Mailman 3 April 2012 - SciPy-User

Re: [SciPy-User] scipy-user, numpy-user on google groups ?
by Scott Sinclair April 24, 2012

April 24, 2012

On 23 April 2012 12:02, denis <denis-bz-gg(a)t-online.de> wrote: > Hi Scott, > would you know what's happened to scipy-user and numpy-user on google > groups ? > They seem to be dormant / unresponsive script since about 1 April > or else, what other newsreader would you recommend ? > Thanks, cheers > -- denis I'm not sure who set up the Google groups to follow the lists, or how to get them working again (it seems the Google account has been disabled by Mailman due to excessive bounces). If you don't want to subscribe to the lists directly, you can try the Gmane archives: http://dir.gmane.org/gmane.comp.python.numeric.general http://dir.gmane.org/gmane.comp.python.scientific.user Cheers, Scott

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Euroscipy 2012 - abstract deadline soon (April 30) + sprints
by Emmanuelle Gouillart April 22, 2012

April 22, 2012

Hello, this is a reminder of the approaching deadline for abstract submission at the Euroscipy 2012 conference: the deadline is April 30, in one week. Euroscipy 2012 will be held in **Brussels**, **August 23-27**, at the Université Libre de Bruxelles (ULB, Solbosch Campus). The EuroSciPy meeting is a cross-disciplinary gathering focused on the use and development of the Python language in scientific research and industry. This event strives to bring together both users and developers of scientific tools, as well as academic research and state of the art industry. More information about the conference, including practical information, are found on the conference website http://www.euroscipy.org/conference/euroscipy2012 We are soliciting talks and posters that discuss topics related to scientific computing using Python. These include applications, teaching, future development directions, and research. We welcome contributions from the industry as well as the academic world. Submission guidelines are found on http://www.euroscipy.org/card/euroscipy2012_call_for_contributions Also, rooms are available at the ULB for sprints on Tuesday August 28th and Wednesday 29th. If you wish to organize a sprint at Euroscipy, please get in touch with Berkin Malkoc (malkocb(a)itu.edu.tr). Any other questions should be addressed exclusively to org-team(a)lists.euroscipy.org We apologize for the inconvenience if you received this e-mail through several mailing-lists. -- Emmanuelle, for the organizing team

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Download moinmoin scipy cookbook locally
by Kliment April 22, 2012

April 22, 2012

Hey guys, I use Zim (Desktop wiki) and accidentally found about moinmoin script (http://zim- wiki.org/wiki/doku.php?id=script_to_convert_moinmoin_pages_to_zim) that could transform mm to Zim format. I immediately thought on Scipy cookbook and went for it. However I know nothing about moinmoin and initially I tried to "wget" http://www.scipy.org/Cookbook recursively - bad idea for many reasons. So I thought to ask here, how can I download moinmoin scipy cookbook locally? TIA

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ANN: IEP 3.0.beta - the Interactive Editor for Python
by Almar Klein April 20, 2012

April 20, 2012

Dear all, On behalf of Rob, Ludo and myself, I'm pleased to finally announce version 3.0.beta of the Interactive Editor for Python. Give it at try and let us know what you think! IEP is a cross-platform Python IDE focused on interactivity and introspection, which makes it very suitable for scientific computing. Its practical design is aimed at simplicity and efficiency. IEP is written in Python 3 and Qt. Binaries are available for Windows, Linux, and Mac. Website: http://code.google.com/p/iep/ Discussion group: http://groups.google.com/group/iep_ Release notes: http://code.google.com/p/iep/wiki/Release Regards, Almar -- Almar Klein, PhD Science Applied phone: +31 6 19268652 e-mail: a.klein(a)science-applied.nl

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Testing scipy: a curiosity
by Sergio Rojas April 20, 2012

April 20, 2012

Hello all, Running the scipy tests in sequence: scipy.test() then, after the previous test finished without errors or failures I run: scipy.test('full') some tests fails (see below). Exiting and starting a new python session and executing only the test suite: scipy.test('full') No failures or errors are reported. The test ends with: ... ---------------------------------------------------------------------- Ran 5832 tests in 423.039s OK (KNOWNFAIL=14, SKIP=42) <nose.result.TextTestResult run=5832 errors=0 failures=0> What could be the problem?. Can we trust these tests results? Is there a way to run these failed tests individually so one can make sure the scipy system is working properly? perhaps an especific hard example could be usefull. Sergio >$ python_gnu Python 2.7.2 (default, Apr 18 2012, 13:06:38) [GCC 4.6.1] on linux3 Type "help", "copyright", "credits" or "license" for more information. >>> >>> >>> scipy.test('full') Running unit tests for scipy NumPy version 1.6.1 NumPy is installed in /home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/si te-packages/numpy SciPy version 0.10.1 SciPy is installed in /home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/si te-packages/scipy Python version 2.7.2 (default, Apr 18 2012, 13:06:38) [GCC 4.6.1] nose version 1.1.2 ..... ====================================================================== ERROR: test_iv_cephes_vs_amos_mass_test (test_basic.TestBessel) ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/sc ipy/special/tests/test_basic.py", line 1642, in test_iv_cephes_vs_amos_mass_test c1 = special.iv(v, x) RuntimeWarning: divide by zero encountered in iv ====================================================================== FAIL: test_mio.test_mat4_3d ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/no se/case.py", line 197, in runTest self.test(*self.arg) File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/sc ipy/io/matlab/tests/test_mio.py", line 740, in test_mat4_3d stream, {'a': arr}, True, '4') File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/nu mpy/testing/utils.py", line 1008, in assert_raises return nose.tools.assert_raises(*args,**kwargs) AssertionError: DeprecationWarning not raised ====================================================================== FAIL: Regression test for #651: better handling of badly conditioned ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/sc ipy/signal/tests/test_filter_design.py", line 34, in test_bad_filter assert_raises(BadCoefficients, tf2zpk, [1e-15], [1.0, 1.0]) File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/nu mpy/testing/utils.py", line 1008, in assert_raises return nose.tools.assert_raises(*args,**kwargs) AssertionError: BadCoefficients not raised ---------------------------------------------------------------------- Ran 5832 tests in 252.953s FAILED (KNOWNFAIL=14, SKIP=42, errors=1, failures=2) <nose.result.TextTestResult run=5832 errors=1 failures=2> scipy.test('full') scipy.test() ====================================================================== FAIL: test_mio.test_mat4_3d ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/no se/case.py", line 197, in runTest self.test(*self.arg) File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/sc ipy/io/matlab/tests/test_mio.py", line 740, in test_mat4_3d stream, {'a': arr}, True, '4') File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/nu mpy/testing/utils.py", line 1008, in assert_raises return nose.tools.assert_raises(*args,**kwargs) AssertionError: DeprecationWarning not raised ====================================================================== FAIL: Regression test for #651: better handling of badly conditioned ---------------------------------------------------------------------- Traceback (most recent call last): File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/sc ipy/signal/tests/test_filter_design.py", line 34, in test_bad_filter assert_raises(BadCoefficients, tf2zpk, [1e-15], [1.0, 1.0]) File "/home/srojas/myPROG/Python272GNU/Linux64b/lib/python2.7/site-packages/nu mpy/testing/utils.py", line 1008, in assert_raises return nose.tools.assert_raises(*args,**kwargs) AssertionError: BadCoefficients not raised ---------------------------------------------------------------------- Ran 5101 tests in 40.225s

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python + fortran (english)
by Leonardo Mello April 19, 2012

April 19, 2012

Hello! I'm having a problem getting calls from FORTRAN in Python. If I put a structure (TYPE) in the code does not create the f2py arquivo.so And if I use of modules with the USE f2py file.so but creates the when I enter the python and try to import does not work. Does anyone know how to use this library f2py you can help me. Thank you PS: excuse my english

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inverting pdist.
by Éric Depagne April 19, 2012

April 19, 2012

Hi. I'm using scipy.spatial.distance.pdist. I was wondering if it was possible to invert the result to get the elements of the input matrix that produced a given result. Let me explain a little. Say we have a,b, c and d. The possible distances are ab, ac, ad, bc, bd and cd. pdist will give the values for those 6 distances. Say the largest is at index 5. How can I get from the pdist result array that it is the bd distance? And if it is not, is there another way of doing so? My data are such that I have close to 100k distances to compute. Thanks. Éric. Un clavier azerty en vaut deux ---------------------------------------------------------- Éric Depagne eric(a)depagne.org

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scipy lapack
by Kenneth P Higgins April 19, 2012

April 19, 2012

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python + fortran
by Leonardo Mello April 19, 2012

April 19, 2012

Olá pessoal ! Estou com um problema para fazer chamadas do FORTRAN no python. Se eu coloco uma estrutura (TYPE) no código o f2py não cria o arquivo.so E se utilizo chamdas de módulos com USE o f2py cria o arquivo.so mas quando entro no python e tento importar não rola. Alguém sabe como utilizar essa biblioteca f2py que possa me ajudar. Vlw

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Re: [SciPy-User] fmin_bfgs failing on simple problem
by Kathleen M Tacina April 18, 2012

April 18, 2012

I've recreated this problem on my machine. It appears to be relating to floating point precision, and only occurs when the x<0 return value is extremely large. >>> def f2(x,badval=1e20): ... if x<=0: ... return badval ... else: ... return x+1/x ... >>> ans=1. >>> badval=1e20 >>> while abs(ans-1.)<1e-5: ... badval = 10*badval ... ans = fmin_bfgs(f2,10,args=(badval,)) The while loop ends when badval is 1.0e301, with ans as nan and the following error message: Warning: Desired error not necessarily achieved due to precision loss. Current function value: nan Iterations: 45 Function evaluations: 1989 Gradient evaluations: 654 But it works with badval=1.0e300. Would it hurt your problem to use 1e200 as your "nearly infinite" value instead of 1.79769313e+308? Or am I missing something here? On Tue, 2012-04-17 at 13:56 -0500, John Salvatier wrote: > Hmm, that's too bad. Looks like there was a big refactoring of > linesearch.py > ( https://github.com/scipy/scipy/blob/master/scipy/optimize/linesearch.py ) a couple of years ago ( https://github.com/scipy/scipy/commit/fefef2d73200d535b95ce0f21dcfe122301a9… ) > > > > Thanks for the help Nathaniel :) > > > On Tue, Apr 17, 2012 at 11:16 AM, Nathaniel Smith <njs(a)pobox.com> > wrote: > > On Tue, Apr 17, 2012 at 7:14 PM, John Salvatier > <jsalvati(a)u.washington.edu> wrote: > > Well that's good news. I have scipy .9.0b1, what version do > you have? > > > > Less good news: I have 0.8.0 :-) > > - N > > > > On Tue, Apr 17, 2012 at 11:13 AM, Nathaniel Smith > <njs(a)pobox.com> wrote: > >> > >> On Tue, Apr 17, 2012 at 6:35 PM, John Salvatier > >> <jsalvati(a)u.washington.edu> wrote: > >> > Hi all! > >> > > >> > I am having a problem with the fmin_bfgs solver that's > surprising to me. > >> > Here's the toy problem I've set up: > >> > > >> > from scipy.optimize import fmin_bfgs, fmin_ncg > >> > from numpy import * > >> > import numpy as np > >> > > >> > def f(x ): > >> > if x < 0: > >> > return 1.79769313e+308 > >> > else : > >> > return x + 1./x > >> > > >> > > >> > xs = fmin_bfgs(f, array( [10.]), retall = True) > >> > > >> > The solver returns [nan] as the solution. > >> > > >> > The problem is designed to be stiff: between 0 and 1, it > slopes upward > >> > to > >> > infinity but between 1 and infinity, it slopes up at a > slope of 1. Left > >> > of 0 > >> > the function has a "nearly infinite" value. If bfgs > encounters a value > >> > that's larger than the current value, it should try a > different step > >> > size, > >> > no? Why does fmin_bfgs fail in this way? > >> > >> I can't reproduce this (on my computer it converges to > 0.99999992), > >> but have you tried making that < into a <=? The > divide-by-zero at f(0) > >> might be making it freak out. > >> > >> -- Nathaniel > >> _______________________________________________ > >> SciPy-User mailing list > >> SciPy-User(a)scipy.org > >> http://mail.scipy.org/mailman/listinfo/scipy-user > > > > > > > > _______________________________________________ > > SciPy-User mailing list > > SciPy-User(a)scipy.org > > http://mail.scipy.org/mailman/listinfo/scipy-user > > > _______________________________________________ > SciPy-User mailing list > SciPy-User(a)scipy.org > http://mail.scipy.org/mailman/listinfo/scipy-user > > > >

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