Mailman 3 June 2008 - SciPy-User

Help required regding Eigenvectors
by Sudheer Phani 14 Mar '22

14 Mar '22

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

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3D plotting
by Robert Cimrman 11 Sep '09

11 Sep '09

Hi, I need to do some simple 3D plots, so I tried the two Cookbook recipes (xplt, mplot3d) and failed: * xplt: does not work when using a custom installation directory such as python setup.py install --root=/home/share/software apparently the gistdata directory path is wrong: gist.error: failed to create drawing -- Gist work.gs style sheet missing * mplot3d: does not work with my version of matplotlib (0.80). I have made the changes mentioned in the Cookbook to no avail. (Axes.__init__() args apparently changed, as well as some other matplotlib object attributes) Any ideas? mplot3d looks great, I would really like to use it! thanks, r.

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assign to diagonal values?
by Carlos Scheidegger 08 Jul '09

08 Jul '09

Say I have a matrix m whose diagonal values I want to replace with the contents of vector new_diagonal. Right now, I'm using m -= diag(m) m += diag(new_diagonal) but that seems pretty wasteful (especially if diag() creates new arrays, which I suspect it does). Is there a standard (or any efficient) way to assign the diagonal values directly without an explicit for loop? Googling for "site:www.scipy.org assign diagonal" only returned results for sparse matrices, which is not the case here - these are plain numpy arrays. Thanks in advance, -carlos

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Is numpy's argsort lying about its numpy.int32 types?
by Rob Clewley 15 May '09

15 May '09

Hi, I'm having a problem comparing some types when using numpy's argsort. I'm using numpy 1.0.2. I can reproduce it simply: Python 2.4.4 (#71, Oct 18 2006, 08:34:43) [MSC v.1310 32 bit (Intel)] << snip >> In [1]: from numpy import argsort, sort, int32, array In [2]: x=array([1,3,2]) In [3]: aa=argsort(x) In [4]: as=sort(x) In [5]: type(aa[0]) Out[5]: <type 'numpy.int32'> In [6]: type(as[0]) Out[6]: <type 'numpy.int32'> In [7]: int32 Out[7]: <type 'numpy.int32'> In [8]: type(as[0])==int32 Out[8]: True In [9]: type(aa[0])==int32 Out[9]: False Any of the three indices in aa give me the same problem. Can someone explain if I should be doing this a different way, and if this is a bug?! Thanks, Rob

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weave problems, weave_imp.o no such file or directory
by Søren Nielsen 02 Dec '08

02 Dec '08

Hi, I've done a fresh install of MinGw 5.14, Python 2.4.4, Scipy 0.6.0, Numpy 1.1.0 and numarray 1.5.2 When I try to use weave i get this: C:\>test_weave.py <weave: compiling> running build_ext running build_src building extension "sc_552cccf5dbf4f6eadd273cdcbd5860523" sources customize Mingw32CCompiler customize Mingw32CCompiler using build_ext customize Mingw32CCompiler customize Mingw32CCompiler using build_ext building 'sc_552cccf5dbf4f6eadd273cdcbd5860523' extension compiling C++ sources C compiler: g++ -mno-cygwin -O2 -Wall compile options: '-IC:\Python24\lib\site-packages\scipy\weave -IC:\Python24\lib\ site-packages\scipy\weave\scxx -IC:\Python24\lib\site-packages\numpy\core\includ e -IC:\Python24\include -IC:\Python24\PC -c' g++ -mno-cygwin -O2 -Wall -IC:\Python24\lib\site-packages\scipy\weave -IC:\Pytho n24\lib\site-packages\scipy\weave\scxx -IC:\Python24\lib\site-packages\numpy\cor e\include -IC:\Python24\include -IC:\Python24\PC -c C:\Python24\lib\site-package s\scipy\weave\scxx\weave_imp.cpp -o c:\docume~1\lisear~1\lokale~1\temp\Lise Arle th\python24_intermediate\compiler_08edc7e348e1c33f63a33ab500aef08e\Release\pytho n24\lib\site-packages\scipy\weave\scxx\weave_imp.o Found executable C:\MinGw\bin\g++.exe g++.exe: Arleth\python24_intermediate\compiler_08edc7e348e1c33f63a33ab500aef08e\ Release\python24\lib\site-packages\scipy\weave\scxx\weave_imp.o: No such file or directory Traceback (most recent call last): File "C:\test_weave.py", line 341, in ? main() File "C:\test_weave.py", line 224, in main weave.inline('printf("%d\\n",a);',['a'], verbose=2, type_converters=converte rs.blitz) #, compiler = 'msvc', verbpse=2, type_converters=converters.blitz, au to_downcast=0) #'msvc' or 'gcc' or 'mingw32' File "C:\Python24\Lib\site-packages\scipy\weave\inline_tools.py", line 338, in inline auto_downcast = auto_downcast, File "C:\Python24\Lib\site-packages\scipy\weave\inline_tools.py", line 447, in compile_function verbose=verbose, **kw) File "C:\Python24\Lib\site-packages\scipy\weave\ext_tools.py", line 365, in co mpile verbose = verbose, **kw) File "C:\Python24\Lib\site-packages\scipy\weave\build_tools.py", line 269, in build_extension setup(name = module_name, ext_modules = [ext],verbose=verb) File "C:\Python24\Lib\site-packages\numpy\distutils\core.py", line 184, in set up return old_setup(**new_attr) File "C:\Python24\lib\distutils\core.py", line 166, in setup raise SystemExit, "error: " + str(msg) distutils.errors.CompileError: error: Command "g++ -mno-cygwin -O2 -Wall -IC:\Py thon24\lib\site-packages\scipy\weave -IC:\Python24\lib\site-packages\scipy\weave \scxx -IC:\Python24\lib\site-packages\numpy\core\include -IC:\Python24\include - IC:\Python24\PC -c C:\Python24\lib\site-packages\scipy\weave\scxx\weave_imp.cpp -o c:\docume~1\lisear~1\lokale~1\temp\Lise Arleth\python24_intermediate\compiler _08edc7e348e1c33f63a33ab500aef08e\Release\python24\lib\site-packages\scipy\weave \scxx\weave_imp.o" failed with exit status 1 the test_weave file was something i found on the scipy dev wiki... I also tried some of my older files that also uses weave and they all give the same error... Can anyone help me with this?

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Re: [SciPy-user] [OpenOpt] lb issue
by dmitrey 05 Jul '08

05 Jul '08

I don't see any difficulties to map my advice to more difficult cases (just don't forget to increase your ineq constraints by contol, for to compare those ones with zero, not contol, and use inf, not the huge value you have mentioned). Current ralg implementation doesn't need objfunc value when point is outside of feasible region (i.e. if *any* constraint is bigger than p.contol, not only lb-ub constraint). OO calls objFunc outside feasible region just for to check some stop criteria, yield iter output point text and possible graphics output. Regards, D. Emanuele Olivetti wrote: > Unfortunately it is not so simple to map this advice to my > real situation, which is more complex than the > proof-of-concept example of the initial message. Returning > a big positive value when x is outside the bounds is an option > I considered some time ago but then discarded. But I'll think > more about it now. > > Ciao, > > Emanuele > > dmitrey wrote: > >> Hi Emanuele, >> >> I could propose you temporary solution (see below), this one doesn't >> require updating oo from svn. However, usually ALGENCAN, ipopt and >> scipy_slsqp work much better for box-bound constrained problems (w/o >> other constraints) than current ralg implementation. >> D. >> >> import numpy as N >> from scikits.openopt import NLP >> from numpy import any, inf >> size = 100 >> dimensions = 2 >> data = N.random.rand(size,dimensions)-0.5 >> >> contol = 1e-6 >> lb=N.zeros(dimensions) + contol >> >> def f(x): >> global data >> if any(x<0): >> #objective function is not defined here, let's use inf instead >> #however, some iters will show objFunVa= inf in text output >> # and graphic output is currently unavailable for the case >> return inf >> return N.dot(data**2,x.T) >> >> x0 = N.ones(dimensions) >> p = NLP(f,x0,lb=lb, contol = contol) >> p.solve('ralg') >> print p.ff,p.xf >> >> > > > > >

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single elements and arrays
by Gideon Simpson 01 Jul '08

01 Jul '08

Suppose I have a function foo def foo(x): blah and i have written foo in a vectorized fashion such that x can be a numpy array of #'s. But suppose I also want to be able to do foo(5.5) where i am interested in the value at a single point. Is there an easy way to handle both cases? Should I just not permit this sort of ambiguity (force everything to be an array)? -gideon

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ANN: NumPy 1.1.0
by Jarrod Millman 30 Jun '08

30 Jun '08

I'm pleased to announce the release of NumPy 1.1.0. NumPy is the fundamental package needed for scientific computing with Python. It contains: * a powerful N-dimensional array object * sophisticated (broadcasting) functions * basic linear algebra functions * basic Fourier transforms * sophisticated random number capabilities * tools for integrating Fortran code. Besides it's obvious scientific uses, NumPy can also be used as an efficient multi-dimensional container of generic data. Arbitrary data-types can be defined. This allows NumPy to seamlessly and speedily integrate with a wide-variety of databases. This is the first minor release since the 1.0 release in October 2006. There are a few major changes, which introduce some minor API breakage. In addition this release includes tremendous improvements in terms of bug-fixing, testing, and documentation. For information, please see the release notes: http://sourceforge.net/project/shownotes.php?release_id=602575&group_id=1369 Thank you to everybody who contributed to this release. Enjoy, -- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/

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accessing only the nonzero elements of a sparse matrix
by Ted Sandler 30 Jun '08

30 Jun '08

It doesn't seem like anything like the numpy arrays method ``nonzero'' is implemented for scipy's sparse matrices. What I am looking for is something like: A = sparse.spidentity(3); A.nonzero() ==> (array([0, 1, 2]), array([0, 1, 2])) I guess I could convert to coordinate form 'COO' and then access the "row" and "col" fields but this seems a little evil as it relies on properties of the 'COO' matrix which could change in the future. It would be nicer to have a uniform method of all sparse matrix types. Thanks for any info on this, -Ted

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2D Interpolation
by Ryan May 30 Jun '08

30 Jun '08

Hi, Can anyone help me use scipy.interpolate correctly. Here's my problem: I'm trying to make a 2D lookup table to save some calculations. The two parameters over which the lookup table is generated are independent and I have complete control over how I divide up the domain. Using this lookup table, I'd like to then calculate values over an unstructured set of parameter values (ie. a list of pairs of parameter values). Is there a function in scipy.interpolate that can help here? What I'd really like to be able to do is generate an interpolator object from my 2D array, and then pass a pair of 1D arrays to the object and have it return 1D array of values. Thanks in advance, Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma

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