Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2008-04-04 Thread Michael McNeil Forbes
On 16 Nov 2007, at 1:46 AM, Michael McNeil Forbes wrote:
> On 15 Nov 2007, at 8:23 PM, David Cournapeau wrote:
>
>> Could you try without atlas ? Also, how did you configure atlas when
>> building it ? It seems that atlas is definitely part of the problem
>> (everybody having the problem does use atlas), and that it involves
>> Core
>> 2 duo.
>>
>> David
>
> It seems to work fine without ATLAS, but then again, it is a somewhat
> "random" error.  I will let some code run tonight and see if I detect
> anything.

Just an update.  I am still having this problem, along with some  
additional problems where occasionally even dot returns nan's.  I  
have confirmed that without ATLAS everything seems to be fine, and  
that the problem still remains with newer versions of ATLAS, Python,  
gcc etc.

ATLAS was configured with

../configure --prefix=${BASE}/apps/${ATLAS}_${SUFFIX}\
  --with-netlib-lapack=${BASE}/src/${LAPACK}_${SUFFIX}/ 
lapack_LINUX.a\
  -A Core2Duo64SSE3\
  --cflags=-fPIC\
  -Fa alg -fPIC

and it passed all the tests.

The problem still exists with ATLAS version 3.8.1, gcc 4.3.0, and  
recent versions of numpy.

  >>> sys.version
  '2.5.2 (r252:60911, Mar 29 2008, 02:55:47) \n[GCC 4.3.0]'
  >>> numpy.version.version
  '1.0.5.dev4915'

I have managed to extract a matrix that causes this failure  
repeatedly once every two or four times eigh is called, so hopefully  
I should be able to run gdb and track down the problem...
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-16 Thread Michael McNeil Forbes
On 15 Nov 2007, at 8:23 PM, David Cournapeau wrote:

> Could you try without atlas ? Also, how did you configure atlas when
> building it ? It seems that atlas is definitely part of the problem
> (everybody having the problem does use atlas), and that it involves  
> Core
> 2 duo.
>
> David

It seems to work fine without ATLAS, but then again, it is a somewhat  
"random" error.  I will let some code run tonight and see if I detect  
anything.

Michael.

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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-15 Thread Michael McNeil Forbes
>> I have also been having random problems with the latest numpy from
>> svn built on an Intel core 2 Duo Linux box running in 64 bit mode
>> under Red Hat 3.4.6-8 with the gcc 3.4.6 20060404 and ATLAS 3.8.0.
>>
> Could you try without atlas ? Also, how did you configure atlas when
> building it ? It seems that atlas is definitely part of the problem
> (everybody having the problem does use atlas), and that it involves  
> Core
> 2 duo.

I will try that.  I made a mistake: it is a Core 2, not a core 2 duo...
model name  : Intel(R) Core(TM)2 CPU  6700  @ 2.66GHz

Michael.
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-15 Thread David Cournapeau
Michael McNeil Forbes wrote:
> On 13 Nov 2007, at 9:43 AM, Geoffrey Zhu wrote:
>   
>> On Nov 13, 2007 2:37 AM, David Cournapeau <[EMAIL PROTECTED] 
>> u.ac.jp> wrote:
>> 
>>> Geoffrey Zhu wrote:
>>>   
 Pointer problems are usually random...
 
> ...
>   
>> The original MSI version hangs on numpy.test() if I open IDLE and type
>>
>> import numpy
>> numpy.test()
>>
>> If I try the OP's test first, once it hang on "from numpy.linalg
>> import eig" and the other time it ran successfully. After it ran
>> successfully, it ran numpy.test() successfully, too.
>>
>> As you said, it is random.
>> 
>
>
> I have also been having random problems with the latest numpy from  
> svn built on an Intel core 2 Duo Linux box running in 64 bit mode  
> under Red Hat 3.4.6-8 with the gcc 3.4.6 20060404 and ATLAS 3.8.0.
>   
Could you try without atlas ? Also, how did you configure atlas when 
building it ? It seems that atlas is definitely part of the problem 
(everybody having the problem does use atlas), and that it involves Core 
2 duo.

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-15 Thread Michael McNeil Forbes
On 13 Nov 2007, at 9:43 AM, Geoffrey Zhu wrote:
> On Nov 13, 2007 2:37 AM, David Cournapeau <[EMAIL PROTECTED] 
> u.ac.jp> wrote:
>> Geoffrey Zhu wrote:
>>> Pointer problems are usually random...
...
> The original MSI version hangs on numpy.test() if I open IDLE and type
>
> import numpy
> numpy.test()
>
> If I try the OP's test first, once it hang on "from numpy.linalg
> import eig" and the other time it ran successfully. After it ran
> successfully, it ran numpy.test() successfully, too.
>
> As you said, it is random.


I have also been having random problems with the latest numpy from  
svn built on an Intel core 2 Duo Linux box running in 64 bit mode  
under Red Hat 3.4.6-8 with the gcc 3.4.6 20060404 and ATLAS 3.8.0.

I am having a problem with numpy.linalg.eigh and complex Hermitian  
matrices.  Randomly, I get seemingly correct answers, and then  
eigenvectors full of Nan's (though not completely.  The first row the  
the eigenvectors seem to be numbers, but incorrect.)

Sometimes, I can stop just after the error with pdb and "play".   
Calling eigh from the debugger sometimes gives a correct answer, and  
then other times gives eigenvalues and eigenvectors full of Nan's  
(not completely full mind you).  For example:

(Pdb) p numpy.linalg.eigh(HH)
(array([-50.50589438, -45.86305013, -40.56713543, -35.57216233,   
38.1497506 ,  40.17291371,  43.35773763,  46.59527636,   
49.42413434,  NaN,  NaN,
 NaN,  NaN,  NaN,   
NaN,  NaN,  NaN,  NaN,  NaN,   
NaN,  NaN,  NaN,
 NaN,  NaN,  NaN,   
NaN,  NaN,  NaN,  NaN,  NaN,   
NaN,  NaN,  NaN,
 NaN]), array([[-0.00072424 +0.j, -0.00136655 +0.j,   
0.00200233 +0.j, ...,  0. +0.j,  0. +0.j,  0.  
+0.j],
[NaN NaNj, NaN NaNj, NaN  
NaNj, ..., NaN NaNj, NaN NaNj, NaN NaNj],
[NaN NaNj, NaN NaNj, NaN  
NaNj, ..., NaN NaNj, NaN NaNj, NaN NaNj],
...,
[NaN NaNj, NaN NaNj, NaN  
NaNj, ..., NaN NaNj, NaN NaNj, NaN NaNj],
[NaN NaNj, NaN NaNj, NaN  
NaNj, ..., NaN NaNj, NaN NaNj, NaN NaNj],
[NaN NaNj, NaN NaNj, NaN  
NaNj, ..., NaN NaNj, NaN NaNj, NaN NaNj]]))
(Pdb) p numpy.linalg.eigh(HH)
(array([-51.06208813, -48.50332834, -48.49643331, -46.25814405,  
-46.25813858, -44.33668063, -44.33668063, -42.73548661, -42.73548661,  
-41.45454929, -41.45454929,
-40.49386126, -40.49386126, -39.85344006, -39.85344006,  
-39.53308677, -39.53308677,  37.91885011,  37.91885011,   
38.2392034 ,  38.2392034 ,  38.8796246 ,
 38.8796246 ,  39.84031263,  39.84031263,  41.12124995,   
41.12124995,  42.72244397,  42.72244398,  44.64390192,  44.6439074 ,   
46.88219666,  46.88909168,
 49.44785148]), array([[ -5.28060016e-04 +0.e+00j,   
-3.92271866e-05 +0.e+00j,   7.72453920e-04 +0.e 
+00j, ...,  -3.36896226e-01 +0.e+00j,
   6.28651296e-02 +0.e+00j,  -2.42202473e-01  
+0.e+00j],
[  1.48818848e-03 +2.78190640e-04j,   1.06069959e-03  
+1.98279117e-04j,  -1.88322135e-03 -3.52035081e-04j, ...,
2.86677919e-01 +5.35893907e-02j,
  -1.77188491e-01 -3.31222694e-02j,   2.38244862e-01  
+4.45356831e-02j],
[ -2.14234988e-03 -8.29950766e-04j,  -2.44246082e-03  
-9.46214364e-04j,   1.92200953e-03 +7.44590459e-04j, ...,   
-1.9231e-01 -7.47685718e-02j,
   2.55119386e-01 +9.88337767e-02j,  -2.26238355e-01  
-8.76452055e-02j],
...,
[  2.06281453e-01 -1.27724068e-01j,  -2.32614835e-01  
+1.44029008e-01j,  -1.75975052e-01 +1.08959139e-01j, ...,
1.75246553e-03 -1.08508072e-03j,
   2.22700685e-03 -1.37890426e-03j,   1.95336925e-03  
-1.20947504e-03j],
[ -2.26004880e-01 +8.75547569e-02j,   1.68085319e-01  
-6.51165996e-02j,   2.71949658e-01 -1.05353859e-01j, ...,   
-1.78646965e-03 +6.92082029e-04j,
  -1.00620547e-03 +3.89806076e-04j,  -1.41173185e-03  
+5.46907831e-04j],
[  2.38078516e-01 -4.45045876e-02j,  -6.17947313e-02  
+1.15514373e-02j,  -3.31159928e-01 +6.19045191e-02j, ...,
7.59301424e-04 -1.41938035e-04j,
   3.85592692e-05 -7.20797663e-06j,   5.19068791e-04  
-9.70307734e-05j]]))

Here is the version info (Everything build from scratch, numpy from  
svn):
 >>> sys.version
'2.5.1 (r251:54863, Nov 10 2007, 00:44:16) \n[GCC 3.4.6 20060404 (Red  
Hat 3.4.6-8)]'
 >>> numpy.version.version
'1.0.5.dev4427'
 >>> scipy.version.version
'0.7.0.dev3511'

Using ATLAS-3.8.0.

This is extremely annoying, and difficult to reproduce.  I will try  
recompiling with some different versions and see if I can reproduce  

Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-15 Thread Michael McNeil Forbes

On 15 Nov 2007, at 2:45 AM, David Cournapeau wrote:

> Which fortran compiler are you using ?

GNU Fortran (GCC) 3.4.6 20060404

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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-15 Thread David Cournapeau
Michael McNeil Forbes wrote:
> On 13 Nov 2007, at 9:43 AM, Geoffrey Zhu wrote:
>   
>> On Nov 13, 2007 2:37 AM, David Cournapeau <[EMAIL PROTECTED] 
>> u.ac.jp> wrote:
>> 
>>> Geoffrey Zhu wrote:
>>>   
 Pointer problems are usually random...
 
> ...
>   
>> The original MSI version hangs on numpy.test() if I open IDLE and type
>>
>> import numpy
>> numpy.test()
>>
>> If I try the OP's test first, once it hang on "from numpy.linalg
>> import eig" and the other time it ran successfully. After it ran
>> successfully, it ran numpy.test() successfully, too.
>>
>> As you said, it is random.
>> 
>
>
> I have also been having random problems with the latest numpy from  
> svn built on an Intel core 2 Duo Linux box running in 64 bit mode  
> under Red Hat 3.4.6-8 with the gcc 3.4.6 20060404 and ATLAS 3.8.0.
>
> I am having a problem with numpy.linalg.eigh and complex Hermitian  
> matrices.  Randomly, I get seemingly correct answers, and then  
> eigenvectors full of Nan's (though not completely.  The first row the  
> the eigenvectors seem to be numbers, but incorrect.)
>   
Which fortran compiler are you using ?

David

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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-14 Thread David Cournapeau
Keith Goodman wrote:
> On Nov 13, 2007 8:42 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
>>
>> Here we are:
>>
>> http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy-1.0.4.win32-py2.4.exe
>
> Thank you. He said it worked. He didn't even notice a slow down
> without ATLAS. On some calculations the results were different
> (between 1.0.2 and 1.0.4) in the last three decimal places. But that's
> to be expected, right? 
I don't think there is any chance to have exactly the same results 
(compiler/OS/CPU/BLAS all enter the equation). ATLAS will not change 
much the general performances of numpy: this only enter the equation for 
some functions (numpy.dot) and linear algebra of course, for relatively 
big numbers. For example, in my use case (linear algebra with maximum a 
few tens dimensions), ATLAS does not give much outside numpy.dot. And 
anyway, if you want good performance from atlas, you should compile it 
by yourself (ATLAS performance seems to really depend on the size of L1 
cache, for example).

So all in all, I think it worths considering just using netlib 
BLAS/LAPACK instead of ATLAS for binaries, at least on windows (I don't 
know who is responsible for the windows binaries); note that we still do 
not know why the official binaries hang, which is bothering.

cheers,

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-14 Thread Keith Goodman
On Nov 13, 2007 8:42 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
>
> Keith Goodman wrote:
> > On Nov 12, 2007 10:51 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> >
> >> On Nov 13, 2007 3:37 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> >>
> >>> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> >>>
>  The following code calling numpy v1.0.4 fails to terminate on my machine,
>  which was not the case with v1.0.3.1
> 
>  from numpy import arange, float64
>  from numpy.linalg import eig
>  a = arange(13*13, dtype = float64)
>  a.shape = (13,13)
>  a = a%17
>  eig(a)
> 
> >>> It sounds like the same problem that was reported in this thread:
> >>>
> >>> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
> >>>
> >>> A friend of mine says the windows binary of 1.0.4 also hangs on eigh
> >>> and lstsq (so linalg in general). I don't have that problem on 1.0.5
> >>> compiled on GNU/Linux.
> >>>
> >> Could you friend try the binaries there:
> >>
> >> http://projects.scipy.org/pipermail/numpy-discussion/2007-November/029811.html
> >>
> >> This may be a problem related to the blas/lapack used for the
> >> binaries. The binaries posted above use non optimized BLAS/LAPACK (I
> >> can update to 1.0.4 if this is a problem).
> >>
> >
> > He tried. But he is using python 2.4. (He said your binary was for 2.5).
> >
> Here we are:
>
> http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy-1.0.4.win32-py2.4.exe

Thank you. He said it worked. He didn't even notice a slow down
without ATLAS. On some calculations the results were different
(between 1.0.2 and 1.0.4) in the last three decimal places. But that's
to be expected, right? ATLAS must give different results than the non
optimized alternative.
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-13 Thread David Cournapeau
Keith Goodman wrote:
> On Nov 12, 2007 10:51 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
>   
>> On Nov 13, 2007 3:37 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>> 
>>> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
>>>   
 The following code calling numpy v1.0.4 fails to terminate on my machine,
 which was not the case with v1.0.3.1

 from numpy import arange, float64
 from numpy.linalg import eig
 a = arange(13*13, dtype = float64)
 a.shape = (13,13)
 a = a%17
 eig(a)
 
>>> It sounds like the same problem that was reported in this thread:
>>>
>>> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
>>>
>>> A friend of mine says the windows binary of 1.0.4 also hangs on eigh
>>> and lstsq (so linalg in general). I don't have that problem on 1.0.5
>>> compiled on GNU/Linux.
>>>   
>> Could you friend try the binaries there:
>>
>> http://projects.scipy.org/pipermail/numpy-discussion/2007-November/029811.html
>>
>> This may be a problem related to the blas/lapack used for the
>> binaries. The binaries posted above use non optimized BLAS/LAPACK (I
>> can update to 1.0.4 if this is a problem).
>> 
>
> He tried. But he is using python 2.4. (He said your binary was for 2.5).
>   
Here we are:

http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy-1.0.4.win32-py2.4.exe

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-13 Thread Geoffrey Zhu
On Nov 13, 2007 2:37 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> >
> > Yes, with the MSI I can always reproduce the problem with
> > numpy.test(). It always hangs.With the egg it does not hang. Pointer
> > problems are usually random, but not random if we are using the same
> > binaries in EGG and MSI and variables are always initialized to
> > certain value.
> Ok, could you try this:
>
> http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy-1.0.4.win32-py2.5.msi
>
> I built it with mingwin, and with NETLIB BLAS/LAPACK. This is just for
> testing, do not use it for anything else.
>
>
> David
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>

I just tried. Your new MSI does not hang on numpy.test() and the OP's
test case, and it seems faster.

The EGG version does not hang on numpy.test() but does on OP's test.

The original MSI version hangs on numpy.test() if I open IDLE and type

import numpy
numpy.test()

If I try the OP's test first, once it hang on "from numpy.linalg
import eig" and the other time it ran successfully. After it ran
successfully, it ran numpy.test() successfully, too.

As you said, it is random.
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-13 Thread Keith Goodman
On Nov 12, 2007 10:51 AM, David Cournapeau <[EMAIL PROTECTED]> wrote:
>
> On Nov 13, 2007 3:37 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> >
> > On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > > which was not the case with v1.0.3.1
> > >
> > > from numpy import arange, float64
> > > from numpy.linalg import eig
> > > a = arange(13*13, dtype = float64)
> > > a.shape = (13,13)
> > > a = a%17
> > > eig(a)
> >
> > It sounds like the same problem that was reported in this thread:
> >
> > http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
> >
> > A friend of mine says the windows binary of 1.0.4 also hangs on eigh
> > and lstsq (so linalg in general). I don't have that problem on 1.0.5
> > compiled on GNU/Linux.
> Could you friend try the binaries there:
>
> http://projects.scipy.org/pipermail/numpy-discussion/2007-November/029811.html
>
> This may be a problem related to the blas/lapack used for the
> binaries. The binaries posted above use non optimized BLAS/LAPACK (I
> can update to 1.0.4 if this is a problem).

He tried. But he is using python 2.4. (He said your binary was for 2.5).
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-13 Thread Peter Creasey
> 
> Yes, with the MSI I can always reproduce the problem with
> numpy.test(). It always hangs.With the egg it does not hang. Pointer
> problems are usually random, but not random if we are using the same
> binaries in EGG and MSI and variables are always initialized to
> certain value.
> 

I can consistently reproduce this problem with the EGG. 

It disappears, however, when I replace the lapack_lite.pyd with the version from
the 1.0.3.1 EGG (python 2.4). 

cheers,

Peter




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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-13 Thread David Cournapeau
Geoffrey Zhu wrote:
>
> Yes, with the MSI I can always reproduce the problem with
> numpy.test(). It always hangs.With the egg it does not hang. Pointer
> problems are usually random, but not random if we are using the same
> binaries in EGG and MSI and variables are always initialized to
> certain value.
Ok, could you try this:

http://www.ar.media.kyoto-u.ac.jp/members/david/archives/numpy-1.0.4.win32-py2.5.msi

I built it with mingwin, and with NETLIB BLAS/LAPACK. This is just for 
testing, do not use it for anything else.

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread Geoffrey Zhu
On Nov 12, 2007 10:26 PM, David Cournapeau <[EMAIL PROTECTED]> wrote:
> Geoffrey Zhu wrote:
> > On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
> >> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> >>> The following code calling numpy v1.0.4 fails to terminate on my machine,
> >>> which was not the case with v1.0.3.1
> >>>
> >>> from numpy import arange, float64
> >>> from numpy.linalg import eig
> >>> a = arange(13*13, dtype = float64)
> >>> a.shape = (13,13)
> >>> a = a%17
> >>> eig(a)
> >> It sounds like the same problem that was reported in this thread:
> >>
> >> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
> >
> > The code hangs on my machine too. In the thread you mentioned above, I
> > wrote that using the EGG instead of MSI appears to fix the
> > numpy.test() problem, but maybe it just somehow hides it.
> When you use the MSI, can you always reproduce the problem ? As I said
> previously, it is hard to know for sure without being able to reproduce
> the bug on our own workstation, but if this is a problem between fortran
> and C argument passing, then the result can be pretty random since the
> problem reduced to a pointer pointing at a wrong address (crash, wrong
> value, etc...).
>
> cheers,
>
> David
>
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Yes, with the MSI I can always reproduce the problem with
numpy.test(). It always hangs.With the egg it does not hang. Pointer
problems are usually random, but not random if we are using the same
binaries in EGG and MSI and variables are always initialized to
certain value.
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread David Cournapeau
Geoffrey Zhu wrote:
> On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
>>> The following code calling numpy v1.0.4 fails to terminate on my machine,
>>> which was not the case with v1.0.3.1
>>>
>>> from numpy import arange, float64
>>> from numpy.linalg import eig
>>> a = arange(13*13, dtype = float64)
>>> a.shape = (13,13)
>>> a = a%17
>>> eig(a)
>> It sounds like the same problem that was reported in this thread:
>>
>> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
>
> The code hangs on my machine too. In the thread you mentioned above, I
> wrote that using the EGG instead of MSI appears to fix the
> numpy.test() problem, but maybe it just somehow hides it.
When you use the MSI, can you always reproduce the problem ? As I said 
previously, it is hard to know for sure without being able to reproduce 
the bug on our own workstation, but if this is a problem between fortran 
and C argument passing, then the result can be pretty random since the 
problem reduced to a pointer pointing at a wrong address (crash, wrong 
value, etc...).

cheers,

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread Geoffrey Zhu
On Nov 12, 2007 12:37 PM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>
> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > which was not the case with v1.0.3.1
> >
> > from numpy import arange, float64
> > from numpy.linalg import eig
> > a = arange(13*13, dtype = float64)
> > a.shape = (13,13)
> > a = a%17
> > eig(a)
>
> It sounds like the same problem that was reported in this thread:
>
> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
>
> A friend of mine says the windows binary of 1.0.4 also hangs on eigh
> and lstsq (so linalg in general). I don't have that problem on 1.0.5
> compiled on GNU/Linux.
>
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The code hangs on my machine too. In the thread you mentioned above, I
wrote that using the EGG instead of MSI appears to fix the
numpy.test() problem, but maybe it just somehow hides it.
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread David Cournapeau
On Nov 13, 2007 3:37 AM, Keith Goodman <[EMAIL PROTECTED]> wrote:
>
> On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> > The following code calling numpy v1.0.4 fails to terminate on my machine,
> > which was not the case with v1.0.3.1
> >
> > from numpy import arange, float64
> > from numpy.linalg import eig
> > a = arange(13*13, dtype = float64)
> > a.shape = (13,13)
> > a = a%17
> > eig(a)
>
> It sounds like the same problem that was reported in this thread:
>
> http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465
>
> A friend of mine says the windows binary of 1.0.4 also hangs on eigh
> and lstsq (so linalg in general). I don't have that problem on 1.0.5
> compiled on GNU/Linux.
Could you friend try the binaries there:

http://projects.scipy.org/pipermail/numpy-discussion/2007-November/029811.html

This may be a problem related to the blas/lapack used for the
binaries. The binaries posted above use non optimized BLAS/LAPACK (I
can update to 1.0.4 if this is a problem).

cheers,

David
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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread Lou Pecora
Works fine on my computer (Mac OS X 10.4), Python 
2.4. Runs in a second or so.

-- Lou Pecora

---Peter wrote:

Hi all,

The following code calling numpy v1.0.4 fails to
terminate on my machine, which was not the case with
v1.0.3.1

from numpy import arange, float64
from numpy.linalg import eig
a = arange(13*13, dtype = float64)
a.shape = (13,13)
a = a%17
eig(a)


Regards,
Peter




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Re: [Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread Keith Goodman
On Nov 12, 2007 10:10 AM, Peter Creasey <[EMAIL PROTECTED]> wrote:
> The following code calling numpy v1.0.4 fails to terminate on my machine,
> which was not the case with v1.0.3.1
>
> from numpy import arange, float64
> from numpy.linalg import eig
> a = arange(13*13, dtype = float64)
> a.shape = (13,13)
> a = a%17
> eig(a)

It sounds like the same problem that was reported in this thread:

http://thread.gmane.org/gmane.comp.python.numeric.general/17456/focus=17465

A friend of mine says the windows binary of 1.0.4 also hangs on eigh
and lstsq (so linalg in general). I don't have that problem on 1.0.5
compiled on GNU/Linux.
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[Numpy-discussion] Problem with numpy.linalg.eig?

2007-11-12 Thread Peter Creasey
Hi all,

The following code calling numpy v1.0.4 fails to terminate on my machine,
which was not the case with v1.0.3.1

from numpy import arange, float64
from numpy.linalg import eig
a = arange(13*13, dtype = float64)
a.shape = (13,13)
a = a%17
eig(a)


Regards,
Peter
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