mail.gmail.com>
	<452DBE9F.3020902@ar.media.kyoto-u.ac.jp>
Message-ID: <c5b438120610121422t441abc2cn9fa07077f179e9c6@mail.gmail.com>

ryan at ubuntu:~$ ldd
/usr/lib/python2.4/site-packages/numpy/core/_dotblas.so  | grep blas
        libblas.so.3 => /usr/lib/atlas/sse2/libblas.so.3 (0xb7387000)

I think I am happy and I am done thinking about this.

Thanks,

Ryan

On 10/11/06, David Cournapeau <david at ar.media.kyoto-u.ac.jp> wrote:
> Ryan Krauss wrote:
> > So, Andrew's packages worked beautifully.  The information I was
> > looking for is actually on
> > http://scipy.org/Installing_SciPy/Linux .  I kept searching the list
> > for the instructions but it is on the website (in case anyone else is
> > ever looking here and finds this message).
> >
> > Are the packages using optimized Atlas and Lapack if I have them
> > installed specific to my processor (sse2)?
> An 'easy' way to check if you are using sse2 optimized atlas is to check
> which libraries the loader loads when loading numpy and scipy libraries.
> For example, for numpy:
>
> ldd /usr/lib/python2.4/site-packages/numpy/core/_dotblas.so  | grep blas
> returns the atlas enabled libblas (in the /usr/lib/sse2 directory, but
> this is distribution dependent, I think)
>
> >   Would I see any
> > performance increases if I built from source?
> >
> Only if your atlas is faster than the shipped one (stating the obvious:)
> ). Concretely, this means that you are able to compile a faster atlas,
> with the correct extended lapack, and this is not trivial, specially if
> your cpu is not in the default. Recent (after 3.7.14, I think) atlas
> have a much easier to use configuration.
>
> If you have a new intel core 2 duo, last atlas give outstanding results
> according to the main developer of Atlas:
>
> http://sourceforge.net/mailarchive/forum.php?thread_id=30384800&forum_id=426
>
> David
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From R.Springuel at umit.maine.edu  Thu Oct 12 18:53:06 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Thu, 12 Oct 2006 18:53:06 -0400
Subject: [SciPy-user] Installation Problems on Mac OS X
Message-ID: <452EC752.7030000@umit.maine.edu>

I have gfortran installed under /usr/local/bin.  I do not have f95 
installed.  Now the output says that it does look for gfortran so I 
shouldn't need f95, right?  If gfortran is sufficient, what do I need to 
do so that scipy can find gfortran?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From ndbecker2 at gmail.com  Thu Oct 12 20:25:46 2006
From: ndbecker2 at gmail.com (Neal Becker)
Date: Thu, 12 Oct 2006 20:25:46 -0400
Subject: [SciPy-user] Prob with romberg integration?
References: <egm2pb$6rs$1@sea.gmane.org>
	<ce557a360610121414h714865a9ya4adc7e126742556@mail.gmail.com>
Message-ID: <egmmg8$ji9$1@sea.gmane.org>

A. M. Archibald wrote:

> On 12/10/06, Neal Becker <ndbecker2 at gmail.com> wrote:
> 
>> AttributeError: 'float' object has no attribute 'dtype'
> 
> Looks like things are not getting converted to Numeric data types. A
> bug, but easy to work around; just wrap the arguments in array()
> calls.
> 

If I print out the value of 'x' in quadrature.py/vectororize1 (the arg to
vfunc), it seems that the first 2 times 'x' is a simple scalar, but the 3rd
time it is a list with 1 element, and that triggers the error.

Something's wrong here. 



From samnemo at gmail.com  Thu Oct 12 23:41:22 2006
From: samnemo at gmail.com (sam n)
Date: Thu, 12 Oct 2006 23:41:22 -0400
Subject: [SciPy-user] warnings+errors(check_integer) with scipy.test() on
	scipy-0.5.1
Message-ID: <ad01d5e90610122041y7b90817cwd770d999e44ad1e3@mail.gmail.com>

Hi All,

I just built and installed numpy-1.0rc2 and scipy-0.5.1 and encountered the
warnings & errors below (only get errors from scipy.test() , no problems
with numpy.test() ). If anyone knows how to fix these problems please let me
know. I already had LAPACK and BLAS installed. I also included diagnostic
information after the warnings & errors. Sorry if this email is too long.

Thanks for any help/suggestions.
Sam

>>> import scipy
>>> scipy.test()
Warning: FAILURE importing tests for <module 'scipy.linalg.lapack' from
'...ckages/scipy/linalg/lapack.pyc'>
/usr/arch/lib/python2.4/site-packages/scipy/linalg/basic.py:23: ImportError:
cannot import name calc_lwork (in ?)
  Found 42 tests for scipy.lib.lapack
Warning: FAILURE importing tests for <module 'scipy.special.basic' from
'...ckages/scipy/special/basic.pyc'>
/usr/arch/lib/python2.4/site-packages/scipy/linalg/basic.py:23: ImportError:
cannot import name calc_lwork (in ?)
======================================================================
ERROR: check_integer (scipy.io.tests.test_array_import.test_read_array)
----------------------------------------------------------------------
Traceback (most recent call last):
  File
"/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_array_import.py",
line 55, in check_integer
    from scipy import stats
  File "/usr/arch/lib/python2.4/site-packages/scipy/stats/__init__.py", line
7, in ?
    from stats import *
  File "/usr/arch/lib/python2.4/site-packages/scipy/stats/stats.py", line
191, in ?
    import scipy.special as special
  File "/usr/arch/lib/python2.4/site-packages/scipy/special/__init__.py",
line 10, in ?
    import orthogonal
  File "/usr/arch/lib/python2.4/site-packages/scipy/special/orthogonal.py",
line 67, in ?
    from scipy.linalg import eig
  File "/usr/arch/lib/python2.4/site-packages/scipy/linalg/__init__.py",
line 8, in ?
    from basic import *
  File "/usr/arch/lib/python2.4/site-packages/scipy/linalg/basic.py", line
23, in ?
    from scipy.linalg import calc_lwork
ImportError: cannot import name calc_lwork

======================================================================
ERROR: check loadmat case cellnest
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 80, in cc
    self._check_case(name, expected)
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 75, in _check_case
    self._check_level(k_label, expected, matdict[k])
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/arch/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 30, in _check_level
    assert len(expected) == len(actual), "Different list lengths at %s" %
label
TypeError: len() of unsized object

----------------------------------------------------------------------
Ran 630 tests in 7.745s

FAILED (errors=2)

diagnostic information from : python -c 'from numpy.f2py.diagnose import
run; run()'
------
os.name='posix'
------
sys.platform='linux2'
------
sys.version:
2.4.1 (#3, May  9 2005, 14:40:40)
[GCC 3.2.3 20030502 (Red Hat Linux 3.2.3-49)]
------
sys.prefix:
/usr/arch
------
sys.path=':/usr/arch/lib/python24.zip:/usr/arch/lib/python2.4:/usr/arch/lib/python2.4/plat-linux2:/usr/arch/lib/python2.4/lib-tk:/usr/arch/lib/python2.4/lib-dynload:/usr/arch/lib/python2.4/site-packages
'
------
Failed to import Numeric: No module named Numeric
Failed to import numarray: No module named numarray
Found new numpy version '1.0rc2' in
/usr/arch/lib/python2.4/site-packages/numpy/__init__.pyc
Found f2py2e version '2_3296' in
/usr/arch/lib/python2.4/site-packages/numpy/f2py/f2py2e.pyc
Found numpy.distutils version '0.4.0' in
'/usr/arch/lib/python2.4/site-packages/numpy/distutils/__init__.pyc'
------
Importing numpy.distutils.fcompiler ... ok
------
Checking availability of supported Fortran compilers:
customize CompaqFCompiler
customize NoneFCompiler
customize AbsoftFCompiler
Could not locate executable ifort
Could not locate executable ifc
Could not locate executable ifort
Could not locate executable efort
Could not locate executable efc
Could not locate executable ifort
Could not locate executable efort
Could not locate executable efc
customize IntelFCompiler
Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize SunFCompiler
customize NAGFCompiler
customize VastFCompiler
customize GnuFCompiler
customize IbmFCompiler
customize Gnu95FCompiler
customize IntelVisualFCompiler
customize G95FCompiler
customize IntelItaniumFCompiler
customize PGroupFCompiler
customize LaheyFCompiler
customize CompaqVisualFCompiler
customize MipsFCompiler
customize HPUXFCompiler
customize IntelItaniumVisualFCompiler
customize IntelEM64TFCompiler
List of available Fortran compilers:
  --fcompiler=gnu  GNU Fortran Compiler (3.2.3)
List of unavailable Fortran compilers:
  --fcompiler=absoft   Absoft Corp Fortran Compiler
  --fcompiler=compaq   Compaq Fortran Compiler
  --fcompiler=compaqv  DIGITAL|Compaq Visual Fortran Compiler
  --fcompiler=g95      G95 Fortran Compiler
  --fcompiler=gnu95    GNU 95 Fortran Compiler
  --fcompiler=hpux     HP Fortran 90 Compiler
  --fcompiler=ibm      IBM XL Fortran Compiler
  --fcompiler=intel    Intel Fortran Compiler for 32-bit apps
  --fcompiler=intele   Intel Fortran Compiler for Itanium apps
  --fcompiler=intelem  Intel Fortran Compiler for EM64T-based apps
  --fcompiler=intelev  Intel Visual Fortran Compiler for Itanium apps
  --fcompiler=intelv   Intel Visual Fortran Compiler for 32-bit apps
  --fcompiler=lahey    Lahey/Fujitsu Fortran 95 Compiler
  --fcompiler=mips     MIPSpro Fortran Compiler
  --fcompiler=nag      NAGWare Fortran 95 Compiler
  --fcompiler=none     Fake Fortran compiler
  --fcompiler=pg       Portland Group Fortran Compiler
  --fcompiler=sun      Sun|Forte Fortran 95 Compiler
  --fcompiler=vast     Pacific-Sierra Research Fortran 90 Compiler
List of unimplemented Fortran compilers:
  --fcompiler=f  Fortran Company/NAG F Compiler
For compiler details, run 'config_fc --verbose' setup command.
------
Importing numpy.distutils.cpuinfo ... ok
------
CPU information: getNCPUs has_mmx has_sse is_32bit is_Intel is_Pentium
is_PentiumII is_PentiumIII is_i686 ------
-------------- next part --------------
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From fredmfp at gmail.com  Fri Oct 13 12:12:07 2006
From: fredmfp at gmail.com (fred)
Date: Fri, 13 Oct 2006 18:12:07 +0200
Subject: [SciPy-user] editing wiki on localhost..
In-Reply-To: <17690.9056.272622.186684@prpc.aero.iitb.ac.in>
References: <45183A9A.5060408@gmail.com>	<17688.50113.296358.856192@prpc.aero.iitb.ac.in>	<45195BCB.4070403@gmail.com>
	<17690.9056.272622.186684@prpc.aero.iitb.ac.in>
Message-ID: <452FBAD7.4090007@gmail.com>

Hi,

I have found some stuff (ViewSourceWith on sourceforge) to edit wiki
pages on localhost.

But I don't understand how scipy.org wiki pages work.

For example, I have to give some information about the files I want to
edit in local.

Uh..., what files ? FredericPetit is a directory or a file ??

If it's a directory, which files are in it ?

I don't see neither directory nor file.

What am I doing wrong ?


Cheers,


-- 
http://scipy.org/FredericPetit


From pecora at anvil.nrl.navy.mil  Fri Oct 13 14:26:11 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Fri, 13 Oct 2006 14:26:11 -0400
Subject: [SciPy-user]  Can't run IPython from SuperPack.  ??
Message-ID: <452FDA43.9040409@anvil.nrl.navy.mil>

I installed the full SuperPack from SciPy.  Things seem to work well for 
pylab and scipy, but I want to use pylab/matplotlib in interactive 
mode.  The current wisdom is to do that in IPython.  The superpack 
intalled IPython down in /Lib/Framework/python...blah, blah/site-packages/.

But typing ipython, IPython or any variations in the Terminal does 
nothing.  I don't see ipython in /bin  /usr/local/bin or other places I 
find python or pythonw executables.

Any idea what I have to do to get up and running with IPython?

MacOS X 10.4 on PPC laptop, python2.4, latest SciPy, Pylab and Matplotlib.

Thanks for any help.

By the way.   My congratulations and endorsement to all who put together 
the SuperPack and its contents.  That's the way to do it for us python 
users.  Almost one-stop shopping.  Very nicely done.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From davidlinke at tiscali.de  Fri Oct 13 15:53:04 2006
From: davidlinke at tiscali.de (David Linke)
Date: Fri, 13 Oct 2006 21:53:04 +0200
Subject: [SciPy-user] editing wiki on localhost..
In-Reply-To: <452FBAD7.4090007@gmail.com>
References: <45183A9A.5060408@gmail.com>	<17688.50113.296358.856192@prpc.aero.iitb.ac.in>	<45195BCB.4070403@gmail.com>	<17690.9056.272622.186684@prpc.aero.iitb.ac.in>
	<452FBAD7.4090007@gmail.com>
Message-ID: <452FEEA0.3040605@tiscali.de>

fred wrote:
> Hi,
> 
> I have found some stuff (ViewSourceWith on sourceforge) to edit wiki
> pages on localhost.
> 
> But I don't understand how scipy.org wiki pages work.
> 
> For example, I have to give some information about the files I want to
> edit in local.
> 
> Uh..., what files ? FredericPetit is a directory or a file ??
> 
> If it's a directory, which files are in it ?
> 
> I don't see neither directory nor file.
> 
> What am I doing wrong ?
> 

I don't know about ViewSourceWith but it may be of interest for you to 
test http://labix.org/editmoin which is made specifically for 
MoinMoin-Wikis.

Regards,
David


From peridot.faceted at gmail.com  Fri Oct 13 16:13:01 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Fri, 13 Oct 2006 16:13:01 -0400
Subject: [SciPy-user] Prob with romberg integration?
In-Reply-To: <egmmg8$ji9$1@sea.gmane.org>
References: <egm2pb$6rs$1@sea.gmane.org>
	<ce557a360610121414h714865a9ya4adc7e126742556@mail.gmail.com>
	<egmmg8$ji9$1@sea.gmane.org>
Message-ID: <ce557a360610131313u2e2a6406idfe3a963c9f647a5@mail.gmail.com>

On 12/10/06, Neal Becker <ndbecker2 at gmail.com> wrote:
> A. M. Archibald wrote:
>
> > On 12/10/06, Neal Becker <ndbecker2 at gmail.com> wrote:
> >
> >> AttributeError: 'float' object has no attribute 'dtype'
> >
> > Looks like things are not getting converted to Numeric data types. A
> > bug, but easy to work around; just wrap the arguments in array()
> > calls.
> >
>
> If I print out the value of 'x' in quadrature.py/vectororize1 (the arg to
> vfunc), it seems that the first 2 times 'x' is a simple scalar, but the 3rd
> time it is a list with 1 element, and that triggers the error.
>
> Something's wrong here.

The bug appears to be in the function vectorize1 (which is internal to
scipy.integrate); it assumes that your function returns a numpy object
(which yours does not). Switching to "from numpy import exp, ..."
would probably cure the problem, as would wrapping the return value in
numpy.array().

You might find that scipy.integrate.quad, which is based on solid
FORTRAN routines from QUADPACK, is faster and more reliable.

Nevertheless, that bug in scipy is annoying.

A. M. Archibald


From fredmfp at gmail.com  Fri Oct 13 18:35:22 2006
From: fredmfp at gmail.com (fred)
Date: Sat, 14 Oct 2006 00:35:22 +0200
Subject: [SciPy-user] editing wiki on localhost..
In-Reply-To: <452FEEA0.3040605@tiscali.de>
References: <45183A9A.5060408@gmail.com>	<17688.50113.296358.856192@prpc.aero.iitb.ac.in>	<45195BCB.4070403@gmail.com>	<17690.9056.272622.186684@prpc.aero.iitb.ac.in>	<452FBAD7.4090007@gmail.com>
	<452FEEA0.3040605@tiscali.de>
Message-ID: <453014AA.1000409@gmail.com>

David Linke a ?crit :

>I don't know about ViewSourceWith but it may be of interest for you to 
>test http://labix.org/editmoin which is made specifically for 
>MoinMoin-Wikis.
>  
>
This is exactly what I was lookin for.
Thanks a lot (again ;-)

-- 
http://scipy.org/FredericPetit



From cygnusx1 at mac.com  Sun Oct 15 09:31:49 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Sun, 15 Oct 2006 09:31:49 -0400
Subject: [SciPy-user]  Missing library will not allow SciPy to load.
Message-ID: <E32C0983-7C0D-42E6-AA3F-D6587D97B06B@mac.com>

> Tom Bridgman wrote:
> >> When I do
> >>
> >> from scipy import *
> >>
> >> I get the following error:
> >>
> >> ImportError: Failure linking new module:
> >> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/
> >> site-packages/scipy/sparse/sparsetools.so:
> >> Library not loaded: /usr/local/lib/libg2c.0.dylib
> >>   Referenced from:
> >> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/
> >> site-packages/scipy/sparse/sparsetools.so
> >>   Reason: image not found
> >>
> >>
> >> It seems I'm missing  libg2c.0.dylib.  I just installed the SciPy
> >> SuperPack.  I guess it wasn't in there or was supposed to be  
> installed
> >> from some other package.  Does anyone know about this?
> >>
> >>
> > I believe this is installed as part of the g77 package (g77v3.4-
> > bin.tar.gz).
> >
> > Tom
> >
>
> Yes, this seemed to do it.  But I did have to use Terminal to manually
> transfer those files into /usr/local and sub directories.  Unlike the
> packages, this one is back up to the user.
>

I believe the -C option in the instructions does that for you:

% sudo tar -xvf g77v3.4-bin.tar -C /

Tom


From pecora at anvil.nrl.navy.mil  Sun Oct 15 10:46:15 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Sun, 15 Oct 2006 10:46:15 -0400
Subject: [SciPy-user] Missing library will not allow SciPy to load.
In-Reply-To: <E32C0983-7C0D-42E6-AA3F-D6587D97B06B@mac.com>
References: <E32C0983-7C0D-42E6-AA3F-D6587D97B06B@mac.com>
Message-ID: <453249B7.2050009@anvil.nrl.navy.mil>

Tom Bridgman wrote:
>>
>> Yes, this seemed to do it.  But I did have to use Terminal to manually
>> transfer those files into /usr/local and sub directories.  Unlike the
>> packages, this one is back up to the user.
>>
>>     
>
> I believe the -C option in the instructions does that for you:
>
> % sudo tar -xvf g77v3.4-bin.tar -C /
>
> Tom
> _____
>   

Well, learn something every day.  I didn't know about that so I did it 
the hard way.  Thanks.


-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From lroubeyrie at limair.asso.fr  Mon Oct 16 03:46:19 2006
From: lroubeyrie at limair.asso.fr (Lionel Roubeyrie)
Date: Mon, 16 Oct 2006 09:46:19 +0200
Subject: [SciPy-user] Dataframe
Message-ID: <200610160946.19215.lroubeyrie@limair.asso.fr>

Hi all,
Where can I find examples for using dataframe? Cookbook is pretty short 
(http://www.scipy.org/Cookbook/DataFrame) and there no documentation in the 
file :-/
thanks

-- 
Lionel Roubeyrie - lroubeyrie at limair.asso.fr
LIMAIR
http://www.limair.asso.fr


From gkoczyk at echostar.pl  Mon Oct 16 05:57:32 2006
From: gkoczyk at echostar.pl (Grzegorz Koczyk)
Date: Mon, 16 Oct 2006 11:57:32 +0200
Subject: [SciPy-user] Problem with scipy on FC5 (PentiumM/PentiumIV)
Message-ID: <1160992652.28112.22.camel@localhost.localdomain>

I am not sure whether this an FC5-specific problem, so I am submitting
this here and not as a ticket. 

For Fedora Core 5 running on Pentium4-based servers following scipy
tests fail and I am at a complete loss, at what can be done (and more
importantly to what extent other modules depends on the tested code):  

[ Note: I did try compiling ATLAS (3.6) from source, however then both
numpy and scipy complain about gfortran missing symbols in
lapack_lite.so - so I am unable to verify whether problem stems from
some peculiarity of vanilla FC5 RPMs. ]

======================================================================
FAIL: check_dot (scipy.linalg.tests.test_blas.test_fblas1_simple)
----------------------------------------------------------------------
Traceback (most recent call last):
  File
"/usr/lib/python2.4/site-packages/scipy/linalg/tests/test_blas.py", line
75, in check_dot
    assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
156, in assert_almost_equal
    assert round(abs(desired - actual),decimal) == 0, msg
AssertionError:
Items are not equal:
 ACTUAL: (3.3613915289673437e-35-1.0143136978149414j)
 DESIRED: (-9+2j)
----------------------------------------------------------------------
Scipy configuration:

>>> numpy.__version__
'1.0.dev3341'
>>> scipy.__version__
'0.5.2.dev2288'
>>> scipy.show_config()
umfpack_info:
  NOT AVAILABLE

atlas_threads_info:
  NOT AVAILABLE

blas_opt_info:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse2']
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    language = c
    include_dirs = ['/usr/include/atlas']

atlas_blas_threads_info:
  NOT AVAILABLE

djbfft_info:
  NOT AVAILABLE

lapack_opt_info:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse2']
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    language = c
    include_dirs = ['/usr/include/atlas']

fftw3_info:
    libraries = ['fftw3']
    library_dirs = ['/usr/lib']
    define_macros = [('SCIPY_FFTW3_H', None)]
    include_dirs = ['/usr/include']

atlas_info:
    libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse2']
    language = c
    include_dirs = ['/usr/include/atlas']

lapack_mkl_info:
  NOT AVAILABLE

blas_mkl_info:
  NOT AVAILABLE

atlas_blas_info:
    libraries = ['f77blas', 'cblas', 'atlas']
    library_dirs = ['/usr/lib/sse2']
    language = c
    include_dirs = ['/usr/include/atlas']

mkl_info:
  NOT AVAILABLE
----------------------------------------------------------------------
Relevant RPMs installed:

atlas-sse2-3.6.0-10.fc5
atlas-sse2-devel-3.6.0-10.fc5
blas-3.0-37.fc5
blas-devel-3.0-37.fc5
fftw-3.1.1-1.fc5
fftw-devel-3.1.1-1.fc5
lapack-3.0-37.fc5
lapack-devel-3.0-37.fc5
python-2.4.3-8.FC5
----------------------------------------------------------------------
/proc/cpuinfo:

processor       : 0
vendor_id       : GenuineIntel
cpu family      : 15
model           : 4
model name      : Intel(R) Pentium(R) 4 CPU 3.00GHz
stepping        : 3
cpu MHz         : 2992.931
cache size      : 2048 KB
physical id     : 0
siblings        : 2
core id         : 0
cpu cores       : 1
fdiv_bug        : no
hlt_bug         : no
f00f_bug        : no
coma_bug        : no
fpu             : yes
fpu_exception   : yes
cpuid level     : 5
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic mtrr pge mca
cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe lm
constant_tsc pni monitor ds_cpl est cid cx16 xtpr
bogomips        : 5997.83

processor       : 1
vendor_id       : GenuineIntel
cpu family      : 15
model           : 4
model name      : Intel(R) Pentium(R) 4 CPU 3.00GHz
stepping        : 3
cpu MHz         : 2992.931
cache size      : 2048 KB
physical id     : 0
siblings        : 2
core id         : 0
cpu cores       : 1
fdiv_bug        : no
hlt_bug         : no
f00f_bug        : no
coma_bug        : no
fpu             : yes
fpu_exception   : yes
cpuid level     : 5
wp              : yes
flags           : fpu vme de pse tsc msr pae mce cx8 apic mtrr pge mca
cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe lm
constant_tsc pni monitor ds_cpl est cid cx16 xtpr
bogomips        : 5985.40
----------------------------------------------------------------------

Any help or information concerning the matter would be highly
appreciated.

Best regards,
Grzegorz Koczyk






From meesters at uni-mainz.de  Mon Oct 16 07:44:29 2006
From: meesters at uni-mainz.de (Christian Meesters)
Date: Mon, 16 Oct 2006 13:44:29 +0200
Subject: [SciPy-user] polynomal regression
Message-ID: <200610161344.30811.meesters@uni-mainz.de>

Hi,

Well, scipy allows to fit a polynomal of arbitrary order. But is there any 
method implemented which does this and returns uncertainties in the 
coefficients as well?
For instance: If the data represent a polynomal p0 + p1*x + p1*x^2, is there a 
way to retreive delta-p0, -p1, and p2?

Sorry, if this question has already been asked - or even answered. I could 
image that somebody came up with it already, but I can't find the thread. Any 
hints / links appreciated ...

TIA
Christian



From gerard.vermeulen at grenoble.cnrs.fr  Mon Oct 16 07:55:31 2006
From: gerard.vermeulen at grenoble.cnrs.fr (Gerard Vermeulen)
Date: Mon, 16 Oct 2006 13:55:31 +0200
Subject: [SciPy-user] Problem with scipy on FC5 (PentiumM/PentiumIV)
In-Reply-To: <1160992652.28112.22.camel@localhost.localdomain>
References: <1160992652.28112.22.camel@localhost.localdomain>
Message-ID: <20061016135531.76512ffb.gerard.vermeulen@grenoble.cnrs.fr>

I have the same unit test failure on Mac OSX where I failed to build ATLAS from
source (it looks like that SciPy falls back on a different BLAS expecting a
different memory layout).

You can try to use something like the following site.cfg when rebuilding NumPy
(put it in the NumPy source tree before building):

cat >site.cfg <<EOF
[atlas]
library_dirs = /usr/lib
atlas_libs = lapack, f77blas, cblas, atlas
EOF

I needed to do this for my home made ATLAS rpm on Mandrake-2005: you have
to adapt it for your system.

Once I had built NumPy with the correct ATLAS settings, SciPy picked it up
and didn't complain about missing symbols anymore.

Gerard

PS: I consider this to be a NumPy bug.  Pre-NumPy versions of SciPy could
pick up my lapack, f77blas, cblas, atlas libraries without my intervention


On Mon, 16 Oct 2006 11:57:32 +0200
Grzegorz Koczyk <gkoczyk at echostar.pl> wrote:

> I am not sure whether this an FC5-specific problem, so I am submitting
> this here and not as a ticket. 
> 
> For Fedora Core 5 running on Pentium4-based servers following scipy
> tests fail and I am at a complete loss, at what can be done (and more
> importantly to what extent other modules depends on the tested code):  
> 
> [ Note: I did try compiling ATLAS (3.6) from source, however then both
> numpy and scipy complain about gfortran missing symbols in
> lapack_lite.so - so I am unable to verify whether problem stems from
> some peculiarity of vanilla FC5 RPMs. ]
> 
> ======================================================================
> FAIL: check_dot (scipy.linalg.tests.test_blas.test_fblas1_simple)
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File
> "/usr/lib/python2.4/site-packages/scipy/linalg/tests/test_blas.py", line
> 75, in check_dot
>     assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
>   File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
> 156, in assert_almost_equal
>     assert round(abs(desired - actual),decimal) == 0, msg
> AssertionError:
> Items are not equal:
>  ACTUAL: (3.3613915289673437e-35-1.0143136978149414j)
>  DESIRED: (-9+2j)
> ----------------------------------------------------------------------
> Scipy configuration:
> 
> >>> numpy.__version__
> '1.0.dev3341'
> >>> scipy.__version__
> '0.5.2.dev2288'
> >>> scipy.show_config()
> umfpack_info:
>   NOT AVAILABLE
> 
> atlas_threads_info:
>   NOT AVAILABLE
> 
> blas_opt_info:
>     libraries = ['f77blas', 'cblas', 'atlas']
>     library_dirs = ['/usr/lib/sse2']
>     define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
>     language = c
>     include_dirs = ['/usr/include/atlas']
> 
> atlas_blas_threads_info:
>   NOT AVAILABLE
> 
> djbfft_info:
>   NOT AVAILABLE
> 
> lapack_opt_info:
>     libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
>     library_dirs = ['/usr/lib/sse2']
>     define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
>     language = c
>     include_dirs = ['/usr/include/atlas']
> 
> fftw3_info:
>     libraries = ['fftw3']
>     library_dirs = ['/usr/lib']
>     define_macros = [('SCIPY_FFTW3_H', None)]
>     include_dirs = ['/usr/include']
> 
> atlas_info:
>     libraries = ['lapack', 'f77blas', 'cblas', 'atlas']
>     library_dirs = ['/usr/lib/sse2']
>     language = c
>     include_dirs = ['/usr/include/atlas']
> 
> lapack_mkl_info:
>   NOT AVAILABLE
> 
> blas_mkl_info:
>   NOT AVAILABLE
> 
> atlas_blas_info:
>     libraries = ['f77blas', 'cblas', 'atlas']
>     library_dirs = ['/usr/lib/sse2']
>     language = c
>     include_dirs = ['/usr/include/atlas']
> 
> mkl_info:
>   NOT AVAILABLE
> ----------------------------------------------------------------------
> Relevant RPMs installed:
> 
> atlas-sse2-3.6.0-10.fc5
> atlas-sse2-devel-3.6.0-10.fc5
> blas-3.0-37.fc5
> blas-devel-3.0-37.fc5
> fftw-3.1.1-1.fc5
> fftw-devel-3.1.1-1.fc5
> lapack-3.0-37.fc5
> lapack-devel-3.0-37.fc5
> python-2.4.3-8.FC5
> ----------------------------------------------------------------------
> /proc/cpuinfo:
> 
> processor       : 0
> vendor_id       : GenuineIntel
> cpu family      : 15
> model           : 4
> model name      : Intel(R) Pentium(R) 4 CPU 3.00GHz
> stepping        : 3
> cpu MHz         : 2992.931
> cache size      : 2048 KB
> physical id     : 0
> siblings        : 2
> core id         : 0
> cpu cores       : 1
> fdiv_bug        : no
> hlt_bug         : no
> f00f_bug        : no
> coma_bug        : no
> fpu             : yes
> fpu_exception   : yes
> cpuid level     : 5
> wp              : yes
> flags           : fpu vme de pse tsc msr pae mce cx8 apic mtrr pge mca
> cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe lm
> constant_tsc pni monitor ds_cpl est cid cx16 xtpr
> bogomips        : 5997.83
> 
> processor       : 1
> vendor_id       : GenuineIntel
> cpu family      : 15
> model           : 4
> model name      : Intel(R) Pentium(R) 4 CPU 3.00GHz
> stepping        : 3
> cpu MHz         : 2992.931
> cache size      : 2048 KB
> physical id     : 0
> siblings        : 2
> core id         : 0
> cpu cores       : 1
> fdiv_bug        : no
> hlt_bug         : no
> f00f_bug        : no
> coma_bug        : no
> fpu             : yes
> fpu_exception   : yes
> cpuid level     : 5
> wp              : yes
> flags           : fpu vme de pse tsc msr pae mce cx8 apic mtrr pge mca
> cmov pat pse36 clflush dts acpi mmx fxsr sse sse2 ss ht tm pbe lm
> constant_tsc pni monitor ds_cpl est cid cx16 xtpr
> bogomips        : 5985.40
> ----------------------------------------------------------------------
> 
> Any help or information concerning the matter would be highly
> appreciated.
> 
> Best regards,
> Grzegorz Koczyk
> 
> 
> 
> 
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
> 


From peridot.faceted at gmail.com  Mon Oct 16 09:27:03 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Mon, 16 Oct 2006 09:27:03 -0400
Subject: [SciPy-user] polynomal regression
In-Reply-To: <200610161344.30811.meesters@uni-mainz.de>
References: <200610161344.30811.meesters@uni-mainz.de>
Message-ID: <ce557a360610160627w15e6b7e9tdc42c1b04e339c39@mail.gmail.com>

On 16/10/06, Christian Meesters <meesters at uni-mainz.de> wrote:
> Hi,
>
> Well, scipy allows to fit a polynomal of arbitrary order. But is there any
> method implemented which does this and returns uncertainties in the
> coefficients as well?
> For instance: If the data represent a polynomal p0 + p1*x + p1*x^2, is there a
> way to retreive delta-p0, -p1, and p2?
>
> Sorry, if this question has already been asked - or even answered. I could
> image that somebody came up with it already, but I can't find the thread. Any
> hints / links appreciated ...

numpy's least-squares fitting procedure will do just what you're
asking for. I think it's called numpy.lstsqr (but it may have a
different number of ss and ts). What you really want is probably the
full covariance matrix, and I think it can give that to you.

A. M. Archibald


From ryanlists at gmail.com  Mon Oct 16 12:24:50 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Mon, 16 Oct 2006 11:24:50 -0500
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
Message-ID: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>

Anybody out there running Scipy/NumPy/Matplotlib under Ubuntu Edgy
Eft?  I am considering building a new computer based on AMD socket AM2
stuff, and from what I learned from a guy on the Ubuntuforums, the
hardware works very well under Edgy.  But my main use will be Scipy
related and I don't want a very fast computer that is good for games
and not for work.

Thanks,

Ryan


From robert.kern at gmail.com  Mon Oct 16 12:28:32 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Mon, 16 Oct 2006 11:28:32 -0500
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>
Message-ID: <4533B330.2020609@gmail.com>

Ryan Krauss wrote:
> Anybody out there running Scipy/NumPy/Matplotlib under Ubuntu Edgy
> Eft?

I'm still on Dapper, but I see no reason why any of those packages would not 
work or perform badly on Edgy Eft.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From stefan at sun.ac.za  Mon Oct 16 12:34:38 2006
From: stefan at sun.ac.za (Stefan van der Walt)
Date: Mon, 16 Oct 2006 18:34:38 +0200
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <4533B330.2020609@gmail.com>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>
	<4533B330.2020609@gmail.com>
Message-ID: <20061016163438.GB4393@mentat.za.net>

On Mon, Oct 16, 2006 at 11:28:32AM -0500, Robert Kern wrote:
> Ryan Krauss wrote:
> > Anybody out there running Scipy/NumPy/Matplotlib under Ubuntu Edgy
> > Eft?
> 
> I'm still on Dapper, but I see no reason why any of those packages would not 
> work or perform badly on Edgy Eft.

Indeed, it runs fine on Edgy.

Cheers
St?fan


From meesters at uni-mainz.de  Mon Oct 16 13:16:22 2006
From: meesters at uni-mainz.de (Christian Meesters)
Date: Mon, 16 Oct 2006 19:16:22 +0200
Subject: [SciPy-user] polynomal regression
In-Reply-To: <ce557a360610160627w15e6b7e9tdc42c1b04e339c39@mail.gmail.com>
References: <200610161344.30811.meesters@uni-mainz.de>
	<ce557a360610160627w15e6b7e9tdc42c1b04e339c39@mail.gmail.com>
Message-ID: <200610161916.23510.meesters@uni-mainz.de>

On Monday 16 October 2006 15:27, A. M. Archibald wrote:
>
> numpy's least-squares fitting procedure will do just what you're
> asking for. I think it's called numpy.lstsqr (but it may have a
> different number of ss and ts). What you really want is probably the
> full covariance matrix, and I think it can give that to you.
Thanks, but I'm not sure what you mean: In my numpy there is no lstsqr in the 
namespace, if I do 'from numpy import *' (fresh download from svn - I needed 
an upgrade anyway).

Perhaps my English prevents me from being understood here ... Another attempt:
Currently what I'm using is scipy.linalg.lstsq for linear regressions (mostly) 
and scipy.polyfit in other cases. For calculating 'errors' / 'deviations' / 
'uncertainties' of the calculated coefficients the function needs the input 
with errors in x & y, right? Is there any such function in scipy?

Christian


From peelle at gmail.com  Mon Oct 16 13:27:06 2006
From: peelle at gmail.com (Jonathan Peelle)
Date: Mon, 16 Oct 2006 13:27:06 -0400
Subject: [SciPy-user] installation issue on OS X
Message-ID: <958c3f860610161027l480241bv9bc07878f773df1c@mail.gmail.com>

I attempted to install SciPy on OS X (10.4.7, Intel processor),
Python2.4, using these instructions:

http://www.scipy.org/Installing_SciPy/Mac_OS_X

The fortran compiler and fftw libraries seemed to install just fine.
(I already had numpy 1.0b5 installed, and that works fine, too.)  As
near as I can tell the scipy installation is able to find all of these
installations.

After installing scipy, two tests fail: check_integer and
check_simple_todense.  The important info seems to be:


ImportError: Failure linking new module:
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/special/_cephes.so:
Symbol not found: ___dso_handle
  Referenced from:
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/special/_cephes.so
  Expected in: dynamic lookup


Output of build command is here:

http://docs.google.com/View?docid=df5p92sv_6fr7292

and output of the install command is here:

http://docs.google.com/View?docid=df5p92sv_7cscvwk


Any suggestions would be much appreciated.  Thanks.


From nwagner at iam.uni-stuttgart.de  Mon Oct 16 13:35:31 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Mon, 16 Oct 2006 19:35:31 +0200
Subject: [SciPy-user] polynomal regression
In-Reply-To: <200610161916.23510.meesters@uni-mainz.de>
References: <200610161344.30811.meesters@uni-mainz.de>
	<ce557a360610160627w15e6b7e9tdc42c1b04e339c39@mail.gmail.com>
	<200610161916.23510.meesters@uni-mainz.de>
Message-ID: <web-60604520@uni-stuttgart.de>

On Mon, 16 Oct 2006 19:16:22 +0200
  Christian Meesters <meesters at uni-mainz.de> wrote:
> On Monday 16 October 2006 15:27, A. M. Archibald wrote:
>>
>> numpy's least-squares fitting procedure will do just 
>>what you're
>> asking for. I think it's called numpy.lstsqr (but it may 
>>have a
>> different number of ss and ts). What you really want is 
>>probably the
>> full covariance matrix, and I think it can give that to 
>>you.
> Thanks, but I'm not sure what you mean: In my numpy 
>there is no lstsqr in the 
> namespace, if I do 'from numpy import *' (fresh download 
>from svn - I needed 
> an upgrade anyway).
> 
> Perhaps my English prevents me from being understood 
>here ... Another attempt:
> Currently what I'm using is scipy.linalg.lstsq for 
>linear regressions (mostly) 
> and scipy.polyfit in other cases. For calculating 
>'errors' / 'deviations' / 
> 'uncertainties' of the calculated coefficients the 
>function needs the input 
> with errors in x & y, right? Is there any such function 
>in scipy?
> 
> Christian
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user

It's linalg.lstsq.
Are you looking for Total Least Squares ?
AFAIK, it's not implemented yet.
Nils


From meesters at uni-mainz.de  Mon Oct 16 13:53:20 2006
From: meesters at uni-mainz.de (Christian Meesters)
Date: Mon, 16 Oct 2006 19:53:20 +0200
Subject: [SciPy-user] polynomal regression
In-Reply-To: <web-60604520@uni-stuttgart.de>
References: <200610161344.30811.meesters@uni-mainz.de>
	<200610161916.23510.meesters@uni-mainz.de>
	<web-60604520@uni-stuttgart.de>
Message-ID: <200610161953.20309.meesters@uni-mainz.de>


>
> It's linalg.lstsq.
> Are you looking for Total Least Squares ?
> AFAIK, it's not implemented yet.
> Nils
Thanks, Nils.
Too bad. Well, back to Origin for me in this case ...

Christian


From oliphant.travis at ieee.org  Mon Oct 16 14:10:11 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Mon, 16 Oct 2006 12:10:11 -0600
Subject: [SciPy-user] polynomal regression
In-Reply-To: <200610161953.20309.meesters@uni-mainz.de>
References: <200610161344.30811.meesters@uni-mainz.de>	<200610161916.23510.meesters@uni-mainz.de>	<web-60604520@uni-stuttgart.de>
	<200610161953.20309.meesters@uni-mainz.de>
Message-ID: <4533CB03.1090304@ieee.org>

Christian Meesters wrote:
>> It's linalg.lstsq.
>> Are you looking for Total Least Squares ?
>> AFAIK, it's not implemented yet.
>> Nils
>>     
> Thanks, Nils.
> Too bad. Well, back to Origin for me in this case ...
>   

Total Least Squares is pretty easy to implement using the SVD.   Try 
your hand.

-Travis



From robert.kern at gmail.com  Mon Oct 16 14:27:51 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Mon, 16 Oct 2006 13:27:51 -0500
Subject: [SciPy-user] polynomal regression
In-Reply-To: <4533CB03.1090304@ieee.org>
References: <200610161344.30811.meesters@uni-mainz.de>	<200610161916.23510.meesters@uni-mainz.de>	<web-60604520@uni-stuttgart.de>	<200610161953.20309.meesters@uni-mainz.de>
	<4533CB03.1090304@ieee.org>
Message-ID: <4533CF27.6050208@gmail.com>

Travis Oliphant wrote:
> Christian Meesters wrote:
>>> It's linalg.lstsq.
>>> Are you looking for Total Least Squares ?
>>> AFAIK, it's not implemented yet.
>>> Nils
>>>     
>> Thanks, Nils.
>> Too bad. Well, back to Origin for me in this case ...
> 
> Total Least Squares is pretty easy to implement using the SVD.   Try 
> your hand.

Total Least Squares can also be implemented as Orthogonal Distance Regression 
(ODR). However, this is neither here nor there for Christian's original 
question, which is how to find estimates of the uncertainties in the estimated 
parameters. This has nothing to do with Total Least Squares.

A. M. Archibald was closest, but got the name of the function wrong. In short, 
the only functions currently implemented that give uncertainties on estimated 
parameters are the non-linear least squares implementations. They aren't too bad 
for linear problems, either. The function A. M. was thinking of was 
scipy.optimize.leastsq() with full_output=True. An alternative is the 
scipy.sandbox.odr package, which can do ordinary least squares or ODR (of which 
Total Least Squares is the linear special case) and provide uncertainty 
estimates for both algorithms.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From ckkart at hoc.net  Mon Oct 16 20:24:39 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Tue, 17 Oct 2006 09:24:39 +0900
Subject: [SciPy-user] polynomal regression
In-Reply-To: <200610161953.20309.meesters@uni-mainz.de>
References: <200610161344.30811.meesters@uni-mainz.de>	<200610161916.23510.meesters@uni-mainz.de>	<web-60604520@uni-stuttgart.de>
	<200610161953.20309.meesters@uni-mainz.de>
Message-ID: <453422C7.2070604@hoc.net>

Christian Meesters wrote:
>> It's linalg.lstsq.
>> Are you looking for Total Least Squares ?
>> AFAIK, it's not implemented yet.
>> Nils
> Thanks, Nils.
> Too bad. Well, back to Origin for me in this case ...

In that case you might want to try peak-o-mat (lorentz.sf.net) which does curve
fitting based on the scipy.sandbox.odr module. The odr module is included in the
software so you can use a standard scipy built.
As fitting model you may enter anything that python understands, e.g.:
a*x**2+b*x+c*x
or you can use predefined tokens, e.g.
CB GA LO LO
for a constant background, a gaussian and two lorentian peak shapes.

Christian


From strawman at astraw.com  Tue Oct 17 00:00:21 2006
From: strawman at astraw.com (Andrew Straw)
Date: Mon, 16 Oct 2006 21:00:21 -0700
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <20061016163438.GB4393@mentat.za.net>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>	<4533B330.2020609@gmail.com>
	<20061016163438.GB4393@mentat.za.net>
Message-ID: <45345555.3060600@astraw.com>

I think William Grant has ported very recent versions of
numpy/scipy/matplotlib to Edgy. Thanks William - this is great!

I'll probably keep my .deb repository up-to-date for Dapper but not
bother with Edgy (unless problems crop up with Ubuntu's mainline
repository). I probably won't be upgrading our work machines to Edgy
given that Dapper is working so well and is a stable target for the next
4.5 years. For a home machine, I'd be tempted to install Edgy,
especially given that xen appears to work without recompiling the
kernel: https://wiki.ubuntu.com/XenOnEdgy

Ciao,
Andrew

Stefan van der Walt wrote:
> On Mon, Oct 16, 2006 at 11:28:32AM -0500, Robert Kern wrote:
>   
>> Ryan Krauss wrote:
>>     
>>> Anybody out there running Scipy/NumPy/Matplotlib under Ubuntu Edgy
>>> Eft?
>>>       
>> I'm still on Dapper, but I see no reason why any of those packages would not 
>> work or perform badly on Edgy Eft.
>>     
>
> Indeed, it runs fine on Edgy.
>
> Cheers
> St?fan
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   



From david at ar.media.kyoto-u.ac.jp  Tue Oct 17 01:05:25 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Tue, 17 Oct 2006 14:05:25 +0900
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <45345555.3060600@astraw.com>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>	<4533B330.2020609@gmail.com>	<20061016163438.GB4393@mentat.za.net>
	<45345555.3060600@astraw.com>
Message-ID: <45346495.8060707@ar.media.kyoto-u.ac.jp>

Andrew Straw wrote:
> I think William Grant has ported very recent versions of
> numpy/scipy/matplotlib to Edgy. Thanks William - this is great!
>
>   
Those are the official numpy packages, right ? scipy + numpy + 
matplotlib are officially included  in edgy, which should really help 
numpy spreading, I think.

cheers,

David


From strawman at astraw.com  Tue Oct 17 02:06:34 2006
From: strawman at astraw.com (Andrew Straw)
Date: Mon, 16 Oct 2006 23:06:34 -0700
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <45346495.8060707@ar.media.kyoto-u.ac.jp>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>	<4533B330.2020609@gmail.com>	<20061016163438.GB4393@mentat.za.net>	<45345555.3060600@astraw.com>
	<45346495.8060707@ar.media.kyoto-u.ac.jp>
Message-ID: <453472EA.5090205@astraw.com>

David Cournapeau wrote:
> Andrew Straw wrote:
>   
>> I think William Grant has ported very recent versions of
>> numpy/scipy/matplotlib to Edgy. Thanks William - this is great!
>>
>>   
>>     
> Those are the official numpy packages, right ? scipy + numpy + 
> matplotlib are officially included  in edgy, which should really help 
> numpy spreading, I think.
>   
As of today, these are the packages you get if you install Edgy, add the
"universe" repository to your /etc/apt/sources.list, and type "apt-get
install python-numpy python-scipy python-matplotlib" (or use the nice
Synaptic Package Manager GUI):

numpy 1.0rc1
matplotlib 0.87.5
scipy 0.5.1

I guess this is what you mean by "the official numpy packages".

We have at least William Alexander Grant, Jordan Mantha, Marco Presi,
Jos? Fonseca, Alexandre Fayolle, Vittorio Palmisano, and Matthias Klose
to thank for creating and maintaining the Debian and Ubuntu ports of
these packages.


From david at ar.media.kyoto-u.ac.jp  Tue Oct 17 02:18:41 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Tue, 17 Oct 2006 15:18:41 +0900
Subject: [SciPy-user] ubuntu Edgy Eft and Scipy
In-Reply-To: <453472EA.5090205@astraw.com>
References: <c5b438120610160924y5019b303id57e7c51844709b4@mail.gmail.com>	<4533B330.2020609@gmail.com>	<20061016163438.GB4393@mentat.za.net>	<45345555.3060600@astraw.com>	<45346495.8060707@ar.media.kyoto-u.ac.jp>
	<453472EA.5090205@astraw.com>
Message-ID: <453475C1.9030003@ar.media.kyoto-u.ac.jp>


> As of today, these are the packages you get if you install Edgy, add the
> "universe" repository to your /etc/apt/sources.list, and type "apt-get
> install python-numpy python-scipy python-matplotlib" (or use the nice
> Synaptic Package Manager GUI):
>
> numpy 1.0rc1
> matplotlib 0.87.5
> scipy 0.5.1
>
> I guess this is what you mean by "the official numpy packages".
>
>   
Yes, exactly. I discovered that the debian packages were included in 
ubuntu as well recently, which would make them easier for me to test (I 
used a debian chroot jail to test them inside my ubuntu machines 
before). But it looks like they are still buggy in the dependencies with 
lapack and such,

David


From ctmedra at unizar.es  Tue Oct 17 12:54:46 2006
From: ctmedra at unizar.es (Carlos Medrano)
Date: Tue, 17 Oct 2006 16:54:46 +0000 (UTC)
Subject: [SciPy-user] loadmat behaviour
Message-ID: <loom.20061017T185240-830@post.gmane.org>

Hi

 I'am using scipy and numpy on Kubuntu 6.0.6

>>> numpy.__version__
'1.0b5'
>>> scipy.__version__
'0.5.2.dev2197'
>>>      

I have got a problem when using loadmat

In matlab I had a matrix L1 that I saved to a file

MATLAB CODE
--------------
>> L1
L1 =
          10
        -352
       97346

>> save datafile  L1
-----------------
I used v6 or v7 of MatLab, but this did not alter the problem I report below.

When I try to use io.loadmat it reads numbers as unsigned integers

>>> ret=io.loadmat('datafile.mat')
>>> ret['L1']
array([        10, 4294966944,      97346], dtype=uint32)


How can I do to read the original data type? 

I can try to do some dirty things afterwards but it would be nice if I just 
could read data in their original format.

Thanks

Carlos Medrano




From matthew.brett at gmail.com  Tue Oct 17 13:10:47 2006
From: matthew.brett at gmail.com (Matthew Brett)
Date: Tue, 17 Oct 2006 18:10:47 +0100
Subject: [SciPy-user] loadmat behaviour
In-Reply-To: <loom.20061017T185240-830@post.gmane.org>
References: <loom.20061017T185240-830@post.gmane.org>
Message-ID: <1e2af89e0610171010w4f47d82eu22956604c4b11924@mail.gmail.com>

Hi,

> When I try to use io.loadmat it reads numbers as unsigned integers
>
> >>> ret=io.loadmat('datafile.mat')
> >>> ret['L1']
> array([        10, 4294966944,      97346], dtype=uint32)
>
>
> How can I do to read the original data type?

This is because matlab saves the data in that format.  You could try
this hardly documented feature:

import scipy.io as sio
MR = sio.MatFile5Reader(open('datafile.mat'), matlab_compatible=True)
ret = MR.get_variables()

Best,

Matthew


From cygnusx1 at mac.com  Tue Oct 17 17:40:12 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Tue, 17 Oct 2006 17:40:12 -0400
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X 10.4.7
	(PPC)
Message-ID: <4F867CBF-BBC0-4633-8674-EA5AD7B10FBF@mac.com>

Selected gcc 3.3
g77v3.4 installed from tarball
fftw libraries installed as described in
http://www.scipy.org/Installing_SciPy/Mac_OS_X

numpy build still fails.  I suspect the important error is

gcc: cannot specify -o with -c or -S and multiple compilations

but I have no idea of where to start with this.

I suspect is something to do with PPC vs Intel build options?   
Perhaps I need to turn off the '-c' which appears in the compile  
options but where is that located?

Suggestions?
Tom

Log below:

Planck:/Users/Shared/ToBeRestored/Python/numpy-1.0rc2 bridgman$ sudo  
python setup.py install
Password:
Running from numpy source directory.
F2PY Version 2_3296
blas_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec', '-I/System/Library/Frameworks/ 
vecLib.framework/Headers']

lapack_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec']

running install
running build
running config_fc
running build_src
building py_modules sources
building extension "numpy.core.multiarray" sources
Generating build/src.macosx-10.4-fat-2.4/numpy/core/config.h
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable f77
Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize GnuFCompiler
customize GnuFCompiler using config
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-I/Library/Frameworks/Python.framework/Versions/2.4/ 
include/python2.4 -Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc: cannot specify -o with -c or -S and multiple compilations
gcc: cannot specify -o with -c or -S and multiple compilations
failure.
removing: _configtest.c _configtest.o
Traceback (most recent call last):
   File "setup.py", line 89, in ?
     setup_package()
   File "setup.py", line 82, in setup_package
     configuration=configuration )
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/core.py", line 174, in setup
     return old_setup(**new_attr)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/core.py", line 149, in setup
     dist.run_commands()
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/dist.py", line 946, in run_commands
     self.run_command(cmd)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/dist.py", line 966, in run_command
     cmd_obj.run()
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/command/install.py", line 16, in run
     r = old_install.run(self)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/command/install.py", line 506, in run
     self.run_command('build')
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/cmd.py", line 333, in run_command
     self.distribution.run_command(command)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/dist.py", line 966, in run_command
     cmd_obj.run()
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/command/build.py", line 112, in run
     self.run_command(cmd_name)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/cmd.py", line 333, in run_command
     self.distribution.run_command(command)
   File "/Library/Frameworks/Python.framework/Versions/2.4//lib/ 
python2.4/distutils/dist.py", line 966, in run_command
     cmd_obj.run()
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/command/build_src.py", line 87, in run
     self.build_sources()
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/command/build_src.py", line 106, in build_sources
     self.build_extension_sources(ext)
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/command/build_src.py", line 212, in build_extension_sources
     sources = self.generate_sources(sources, ext)
   File "/Users/Shared/ToBeRestored/Python/numpy-1.0rc2/numpy/ 
distutils/command/build_src.py", line 270, in generate_sources
     source = func(extension, build_dir)
   File "numpy/core/setup.py", line 50, in generate_config_h
     raise "ERROR: Failed to test configuration"
ERROR: Failed to test configuration
Planck:/Users/Shared/ToBeRestored/Python/numpy-1.0rc2 bridgman$





From oliphant at ee.byu.edu  Tue Oct 17 17:47:05 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Tue, 17 Oct 2006 15:47:05 -0600
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X
 10.4.7 (PPC)
In-Reply-To: <4F867CBF-BBC0-4633-8674-EA5AD7B10FBF@mac.com>
References: <4F867CBF-BBC0-4633-8674-EA5AD7B10FBF@mac.com>
Message-ID: <45354F59.90304@ee.byu.edu>

Tom Bridgman wrote:

>Selected gcc 3.3
>g77v3.4 installed from tarball
>fftw libraries installed as described in
>http://www.scipy.org/Installing_SciPy/Mac_OS_X
>
>numpy build still fails.  I suspect the important error is
>
>gcc: cannot specify -o with -c or -S and multiple compilations
>
>but I have no idea of where to start with this.
>
>I suspect is something to do with PPC vs Intel build options?   
>Perhaps I need to turn off the '-c' which appears in the compile  
>  
>
>options but where is that located?
>  
>

I think this is a Python build issue.  As far as I know the build flags 
are gathered from Python. 

Look for a config directory where Python is installed and the Makefile 
in that directory.

On my system it is in

/usr/lib/python2.4/config/Makefile

Changing the options there seems to affect distutils which is where 
numpy gets it's information about how to build.

-Travis



From robert.kern at gmail.com  Tue Oct 17 17:58:32 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 17 Oct 2006 16:58:32 -0500
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X
 10.4.7 (PPC)
In-Reply-To: <4F867CBF-BBC0-4633-8674-EA5AD7B10FBF@mac.com>
References: <4F867CBF-BBC0-4633-8674-EA5AD7B10FBF@mac.com>
Message-ID: <45355208.5030305@gmail.com>

Tom Bridgman wrote:
> Selected gcc 3.3
> g77v3.4 installed from tarball
> fftw libraries installed as described in
> http://www.scipy.org/Installing_SciPy/Mac_OS_X
> 
> numpy build still fails.  I suspect the important error is
> 
> gcc: cannot specify -o with -c or -S and multiple compilations
> 
> but I have no idea of where to start with this.
> 
> I suspect is something to do with PPC vs Intel build options?   
> Perhaps I need to turn off the '-c' which appears in the compile  
> options but where is that located?

With a Universal build of Python, you will need to use gcc 4.0. Unfortunately, 
that may mean you will have to use gfortran instead of g77.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From bpederse at gmail.com  Tue Oct 17 19:02:45 2006
From: bpederse at gmail.com (Brent Pedersen)
Date: Tue, 17 Oct 2006 16:02:45 -0700
Subject: [SciPy-user] object based image classification
Message-ID: <e183a99d0610171602h784c78batf0d246ccbc7b9c75@mail.gmail.com>

hi, object based classification
(http://en.wikipedia.org/wiki/Object-oriented_image_classification )
for digital image processing seems to be getting popular in
remote-sensing/GIS. i'm told that the only software available to do that is
e-cognition (
http://www.definiens.com/
http://www.infoserve.co.jp/Tech_spec/eCognition/Definiens_paper_Elsevier.pdf
)


has anyone done anything similar with python and/or open source tools? are
there any libs out there for medical imaging or astronomy that i could look
into?
any pointers to related info?

thanks,
-brent
-------------- next part --------------
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From ahoover at eecs.berkeley.edu  Tue Oct 17 20:53:05 2006
From: ahoover at eecs.berkeley.edu (Aaron Hoover)
Date: Tue, 17 Oct 2006 17:53:05 -0700
Subject: [SciPy-user] object based image classification
In-Reply-To: <e183a99d0610171602h784c78batf0d246ccbc7b9c75@mail.gmail.com>
References: <e183a99d0610171602h784c78batf0d246ccbc7b9c75@mail.gmail.com>
Message-ID: <45357AF1.5000701@eecs.berkeley.edu>

Hi Brent,

I'm using Intel's open source computer vision library OpenCV with Python 
wrappers (SciPy, NumPy, etc) for vision tasks that are similar to what 
you're describing. There's quite a bit of computer vision research going 
on these days, and object recognition/shape context/feature matching are 
all active problems. The OpenCV wiki is online at 
http://opencvlibrary.sourceforge.net/. The project is fairly mature 
(there's a 1.0 beta) and the community is active (even if the signal to 
noise ratio on the newsgroup is a little low). As far as medical imaging 
vs. astronomy vs. machine vision the subproblems in those domains are 
simply specific cases of more general problems like shape recognition, 
feature matching, image registration, correspondence, etc. for which 
OpenCV provides a host of tools.

If you're interested in knowing more, send me an email off-list.

Cheers,
Aaron

Brent Pedersen wrote:
> hi, object based classification
> (http://en.wikipedia.org/wiki/Object-oriented_image_classification )
> for digital image processing seems to be getting popular in 
> remote-sensing/GIS. i'm told that the only software available to do 
> that is e-cognition (
> http://www.definiens.com/
> http://www.infoserve.co.jp/Tech_spec/eCognition/Definiens_paper_Elsevier.pdf 
> <http://www.infoserve.co.jp/Tech_spec/eCognition/Definiens_paper_Elsevier.pdf>
> )
>
>
> has anyone done anything similar with python and/or open source tools? 
> are there any libs out there for medical imaging or astronomy that i 
> could look into?
> any pointers to related info?
>
> thanks,
> -brent
>
> ------------------------------------------------------------------------
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   



From cygnusx1 at mac.com  Tue Oct 17 22:24:47 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Tue, 17 Oct 2006 22:24:47 -0400
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X 10.4.7
	(PPC)
Message-ID: <3F072FD0-CC2F-458C-A919-23B42B237B26@mac.com>

> I think this is a Python build issue.  As far as I know the build  
> flags
> are gathered from Python.
>
> Look for a config directory where Python is installed and the Makefile
> in that directory.
>
> On my system it is in
>
> /usr/lib/python2.4/config/Makefile
>
> Changing the options there seems to affect distutils which is where
> numpy gets it's information about how to build.
>
> -Travis
>

I've found the OS X version of this file in /Library/Frameworks/ 
Python.framework/Versions/2.4/lib/python2.4/config/Makefile.  There  
appear to be -c compiler flags in a section under the heading:  
"Special rules for object files".  Don't have time to try it this  
evening but it is a place to start for tomorrow.

My 'plan B' will be R. Kern's suggestion of using gFortran, by which  
I assume he means use gfortran-bin.tar.gz located here: http:// 
hpc.sourceforge.net/.  I did use the Universal Python build.

Seems like there are more possible branching options in this  
installation than indicated on the installation page.  I'll try these  
out over the next day or so and get back with my results.

Thanks,
Tom
--
W.T. Bridgman, Ph.D.
Physics & Astronomy



From robert.kern at gmail.com  Tue Oct 17 23:22:27 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 17 Oct 2006 22:22:27 -0500
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X
 10.4.7 (PPC)
In-Reply-To: <3F072FD0-CC2F-458C-A919-23B42B237B26@mac.com>
References: <3F072FD0-CC2F-458C-A919-23B42B237B26@mac.com>
Message-ID: <45359DF3.5010502@gmail.com>

Tom Bridgman wrote:

> My 'plan B' will be R. Kern's suggestion of using gFortran,

Actually, my suggestion is to use gcc 4.0. This should be your "Plan A" since 
gcc 3.3 *cannot* be used to build extensions for the Universal build of Python. 
Don't bother futzing with the Makefile.

A side effect of this is that you must use gfortran instead of g77 since g77 was 
never upgraded to work with gcc 4.0. Of course, your FORTRAN compiler does not 
matter when building numpy, just scipy.

> by which  
> I assume he means use gfortran-bin.tar.gz located here: http:// 
> hpc.sourceforge.net/.

Yes, if you like. I use the one from MacPorts, but whatever works for you.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From ahoover at eecs.berkeley.edu  Tue Oct 17 23:52:39 2006
From: ahoover at eecs.berkeley.edu (Aaron Hoover)
Date: Tue, 17 Oct 2006 20:52:39 -0700
Subject: [SciPy-user] one-liner to retrieve indices of n smallest values
	from an array?
Message-ID: <4627044B-0FE0-42CE-99EA-279675F470BF@eecs.berkeley.edu>

Hi all,

Perhaps this is better suited for the NumPy list, but is there a  
simple (one line, perhaps) way to get the indices of the n smallest  
elements of an array? Something along the lines of argmin() that  
could take a parameter indicating
how many minimal values to return?

Thanks,
Aaron


From robert.kern at gmail.com  Tue Oct 17 23:52:51 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Tue, 17 Oct 2006 22:52:51 -0500
Subject: [SciPy-user] one-liner to retrieve indices of n smallest values
 from an array?
In-Reply-To: <4627044B-0FE0-42CE-99EA-279675F470BF@eecs.berkeley.edu>
References: <4627044B-0FE0-42CE-99EA-279675F470BF@eecs.berkeley.edu>
Message-ID: <4535A513.70406@gmail.com>

Aaron Hoover wrote:
> Hi all,
> 
> Perhaps this is better suited for the NumPy list, but is there a  
> simple (one line, perhaps) way to get the indices of the n smallest  
> elements of an array? Something along the lines of argmin() that  
> could take a parameter indicating
> how many minimal values to return?

a.argsort()[:n]

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From ahoover at eecs.berkeley.edu  Wed Oct 18 00:09:14 2006
From: ahoover at eecs.berkeley.edu (Aaron Hoover)
Date: Tue, 17 Oct 2006 21:09:14 -0700
Subject: [SciPy-user] one-liner to retrieve indices of n smallest values
	from an array?
In-Reply-To: <4535A513.70406@gmail.com>
References: <4627044B-0FE0-42CE-99EA-279675F470BF@eecs.berkeley.edu>
	<4535A513.70406@gmail.com>
Message-ID: <FF6515F2-44E3-4F44-A48F-3788F26F6812@eecs.berkeley.edu>

Hi Robert,

Thanks, is there a simple way to extend this to 2D arrays, or does  
that require the use of ravel()?

-Aaron
On Oct 17, 2006, at 8:52 PM, Robert Kern wrote:

> Aaron Hoover wrote:
>> Hi all,
>>
>> Perhaps this is better suited for the NumPy list, but is there a
>> simple (one line, perhaps) way to get the indices of the n smallest
>> elements of an array? Something along the lines of argmin() that
>> could take a parameter indicating
>> how many minimal values to return?
>
> a.argsort()[:n]
>
> -- 
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a  
> harmless enigma
>   that is made terrible by our own mad attempt to interpret it as  
> though it had
>   an underlying truth."
>    -- Umberto Eco
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user



From fperez.net at gmail.com  Wed Oct 18 01:47:47 2006
From: fperez.net at gmail.com (Fernando Perez)
Date: Tue, 17 Oct 2006 23:47:47 -0600
Subject: [SciPy-user] Can't run IPython from SuperPack. ??
In-Reply-To: <452FDA43.9040409@anvil.nrl.navy.mil>
References: <452FDA43.9040409@anvil.nrl.navy.mil>
Message-ID: <db6b5ecc0610172247kc30830aqe63c78b5e3ec0355@mail.gmail.com>

Hi Louis,

On 10/13/06, Louis Pecora <pecora at anvil.nrl.navy.mil> wrote:
> I installed the full SuperPack from SciPy.  Things seem to work well for
> pylab and scipy, but I want to use pylab/matplotlib in interactive
> mode.  The current wisdom is to do that in IPython.  The superpack
> intalled IPython down in /Lib/Framework/python...blah, blah/site-packages/.
>
> But typing ipython, IPython or any variations in the Terminal does
> nothing.  I don't see ipython in /bin  /usr/local/bin or other places I
> find python or pythonw executables.
>
> Any idea what I have to do to get up and running with IPython?
>
> MacOS X 10.4 on PPC laptop, python2.4, latest SciPy, Pylab and Matplotlib.
>
> Thanks for any help.
>
> By the way.   My congratulations and endorsement to all who put together
> the SuperPack and its contents.  That's the way to do it for us python
> users.  Almost one-stop shopping.  Very nicely done.

sorry for the delayed reply...

I'm not a mac user so I'm not 100% sure why the superpack isn't giving
you the ipython startup script.  This sounds like a build problem with
the SP, but fortunately one you can easily remedy manually.

Just grab

http://projects.scipy.org/ipython/ipython/browser/ipython/trunk/scripts/ipython?format=raw

and drop it anywwhere in your $PATH (chmod +x).

This startup script hasn't changed in years and is deliberately
trivial, so you should be fine just copying it by hand.

I hope this helps,

f


From ctmedra at unizar.es  Wed Oct 18 02:37:09 2006
From: ctmedra at unizar.es (Carlos Medrano)
Date: Wed, 18 Oct 2006 06:37:09 +0000 (UTC)
Subject: [SciPy-user] loadmat behaviour
References: <loom.20061017T185240-830@post.gmane.org>
	<1e2af89e0610171010w4f47d82eu22956604c4b11924@mail.gmail.com>
Message-ID: <loom.20061018T082513-817@post.gmane.org>

Matthew Brett <matthew.brett <at> gmail.com> writes:

> 
> Hi,
> 
> > When I try to use io.loadmat it reads numbers as unsigned integers
> >
> > >>> ret=io.loadmat('datafile.mat')
> > >>> ret['L1']
> > array([        10, 4294966944,      97346], dtype=uint32)
> >
> >
> > How can I do to read the original data type?
> 
> This is because matlab saves the data in that format.  You could try
> this hardly documented feature:
> 
> import scipy.io as sio
> MR = sio.MatFile5Reader(open('datafile.mat'), matlab_compatible=True)
> ret = MR.get_variables()
> 
> Best,
> 
> Matthew
> 

Hi

If I try your code I get the following error:
>>> import scipy.io as sio 
>>> MR = sio.MatFile5Reader(open('datafile_v7.mat'), matlab_compatible=True)
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
AttributeError: 'module' object has no attribute 'MatFile5Reader'

Anyway, you give me a valuable information. If this is caused by the way matlab 
saves the data, this means I was not doing anything wrong. So perhaps the best 
way to solve this kind of problems is to use some other way of saving data in 
matlab (fprintf and friends).

Thank you 

Carlos Medrano





From nwagner at iam.uni-stuttgart.de  Wed Oct 18 02:42:08 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Wed, 18 Oct 2006 08:42:08 +0200
Subject: [SciPy-user] loadmat behaviour
In-Reply-To: <loom.20061018T082513-817@post.gmane.org>
References: <loom.20061017T185240-830@post.gmane.org>	<1e2af89e0610171010w4f47d82eu22956604c4b11924@mail.gmail.com>
	<loom.20061018T082513-817@post.gmane.org>
Message-ID: <4535CCC0.5060405@iam.uni-stuttgart.de>

Carlos Medrano wrote:
> Matthew Brett <matthew.brett <at> gmail.com> writes:
>
>   
>> Hi,
>>
>>     
>>> When I try to use io.loadmat it reads numbers as unsigned integers
>>>
>>>       
>>>>>> ret=io.loadmat('datafile.mat')
>>>>>> ret['L1']
>>>>>>             
>>> array([        10, 4294966944,      97346], dtype=uint32)
>>>
>>>
>>> How can I do to read the original data type?
>>>       
>> This is because matlab saves the data in that format.  You could try
>> this hardly documented feature:
>>
>> import scipy.io as sio
>> MR = sio.MatFile5Reader(open('datafile.mat'), matlab_compatible=True)
>> ret = MR.get_variables()
>>
>> Best,
>>
>> Matthew
>>
>>     
>
> Hi
>
> If I try your code I get the following error:
>   
>>>> import scipy.io as sio 
>>>> MR = sio.MatFile5Reader(open('datafile_v7.mat'), matlab_compatible=True)
>>>>         
> Traceback (most recent call last):
>   File "<stdin>", line 1, in ?
> AttributeError: 'module' object has no attribute 'MatFile5Reader'
>
> Anyway, you give me a valuable information. If this is caused by the way matlab 
> saves the data, this means I was not doing anything wrong. So perhaps the best 
> way to solve this kind of problems is to use some other way of saving data in 
> matlab (fprintf and friends).
>
> Thank you 
>
> Carlos Medrano
>
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   
>>> io.MatFile5Reader
<class 'scipy.io.mio5.MatFile5Reader'>
>>> scipy.__version__
'0.5.2.dev2289'

I guess you need a recent version of scipy.

Nils


 



From excellent.frizou at gmail.com  Wed Oct 18 05:11:39 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Wed, 18 Oct 2006 11:11:39 +0200
Subject: [SciPy-user] Shape Problem
Message-ID: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>

Hi,

I use a matrix M of shape (20,25).

If I do N=M[18:,18:] I correctly obtain the submatrix of M of shape (2,7).

Now, if I do N=M[19:,19:], I expect to have the submatrix of M of
shape (1,6) but the shape of N is (6,1).
Is there any way to obtain the correct shape in any case ?

Thank you very much for your help.

Sam


From david at ar.media.kyoto-u.ac.jp  Wed Oct 18 05:12:44 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Wed, 18 Oct 2006 18:12:44 +0900
Subject: [SciPy-user] loadmat behaviour
In-Reply-To: <loom.20061018T082513-817@post.gmane.org>
References: <loom.20061017T185240-830@post.gmane.org>	<1e2af89e0610171010w4f47d82eu22956604c4b11924@mail.gmail.com>
	<loom.20061018T082513-817@post.gmane.org>
Message-ID: <4535F00C.3010904@ar.media.kyoto-u.ac.jp>

Carlos Medrano wrote:
>
> Anyway, you give me a valuable information. If this is caused by the way matlab 
> saves the data, this means I was not doing anything wrong. So perhaps the best 
> way to solve this kind of problems is to use some other way of saving data in 
> matlab (fprintf and friends).
>
>   
A better and easier solution would be to use the hd5 support available 
in recent matlabs: files exported this way can be imported by pytables, 
and exported back. This is what I am using to plumb matlab and python 
code, when I don't have (yet) a scipy replacement for some matlab codes.

hdf5 file format is an established standard, with a C library available 
under a liberal license, which means many different applications can use it.

cheers,

David


From andy at insectnation.org  Wed Oct 18 08:04:33 2006
From: andy at insectnation.org (Andy Buckley)
Date: Wed, 18 Oct 2006 13:04:33 +0100
Subject: [SciPy-user] Studentized range distribution?
Message-ID: <45361851.9030908@insectnation.org>

Hi,

I'm afraid this may be only a tenuously SciPy questions, so apologies. That 
said, it is a stats method that I'm trying to apply using SciPy, so I'd be very 
grateful if someone could help :)

Here goes: I need to compute some statistics from a Studentized range 
distribution in SciPy, but it doesn't seem to be one of the implemented 
distributions according to 
http://www.scipy.org/doc/api_docs/scipy.stats.distributions.html.

I've tried searching the Web for a closed form definition of the PDF, CDF etc., 
but all I find is tables like this:
http://cse.niaes.affrc.go.jp/miwa/probcalc/s-range/srng_tbl.html
(It's a generalised t distribution for k sets of means and df degrees of 
freedom, so equal to stats.distributions.t for k = 2)

So, does anyone here happen to a) know a closed form representation of the SRD 
b) know how to implement it as a distribution in SciPy? :) Specifically, I'll 
need the percent point function: I don't know if that's calculated by 
numerically inverting the CDF or if there's a closed form expression for it.

Thanks!
Andy


From pecora at anvil.nrl.navy.mil  Wed Oct 18 08:17:49 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Wed, 18 Oct 2006 08:17:49 -0400
Subject: [SciPy-user] Can't run IPython from SuperPack. ??
In-Reply-To: <db6b5ecc0610172247kc30830aqe63c78b5e3ec0355@mail.gmail.com>
References: <452FDA43.9040409@anvil.nrl.navy.mil>
	<db6b5ecc0610172247kc30830aqe63c78b5e3ec0355@mail.gmail.com>
Message-ID: <45361B6D.4080008@anvil.nrl.navy.mil>

Fernando Perez wrote:
> Hi Louis,
>
> On 10/13/06, Louis Pecora <pecora at anvil.nrl.navy.mil> wrote:
>   
>> I installed the full SuperPack from SciPy.  Things seem to work well for
>> pylab and scipy, but I want to use pylab/matplotlib in interactive
>> mode.  The current wisdom is to do that in IPython.  The superpack
>> intalled IPython down in /Lib/Framework/python...blah, blah/site-packages/.
>>
>> But typing ipython, IPython or any variations in the Terminal does
>> nothing.  I don't see ipython in /bin  /usr/local/bin or other places I
>> find python or pythonw executables.
>>     
> sorry for the delayed reply...
>
> I'm not a mac user so I'm not 100% sure why the superpack isn't giving
> you the ipython startup script.  This sounds like a build problem with
> the SP, but fortunately one you can easily remedy manually.
>
> Just grab
>
> http://projects.scipy.org/ipython/ipython/browser/ipython/trunk/scripts/ipython?format=raw
>
> and drop it anywwhere in your $PATH (chmod +x).
>
> This startup script hasn't changed in years and is deliberately
> trivial, so you should be fine just copying it by hand.
>
> I hope this helps,
>
> f
>   

Thanks, Ferdnando.  You are essentially right.  I was told in a NG by 
someone in the know that the superpack installation of IPython is 
broken.  So I will do it from the command line.


-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From pecora at anvil.nrl.navy.mil  Wed Oct 18 08:22:01 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Wed, 18 Oct 2006 08:22:01 -0400
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
Message-ID: <45361C69.7090009@anvil.nrl.navy.mil>

Sam frizou wrote:
> Hi,
>
> I use a matrix M of shape (20,25).
>
> If I do N=M[18:,18:] I correctly obtain the submatrix of M of shape (2,7).
>
> Now, if I do N=M[19:,19:], I expect to have the submatrix of M of
> shape (1,6) but the shape of N is (6,1).
> Is there any way to obtain the correct shape in any case ?
>
> Thank you very much for your help.
>
> Sam
>   

I just tried this (MacOS X 10.4, Python 2.4, NumPy) and got the right 
answer (1,6).  What modules are you using?  Might need an upgrade there.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From gonzalezmancera+scipy at gmail.com  Wed Oct 18 10:45:49 2006
From: gonzalezmancera+scipy at gmail.com (Andres GM)
Date: Wed, 18 Oct 2006 10:45:49 -0400
Subject: [SciPy-user] numpy-1.0rc2 still does not build on MacOS X
Message-ID: <c990a6a50610180745x151123b3pcadd0dc7f8e7bed9@mail.gmail.com>

Hi tom, I had the same problem when I upgraded to a Universal Binary
version of Python (ie. Python 2.5). My solution was to install Numpy
using gcc 4.0 and gfortran as explained in the scipy documentation for
Macintels. I was succesful with this installation and everything seems
to work fine.

I used the gfortran from hpc.sourceforge.net and the latest version of
the Developer tools from Apple.

I hope this works.

Andres


From excellent.frizou at gmail.com  Wed Oct 18 10:53:44 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Wed, 18 Oct 2006 16:53:44 +0200
Subject: [SciPy-user] Shape Problem
In-Reply-To: <45361C69.7090009@anvil.nrl.navy.mil>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
	<45361C69.7090009@anvil.nrl.navy.mil>
Message-ID: <1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>

Actually, my matrix M comes from a ndarray N:

M=asmatrix(N)

So, M is not a numpy.matrix object (for which I do not have this shape
problem), but a numpy.core.defmatrix.matrix object (for wich I have
the shape problem).

Maybe there exists a way to really cast a ndarray into a numpy.matrix object ?

Thanks


On 10/18/06, Louis Pecora <pecora at anvil.nrl.navy.mil> wrote:
> Sam frizou wrote:
> > Hi,
> >
> > I use a matrix M of shape (20,25).
> >
> > If I do N=M[18:,18:] I correctly obtain the submatrix of M of shape (2,7).
> >
> > Now, if I do N=M[19:,19:], I expect to have the submatrix of M of
> > shape (1,6) but the shape of N is (6,1).
> > Is there any way to obtain the correct shape in any case ?
> >
> > Thank you very much for your help.
> >
> > Sam
> >
>
> I just tried this (MacOS X 10.4, Python 2.4, NumPy) and got the right
> answer (1,6).  What modules are you using?  Might need an upgrade there.
>
> --
> Cheers,
>
> Lou Pecora
>
> Code 6362
> Naval Research Lab
> Washington, DC  20375
> USA
> Ph:  +202-767-6002
> email:  pecora at anvil.nrl.navy.mil
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From hchase at ball.com  Wed Oct 18 11:32:07 2006
From: hchase at ball.com (Chase, Holden)
Date: Wed, 18 Oct 2006 09:32:07 -0600
Subject: [SciPy-user] More elegant way to get indices of the max value in an
	array?
Message-ID: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>

Hi,

 

I would like to get the array indices of the max value in an array.  Is
there a more elegant way than what I have implemented below using
argmax()?  This routine returns the indices and the max value.  

 

Thanks,

Holden

-----------------------------

import numpy                #Could be numarray as well

 

def arrayMaxInd(data):

    xMax = data.argmax(1)

    maxVal = 0

    xMaxInd = 0

    yMaxInd = 0

    for yInd in range(data.shape[0]):

        if data[yInd][xMax[yInd]] > maxVal:

            maxVal = data[yInd][xMax[yInd]]

            yMaxInd = yInd

            xMaxInd = xMax[yInd] 

    return [xMaxInd, yMaxInd, maxVal]

 

# test the function

testdata = numpy.random.rand(4,6)

print arrayMaxInd(testdata)

print testdata

----------------------------- 

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From aisaac at american.edu  Wed Oct 18 11:47:30 2006
From: aisaac at american.edu (Alan G Isaac)
Date: Wed, 18 Oct 2006 11:47:30 -0400
Subject: [SciPy-user]
 =?utf-8?q?More_elegant_way_to_get_indices_of_the_max?=
 =?utf-8?q?_value_in_an=09array=3F?=
In-Reply-To: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>
References: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>
Message-ID: <Mahogany-0.67.0-928-20061018-114730.00@american.edu>

On Wed, 18 Oct 2006, Holden Chase apparently wrote:
> I would like to get the array indices of the max value in an array.  Is
> there a more elegant way than what I have implemented below using
> argmax()?  This routine returns the indices and the max value.


Untested:
def arrayMaxInd(data):
        a = asarray(data)
        argmax1d = a.argmax()
        rs,cs = a.shape
        r,c = argmax1d//cs, argmax1d%cs
        return (r,c,argmax1d)

hth,
Alan Isaac







From stefan at sun.ac.za  Wed Oct 18 12:13:50 2006
From: stefan at sun.ac.za (Stefan van der Walt)
Date: Wed, 18 Oct 2006 18:13:50 +0200
Subject: [SciPy-user] More elegant way to get indices of the max value
	in an?array?
In-Reply-To: <Mahogany-0.67.0-928-20061018-114730.00@american.edu>
References: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>
	<Mahogany-0.67.0-928-20061018-114730.00@american.edu>
Message-ID: <20061018161350.GX17998@mentat.za.net>

On Wed, Oct 18, 2006 at 11:47:30AM -0400, Alan G Isaac wrote:
> On Wed, 18 Oct 2006, Holden Chase apparently wrote:
> > I would like to get the array indices of the max value in an array.  Is
> > there a more elegant way than what I have implemented below using
> > argmax()?  This routine returns the indices and the max value.
> 
> 
> Untested:
> def arrayMaxInd(data):
>         a = asarray(data)
>         argmax1d = a.argmax()
>         rs,cs = a.shape
>         r,c = argmax1d//cs, argmax1d%cs
>         return (r,c,argmax1d)

How about numpy.unravel_index?

Cheers
St?fan


From lists.steve at arachnedesign.net  Wed Oct 18 12:24:28 2006
From: lists.steve at arachnedesign.net (Steve Lianoglou)
Date: Wed, 18 Oct 2006 12:24:28 -0400
Subject: [SciPy-user] More elegant way to get indices of the max value
	in an?array?
In-Reply-To: <20061018161350.GX17998@mentat.za.net>
References: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>
	<Mahogany-0.67.0-928-20061018-114730.00@american.edu>
	<20061018161350.GX17998@mentat.za.net>
Message-ID: <D01AD1EC-09C1-4942-B618-2D6E279B05D7@arachnedesign.net>

> On Wed, Oct 18, 2006 at 11:47:30AM -0400, Alan G Isaac wrote:
>> On Wed, 18 Oct 2006, Holden Chase apparently wrote:
>>> I would like to get the array indices of the max value in an  
>>> array.  Is
>>> there a more elegant way than what I have implemented below using
>>> argmax()?  This routine returns the indices and the max value.
>>
>>
>> Untested:
>> def arrayMaxInd(data):
>>         a = asarray(data)
>>         argmax1d = a.argmax()
>>         rs,cs = a.shape
>>         r,c = argmax1d//cs, argmax1d%cs
>>         return (r,c,argmax1d)
>
> How about numpy.unravel_index

If you're just looking for the indices of the max value in your  
array, why not just do something like:

---

import numpy as np

# ...
# let some_array be your array that you want to find max val for

maxval_indices = np.where(some_array == some_array.max())

---

That would do the trick, too .. no?

-steve



From aisaac at american.edu  Wed Oct 18 12:43:36 2006
From: aisaac at american.edu (Alan G Isaac)
Date: Wed, 18 Oct 2006 12:43:36 -0400
Subject: [SciPy-user]
 =?iso-8859-1?q?More_elegant_way_to_get_indices_of_th?=
 =?iso-8859-1?q?e_max_value=09in_an=3Farray=3F?=
In-Reply-To: <20061018161350.GX17998@mentat.za.net>
References: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM><Mahogany-0.67.0-928-20061018-114730.00@american.edu>
	<20061018161350.GX17998@mentat.za.net>
Message-ID: <Mahogany-0.67.0-928-20061018-124336.00@american.edu>

On Wed, 18 Oct 2006, alan wrote
> return (r,c,argmax1d) 

That should have been a[r][c] or a[r,c] of course.
But better ideas have been floated.

Cheers,
Alan



From pgmdevlist at gmail.com  Wed Oct 18 12:44:37 2006
From: pgmdevlist at gmail.com (P GM)
Date: Wed, 18 Oct 2006 12:44:37 -0400
Subject: [SciPy-user] More elegant way to get indices of the max value
	in an?array?
In-Reply-To: <Mahogany-0.67.0-928-20061018-124336.00@american.edu>
References: <B386A967729AA844B2D9C7B6D83467010462AB07@AEROMSG3.AERO.BALL.COM>
	<Mahogany-0.67.0-928-20061018-114730.00@american.edu>
	<20061018161350.GX17998@mentat.za.net>
	<Mahogany-0.67.0-928-20061018-124336.00@american.edu>
Message-ID: <777651ce0610180944g4dbd1b69u4a7ddb57c1e02ef2@mail.gmail.com>

> How about numpy.unravel_index?

Sweet ! I didn't know this function existed ! Thx a lot.
So that gives us:

def argmax_coords(data):
    data = numpy.asarray(data)
    imax = data.argmax()
    return list(numpy.unravel_index(imax,data.shape) + [data.max(),]

On 10/18/06, Alan G Isaac <aisaac at american.edu> wrote:
> On Wed, 18 Oct 2006, alan wrote
> > return (r,c,argmax1d)
>
> That should have been a[r][c] or a[r,c] of course.
> But better ideas have been floated.
>
> Cheers,
> Alan
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From hchase at ball.com  Wed Oct 18 13:11:06 2006
From: hchase at ball.com (Chase, Holden)
Date: Wed, 18 Oct 2006 11:11:06 -0600
Subject: [SciPy-user] More elegant way to get indices of the max value value
	in an array?
Message-ID: <B386A967729AA844B2D9C7B6D83467010462AB0E@AEROMSG3.AERO.BALL.COM>

Thanks to all for the great suggestions.

 

Holden

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From pecora at anvil.nrl.navy.mil  Wed Oct 18 13:25:07 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Wed, 18 Oct 2006 13:25:07 -0400
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>
	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
Message-ID: <45366373.5000300@anvil.nrl.navy.mil>

Sam frizou wrote:
> Actually, my matrix M comes from a ndarray N:
>
> M=asmatrix(N)
>
> So, M is not a numpy.matrix object (for which I do not have this shape
> problem), but a numpy.core.defmatrix.matrix object (for wich I have
> the shape problem).
>   
Oh.  I don't know about ndarrays.
> Maybe there exists a way to really cast a ndarray into a numpy.matrix object ?
>
>   
Only thing I can think of is the usual  array(M), but not sure that 
would work and it creates a numpy copy of M.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From oliphant.travis at ieee.org  Wed Oct 18 13:41:19 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Wed, 18 Oct 2006 11:41:19 -0600
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>
	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
Message-ID: <4536673F.2070500@ieee.org>

Sam frizou wrote:
> Actually, my matrix M comes from a ndarray N:
>
> M=asmatrix(N)
>
> So, M is not a numpy.matrix object (for which I do not have this shape
> problem), but a numpy.core.defmatrix.matrix object (for wich I have
> the shape problem).
>   
These are the same thing.  There is only one matrix object.    Please 
show the code that is giving you the problem as I cannot reproduce it.

-Travis



From excellent.frizou at gmail.com  Wed Oct 18 14:57:23 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Wed, 18 Oct 2006 20:57:23 +0200
Subject: [SciPy-user] Shape Problem
In-Reply-To: <4536673F.2070500@ieee.org>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
	<45361C69.7090009@anvil.nrl.navy.mil>
	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
	<4536673F.2070500@ieee.org>
Message-ID: <1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>

from scipy import *


N=zeros((20,25))
print N[19:,19:].shape
# >>> (1,6)


M=matrix(N)
print M[19:,19:].shape
# >>> (6,1)


On 10/18/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
> Sam frizou wrote:
> > Actually, my matrix M comes from a ndarray N:
> >
> > M=asmatrix(N)
> >
> > So, M is not a numpy.matrix object (for which I do not have this shape
> > problem), but a numpy.core.defmatrix.matrix object (for wich I have
> > the shape problem).
> >
> These are the same thing.  There is only one matrix object.    Please
> show the code that is giving you the problem as I cannot reproduce it.
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From jimmy.touma.ctr at eglin.af.mil  Wed Oct 18 17:26:40 2006
From: jimmy.touma.ctr at eglin.af.mil (Touma Jimmy E CTR USAF AFRL/MNGG)
Date: Wed, 18 Oct 2006 16:26:40 -0500
Subject: [SciPy-user] interp1d question
Message-ID: <B723C39656E9B74E8DA2012A36AEB2632FAF5E@mail15.eglin.af.mil>

Hi all,


I am trying to interpolate in 1d along a columns as opposed to rows 
and it doesn't seem to work. The code below emulates reading data
where interpolation should be done column wise. The error when 
running this code follows. If you could please tell me what I am doing
wrong and how to interpolate along columns.

Thanks,
Jimmy






Here is my code:

#################################################################
import scipy
import numpy

x    = numpy.arange(0,10)
xnew = numpy.arange(0, 9, 0.5)
x    = x.reshape(len(x),1)
xnew = xnew.reshape(len(xnew),1)

y = scipy.exp(-x/3.0)
z = scipy.exp(-x/2.0)
v = scipy.exp(-x)



y = numpy.asanyarray(y)
z = numpy.asanyarray(z)
v = numpy.asanyarray(v)

y=y.reshape(len(y),1)
z=z.reshape(len(z),1)
v=v.reshape(len(v),1)

u = numpy.hstack((y,z,v))


f=scipy.interpolate.interp1d(x,u,kind='linear', axis=0)
##############################################################

I get the following error when I run it:
---------------------------------------------------------------------------
exceptions.ValueError                                Traceback (most recent
call last)

/home/touma/d1.py
     24
     25
---> 26 f=scipy.interpolate.interp1d(x,u,kind='linear', axis=0)
     27
     28

/usr/lib/python2.4/site-packages/scipy/interpolate/interpolate.py in
__init__(self, x, y, kind, axis, copy, bounds_error, fill_value)
    143         len_x,len_y = shape(oriented_x)[interp_axis],
shape(oriented_y)[interp_axis]
    144         if len_x != len_y:
--> 145             raise ValueError, "x and y arrays must be equal in
length along "\
    146                               "interpolation axis."
    147         if len_x < 2 or len_y < 2:

ValueError: x and y arrays must be equal in length along interpolation axis.
WARNING: Failure executing file: <d1.py>

In [3]: numpy.__version__
Out[3]: '1.0b5'

In [4]: scipy.__version__
Out[4]: '0.3.2'




-------------- next part --------------
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From robert.kern at gmail.com  Wed Oct 18 17:34:56 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Wed, 18 Oct 2006 16:34:56 -0500
Subject: [SciPy-user] interp1d question
In-Reply-To: <B723C39656E9B74E8DA2012A36AEB2632FAF5E@mail15.eglin.af.mil>
References: <B723C39656E9B74E8DA2012A36AEB2632FAF5E@mail15.eglin.af.mil>
Message-ID: <45369E00.4010703@gmail.com>

Touma Jimmy E CTR USAF AFRL/MNGG wrote:
> Hi all,
> 
> 
> I am trying to interpolate in 1d along a columns as opposed to rows
> and it doesn't seem to work. The code below emulates reading data
> where interpolation should be done column wise. The error when
> running this code follows. If you could please tell me what I am doing
> wrong and how to interpolate along columns.

> /usr/lib/python2.4/site-packages/scipy/interpolate/interpolate.py in 
> __init__(self, x, y, kind, axis, copy, bounds_error, fill_value)
> 
>     143         len_x,len_y = shape(oriented_x)[interp_axis], 
> shape(oriented_y)[interp_axis]
>     144         if len_x != len_y:
> --> 145             raise ValueError, "x and y arrays must be equal in 
> length along "\
>     146                               "interpolation axis."
>     147         if len_x < 2 or len_y < 2:
> 
> ValueError: x and y arrays must be equal in length along interpolation 
> axis.
> WARNING: Failure executing file: <d1.py>
> 
> In [3]: numpy.__version__
> Out[3]: '1.0b5'
> 
> In [4]: scipy.__version__
> Out[4]: '0.3.2'

You have a *very* old version of scipy. It uses Numeric, not numpy. Please upgrade.

In recent versions, interp1d does not accept x arrays with more than one 
dimension. I'm not entirely sure why the old version did; it makes no sense.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From josegomez at gmx.net  Wed Oct 18 17:52:59 2006
From: josegomez at gmx.net (Jose Luis Gomez Dans)
Date: Wed, 18 Oct 2006 23:52:59 +0200
Subject: [SciPy-user] Dataframe
In-Reply-To: <200610160946.19215.lroubeyrie@limair.asso.fr>
References: <200610160946.19215.lroubeyrie@limair.asso.fr>
Message-ID: <20061018215259.310820@gmx.net>

Salut Lionel!

-------- Original-Nachricht --------
> Where can I find examples for using dataframe? Cookbook is pretty short 
> (http://www.scipy.org/Cookbook/DataFrame) and there no documentation in
> the 
> file :-/

I started the wiki page, but I realised that I could throw in some documentation and examples as well. However, I got diverted by work, and I'm not around in the next couple of weeks. Hopefully, after that I'll be able to document it properly with examples. I learned by trial and error, and apart from optimisations, it is an excellent module.

Sorry, it's me being slack in updating things!
Jose
-- 
GMX DSL-Flatrate 0,- Euro* - ?berall, wo DSL verf?gbar ist!
NEU: Jetzt bis zu 16.000 kBit/s! http://www.gmx.net/de/go/dsl


From oliphant at ee.byu.edu  Wed Oct 18 17:55:28 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Wed, 18 Oct 2006 15:55:28 -0600
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>	<4536673F.2070500@ieee.org>
	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>
Message-ID: <4536A2D0.30900@ee.byu.edu>

Sam frizou wrote:

>from scipy import *
>
>
>N=zeros((20,25))
>print N[19:,19:].shape
># >>> (1,6)
>
>
>M=matrix(N)
>print M[19:,19:].shape
># >>> (6,1)
>  
>

Please run the following

from scipy import *

print repr(matrix)

import scipy
print scipy.__version__

import numpy
print numpy.__version__


Thanks,

-Travis



From excellent.frizou at gmail.com  Wed Oct 18 18:18:35 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 00:18:35 +0200
Subject: [SciPy-user] Shape Problem
In-Reply-To: <4536A2D0.30900@ee.byu.edu>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
	<45361C69.7090009@anvil.nrl.navy.mil>
	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
	<4536673F.2070500@ieee.org>
	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>
	<4536A2D0.30900@ee.byu.edu>
Message-ID: <1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>

<class 'numpy.core.defmatrix.matrix'>
0.5.0.2116
1.1.2880

On 10/18/06, Travis Oliphant <oliphant at ee.byu.edu> wrote:
> Sam frizou wrote:
>
> >from scipy import *
> >
> >
> >N=zeros((20,25))
> >print N[19:,19:].shape
> ># >>> (1,6)
> >
> >
> >M=matrix(N)
> >print M[19:,19:].shape
> ># >>> (6,1)
> >
> >
>
> Please run the following
>
> from scipy import *
>
> print repr(matrix)
>
> import scipy
> print scipy.__version__
>
> import numpy
> print numpy.__version__
>
>
> Thanks,
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From oliphant at ee.byu.edu  Wed Oct 18 18:26:06 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Wed, 18 Oct 2006 16:26:06 -0600
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>	<4536673F.2070500@ieee.org>	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>	<4536A2D0.30900@ee.byu.edu>
	<1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>
Message-ID: <4536A9FE.6090508@ee.byu.edu>

Sam frizou wrote:

><class 'numpy.core.defmatrix.matrix'>
>0.5.0.2116
>1.1.2880
>  
>

Your version of NumPy is old.  There were some issues with Matrix 
indexing that were fixed a while ago.  The current revision is 3352 (you 
are using revision 2880).   The 1.1 was a mis-nomer and was changed in 
August I belived.

The name for the most recent development version is

1.0.dev3359



-Travis





From excellent.frizou at gmail.com  Wed Oct 18 18:33:24 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 00:33:24 +0200
Subject: [SciPy-user] Shape Problem
In-Reply-To: <4536A9FE.6090508@ee.byu.edu>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>
	<45361C69.7090009@anvil.nrl.navy.mil>
	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>
	<4536673F.2070500@ieee.org>
	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>
	<4536A2D0.30900@ee.byu.edu>
	<1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>
	<4536A9FE.6090508@ee.byu.edu>
Message-ID: <1d2f6e8c0610181533t60b912c7j7b64ca5f9b3cdcf0@mail.gmail.com>

In fact I installed numpy from "SciPy Superpack for Python 2.4 (Intel)"

Thank you very much

On 10/19/06, Travis Oliphant <oliphant at ee.byu.edu> wrote:
> Sam frizou wrote:
>
> ><class 'numpy.core.defmatrix.matrix'>
> >0.5.0.2116
> >1.1.2880
> >
> >
>
> Your version of NumPy is old.  There were some issues with Matrix
> indexing that were fixed a while ago.  The current revision is 3352 (you
> are using revision 2880).   The 1.1 was a mis-nomer and was changed in
> August I belived.
>
> The name for the most recent development version is
>
> 1.0.dev3359
>
>
>
> -Travis
>
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From oliphant at ee.byu.edu  Wed Oct 18 18:39:54 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Wed, 18 Oct 2006 16:39:54 -0600
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610181533t60b912c7j7b64ca5f9b3cdcf0@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>	<4536673F.2070500@ieee.org>	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>	<4536A2D0.30900@ee.byu.edu>	<1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>	<4536A9FE.6090508@ee.byu.edu>
	<1d2f6e8c0610181533t60b912c7j7b64ca5f9b3cdcf0@mail.gmail.com>
Message-ID: <4536AD3A.3080800@ee.byu.edu>

Sam frizou wrote:

>In fact I installed numpy from "SciPy Superpack for Python 2.4 (Intel)"
>  
>
It's too bad that this version of NumPy got placed in the Super-pack.  I 
don't remember exactly how long the version number had a 1.1 on it  but 
I think it was only a few days.   When 1.0b1 was released I bumped up 
the version number of the tree and was brought to my senses a bit later 
and the whole dev# scheme for the SVN tree was put in-place. 

You have to look at the revision number to see where 1.1 fits in.  It 
sounds like something pre 1.0b2 which would mean that it won't work with 
SciPy 0.5.1.

-Travis



From pecora at anvil.nrl.navy.mil  Wed Oct 18 19:59:52 2006
From: pecora at anvil.nrl.navy.mil (Louis Pecora)
Date: Wed, 18 Oct 2006 19:59:52 -0400
Subject: [SciPy-user] Shape Problem
In-Reply-To: <1d2f6e8c0610181533t60b912c7j7b64ca5f9b3cdcf0@mail.gmail.com>
References: <1d2f6e8c0610180211w302dcc58l82abbbee6ed798d5@mail.gmail.com>	<45361C69.7090009@anvil.nrl.navy.mil>	<1d2f6e8c0610180753k7c414655k3e721efb98f1cc60@mail.gmail.com>	<4536673F.2070500@ieee.org>	<1d2f6e8c0610181157y69f84025j6fbe40fd649fa7c8@mail.gmail.com>	<4536A2D0.30900@ee.byu.edu>	<1d2f6e8c0610181518g463365aau748f58c5fef7a7b7@mail.gmail.com>	<4536A9FE.6090508@ee.byu.edu>
	<1d2f6e8c0610181533t60b912c7j7b64ca5f9b3cdcf0@mail.gmail.com>
Message-ID: <4536BFF8.4010203@anvil.nrl.navy.mil>

Sam frizou wrote:
> In fact I installed numpy from "SciPy Superpack for Python 2.4 (Intel)"
>
> Thank you very much
>
> On 10/19/06, Travis Oliphant <oliphant at ee.byu.edu> wrote:
>   
>> Sam frizou wrote:
>>
>>     
>>> <class 'numpy.core.defmatrix.matrix'>
>>> 0.5.0.2116
>>> 1.1.2880
>>>
>>>
>>>       
>> Your version of NumPy is old.  There were some issues with Matrix
>> indexing that were fixed a while ago.  The current revision is 3352 (you
>> are using revision 2880).   The 1.1 was a mis-nomer and was changed in
>> August I belived.
>>
>> The name for the most recent development version is
>>
>> 1.0.dev3359
>>
>>
>>
>> -Travis
>>     

I have the same version, but on a PPC Python2.4 version and I do not 
have the same problem.  Strange.

-- 
Cheers,

Lou Pecora

Code 6362
Naval Research Lab
Washington, DC  20375
USA
Ph:  +202-767-6002
email:  pecora at anvil.nrl.navy.mil



From cygnusx1 at mac.com  Wed Oct 18 20:58:29 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Wed, 18 Oct 2006 20:58:29 -0400
Subject: [SciPy-user] Partial success (was: numpy-1.0rc2 still does not
	build on MacOS X)
Message-ID: <0CDC2899-9497-45CC-A584-3B67EA6C8F51@mac.com>

Okay, I tried using gfortran instead of g77 for the Tiger PPC build  
(make sure /usr/bin/g77 is gone because scipy will try to use it if  
there).

A number of scipy tests fail, some apparently in some more important  
modules:

'cblas module is empty'
FAIL: check_rvs (scipy.stats.tests.test_distributions.test_randint)
FAIL: check loadmat case vec
FAIL: check_dot (scipy.lib.tests.test_blas.test_fblas1_simple)
FAIL: check_dot (scipy.linalg.tests.test_blas.test_fblas1_simple)

I'm concerned about some of these failures.

Suggestions?

Thanks,
Tom

Here's my general build instructions and scipy test output:


> gFortran
> % gunzip gfortran-bin.tar.gz
> % sudo tar -xvf gfortran-bin.tar -C /
>
> FFTW Libraries
> % sudo gcc_select 4.0
> % gnutar xzf fftw-3.1.2.tar.gz
> % cd fftw-3.1.2
> % ./configure
> % make
> % sudo make install
> % sudo ln -s /usr/local/lib/libfftw3.a /usr/local/lib/libfftw.a
> % sudo ln -s /usr/local/lib/libfftw3.la /usr/local/lib/libfftw.la
> % sudo ln -s /usr/local/include/fftw3.h /usr/local/include/fftw.h
>
> numpy
> % gnutar xzf numpy-1.0rc2.tar.gz
> % cd numpy-1.0rc2
> % sudo python setup.py install
> % python
> >>> import numpy
> >>> numpy.test(1,1)
> (ALL PASSED)
>
> % gnutar xzf scipy-0.5.1.tar.gz
> % cd scipy-0.5.1
> % sudo ln -s /usr/lib/gcc/powerpc-apple-darwin8/4.0.1/libgcc.a /usr/ 
> local/lib/libcc_dynamic.a
> % python setup.py build
> % sudo python setup.py install
> % python
> >>> import scipy
> >>> scipy.test(level=2)

Here the result of the test run

 >>> scipy.test(level=2)
   Found 4 tests for scipy.io.array_import
   Found 128 tests for scipy.linalg.fblas
   Found 397 tests for scipy.ndimage
   Found 10 tests for scipy.integrate.quadpack
   Found 97 tests for scipy.stats.stats
   Found 47 tests for scipy.linalg.decomp
   Found 2 tests for scipy.integrate.quadrature
   Found 95 tests for scipy.sparse.sparse
   Found 20 tests for scipy.fftpack.pseudo_diffs
   Found 6 tests for scipy.optimize.optimize
   Found 5 tests for scipy.interpolate.fitpack
   Found 1 tests for scipy.interpolate
   Found 70 tests for scipy.stats.distributions
   Found 12 tests for scipy.io.mmio
   Found 10 tests for scipy.stats.morestats
   Found 4 tests for scipy.linalg.lapack
   Found 18 tests for scipy.fftpack.basic
   Found 4 tests for scipy.linsolve.umfpack
   Found 4 tests for scipy.optimize.zeros
   Found 17 tests for scipy.io.mio
   Found 41 tests for scipy.linalg.basic
   Found 2 tests for scipy.maxentropy.maxentropy
   Found 358 tests for scipy.special.basic
   Found 128 tests for scipy.lib.blas.fblas
   Found 7 tests for scipy.linalg.matfuncs

****************************************************************
WARNING: clapack module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
   then scipy uses flapack instead of clapack.
****************************************************************

   Found 42 tests for scipy.lib.lapack
   Found 1 tests for scipy.optimize.cobyla
   Found 16 tests for scipy.lib.blas
   Found 1 tests for scipy.integrate
   Found 14 tests for scipy.linalg.blas
   Found 4 tests for scipy.fftpack.helper
   Found 4 tests for scipy.signal.signaltools
   Found 0 tests for __main__

Don't worry about a warning regarding the number of bytes read.
Warning: 1000000 bytes requested, 20 bytes read.
.......caxpy:n=4
..caxpy:n=3
....ccopy:n=4
..ccopy:n=3
.............cscal:n=4
....cswap:n=4
..cswap:n=3
.....daxpy:n=4
..daxpy:n=3
....dcopy:n=4
..dcopy:n=3
.............dscal:n=4
....dswap:n=4
..dswap:n=3
.....saxpy:n=4
..saxpy:n=3
....scopy:n=4
..scopy:n=3
.............sscal:n=4
....sswap:n=4
..sswap:n=3
.....zaxpy:n=4
..zaxpy:n=3
....zcopy:n=4
..zcopy:n=3
.............zscal:n=4
....zswap:n=4
..zswap:n=3
........................................................................ 
........................................................................ 
........................................................................ 
........................................................................ 
........................................................................ 
........................................................................ 
........................................................................ 
.................................................Took 13 points.
..........Resizing... 16 17 24
Resizing... 20 7 35
Resizing... 23 7 47
Resizing... 24 25 58
Resizing... 28 7 68
Resizing... 28 27 73
.....Use minimum degree ordering on A'+A.
........................Use minimum degree ordering on A'+A.
...................Resizing... 16 17 24
Resizing... 20 7 35
Resizing... 23 7 47
Resizing... 24 25 58
Resizing... 28 7 68
Resizing... 28 27 73
.....Use minimum degree ordering on A'+A.
.................Resizing... 16 17 24
Resizing... 20 7 35
Resizing... 23 7 47
Resizing... 24 25 58
Resizing... 28 7 68
Resizing... 28 27 73
.....Use minimum degree ordering on A'+A.
....................................../Library/Frameworks/ 
Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/ 
interpolate/fitpack2.py:410: UserWarning:
The coefficients of the spline returned have been computed as the
minimal norm least-squares solution of a (numerically) rank deficient
system (deficiency=7). If deficiency is large, the results may be
inaccurate. Deficiency may strongly depend on the value of eps.
   warnings.warn(message)
..................................................................F..... 
..................Ties preclude use of exact statistic.
..Ties preclude use of exact statistic.
........
****************************************************************
WARNING: clapack module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
   then scipy uses flapack instead of clapack.
****************************************************************

....................data-ftype: z compared to data D
Calling _superlu.zgssv
Use minimum degree ordering on A'+A.
.data-ftype: c compared to data F
Calling _superlu.cgssv
Use minimum degree ordering on A'+A.
.data-ftype: d compared to data d
Calling _superlu.dgssv
Use minimum degree ordering on A'+A.
.data-ftype: s compared to data f
Calling _superlu.sgssv
Use minimum degree ordering on A'+A.
.......E.............Warning: 184549376 bytes requested, 73 bytes read.
F....................................................................... 
........................................................................ 
........................................................................ 
........................................................................ 
........................................................................ 
.............................................caxpy:n=4
..caxpy:n=3
....ccopy:n=4
..ccopy:n=3
.............cscal:n=4
....cswap:n=4
..cswap:n=3
.....daxpy:n=4
..daxpy:n=3
....dcopy:n=4
..dcopy:n=3
.............dscal:n=4
....dswap:n=4
..dswap:n=3
.....saxpy:n=4
..saxpy:n=3
....scopy:n=4
..scopy:n=3
.............sscal:n=4
....sswap:n=4
..sswap:n=3
.....zaxpy:n=4
..zaxpy:n=3
....zcopy:n=4
..zcopy:n=3
.............zscal:n=4
....zswap:n=4
..zswap:n=3
...Result may be inaccurate, approximate err = 1.6582899877e-08
...Result may be inaccurate, approximate err = 4.54747350886e-13
......................................................F.......Residual:  
1.05006926991e-07
.
****************************************************************
WARNING: cblas module is empty
-----------
See scipy/INSTALL.txt for troubleshooting.
Notes:
* If atlas library is not found by numpy/distutils/system_info.py,
   then scipy uses fblas instead of cblas.
****************************************************************

.......F..............
======================================================================
ERROR: check loadmat case cellnest
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 80, in cc
     self._check_case(name, expected)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 75, in  
_check_case
     self._check_level(k_label, expected, matdict[k])
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in  
_check_level
     self._check_level(level_label, ev, actual[i])
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in  
_check_level
     self._check_level(level_label, ev, actual[i])
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in  
_check_level
     self._check_level(level_label, ev, actual[i])
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 30, in  
_check_level
     assert len(expected) == len(actual), "Different list lengths at % 
s" % label
TypeError: len() of unsized object

======================================================================
FAIL: check_rvs (scipy.stats.tests.test_distributions.test_randint)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/stats/tests/test_distributions.py",  
line 84, in check_rvs
     assert isinstance(val, numpy.ScalarType),`type(val)`
AssertionError: <type 'numpy.ndarray'>

======================================================================
FAIL: check loadmat case vec
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 80, in cc
     self._check_case(name, expected)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/io/tests/test_mio.py", line 74, in  
_check_case
     assert k in matdict, "Missing key at %s" % k_label
AssertionError: Missing key at Test 'vec', file:/Library/Frameworks/ 
Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/io/ 
tests/./data/testvec_4_GLNX86.mat, variable fit_params

======================================================================
FAIL: check_dot (scipy.lib.tests.test_blas.test_fblas1_simple)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/lib/blas/tests/test_blas.py", line 76,  
in check_dot
     assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/numpy/testing/utils.py", line 156, in  
assert_almost_equal
     assert round(abs(desired - actual),decimal) == 0, msg
AssertionError:
Items are not equal:
ACTUAL: (-1.9988694190979004+6.3421880632634224e-37j)
DESIRED: (-9+2j)

======================================================================
FAIL: check_dot (scipy.linalg.tests.test_blas.test_fblas1_simple)
----------------------------------------------------------------------
Traceback (most recent call last):
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/scipy/linalg/tests/test_blas.py", line 75, in  
check_dot
     assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
python2.4/site-packages/numpy/testing/utils.py", line 156, in  
assert_almost_equal
     assert round(abs(desired - actual),decimal) == 0, msg
AssertionError:
Items are not equal:
ACTUAL: (-1.9988694190979004+6.3421880632634224e-37j)
DESIRED: (-9+2j)

----------------------------------------------------------------------
Ran 1569 tests in 10.511s

FAILED (failures=4, errors=1)
<unittest.TextTestRunner object at 0x2db4f70>
 >>>



From oliphant.travis at ieee.org  Thu Oct 19 01:37:49 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Wed, 18 Oct 2006 23:37:49 -0600
Subject: [SciPy-user] Installing SciPy on Intel Macs
Message-ID: <45370F2D.7060602@ieee.org>


I've successfully installed SciPy on Intel Macs using gfortran and 
cctools 590.36

The last one is necessary to get rid of the __dso_handle error that I 
was getting with an older version of cctools.

I'm not sure if the new version of cctools is in the latest Xcode 
release of Mac OS X, but I suspect it is.  I just wanted to document 
this somewhere before I forget.

-Travis



From excellent.frizou at gmail.com  Thu Oct 19 05:25:19 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 11:25:19 +0200
Subject: [SciPy-user] Installing SciPy on Intel Macs
In-Reply-To: <45370F2D.7060602@ieee.org>
References: <45370F2D.7060602@ieee.org>
Message-ID: <1d2f6e8c0610190225n55ad6379o7f8e703d6cda1fb9@mail.gmail.com>

Hi,

I installed succesfully the latest version of numpy and scipy on my
macintel (as described on the scipy wesite:
-Apple's developer tools
-gcc-intel-bin.tar.gz
-fftw version 3.1.2
-numpy 1.0.rc2
-scipy-0.5.1
).

But, when I do
from scipy import *

I have an error which I think is one you describe:

ImportError: Failure linking new module:
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so:
Symbol not found: ___dso_handle
  Referenced from:
/Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so
  Expected in: dynamic lookup


So, I downloaded and installed cctools 590.36. (the dmg)

Then reinstalled scipy doing

python setup.py build
sudo python serup.py install

But I still have the same error when I do
from scipy import *

I read on previous mails that this can be avoid by commentting
something concerning sparse matrices, but I need them.

Can you please detail how you succeed in your installation please ?

Thanks

On 10/19/06, Travis Oliphant <oliphant.travis at ieee.org> wrote:
>
> I've successfully installed SciPy on Intel Macs using gfortran and
> cctools 590.36
>
> The last one is necessary to get rid of the __dso_handle error that I
> was getting with an older version of cctools.
>
> I'm not sure if the new version of cctools is in the latest Xcode
> release of Mac OS X, but I suspect it is.  I just wanted to document
> this somewhere before I forget.
>
> -Travis
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From marcos at burke.ath.cx  Thu Oct 19 08:01:23 2006
From: marcos at burke.ath.cx (=?ISO-8859-1?Q?Marcos_S=E1nchez_Provencio_Bke?=)
Date: Thu, 19 Oct 2006 14:01:23 +0200
Subject: [SciPy-user] python-scipy in amd64 ubuntu dapper
Message-ID: <45376913.208@burke.ath.cx>

To whom it may concern:
https://launchpad.net/distros/ubuntu/+source/python-scipy/+bug/66904

Binary package hint: python-scipy

In an amd64 dapper install

python -c 'import scipy.xplt as s; s.plmesh'

TypeError: Array can not be safely cast to required type

Can probably be corrected (does not throw exception, but I have not 
checked correct results) with

in /usr/lib/python2.4/site-packages/scipy/xplt/slice3:1578
   mask = find_mask (below, _node_edges3 [itype].astype(Int32))

/////////////

Sorry if this has been reported or if it does not belong here.


From nwagner at iam.uni-stuttgart.de  Thu Oct 19 08:16:22 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Thu, 19 Oct 2006 14:16:22 +0200
Subject: [SciPy-user] python-scipy in amd64 ubuntu dapper
In-Reply-To: <45376913.208@burke.ath.cx>
References: <45376913.208@burke.ath.cx>
Message-ID: <45376C96.3060606@iam.uni-stuttgart.de>

Marcos S?nchez Provencio Bke wrote:
> To whom it may concern:
> https://launchpad.net/distros/ubuntu/+source/python-scipy/+bug/66904
>
> Binary package hint: python-scipy
>
> In an amd64 dapper install
>
> python -c 'import scipy.xplt as s; s.plmesh'
>
> TypeError: Array can not be safely cast to required type
>
> Can probably be corrected (does not throw exception, but I have not 
> checked correct results) with
>
> in /usr/lib/python2.4/site-packages/scipy/xplt/slice3:1578
>    mask = find_mask (below, _node_edges3 [itype].astype(Int32))
>
> /////////////
>
> Sorry if this has been reported or if it does not belong here.
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   
AFAIK the sandbox package xplt is not ready for 64-bit.
You may switch over to matplotlib.

Nils
 


From jimmy.touma.ctr at eglin.af.mil  Thu Oct 19 09:29:50 2006
From: jimmy.touma.ctr at eglin.af.mil (Touma Jimmy E CTR USAF AFRL/MNGG)
Date: Thu, 19 Oct 2006 08:29:50 -0500
Subject: [SciPy-user] interp1d question
Message-ID: <B723C39656E9B74E8DA2012A36AEB2632FAF63@mail15.eglin.af.mil>

Thanks Robert. I will update my version. However, x is an array with one
dimension(Mx1). 'u' on the other hand is an array with MxN dimensions and I
was wanting to interpolate column wise as opposed to row wise (that'll save
me a couple of operation after reading the data in from a file)

Thanks,
Jimmy


PS. It works row wise...



-----Original Message-----
From: scipy-user-bounces at scipy.org [mailto:scipy-user-bounces at scipy.org] On
Behalf Of Robert Kern
Sent: Wednesday, October 18, 2006 4:35 PM
To: SciPy Users List
Subject: Re: [SciPy-user] interp1d question

Touma Jimmy E CTR USAF AFRL/MNGG wrote:
> Hi all,
> 
> 
> I am trying to interpolate in 1d along a columns as opposed to rows
> and it doesn't seem to work. The code below emulates reading data
> where interpolation should be done column wise. The error when
> running this code follows. If you could please tell me what I am doing
> wrong and how to interpolate along columns.

> /usr/lib/python2.4/site-packages/scipy/interpolate/interpolate.py in 
> __init__(self, x, y, kind, axis, copy, bounds_error, fill_value)
> 
>     143         len_x,len_y = shape(oriented_x)[interp_axis], 
> shape(oriented_y)[interp_axis]
>     144         if len_x != len_y:
> --> 145             raise ValueError, "x and y arrays must be equal in 
> length along "\
>     146                               "interpolation axis."
>     147         if len_x < 2 or len_y < 2:
> 
> ValueError: x and y arrays must be equal in length along interpolation 
> axis.
> WARNING: Failure executing file: <d1.py>
> 
> In [3]: numpy.__version__
> Out[3]: '1.0b5'
> 
> In [4]: scipy.__version__
> Out[4]: '0.3.2'

You have a *very* old version of scipy. It uses Numeric, not numpy. Please
upgrade.

In recent versions, interp1d does not accept x arrays with more than one 
dimension. I'm not entirely sure why the old version did; it makes no sense.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it
had
  an underlying truth."
   -- Umberto Eco
_______________________________________________
SciPy-user mailing list
SciPy-user at scipy.org
http://projects.scipy.org/mailman/listinfo/scipy-user
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From oliphant.travis at ieee.org  Thu Oct 19 09:48:08 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Thu, 19 Oct 2006 07:48:08 -0600
Subject: [SciPy-user] Installing SciPy on Intel Macs
In-Reply-To: <1d2f6e8c0610190225n55ad6379o7f8e703d6cda1fb9@mail.gmail.com>
References: <45370F2D.7060602@ieee.org>
	<1d2f6e8c0610190225n55ad6379o7f8e703d6cda1fb9@mail.gmail.com>
Message-ID: <45378218.1010904@ieee.org>

Sam frizou wrote:
> Hi,
>
> I installed succesfully the latest version of numpy and scipy on my
> macintel (as described on the scipy wesite:
> -Apple's developer tools
> -gcc-intel-bin.tar.gz
> -fftw version 3.1.2
> -numpy 1.0.rc2
> -scipy-0.5.1
> ).
>
> But, when I do
> from scipy import *
>
> I have an error which I think is one you describe:
>
> ImportError: Failure linking new module:
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so:
> Symbol not found: ___dso_handle
>   Referenced from:
> /Library/Frameworks/Python.framework/Versions/2.4/lib/python2.4/site-packages/scipy/sparse/sparsetools.so
>   Expected in: dynamic lookup
>
>
> So, I downloaded and installed cctools 590.36. (the dmg)
>
> Then reinstalled scipy doing
>
> python setup.py build
> sudo python serup.py install
>   
You need to remove the build directory and redo the install.  Otherwise 
the codes are not re-linked using the upgraded cctools.

That's all I did and it seemed to work.

> I read on previous mails that this can be avoid by commentting
> something concerning sparse matrices, but I need them.
>   
I think that's a separate issue.

-Travis



From excellent.frizou at gmail.com  Thu Oct 19 10:51:47 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 16:51:47 +0200
Subject: [SciPy-user] Invert of a sparse matrix
Message-ID: <1d2f6e8c0610190751p6fab62fev5dc5b5bfcef5d5c3@mail.gmail.com>

Hi,

Is there a trick for computing the invert of a square SPARSE matrix ?

Thanks


From nwagner at iam.uni-stuttgart.de  Thu Oct 19 10:58:53 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Thu, 19 Oct 2006 16:58:53 +0200
Subject: [SciPy-user] Invert of a sparse matrix
In-Reply-To: <1d2f6e8c0610190751p6fab62fev5dc5b5bfcef5d5c3@mail.gmail.com>
References: <1d2f6e8c0610190751p6fab62fev5dc5b5bfcef5d5c3@mail.gmail.com>
Message-ID: <453792AD.1030204@iam.uni-stuttgart.de>

Sam frizou wrote:
> Hi,
>
> Is there a trick for computing the invert of a square SPARSE matrix ?
>
> Thanks
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   
You can solve n equations where the i-th rhs is a unit-vector e_i in the
corresponding direction.
But why do you need the inverse of a sparse matrix ?

Nils



From excellent.frizou at gmail.com  Thu Oct 19 11:12:53 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 17:12:53 +0200
Subject: [SciPy-user] Invert of a sparse matrix
In-Reply-To: <453792AD.1030204@iam.uni-stuttgart.de>
References: <1d2f6e8c0610190751p6fab62fev5dc5b5bfcef5d5c3@mail.gmail.com>
	<453792AD.1030204@iam.uni-stuttgart.de>
Message-ID: <1d2f6e8c0610190812r263d1cc3ocbedae46ed3eccca@mail.gmail.com>

> But why do you need the inverse of a sparse matrix ?
I compute generators of homology groups of combinatorial objects.
For that I use HUGE and SPARSE matrices.

thanks,


From robert.kern at gmail.com  Thu Oct 19 11:14:14 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Thu, 19 Oct 2006 10:14:14 -0500
Subject: [SciPy-user] interp1d question
In-Reply-To: <B723C39656E9B74E8DA2012A36AEB2632FAF63@mail15.eglin.af.mil>
References: <B723C39656E9B74E8DA2012A36AEB2632FAF63@mail15.eglin.af.mil>
Message-ID: <45379646.8060003@gmail.com>

Touma Jimmy E CTR USAF AFRL/MNGG wrote:
> Thanks Robert. I will update my version. However, x is an array with one 
> dimension(Mx1). 'u' on the other hand is an array with MxN dimensions 
> and I was wanting to interpolate column wise as opposed to row wise 
> (that'll save me a couple of operation after reading the data in from a 
> file)

No, x has two dimensions, (M, 1).

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From strawman at astraw.com  Thu Oct 19 11:46:34 2006
From: strawman at astraw.com (Andrew Straw)
Date: Thu, 19 Oct 2006 08:46:34 -0700
Subject: [SciPy-user] python-scipy in amd64 ubuntu dapper
In-Reply-To: <45376C96.3060606@iam.uni-stuttgart.de>
References: <45376913.208@burke.ath.cx> <45376C96.3060606@iam.uni-stuttgart.de>
Message-ID: <45379DDA.1010808@astraw.com>

Nils Wagner wrote:
> Marcos S?nchez Provencio Bke wrote:
>   
>> To whom it may concern:
>> https://launchpad.net/distros/ubuntu/+source/python-scipy/+bug/66904
>>     
> AFAIK the sandbox package xplt is not ready for 64-bit.
> You may switch over to matplotlib.
>   
Furthermore, Ubuntu's official Dapper packages for scipy are 0.3.2,
which are not going to receive much care from the developers, who are
now focused on 0.5.x development. You're welcome to use my Dapper
packages of the newer release, as described here:
http://scipy.org/Installing_SciPy/Linux


From cimrman3 at ntc.zcu.cz  Thu Oct 19 11:53:38 2006
From: cimrman3 at ntc.zcu.cz (Robert Cimrman)
Date: Thu, 19 Oct 2006 17:53:38 +0200
Subject: [SciPy-user] Invert of a sparse matrix
In-Reply-To: <453792AD.1030204@iam.uni-stuttgart.de>
References: <1d2f6e8c0610190751p6fab62fev5dc5b5bfcef5d5c3@mail.gmail.com>
	<453792AD.1030204@iam.uni-stuttgart.de>
Message-ID: <45379F82.5010701@ntc.zcu.cz>

Nils Wagner wrote:
> Sam frizou wrote:
>> Hi,
>>
>> Is there a trick for computing the invert of a square SPARSE matrix ?
>>
>> Thanks
>> _______________________________________________
>> SciPy-user mailing list
>> SciPy-user at scipy.org
>> http://projects.scipy.org/mailman/listinfo/scipy-user
>>   
> You can solve n equations where the i-th rhs is a unit-vector e_i in the
> corresponding direction.

and for this you should first perform LU factorization and then use the
pre-factorized matrix for the multiple-rhs problem, see scipy.linsolve docs.

r.


From excellent.frizou at gmail.com  Thu Oct 19 12:49:11 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Thu, 19 Oct 2006 18:49:11 +0200
Subject: [SciPy-user] Sparse matrices operations
Message-ID: <1d2f6e8c0610190949s3491b4e2qd4d5af42832ef111@mail.gmail.com>

Hi,

I use sparse matrices and I have to do row and column operations.

1) Is it possible to assign an entire row ? an entire column ?
for example if R is a lil_matrix of shape (1,10) and M is a lil_matrix
of shape (3,10) and I want to assign R to the second row of M. I am
looking for something like:
M[2,:]=R
or
M.setrow(2,R)

2) Is it possible to have the list of the empty coordinates ? ("where"
does not seem to be implemented yet)

Thanks


From jkgruet at sandia.gov  Thu Oct 19 15:14:43 2006
From: jkgruet at sandia.gov (James K. Gruetzner)
Date: Thu, 19 Oct 2006 13:14:43 -0600
Subject: [SciPy-user] numpy - scipy version hell
Message-ID: <200610191314.49095.jkgruet@sandia.gov>

I'm using Fedora core 5, that insect-laden wonder, which includes python 
2.4.3.  I'm trying to install numpy (scipy-core) and scipy (the rest).   I 
can't seem to get around package conflicts.  I've tried two methods, one in 
which numpy fails and one in which scipy fails.   This is the "scipy fails" 
one (I sent the numpy fails one to the numpy-discussions list).  

METHOD 2 (scipy fails)
OK, remove the previously installed numpy packages 
from /usr/lib/python2.4/site-packages.  Now use yum to install numpy 
0.9.8-1.fc5 from the extras repository.   Hooray, numpy imports fine!
So, now time to download scipy, v.0.5.1.  Untarball it and cd.  IT fails to 
install, with the following (long) error message:

non-existing path in 'Lib/maxentropy': 'doc'
Traceback (most recent call last):
  File "setup.py", line 55, in ?
    setup_package()
  File "setup.py", line 47, in setup_package
    configuration=configuration )
  File "/usr/lib/python2.4/site-packages/numpy/distutils/core.py", line 140, 
in setup
    config = configuration()
  File "setup.py", line 19, in configuration
    config.add_subpackage('Lib')
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
740, in add_subpackage
    caller_level = 2)
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
723, in get_subpackage
    caller_level = caller_level + 1)
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
670, in _get_configuration_from_setup_py
    config = setup_module.configuration(*args)
  File "./Lib/setup.py", line 22, in configuration
    config.add_subpackage('ndimage')
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
740, in add_subpackage
    caller_level = 2)
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
723, in get_subpackage
    caller_level = caller_level + 1)
  File "/usr/lib/python2.4/site-packages/numpy/distutils/misc_util.py", line 
655, in _get_configuration_from_setup_py
    ('.py', 'U', 1))
  File "Lib/ndimage/setup.py", line 3, in ?
    from numpy.numarray import get_numarray_include_dirs
ImportError: No module named numarray

I suspect that there's a bit of out-of-sync with the packages, but am not 
sure.  Bottom line question:  how do I get both installed at once?

Thanks!
   James




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From oliphant at ee.byu.edu  Thu Oct 19 15:17:29 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Thu, 19 Oct 2006 13:17:29 -0600
Subject: [SciPy-user] numpy - scipy version hell
In-Reply-To: <200610191314.49095.jkgruet@sandia.gov>
References: <200610191314.49095.jkgruet@sandia.gov>
Message-ID: <4537CF49.8000008@ee.byu.edu>

James K. Gruetzner wrote:

>I'm using Fedora core 5, that insect-laden wonder, which includes python 
>2.4.3.  I'm trying to install numpy (scipy-core) and scipy (the rest).   I 
>can't seem to get around package conflicts.  I've tried two methods, one in 
>which numpy fails and one in which scipy fails.   This is the "scipy fails" 
>one (I sent the numpy fails one to the numpy-discussions list).  
>
>  
>
Very few packages will have the correct versions of numpy and scipy that 
work together.

The latest that work together is Scipy 0.5.1 and NumPy 1.0rc2

Look for an updated SciPy release to work with NumPy 1.0 when it comes 
out next week.

-Travis



From robert.kern at gmail.com  Thu Oct 19 15:19:01 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Thu, 19 Oct 2006 14:19:01 -0500
Subject: [SciPy-user] numpy - scipy version hell
In-Reply-To: <200610191314.49095.jkgruet@sandia.gov>
References: <200610191314.49095.jkgruet@sandia.gov>
Message-ID: <4537CFA5.1040002@gmail.com>

James K. Gruetzner wrote:
> I'm using Fedora core 5, that insect-laden wonder, which includes python 
> 2.4.3.  I'm trying to install numpy (scipy-core) and scipy (the rest).   I 
> can't seem to get around package conflicts.  I've tried two methods, one in 
> which numpy fails and one in which scipy fails.   This is the "scipy fails" 
> one (I sent the numpy fails one to the numpy-discussions list).  
> 
> METHOD 2 (scipy fails)
> OK, remove the previously installed numpy packages 
> from /usr/lib/python2.4/site-packages.  Now use yum to install numpy 
> 0.9.8-1.fc5 from the extras repository.   Hooray, numpy imports fine!
> So, now time to download scipy, v.0.5.1.  Untarball it and cd.  IT fails to 
> install, with the following (long) error message:

numpy 0.9.8 is quite old compared to scipy 0.5.1. You will want the recent 
1.0rc3 release.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From jkgruet at sandia.gov  Thu Oct 19 15:25:22 2006
From: jkgruet at sandia.gov (James K. Gruetzner)
Date: Thu, 19 Oct 2006 13:25:22 -0600
Subject: [SciPy-user] numpy - scipy version hell
In-Reply-To: <4537CFA5.1040002@gmail.com>
References: <200610191314.49095.jkgruet@sandia.gov>
	<4537CFA5.1040002@gmail.com>
Message-ID: <200610191325.24097.jkgruet@sandia.gov>

Thanks much, Robert.  Alas, that's where METHOD 1 (numpy fails) has its 
problem.   I can't get numpy 1.0rc3 to install:  it gives a different error 
(undefined symbol: s_cat).  

Thanks again.
   James

On Thursday 19 October 2006 13:19, you wrote:
> James K. Gruetzner wrote:
> > I'm using Fedora core 5, that insect-laden wonder, which includes python
> > 2.4.3.  I'm trying to install numpy (scipy-core) and scipy (the rest).  
> > I can't seem to get around package conflicts.  I've tried two methods,
> > one in which numpy fails and one in which scipy fails.   This is the
> > "scipy fails" one (I sent the numpy fails one to the numpy-discussions
> > list).
> >
> > METHOD 2 (scipy fails)
> > OK, remove the previously installed numpy packages
> > from /usr/lib/python2.4/site-packages.  Now use yum to install numpy
> > 0.9.8-1.fc5 from the extras repository.   Hooray, numpy imports fine!
> > So, now time to download scipy, v.0.5.1.  Untarball it and cd.  IT fails
> > to install, with the following (long) error message:
>
> numpy 0.9.8 is quite old compared to scipy 0.5.1. You will want the recent
> 1.0rc3 release.
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From cygnusx1 at mac.com  Thu Oct 19 20:02:56 2006
From: cygnusx1 at mac.com (Tom Bridgman)
Date: Thu, 19 Oct 2006 20:02:56 -0400
Subject: [SciPy-user] numpy-1.0rc3 on MacOS X 10.4 (PPC). Builds with errors,
	tests fail
Message-ID: <A7761C73-9B5B-424B-AB35-98C8357CBE0F@mac.com>

Still trying to get scipy working.  Saw the new numpy and tried it  
under gFortran & fftw-3.1.2.

Seems to build okay but tests generate many warnings, then fail.  A  
number of errors appear in _configuretest.c:4 stage of the build.  I  
had to truncate the listing as it exceeding the posting limit for  
this list.

Here's the test output for numpy.

Suggestions welcome.

> Planck:/Users/Shared/ToBeRestored/Python bridgman$ python
> Python 2.4.3 (#1, Apr  7 2006, 10:54:33)
> [GCC 4.0.1 (Apple Computer, Inc. build 5250)] on darwin
> Type "help", "copyright", "credits" or "license" for more information.
> >>> import numpy
> >>> numpy.test(1,1)
>   Found 5 tests for numpy.distutils.misc_util
>   Found 3 tests for numpy.lib.getlimits
>   Found 31 tests for numpy.core.numerictypes
>   Found 32 tests for numpy.linalg
>   Found 13 tests for numpy.core.umath
>   Found 4 tests for numpy.core.scalarmath
>   Found 9 tests for numpy.lib.arraysetops
>   Found 42 tests for numpy.lib.type_check
>   Found 183 tests for numpy.core.multiarray
>   Found 3 tests for numpy.fft.helper
>   Found 36 tests for numpy.core.ma
>   Found 12 tests for numpy.lib.twodim_base
>   Found 10 tests for numpy.core.defmatrix
>   Found 1 tests for numpy.lib.ufunclike
>   Found 4 tests for numpy.ctypeslib
>   Found 41 tests for numpy.lib.function_base
>   Found 2 tests for numpy.lib.polynomial
>   Found 8 tests for numpy.core.records
>   Found 26 tests for numpy.core.numeric
>   Found 4 tests for numpy.lib.index_tricks
>   Found 47 tests for numpy.lib.shape_base
>   Found 0 tests for __main__
> ...................................................................... 
> .................................Warning: invalid value encountered  
> in divide
> ..Warning: invalid value encountered in divide
> ..Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> ..Warning: invalid value encountered in divide
> .Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> ..Warning: invalid value encountered in divide
> ..Warning: invalid value encountered in divide
> ..Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> .Warning: divide by zero encountered in divide
> ........Warning: invalid value encountered in divide
> .Warning: invalid value encountered in divide
> ..Warning: divide by zero encountered in divide
> ...................................................................... 
> ................................................F..................... 
> ............................................................Warning: d 
> ivide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> Warning: divide by zero encountered in divide
> .....................Warning: invalid value encountered in sqrt
> Warning: invalid value encountered in log
> Warning: invalid value encountered in log10
> ..Warning: invalid value encountered in sqrt
> Warning: invalid value encountered in sqrt
> Warning: divide by zero encountered in log
> Warning: divide by zero encountered in log
> Warning: divide by zero encountered in log10
> Warning: divide by zero encountered in log10
> Warning: invalid value encountered in arcsin
> Warning: invalid value encountered in arcsin
> Warning: invalid value encountered in arccos
> Warning: invalid value encountered in arccos
> Warning: invalid value encountered in arccosh
> Warning: invalid value encountered in arccosh
> Warning: divide by zero encountered in arctanh
> Warning: divide by zero encountered in arctanh
> Warning: invalid value encountered in divide
> Warning: invalid value encountered in true_divide
> Warning: invalid value encountered in floor_divide
> Warning: invalid value encountered in remainder
> Warning: invalid value encountered in fmod
> ...................................................................... 
> ...................................................................... 
> ...................
> ======================================================================
> FAIL: Ticket #112
> ----------------------------------------------------------------------
> Traceback (most recent call last):
>   File "/Library/Frameworks/Python.framework/Versions/2.4/lib/ 
> python2.4/site-packages/numpy/core/tests/test_regression.py", line  
> 219, in check_longfloat_repr
>     assert(str(a)[1:9] == str(a[0])[:8])
> AssertionError
>
> ----------------------------------------------------------------------
> Ran 516 tests in 1.782s
>
> FAILED (failures=1)
> <unittest.TextTestRunner object at 0x1636ed0>
> >>>
>

Here's the build output:

Planck:/Users/Shared/ToBeRestored/Python/numpy-1.0rc3 bridgman$  
python setup.py build
Running from numpy source directory.
F2PY Version 2_3364
blas_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec', '-I/System/Library/Frameworks/ 
vecLib.framework/Headers']

lapack_opt_info:
   FOUND:
     extra_link_args = ['-Wl,-framework', '-Wl,Accelerate']
     define_macros = [('NO_ATLAS_INFO', 3)]
     extra_compile_args = ['-faltivec']

running build
running config_fc
running build_src
building py_modules sources
creating build
creating build/src.macosx-10.4-fat-2.4
creating build/src.macosx-10.4-fat-2.4/numpy
creating build/src.macosx-10.4-fat-2.4/numpy/distutils
building extension "numpy.core.multiarray" sources
creating build/src.macosx-10.4-fat-2.4/numpy/core
Generating build/src.macosx-10.4-fat-2.4/numpy/core/config.h
customize NAGFCompiler
customize AbsoftFCompiler
customize IbmFCompiler
Could not locate executable g77
Could not locate executable f77
Could not locate executable f95
customize GnuFCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler
customize Gnu95FCompiler using config
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-I/Library/Frameworks/Python.framework/Versions/2.4/ 
include/python2.4 -Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -L/Library/Frameworks/Python.framework/Versions/2.4/ 
lib -L/usr/local/lib -L/usr/lib -o _configtest
_configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
_configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
gcc _configtest.o -o _configtest
success!
removing: _configtest.c _configtest.o _configtest
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
_configtest.c: In function 'main':
_configtest.c:4: error: 'isnan' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
_configtest.c: In function 'main':
_configtest.c:4: error: 'isnan' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
lipo: can't figure out the architecture type of: /var/tmp//ccpygvET.out
_configtest.c: In function 'main':
_configtest.c:4: error: 'isnan' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
_configtest.c: In function 'main':
_configtest.c:4: error: 'isnan' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
lipo: can't figure out the architecture type of: /var/tmp//ccpygvET.out
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

compile options: '-Inumpy/core/src -Inumpy/core/include -I/Library/ 
Frameworks/Python.framework/Versions/2.4/include/python2.4 -c'
gcc: _configtest.c
_configtest.c: In function 'main':
_configtest.c:4: error: 'isinf' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
_configtest.c: In function 'main':
_configtest.c:4: error: 'isinf' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
lipo: can't figure out the architecture type of: /var/tmp//ccEsTb4T.out
_configtest.c: In function 'main':
_configtest.c:4: error: 'isinf' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
_configtest.c: In function 'main':
_configtest.c:4: error: 'isinf' undeclared (first use in this function)
_configtest.c:4: error: (Each undeclared identifier is reported only  
once
_configtest.c:4: error: for each function it appears in.)
lipo: can't figure out the architecture type of: /var/tmp//ccEsTb4T.out
failure.
removing: _configtest.c _configtest.o
C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ 
MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp  
-mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3

[truncated]


From alan at ajackson.org  Thu Oct 19 23:03:25 2006
From: alan at ajackson.org (Alan Jackson)
Date: Thu, 19 Oct 2006 22:03:25 -0500
Subject: [SciPy-user] fft giving error
Message-ID: <20061019220325.ed3fc35b.alan@ajackson.org>

I'm trying to run the example from http://linuxgazette.net/115/andreasen.html
to plot the frequency spectrum of sunspot numbers from ipython...

     from scipy import *
     from scipy import fftpack
     
     from scipy.io import read_array
     sunspot = read_array('sunspots.dat')
     
     year=sunspot[:,0]
     wolfer=sunspot[:,1]
     Y=fft(wolfer)

and I get the following error....


In [68]: Y=fft(wolfer)
---------------------------------------------------------------------------
exceptions.TypeError                                 Traceback (most recent call last)

/home/ajackson/projects/cyclicity/<console> 

TypeError: 'module' object is not callable


Running gentoo Linux, 2.6.16-gentoo-r3, AMD Athlon X2 64 bit,
blas-atlas-3.7.17
lapack-atlas-3.7.17
scipy-0.5.1
numpy-1.0_rc1
python-2.4.3

Parenthetically, it all builds quite nicely with the gentoo emerge. Kudos
to the gentoo package maintainers.

-- 
-----------------------------------------------------------------------
| Alan K. Jackson            | To see a World in a Grain of Sand      |
| alan at ajackson.org          | And a Heaven in a Wild Flower,         |
| www.ajackson.org           | Hold Infinity in the palm of your hand |
| Houston, Texas             | And Eternity in an hour. - Blake       |
-----------------------------------------------------------------------


From pgmdevlist at gmail.com  Thu Oct 19 23:14:49 2006
From: pgmdevlist at gmail.com (Pierre GM)
Date: Thu, 19 Oct 2006 23:14:49 -0400
Subject: [SciPy-user] fft giving error
In-Reply-To: <20061019220325.ed3fc35b.alan@ajackson.org>
References: <20061019220325.ed3fc35b.alan@ajackson.org>
Message-ID: <200610192314.49503.pgmdevlist@gmail.com>

On Thursday 19 October 2006 23:03, Alan Jackson wrote:
> I'm trying to run the example from
> http://linuxgazette.net/115/andreasen.html to plot the frequency spectrum
> of sunspot numbers from ipython...
>
>      from scipy import *
>      from scipy import fftpack

When you type 
from scipy import *
I think you also import the fft module from numpy (as there's a from numpy 
import * in scipy.__init__). So 'fft' is the package numpy.fft
When you type
from scipy import fftpack
the fft routine is available as fftpack.fft

So, if you wanna overwrite fft, you should do
from scipy.fftpack import *




From ckkart at hoc.net  Fri Oct 20 03:06:29 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Fri, 20 Oct 2006 16:06:29 +0900
Subject: [SciPy-user] fft giving error
In-Reply-To: <20061019220325.ed3fc35b.alan@ajackson.org>
References: <20061019220325.ed3fc35b.alan@ajackson.org>
Message-ID: <45387575.5070003@hoc.net>

Alan Jackson wrote:
> I'm trying to run the example from http://linuxgazette.net/115/andreasen.html
> to plot the frequency spectrum of sunspot numbers from ipython...
> 
>      from scipy import *
>      from scipy import fftpack
>      
>      from scipy.io import read_array
>      sunspot = read_array('sunspots.dat')
>      
>      year=sunspot[:,0]
>      wolfer=sunspot[:,1]
>      Y=fft(wolfer)
> 
> and I get the following error....
> 
> 
> In [68]: Y=fft(wolfer)
> ---------------------------------------------------------------------------
> exceptions.TypeError                                 Traceback (most recent call last)
> 
> /home/ajackson/projects/cyclicity/<console> 
> 
> TypeError: 'module' object is not callable

I think, some numpy/scipy modules have been rearranged since that article was
written. In fact the line
from scipy import fftpack
is not needed since fftpack is not used in the script.
With
from scipy import *
you'll now import a *module* called fft. The function you're looking for is then
called fft.fft. Try help(fft).

Christian


From trond.danielsen at gmail.com  Fri Oct 20 05:17:06 2006
From: trond.danielsen at gmail.com (Trond Danielsen)
Date: Fri, 20 Oct 2006 11:17:06 +0200
Subject: [SciPy-user] Building scipy on FC5 x86_64
Message-ID: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>

Hi!

I am trying to build scipy on Fedora Core 5 (x86_64), but setup.py
cannot find the required libraries. How can I add /usr/lib64 to the
lib-path?

I have followed the instructions on the website for installing on fc5,
so the required libs are installed. scipy version is 0.4.8 and numpy
is the latest from fedora extra.

Best regards,
-- 
Trond Danielsen


From nwagner at iam.uni-stuttgart.de  Fri Oct 20 05:24:32 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Fri, 20 Oct 2006 11:24:32 +0200
Subject: [SciPy-user] Building scipy on FC5 x86_64
In-Reply-To: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
References: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
Message-ID: <453895D0.5050908@iam.uni-stuttgart.de>

Trond Danielsen wrote:
> Hi!
>
> I am trying to build scipy on Fedora Core 5 (x86_64), but setup.py
> cannot find the required libraries. How can I add /usr/lib64 to the
> lib-path?
>
> I have followed the instructions on the website for installing on fc5,
> so the required libs are installed. scipy version is 0.4.8 and numpy
> is the latest from fedora extra.
>
> Best regards,
>   
AFAIK you can add an entry in the file system_info.py in line 140
(numpy/numpy/distutils).

Nils
 


From ndbecker2 at gmail.com  Fri Oct 20 09:54:37 2006
From: ndbecker2 at gmail.com (Neal Becker)
Date: Fri, 20 Oct 2006 09:54:37 -0400
Subject: [SciPy-user] Building scipy on FC5 x86_64
References: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
	<453895D0.5050908@iam.uni-stuttgart.de>
Message-ID: <ehakh2$he8$1@sea.gmane.org>

Nils Wagner wrote:

> Trond Danielsen wrote:
>> Hi!
>>
>> I am trying to build scipy on Fedora Core 5 (x86_64), but setup.py
>> cannot find the required libraries. How can I add /usr/lib64 to the
>> lib-path?
>>
>> I have followed the instructions on the website for installing on fc5,
>> so the required libs are installed. scipy version is 0.4.8 and numpy
>> is the latest from fedora extra.
>>
>> Best regards,
>>   
> AFAIK you can add an entry in the file system_info.py in line 140
> (numpy/numpy/distutils).
> 
> Nils
env CFLAGS="$RPM_OPT_FLAGS" ATLAS=%{_libdir} FFTW=%{_libdir} BLAS=%{_libdir} 
LAPACK=%{_libdir} python setup.py config_fc --fcompiler=gnu95 build



From icy.flame.gm at gmail.com  Fri Oct 20 10:20:21 2006
From: icy.flame.gm at gmail.com (iCy-fLaME)
Date: Fri, 20 Oct 2006 15:20:21 +0100
Subject: [SciPy-user] scipy.test failures=22, errors=3;
	Looks like i am doing something horribly wrong again.
Message-ID: <bfb379e10610200720k7f81f661rb093ff56d076a607@mail.gmail.com>

Any thoughts are appreciated.



Python 2.4.3 (#1, Jun 13 2006, 16:41:18)
[GCC 4.0.2 20051125 (Red Hat 4.0.2-8)] on linux2

>>> import numpy.version
>>> numpy.version.version
'1.0rc3'
>>> import scipy
>>> scipy.version.version
'0.5.1'
>>> scipy.test(level=1)

======================================================================
ERROR: line-search Newton conjugate gradient optimization routine
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/optimize/tests/test_optimize.py",
line 104, in check_ncg
    full_output=False, disp=False, retall=False)
  File "/usr/lib/python2.4/site-packages/scipy/optimize/optimize.py",
line 971, in fmin_ncg
    alphak, fc, gc, old_fval = line_search_BFGS(f,xk,pk,gfk,old_fval)
  File "/usr/lib/python2.4/site-packages/scipy/optimize/optimize.py",
line 535, in line_search_BFGS
    phi_a2 = apply(f,(xk+alpha2*pk,)+args)
  File "/usr/lib/python2.4/site-packages/scipy/optimize/optimize.py",
line 94, in function_wrapper
    return function(x, *args)
  File "/usr/lib/python2.4/site-packages/scipy/optimize/tests/test_optimize.py",
line 31, in func
    raise RuntimeError, "too many iterations in optimization routine"
RuntimeError: too many iterations in optimization routine

======================================================================
ERROR: Solve: single precision complex
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/linsolve/umfpack/tests/test_umfpack.py",
line 25, in check_solve_complex_without_umfpack
    x = linsolve.spsolve(a, b)
  File "/usr/lib/python2.4/site-packages/scipy/linsolve/linsolve.py",
line 76, in spsolve
    return gssv(N, lastel, data, index0, index1, b, csc, permc_spec)[0]
TypeError: array cannot be safely cast to required type

======================================================================
ERROR: check loadmat case cellnest
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 80, in cc
    self._check_case(name, expected)
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 75, in _check_case
    self._check_level(k_label, expected, matdict[k])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py",
line 30, in _check_level
    assert len(expected) == len(actual), "Different list lengths at %s" % label
TypeError: len() of unsized object

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_diff)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 85, in check_definition
    assert_array_almost_equal(diff(sin(x)),direct_diff(sin(x)))
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 87.5%)
 x: array([  1.00000000e+00,   9.23879533e-01,   7.07106781e-01,
         3.82683432e-01,   8.80098148e-17,  -3.82683432e-01,
        -7.07106781e-01,  -9.23879533e-01,  -1.00000000e-00,...
 y: array([ -0.00000000e+00,   5.00000000e-01,   7.76627939e-17,
         1.29677356e-16,   1.24900090e-16,   2.16128927e-16,
         1.49721655e-16,  -9.71445147e-17,   0.00000000e+00,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_hilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 301, in check_definition
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 87.5%)
 x: array([  1.00000000e+00,   9.23879533e-01,   7.07106781e-01,
         3.82683432e-01,   8.23044233e-17,  -3.82683432e-01,
        -7.07106781e-01,  -9.23879533e-01,  -1.00000000e+00,...
 y: array([ -0.00000000e+00 +0.00000000e+00j,
         5.00000000e-01 -7.31057196e-17j,
         3.88313970e-17 -2.42387134e-17j,...

======================================================================
FAIL: check_random_even (scipy.fftpack.tests.test_pseudo_diffs.test_hilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 332, in check_random_even
    assert_array_almost_equal(direct_hilbert(direct_ihilbert(f)),f)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([  0.00000000e+00+0.j        ,  -3.39208538e-04+0.00036363j,
        -1.06020671e-03-0.00021316j,  -5.23844841e-04+0.00028867j,
         3.09111343e-04-0.0020875j ,   7.67990574e-04+0.00133127j,...
 y: array([-0.11060715, -0.49769099,  0.47834226, -0.33737298,  0.24581014,
        0.02109089, -0.4631084 ,  0.19285299,  0.47922014, -0.39063467,
        0.22212061,  0.031721  ,  0.04744712, -0.10681613, -0.04652146,...

======================================================================
FAIL: check_tilbert_relation
(scipy.fftpack.tests.test_pseudo_diffs.test_hilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 311, in check_tilbert_relation
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 62.5%)
 x: array([  1.00000000e+00,   6.53281482e-01,   2.12809267e-16,
        -2.70598050e-01,  -1.06260199e-16,   2.70598050e-01,
         1.53930800e-16,  -6.53281482e-01,  -1.00000000e+00,...
 y: array([ -0.00000000e+00 +0.00000000e+00j,
         2.50000000e-01 -3.52840045e-17j,
        -1.19052598e-18 +4.47468130e-17j,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_ihilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 370, in check_definition
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 87.5%)
 x: array([ -1.00000000e+00,  -9.23879533e-01,  -7.07106781e-01,
        -3.82683432e-01,  -8.23044233e-17,   3.82683432e-01,
         7.07106781e-01,   9.23879533e-01,   1.00000000e+00,...
 y: array([  0.00000000e+00 -0.00000000e+00j,
        -5.00000000e-01 +7.31057196e-17j,
        -3.88313970e-17 +2.42387134e-17j,...

======================================================================
FAIL: check_itilbert_relation
(scipy.fftpack.tests.test_pseudo_diffs.test_ihilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 380, in check_itilbert_relation
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 62.5%)
 x: array([ -1.00000000e+00,  -6.53281482e-01,  -2.12809267e-16,
         2.70598050e-01,   1.06260199e-16,  -2.70598050e-01,
        -1.53930800e-16,   6.53281482e-01,   1.00000000e+00,...
 y: array([  0.00000000e+00 -0.00000000e+00j,
        -2.50000000e-01 +3.52840045e-17j,
         1.19052598e-18 -4.47468130e-17j,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_itilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 288, in check_definition
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 87.5%)
 x: array([ -9.96679946e-02,  -9.20812203e-02,  -7.04759149e-02,
        -3.81412903e-02,  -7.12619106e-18,   3.81412903e-02,
         7.04759149e-02,   9.20812203e-02,   9.96679946e-02,...
 y: array([ -0.00000000e+00 +0.00000000e+00j,
        -4.98339973e-02 +7.28630047e-18j,
        -7.66435941e-18 +4.78412381e-18j,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_shift)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 390, in check_definition
    assert_array_almost_equal(shift(sin(x),a),direct_shift(sin(x),a))
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 0.09983342,  0.19688015,  0.29203083,  0.38436909,  0.47300566,
        0.55708693,  0.63580315,  0.70839623,  0.77416708,  0.83248227,
        0.8827802 ,  0.92457648,  0.95746858,  0.98113973,  0.99536197,...
 y: array([  1.23217883e-17,   4.99167083e-02,   2.46487097e-19,
         8.84658105e-18,   5.94125166e-18,   2.09940707e-17,
         1.47767496e-17,   1.22028436e-17,  -4.63296513e-18,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_pseudo_diffs.test_tilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 227, in check_definition
    assert_array_almost_equal (y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 87.5%)
 x: array([  1.00333111e+01,   9.26957080e+00,   7.09462234e+00,
         3.83958194e+00,   1.10138648e-15,  -3.83958194e+00,
        -7.09462234e+00,  -9.26957080e+00,  -1.00333111e+01,...
 y: array([ -0.00000000e+00 +0.00000000e+00j,
         5.01665557e+00 -7.33492430e-16j,
         1.96738867e-16 -1.22805188e-16j,...

======================================================================
FAIL: check_random_even (scipy.fftpack.tests.test_pseudo_diffs.test_tilbert)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_pseudo_diffs.py",
line 240, in check_random_even
    assert_array_almost_equal(direct_tilbert(direct_itilbert(f,h),h),f)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ -0.00000000e+00 +0.00000000e+00j,
         1.43984280e-03 +1.83732630e-03j,
        -8.76803558e-04 +9.96589953e-04j,...
 y: array([ 0.50751095, -0.23808924, -0.20386413, -0.30474938, -0.21144356,
        0.45414021, -0.11937844, -0.0768124 , -0.15613727,  0.10529999,
        0.03414752, -0.22981309, -0.38280197,  0.06423689,  0.06691425,...

======================================================================
FAIL: check_rvs (scipy.stats.tests.test_distributions.test_randint)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/stats/tests/test_distributions.py",
line 84, in check_rvs
    assert isinstance(val, numpy.ScalarType),`type(val)`
AssertionError: <type 'numpy.ndarray'>

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_basic.test_fft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 99, in check_definition
    assert_array_almost_equal(y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 1.+0.j,  2.+0.j,  3.+0.j,  4.+1.j,  1.+0.j,  2.+0.j,  3.+0.j,
        4.+2.j])
 y: array([ 20.        +3.j        ,  -0.70710678+0.70710678j,
        -7.        +4.j        ,  -0.70710678-0.70710678j,
        -4.        -3.j        ,   0.70710678-0.70710678j,
        -1.        -4.j        ,   0.70710678+0.70710678j])

======================================================================
FAIL: check_djbfft (scipy.fftpack.tests.test_basic.test_fft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 125, in check_djbfft
    assert_array_almost_equal(y,y2)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 0.+0.j,  1.+0.j,  2.+0.j,  3.+0.j])
 y: array([ 6.+0.j, -2.+2.j, -2.+0.j, -2.-2.j])

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_basic.test_fftn)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 380, in check_definition
    assert_array_almost_equal(fftn(x),direct_dftn(x))
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([[[[  6.00785656e+02 +0.j        ,  -5.43773337e+00 +3.46229661j,
           -1.23088437e+01 -2.42889835j, ...,
           -1.26123816e+01-16.10100662j,  -1.23088437e+01 +2.42889835j,...
 y: array([[[[  1.56754048e+02+0.j        ,  -1.02378379e+00-3.98450277j,
           -5.04603298e+00+0.77949078j, ...,   6.41083848e-01-6.21599229j,
           -5.04603298e+00-0.77949078j,  -1.02378379e+00+3.98450277j],...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_basic.test_ifft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 171, in check_definition
    assert_array_almost_equal(y,y1)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 0.125+0.j   ,  0.25 +0.j   ,  0.375+0.j   ,  0.5  +0.125j,
        0.125+0.j   ,  0.25 +0.j   ,  0.375+0.j   ,  0.5  +0.25j ])
 y: array([ 2.5       +0.375j     ,  0.08838835+0.08838835j,
       -0.125     -0.5j       ,  0.08838835-0.08838835j,
       -0.5       -0.375j     , -0.08838835-0.08838835j,
       -0.875     +0.5j       , -0.08838835+0.08838835j])

======================================================================
FAIL: check_djbfft (scipy.fftpack.tests.test_basic.test_ifft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 187, in check_djbfft
    assert_array_almost_equal(y,y2)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 0.  +0.j,  0.25+0.j,  0.5 +0.j,  0.75+0.j])
 y: array([ 1.5+0.j , -0.5-0.5j, -0.5+0.j , -0.5+0.5j])

======================================================================
FAIL: check_random_complex (scipy.fftpack.tests.test_basic.test_ifft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 195, in check_random_complex
    assert_array_almost_equal (ifft(fft(x)),x)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([  9.42894405e-03+0.00342265j,   1.14753943e-02+0.01060178j,
         1.29591488e-03+0.00189321j,   5.93220438e-03+0.00153937j,
         9.05895435e-03+0.00339772j,   1.54679173e-03+0.00557983j,...
 y: array([ 0.60345242+0.21904973j,  0.73442523+0.67851408j,
        0.08293855+0.12116574j,  0.37966108+0.09851944j,
        0.57977308+0.21745381j,  0.09899467+0.35710892j,...

======================================================================
FAIL: check_random_real (scipy.fftpack.tests.test_basic.test_ifft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 201, in check_random_real
    assert_array_almost_equal (ifft(fft(x)),x)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 0.50529514+0.j        , -0.00891716+0.01194018j,
       -0.05414143-0.0252995j ,  0.03278662+0.02075578j,
        0.04225036+0.04154863j, -0.04497517+0.00314367j,...
 y: array([ 0.65301309,  0.59886448,  0.00535917,  0.42038218,  0.33614078,
        0.25537539,  0.02969843,  0.47543031,  0.75088581,  0.77640457,
        0.60916846,  0.44936911,  0.16806369,  0.67254209,  0.54249481,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_basic.test_ifftn)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 541, in check_definition
    assert_array_almost_equal(ifftn(x),direct_idftn(x))
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([[[[  4.99182623e-01 +0.00000000e+00j,
            9.92310707e-05 -4.45232854e-04j,
            1.38377527e-03 -1.81726474e-03j, ...,...
 y: array([[[[  1.32547471e-01 +0.00000000e+00j,
           -6.49846621e-04 +3.22985157e-03j,
           -1.78142582e-05 -1.17333233e-03j, ...,...

======================================================================
FAIL: check_definition (scipy.fftpack.tests.test_basic.test_irfft)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/fftpack/tests/test_basic.py",
line 303, in check_definition
    assert_array_almost_equal(y,ifft(x1))
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
230, in assert_array_almost_equal
    header='Arrays are not almost equal')
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
215, in assert_array_compare
    assert cond, msg
AssertionError:
Arrays are not almost equal

(mismatch 100.0%)
 x: array([ 2.625     , -1.68566017, -0.375     , -1.18566017,  0.625     ,
        0.43566017, -0.375     ,  0.93566017])
 y: array([ 0.125+0.j   ,  0.25 +0.375j,  0.5  +0.125j,  0.25 +0.375j,
        0.5  +0.j   ,  0.25 -0.375j,  0.5  -0.125j,  0.25 -0.375j])

======================================================================
FAIL: check_dot (scipy.lib.tests.test_blas.test_fblas1_simple)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/lib/blas/tests/test_blas.py",
line 76, in check_dot
    assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
156, in assert_almost_equal
    assert round(abs(desired - actual),decimal) == 0, msg
AssertionError:
Items are not equal:
 ACTUAL: (2.125+0j)
 DESIRED: (-9+2j)

======================================================================
FAIL: check_dot (scipy.linalg.tests.test_blas.test_fblas1_simple)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/linalg/tests/test_blas.py",
line 75, in check_dot
    assert_almost_equal(f([3j,-4,3-4j],[2,3,1]),-9+2j)
  File "/usr/lib/python2.4/site-packages/numpy/testing/utils.py", line
156, in assert_almost_equal
    assert round(abs(desired - actual),decimal) == 0, msg
AssertionError:
Items are not equal:
 ACTUAL: (2.125+0j)
 DESIRED: (-9+2j)

----------------------------------------------------------------------
Ran 1569 tests in 851.074s

FAILED (failures=22, errors=3)








-- 
iCy-fLaME
------------------------------------------------
The body maybe wounded, but it is the mind that hurts.


From trond.danielsen at gmail.com  Fri Oct 20 12:41:38 2006
From: trond.danielsen at gmail.com (Trond Danielsen)
Date: Fri, 20 Oct 2006 18:41:38 +0200
Subject: [SciPy-user] Building scipy on FC5 x86_64
In-Reply-To: <ehakh2$he8$1@sea.gmane.org>
References: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
	<453895D0.5050908@iam.uni-stuttgart.de> <ehakh2$he8$1@sea.gmane.org>
Message-ID: <409676c70610200941w22d3d33ah6d13d5f648946a08@mail.gmail.com>

On 10/20/06, Neal Becker <ndbecker2 at gmail.com> wrote:
> env CFLAGS="$RPM_OPT_FLAGS" ATLAS=%{_libdir} FFTW=%{_libdir} BLAS=%{_libdir}
> LAPACK=%{_libdir} python setup.py config_fc --fcompiler=gnu95 build

Thank you for taking the time to reply! I tried that command, but it
still failed. Could you give a little more detailed instruction?

Thanks in advance,

-- 
Trond Danielsen


From ndbecker2 at gmail.com  Fri Oct 20 13:13:30 2006
From: ndbecker2 at gmail.com (Neal Becker)
Date: Fri, 20 Oct 2006 13:13:30 -0400
Subject: [SciPy-user] Building scipy on FC5 x86_64
References: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
	<453895D0.5050908@iam.uni-stuttgart.de>
	<ehakh2$he8$1@sea.gmane.org>
Message-ID: <ehb05u$5m0$1@sea.gmane.org>

Neal Becker wrote:

> Nils Wagner wrote:
> 
>> Trond Danielsen wrote:
>>> Hi!
>>>
>>> I am trying to build scipy on Fedora Core 5 (x86_64), but setup.py
>>> cannot find the required libraries. How can I add /usr/lib64 to the
>>> lib-path?
>>>
>>> I have followed the instructions on the website for installing on fc5,
>>> so the required libs are installed. scipy version is 0.4.8 and numpy
>>> is the latest from fedora extra.
>>>
>>> Best regards,
>>>   
>> AFAIK you can add an entry in the file system_info.py in line 140
>> (numpy/numpy/distutils).
>> 
>> Nils
> env CFLAGS="$RPM_OPT_FLAGS" ATLAS=%{_libdir} FFTW=%{_libdir}
> BLAS=%{_libdir} LAPACK=%{_libdir} python setup.py config_fc
> --fcompiler=gnu95 build

This was pasted directly from an rpm spec file.  Try:
ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK=/usr/lib64 python setup.py config_fc --fcompiler=gnu95 build

make sure you have numpy fftw2-devel, blas-devel, lapack-devel, gcc-gfortran, gcc-c++, libstdc++, python-devel



From ryanlists at gmail.com  Sat Oct 21 14:11:03 2006
From: ryanlists at gmail.com (Ryan Krauss)
Date: Sat, 21 Oct 2006 13:11:03 -0500
Subject: [SciPy-user] signal.lti __mul__ and feedback
Message-ID: <c5b438120610211111j5c263b79oe326a772320cb5df@mail.gmail.com>

As I continue to try to make scipy.signal a replacment for the Matlab
controls toolbox, I need to be able to multiply signal.lti instances
by other instances and by constants (to model a controller transfer
function times a plant transfer function) and I need to create a
feedback command (i.e. closed-loop tf= Gc*Gp/(1+Gc*Gp) if Gc is the
controller transfer function and Gp is the plant transfer function -
assuming unity feedback).  I wanted to make sure these things haven't
already been done and ask for any input before I get started.  I was
basically planning to define __mul__ and __rmul__ for multiplication
by integers, floats, or other lti instances.  When multpliying by
other instances, I was going to just multiply the numerators and
denominators seperately and let poly1d handle that.  The only problem
with that is what to do when there should be a cancelation (i.e.
(s+1)/(s+2)*(s+3)/(s+1)= [(s+3)*(s+1)]/[(s+2)*(s+1)]).  Once an
__add__ method is defined as well, feedback is easy (I guess I would
need a __div__ and probably an __rdiv_ as well).

I had started a seperate controls module before I knew about the
signal.lti stuff.  It is attached.  It would have to be seperated from
some of my other modules to make it more portable, but most of what I
am talking about could be done by making my TransferFunction class
derive from signal.lti (or incorporate all of its methods into
signal.lti).  Any thoughts on this?

Thanks,

Ryan
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From peridot.faceted at gmail.com  Sat Oct 21 15:34:36 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Sat, 21 Oct 2006 15:34:36 -0400
Subject: [SciPy-user] signal.lti __mul__ and feedback
In-Reply-To: <c5b438120610211111j5c263b79oe326a772320cb5df@mail.gmail.com>
References: <c5b438120610211111j5c263b79oe326a772320cb5df@mail.gmail.com>
Message-ID: <ce557a360610211234l5c4769e8ke07576840b985d84@mail.gmail.com>

On 21/10/06, Ryan Krauss <ryanlists at gmail.com> wrote:
> As I continue to try to make scipy.signal a replacment for the Matlab
> controls toolbox, I need to be able to multiply signal.lti instances
> by other instances and by constants (to model a controller transfer
> function times a plant transfer function) and I need to create a
> feedback command (i.e. closed-loop tf= Gc*Gp/(1+Gc*Gp) if Gc is the
> controller transfer function and Gp is the plant transfer function -
> assuming unity feedback).  I wanted to make sure these things haven't
> already been done and ask for any input before I get started.  I was
> basically planning to define __mul__ and __rmul__ for multiplication
> by integers, floats, or other lti instances.  When multpliying by
> other instances, I was going to just multiply the numerators and
> denominators seperately and let poly1d handle that.  The only problem
> with that is what to do when there should be a cancelation (i.e.
> (s+1)/(s+2)*(s+3)/(s+1)= [(s+3)*(s+1)]/[(s+2)*(s+1)]).  Once an
> __add__ method is defined as well, feedback is easy (I guess I would
> need a __div__ and probably an __rdiv_ as well).

One could deal with common factors by implementing a polynomial GCD
(using Euclid's method), but unfortunately in the presence of roundoff
error it becomes rather a sticky subject. When you do polynomial long
division and get a remainder, when do you consider that remainder
zero? What effect does this rounding have?

Of course, if your coefficients are all integers, this problem does
not arise, but I doubt that integer-only arrangements are of much use.
Can you simply tolerate common factors?

A. M. Archibald


From hurak at control.felk.cvut.cz  Sun Oct 22 12:23:53 2006
From: hurak at control.felk.cvut.cz (=?ISO-8859-2?Q?Zden=ECk_Hur=E1k?=)
Date: Sun, 22 Oct 2006 18:23:53 +0200
Subject: [SciPy-user] signal.lti __mul__ and feedback
References: <c5b438120610211111j5c263b79oe326a772320cb5df@mail.gmail.com>
Message-ID: <ehg5un$5nc$1@sea.gmane.org>

Ryan Krauss wrote:

> As I continue to try to make scipy.signal a replacment for the Matlab
> controls toolbox, 

Honestly, I feel that the word "replacement" is too strong...

> I need to be able to multiply signal.lti instances 
> by other instances ...
[...]
> The only problem 
> with that is what to do when there should be a cancelation (i.e.
> (s+1)/(s+2)*(s+3)/(s+1)= [(s+3)*(s+1)]/[(s+2)*(s+1)]).  

Well, the problem of cancelling commong factors when manipulating transfer
functions is one of fundamental ones in control computation. In Matlab,
factors are not cancelled automatically except for a special case when both
the pole and the zero are at EXACT 0. In all other instances, you have to
tell Matlab explicitly that you want a "minimal realization" by calling
minreal function.

[...]
> I had started a seperate controls module before I knew about the
> signal.lti stuff.  It is attached.  It would have to be seperated from
> some of my other modules to make it more portable, but most of what I
> am talking about could be done by making my TransferFunction class
> derive from signal.lti (or incorporate all of its methods into
> signal.lti).  Any thoughts on this?

By the way, does your module support MIMO (multi-input-multi-output)
systems? Without this, I am afraid, it will be useless. But starting a SISO
(single-input-single-output) version without having a good plan about how
to extend it later to MIMO case will surely bring you to dead ends. And the
fact is, that computing with matrices of transfer functions is numerically
badly inferior to state space method. The only alternative capable of
competing is the so-called polynomial matrix fraction approach, when the
natural extension of a rational function to MIMO systems is a fraction of
two polynomial matrices. You might perhaps take some inspiration from a
commercial Polynomial Toolbox for Matlab http://www.polyx.com (the manual
is available) or free Polmat package for Mupad at http://polmat.wz.cz.

Should you stick with state-space methods, be sure not to develop your own
solvers for Riccati and Ljapunov equations and alike but to use somehow the
SLICOT Fortran library http://www.slicot.de. 

Best,
Zdenek


> 
> Thanks,
> 
> Ryan




From jeff at taupro.com  Sun Oct 22 14:20:19 2006
From: jeff at taupro.com (Jeff Rush)
Date: Sun, 22 Oct 2006 13:20:19 -0500
Subject: [SciPy-user] A Call for SciPy Talks at PyCon 2007
Message-ID: <453BB663.6070803@taupro.com>

We're rapidly approaching the deadline (Oct 31) for submitting a talk proposal
for PyCon 2007, being held Feb 23-25 in Addison (Dallas), Texas.  As co-chair
of this year's conference I'd like to encourage the SciPy/NumPy community to
submit a few talks.  While we're in the early stages of keynote selection, it
appears to be shaping up as a "Python Empowers Education" conference theme,
with participants from the One Laptop Per Child project.  And with one focus
of SciPy being education, from the SciPy Developer Zone,

"Today Python is used as a tool for research and higher education, but we
would also like to see secondary-school students and their teachers choosing
Python as an educational tool over commercial offerings."

I think SciPy can be a significant player at PyCon.  We also run half-day paid
tutorials taught by community members on Feb 22 and the course submission
deadline for those is Nov 15.  It'd be really cool to have a half-day
hands-out introduction to SciPy, and the teachers get paid up to $1500 per
half-day, depending upon the number of students.

For talk ideas check out our wiki page at:

  http://us.pycon.org/TX2007/TalkIdeas

And to submit a talk proposal:

  http://us.pycon.org/TX2007/CallForProposals

or a tutorial:

  http://us.pycon.org/TX2007/CallForTutorials

Also please spread the word about the conference and encourage those in the
scientific, engineering and education communities to attend.

Jeff Rush
PyCon 2007 Co-Chair


From simon at arrowtheory.com  Sun Oct 22 17:38:21 2006
From: simon at arrowtheory.com (Simon Burton)
Date: Sun, 22 Oct 2006 14:38:21 -0700
Subject: [SciPy-user] PyDX - announcement
Message-ID: <20061022143821.3b085ca4.simon@arrowtheory.com>


Apologies if this is too off-topic for these lists, but
I hope some people here find this interesting!


PyDX - first public announcement
================================

Overview
--------

    PyDX is a package for working with calculus (differential geometry),
arbitrary precision arithmetic (using gmpy), and interval arithmetic.

It provides:
    * multivariate automatic differentiation (to arbitrary order)
    * Tensor objects for computations in differential geometry
    * Interval scalars (based on libMPFI) for calculating rigorous bounds
on arithmetic operations (validated numerics).
    * Arbitrary order validated ODE solver.

PyDX uses lazy computation techniques to greatly enhance performance of
the resulting functions.

This code grew out of a research project at The Australian National University,
Department of Physics, which involved computing bounds on geodesics in 
relativistic space-time's.

Documentation
-------------

http://gr.anu.edu.au/svn/people/sdburton/pydx/doc/user-guide.html
http://gr.anu.edu.au/svn/people/sdburton/pydx/doc/api/index.html

Subversion Repository
---------------------

http://gr.anu.edu.au/svn/people/sdburton/pydx/


Simon Burton
October 22 2006
The Australian National University


From vinicius.lobosco at gmail.com  Sun Oct 22 21:26:00 2006
From: vinicius.lobosco at gmail.com (Vinicius Lobosco)
Date: Mon, 23 Oct 2006 03:26:00 +0200
Subject: [SciPy-user] Wrong plot with matplotlib
In-Reply-To: <b38fcfa10610221824l24467469t845891809a47fc3d@mail.gmail.com>
References: <b38fcfa10610221824l24467469t845891809a47fc3d@mail.gmail.com>
Message-ID: <b38fcfa10610221826o4471c75erdfccc18405fb5fe8@mail.gmail.com>

Hi folks!

I have a very strange problem. After some calculations, I try to plot a
graphic with pylab. But it doesn't plot the right data. If i print the data
to the screen (with print), they are allright, but not if I plot with pylab
0.83 on Mandriva. The same script on a Ubuntu machine with pylab 0.82 works
fine. The code also works fine if vectorise the __call__ of a class
function. Have anyone had simular problems with pylab?

Thanks!

Vinicius

-- 
---------------------------------
Vinicius Lobosco, PhD
www.paperplat.com

Sv?rdl?ngsv?gen 39
SE-120 60 Stockholm
+46 73 925 8476

-- 
---------------------------------
Vinicius Lobosco, PhD
www.paperplat.com

Sv?rdl?ngsv?gen 39
SE-120 60 Stockholm
+46 73 925 8476
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From robert.kern at gmail.com  Sun Oct 22 21:32:16 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Sun, 22 Oct 2006 20:32:16 -0500
Subject: [SciPy-user] Wrong plot with matplotlib
In-Reply-To: <b38fcfa10610221826o4471c75erdfccc18405fb5fe8@mail.gmail.com>
References: <b38fcfa10610221824l24467469t845891809a47fc3d@mail.gmail.com>
	<b38fcfa10610221826o4471c75erdfccc18405fb5fe8@mail.gmail.com>
Message-ID: <453C1BA0.6060209@gmail.com>

Vinicius Lobosco wrote:
> Hi folks!
> 
> I have a very strange problem. After some calculations, I try to plot a 
> graphic with pylab. But it doesn't plot the right data. If i print the 
> data to the screen (with print), they are allright, but not if I plot 
> with pylab 0.83 on Mandriva. The same script on a Ubuntu machine with 
> pylab 0.82 works fine. The code also works fine if vectorise the 
> __call__ of a class function. Have anyone had simular problems with pylab?

You will need to ask on the matplotlib-users list.

   https://lists.sourceforge.net/lists/listinfo/matplotlib-users

However, you will also need to provide more information. Please try to come up 
with a small example that displays the problem. Post the code and copy-and-paste 
any error messages that are printed.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From vinicius.lobosco at gmail.com  Sun Oct 22 21:46:06 2006
From: vinicius.lobosco at gmail.com (Vinicius Lobosco)
Date: Mon, 23 Oct 2006 03:46:06 +0200
Subject: [SciPy-user] Wrong plot with matplotlib
In-Reply-To: <453C1BA0.6060209@gmail.com>
References: <b38fcfa10610221824l24467469t845891809a47fc3d@mail.gmail.com>
	<b38fcfa10610221826o4471c75erdfccc18405fb5fe8@mail.gmail.com>
	<453C1BA0.6060209@gmail.com>
Message-ID: <b38fcfa10610221846t7174fa90i200b7e589fed658a@mail.gmail.com>

Dear Robert!

Thanks for your prompt response. You're right, I should have given betten
exaple, but I think it tourned out to be a problem on my machine. Tried with
xplt and got the same results. But the problem was solved magically :-D
There was an available scipy package not already installed from urpmi
although I already had scipy on my machine :-S  When I installed it, it
worked fine. I guess it was a kind of a old version of scipy conflict
somehow. Maybe I've installed it from subversion before. Thanks anyway.

Best regards, Vinicius

2006/10/23, Robert Kern <robert.kern at gmail.com>:
>
> Vinicius Lobosco wrote:
> > Hi folks!
> >
> > I have a very strange problem. After some calculations, I try to plot a
> > graphic with pylab. But it doesn't plot the right data. If i print the
> > data to the screen (with print), they are allright, but not if I plot
> > with pylab 0.83 on Mandriva. The same script on a Ubuntu machine with
> > pylab 0.82 works fine. The code also works fine if vectorise the
> > __call__ of a class function. Have anyone had simular problems with
> pylab?
>
> You will need to ask on the matplotlib-users list.
>
>    https://lists.sourceforge.net/lists/listinfo/matplotlib-users
>
> However, you will also need to provide more information. Please try to
> come up
> with a small example that displays the problem. Post the code and
> copy-and-paste
> any error messages that are printed.
>
> --
> Robert Kern
>
> "I have come to believe that the whole world is an enigma, a harmless
> enigma
>   that is made terrible by our own mad attempt to interpret it as though
> it had
>   an underlying truth."
>    -- Umberto Eco
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
---------------------------------
Vinicius Lobosco, PhD
www.paperplat.com

Sv?rdl?ngsv?gen 39
SE-120 60 Stockholm
+46 73 925 8476
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From sadrejeb at gmx.ch  Mon Oct 23 02:26:29 2006
From: sadrejeb at gmx.ch (Sadruddin Rejeb)
Date: Mon, 23 Oct 2006 08:26:29 +0200
Subject: [SciPy-user] Python-2.5 Win32 binaries
Message-ID: <1161584789.4908.10.camel@localhost.localdomain>

Hello,

Is there any Python-2.5 windows binary package of scipy-0.5.1 planned to
be released? Or will Python-2.5 binaries be introduced only with version
0.5.2?

Thanks,
Sad



From trond.danielsen at gmail.com  Mon Oct 23 03:57:09 2006
From: trond.danielsen at gmail.com (Trond Danielsen)
Date: Mon, 23 Oct 2006 09:57:09 +0200
Subject: [SciPy-user] Building scipy on FC5 x86_64
In-Reply-To: <ehb05u$5m0$1@sea.gmane.org>
References: <409676c70610200217g56e264d5t9f26fe644039e82b@mail.gmail.com>
	<453895D0.5050908@iam.uni-stuttgart.de> <ehakh2$he8$1@sea.gmane.org>
	<ehb05u$5m0$1@sea.gmane.org>
Message-ID: <409676c70610230057j10ef3f96y279ec2e18ab21275@mail.gmail.com>

2006/10/20, Neal Becker <ndbecker2 at gmail.com>:
>
> This was pasted directly from an rpm spec file.  Try:
> ATLAS=/usr/lib64 FFTW=/usr/lib64 BLAS=/usr/lib64 LAPACK=/usr/lib64 python setup.py config_fc --fcompiler=gnu95 build
>
> make sure you have numpy fftw2-devel, blas-devel, lapack-devel, gcc-gfortran, gcc-c++, libstdc++, python-devel
>

Thank you! That worked great. Maybe the instructions on the wiki
should be updated?

-- 
Trond Danielsen


From vmas at carabos.com  Mon Oct 23 04:57:37 2006
From: vmas at carabos.com (Vicent Mas (V+))
Date: Mon, 23 Oct 2006 10:57:37 +0200
Subject: [SciPy-user] image processing
Message-ID: <200610231057.37151.vmas@carabos.com>

Hello,

I'm a newcomer to process image and scipy. I'm trying to process a 
binary image in order to get the biggest connected component. In matlab 
one can use the bwareaopen to achieve this goal but I don't know how to 
do it with scipy.  I've been looking at scipy.ndimage module with no 
luck. Could you help me, please?

Thanks in advance.
-- 
::

	 \ /	Vicent Mas	http://www.carabos.com
	 0;0	
	/   \	C?rabos Coop.	Enjoy Data
	V   V
	 " "


From R.Springuel at umit.maine.edu  Sat Oct 21 12:48:28 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Sat, 21 Oct 2006 12:48:28 -0400
Subject: [SciPy-user] Installation Problems on Mac OS 10.4
Message-ID: <453A4F5C.8040800@umit.maine.edu>

Okay, I finally figured out the problem with the Fortran compiler, and 
was able to get Scipy to find and use gfortran on my system.  However, 
I'm now getting the following error:

gcc: unrecognized option '-no-cpp-precomp'
cc1: error: unrecognized command line option "-mno-fused-madd"
cc1: error: unrecognized command line option "-arch"
cc1: error: unrecognized command line option "-arch"
cc1: error: unrecognized command line option "-Wno-long-double"
gcc: unrecognized option '-no-cpp-precomp'
cc1: error: unrecognized command line option "-mno-fused-madd"
cc1: error: unrecognized command line option "-arch"
cc1: error: unrecognized command line option "-arch"
cc1: error: unrecognized command line option "-Wno-long-double"
error: Command "gcc -arch ppc -arch i386 -isysroot 
/Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double 
-no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3 
-DUSE_VENDOR_BLAS=1 -c Lib/linsolve/SuperLU/SRC/clangs.c -o 
build/temp.macosx-10.3-fat-2.5/Lib/linsolve/SuperLU/SRC/clangs.o" failed 
with exit status 1

I get this error with both gcc 4.0 and 3.3.  Does anyone know how to fix it?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm



From w.richert at gmx.net  Tue Oct 24 04:12:06 2006
From: w.richert at gmx.net (Willi Richert)
Date: Tue, 24 Oct 2006 10:12:06 +0200
Subject: [SciPy-user] Error with 0.5.1 tests
Message-ID: <200610241012.06718.w.richert@gmx.net>

Hi,

I installed numpy-1.0rc3 and scipy. At the python shell I did scipy.test() and got:

======================================================================
ERROR: Solve: single precision complex
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/linsolve/umfpack/tests/test_umfpack.py", line 25, in check_solve_complex_without_umfpack
    x = linsolve.spsolve(a, b)
  File "/usr/lib/python2.4/site-packages/scipy/linsolve/linsolve.py", line 76, in spsolve
    return gssv(N, lastel, data, index0, index1, b, csc, permc_spec)[0]
TypeError: array cannot be safely cast to required type

======================================================================
ERROR: check loadmat case cellnest
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 80, in cc
    self._check_case(name, expected)
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 75, in _check_case
    self._check_level(k_label, expected, matdict[k])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 33, in _check_level
    self._check_level(level_label, ev, actual[i])
  File "/usr/lib/python2.4/site-packages/scipy/io/tests/test_mio.py", line 30, in _check_level
    assert len(expected) == len(actual), "Different list lengths at %s" % label
TypeError: len() of unsized object

======================================================================
FAIL: check_rvs (scipy.stats.tests.test_distributions.test_randint)
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/usr/lib/python2.4/site-packages/scipy/stats/tests/test_distributions.py", line 84, in check_rvs
    assert isinstance(val, numpy.ScalarType),`type(val)`
AssertionError: <type 'numpy.ndarray'>

----------------------------------------------------------------------
Ran 1569 tests in 4.551s

FAILED (failures=1, errors=2)

Any hints?
wr

PS: Here is the output head of "python setup.py install":
fft_opt_info:
fftw3_info:
  libraries fftw3 not found in /usr/local/lib
  libraries fftw3 not found in /usr/lib
  fftw3 not found
  NOT AVAILABLE

fftw2_info:
  libraries rfftw,fftw not found in /usr/local/lib
  libraries rfftw,fftw not found in /usr/lib
  fftw2 not found
  NOT AVAILABLE

dfftw_info:
  libraries drfftw,dfftw not found in /usr/local/lib
  libraries drfftw,dfftw not found in /usr/lib
  dfftw not found
  NOT AVAILABLE

djbfft_info:
  NOT AVAILABLE

  NOT AVAILABLE

blas_opt_info:
blas_mkl_info:
  libraries mkl,vml,guide not found in /usr/local/lib
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

atlas_blas_threads_info:
Setting PTATLAS=ATLAS
  libraries lapack,blas not found in /usr/local/lib
Setting PTATLAS=ATLAS
Setting PTATLAS=ATLAS
  FOUND:
    libraries = ['lapack', 'blas']
    library_dirs = ['/usr/lib/atlas']
    language = c
    include_dirs = ['/usr/include']

Could not locate executable gfortran
Could not locate executable f95
customize GnuFCompiler
customize GnuFCompiler
customize GnuFCompiler using config
compiling '_configtest.c':

/* This file is generated from numpy_distutils/system_info.py */
void ATL_buildinfo(void);
int main(void) {
  ATL_buildinfo();
  return 0;
}
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC

compile options: '-c'
gcc: _configtest.c
gcc -pthread _configtest.o -L/usr/lib/atlas -llapack -lblas -o _configtest
ATLAS version 3.6.0 built by camm on Tue Jun 15 03:19:44 UTC 2004:
   UNAME    : Linux intech131 2.4.20 #1 SMP Thu Jan 23 11:24:05 EST 2003 i686 GNU/Linux
   INSTFLG  :
   MMDEF    :
   ARCHDEF  :
   F2CDEFS  : -DAdd__ -DStringSunStyle
   CACHEEDGE: 196608
   F77      : /usr/bin/g77, version GNU Fortran (GCC) 3.3.5 (Debian 1:3.3.5-1)
   F77FLAGS : -O
   CC       : /usr/bin/gcc, version gcc (GCC) 3.3.5 (Debian 1:3.3.5-1)
   CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
   MCC      : /usr/bin/gcc, version gcc (GCC) 3.3.5 (Debian 1:3.3.5-1)
   MCCFLAGS : -fomit-frame-pointer -O
success!
removing: _configtest.c _configtest.o _configtest
  FOUND:
    libraries = ['lapack', 'blas']
    library_dirs = ['/usr/lib/atlas']
    language = c
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

ATLAS version 3.6.0
lapack_opt_info:
lapack_mkl_info:
mkl_info:
  libraries mkl,vml,guide not found in /usr/local/lib
  libraries mkl,vml,guide not found in /usr/lib
  NOT AVAILABLE

  NOT AVAILABLE

atlas_threads_info:
Setting PTATLAS=ATLAS
  libraries lapack,blas not found in /usr/local/lib
  libraries lapack_atlas not found in /usr/local/lib
  libraries lapack_atlas not found in /usr/lib/atlas
numpy.distutils.system_info.atlas_threads_info
Setting PTATLAS=ATLAS
Setting PTATLAS=ATLAS
  FOUND:
    libraries = ['lapack', 'lapack', 'blas']
    library_dirs = ['/usr/lib/atlas']
    language = f77
    include_dirs = ['/usr/include']

customize GnuFCompiler
customize GnuFCompiler
customize GnuFCompiler using config
compiling '_configtest.c':

/* This file is generated from numpy_distutils/system_info.py */
void ATL_buildinfo(void);
int main(void) {
  ATL_buildinfo();
  return 0;
}
C compiler: gcc -pthread -fno-strict-aliasing -DNDEBUG -g -O3 -Wall -Wstrict-prototypes -fPIC

compile options: '-c'
gcc: _configtest.c
gcc -pthread _configtest.o -L/usr/lib/atlas -llapack -llapack -lblas -o _configtest
ATLAS version 3.6.0 built by camm on Tue Jun 15 03:19:44 UTC 2004:
   UNAME    : Linux intech131 2.4.20 #1 SMP Thu Jan 23 11:24:05 EST 2003 i686 GNU/Linux
   INSTFLG  :
   MMDEF    :
   ARCHDEF  :
   F2CDEFS  : -DAdd__ -DStringSunStyle
   CACHEEDGE: 196608
   F77      : /usr/bin/g77, version GNU Fortran (GCC) 3.3.5 (Debian 1:3.3.5-1)
   F77FLAGS : -O
   CC       : /usr/bin/gcc, version gcc (GCC) 3.3.5 (Debian 1:3.3.5-1)
   CC FLAGS : -fomit-frame-pointer -O3 -funroll-all-loops
   MCC      : /usr/bin/gcc, version gcc (GCC) 3.3.5 (Debian 1:3.3.5-1)
   MCCFLAGS : -fomit-frame-pointer -O
success!
removing: _configtest.c _configtest.o _configtest
  FOUND:
    libraries = ['lapack', 'lapack', 'blas']
    library_dirs = ['/usr/lib/atlas']
    language = f77
    define_macros = [('ATLAS_INFO', '"\\"3.6.0\\""')]
    include_dirs = ['/usr/include']

ATLAS version 3.6.0
ATLAS version 3.6.0
non-existing path in 'Lib/linsolve': 'tests'
umfpack_info:
  libraries umfpack not found in /usr/local/lib
  libraries umfpack not found in /usr/lib
/usr/lib/python2.4/site-packages/numpy/distutils/system_info.py:401: UserWarning:
    UMFPACK sparse solver (http://www.cise.ufl.edu/research/sparse/umfpack/)
    not found. Directories to search for the libraries can be specified in the
    numpy/distutils/site.cfg file (section [umfpack]) or by setting
    the UMFPACK environment variable.
  warnings.warn(self.notfounderror.__doc__)
  NOT AVAILABLE

non-existing path in 'Lib/maxentropy': 'doc'
Warning: Subpackage 'Lib' configuration returned as 'scipy'
running install
running build
running config_fc
running build_src
...


From ctmedra at unizar.es  Tue Oct 24 04:25:41 2006
From: ctmedra at unizar.es (Carlos Medrano)
Date: Tue, 24 Oct 2006 08:25:41 +0000 (UTC)
Subject: [SciPy-user] image processing
References: <200610231057.37151.vmas@carabos.com>
Message-ID: <loom.20061024T101958-962@post.gmane.org>

Vicent Mas (V+ <vmas <at> carabos.com> writes:

> 
> Hello,
> 
> I'm a newcomer to process image and scipy. I'm trying to process a 
> binary image in order to get the biggest connected component. In matlab 
> one can use the bwareaopen to achieve this goal but I don't know how to 
> do it with scipy.  I've been looking at scipy.ndimage module with no 
> luck. Could you help me, please?
> 
> Thanks in advance.

I dont' know if this can help you, but check:

OpenCV library (supposed to have a python interface)

http://opencvlibrary.sourceforge.net/Welcome?highlight=%28%28Welcome%29%29

and PIL (Python Imaging library)

http://www.pythonware.com/products/index.htm


Carlos Medrano






From vmas at carabos.com  Tue Oct 24 05:54:57 2006
From: vmas at carabos.com (Vicent Mas (V+))
Date: Tue, 24 Oct 2006 11:54:57 +0200
Subject: [SciPy-user] image processing
In-Reply-To: <loom.20061024T101958-962@post.gmane.org>
References: <200610231057.37151.vmas@carabos.com>
	<loom.20061024T101958-962@post.gmane.org>
Message-ID: <200610241154.57228.vmas@carabos.com>

El Tuesday, 24 de October de 2006 10:25, Carlos Medrano escribi?:
> Vicent Mas (V+ <vmas <at> carabos.com> writes:
> > Hello,
> >
> > I'm a newcomer to process image and scipy. I'm trying to process a
> > binary image in order to get the biggest connected component. In
> > matlab one can use the bwareaopen to achieve this goal but I don't
> > know how to do it with scipy.  I've been looking at scipy.ndimage
> > module with no luck. Could you help me, please?
> >
> > Thanks in advance.
>
> I dont' know if this can help you, but check:
>
> OpenCV library (supposed to have a python interface)
>
> http://opencvlibrary.sourceforge.net/Welcome?highlight=%28%28Welcome%
>29%29
>
> and PIL (Python Imaging library)
>
> http://www.pythonware.com/products/index.htm
>
>
> Carlos Medrano
>

It is exactly what I'm doing.

Thanks for your advice.

-- 
::

	 \ /	Vicent Mas	http://www.carabos.com
	 0;0	
	/   \	C?rabos Coop.	Enjoy Data
	V   V
	 " "


From gruben at bigpond.net.au  Tue Oct 24 07:41:13 2006
From: gruben at bigpond.net.au (Gary Ruben)
Date: Tue, 24 Oct 2006 21:41:13 +1000
Subject: [SciPy-user] image processing
In-Reply-To: <loom.20061024T101958-962@post.gmane.org>
References: <200610231057.37151.vmas@carabos.com>
	<loom.20061024T101958-962@post.gmane.org>
Message-ID: <453DFBD9.6060304@bigpond.net.au>

I haven't actually tried this, but I think you should take a look at
scipy.ndimage.measurements.label
followed by
scipy.ndimage.measurements.find_objects
and
scipy.ndimage.measurements.maximum

These sound like they will do what you want.

Gary R.

Carlos Medrano wrote:
> Vicent Mas (V+ <vmas <at> carabos.com> writes:
> 
>> Hello,
>>
>> I'm a newcomer to process image and scipy. I'm trying to process a 
>> binary image in order to get the biggest connected component. In matlab 
>> one can use the bwareaopen to achieve this goal but I don't know how to 
>> do it with scipy.  I've been looking at scipy.ndimage module with no 
>> luck. Could you help me, please?
>>
>> Thanks in advance.
> 
> I dont' know if this can help you, but check:
> 
> OpenCV library (supposed to have a python interface)
> 
> http://opencvlibrary.sourceforge.net/Welcome?highlight=%28%28Welcome%29%29
> 
> and PIL (Python Imaging library)
> 
> http://www.pythonware.com/products/index.htm
> 
> 
> Carlos Medrano



From fredmfp at gmail.com  Tue Oct 24 14:23:24 2006
From: fredmfp at gmail.com (fred)
Date: Tue, 24 Oct 2006 20:23:24 +0200
Subject: [SciPy-user] wiki
Message-ID: <453E5A1C.6040902@gmail.com>

Hi the list,

Only two shorts question:

1) How can I add a page ?
I want to add Cookbook/MayaVi/InstallPythonStuffFromSource page.

2) How can I delete some png image files previously uploaded ?

Thanks in advance.

Cheers,

-- 
http://scipy.org/FredericPetit



From cookedm at physics.mcmaster.ca  Tue Oct 24 14:46:16 2006
From: cookedm at physics.mcmaster.ca (David M. Cooke)
Date: Tue, 24 Oct 2006 14:46:16 -0400
Subject: [SciPy-user] Installation Problems on Mac OS 10.4
In-Reply-To: <453A4F5C.8040800@umit.maine.edu>
References: <453A4F5C.8040800@umit.maine.edu>
Message-ID: <703B54E1-70AA-4BB4-8B2F-C2D399E39654@physics.mcmaster.ca>


On Oct 21, 2006, at 12:48 , R. Padraic Springuel wrote:

> Okay, I finally figured out the problem with the Fortran compiler, and
> was able to get Scipy to find and use gfortran on my system.  However,
> I'm now getting the following error:
>
> gcc: unrecognized option '-no-cpp-precomp'
> cc1: error: unrecognized command line option "-mno-fused-madd"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-Wno-long-double"
> gcc: unrecognized option '-no-cpp-precomp'
> cc1: error: unrecognized command line option "-mno-fused-madd"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-Wno-long-double"
> error: Command "gcc -arch ppc -arch i386 -isysroot
> /Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double
> -no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3
> -DUSE_VENDOR_BLAS=1 -c Lib/linsolve/SuperLU/SRC/clangs.c -o
> build/temp.macosx-10.3-fat-2.5/Lib/linsolve/SuperLU/SRC/clangs.o"  
> failed
> with exit status 1
>
> I get this error with both gcc 4.0 and 3.3.  Does anyone know how  
> to fix it?

Are you sure you're using Apple's gcc? These look the errors that a  
non-Apple gcc would spew (especially the -arch and -no-cpp-precomp).  
Check what gcc --version gives you. You can also specify which one to  
use by setting the environment variable CC (as in, 'export CC=/usr/ 
bin/gcc-4.0').

-- 
|>|\/|<
/------------------------------------------------------------------\
|David M. Cooke              http://arbutus.physics.mcmaster.ca/dmc/
|cookedm at physics.mcmaster.ca



From cookedm at physics.mcmaster.ca  Tue Oct 24 14:46:16 2006
From: cookedm at physics.mcmaster.ca (David M. Cooke)
Date: Tue, 24 Oct 2006 14:46:16 -0400
Subject: [SciPy-user] Installation Problems on Mac OS 10.4
In-Reply-To: <453A4F5C.8040800@umit.maine.edu>
References: <453A4F5C.8040800@umit.maine.edu>
Message-ID: <703B54E1-70AA-4BB4-8B2F-C2D399E39654@physics.mcmaster.ca>


On Oct 21, 2006, at 12:48 , R. Padraic Springuel wrote:

> Okay, I finally figured out the problem with the Fortran compiler, and
> was able to get Scipy to find and use gfortran on my system.  However,
> I'm now getting the following error:
>
> gcc: unrecognized option '-no-cpp-precomp'
> cc1: error: unrecognized command line option "-mno-fused-madd"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-Wno-long-double"
> gcc: unrecognized option '-no-cpp-precomp'
> cc1: error: unrecognized command line option "-mno-fused-madd"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-arch"
> cc1: error: unrecognized command line option "-Wno-long-double"
> error: Command "gcc -arch ppc -arch i386 -isysroot
> /Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double
> -no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3
> -DUSE_VENDOR_BLAS=1 -c Lib/linsolve/SuperLU/SRC/clangs.c -o
> build/temp.macosx-10.3-fat-2.5/Lib/linsolve/SuperLU/SRC/clangs.o"  
> failed
> with exit status 1
>
> I get this error with both gcc 4.0 and 3.3.  Does anyone know how  
> to fix it?

Are you sure you're using Apple's gcc? These look the errors that a  
non-Apple gcc would spew (especially the -arch and -no-cpp-precomp).  
Check what gcc --version gives you. You can also specify which one to  
use by setting the environment variable CC (as in, 'export CC=/usr/ 
bin/gcc-4.0').

-- 
|>|\/|<
/------------------------------------------------------------------\
|David M. Cooke              http://arbutus.physics.mcmaster.ca/dmc/
|cookedm at physics.mcmaster.ca



From cookedm at physics.mcmaster.ca  Tue Oct 24 14:54:08 2006
From: cookedm at physics.mcmaster.ca (David M. Cooke)
Date: Tue, 24 Oct 2006 14:54:08 -0400
Subject: [SciPy-user] [Numpy-discussion] PyDX - announcement
In-Reply-To: <20061022143821.3b085ca4.simon@arrowtheory.com>
References: <20061022143821.3b085ca4.simon@arrowtheory.com>
Message-ID: <0294D4F3-4E20-4BCB-A53E-5D2FDB9895C9@physics.mcmaster.ca>

On Oct 22, 2006, at 17:38 , Simon Burton wrote:
>
> Apologies if this is too off-topic for these lists, but
> I hope some people here find this interesting!

It looks very nifty. Interval arithmetic for rigourous bounds is  
something that should be used more often, I think.

You should add it to the topical software list at http:// 
www.scipy.org/Topical_Software.

[and it's on topic, btw; announcements of Python numerical software  
is always welcome here].

> PyDX - first public announcement
> ================================
>
> Overview
> --------
>
>     PyDX is a package for working with calculus (differential  
> geometry),
> arbitrary precision arithmetic (using gmpy), and interval arithmetic.
>
> It provides:
>     * multivariate automatic differentiation (to arbitrary order)
>     * Tensor objects for computations in differential geometry
>     * Interval scalars (based on libMPFI) for calculating rigorous  
> bounds
> on arithmetic operations (validated numerics).
>     * Arbitrary order validated ODE solver.
>
> PyDX uses lazy computation techniques to greatly enhance  
> performance of
> the resulting functions.
>
> This code grew out of a research project at The Australian National  
> University,
> Department of Physics, which involved computing bounds on geodesics in
> relativistic space-time's.

-- 
|>|\/|<
/------------------------------------------------------------------\
|David M. Cooke              http://arbutus.physics.mcmaster.ca/dmc/
|cookedm at physics.mcmaster.ca



From mforbes at phys.washington.edu  Tue Oct 24 20:43:36 2006
From: mforbes at phys.washington.edu (Michael McNeil Forbes)
Date: Tue, 24 Oct 2006 17:43:36 -0700
Subject: [SciPy-user] Subclassing array
Message-ID: <mforbes-E139B0.17433524102006@news.gmane.org>

I have a question about the best way to subclass array types.

I would like to create a subclass of the array types that allows me to 
name the entries of the array.  Here is a sample of my desired usage:

>>> from scipy import *
>>> a = array([1.0,2.0])
>>>
>>> class MyArray(a.__class__):
>>>   _names = ['x','y']
>>>   ... (redefine __get__ etc. as needed)
>>>
>>> c = MyArray(x=2,y=3)
>>> c.x, c.y
(2, 3)

etc.

I want c to be an array with two elements, but essentially want to be 
able to change c.__class__ to be a modified class that can access 
elements as specified by c._names.

Ideally, I would like this to work with any type that supports simple 
indexing, such as arrays, lists etc. but my first attempts seem to 
require redefining __new__ which varies for different types making the 
solution much less general.

It seems like I should be able to get the desired behaviour with 
something like the following:

      def __new__(cls,**kwargs):
        self = deepcopy(a)
        self[:] = map(kwargs.get,cls._names)
        self.__class__ = cls
        return cls

but this is not allowed because __class__ can only be set for heap types.

Is there a standard and safe way to achieve this behaviour?

Thanks,
Michael.



From strawman at astraw.com  Tue Oct 24 23:03:28 2006
From: strawman at astraw.com (Andrew Straw)
Date: Tue, 24 Oct 2006 20:03:28 -0700
Subject: [SciPy-user] [JOB] hiring software engineer
Message-ID: <453ED400.5020607@astraw.com>

The lab I work in at Caltech is hiring a software engineer. I'd love to
get someone with an interest in scientific computing with Python. If you
might be interested, please check out our job posting:

http://www.recruitingcenter.net/clients/CalTech/publicjobs/controller.cfm?jbaction=JobProfile&Job_Id=13370&esid=az

Please pursue any formal inquiries through the URL above.

-Andrew


From bryan.cole at teraview.com  Wed Oct 25 05:23:07 2006
From: bryan.cole at teraview.com (Bryan Cole)
Date: Wed, 25 Oct 2006 10:23:07 +0100
Subject: [SciPy-user] [JOB] UK Posting: senior software engineer (C++ &
	Python)
Message-ID: <1161768187.26636.14.camel@bryan.teraview.local>

Teraview Ltd., UK is looking for a senior software engineer to lead the
development of instrumentation software for our new range of
spectrometer and imaging products. The formal job spec can be found at
http://www.teraview.com/about/vacsoftware.html . 

Although the job-spec doesn't mention Python, we make extensive use of
Python/Numeric/Scipy in our development, so a candidate with these
skills would have a compelling advantage. However, experience with C++
and Windows programming is essential to maintain and extend our existing
codebase.

Anyone interested in this position should either send their CV directly
to the address given in the posting, or email me directly for more
information.

cheers,
Bryan

-- 
Group Leader, Technical Development Group - Teraview Ltd.
web: www.teraview.com




From tom.denniston at alum.dartmouth.org  Wed Oct 25 14:53:37 2006
From: tom.denniston at alum.dartmouth.org (Tom Denniston)
Date: Wed, 25 Oct 2006 13:53:37 -0500
Subject: [SciPy-user] lexsort in numpy crashing on strings
Message-ID: <d6f2d3dd0610251153u55a3e945w661040e6031417cb@mail.gmail.com>

Hi, I've been using the lexsort and it is really nice.  Much simpler and
faster than the implementation I had before.   The only problem is it seems
to crash on strings.

Do I just need to upgrade numpy or is it a current bug?
   In [2]: import numpy
   nu
   In [3]: numpy.array(['a', 'b', 'c'])
   Out[3]:
   array([a, b, c],
         dtype='|S1')
   In [4]: strArray = numpy.array(['a', 'b', 'c'])
   In [5]: intArray = numpy.array([1,2,3])
   In [6]: numpy.__version__
   Out[6]: '1.0b5'
   In [7]: numpy.lexsort((intArray,))
   Out[7]: array([0, 1, 2])
   In [8]: numpy.lexsort((intArray,intArray))
   Out[8]: array([0, 1, 2])
   In [9]: numpy.lexsort((strArray,intArray))
   Segmentation fault (core dumped)
-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.scipy.org/pipermail/scipy-user/attachments/20061025/c656960a/attachment.html>

From R.Springuel at umit.maine.edu  Wed Oct 25 15:17:42 2006
From: R.Springuel at umit.maine.edu (R. Padraic Springuel)
Date: Wed, 25 Oct 2006 15:17:42 -0400
Subject: [SciPy-user] Installation problems on Max OS X
Message-ID: <453FB856.4060900@umit.maine.edu>

gcc --version yields the following:

i686-apple-darwin8-gcc-4.0.1 (GCC) 4.0.1 (Apple Computer, Inc. build 5363)
Copyright (C) 2005 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

I tried setting the environment variable as suggested and still get the 
following very similar error:

g++: unrecognized option '-no-cpp-precomp'
cc1plus: error: unrecognized command line option "-mno-fused-madd"
cc1plus: error: unrecognized command line option "-arch"
cc1plus: error: unrecognized command line option "-arch"
cc1plus: error: unrecognized command line option "-Wno-long-double"
g++: unrecognized option '-no-cpp-precomp'
cc1plus: error: unrecognized command line option "-mno-fused-madd"
cc1plus: error: unrecognized command line option "-arch"
cc1plus: error: unrecognized command line option "-arch"
cc1plus: error: unrecognized command line option "-Wno-long-double"
error: Command "g++ -arch ppc -arch i386 -isysroot 
/Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double 
-no-cpp-precomp -mno-fused-madd -fno-common -dynamic -DNDEBUG -g -O3 
-I/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/numpy/core/include 
-I/Library/Frameworks/Python.framework/Versions/2.5/include/python2.5 -c 
Lib/cluster/src/vq_wrap.cpp -o 
build/temp.macosx-10.3-fat-2.5/Lib/cluster/src/vq_wrap.o" failed with 
exit status 1

It's different at least, so that means I'm making progress, right?
-- 

R. Padraic Springuel
Teaching Assistant
Department of Physics and Astronomy
University of Maine
Bennett 309
Office Hours: Wednesday 2-3pm


From coughlan at ski.org  Wed Oct 25 15:39:40 2006
From: coughlan at ski.org (James Coughlan)
Date: Wed, 25 Oct 2006 12:39:40 -0700
Subject: [SciPy-user] can't get weave to work
Message-ID: <453FBD7C.2030609@ski.org>

Hello,

When I try to run a simple weave example (main.py):

from scipy import weave
a=1
weave.inline('printf("%d",a);',['a'],compiler='gcc')

it gives me this error message:
"
CompileError: error: Command "g++ -mno-cygwin -mdll -O2 -w 
-IC:\Python24\lib\site-packages\scipy\wea
ve -IC:\Python24\lib\site-packages\scipy\weave\scxx 
-IC:\Python24\lib\site-packages\numpy\core\inclu
de -IC:\Python24\include -IC:\Python24\PC -c 
C:\Python24\lib\site-packages\scipy\weave\scxx\weave_im
p.cpp -o 
c:\docume~1\james\locals~1\temp\James\python24_intermediate\compiler_ad9404e4505a343c45a7cd
09360558c2\Release\python24\lib\site-packages\scipy\weave\scxx\weave_imp.o" 
failed with exit status
2
WARNING: Failure executing file: <main.py>
"

If I instead specify compiler='msvc' I get a different error message:
"
DistutilsPlatformError: The .NET Framework SDK needs to be installed 
before building extensions for
Python.
WARNING: Failure executing file: <main.py>
"

When I ran weave.test() I get this report: "Ran 132 tests in 3.445s", 
but it also produced some errors, e.g. "specified build_dir '_bad_path_' 
does not exist or is not writable".

I am running Python Enthought Edition -- Python 2.4.3 for Windows 
Enhanced Python Distribution, which includes SciPy version 0.5.0.2033. 
Weave *used* to work for me when I was running Python 2.3.

Can anybody give me any suggestions, or suggest someone who might be 
able to help me?

Thanks,
James

-- 
-------------------------------------------------------
James Coughlan, Ph.D., Associate Scientist                     

Smith-Kettlewell Eye Research Institute

Email: coughlan at ski.org
URL: http://www.ski.org/Rehab/Coughlan_lab/
Phone: 415-345-2146 
Fax: 415-345-8455
-------------------------------------------------------



From robert.kern at gmail.com  Wed Oct 25 15:28:13 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Wed, 25 Oct 2006 14:28:13 -0500
Subject: [SciPy-user] lexsort in numpy crashing on strings
In-Reply-To: <d6f2d3dd0610251153u55a3e945w661040e6031417cb@mail.gmail.com>
References: <d6f2d3dd0610251153u55a3e945w661040e6031417cb@mail.gmail.com>
Message-ID: <ehodsd$l3i$1@sea.gmane.org>

Tom Denniston wrote:
> Hi, I've been using the lexsort and it is really nice.  Much simpler and 
> faster than the implementation I had before.   The only problem is it 
> seems  to crash on strings.
> 
> Do I just need to upgrade numpy or is it a current bug?

Upgrade numpy. I believe this bug has been fixed.

http://projects.scipy.org/scipy/numpy/ticket/298

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco



From gael.varoquaux at normalesup.org  Wed Oct 25 16:36:26 2006
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Wed, 25 Oct 2006 22:36:26 +0200
Subject: [SciPy-user] wiki
In-Reply-To: <453E5A1C.6040902@gmail.com>
References: <453E5A1C.6040902@gmail.com>
Message-ID: <20061025203626.GG5588@clipper.ens.fr>

On Tue, Oct 24, 2006 at 08:23:24PM +0200, fred wrote:
> 1) How can I add a page ?
> I want to add Cookbook/MayaVi/InstallPythonStuffFromSource page.

Just create a link to this page from another one. Then you can click on
this link, and edit the blank page.

> 2) How can I delete some png image files previously uploaded ?

You cannot.

Ga?l


From fredmfp at gmail.com  Wed Oct 25 17:27:10 2006
From: fredmfp at gmail.com (fred)
Date: Wed, 25 Oct 2006 23:27:10 +0200
Subject: [SciPy-user] wiki
In-Reply-To: <20061025203626.GG5588@clipper.ens.fr>
References: <453E5A1C.6040902@gmail.com> <20061025203626.GG5588@clipper.ens.fr>
Message-ID: <453FD6AE.2050801@gmail.com>

Gael Varoquaux a ?crit :

>On Tue, Oct 24, 2006 at 08:23:24PM +0200, fred wrote:
>  
>
>>1) How can I add a page ?
>>I want to add Cookbook/MayaVi/InstallPythonStuffFromSource page.
>>    
>>
>
>Just create a link to this page from another one. Then you can click on
>this link, and edit the blank page.
>
Ok, fine.

I was missing the second ":" in my link.
Sorry.

>>2) How can I delete some png image files previously uploaded ?
>>    
>>
>
>You cannot.
>  
>
I only want to upgrade some png file I have uploaded.
Then, why is there a "delete" item beside images in info page ?


Cheers,

-- 
http://scipy.org/FredericPetit



From coughlan at ski.org  Wed Oct 25 18:05:12 2006
From: coughlan at ski.org (James Coughlan)
Date: Wed, 25 Oct 2006 15:05:12 -0700
Subject: [SciPy-user] can't get weave to work (apologies for resend)
Message-ID: <453FDF98.2020708@ski.org>

Hello,

When I try to run a simple weave example (main.py):

from scipy import weave
a=1
weave.inline('printf("%d",a);',['a'],compiler='gcc')

it gives me this error message:
"
CompileError: error: Command "g++ -mno-cygwin -mdll -O2 -w 
-IC:\Python24\lib\site-packages\scipy\wea
ve -IC:\Python24\lib\site-packages\scipy\weave\scxx 
-IC:\Python24\lib\site-packages\numpy\core\inclu
de -IC:\Python24\include -IC:\Python24\PC -c 
C:\Python24\lib\site-packages\scipy\weave\scxx\weave_im
p.cpp -o 
c:\docume~1\james\locals~1\temp\James\python24_intermediate\compiler_ad9404e4505a343c45a7cd 

09360558c2\Release\python24\lib\site-packages\scipy\weave\scxx\weave_imp.o" 
failed with exit status
2
WARNING: Failure executing file: <main.py>
"

If I instead specify compiler='msvc' I get a different error message:
"
DistutilsPlatformError: The .NET Framework SDK needs to be installed 
before building extensions for
Python.
WARNING: Failure executing file: <main.py>
"

When I ran weave.test() I get this report: "Ran 132 tests in 3.445s", 
but it also produced some errors, e.g. "specified build_dir '_bad_path_' 
does not exist or is not writable".

I am running Python Enthought Edition -- Python 2.4.3 for Windows 
Enhanced Python Distribution, which includes SciPy version 0.5.0.2033. 
Weave *used* to work for me when I was running Python 2.3.

Can anybody give me any suggestions, or point me to someone who might be 
able to help me?

Thanks,
James

-- 
-------------------------------------------------------
James Coughlan, Ph.D., Associate Scientist                     

Smith-Kettlewell Eye Research Institute

Email: coughlan at ski.org
URL: http://www.ski.org/Rehab/Coughlan_lab/
Phone: 415-345-2146 
Fax: 415-345-8455
-------------------------------------------------------



From scipy at mspacek.mm.st  Thu Oct 26 02:43:24 2006
From: scipy at mspacek.mm.st (Martin Spacek)
Date: Wed, 25 Oct 2006 23:43:24 -0700
Subject: [SciPy-user] Maximum entropy distribution for Ising model - setup?
Message-ID: <4540590C.5090905@mspacek.mm.st>

Hello,

This is mostly directed to Ed Schofield, but maybe someone else might be 
able to help as well.

I'm trying to use the scipy.maxentropy model but I've run into a snag, 
and I suspect I simply haven't set it up correctly for my situation.

I'd like to find the maximum entropy distribution of an Ising model of 
magnetic spins (in my case, the spins are actually activity states of 
neurons in a cortical network). Spins can either be down or up (-1 or 1 
respectively). Spins can interact with each other in a pairwise way.

 From what I understand, the Ising model is this:

P(s1, s2, ..., sN) = 1 / Z * exp( sum(hi*si) + 0.5*sum(Jij*si*sj) )
                                    i               i!=j

The si are the spins. I want to model roughly N=10 of them. The hi and 
Jij are the Lagrange multipliers. The hi are the local magnetic fields 
acting on each spin, and the Jij are the degree in which each pair of 
spins interacts. Z is the normalizing partition function.

I'd like to be able to provide the average value for each spin in my 
system (a list of 10 floats in the range (-1, 1)), as well as the 
averages of all possible pairwise products of spins (a list of 10 choose 
2 == 45 floats, also in the range (-1, 1)). Then, after running 
(whichever) maxentropy algorithm and fitting it to the provided data, 
I'd like to be able to pull out the probabilities of each and every 
possible state of the population of spins (say [-1, -1, 1, ...] or [1, 
-1, -1, ...]).

I used scipy/maxentropy/examples/bergerexample.py to get started. I've 
got the following code:

#-----------
import neuropy as np
from scipy import maxentropy

def f1(x):
     return x==1

class Ising(object):
     """Ising maximum entropy model"""
     def __init__(self, means, pairmeans, algorithm='CG'):
         nbits = len(means)
         samplespace = [-1, 1] # non spiking or spiking
         f1s = [ f1 ]*nbits

         # Return True if they're either both spiking or both non-spiking
         # (correlated), otherwise, return False
         f2s = [ lambda x: f1s[i](x) == f1s[j](x) \
                 for i in range(0, nbits) for j in range(i+1, nbits) ]
         f = np.concatenate((f1s, f2s))
         self.model = maxentropy.model(f, samplespace)
         self.model.verbose = True

         # Now set the desired feature expectations
         means = np.asarray(means)
         pairmeans = np.asarray(pairmeans)
         pairmeans /= 2.0 # add the one half in front of each coefficient
         K = np.concatenate((means, pairmeans))

         # Fit the model
         self.model.fit(K, algorithm=algorithm)

         # Output the distribution
         print "\nFitted model parameters are:\n" \
                + str(self.model.params)
         print "\nFitted distribution is:"
         p = self.model.probdist()
         for j in range(len(self.model.samplespace)):
             x = self.model.samplespace[j]
             print '\tx:%s, p(x):%s' % (x, p[j])

i = Ising(means, pairmeans)

#--------------
means is a list of 10 floats that mostly hover around -0.8 to -0.5. 
pairmeans is a list of 45 floats that are mostly around 0.4 to 0.9. This 
runs, but gives me a DivergenceError:

Grad eval #0
   norm of gradient = 6.02170024163
Function eval # 0
   dual is  0.69314718056
Function eval # 1
   dual is  -29.5692018412
Grad eval #1
   norm of gradient = 5.03761439516
Function eval # 2
   dual is  -147.846016909
Grad eval #2
   norm of gradient = 5.03761183138
Function eval # 3
   dual is  -620.953271018
Grad eval #3
   norm of gradient = 5.03761183138
Function eval # 4
   dual is  -1478.46016909
Grad eval #4
   norm of gradient = 5.03761183138
Iteration # 0
Function eval # 5
   dual is  -1478.46016909
Traceback (most recent call last):
<snip>
   File 
"C:\bin\Python24\lib\site-packages\scipy\maxentropy\maxentropy.py", line 
221, in fit
     callback=callback)
   File "C:\bin\Python24\Lib\site-packages\scipy\optimize\optimize.py", 
line 811, in fmin_cg
     callback(xk)
   File 
"C:\bin\Python24\lib\site-packages\scipy\maxentropy\maxentropy.py", line 
397, in log
     raise DivergenceError, "dual is below the threshold 'mindual'" \
DivergenceError: "dual is below the threshold 'mindual' and may be 
diverging to -inf.  Fix the constraints or lower the threshold!"

I tried changing the model's mindual attrib from -100 to something 
ridiculous like -100000, but that didn't change much, just took more 
iterations before bombing out. I've also tried some of the algorithms 
other than 'CG', without any luck.

I don't know much about maximum entropy modelling, especially the actual 
algorithms. I only have a general idea of what it's supposed to do, so 
the above code is really just a shot in the dark. I suspect the problem 
is in properly defining both the means and the pairwise means for the 
model. Or it may have something to do with continuous vs. discrete 
values. Any suggestions?

Thanks,

Martin


P.S. For anyone interested, this is related to the recent Nature paper 
"Weak pairwise correlation imply strongly correlated network states in a 
neural population" by Schneidman et al:

http://www.nature.com/nature/journal/v440/n7087/abs/nature04701.html


From fullung at gmail.com  Thu Oct 26 03:50:24 2006
From: fullung at gmail.com (Albert Strasheim)
Date: Thu, 26 Oct 2006 09:50:24 +0200
Subject: [SciPy-user] Subclassing array
In-Reply-To: <mforbes-E139B0.17433524102006@news.gmane.org>
Message-ID: <E1Gd00P-0006mx-2F@mail3.sun.ac.za>

Hey Michael

Don't record arrays already solve your problem? See the following page on
the wiki for some examples:

http://www.scipy.org/RecordArrays

Cheers,

Albert

> -----Original Message-----
> From: scipy-user-bounces at scipy.org [mailto:scipy-user-bounces at scipy.org]
> On Behalf Of Michael McNeil Forbes
> Sent: 25 October 2006 02:44
> To: scipy-user at scipy.org
> Subject: [SciPy-user] Subclassing array
> 
> I have a question about the best way to subclass array types.
> 
> I would like to create a subclass of the array types that allows me to
> name the entries of the array.  Here is a sample of my desired usage:
> 
> >>> from scipy import *
> >>> a = array([1.0,2.0])
> >>>
> >>> class MyArray(a.__class__):
> >>>   _names = ['x','y']
> >>>   ... (redefine __get__ etc. as needed)
> >>>
> >>> c = MyArray(x=2,y=3)
> >>> c.x, c.y
> (2, 3)



From davidlinke at tiscali.de  Thu Oct 26 14:24:56 2006
From: davidlinke at tiscali.de (David Linke)
Date: Thu, 26 Oct 2006 20:24:56 +0200
Subject: [SciPy-user] wiki
In-Reply-To: <453FD6AE.2050801@gmail.com>
References: <453E5A1C.6040902@gmail.com> <20061025203626.GG5588@clipper.ens.fr>
	<453FD6AE.2050801@gmail.com>
Message-ID: <4540FD78.4000303@tiscali.de>

fred wrote:
> Gael Varoquaux a ?crit :
> 
> 
>>On Tue, Oct 24, 2006 at 08:23:24PM +0200, fred wrote:
>> 
>>
>>
>>>1) How can I add a page ?
>>>I want to add Cookbook/MayaVi/InstallPythonStuffFromSource page.
>>>   
>>>
>>
>>Just create a link to this page from another one. Then you can click on
>>this link, and edit the blank page.
>>
> 
> Ok, fine.
> 
> I was missing the second ":" in my link.
> Sorry.

This ":" syntax is an experimental syntax in MoinMoin. I am wondering 
why it is used on scipy wiki so often. The standard link to a page with 
a non-wikiname is ["Wikipage"] or [Self:Wikipage Other name for page]. 
The : notation is a replacement for the latter. Yet another way to 
create a page is to go to  http://scipy.org/FindPage and enter the name 
of the new page in the field with the "Go To Page" button (and click the 
bottom ;-)).

>>>2) How can I delete some png image files previously uploaded ?
>>>   
>>>
>>
>>You cannot.
>> 
>
> I only want to upgrade some png file I have uploaded.
> Then, why is there a "delete" item beside images in info page ?

Ask someone listed on http://scipy.org/EditorsGroup to add your name to 
that page.

Regards,
David


From fredmfp at gmail.com  Thu Oct 26 16:47:27 2006
From: fredmfp at gmail.com (fred)
Date: Thu, 26 Oct 2006 22:47:27 +0200
Subject: [SciPy-user] wiki
In-Reply-To: <4540FD78.4000303@tiscali.de>
References: <453E5A1C.6040902@gmail.com>
	<20061025203626.GG5588@clipper.ens.fr>	<453FD6AE.2050801@gmail.com>
	<4540FD78.4000303@tiscali.de>
Message-ID: <45411EDF.9080905@gmail.com>

David Linke a ?crit :

[snip]

>Ask someone listed on http://scipy.org/EditorsGroup to add your name to 
>that page.
>  
>
Thanks again, David !

-- 
http://scipy.org/FredericPetit



From coughlan at ski.org  Thu Oct 26 18:08:31 2006
From: coughlan at ski.org (James Coughlan)
Date: Thu, 26 Oct 2006 15:08:31 -0700
Subject: [SciPy-user] can't get weave to work (apologies for resend)
Message-ID: <454131DF.7080405@ski.org>

Hello,

When I try to run a simple weave example (main.py):

from scipy import weave
a=1
weave.inline('printf("%d",a);',['a'],compiler='gcc')

it gives me this error message:
"
CompileError: error: Command "g++ -mno-cygwin -mdll -O2 -w
-IC:\Python24\lib\site-packages\scipy\wea
ve -IC:\Python24\lib\site-packages\scipy\weave\scxx
-IC:\Python24\lib\site-packages\numpy\core\inclu
de -IC:\Python24\include -IC:\Python24\PC -c
C:\Python24\lib\site-packages\scipy\weave\scxx\weave_im
p.cpp -o
c:\docume~1\james\locals~1\temp\James\python24_intermediate\compiler_ad9404e4505a343c45a7cd 


09360558c2\Release\python24\lib\site-packages\scipy\weave\scxx\weave_imp.o"
failed with exit status
2
WARNING: Failure executing file: <main.py>
"

If I instead specify compiler='msvc' I get a different error message:
"
DistutilsPlatformError: The .NET Framework SDK needs to be installed
before building extensions for
Python.
WARNING: Failure executing file: <main.py>
"

When I ran weave.test() I get this report: "Ran 132 tests in 3.445s",
but it also produced some errors, e.g. "specified build_dir '_bad_path_'
does not exist or is not writable".

I am running Python Enthought Edition -- Python 2.4.3 for Windows
Enhanced Python Distribution, which includes SciPy version 0.5.0.2033.
Weave *used* to work for me when I was running Python 2.3.

Can anybody give me any suggestions, or point me to someone who might be
able to help me?

Thanks,
James

-- 
-------------------------------------------------------
James Coughlan, Ph.D., Associate Scientist

Smith-Kettlewell Eye Research Institute

Email: coughlan at ski.org
URL: http://www.ski.org/Rehab/Coughlan_lab/
Phone: 415-345-2146
Fax: 415-345-8455
-------------------------------------------------------




From oliphant at ee.byu.edu  Thu Oct 26 19:28:39 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Thu, 26 Oct 2006 17:28:39 -0600
Subject: [SciPy-user] can't get weave to work (apologies for resend)
In-Reply-To: <454131DF.7080405@ski.org>
References: <454131DF.7080405@ski.org>
Message-ID: <454144A7.4040100@ee.byu.edu>

James Coughlan wrote:

>Hello,
>
>When I try to run a simple weave example (main.py):
>
>from scipy import weave
>a=1
>weave.inline('printf("%d",a);',['a'],compiler='gcc')
>
>it gives me this error message:
>"
>CompileError: error: Command "g++ -mno-cygwin -mdll -O2 -w
>-IC:\Python24\lib\site-packages\scipy\wea
>ve -IC:\Python24\lib\site-packages\scipy\weave\scxx
>-IC:\Python24\lib\site-packages\numpy\core\inclu
>de -IC:\Python24\include -IC:\Python24\PC -c
>C:\Python24\lib\site-packages\scipy\weave\scxx\weave_im
>p.cpp -o
>c:\docume~1\james\locals~1\temp\James\python24_intermediate\compiler_ad9404e4505a343c45a7cd 
>
>
>09360558c2\Release\python24\lib\site-packages\scipy\weave\scxx\weave_imp.o"
>failed with exit status
>2
>WARNING: Failure executing file: <main.py>
>"
>  
>

It looks like your compiler is not working. 

Go to the temporary directory where weave has stored the source code it 
is compiling and try to compile it at the command line.  Perhaps we are 
not seeing all the error messages that would identify what is wrong with 
your set-up.





From tim.leslie at gmail.com  Fri Oct 27 01:45:38 2006
From: tim.leslie at gmail.com (Tim Leslie)
Date: Fri, 27 Oct 2006 15:45:38 +1000
Subject: [SciPy-user] Maximum entropy distribution for Ising model -
	setup?
In-Reply-To: <4540590C.5090905@mspacek.mm.st>
References: <4540590C.5090905@mspacek.mm.st>
Message-ID: <d32b45350610262245t7b8453b6r80f1bf198e8d2e6c@mail.gmail.com>

On 10/26/06, Martin Spacek <scipy at mspacek.mm.st> wrote:
> Hello,
>
> This is mostly directed to Ed Schofield, but maybe someone else might be
> able to help as well.
>
> I'm trying to use the scipy.maxentropy model but I've run into a snag,
> and I suspect I simply haven't set it up correctly for my situation.
>
> I'd like to find the maximum entropy distribution of an Ising model of
> magnetic spins (in my case, the spins are actually activity states of
> neurons in a cortical network). Spins can either be down or up (-1 or 1
> respectively). Spins can interact with each other in a pairwise way.
>
>  From what I understand, the Ising model is this:
>
> P(s1, s2, ..., sN) = 1 / Z * exp( sum(hi*si) + 0.5*sum(Jij*si*sj) )
>                                     i               i!=j
>
> The si are the spins. I want to model roughly N=10 of them. The hi and
> Jij are the Lagrange multipliers. The hi are the local magnetic fields
> acting on each spin, and the Jij are the degree in which each pair of
> spins interacts. Z is the normalizing partition function.
>

I could be wrong here, but doesn't the Ising model only consider
nearest neighbour interactions? Would changing your setup to only
consider these interactions make things work?

Tim

> I'd like to be able to provide the average value for each spin in my
> system (a list of 10 floats in the range (-1, 1)), as well as the
> averages of all possible pairwise products of spins (a list of 10 choose
> 2 == 45 floats, also in the range (-1, 1)). Then, after running
> (whichever) maxentropy algorithm and fitting it to the provided data,
> I'd like to be able to pull out the probabilities of each and every
> possible state of the population of spins (say [-1, -1, 1, ...] or [1,
> -1, -1, ...]).
>
> I used scipy/maxentropy/examples/bergerexample.py to get started. I've
> got the following code:
>
> #-----------
> import neuropy as np
> from scipy import maxentropy
>
> def f1(x):
>      return x==1
>
> class Ising(object):
>      """Ising maximum entropy model"""
>      def __init__(self, means, pairmeans, algorithm='CG'):
>          nbits = len(means)
>          samplespace = [-1, 1] # non spiking or spiking
>          f1s = [ f1 ]*nbits
>
>          # Return True if they're either both spiking or both non-spiking
>          # (correlated), otherwise, return False
>          f2s = [ lambda x: f1s[i](x) == f1s[j](x) \
>                  for i in range(0, nbits) for j in range(i+1, nbits) ]
>          f = np.concatenate((f1s, f2s))
>          self.model = maxentropy.model(f, samplespace)
>          self.model.verbose = True
>
>          # Now set the desired feature expectations
>          means = np.asarray(means)
>          pairmeans = np.asarray(pairmeans)
>          pairmeans /= 2.0 # add the one half in front of each coefficient
>          K = np.concatenate((means, pairmeans))
>
>          # Fit the model
>          self.model.fit(K, algorithm=algorithm)
>
>          # Output the distribution
>          print "\nFitted model parameters are:\n" \
>                 + str(self.model.params)
>          print "\nFitted distribution is:"
>          p = self.model.probdist()
>          for j in range(len(self.model.samplespace)):
>              x = self.model.samplespace[j]
>              print '\tx:%s, p(x):%s' % (x, p[j])
>
> i = Ising(means, pairmeans)
>
> #--------------
> means is a list of 10 floats that mostly hover around -0.8 to -0.5.
> pairmeans is a list of 45 floats that are mostly around 0.4 to 0.9. This
> runs, but gives me a DivergenceError:
>
> Grad eval #0
>    norm of gradient = 6.02170024163
> Function eval # 0
>    dual is  0.69314718056
> Function eval # 1
>    dual is  -29.5692018412
> Grad eval #1
>    norm of gradient = 5.03761439516
> Function eval # 2
>    dual is  -147.846016909
> Grad eval #2
>    norm of gradient = 5.03761183138
> Function eval # 3
>    dual is  -620.953271018
> Grad eval #3
>    norm of gradient = 5.03761183138
> Function eval # 4
>    dual is  -1478.46016909
> Grad eval #4
>    norm of gradient = 5.03761183138
> Iteration # 0
> Function eval # 5
>    dual is  -1478.46016909
> Traceback (most recent call last):
> <snip>
>    File
> "C:\bin\Python24\lib\site-packages\scipy\maxentropy\maxentropy.py", line
> 221, in fit
>      callback=callback)
>    File "C:\bin\Python24\Lib\site-packages\scipy\optimize\optimize.py",
> line 811, in fmin_cg
>      callback(xk)
>    File
> "C:\bin\Python24\lib\site-packages\scipy\maxentropy\maxentropy.py", line
> 397, in log
>      raise DivergenceError, "dual is below the threshold 'mindual'" \
> DivergenceError: "dual is below the threshold 'mindual' and may be
> diverging to -inf.  Fix the constraints or lower the threshold!"
>
> I tried changing the model's mindual attrib from -100 to something
> ridiculous like -100000, but that didn't change much, just took more
> iterations before bombing out. I've also tried some of the algorithms
> other than 'CG', without any luck.
>
> I don't know much about maximum entropy modelling, especially the actual
> algorithms. I only have a general idea of what it's supposed to do, so
> the above code is really just a shot in the dark. I suspect the problem
> is in properly defining both the means and the pairwise means for the
> model. Or it may have something to do with continuous vs. discrete
> values. Any suggestions?
>
> Thanks,
>
> Martin
>
>
> P.S. For anyone interested, this is related to the recent Nature paper
> "Weak pairwise correlation imply strongly correlated network states in a
> neural population" by Schneidman et al:
>
> http://www.nature.com/nature/journal/v440/n7087/abs/nature04701.html
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From scipy at mspacek.mm.st  Fri Oct 27 04:51:36 2006
From: scipy at mspacek.mm.st (Martin Spacek)
Date: Fri, 27 Oct 2006 01:51:36 -0700
Subject: [SciPy-user] Maximum entropy distribution for Ising model
	-	setup?
In-Reply-To: <d32b45350610262245t7b8453b6r80f1bf198e8d2e6c@mail.gmail.com>
References: <4540590C.5090905@mspacek.mm.st>
	<d32b45350610262245t7b8453b6r80f1bf198e8d2e6c@mail.gmail.com>
Message-ID: <4541C898.3040109@mspacek.mm.st>

Tim Leslie wrote:

> I could be wrong here, but doesn't the Ising model only consider
> nearest neighbour interactions? Would changing your setup to only
> consider these interactions make things work?

Yeah, that's what I've read as well, so I'm a bit confused over why the 
paper I mentioned calls this an Ising model. What we're doing is 
considering interactions among all pairs, although most of those are 
very weak. Anyway, what I need is to run maxentropy on this system:

P(s1, s2, ..., sN) = 1 / Z * exp( sum(hi*si) + 0.5*sum(Jij*si*sj) )
                                    i               i!=j

regardless of whether it's Ising or not. I think I can see how to do it 
in scipy.maxentropy if it were simply:

P(s1, s2, ..., sN) = 1 / Z * exp( sum(hi*si) )
                                    i

But getting it to work with the pairwise terms is just guesswork on my 
part...

Martin


From david at ar.media.kyoto-u.ac.jp  Fri Oct 27 05:46:03 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Fri, 27 Oct 2006 18:46:03 +0900
Subject: [SciPy-user] pyaudio, a module to make noise from numpy arrays
Message-ID: <4541D55B.9090505@ar.media.kyoto-u.ac.jp>

Hi,
    I announce the first release of pyaudio, a module to make noise from 
numpy arrays (read, write and play audio files with numpy arrays).

 * WHAT FOR ?:

    The Goal is to give to a numpy/scipy environmenet some basic audio 
IO facilities (ala sound, wavread, wavwrite of matlab).

    With pyaudio, you should be able to read and write most common audio 
files from and to numpy arrays. The underlying IO operations are done 
using libsndfile from Erik Castro Lopo 
(http://www.mega-nerd.com/libsndfile/), so he is the one who did the 
hard work. As libsndfile has support for a vast number of audio files 
(including wav, aiff, but also htk, ircam, and flac, an open source 
lossless codec), pyaudio enables the import from and export to a fairly 
large number of file formats.
    There is also a really crude player, which uses tempfile to play 
audio, and which only works for linux-alsa anyway. I intend to add 
better support at least for linux, and for other platforms if this does 
not involve too much hassle.

    So basically, if you are lucky enough to use a recent linux system, 
pyaudio already gives you the equivalent of wavread, wavwrite and sound.

 * DOWNLOAD:

    http://www.ar.media.kyoto-u.ac.jp/members/david/pyaudio.tar.gz

 * INSTALLATION INSTRUCTIONS:

    Just untar the package and drop it into scipy/Lib/sandbox, and add 
the two following lines to scipy/Lib/sandbox/setup.py:
    
    # Package to make some noise using numpy
    config.add_subpackage('pyaudio')

    (if libsndfile.so is not in /usr/lib, a fortiori if you are a 
windows user, you should also change set the right location for 
libsndfile in pyaudio/pysndfile.py, at the line 
_snd.cdll.LoadLibrary('/usr/lib/libsndfile.so') )

 * EXAMPLE USAGE

    == Reading example ==

    # Reading from '/home/david/blop.flac'
    from scipy.sandbox.pyaudio import sndfile

    a = sndfile('/home/david/blop.flac')
    print a

    tmp = a.read_frames_float(1024)

    --> Prints:

    File        : /home/david/blop.flac
    Sample rate : 44100
    Channels    : 2
    Frames      : 9979776
    Format      : 0x00170002
    Sections    : 1
    Seekable    : True
    Duration    : 00:03:46.298

    And put into tmp the 1024 first frames (a frame is the equivalent of 
a sample, but taking into account the number of channels: so 1024 frames 
gives you 2048 samples here).

    == Writing example ==
    # Writing to a wavfile:
    from scipy.sandbox.pyaudio import sndfile
    import numpy as N

    noise     = N.random.randn((44100))
    a         = sndfile('/home/david/blop.flac', sfm['SFM_WRITE'], 
sf_format['SF_FORMAT_WAV'] | sf_format['SF_FORMAT_PCM16'],
        1, 44100)

    a.write_frames(noise, 44100)
    a.close()

    -> should gives you a lossless compressed white noise !

    This is really a first release, not really tested, not much 
documentation, I can just say it works for me. I haven't found a good 
way to emulate enumerations, which libsndfile uses a lot, so I am using 
dictionaries generated from the library C header to get a relation enum 
label <=> value. If someone has a better idea, I am open to suggestions !

    Cheers,

    David


From coughlan at ski.org  Fri Oct 27 16:11:39 2006
From: coughlan at ski.org (James Coughlan)
Date: Fri, 27 Oct 2006 13:11:39 -0700
Subject: [SciPy-user] Maximum entropy distribution for Ising model -
	setup?
In-Reply-To: <4540590C.5090905@mspacek.mm.st>
References: <4540590C.5090905@mspacek.mm.st>
Message-ID: <454267FB.1060806@ski.org>

Hi,

I've done some max. ent. modeling, although I'm unfamiliar with the 
scipy maxentropy package. A few points:

1.) If N=10 spins suffices, then there are only 2^10=1024 possible 
configurations of your model, so you can calculate Z and thus the 
average spin <si> (and spin product <si*sj>) values exactly by hand, and 
completely bypass the maxentropy package. On the other hand, maybe scipy 
maxentropy can save you a lot of work!

2.) If you are doing max. ent. modeling, then you are given *empirical* 
(measured) values of <si>_{emp} and <si*sj>_{emp} and are trying to find 
model parameters hi and Jij to match these values, i.e. <si>=<si>_{emp} 
and <si*sj>=<si*sj>_{emp} where the LHS's are the averages w.r.t. the 
model. You can solve for the model parameters by iterating these 
gradient descent equations:

hi_{new}=hi_{old} + K * (<si> - <si>_{emp})
Jij_{new}=Jij_{old}+ K' * (<si*sj> - <si*sj>_{emp})

where K and K' are pos. "step size" constants. (On the RHS, <si> and 
<si*sj> are w.r.t. hi_{old} and Jij_{old}.)

But this process can be slow. It can be sped up by choosing K, K' 
adaptively; maybe the maxentropy package does this more intelligently.

3.) In a typical Ising model, interactions are nearest neighbor, which 
means that Jij is sparse (i.e. it only =1 for neighboring spins i and 
j). But in principal your model can certainly handle arbitrary Jij. 
However, it might be easier (and less prone to overfitting) if you keep 
Jij sparse.

Hope this helps.

Best,

James


From ivan.nazarenko at gmail.com  Fri Oct 27 17:12:59 2006
From: ivan.nazarenko at gmail.com (Ivan Nazarenko)
Date: Fri, 27 Oct 2006 21:12:59 +0000 (UTC)
Subject: [SciPy-user] numpy - scipy version hell
References: <200610191314.49095.jkgruet@sandia.gov>
	<4537CF49.8000008@ee.byu.edu>
Message-ID: <loom.20061027T225859-642@post.gmane.org>

Travis Oliphant <oliphant <at> ee.byu.edu> writes:

> Very few packages will have the correct versions of numpy and scipy that 
> work together.
> 
> The latest that work together is Scipy 0.5.1 and NumPy 1.0rc2
> 
> Look for an updated SciPy release to work with NumPy 1.0 when it comes 
> out next week.
> 
> -Travis

I had a similar problem, and OK, I will wait until next Scipy release. But it 
is a bit odd that we can't download the 1.0rc2 version easily; sourceforge is 
only hosting 1.0 (final), at least for linux.

I downloaded the most recent versions of numpy and scipy and can't make them 
work. And can't even download a compatible numpy version!!! Go figure...

Ivan






From oliphant.travis at ieee.org  Fri Oct 27 17:31:44 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Fri, 27 Oct 2006 15:31:44 -0600
Subject: [SciPy-user] numpy - scipy version hell
In-Reply-To: <loom.20061027T225859-642@post.gmane.org>
References: <200610191314.49095.jkgruet@sandia.gov>	<4537CF49.8000008@ee.byu.edu>
	<loom.20061027T225859-642@post.gmane.org>
Message-ID: <45427AC0.4000905@ieee.org>

Ivan Nazarenko wrote:
> Travis Oliphant <oliphant <at> ee.byu.edu> writes:
>
>   
>> Very few packages will have the correct versions of numpy and scipy that 
>> work together.
>>
>> The latest that work together is Scipy 0.5.1 and NumPy 1.0rc2
>>
>> Look for an updated SciPy release to work with NumPy 1.0 when it comes 
>> out next week.
>>
>> -Travis
>>     
>
> I had a similar problem, and OK, I will wait until next Scipy release. But it 
> is a bit odd that we can't download the 1.0rc2 version easily; sourceforge is 
> only hosting 1.0 (final), at least for linux.
>   
If you are building from scratch, then you don't need the binaries.  You 
can build 1.0 and 0.5.1 and they will work together.  You will have a 
few unit tests fail, but they are pretty inconsequential.

> I downloaded the most recent versions of numpy and scipy and can't make them 
> work. And can't even download a compatible numpy version!!! Go figure...
>   

what is the error you are getting?   They should work fine when you 
build them yourself.

The only issue is binary compatibility which is the reason 1.0rc2 
binaries are made available.


From ckkart at hoc.net  Fri Oct 27 21:47:01 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Sat, 28 Oct 2006 10:47:01 +0900
Subject: [SciPy-user] packaging with numpy.distutils
Message-ID: <4542B695.8040806@hoc.net>

Hi,

I posted this to the numpy list but maybe it has been overlooked. Apologizes for
asking here.
I am creating a binary package on windows (bdist_wininst) making use of
numpy.distutils and I would like to have something installed into PREFIX. With
standard distutils this can be achieved by using the data_files keyword with
setup. With numpy.distutils however those data end up in site-packages.
Any ideas?

Christian


From scipy at mspacek.mm.st  Sat Oct 28 08:23:36 2006
From: scipy at mspacek.mm.st (Martin Spacek)
Date: Sat, 28 Oct 2006 05:23:36 -0700
Subject: [SciPy-user] Maximum entropy distribution for Ising model
	-	setup?
In-Reply-To: <454267FB.1060806@ski.org>
References: <4540590C.5090905@mspacek.mm.st> <454267FB.1060806@ski.org>
Message-ID: <45434BC8.9000909@mspacek.mm.st>

Hi James,

Bear with me, I don't exactly have a complete understanding of this.

James Coughlan wrote:
> Hi,
> 
> I've done some max. ent. modeling, although I'm unfamiliar with the 
> scipy maxentropy package. A few points:
> 
> 1.) If N=10 spins suffices, then there are only 2^10=1024 possible 
> configurations of your model, so you can calculate Z and thus the 
> average spin <si> (and spin product <si*sj>) values exactly by hand, and 
> completely bypass the maxentropy package. On the other hand, maybe scipy 
> maxentropy can save you a lot of work!

Hmm. I don't really follow you. I already have the average spin values 
<si> and average spin product values <si*sj> (I get those from 
experiment). I want to find a combination of the individual spins and 
spin products that maximizes the entropy = -sum( pi*log(pi) )
(where each pi is the model's predicted probability of one of 1024 
states) of the probability distribution for all possible combinations of 
spin states (up, up, down.... , or up, down, up...).

> 2.) If you are doing max. ent. modeling, then you are given *empirical* 
> (measured) values of <si>_{emp} and <si*sj>_{emp} and are trying to find 
> model parameters hi and Jij to match these values, i.e. <si>=<si>_{emp} 
> and <si*sj>=<si*sj>_{emp} where the LHS's are the averages w.r.t. the 
> model. You can solve for the model parameters by iterating these 
> gradient descent equations:
> 
> hi_{new}=hi_{old} + K * (<si> - <si>_{emp})
> Jij_{new}=Jij_{old}+ K' * (<si*sj> - <si*sj>_{emp})
> 
> where K and K' are pos. "step size" constants. (On the RHS, <si> and 
> <si*sj> are w.r.t. hi_{old} and Jij_{old}.)
> 
> But this process can be slow. It can be sped up by choosing K, K' 
> adaptively; maybe the maxentropy package does this more intelligently.

I thought the whole magic of running maximum entropy is not just that 
you end up with a set of hi and Jij that give you a probability 
distribution that matches the expectation values that you asked for (to 
within some tolerance), but that you also choose those hi and Jij such 
that the distribution's entropy is maximized, thereby minimizing any 
assumptions about it that weren't specified by the constraints (such as 
third, or fourth, or higher order statistics).

> 3.) In a typical Ising model, interactions are nearest neighbor, which 
> means that Jij is sparse (i.e. it only =1 for neighboring spins i and 
> j). But in principal your model can certainly handle arbitrary Jij. 
> However, it might be easier (and less prone to overfitting) if you keep 
> Jij sparse.

In this case, there's no measure of nearness of neighbours that I can 
use. They're all equally potential neighbours of each other. I'm not 
sure this is a typical nearest neighbour Ising model. After some more 
reading, I almost suspect that the authors of the Nature paper I 
mentioned shouldn't have chosen to call it Ising. I think many of the 
Jij will be quite small, but I want that to come out of the model. I 
don't have any way to justify setting some of them to zero ahead of 
time. I certainly doubt that any of the Jij would end up equal to 1.

Martin


From coughlan at ski.org  Sat Oct 28 13:18:45 2006
From: coughlan at ski.org (James Coughlan)
Date: Sat, 28 Oct 2006 10:18:45 -0700
Subject: [SciPy-user] Maximum entropy distribution for Ising
	model	-	setup?
In-Reply-To: <45434BC8.9000909@mspacek.mm.st>
References: <4540590C.5090905@mspacek.mm.st> <454267FB.1060806@ski.org>
	<45434BC8.9000909@mspacek.mm.st>
Message-ID: <454390F5.5020806@ski.org>

Martin,

Hope this makes sense. If not, why don't we take this discussion offline.

Best,

James

1.) "I want to find a combination of the individual spins and
spin products that maximizes the entropy"

No, you want to find a *probability distribution* of spins that 
maximizes the entropy. Remember, the entropy of a random variable is 
defined for a distribution of the variable (e.g. configuration of 
spins), not for a particular value of the variable.

2.) "I thought the whole magic of running maximum entropy is not just that
you end up with a set of hi and Jij that give you a probability
distribution that matches the expectation values that you asked for (to
within some tolerance), but that you also choose those hi and Jij such
that the distribution's entropy is maximized"

True -- see the summary below.

3.) "I think many of the Jij will be quite small, but I want that to 
come out of the model. I
don't have any way to justify setting some of them to zero ahead of
time."

No problem, as long as your empirical values are measured accurately 
enough (and assuming the max.entr. framework makes sense for your 
application).

4.) Maxent summary:

Case 1. A single scalar empirical statistic

Given a variable x (e.g. N spin states) and empirical stastic 
<f(x)>_{emp}, the max. ent. distr. whose statistic matches the empirical 
statistic is:

P(x) = e^{a*f(x)} / Z(a)

where a is chosen such that <f(x)> = <f(x)>_{emp}. Entropy is defined as 
H = -\sum_x P(x) log P(x).

Proof (sketch): Use lagrange multiplier to maximize entropy subject to 
constraint <f(x)> = <f(x)>_{emp}:

E = H - a(<f(x)> - <f(x)>_{emp}) where a is the lagrange multiplier.

Maximize E wrt P(x) and a, get P(x) = const * e^{a*f(x)}, where we call 
const Z(a) since it depends on a, and where a is chosen to satisfy 
<f(x)> = <f(x)>_{emp}.


Case 2. More than one scalar empirical statistic

Now f(x) can be a scalar or vector function (one component for each 
empirically observed scalar value) of x. In your spin example, it is a 
vector with many components: f(s)=(s_1, ... s_N; s_12, ... s_1N, s_22, 
... s_2N, s_N1, ... s_NN), in which case the lagrange multipliers are 
the h_i and J_ij 's.

Similar result is obtained.


From arserlom at gmail.com  Sat Oct 28 14:30:36 2006
From: arserlom at gmail.com (Armando Serrano Lombillo)
Date: Sat, 28 Oct 2006 20:30:36 +0200
Subject: [SciPy-user] How to calculate minors.
In-Reply-To: <ce557a360610101414u7c8319a7r7a305b5e0b2ffca1@mail.gmail.com>
References: <d7ab268c0610100901w63a38414ya0f4721193abe2c5@mail.gmail.com>
	<ce557a360610101414u7c8319a7r7a305b5e0b2ffca1@mail.gmail.com>
Message-ID: <d7ab268c0610281130l59fd630eg79ebe8b1d40d987e@mail.gmail.com>

Thanks to both for your answers and excuse me for being so slow in my reply,
I've been quite busy lately.

Stephen:
I didn't know you could calculate minors that way, thanks for the tip.
Anyway, it looks like it's not the most efficient way of calculating them.
I also think a minor() function should be included in numpy.

Archibald:
I've built two python functions, but I was not able to write them with just
indexing, I had to use hstack and vstack also. Here are the functions

from numpy import *
def erase(array,row,column):
    return vstack((hstack((array[:row,:column],
                           array[:row,column+1:])),
                   hstack((array[row+1:,:column],
                           array[row+1:,column+1:]))))
def minor(array,index):
    return linalg.det(erase(array,index,index))

Is it possible to avoid using hstack and vstack in erase(), it looks like
there must be an easier way of doing the same thing.

Anyway, in my opinion, both functions are homemade workarounds for things
that should be included in numpy.

Armando Serrano.
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From fiepye at atlas.cz  Sun Oct 29 03:36:42 2006
From: fiepye at atlas.cz (fiepye at atlas.cz)
Date: Sun, 29 Oct 2006 09:36:42 +0100
Subject: [SciPy-user] Parallel OO programming in Python.
Message-ID: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>

Hello.

I am interested in parallel computing in Python. Except other modules I would like to use new modules for vector and matrix operations and scientific computing SciPy and NumPy. I have already installed LAPACK and BLAS libraries. It works well.

For object oriented parallel programming in Python on a single machine I can use techniques such as Bulk Synchronous Parallelism (BSP) or Message Passing Interface (MPI). There are mentioned some modules and packages for Python on
http://www.scipy.org/Topical_Software
Article: Parallel and distributed programming. 
After reading prerequisites and limitations I thing that the following ones could be good for me:
PyMPI
Pypar
MPI for Python

But I can't distinguish which one brings fewer limitations, is efficient in application and will develop in future.
My favorite is BSP, but I can't find a package for present SciPy and NumPy.

Could anybody give me a recommendation, which way I should go.

Thanks.
Fie Pye




---------------------------------------
M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz




From sodomau at postech.ac.kr  Sun Oct 29 05:44:48 2006
From: sodomau at postech.ac.kr (Sunghyun Cho)
Date: Sun, 29 Oct 2006 18:44:48 +0800
Subject: [SciPy-user] Nonlinear optimization with linear constraints
Message-ID: <5143a98b0610290244t3a9dd406ma9dd64cf3d06a35e@mail.gmail.com>

Hello, Scipy users.

I'm currently looking for a way to optimize nonlinear problem with linear
constraints.
I read documents of scipy, but I found there are just optimization methods
with bound constraints which just use min and max values.
If you know any packages related to this problem, please let me know.
I'll deeply appreciate your reply.

THANK YOU!

-- 
Sunghyun Cho
sodomau at postech.ac.kr
http://sodomau.plus.or.kr
Computer Graphics Lab.
POSTECH
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From hgk at et.uni-magdeburg.de  Sun Oct 29 08:32:23 2006
From: hgk at et.uni-magdeburg.de (Dr. Hans Georg Krauthaeuser)
Date: Sun, 29 Oct 2006 14:32:23 +0100
Subject: [SciPy-user] Combinatoric/Statistics: length of longest sequence
Message-ID: <ei2ah7$5bd$1@sea.gmane.org>

Dear All,

I have a 2d-array A of p-values (coming from pairwise statistical tests
of N datasets). N is typically in the range of 100-1000. Now, given a
certain threshold, I want to find the longest subset S of range(N), so
that A[i][j]>threshold for all i,j from S.

Unfortunately, the array A is not 'sparse', i.e. a lot of pairs (i,j)
will fulfill A[i][j]>threshold (typically ~50% of the elements).

All I can think of are brute force algorithms that probably will run
forever because of the large number of possible combinations to check.

It would be great if someone could give a pointer to a smart algorithm.

If it is not possible to give the exact answer, what algorithm could be
used to get a good approximative answer?

Regards
Hans Georg



From ellisonbg.net at gmail.com  Sun Oct 29 14:16:44 2006
From: ellisonbg.net at gmail.com (Brian Granger)
Date: Sun, 29 Oct 2006 12:16:44 -0700
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
Message-ID: <6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>

> For object oriented parallel programming in Python on a single machine I can use techniques such as Bulk Synchronous Parallelism (BSP) or Message Passing Interface (MPI). There are mentioned some modules and packages for Python on
> http://www.scipy.org/Topical_Software
> Article: Parallel and distributed programming.
> After reading prerequisites and limitations I thing that the following ones could be good for me:
> PyMPI
> Pypar
> MPI for Python

I think mpi4py is the best option.  It is a very nice implementation
and the developer is working really hard to make it a great package.
Also, I don't think pympi and pypar are being developed actively
anymore.

Another thing you might check out is IPython's parallel computing
facilities that let you use mpi4py (and other mpi bindings)
interactively:

http://ipython.scipy.org/moin/Parallel_Computing

I have never used BPS, but am familiar with the model.  Can probably
get it working interactively with IPython as well.

Cheers,

Brian

> But I can't distinguish which one brings fewer limitations, is efficient in application and will develop in future.
> My favorite is BSP, but I can't find a package for present SciPy and NumPy.
>
> Could anybody give me a recommendation, which way I should go.
>
> Thanks.
> Fie Pye
>
>
>
>
> ---------------------------------------
> M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
>
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>

From haase at msg.ucsf.edu  Sun Oct 29 18:04:38 2006
From: haase at msg.ucsf.edu (Sebastian Haase)
Date: Sun, 29 Oct 2006 15:04:38 -0800
Subject: [SciPy-user] Nonlinear optimization with linear constraints
In-Reply-To: <5143a98b0610290244t3a9dd406ma9dd64cf3d06a35e@mail.gmail.com>
References: <5143a98b0610290244t3a9dd406ma9dd64cf3d06a35e@mail.gmail.com>
Message-ID: <45453386.6020002@msg.ucsf.edu>

Sunghyun Cho wrote:
> Hello, Scipy users.
>  
> I'm currently looking for a way to optimize nonlinear problem with 
> linear constraints.
> I read documents of scipy, but I found there are just optimization 
> methods with bound constraints which just use min and max values.
> If you know any packages related to this problem, please let me know.
> I'll deeply appreciate your reply.
>  
> THANK YOU!
> 
> -- 
> Sunghyun Cho
> sodomau at postech.ac.kr <mailto:sodomau at postech.ac.kr>
> http://sodomau.plus.or.kr
> Computer Graphics Lab.
> POSTECH
> 
> 

Would the cobyla function help you ? It is in scipy.optimize.
Look also in the archive of this list for it.

-Sebastian


From peridot.faceted at gmail.com  Sun Oct 29 18:14:00 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Sun, 29 Oct 2006 19:14:00 -0400
Subject: [SciPy-user] Combinatoric/Statistics: length of longest sequence
In-Reply-To: <ei2ah7$5bd$1@sea.gmane.org>
References: <ei2ah7$5bd$1@sea.gmane.org>
Message-ID: <ce557a360610291514x1ed2525eydbf313a99ee59c12@mail.gmail.com>

On 29/10/06, Dr. Hans Georg Krauthaeuser <hgk at et.uni-magdeburg.de> wrote:
> Dear All,
>
> I have a 2d-array A of p-values (coming from pairwise statistical tests
> of N datasets). N is typically in the range of 100-1000. Now, given a
> certain threshold, I want to find the longest subset S of range(N), so
> that A[i][j]>threshold for all i,j from S.

It's not quite clear, here, whether you want the longest *contiguous*
subset ({2,3,4,5,6}) or the largest arbitrary subset ({2,17,21,22}).

> Unfortunately, the array A is not 'sparse', i.e. a lot of pairs (i,j)
> will fulfill A[i][j]>threshold (typically ~50% of the elements).
>
> All I can think of are brute force algorithms that probably will run
> forever because of the large number of possible combinations to check.

If you want the longest contiguous subset, for N=1000 that's only of
order a million operations for a brute-force algorithm (for each
starting element, see how long the run is), so unless you want to do
it lots of times I wouldn't worry. If you do, some Numeric cleverness
might allow you to move some of the heavy lifting to C, though for
simple indexing calculations pure python can be plenty fast.

If you want the largest arbitrary subset, that's going to be
expensive, and it bears an unnerving resemblance to the subset-sum
problem. I can imagine an expensive  recursive algorithm that would do
it without too much pain, though the space to search is so huge you're
liable to be taking a very long time. However you go about it, you may
be better off using python's set datatype (for element i, form the set
of all elements j for which A[i][j]>threshold).

I've attached a demonstration program that solves both interpretations
of your problem; the difficult one appears to bog down seriously
around N=200 (with p=0.5) but the easy one runs into memory problems
before taking too long.

A. M. Archibald
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From gael.varoquaux at normalesup.org  Sun Oct 29 18:39:53 2006
From: gael.varoquaux at normalesup.org (Gael Varoquaux)
Date: Mon, 30 Oct 2006 00:39:53 +0100
Subject: [SciPy-user] Error on the wiki
Message-ID: <20061029233953.GC25515@clipper.ens.fr>

It looks like someone made an error on the wiki and killed the end of
the TentativeNumpyTutorial. I do not know how to revert the change,
could someone less clumsy then me do it.

Cheers,

Ga?l


From robert.kern at gmail.com  Sun Oct 29 18:55:44 2006
From: robert.kern at gmail.com (Robert Kern)
Date: Sun, 29 Oct 2006 17:55:44 -0600
Subject: [SciPy-user] Error on the wiki
In-Reply-To: <20061029233953.GC25515@clipper.ens.fr>
References: <20061029233953.GC25515@clipper.ens.fr>
Message-ID: <45453F80.5010605@gmail.com>

Gael Varoquaux wrote:
> It looks like someone made an error on the wiki and killed the end of
> the TentativeNumpyTutorial. I do not know how to revert the change,
> could someone less clumsy then me do it.

I've reverted back to revision 42. The trick is to click on the "info" icon (the 
white "i" on a blue square). You will see a table with the whole revision 
history. You can view the diffs between revisions by choosing revisions in the 
"Diff" column (left radio button is the "from" revision, right is "to") and 
clicking on the "Diff" button. You can see that revisions 43 and 44 deleted a 
whole bunch of text by accident. So, to revert, I went to the revision 42 row 
and click on the "revert" link in the rightmost column.

-- 
Robert Kern

"I have come to believe that the whole world is an enigma, a harmless enigma
  that is made terrible by our own mad attempt to interpret it as though it had
  an underlying truth."
   -- Umberto Eco


From dahl.joachim at gmail.com  Mon Oct 30 01:48:49 2006
From: dahl.joachim at gmail.com (Joachim Dahl)
Date: Mon, 30 Oct 2006 07:48:49 +0100
Subject: [SciPy-user] Nonlinear optimization with linear constraints
In-Reply-To: <45453386.6020002@msg.ucsf.edu>
References: <5143a98b0610290244t3a9dd406ma9dd64cf3d06a35e@mail.gmail.com>
	<45453386.6020002@msg.ucsf.edu>
Message-ID: <47347f490610292248p77e39679m1c98c41ef1ebcdda@mail.gmail.com>

On 10/30/06, Sebastian Haase <haase at msg.ucsf.edu> wrote:
>
> Sunghyun Cho wrote:
> > Hello, Scipy users.
> >
> > I'm currently looking for a way to optimize nonlinear problem with
> > linear constraints.
> > I read documents of scipy, but I found there are just optimization
> > methods with bound constraints which just use min and max values.
> > If you know any packages related to this problem, please let me know.
> > I'll deeply appreciate your reply.
> >


If your cost-function is convex you could try CVXOPT, which is a general
package for solving convex optimization problems;  it works quite well with
SciPy via the array interface protocol.

- Joachim

> THANK YOU!
> >
> > --
> > Sunghyun Cho
> > sodomau at postech.ac.kr <mailto:sodomau at postech.ac.kr>
> > http://sodomau.plus.or.kr
> > Computer Graphics Lab.
> > POSTECH
> >
> >
>
> Would the cobyla function help you ? It is in scipy.optimize.
> Look also in the archive of this list for it.
>
> -Sebastian
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
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From hgk at et.uni-magdeburg.de  Mon Oct 30 03:03:04 2006
From: hgk at et.uni-magdeburg.de (Dr. Hans Georg Krauthaeuser)
Date: Mon, 30 Oct 2006 09:03:04 +0100
Subject: [SciPy-user] Combinatoric/Statistics: length of longest sequence
In-Reply-To: <ce557a360610291514x1ed2525eydbf313a99ee59c12@mail.gmail.com>
References: <ei2ah7$5bd$1@sea.gmane.org>
	<ce557a360610291514x1ed2525eydbf313a99ee59c12@mail.gmail.com>
Message-ID: <ei4bjo$8la$1@sea.gmane.org>

A. M. Archibald wrote:
> On 29/10/06, Dr. Hans Georg Krauthaeuser <hgk at et.uni-magdeburg.de> wrote:
>> Dear All,
>>
>> I have a 2d-array A of p-values (coming from pairwise statistical tests
>> of N datasets). N is typically in the range of 100-1000. Now, given a
>> certain threshold, I want to find the longest subset S of range(N), so
>> that A[i][j]>threshold for all i,j from S.
> 
> It's not quite clear, here, whether you want the longest *contiguous*
> subset ({2,3,4,5,6}) or the largest arbitrary subset ({2,17,21,22}).

Oh well, sorry for being not precise enough. I'm searching for the
largest arbitrary subset.

> 
>> Unfortunately, the array A is not 'sparse', i.e. a lot of pairs (i,j)
>> will fulfill A[i][j]>threshold (typically ~50% of the elements).
>>
>> All I can think of are brute force algorithms that probably will run
>> forever because of the large number of possible combinations to check.
> 
> If you want the longest contiguous subset, for N=1000 that's only of
> order a million operations for a brute-force algorithm (for each
> starting element, see how long the run is), so unless you want to do
> it lots of times I wouldn't worry. If you do, some Numeric cleverness
> might allow you to move some of the heavy lifting to C, though for
> simple indexing calculations pure python can be plenty fast.
> 
> If you want the largest arbitrary subset, that's going to be
> expensive, and it bears an unnerving resemblance to the subset-sum
> problem. I can imagine an expensive  recursive algorithm that would do
> it without too much pain, though the space to search is so huge you're
> liable to be taking a very long time. However you go about it, you may
> be better off using python's set datatype (for element i, form the set
> of all elements j for which A[i][j]>threshold).
> 
> I've attached a demonstration program that solves both interpretations
> of your problem; the difficult one appears to bog down seriously
> around N=200 (with p=0.5) but the easy one runs into memory problems
> before taking too long.
> 
> A. M. Archibald
> 
> 

Thanks a lot for your hints and for the example code. I will check what
I can do with it. I'll be back when I have some results.


Regards
Hans Georg



From peridot.faceted at gmail.com  Mon Oct 30 04:04:59 2006
From: peridot.faceted at gmail.com (A. M. Archibald)
Date: Mon, 30 Oct 2006 04:04:59 -0500
Subject: [SciPy-user] Combinatoric/Statistics: length of longest sequence
In-Reply-To: <ei4bjo$8la$1@sea.gmane.org>
References: <ei2ah7$5bd$1@sea.gmane.org>
	<ce557a360610291514x1ed2525eydbf313a99ee59c12@mail.gmail.com>
	<ei4bjo$8la$1@sea.gmane.org>
Message-ID: <ce557a360610300104l2f2e1091x6a4c56bf0aa4f0e5@mail.gmail.com>

On 30/10/06, Dr. Hans Georg Krauthaeuser <hgk at et.uni-magdeburg.de> wrote:
> A. M. Archibald wrote:
> > On 29/10/06, Dr. Hans Georg Krauthaeuser <hgk at et.uni-magdeburg.de> wrote:
> >> Dear All,
> >>
> >> I have a 2d-array A of p-values (coming from pairwise statistical tests
> >> of N datasets). N is typically in the range of 100-1000. Now, given a
> >> certain threshold, I want to find the longest subset S of range(N), so
> >> that A[i][j]>threshold for all i,j from S.
> >
> > It's not quite clear, here, whether you want the longest *contiguous*
> > subset ({2,3,4,5,6}) or the largest arbitrary subset ({2,17,21,22}).
>
> Oh well, sorry for being not precise enough. I'm searching for the
> largest arbitrary subset.

Ah, then you are definitely looking at an NP-complete problem:
http://en.wikipedia.org/wiki/Clique_problem

They suggest a heuristic, but I don't know how effective it is likely
to be; it probably depends on the structure of your graph (matrix).
It's possible, though unlikely, that a more continuous version of your
problem (one that took into account the actual values of A[i][j], for
example) would be more tractable - in fact, the eigenvector
corresponding to the maximal eigenvalue of A should be a node
weighting which has larger values for the "more connected" nodes (in a
particular sense).

> Thanks a lot for your hints and for the example code. I will check what
> I can do with it. I'll be back when I have some results.

It's just a quick hack, and can probably be significantly improved,
but good luck.

A. M. Archibald


From nwagner at iam.uni-stuttgart.de  Mon Oct 30 07:20:11 2006
From: nwagner at iam.uni-stuttgart.de (Nils Wagner)
Date: Mon, 30 Oct 2006 13:20:11 +0100
Subject: [SciPy-user] CVXOPT
In-Reply-To: <47347f490610292248p77e39679m1c98c41ef1ebcdda@mail.gmail.com>
References: <5143a98b0610290244t3a9dd406ma9dd64cf3d06a35e@mail.gmail.com>	<45453386.6020002@msg.ucsf.edu>
	<47347f490610292248p77e39679m1c98c41ef1ebcdda@mail.gmail.com>
Message-ID: <4545EDFB.1050900@iam.uni-stuttgart.de>

Joachim Dahl wrote:
>
>
> On 10/30/06, *Sebastian Haase* <haase at msg.ucsf.edu
> <mailto:haase at msg.ucsf.edu>> wrote:
>
>     Sunghyun Cho wrote:
>     > Hello, Scipy users.
>     >
>     > I'm currently looking for a way to optimize nonlinear problem with
>     > linear constraints.
>     > I read documents of scipy, but I found there are just optimization
>     > methods with bound constraints which just use min and max values.
>     > If you know any packages related to this problem, please let me
>     know.
>     > I'll deeply appreciate your reply.
>     >
>
>
> If your cost-function is convex you could try CVXOPT, which is a general
> package for solving convex optimization problems;  it works quite well
> with
> SciPy via the array interface protocol.
>
> - Joachim
>
>     > THANK YOU!
>     >
>     > --
>     > Sunghyun Cho
>     > sodomau at postech.ac.kr <mailto:sodomau at postech.ac.kr>
>     <mailto:sodomau at postech.ac.kr <mailto:sodomau at postech.ac.kr>>
>     > http://sodomau.plus.or.kr
>     > Computer Graphics Lab.
>     > POSTECH
>     >
>     >
>
>     Would the cobyla function help you ? It is in scipy.optimize.
>     Look also in the archive of this list for it.
>
>     -Sebastian
>     _______________________________________________
>     SciPy-user mailing list
>     SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
>     http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
> ------------------------------------------------------------------------
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   


I have installed CVXOPT. Where can I get a pdf version of the
documentation ?
http://www.ee.ucla.edu/~vandenbe/cvxopt/doc/cvxopt.html

A make in cvxopt-0.8/doc failed

mkhowto: Command not found

Nils



From fccoelho at gmail.com  Mon Oct 30 07:27:35 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Mon, 30 Oct 2006 09:27:35 -0300
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
Message-ID: <d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>

Thank you for this post and many thanks to Fernando Perez, for the awesome
tool that Ipython1 is becomming!!! I am beginning to use it today!!

Fl?vio

On 10/29/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
>
> > For object oriented parallel programming in Python on a single machine I
> can use techniques such as Bulk Synchronous Parallelism (BSP) or Message
> Passing Interface (MPI). There are mentioned some modules and packages for
> Python on
> > http://www.scipy.org/Topical_Software
> > Article: Parallel and distributed programming.
> > After reading prerequisites and limitations I thing that the following
> ones could be good for me:
> > PyMPI
> > Pypar
> > MPI for Python
>
> I think mpi4py is the best option.  It is a very nice implementation
> and the developer is working really hard to make it a great package.
> Also, I don't think pympi and pypar are being developed actively
> anymore.
>
> Another thing you might check out is IPython's parallel computing
> facilities that let you use mpi4py (and other mpi bindings)
> interactively:
>
> http://ipython.scipy.org/moin/Parallel_Computing
>
> I have never used BPS, but am familiar with the model.  Can probably
> get it working interactively with IPython as well.
>
> Cheers,
>
> Brian
>
> > But I can't distinguish which one brings fewer limitations, is efficient
> in application and will develop in future.
> > My favorite is BSP, but I can't find a package for present SciPy and
> NumPy.
> >
> > Could anybody give me a recommendation, which way I should go.
> >
> > Thanks.
> > Fie Pye
> >
> >
> >
> >
> > ---------------------------------------
> > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> >
> >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismark
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From Giovanni.Samaey at cs.kuleuven.be  Mon Oct 30 09:03:26 2006
From: Giovanni.Samaey at cs.kuleuven.be (Giovanni Samaey)
Date: Mon, 30 Oct 2006 15:03:26 +0100
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
Message-ID: <4546062E.1020501@cs.kuleuven.ac.be>

Hi,

I also looked at the entry on Ipython1 and it looks really promising.
Did I understand correctly that Ipython1 is able to run parallel python
code, regardless of which "MPI for python" package one eventually uses?

Giovanni

Flavio Coelho wrote:
> Thank you for this post and many thanks to Fernando Perez, for the 
> awesome tool that Ipython1 is becomming!!! I am beginning to use it 
> today!!
>
> Fl?vio
>
> On 10/29/06, * Brian Granger* <ellisonbg.net at gmail.com 
> <mailto:ellisonbg.net at gmail.com>> wrote:
>
>     > For object oriented parallel programming in Python on a single
>     machine I can use techniques such as Bulk Synchronous Parallelism
>     (BSP) or Message Passing Interface (MPI). There are mentioned some
>     modules and packages for Python on
>     > http://www.scipy.org/Topical_Software
>     > Article: Parallel and distributed programming.
>     > After reading prerequisites and limitations I thing that the
>     following ones could be good for me:
>     > PyMPI
>     > Pypar
>     > MPI for Python
>
>     I think mpi4py is the best option.  It is a very nice implementation
>     and the developer is working really hard to make it a great package.
>     Also, I don't think pympi and pypar are being developed actively
>     anymore.
>
>     Another thing you might check out is IPython's parallel computing
>     facilities that let you use mpi4py (and other mpi bindings)
>     interactively:
>
>     http://ipython.scipy.org/moin/Parallel_Computing
>
>     I have never used BPS, but am familiar with the model.  Can probably
>     get it working interactively with IPython as well.
>
>     Cheers,
>
>     Brian
>
>     > But I can't distinguish which one brings fewer limitations, is
>     efficient in application and will develop in future.
>     > My favorite is BSP, but I can't find a package for present SciPy
>     and NumPy.
>     >
>     > Could anybody give me a recommendation, which way I should go.
>     >
>     > Thanks.
>     > Fie Pye
>     >
>     >
>     >
>     >
>     > ---------------------------------------
>     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
>     <http://www.neuservis.cz>
>     >
>     >
>     > _______________________________________________
>     > SciPy-user mailing list
>     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
>     > http://projects.scipy.org/mailman/listinfo/scipy-user
>     <http://projects.scipy.org/mailman/listinfo/scipy-user>
>     >
>     _______________________________________________
>     SciPy-user mailing list
>     SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
>     http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
>
>
> -- 
> Fl?vio Code?o Coelho
> registered Linux user # 386432
> ---------------------------
> "Laws are like sausages. It's better not to see them being made."
> Otto von Bismark
> ------------------------------------------------------------------------
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>   


From ellisonbg.net at gmail.com  Mon Oct 30 11:01:53 2006
From: ellisonbg.net at gmail.com (Brian Granger)
Date: Mon, 30 Oct 2006 09:01:53 -0700
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <4546062E.1020501@cs.kuleuven.ac.be>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<4546062E.1020501@cs.kuleuven.ac.be>
Message-ID: <6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>

> I also looked at the entry on Ipython1 and it looks really promising.
> Did I understand correctly that Ipython1 is able to run parallel python
> code, regardless of which "MPI for python" package one eventually uses?

In principle yes.  The IPython engines have a configuration option
that you use to import the mpi bindings of your choice.  But, to work
properly, the import statement must cause MPI_Init() to be called.  If
the bindings you are using don't do that, it should b easy to write a
wrapper module that imports and also calls MPI_Init().  Also, some of
this depends on what MPI implementation you are using.  The more
moderns ones (like openmpi) are really nice and pretty forgiving.  The
older ones, though, sometimes require that Python itself (not your
script) call MPI_Init().  This is also very easy to work around.  The
bottom line is that we can help you get it to work with whatever mpi
binding and implementation you want.

Withh that said, I highly do highly recommend mpi4py and openmpi - we
use these regularly with ipython and it all works well.

Brian


> Giovanni
>
> Flavio Coelho wrote:
> > Thank you for this post and many thanks to Fernando Perez, for the
> > awesome tool that Ipython1 is becomming!!! I am beginning to use it
> > today!!
> >
> > Fl?vio
> >
> > On 10/29/06, * Brian Granger* <ellisonbg.net at gmail.com
> > <mailto:ellisonbg.net at gmail.com>> wrote:
> >
> >     > For object oriented parallel programming in Python on a single
> >     machine I can use techniques such as Bulk Synchronous Parallelism
> >     (BSP) or Message Passing Interface (MPI). There are mentioned some
> >     modules and packages for Python on
> >     > http://www.scipy.org/Topical_Software
> >     > Article: Parallel and distributed programming.
> >     > After reading prerequisites and limitations I thing that the
> >     following ones could be good for me:
> >     > PyMPI
> >     > Pypar
> >     > MPI for Python
> >
> >     I think mpi4py is the best option.  It is a very nice implementation
> >     and the developer is working really hard to make it a great package.
> >     Also, I don't think pympi and pypar are being developed actively
> >     anymore.
> >
> >     Another thing you might check out is IPython's parallel computing
> >     facilities that let you use mpi4py (and other mpi bindings)
> >     interactively:
> >
> >     http://ipython.scipy.org/moin/Parallel_Computing
> >
> >     I have never used BPS, but am familiar with the model.  Can probably
> >     get it working interactively with IPython as well.
> >
> >     Cheers,
> >
> >     Brian
> >
> >     > But I can't distinguish which one brings fewer limitations, is
> >     efficient in application and will develop in future.
> >     > My favorite is BSP, but I can't find a package for present SciPy
> >     and NumPy.
> >     >
> >     > Could anybody give me a recommendation, which way I should go.
> >     >
> >     > Thanks.
> >     > Fie Pye
> >     >
> >     >
> >     >
> >     >
> >     > ---------------------------------------
> >     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> >     <http://www.neuservis.cz>
> >     >
> >     >
> >     > _______________________________________________
> >     > SciPy-user mailing list
> >     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> >     > http://projects.scipy.org/mailman/listinfo/scipy-user
> >     <http://projects.scipy.org/mailman/listinfo/scipy-user>
> >     >
> >     _______________________________________________
> >     SciPy-user mailing list
> >     SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> >     http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> >
> >
> >
> > --
> > Fl?vio Code?o Coelho
> > registered Linux user # 386432
> > ---------------------------
> > "Laws are like sausages. It's better not to see them being made."
> > Otto von Bismark
> > ------------------------------------------------------------------------
> >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>

From fccoelho at gmail.com  Mon Oct 30 12:53:54 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Mon, 30 Oct 2006 15:53:54 -0200
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<4546062E.1020501@cs.kuleuven.ac.be>
	<6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>
Message-ID: <d9af7a880610300953s741be2b0g1b82ed544e594d3d@mail.gmail.com>

Hi Brian,

Can Ipython1 take advantage of multiple core cpus or SMP machines in the
same way it does for a networked cluster? It would be nice to have that
since quad-core cpu are arriving on the market and SMP machines are pretty
common already.

Thanks!

Fl?vio

On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
>
> > I also looked at the entry on Ipython1 and it looks really promising.
> > Did I understand correctly that Ipython1 is able to run parallel python
> > code, regardless of which "MPI for python" package one eventually uses?
>
> In principle yes.  The IPython engines have a configuration option
> that you use to import the mpi bindings of your choice.  But, to work
> properly, the import statement must cause MPI_Init() to be called.  If
> the bindings you are using don't do that, it should b easy to write a
> wrapper module that imports and also calls MPI_Init().  Also, some of
> this depends on what MPI implementation you are using.  The more
> moderns ones (like openmpi) are really nice and pretty forgiving.  The
> older ones, though, sometimes require that Python itself (not your
> script) call MPI_Init().  This is also very easy to work around.  The
> bottom line is that we can help you get it to work with whatever mpi
> binding and implementation you want.
>
> Withh that said, I highly do highly recommend mpi4py and openmpi - we
> use these regularly with ipython and it all works well.
>
> Brian
>
>
> > Giovanni
> >
> > Flavio Coelho wrote:
> > > Thank you for this post and many thanks to Fernando Perez, for the
> > > awesome tool that Ipython1 is becomming!!! I am beginning to use it
> > > today!!
> > >
> > > Fl?vio
> > >
> > > On 10/29/06, * Brian Granger* <ellisonbg.net at gmail.com
> > > <mailto:ellisonbg.net at gmail.com>> wrote:
> > >
> > >     > For object oriented parallel programming in Python on a single
> > >     machine I can use techniques such as Bulk Synchronous Parallelism
> > >     (BSP) or Message Passing Interface (MPI). There are mentioned some
> > >     modules and packages for Python on
> > >     > http://www.scipy.org/Topical_Software
> > >     > Article: Parallel and distributed programming.
> > >     > After reading prerequisites and limitations I thing that the
> > >     following ones could be good for me:
> > >     > PyMPI
> > >     > Pypar
> > >     > MPI for Python
> > >
> > >     I think mpi4py is the best option.  It is a very nice
> implementation
> > >     and the developer is working really hard to make it a great
> package.
> > >     Also, I don't think pympi and pypar are being developed actively
> > >     anymore.
> > >
> > >     Another thing you might check out is IPython's parallel computing
> > >     facilities that let you use mpi4py (and other mpi bindings)
> > >     interactively:
> > >
> > >     http://ipython.scipy.org/moin/Parallel_Computing
> > >
> > >     I have never used BPS, but am familiar with the model.  Can
> probably
> > >     get it working interactively with IPython as well.
> > >
> > >     Cheers,
> > >
> > >     Brian
> > >
> > >     > But I can't distinguish which one brings fewer limitations, is
> > >     efficient in application and will develop in future.
> > >     > My favorite is BSP, but I can't find a package for present SciPy
> > >     and NumPy.
> > >     >
> > >     > Could anybody give me a recommendation, which way I should go.
> > >     >
> > >     > Thanks.
> > >     > Fie Pye
> > >     >
> > >     >
> > >     >
> > >     >
> > >     > ---------------------------------------
> > >     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> > >     <http://www.neuservis.cz>
> > >     >
> > >     >
> > >     > _______________________________________________
> > >     > SciPy-user mailing list
> > >     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> > >     > http://projects.scipy.org/mailman/listinfo/scipy-user
> > >     <http://projects.scipy.org/mailman/listinfo/scipy-user>
> > >     >
> > >     _______________________________________________
> > >     SciPy-user mailing list
> > >     SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> > >     http://projects.scipy.org/mailman/listinfo/scipy-user
> > >
> > >
> > >
> > >
> > > --
> > > Fl?vio Code?o Coelho
> > > registered Linux user # 386432
> > > ---------------------------
> > > "Laws are like sausages. It's better not to see them being made."
> > > Otto von Bismark
> > >
> ------------------------------------------------------------------------
> > >
> > > _______________________________________________
> > > SciPy-user mailing list
> > > SciPy-user at scipy.org
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismark
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From ellisonbg.net at gmail.com  Mon Oct 30 14:18:34 2006
From: ellisonbg.net at gmail.com (Brian Granger)
Date: Mon, 30 Oct 2006 12:18:34 -0700
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <d9af7a880610300953s741be2b0g1b82ed544e594d3d@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<4546062E.1020501@cs.kuleuven.ac.be>
	<6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>
	<d9af7a880610300953s741be2b0g1b82ed544e594d3d@mail.gmail.com>
Message-ID: <6ce0ac130610301118ncd8d3al32a4c68f6db3801@mail.gmail.com>

> Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> same way it does for a networked cluster? It would be nice to have that
> since quad-core cpu are arriving on the market and SMP machines are pretty
> common already.

This was one of the major usage cases we have had in mind.  So yes.
Some details though:

In IPython1 computations are done by a separate process that we are
calling the IPython engine.  Multiple IPython engines can be run on
multiple systems (distributed memory), a single (multi CPU and/or
multi-core) system or a combination of the two.  I have run two
IPython engines on my dual core MacBook and seen 2x speedup with
simple python scripts.  I wasn't using MPI, but with MPi you should
see a similar behavior as long as your algorithm scales linearly to 2
instances processes.

I can't wait to use IPython1 with 4/8/16 cores on my workstation :)

Please let us know if you have questions or problems.

Brian

On 10/30/06, Flavio Coelho <fccoelho at gmail.com> wrote:
> Hi Brian,
>
> Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> same way it does for a networked cluster? It would be nice to have that
> since quad-core cpu are arriving on the market and SMP machines are pretty
> common already.
>
> Thanks!
>
> Fl?vio
>
>
> On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
> > > I also looked at the entry on Ipython1 and it looks really promising.
> > > Did I understand correctly that Ipython1 is able to run parallel python
> > > code, regardless of which "MPI for python" package one eventually uses?
> >
> > In principle yes.  The IPython engines have a configuration option
> > that you use to import the mpi bindings of your choice.  But, to work
> > properly, the import statement must cause MPI_Init() to be called.  If
> > the bindings you are using don't do that, it should b easy to write a
> > wrapper module that imports and also calls MPI_Init().  Also, some of
> > this depends on what MPI implementation you are using.  The more
> > moderns ones (like openmpi) are really nice and pretty forgiving.  The
> > older ones, though, sometimes require that Python itself (not your
> > script) call MPI_Init().  This is also very easy to work around.  The
> > bottom line is that we can help you get it to work with whatever mpi
> > binding and implementation you want.
> >
> > Withh that said, I highly do highly recommend mpi4py and openmpi - we
> > use these regularly with ipython and it all works well.
> >
> > Brian
> >
> >
> > > Giovanni
> > >
> > > Flavio Coelho wrote:
> > > > Thank you for this post and many thanks to Fernando Perez, for the
> > > > awesome tool that Ipython1 is becomming!!! I am beginning to use it
> > > > today!!
> > > >
> > > > Fl?vio
> > > >
> > > > On 10/29/06, * Brian Granger* < ellisonbg.net at gmail.com
> > > > <mailto:ellisonbg.net at gmail.com>> wrote:
> > > >
> > > >     > For object oriented parallel programming in Python on a single
> > > >     machine I can use techniques such as Bulk Synchronous Parallelism
> > > >     (BSP) or Message Passing Interface (MPI). There are mentioned some
> > > >     modules and packages for Python on
> > > >     > http://www.scipy.org/Topical_Software
> > > >     > Article: Parallel and distributed programming.
> > > >     > After reading prerequisites and limitations I thing that the
> > > >     following ones could be good for me:
> > > >     > PyMPI
> > > >     > Pypar
> > > >     > MPI for Python
> > > >
> > > >     I think mpi4py is the best option.  It is a very nice
> implementation
> > > >     and the developer is working really hard to make it a great
> package.
> > > >     Also, I don't think pympi and pypar are being developed actively
> > > >     anymore.
> > > >
> > > >     Another thing you might check out is IPython's parallel computing
> > > >     facilities that let you use mpi4py (and other mpi bindings)
> > > >     interactively:
> > > >
> > > >     http://ipython.scipy.org/moin/Parallel_Computing
> > > >
> > > >     I have never used BPS, but am familiar with the model.  Can
> probably
> > > >     get it working interactively with IPython as well.
> > > >
> > > >     Cheers,
> > > >
> > > >     Brian
> > > >
> > > >     > But I can't distinguish which one brings fewer limitations, is
> > > >     efficient in application and will develop in future.
> > > >     > My favorite is BSP, but I can't find a package for present SciPy
> > > >     and NumPy.
> > > >     >
> > > >     > Could anybody give me a recommendation, which way I should go.
> > > >     >
> > > >     > Thanks.
> > > >     > Fie Pye
> > > >     >
> > > >     >
> > > >     >
> > > >     >
> > > >     > ---------------------------------------
> > > >     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> > > >     <http://www.neuservis.cz>
> > > >     >
> > > >     >
> > > >     > _______________________________________________
> > > >     > SciPy-user mailing list
> > > >     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> > > >     >
> http://projects.scipy.org/mailman/listinfo/scipy-user
> > > >
> <http://projects.scipy.org/mailman/listinfo/scipy-user >
> > > >     >
> > > >     _______________________________________________
> > > >     SciPy-user mailing list
> > > >     SciPy-user at scipy.org <mailto: SciPy-user at scipy.org>
> > > >
> http://projects.scipy.org/mailman/listinfo/scipy-user
> > > >
> > > >
> > > >
> > > >
> > > > --
> > > > Fl?vio Code?o Coelho
> > > > registered Linux user # 386432
> > > > ---------------------------
> > > > "Laws are like sausages. It's better not to see them being made."
> > > > Otto von Bismark
> > > >
> ------------------------------------------------------------------------
> > > >
> > > > _______________________________________________
> > > > SciPy-user mailing list
> > > > SciPy-user at scipy.org
> > > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > >
> > > _______________________________________________
> > > SciPy-user mailing list
> > > SciPy-user at scipy.org
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
>
>
>
> --
>
> Fl?vio Code?o Coelho
> registered Linux user # 386432
> ---------------------------
> "Laws are like sausages. It's better not to see them being made."
> Otto von Bismark
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
>

From fperez.net at gmail.com  Mon Oct 30 14:25:44 2006
From: fperez.net at gmail.com (Fernando Perez)
Date: Mon, 30 Oct 2006 12:25:44 -0700
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
Message-ID: <db6b5ecc0610301125g4d8b36d3t98ba57f7106fcead@mail.gmail.com>

On 10/30/06, Flavio Coelho <fccoelho at gmail.com> wrote:
> Thank you for this post and many thanks to Fernando Perez, for the awesome
> tool that Ipython1 is becomming!!! I am beginning to use it today!!

As much as I like to see my name attached to such statements, it's
important to acknowledge that virtually all the credit for this effort
should go to Brian Granger and not to me :)  Without his interest,
boundless energy, and his involvement of Benjamin Ragan-Kelley (who
also deserves much credit for doing lots of the nasty Twisted coding
over this summer), we wouldn't be anywhere near this.

But thanks anyway ;)

Cheers,

f


From icy.flame.gm at gmail.com  Mon Oct 30 14:31:19 2006
From: icy.flame.gm at gmail.com (iCy-fLaME)
Date: Mon, 30 Oct 2006 19:31:19 +0000
Subject: [SciPy-user] No longer able to load scipy
Message-ID: <bfb379e10610301131j4a4df6c5tcc59869553aedf31@mail.gmail.com>

Not sure since when my scipy gets broken, but it worked fine at least
a week ago, so I removed both numpy and scipy, and download the
lastest (numpy-1.0.tar.gz & scipy-0.5.1.tar.gz) then recompile from
source.

No complains while compiling and installing both numpy and scipy, but
still unable to import scipy, while numpy works fine.

I am using:
python-2.4.3-18.fc6


>>> import scipy
Traceback (most recent call last):
  File "<stdin>", line 1, in ?
  File "/usr/lib/python2.4/site-packages/scipy/__init__.py", line 18, in ?
    import pkg_resources as _pr # activate namespace packages
(manipulates __path__)
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 2470, in ?
    working_set = WorkingSet()
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 343,
in __init__
    self.add_entry(entry)
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 358,
in add_entry
    for dist in find_distributions(entry, True):
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 1565,
in find_on_path
    path_item = _normalize_cached(path_item)
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 1712,
in _normalize_cached
    _cache[filename] = result = normalize_path(filename)
  File "/usr/lib/python2.4/site-packages/pkg_resources.py", line 1706,
in normalize_path
    return os.path.normcase(os.path.realpath(filename))
  File "/usr/lib/python2.4/posixpath.py", line 431, in realpath
    return abspath(filename)
  File "/usr/lib/python2.4/posixpath.py", line 404, in abspath
    path = join(os.getcwd(), path)
OSError: [Errno 2] No such file or directory


Any thoughts?


From fccoelho at gmail.com  Mon Oct 30 14:32:16 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Mon, 30 Oct 2006 17:32:16 -0200
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <db6b5ecc0610301125g4d8b36d3t98ba57f7106fcead@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<db6b5ecc0610301125g4d8b36d3t98ba57f7106fcead@mail.gmail.com>
Message-ID: <d9af7a880610301132s25812563u2fc4c6f52978f8b7@mail.gmail.com>

Ooops,

Sorry for that mistake! So I redirect my thanks to Brian !! Thanks Brian!

Fl?vio

On 10/30/06, Fernando Perez <fperez.net at gmail.com> wrote:
>
> On 10/30/06, Flavio Coelho <fccoelho at gmail.com> wrote:
> > Thank you for this post and many thanks to Fernando Perez, for the
> awesome
> > tool that Ipython1 is becomming!!! I am beginning to use it today!!
>
> As much as I like to see my name attached to such statements, it's
> important to acknowledge that virtually all the credit for this effort
> should go to Brian Granger and not to me :)  Without his interest,
> boundless energy, and his involvement of Benjamin Ragan-Kelley (who
> also deserves much credit for doing lots of the nasty Twisted coding
> over this summer), we wouldn't be anywhere near this.
>
> But thanks anyway ;)
>
> Cheers,
>
> f
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismark
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From fccoelho at gmail.com  Mon Oct 30 14:47:10 2006
From: fccoelho at gmail.com (Flavio Coelho)
Date: Mon, 30 Oct 2006 17:47:10 -0200
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <6ce0ac130610301118ncd8d3al32a4c68f6db3801@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<4546062E.1020501@cs.kuleuven.ac.be>
	<6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>
	<d9af7a880610300953s741be2b0g1b82ed544e594d3d@mail.gmail.com>
	<6ce0ac130610301118ncd8d3al32a4c68f6db3801@mail.gmail.com>
Message-ID: <d9af7a880610301147y414174bqef3edaa7b5812cc1@mail.gmail.com>

Thanks Brian,

I am playing with it right now!  I am planning to run it soon on multiple
machines with multiple CPUs. Will I have to install Ipython1 on every node
or Will the controller host spawn the processes across the net? In the
README you seem to be starting the engines locally on each host....

but before I get Ahead of myself , I am getting the following error when I
try to start an engine on my localhost:
fccoelho at sombra ~/Downloads/Twisted $ ipengine &
[2] 32018
fccoelho at sombra ~/Downloads/Twisted $ 2006/10/30 16:44 -0200 [-] Log opened.
2006/10/30 16:44 -0200 [-] Starting factory <
ipython1.kernel.enginevanilla.VanillaEngineClientFactoryFromEngineServiceobject
at 0xb6706eac>
2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0,127.0.0.1] Unhandled
Error
        Traceback (most recent call last):
          File "/usr/lib/python2.4/site-packages/twisted/python/log.py",
line 48, in callWithLogger
            return callWithContext({"system": lp}, func, *args, **kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/log.py",
line 33, in callWithContext
            return context.call({ILogContext: newCtx}, func, *args, **kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/context.py",
line 59, in callWithContext
            return self.currentContext().callWithContext(ctx, func, *args,
**kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/context.py",
line 37, in callWithContext
            return func(*args,**kw)
        --- <exception caught here> ---
          File
"/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py", line
139, in _doReadOrWrite
            why = getattr(selectable, method)()
          File "/usr/lib/python2.4/site-packages/twisted/internet/tcp.py",
line 362, in doRead
            return self.protocol.dataReceived(data)
          File
"/usr/lib/python2.4/site-packages/twisted/protocols/basic.py", line 99, in
dataReceived
            self.doData()
          File
"/usr/lib/python2.4/site-packages/twisted/protocols/basic.py", line 62, in
doData
            self.stringReceived(self.__buffer)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py", line
557, in stringReceived
            self.nextHandler(msg)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py", line
573, in dispatch
            f(args)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py", line
706, in handle_REGISTER
            qe = engineservice.QueuedEngine(self, keepUpToDate=True)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/engineservice.py", line
342, in __init__
            self.registerMethods()
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/engineservice.py", line
345, in registerMethods
            zi.alsoProvides(self, *self.engine.__provides__)
        exceptions.AttributeError: 'module' object has no attribute
'alsoProvides'

2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0,127.0.0.1]
unregistered engine None
2006/10/30 16:44 -0200 [VanillaEngineClientProtocol,client] Stopping factory
<ipython1.kernel.enginevanilla.VanillaEngineClientFactoryFromEngineServiceobject
at 0xb6706eac>
2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0,127.0.0.1] Unhandled
Error
        Traceback (most recent call last):
          File "/usr/bin/ipcontroller", line 51, in main
            reactor.run()
          File
"/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py", line 218,
in run
            self.mainLoop()
          File
"/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py", line 229,
in mainLoop
            self.doIteration(t)
          File
"/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py", line
133, in doSelect
            _logrun(selectable, _drdw, selectable, method, dict)
        --- <exception caught here> ---
          File "/usr/lib/python2.4/site-packages/twisted/python/log.py",
line 48, in callWithLogger
            return callWithContext({"system": lp}, func, *args, **kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/log.py",
line 33, in callWithContext
            return context.call({ILogContext: newCtx}, func, *args, **kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/context.py",
line 59, in callWithContext
            return self.currentContext().callWithContext(ctx, func, *args,
**kw)
          File "/usr/lib/python2.4/site-packages/twisted/python/context.py",
line 37, in callWithContext
            return func(*args,**kw)
          File
"/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py", line
149, in _doReadOrWrite
            self._disconnectSelectable(selectable, why, method=="doRead")
          File
"/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py", line 256,
in _disconnectSelectable
            selectable.connectionLost(failure.Failure(why))
          File "/usr/lib/python2.4/site-packages/twisted/internet/tcp.py",
line 416, in connectionLost
            protocol.connectionLost(reason)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py", line
538, in connectionLost
            self.factory.unregisterEngine(self.id)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py", line
1023, in unregisterEngine
            return self.service.unregisterEngine(id)
          File
"/usr/lib/python2.4/site-packages/ipython1/kernel/controllerservice.py",
line 300, in unregisterEngine
            del self.engines[id]
        exceptions.KeyError:


On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
>
> > Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> > same way it does for a networked cluster? It would be nice to have that
> > since quad-core cpu are arriving on the market and SMP machines are
> pretty
> > common already.
>
> This was one of the major usage cases we have had in mind.  So yes.
> Some details though:
>
> In IPython1 computations are done by a separate process that we are
> calling the IPython engine.  Multiple IPython engines can be run on
> multiple systems (distributed memory), a single (multi CPU and/or
> multi-core) system or a combination of the two.  I have run two
> IPython engines on my dual core MacBook and seen 2x speedup with
> simple python scripts.  I wasn't using MPI, but with MPi you should
> see a similar behavior as long as your algorithm scales linearly to 2
> instances processes.
>
> I can't wait to use IPython1 with 4/8/16 cores on my workstation :)
>
> Please let us know if you have questions or problems.
>
> Brian
>
> On 10/30/06, Flavio Coelho <fccoelho at gmail.com> wrote:
> > Hi Brian,
> >
> > Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> > same way it does for a networked cluster? It would be nice to have that
> > since quad-core cpu are arriving on the market and SMP machines are
> pretty
> > common already.
> >
> > Thanks!
> >
> > Fl?vio
> >
> >
> > On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
> > > > I also looked at the entry on Ipython1 and it looks really
> promising.
> > > > Did I understand correctly that Ipython1 is able to run parallel
> python
> > > > code, regardless of which "MPI for python" package one eventually
> uses?
> > >
> > > In principle yes.  The IPython engines have a configuration option
> > > that you use to import the mpi bindings of your choice.  But, to work
> > > properly, the import statement must cause MPI_Init() to be called.  If
> > > the bindings you are using don't do that, it should b easy to write a
> > > wrapper module that imports and also calls MPI_Init().  Also, some of
> > > this depends on what MPI implementation you are using.  The more
> > > moderns ones (like openmpi) are really nice and pretty forgiving.  The
> > > older ones, though, sometimes require that Python itself (not your
> > > script) call MPI_Init().  This is also very easy to work around.  The
> > > bottom line is that we can help you get it to work with whatever mpi
> > > binding and implementation you want.
> > >
> > > Withh that said, I highly do highly recommend mpi4py and openmpi - we
> > > use these regularly with ipython and it all works well.
> > >
> > > Brian
> > >
> > >
> > > > Giovanni
> > > >
> > > > Flavio Coelho wrote:
> > > > > Thank you for this post and many thanks to Fernando Perez, for the
> > > > > awesome tool that Ipython1 is becomming!!! I am beginning to use
> it
> > > > > today!!
> > > > >
> > > > > Fl?vio
> > > > >
> > > > > On 10/29/06, * Brian Granger* < ellisonbg.net at gmail.com
> > > > > <mailto:ellisonbg.net at gmail.com>> wrote:
> > > > >
> > > > >     > For object oriented parallel programming in Python on a
> single
> > > > >     machine I can use techniques such as Bulk Synchronous
> Parallelism
> > > > >     (BSP) or Message Passing Interface (MPI). There are mentioned
> some
> > > > >     modules and packages for Python on
> > > > >     > http://www.scipy.org/Topical_Software
> > > > >     > Article: Parallel and distributed programming.
> > > > >     > After reading prerequisites and limitations I thing that the
> > > > >     following ones could be good for me:
> > > > >     > PyMPI
> > > > >     > Pypar
> > > > >     > MPI for Python
> > > > >
> > > > >     I think mpi4py is the best option.  It is a very nice
> > implementation
> > > > >     and the developer is working really hard to make it a great
> > package.
> > > > >     Also, I don't think pympi and pypar are being developed
> actively
> > > > >     anymore.
> > > > >
> > > > >     Another thing you might check out is IPython's parallel
> computing
> > > > >     facilities that let you use mpi4py (and other mpi bindings)
> > > > >     interactively:
> > > > >
> > > > >     http://ipython.scipy.org/moin/Parallel_Computing
> > > > >
> > > > >     I have never used BPS, but am familiar with the model.  Can
> > probably
> > > > >     get it working interactively with IPython as well.
> > > > >
> > > > >     Cheers,
> > > > >
> > > > >     Brian
> > > > >
> > > > >     > But I can't distinguish which one brings fewer limitations,
> is
> > > > >     efficient in application and will develop in future.
> > > > >     > My favorite is BSP, but I can't find a package for present
> SciPy
> > > > >     and NumPy.
> > > > >     >
> > > > >     > Could anybody give me a recommendation, which way I should
> go.
> > > > >     >
> > > > >     > Thanks.
> > > > >     > Fie Pye
> > > > >     >
> > > > >     >
> > > > >     >
> > > > >     >
> > > > >     > ---------------------------------------
> > > > >     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> > > > >     <http://www.neuservis.cz>
> > > > >     >
> > > > >     >
> > > > >     > _______________________________________________
> > > > >     > SciPy-user mailing list
> > > > >     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> > > > >     >
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > >
> > <http://projects.scipy.org/mailman/listinfo/scipy-user >
> > > > >     >
> > > > >     _______________________________________________
> > > > >     SciPy-user mailing list
> > > > >     SciPy-user at scipy.org <mailto: SciPy-user at scipy.org>
> > > > >
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > >
> > > > >
> > > > >
> > > > >
> > > > > --
> > > > > Fl?vio Code?o Coelho
> > > > > registered Linux user # 386432
> > > > > ---------------------------
> > > > > "Laws are like sausages. It's better not to see them being made."
> > > > > Otto von Bismark
> > > > >
> > ------------------------------------------------------------------------
> > > > >
> > > > > _______________________________________________
> > > > > SciPy-user mailing list
> > > > > SciPy-user at scipy.org
> > > > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > >
> > > > _______________________________________________
> > > > SciPy-user mailing list
> > > > SciPy-user at scipy.org
> > > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > >
> > > _______________________________________________
> > > SciPy-user mailing list
> > > SciPy-user at scipy.org
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > >
> >
> >
> >
> > --
> >
> > Fl?vio Code?o Coelho
> > registered Linux user # 386432
> > ---------------------------
> > "Laws are like sausages. It's better not to see them being made."
> > Otto von Bismark
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> >
> >
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>



-- 
Fl?vio Code?o Coelho
registered Linux user # 386432
---------------------------
"Laws are like sausages. It's better not to see them being made."
Otto von Bismark
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From ahoover at eecs.berkeley.edu  Mon Oct 30 15:35:39 2006
From: ahoover at eecs.berkeley.edu (Aaron Hoover)
Date: Mon, 30 Oct 2006 12:35:39 -0800
Subject: [SciPy-user] how to filter outliers from an array
Message-ID: <27403C7D-BDFF-4475-8884-3E07C2DCABC3@eecs.berkeley.edu>

Hi All,

I'm doing feature matching between two images and as a result I get  
back an array of dx, dy shift values in pixel space for potential  
features that match between two images. I'd like to be able to throw  
out [dx, dy] vectors for which either value deviates significantly  
(more than one std deviation, perhaps) from the mean (I'm dealing  
with 2D rigid body translations only. I could do this by looping over  
the values and comparing them individually to the mean, but I'm  
wondering if there's a more compact (single line?) way of doing this  
perhaps using the scipy.stats package. Something along the lines of  
the filter built-in for lists, but that handles the higher  
dimensionality, would be nice.

Thanks,
Aaron




From coughlan at ski.org  Mon Oct 30 15:48:57 2006
From: coughlan at ski.org (James Coughlan)
Date: Mon, 30 Oct 2006 12:48:57 -0800
Subject: [SciPy-user] how to filter outliers from an array
In-Reply-To: <27403C7D-BDFF-4475-8884-3E07C2DCABC3@eecs.berkeley.edu>
References: <27403C7D-BDFF-4475-8884-3E07C2DCABC3@eecs.berkeley.edu>
Message-ID: <45466539.6030009@ski.org>

How about this?

####
dx=rand(5,5) #substitute whatever matrices you're actually
dy=rand(5,5) #using here

import scipy.stats
#compute mean and std for dx and dy:
mx=stats.mean(dx.flat)
my=stats.mean(dy.flat)
sx=stats.std(dx.flat)
sy=stats.std(dy.flat)

wx=abs(dx-mx)>sx
wy=abs(dy-my)>sy
print wx | wy # logical or
####

Here wx and wy are arrays whose elements are set to True if they lie 
more than 1 std. from mean. So wx | xy will flag those elements for 
which either the x or y components are outliers.

James



Aaron Hoover wrote:

>Hi All,
>
>I'm doing feature matching between two images and as a result I get  
>back an array of dx, dy shift values in pixel space for potential  
>features that match between two images. I'd like to be able to throw  
>out [dx, dy] vectors for which either value deviates significantly  
>(more than one std deviation, perhaps) from the mean (I'm dealing  
>with 2D rigid body translations only. I could do this by looping over  
>the values and comparing them individually to the mean, but I'm  
>wondering if there's a more compact (single line?) way of doing this  
>perhaps using the scipy.stats package. Something along the lines of  
>the filter built-in for lists, but that handles the higher  
>dimensionality, would be nice.
>
>Thanks,
>Aaron
>
>
>_______________________________________________
>SciPy-user mailing list
>SciPy-user at scipy.org
>http://projects.scipy.org/mailman/listinfo/scipy-user
>  
>


-- 
-------------------------------------------------------
James Coughlan, Ph.D., Associate Scientist                     

Smith-Kettlewell Eye Research Institute

Email: coughlan at ski.org
URL: http://www.ski.org/Rehab/Coughlan_lab/
Phone: 415-345-2146 
Fax: 415-345-8455
-------------------------------------------------------



From bhendrix at enthought.com  Mon Oct 30 15:57:08 2006
From: bhendrix at enthought.com (Bryce Hendrix)
Date: Mon, 30 Oct 2006 14:57:08 -0600
Subject: [SciPy-user] packaging with numpy.distutils
In-Reply-To: <4542B695.8040806@hoc.net>
References: <4542B695.8040806@hoc.net>
Message-ID: <45466724.7030706@enthought.com>

What may be the easiest thing for you to do is to create a script that 
is ran as a post-install that just moves the files to where you want 
them. You have to add the script to the scripts argument to setup, then 
specify the script with --install-script on the command line.

Bryce

Christian Kristukat wrote:
> Hi,
>
> I posted this to the numpy list but maybe it has been overlooked. Apologizes for
> asking here.
> I am creating a binary package on windows (bdist_wininst) making use of
> numpy.distutils and I would like to have something installed into PREFIX. With
> standard distutils this can be achieved by using the data_files keyword with
> setup. With numpy.distutils however those data end up in site-packages.
> Any ideas?
>
> Christian
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>   



From vmas at carabos.com  Mon Oct 30 15:59:17 2006
From: vmas at carabos.com (Vicent Mas (V+))
Date: Mon, 30 Oct 2006 21:59:17 +0100
Subject: [SciPy-user] Bug in find_objects? (Was: Re:  image processing)
In-Reply-To: <453DFBD9.6060304@bigpond.net.au>
References: <200610231057.37151.vmas@carabos.com>
	<loom.20061024T101958-962@post.gmane.org>
	<453DFBD9.6060304@bigpond.net.au>
Message-ID: <200610302159.17749.vmas@carabos.com>

El Tuesday, 24 de October de 2006 13:41, Gary Ruben escribi?:
> I haven't actually tried this, but I think you should take a look at
> scipy.ndimage.measurements.label
> followed by
> scipy.ndimage.measurements.find_objects
> and
> scipy.ndimage.measurements.maximum
>
> These sound like they will do what you want.
>
> Gary R.
>
> Carlos Medrano wrote:
> > Vicent Mas (V+ <vmas <at> carabos.com> writes:
> >> Hello,
> >>
> >> I'm a newcomer to process image and scipy. I'm trying to process a
> >> binary image in order to get the biggest connected component. In
> >> matlab one can use the bwareaopen to achieve this goal but I don't
> >> know how to do it with scipy.  I've been looking at scipy.ndimage
> >> module with no luck. Could you help me, please?
> >>
> >> Thanks in advance.
> >
>> [...]

Hello,


I'm trying to use Gary's receipt (thanks Gary, and sorry for answering 
so slowly :-( but I get the following error (as can be seen running the 
attached script):

Traceback (most recent call last):
  File "finder.py", line 13, in ?
    measurements.find_objects(label_matrix)
  
File "/usr/local/lib/python2.4/site-packages/scipy/ndimage/measurements.py", 
line 89, in find_objects
    return _nd_image.find_objects(input, max_label)
RuntimeError: data type not supported


It seems to be a bug. Am I right? Or am I doing something stupid?

Thanks in advance for your help.

-- 
::

	 \ /	Vicent Mas	http://www.carabos.com
	 0;0	
	/   \	C?rabos Coop.	Enjoy Data
	V   V
	 " "
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From conor.robinson at gmail.com  Mon Oct 30 16:38:19 2006
From: conor.robinson at gmail.com (Conor Robinson)
Date: Mon, 30 Oct 2006 13:38:19 -0800
Subject: [SciPy-user] how to filter outliers from an array
In-Reply-To: <45466539.6030009@ski.org>
References: <27403C7D-BDFF-4475-8884-3E07C2DCABC3@eecs.berkeley.edu>
	<45466539.6030009@ski.org>
Message-ID: <f1b195420610301338w54a17ad8o474da9bdef6efbee@mail.gmail.com>

I have found scipy.where() useful, although James' solution is very
nice as well.

On 10/30/06, James Coughlan <coughlan at ski.org> wrote:
> How about this?
>
> ####
> dx=rand(5,5) #substitute whatever matrices you're actually
> dy=rand(5,5) #using here
>
> import scipy.stats
> #compute mean and std for dx and dy:
> mx=stats.mean(dx.flat)
> my=stats.mean(dy.flat)
> sx=stats.std(dx.flat)
> sy=stats.std(dy.flat)
>
> wx=abs(dx-mx)>sx
> wy=abs(dy-my)>sy
> print wx | wy # logical or
> ####
>
> Here wx and wy are arrays whose elements are set to True if they lie
> more than 1 std. from mean. So wx | xy will flag those elements for
> which either the x or y components are outliers.
>
> James
>
>
>
> Aaron Hoover wrote:
>
> >Hi All,
> >
> >I'm doing feature matching between two images and as a result I get
> >back an array of dx, dy shift values in pixel space for potential
> >features that match between two images. I'd like to be able to throw
> >out [dx, dy] vectors for which either value deviates significantly
> >(more than one std deviation, perhaps) from the mean (I'm dealing
> >with 2D rigid body translations only. I could do this by looping over
> >the values and comparing them individually to the mean, but I'm
> >wondering if there's a more compact (single line?) way of doing this
> >perhaps using the scipy.stats package. Something along the lines of
> >the filter built-in for lists, but that handles the higher
> >dimensionality, would be nice.
> >
> >Thanks,
> >Aaron
> >
> >
> >_______________________________________________
> >SciPy-user mailing list
> >SciPy-user at scipy.org
> >http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> >
>
>
> --
> -------------------------------------------------------
> James Coughlan, Ph.D., Associate Scientist
>
> Smith-Kettlewell Eye Research Institute
>
> Email: coughlan at ski.org
> URL: http://www.ski.org/Rehab/Coughlan_lab/
> Phone: 415-345-2146
> Fax: 415-345-8455
> -------------------------------------------------------
>
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>


From ellisonbg.net at gmail.com  Mon Oct 30 17:00:22 2006
From: ellisonbg.net at gmail.com (Brian Granger)
Date: Mon, 30 Oct 2006 15:00:22 -0700
Subject: [SciPy-user] Parallel OO programming in Python.
In-Reply-To: <d9af7a880610301147y414174bqef3edaa7b5812cc1@mail.gmail.com>
References: <aaa2c8dc751a4631888dce898a10554d@atlas.cz>
	<6ce0ac130610291116rf184702i6d1f5ccc476ae886@mail.gmail.com>
	<d9af7a880610300427j2abce902h2f0b230da569f970@mail.gmail.com>
	<4546062E.1020501@cs.kuleuven.ac.be>
	<6ce0ac130610300801s5707a6a3h3480ce08899ecd46@mail.gmail.com>
	<d9af7a880610300953s741be2b0g1b82ed544e594d3d@mail.gmail.com>
	<6ce0ac130610301118ncd8d3al32a4c68f6db3801@mail.gmail.com>
	<d9af7a880610301147y414174bqef3edaa7b5812cc1@mail.gmail.com>
Message-ID: <6ce0ac130610301400l491fae58n96e1df7518977845@mail.gmail.com>

It looks like you are using an older version of zope.interface.  I
would grab this version and try it.

http://www.zope.org/Products/ZopeInterface/3.1.0c1/ZopeInterface-3.1.0c1.tgz

also, I would use a recent (I alway use the svn trunk) version of
twisted.  Let me know if that helps.

> I am playing with it right now!  I am planning to run it soon on multiple
> machines with multiple CPUs. Will I have to install Ipython1 on every node
> or Will the controller host spawn the processes across the net? In the
> README you seem to be starting the engines locally on each host....

Yes, you will need to install everything on each host and start the
engines on each machine.  If you have mpi installed, you can start the
engines using mpirun and this will handle it.  Let us know how it
goes.

Brian

> but before I get Ahead of myself , I am getting the following error when I
> try to start an engine on my localhost:
> fccoelho at sombra ~/Downloads/Twisted $ ipengine &
> [2] 32018
> fccoelho at sombra ~/Downloads/Twisted $ 2006/10/30 16:44 -0200 [-] Log opened.
> 2006/10/30 16:44 -0200 [-] Starting factory
> <ipython1.kernel.enginevanilla.VanillaEngineClientFactoryFromEngineService
> object at 0xb6706eac>
> 2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0, 127.0.0.1] Unhandled
> Error
>         Traceback (most recent call last):
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/log.py",
> line 48, in callWithLogger
>             return callWithContext({"system": lp}, func, *args, **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/log.py",
> line 33, in callWithContext
>             return context.call({ILogContext: newCtx}, func, *args, **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/context.py",
> line 59, in callWithContext
>             return self.currentContext().callWithContext(ctx, func, *args,
> **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/context.py",
> line 37, in callWithContext
>             return func(*args,**kw)
>         --- <exception caught here> ---
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py",
> line 139, in _doReadOrWrite
>             why = getattr(selectable, method)()
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/tcp.py",
> line 362, in doRead
>             return self.protocol.dataReceived(data)
>           File
> "/usr/lib/python2.4/site-packages/twisted/protocols/basic.py",
> line 99, in dataReceived
>             self.doData()
>           File
> "/usr/lib/python2.4/site-packages/twisted/protocols/basic.py",
> line 62, in doData
>             self.stringReceived(self.__buffer)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py",
> line 557, in stringReceived
>             self.nextHandler(msg)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py",
> line 573, in dispatch
>             f(args)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py",
> line 706, in handle_REGISTER
>             qe = engineservice.QueuedEngine(self, keepUpToDate=True)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/engineservice.py",
> line 342, in __init__
>             self.registerMethods ()
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/engineservice.py",
> line 345, in registerMethods
>             zi.alsoProvides(self, *self.engine.__provides__)
>         exceptions.AttributeError : 'module' object has no attribute
> 'alsoProvides'
>
> 2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0,127.0.0.1]
> unregistered engine None
> 2006/10/30 16:44 -0200 [VanillaEngineClientProtocol,client]
> Stopping factory <
> ipython1.kernel.enginevanilla.VanillaEngineClientFactoryFromEngineService
> object at 0xb6706eac>
> 2006/10/30 16:44 -0200 [VanillaEngineServerProtocol,0,127.0.0.1] Unhandled
> Error
>         Traceback (most recent call last):
>           File "/usr/bin/ipcontroller", line 51, in main
>             reactor.run()
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py",
> line 218, in run
>             self.mainLoop()
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py",
> line 229, in mainLoop
>             self.doIteration(t)
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py",
> line 133, in doSelect
>             _logrun(selectable, _drdw, selectable, method, dict)
>         --- <exception caught here> ---
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/log.py",
> line 48, in callWithLogger
>             return callWithContext({"system": lp}, func, *args, **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/log.py",
> line 33, in callWithContext
>             return context.call ({ILogContext: newCtx}, func, *args, **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/context.py",
> line 59, in callWithContext
>             return self.currentContext().callWithContext(ctx, func, *args,
> **kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/python/context.py",
> line 37, in callWithContext
>             return func(*args,**kw)
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/selectreactor.py",
> line 149, in _doReadOrWrite
>             self._disconnectSelectable(selectable, why,
> method=="doRead")
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/posixbase.py",
> line 256, in _disconnectSelectable
>             selectable.connectionLost(failure.Failure(why))
>           File
> "/usr/lib/python2.4/site-packages/twisted/internet/tcp.py",
> line 416, in connectionLost
>             protocol.connectionLost(reason)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py",
> line 538, in connectionLost
>             self.factory.unregisterEngine(self.id)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/enginevanilla.py",
> line 1023, in unregisterEngine
>             return self.service.unregisterEngine(id)
>           File
> "/usr/lib/python2.4/site-packages/ipython1/kernel/controllerservice.py",
> line 300, in unregisterEngine
>             del self.engines[id]
>         exceptions.KeyError :
>
>
>
> On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
> >
> > > Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> > > same way it does for a networked cluster? It would be nice to have that
> > > since quad-core cpu are arriving on the market and SMP machines are
> pretty
> > > common already.
> >
> > This was one of the major usage cases we have had in mind.  So yes.
> > Some details though:
> >
> > In IPython1 computations are done by a separate process that we are
> > calling the IPython engine.  Multiple IPython engines can be run on
> > multiple systems (distributed memory), a single (multi CPU and/or
> > multi-core) system or a combination of the two.  I have run two
> > IPython engines on my dual core MacBook and seen 2x speedup with
> > simple python scripts.  I wasn't using MPI, but with MPi you should
> > see a similar behavior as long as your algorithm scales linearly to 2
> > instances processes.
> >
> > I can't wait to use IPython1 with 4/8/16 cores on my workstation :)
> >
> > Please let us know if you have questions or problems.
> >
> > Brian
> >
> > On 10/30/06, Flavio Coelho <fccoelho at gmail.com> wrote:
> > > Hi Brian,
> > >
> > > Can Ipython1 take advantage of multiple core cpus or SMP machines in the
> > > same way it does for a networked cluster? It would be nice to have that
> > > since quad-core cpu are arriving on the market and SMP machines are
> pretty
> > > common already.
> > >
> > > Thanks!
> > >
> > > Fl?vio
> > >
> > >
> > > On 10/30/06, Brian Granger <ellisonbg.net at gmail.com> wrote:
> > > > > I also looked at the entry on Ipython1 and it looks really
> promising.
> > > > > Did I understand correctly that Ipython1 is able to run parallel
> python
> > > > > code, regardless of which "MPI for python" package one eventually
> uses?
> > > >
> > > > In principle yes.  The IPython engines have a configuration option
> > > > that you use to import the mpi bindings of your choice.  But, to work
> > > > properly, the import statement must cause MPI_Init() to be called.  If
> > > > the bindings you are using don't do that, it should b easy to write a
> > > > wrapper module that imports and also calls MPI_Init().  Also, some of
> > > > this depends on what MPI implementation you are using.  The more
> > > > moderns ones (like openmpi) are really nice and pretty forgiving.  The
> > > > older ones, though, sometimes require that Python itself (not your
> > > > script) call MPI_Init().  This is also very easy to work around.  The
> > > > bottom line is that we can help you get it to work with whatever mpi
> > > > binding and implementation you want.
> > > >
> > > > Withh that said, I highly do highly recommend mpi4py and openmpi - we
> > > > use these regularly with ipython and it all works well.
> > > >
> > > > Brian
> > > >
> > > >
> > > > > Giovanni
> > > > >
> > > > > Flavio Coelho wrote:
> > > > > > Thank you for this post and many thanks to Fernando Perez, for the
> > > > > > awesome tool that Ipython1 is becomming!!! I am beginning to use
> it
> > > > > > today!!
> > > > > >
> > > > > > Fl?vio
> > > > > >
> > > > > > On 10/29/06, * Brian Granger* < ellisonbg.net at gmail.com
> > > > > > <mailto:ellisonbg.net at gmail.com>> wrote:
> > > > > >
> > > > > >     > For object oriented parallel programming in Python on a
> single
> > > > > >     machine I can use techniques such as Bulk Synchronous
> Parallelism
> > > > > >     (BSP) or Message Passing Interface (MPI). There are mentioned
> some
> > > > > >     modules and packages for Python on
> > > > > >     > http://www.scipy.org/Topical_Software
> > > > > >     > Article: Parallel and distributed programming.
> > > > > >     > After reading prerequisites and limitations I thing that the
> > > > > >     following ones could be good for me:
> > > > > >     > PyMPI
> > > > > >     > Pypar
> > > > > >     > MPI for Python
> > > > > >
> > > > > >     I think mpi4py is the best option.  It is a very nice
> > > implementation
> > > > > >     and the developer is working really hard to make it a great
> > > package.
> > > > > >     Also, I don't think pympi and pypar are being developed
> actively
> > > > > >     anymore.
> > > > > >
> > > > > >     Another thing you might check out is IPython's parallel
> computing
> > > > > >     facilities that let you use mpi4py (and other mpi bindings)
> > > > > >     interactively:
> > > > > >
> > > > > >
> http://ipython.scipy.org/moin/Parallel_Computing
> > > > > >
> > > > > >     I have never used BPS, but am familiar with the model.  Can
> > > probably
> > > > > >     get it working interactively with IPython as well.
> > > > > >
> > > > > >     Cheers,
> > > > > >
> > > > > >     Brian
> > > > > >
> > > > > >     > But I can't distinguish which one brings fewer limitations,
> is
> > > > > >     efficient in application and will develop in future.
> > > > > >     > My favorite is BSP, but I can't find a package for present
> SciPy
> > > > > >     and NumPy.
> > > > > >     >
> > > > > >     > Could anybody give me a recommendation, which way I should
> go.
> > > > > >     >
> > > > > >     > Thanks.
> > > > > >     > Fie Pye
> > > > > >     >
> > > > > >     >
> > > > > >     >
> > > > > >     >
> > > > > >     > ---------------------------------------
> > > > > >     > M?me dal?? spot P.?tvrtn??ka. Pod?vejte se www.neuservis.cz
> > > > > >     < http://www.neuservis.cz>
> > > > > >     >
> > > > > >     >
> > > > > >     >
> _______________________________________________
> > > > > >     > SciPy-user mailing list
> > > > > >     > SciPy-user at scipy.org <mailto:SciPy-user at scipy.org>
> > > > > >     >
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > > >
> > > <http://projects.scipy.org/mailman/listinfo/scipy-user
> >
> > > > > >     >
> > > > > >
> _______________________________________________
> > > > > >     SciPy-user mailing list
> > > > > >     SciPy-user at scipy.org <mailto: SciPy-user at scipy.org>
> > > > > >
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > > >
> > > > > >
> > > > > >
> > > > > >
> > > > > > --
> > > > > > Fl?vio Code?o Coelho
> > > > > > registered Linux user # 386432
> > > > > > ---------------------------
> > > > > > "Laws are like sausages. It's better not to see them being made."
> > > > > > Otto von Bismark
> > > > > >
> > >
> ------------------------------------------------------------------------
> > > > > >
> > > > > > _______________________________________________
> > > > > > SciPy-user mailing list
> > > > > > SciPy-user at scipy.org
> > > > > >
> http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > > >
> > > > > _______________________________________________
> > > > > SciPy-user mailing list
> > > > > SciPy-user at scipy.org
> > > > >
> http://projects.scipy.org/mailman/listinfo/scipy-user
> > > > >
> > > > _______________________________________________
> > > > SciPy-user mailing list
> > > > SciPy-user at scipy.org
> > > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > > >
> > >
> > >
> > >
> > > --
> > >
> > > Fl?vio Code?o Coelho
> > > registered Linux user # 386432
> > > ---------------------------
> > > "Laws are like sausages. It's better not to see them being made."
> > > Otto von Bismark
> > > _______________________________________________
> > > SciPy-user mailing list
> > > SciPy-user at scipy.org
> > > http://projects.scipy.org/mailman/listinfo/scipy-user
> > >
> > >
> > >
> > _______________________________________________
> > SciPy-user mailing list
> > SciPy-user at scipy.org
> > http://projects.scipy.org/mailman/listinfo/scipy-user
> >
>
>
>
> --
> Fl?vio Code?o Coelho
> registered Linux user # 386432
> ---------------------------
> "Laws are like sausages. It's better not to see them being made."
> Otto von Bismark
> _______________________________________________
> SciPy-user mailing list
> SciPy-user at scipy.org
> http://projects.scipy.org/mailman/listinfo/scipy-user
>
>
>

From ckkart at hoc.net  Tue Oct 31 05:57:11 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Tue, 31 Oct 2006 19:57:11 +0900
Subject: [SciPy-user] packaging with numpy.distutils
In-Reply-To: <45466724.7030706@enthought.com>
References: <4542B695.8040806@hoc.net> <45466724.7030706@enthought.com>
Message-ID: <45472C07.5020202@hoc.net>

Bryce Hendrix wrote:
> What may be the easiest thing for you to do is to create a script that 
> is ran as a post-install that just moves the files to where you want 
> them. You have to add the script to the scripts argument to setup, then 
> specify the script with --install-script on the command line.

Thanks, that's true. But I do not quite like the idea that data will be lying
around in site-packages. But it seems there is now other way.

Christian


From oliphant.travis at ieee.org  Tue Oct 31 07:57:37 2006
From: oliphant.travis at ieee.org (Travis Oliphant)
Date: Tue, 31 Oct 2006 05:57:37 -0700
Subject: [SciPy-user] Need more comments from scientific community on
	python-dev
Message-ID: <45474841.9030802@ieee.org>


I'm recruiting more comments on python-dev regarding my two proposals 
for improving Python's native ability to share ndarray-like information.

There is a dearth of scientific-computing and number-crunching-aware 
people on python-dev.  The result is that I sound like a lone voice 
arguing for something that nobody cares about.  When, I don't think that 
is true.  Please, please.  If you want Python to grow support for the 
array interface (or something like it), then please speak up on 
python-dev. 

Even something as simple as I really see the need for a way to exchange 
data-format information between two objects sharing the buffer protocol 
can be helpful.

You can post through the gmane newsgroup interface: 

gmane.comp.python.devel

Find any of the posts on the PEP's I've introduced.  Thanks for your help.

-Travis



From david at ar.media.kyoto-u.ac.jp  Tue Oct 31 08:37:31 2006
From: david at ar.media.kyoto-u.ac.jp (David Cournapeau)
Date: Tue, 31 Oct 2006 22:37:31 +0900
Subject: [SciPy-user] pyaudio 0.3, with docs !
Message-ID: <4547519B.4040201@ar.media.kyoto-u.ac.jp>

Hi,

    I improved pyaudio last WE using indications given by various people 
on the list or privately, and as I finally got the motivation to set-up 
something which looks like a webpage, there is a doc with examples which 
show how to use it. The API to open files for writing is much saner, and 
the setup.py should be smart enough to grab all informations necessary 
to the wrapper, including the location of the shared libsndfile:
   
    download: 
http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/pyaudio/#installation
    doc + examples: 
http://www.ar.media.kyoto-u.ac.jp/members/david/softwares/pyaudio/

    I would appreciate to hear reports on platforms which are not linux 
(windows, mac os X) to see if my the setup.py works there,

    Cheers,

    David


From aisaac at american.edu  Tue Oct 31 11:14:00 2006
From: aisaac at american.edu (Alan Isaac)
Date: Tue, 31 Oct 2006 11:14:00 -0500
Subject: [SciPy-user] [Numpy-discussion] Need more comments from
	scientific community on python-dev
In-Reply-To: <45474841.9030802@ieee.org>
References: <45474841.9030802@ieee.org>
Message-ID: <Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>

On Tue, 31 Oct 2006, Travis Oliphant wrote: 
> Please, please.  If you want Python to grow support for 
> the array interface (or something like it), then please 
> speak up on python-dev. 

The easiest access to this discussion for me was
http://news.gmane.org/group/gmane.comp.python.devel/
I cannot add to this discussion, but I REALLY hope others 
will help Travis out here.  (A few have.)  He is fielding a lot 
of questions, some of which look to me to be from 
individuals who are ready to have fairly strong opinions 
without really understanding the "why" of his proposals.

The good news is, there seems to be (on my naive reading) 
some sympathy for what Travis is trying to do.  I think more 
motivating examples would prove helpful in swinging things.

Cheers,
Alan Isaac





From rshepard at appl-ecosys.com  Tue Oct 31 11:41:35 2006
From: rshepard at appl-ecosys.com (Rich Shepard)
Date: Tue, 31 Oct 2006 08:41:35 -0800 (PST)
Subject: [SciPy-user] [Numpy-discussion] Need more comments from
 scientific community on python-dev
In-Reply-To: <Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
References: <45474841.9030802@ieee.org>
	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
Message-ID: <Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>

On Tue, 31 Oct 2006, Alan Isaac wrote:

> The easiest access to this discussion for me was
> http://news.gmane.org/group/gmane.comp.python.devel/ I cannot add to this
> discussion, but I REALLY hope others will help Travis out here.  (A few
> have.) He is fielding a lot of questions, some of which look to me to be
> from individuals who are ready to have fairly strong opinions without
> really understanding the "why" of his proposals.

   All this is sufficiently far from my areas of expertise that I cannot
contribute anything useful. Otherwise, I'd be happy to lend support.

Rich

-- 
Richard B. Shepard, Ph.D.               |    The Environmental Permitting
Applied Ecosystem Services, Inc.(TM)    |            Accelerator
<http://www.appl-ecosys.com>     Voice: 503-667-4517      Fax: 503-667-8863


From fperez.net at gmail.com  Tue Oct 31 11:47:57 2006
From: fperez.net at gmail.com (Fernando Perez)
Date: Tue, 31 Oct 2006 09:47:57 -0700
Subject: [SciPy-user] [Numpy-discussion] Need more comments from
	scientific community on python-dev
In-Reply-To: <Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
References: <45474841.9030802@ieee.org>
	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
Message-ID: <db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>

On 10/31/06, Rich Shepard <rshepard at appl-ecosys.com> wrote:
> On Tue, 31 Oct 2006, Alan Isaac wrote:
>
> > The easiest access to this discussion for me was
> > http://news.gmane.org/group/gmane.comp.python.devel/ I cannot add to this
> > discussion, but I REALLY hope others will help Travis out here.  (A few
> > have.) He is fielding a lot of questions, some of which look to me to be
> > from individuals who are ready to have fairly strong opinions without
> > really understanding the "why" of his proposals.
>
>    All this is sufficiently far from my areas of expertise that I cannot
> contribute anything useful. Otherwise, I'd be happy to lend support.

I actually worry about the same: I really would like to help, but
after reading the whole discussion, I realized that the low-level
details being asked and discussed are something I don't really know
enough to say anything.  And I don't want to sound simply saying 'Hey,
Travis is great, listen to him!' to python-dev, since that (asides
from looking silly) can be somewhat counter-productive.

It seems to me that Travis has already tried hard to organize the
high-level overview of the issue for python-dev, and the rest of the
discussion is one that only those who really have used these features
can contribute to.

But Travis obviously needs help on this, and it seems to me that some
in the python-dev crowd are just resisting.  I was wondering if a way
to contribute could be to set up a wiki page for this particular
topic, where the salient points of the discussion can be summarized
and polished as things evolve.  This would also give a reference for
each idea as it clarifies, and it could serve to point the
hard-to-break python-devvers to: by having a clean summary of the
points, both high- and low-level, they might see the whole thing with
more clarity.

How does that sound, Travis?  Is that something you think might help
you, esp. since so many of us are feeling woefully underqualified to
lend a useful hand in the actual discussion on python-dev?

Regards,

f


From oliphant at ee.byu.edu  Tue Oct 31 12:04:48 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Tue, 31 Oct 2006 10:04:48 -0700
Subject: [SciPy-user] [Numpy-discussion] Need more comments
 from	scientific community on python-dev
In-Reply-To: <db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>
References: <45474841.9030802@ieee.org>	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
	<db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>
Message-ID: <45478230.2050709@ee.byu.edu>

Fernando Perez wrote:

>On 10/31/06, Rich Shepard <rshepard at appl-ecosys.com> wrote:
>  
>
>>On Tue, 31 Oct 2006, Alan Isaac wrote:
>>
>>    
>>
>>>The easiest access to this discussion for me was
>>>http://news.gmane.org/group/gmane.comp.python.devel/ I cannot add to this
>>>discussion, but I REALLY hope others will help Travis out here.  (A few
>>>have.) He is fielding a lot of questions, some of which look to me to be
>>>from individuals who are ready to have fairly strong opinions without
>>>really understanding the "why" of his proposals.
>>>      
>>>
>>   All this is sufficiently far from my areas of expertise that I cannot
>>contribute anything useful. Otherwise, I'd be happy to lend support.
>>    
>>
>
>I actually worry about the same: I really would like to help, but
>after reading the whole discussion, I realized that the low-level
>details being asked and discussed are something I don't really know
>enough to say anything.  And I don't want to sound simply saying 'Hey,
>Travis is great, listen to him!' to python-dev, since that (asides
>from looking silly) can be somewhat counter-productive.
>
>
>How does that sound, Travis?  Is that something you think might help
>you, esp. since so many of us are feeling woefully underqualified to
>lend a useful hand in the actual discussion on python-dev?
>  
>

That would be great.   I think a couple of things would also be useful.

1) Some way to indicate to python-dev that I'm actually speaking for 
more than just myself.  So, while I agree that just supporting my PEP 
(which probably in reality needs work) without understanding it is 
counter-productive, a voice that says.  "We really do need this kind of 
functionality" is at least one more voice. 

2) Examples of sharing memory between two objects.   PIL is the classic 
example and has some merit, but because the internal memory layout of 
the PIL is 'pointer-to-pointers' instead of 'big-chunk-of-memory' it's 
not a 1-1 match to NumPy and the array interface only can comunicate 
information about the "mode."  But, I can see other examples.  PyMedia, 
PyGame, PyVideo?  CVXOPT, PyVoxel. 

All of these seem to define their own objects which are basically just 
interpretations of chunks of memory.  At one time, we might have said 
"these should all be sub-classes of the ndarray".  Now, we are thinking 
more along the lines of "these should all expose an array interface".  
The array interface is still more bulky then it needs to be (it has to 
go through the attribute-lookup process which can be slow).   It would 
be much better if the extended buffer protocol were available as a 
function-pointer on the type object of the type.

If you have an application where you've ever wanted NumPy in the core.  
See if the extended buffer protocol serves your purposes and if you 
agree, voice your approval for the PEP. 

In my mind, the data-format PEP does not need to go through if there 
really is a better way to pass data-format information through the 
buffer protocol.   But, the extended buffer protocol we *do* need.


-Travis




>Regards,
>
>f
>_______________________________________________
>SciPy-user mailing list
>SciPy-user at scipy.org
>http://projects.scipy.org/mailman/listinfo/scipy-user
>  
>



From jdhunter at ace.bsd.uchicago.edu  Tue Oct 31 12:13:24 2006
From: jdhunter at ace.bsd.uchicago.edu (John Hunter)
Date: Tue, 31 Oct 2006 11:13:24 -0600
Subject: [SciPy-user] [Numpy-discussion] Need more comments
	from	scientific community on python-dev
In-Reply-To: <45478230.2050709@ee.byu.edu> (Travis Oliphant's message of
	"Tue, 31 Oct 2006 10:04:48 -0700")
References: <45474841.9030802@ieee.org>
	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
	<db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>
	<45478230.2050709@ee.byu.edu>
Message-ID: <87r6wo5ryj.fsf@peds-pc311.bsd.uchicago.edu>

>>>>> "Travis" == Travis Oliphant <oliphant at ee.byu.edu> writes:
    Travis> All of these seem to define their own objects which are
    Travis> basically just interpretations of chunks of memory.  At
    Travis> one time, we might have said "these should all be
    Travis> sub-classes of the ndarray".  Now, we are thinking more

What about blitting pixel buffers from mpl or chaco agg into various
GUI windows, GTK, Tk, WX, etc....  This seems like a ready made case
for the array interface.  I could pipe in with an example like this if
it would help.

JDH


From oliphant at ee.byu.edu  Tue Oct 31 12:20:35 2006
From: oliphant at ee.byu.edu (Travis Oliphant)
Date: Tue, 31 Oct 2006 10:20:35 -0700
Subject: [SciPy-user] [Numpy-discussion] Need more
 comments	from	scientific community on python-dev
In-Reply-To: <87r6wo5ryj.fsf@peds-pc311.bsd.uchicago.edu>
References: <45474841.9030802@ieee.org>	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>	<db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>	<45478230.2050709@ee.byu.edu>
	<87r6wo5ryj.fsf@peds-pc311.bsd.uchicago.edu>
Message-ID: <454785E3.1020505@ee.byu.edu>

John Hunter wrote:

>>>>>>"Travis" == Travis Oliphant <oliphant at ee.byu.edu> writes:
>>>>>>            
>>>>>>
>    Travis> All of these seem to define their own objects which are
>    Travis> basically just interpretations of chunks of memory.  At
>    Travis> one time, we might have said "these should all be
>    Travis> sub-classes of the ndarray".  Now, we are thinking more
>
>What about blitting pixel buffers from mpl or chaco agg into various
>GUI windows, GTK, Tk, WX, etc....  This seems like a ready made case
>for the array interface.  I could pipe in with an example like this if
>it would help.
>  
>
Somebody mentioned something like this, but another example would 
help.   The thread degenerated into a discussion of how RGBA is often 
different so you "can't share memory" anyway.

I think what is being missed is that you would set up the NumPy array in 
the correct memory layout for whatever the blitting code you are using 
expects and then could do processing with arrays and then write them to 
the screen directly from the NumPy array (rather than going through a 
string) or using an attribute lookup to use the array interface.

So, an example of how you "calculate with NumPy" and then "blit to the 
screen" the result would be very helpful.  

-Travis



From gpajer at rider.edu  Tue Oct 31 13:08:08 2006
From: gpajer at rider.edu (Gary Pajer)
Date: Tue, 31 Oct 2006 13:08:08 -0500
Subject: [SciPy-user] [Numpy-discussion] Need more
 comments	from	scientific community on python-dev
In-Reply-To: <87r6wo5ryj.fsf@peds-pc311.bsd.uchicago.edu>
References: <45474841.9030802@ieee.org>
	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
	<db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>
	<45478230.2050709@ee.byu.edu>
	<87r6wo5ryj.fsf@peds-pc311.bsd.uchicago.edu>
Message-ID: <45479108.4030704@rider.edu>

John Hunter wrote:

>>>>>>"Travis" == Travis Oliphant <oliphant at ee.byu.edu> writes:
>>>>>>            
>>>>>>
>    Travis> All of these seem to define their own objects which are
>    Travis> basically just interpretations of chunks of memory.  At
>    Travis> one time, we might have said "these should all be
>    Travis> sub-classes of the ndarray".  Now, we are thinking more
>
>What about blitting pixel buffers from mpl or chaco agg into various
>GUI windows, GTK, Tk, WX, etc....  This seems like a ready made case
>for the array interface.  I could pipe in with an example like this if
>it would help.
>
>JDH
>  
>
Does this bear on the issue of fast updating of graphs (stripchart ) ?
If so ... it's something I could use, and I revisit the problem every 
now and again.  Now happens to be one of those nows.
If my voice would help, what would the best way to communicate?

-gary

>_______________________________________________
>SciPy-user mailing list
>SciPy-user at scipy.org
>http://projects.scipy.org/mailman/listinfo/scipy-user
>
>  
>



From fperez.net at gmail.com  Tue Oct 31 13:18:03 2006
From: fperez.net at gmail.com (Fernando Perez)
Date: Tue, 31 Oct 2006 11:18:03 -0700
Subject: [SciPy-user] [Numpy-discussion] Need more comments from
	scientific community on python-dev
In-Reply-To: <45478230.2050709@ee.byu.edu>
References: <45474841.9030802@ieee.org>
	<Mahogany-0.67.0-3016-20061031-111400.00@CASC64043305.american.edu>
	<Pine.LNX.4.64.0610310840100.18434@salmo.appl-ecosys.com>
	<db6b5ecc0610310847u331fb8daud97a6a13964c23ad@mail.gmail.com>
	<45478230.2050709@ee.byu.edu>
Message-ID: <db6b5ecc0610311018v26695202udafe039ee767b580@mail.gmail.com>

On 10/31/06, Travis Oliphant <oliphant at ee.byu.edu> wrote:
> Fernando Perez wrote:

> >I actually worry about the same: I really would like to help, but
> >after reading the whole discussion, I realized that the low-level
> >details being asked and discussed are something I don't really know
> >enough to say anything.  And I don't want to sound simply saying 'Hey,
> >Travis is great, listen to him!' to python-dev, since that (asides
> >from looking silly) can be somewhat counter-productive.
> >
> >
> >How does that sound, Travis?  Is that something you think might help
> >you, esp. since so many of us are feeling woefully underqualified to
> >lend a useful hand in the actual discussion on python-dev?
> >
> >
>
> That would be great.   I think a couple of things would also be useful.

OK, my experience so far has been that there's a certain 'activation
barrier' with Wikis, but once pages are there, people for some reason
feel more comfortable filling in.  So even though it's mostly a place
holder, I went ahead and made this:

http://www.scipy.org/ArrayInterfacePEP

Hopefully as the discussion evolves, this page can be filled in with
all the necessary info in one place, and it will become in a few days
a solid, organized repository of all the key points in this
discussion.  This will be a LOT easier to refer to in the python-dev
battle than randomly scattered bits of emails in the discussion
thread.

I'll try to spend more time on it over the next few days to fill in,
but I'm pretty busy with other things as well, so hopefully others can
pitch in as well.

Cheers,

f

ps - one more thing.  This guy:

http://blog.vrplumber.com/

has been rewriting the OpenGL bindings using ctypes, and I've seen
posts from him about numpy (in his blog).  He might be able to
contribute something...


From souheil.inati at nyu.edu  Tue Oct 31 13:36:28 2006
From: souheil.inati at nyu.edu (Souheil Inati)
Date: Tue, 31 Oct 2006 13:36:28 -0500
Subject: [SciPy-user] scipy 0.5.1 and numpy 1.0
Message-ID: <BA66E290-E3DD-4A6E-8696-C43E4D6E80F7@nyu.edu>

Checking the website here http://www.scipy.org/Download, it is  
unclear if the latest stable release of SciPy (0.5.1) is compatible  
with the latest stable release of (NumPy 1.0).  Could someone please  
clarify this for me.

Thanks,
Souheil


From excellent.frizou at gmail.com  Tue Oct 31 14:37:36 2006
From: excellent.frizou at gmail.com (Sam frizou)
Date: Tue, 31 Oct 2006 20:37:36 +0100
Subject: [SciPy-user] csr_matrix
Message-ID: <1d2f6e8c0610311137r58329fb6x4e8967e6ffe8783d@mail.gmail.com>

Hi,

Is it possible to get the set of indices of non null elements of a
sparse matrix M ?
I means I can see them by doing "print M", but I want to use them, so
I would like something like a list of (i,j).

Thanks.


-- 
On obtient beaucoup plus avec un mot gentil et une arme qu'avec
seulement un mot gentil - "Al Capone".


From ckkart at hoc.net  Tue Oct 31 18:12:44 2006
From: ckkart at hoc.net (Christian Kristukat)
Date: Wed, 01 Nov 2006 08:12:44 +0900
Subject: [SciPy-user] scipy 0.5.1 and numpy 1.0
In-Reply-To: <BA66E290-E3DD-4A6E-8696-C43E4D6E80F7@nyu.edu>
References: <BA66E290-E3DD-4A6E-8696-C43E4D6E80F7@nyu.edu>
Message-ID: <4547D86C.6090400@hoc.net>

Souheil Inati wrote:
> Checking the website here http://www.scipy.org/Download, it is  
> unclear if the latest stable release of SciPy (0.5.1) is compatible  
> with the latest stable release of (NumPy 1.0).  Could someone please  
> clarify this for me.

I think the last numpy which works with scipy 0.5.1 is 1.0rc2. At least it works
here.

Christian