[SciPy-user] [OpenOpt] problem with ralg (latest SVN)

Emanuele Olivetti emanuele@relativita....
Fri Sep 5 17:51:01 CDT 2008


Thanks for help.

Unfortunately after updating from SVN again I'm not able to reproduce
the same error, but instead I get this, about failing to import "cond" from
numpy.linalg. It seems that "cond" is not available until the very latest
numpy (and even autogenerated NumPy API on scipy.org have no "cond"):
----
$ python openopt/scikits/openopt/examples/nlp_1.py
OpenOpt checks user-supplied gradient df (shape: (150,) )
according to:
    prob.diffInt = [  1.00000000e-07]
    |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
derivatives are equal
========================
OpenOpt checks user-supplied gradient dc (shape: (2, 150) )
according to:
    prob.diffInt = [  1.00000000e-07]
    |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
derivatives are equal
========================
OpenOpt checks user-supplied gradient dh (shape: (2, 150) )
according to:
    prob.diffInt = [  1.00000000e-07]
    |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
derivatives are equal
========================
Traceback (most recent call last):
  File "openopt/scikits/openopt/examples/nlp_1.py", line 108, in <module>
    r = p.solve('ralg', debug = 1)
  File
"/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/BaseProblem.py",
line 185, in solve
    return runProbSolver(self, solvers, *args, **kwargs)
  File
"/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/runProbSolver.py",
line 43, in runProbSolver
    solverClass =  getattr(my_import(__solverPaths__[solver_str]),
solver_str)
  File
"/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/runProbSolver.py",
line 268, in my_import
    mod = __import__(name)
  File
"/usr/lib/python2.5/site-packages/scikits/openopt/solvers/UkrOpt/ralg_oo.py",
line 2, in <module>
    from numpy.linalg import norm, cond
ImportError: cannot import name cond
----

Any suggestion on how to solve this?

Sorry for the mess.

Emanuele

Note: this error pops out using numpy+scipy shipped with
ubuntu. When using recent SVN version of numpy+scipy
everything works well.

dmitrey wrote:
> Hi Emanuele,
>  as it is mentioned in openopt install webpage and README.txt  numpy v 
>  >= 1.1.0 is recommended. Some other oo users informed of bugs due to 
> older versions.
>
> Could you inform what will be outputed if you set p.debug = 1? (either 
> directly or via p = NLP(..., debug=1,...))
>
> If the problem with numpy versions is critical for users of your soft, 
> you'd better to put more recent numpy into Debian soft channel.
>
> Regards, D.
>
> Emanuele Olivetti wrote:
>   
>> Same problem with numpy 1.0.4 + scipy 0.6.0
>> (shipped with ubuntu 8.04 hardy heron).
>>
>> E.
>>
>> Emanuele Olivetti wrote:
>>   
>>     
>>> Dear all and Dmitrey,
>>>
>>> I've just updated to latest openopt (SVN). When using numpy 1.0.3
>>> and scipy 0.5.2 (standard in Ubuntu 7.10 gutsy gibbon) openopt says
>>> that "ralg" (NLP) algorithm is missing! With more recent numpy
>>> and scipy it seems to work reliably. But what happened with respect
>>> to older numpy+scipy? In that case even running examples/nlp_1.py
>>> returns:
>>> ----
>>> $ python nlp_1.py
>>> OpenOpt checks user-supplied gradient df (shape: (150,) )
>>> according to:
>>>     prob.diffInt = [  1.00000000e-07]
>>>     |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
>>> derivatives are equal
>>> ========================
>>> OpenOpt checks user-supplied gradient dc (shape: (2, 150) )
>>> according to:
>>>     prob.diffInt = [  1.00000000e-07]
>>>     |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
>>> derivatives are equal
>>> ========================
>>> OpenOpt checks user-supplied gradient dh (shape: (2, 150) )
>>> according to:
>>>     prob.diffInt = [  1.00000000e-07]
>>>     |1 - info_user/info_numerical| <= prob.maxViolation = 0.01
>>> derivatives are equal
>>> ========================
>>> OO Error:incorrect solver is called, maybe the solver "ralg" is not
>>> installed. Maybe setting p.debug=1 could specify the matter more precisely
>>> Traceback (most recent call last):
>>>   File "nlp_1.py", line 110, in <module>
>>>     r = p.solve('ralg')
>>>   File
>>> "/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/BaseProblem.py",
>>> line 185, in solve
>>>     return runProbSolver(self, solvers, *args, **kwargs)
>>>   File
>>> "/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/runProbSolver.py",
>>> line 48, in runProbSolver
>>>     p.err('incorrect solver is called, maybe the solver "' + solver_str
>>> +'" is not installed. Maybe setting p.debug=1 could specify the matter
>>> more precisely')
>>>   File
>>> "/usr/lib/python2.5/site-packages/scikits/openopt/Kernel/oologfcn.py",
>>> line 16, in ooerr
>>>     raise OpenOptException(msg)
>>> scikits.openopt.Kernel.oologfcn.OpenOptException: incorrect solver is
>>> called, maybe the solver "ralg" is not installed. Maybe setting
>>> p.debug=1 could specify the matter more precisely
>>> ----
>>>
>>> This did not happen before so I guess it is due to a recent
>>> commit. It is possible to solve the problem?
>>>
>>> Kind Regards,
>>>
>>> Emanuele
>>>
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>>> SciPy-user@scipy.org
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>>>
>>>   
>>>     
>>>       
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