Mailman 3 February 2008 - SciPy-User

Help required regding Eigenvectors
by Sudheer Phani March 14, 2022

March 14, 2022

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 Sept. 10, 2009

Sept. 10, 2009

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 July 7, 2009

July 7, 2009

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 May 15, 2009

May 15, 2009

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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Installing Scipy
by David Arnold April 11, 2008

April 11, 2008

All, Mac OS X 10.4.11 PPC. Installed python from this: http://www.python.org/ftp/python/2.5.1/python-2.5.1-macosx.dmg Installation finishes with "There were errors installing the software. Please try installing again." Installing again makes no difference, but Python appears to be running: scipy-0.6.0 $ python Python 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> Downloaded scipy from: http://prdownloads.sourceforge.net/scipy/ scipy-0.6.0.tar.gz?download After unpacking and changing directories, simply did this: scipy-0.6.0 $ sudo python setup.py install Seem to finish OK. Lots of "Warnings.' But testing according to INSTALL.txt resulted in: scipy-0.6.0 $ python Python 2.5.1 (r251:54869, Apr 18 2007, 22:08:04) [GCC 4.0.1 (Apple Computer, Inc. build 5367)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import scipy Traceback (most recent call last): File "<stdin>", line 1, in <module> File "scipy/__init__.py", line 54, in <module> from __config__ import show as show_config ImportError: No module named __config__ Any ideas or advice? Thanks David.

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What happened to ARPACK shift-invert/general eigenproblem routine?
by Neilen Marais April 9, 2008

April 9, 2008

Hi, I used to use scipy.sandbox.arpack.speigs.ARPACK_gen_eigs() to use the shift-invert mode of ARPACK to solve my problems. With the move of arpack from sandbox to splinalg.arpack I can't seem to find this function. Any hints? Thanks Neilen

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Faster allclose, comparing arrays
by Tom Johnson April 4, 2008

April 4, 2008

Frequently, I am comparing vectors to one another, and I am finding that a good portion of my time is spent in allclose. This is done through a class which stores a bunch of metadata and also a 'vector' attribute: def __eq__(self, other): return allclose(self.vector, other.vector, rtol=RTOL, atol=ATOL) So I place these objects in a list and check equality via "if x in objlist". Couple of questions: 1) Is this a "good" method for comparing arrays? 2) Is there any way to speed up allclose? Thanks.

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scipy installation without root access
by Alastair Basden March 12, 2008

March 12, 2008

Hi, can anyone give me some help/tips installing a working scipy on a Suse 10.0 machine (86_64) without root access? I can't use RPMs, as some of the dependencies are non-relocatable... The main problem that I'm having (as I see it) is getting the gfortran/g77 mix right, such that the functions all work when installed... Thanks...

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illegal instruction error in scipy.linalg.decomp.svd
by Lev Givon March 11, 2008

March 11, 2008

On a Pentium 4 Linux box running python 2.5.1, scipy 0.6.0, numpy 1.0.4, and lapack 3.0, I recently noticed that scipy.linalg.decomp.svd() fails (and causes python to crash) with an "illegal instruction" error. A bit of debugging revealed that the error occurs in the line lwork = calc_lwork.gesdd(gesdd.prefix,m,n,compute_uv)[1] in scipy/linalg/decomp.py. Interestingly, scipy 0.5.2.1 on the same box (with all of the other software packages unchanged) does not exhibit this problem. Moreover, when I install scipy 0.6.0 along with all of the other packages on a Linux machine containing a Pentium D CPU, I do not observe the problem either. Being that I am running Mandriva Linux, closed scipy bug 540 caught my eye. I'm not sure how it could be related to the above problem, though (and I also do not know what the lapack patch mentioned in the ticket could have been - even though I have been maintaining Mandriva's lapack lately :-). Thoughts? L.G.

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Re: [SciPy-user] handling of huge files for post-processing
by Christoph Scheit March 5, 2008

March 5, 2008

Hello David, indeed data in file a depends on data in file b... that the biggest problem and consequently I guess I need something that operates better on the file-system than in main memory. Do you think, it's possible to use PyTables to tackle the problem? I would need something that can group together such enormous data-sets. sqlite is nice to group data of a table together, but I guess my data-sets are just to big... Acutally I unfortunately don't see the possibility to iterate over the entries of the files in the manner you described below.... Thanks, Christoph ------------------------------ Message: 3 Date: Tue, 26 Feb 2008 09:17:00 -0500 From: "David Huard" <david.huard(a)gmail.com> Subject: Re: [SciPy-user] handling of huge files for post-processing To: "SciPy Users List" <scipy-user(a)scipy.org> Message-ID: <91cf711d0802260617o4d768824wbf5fae702b59f00a(a)mail.gmail.com> Content-Type: text/plain; charset="iso-8859-1" Cristoph, Do you mean that b depends on the entire dataset a ? In this case, you might consider buying additional memory; this is often way cheaper in terms of time than trying to optimize the code. What I mean by iterators is that when you open a binary file, you generally have the possibility to iterate over each element in the file. For instance, when reading an ascii file: for line in f.readline(): some operation on the current line. instead of loading all the file in memory: lines = f.readlines() This way, only one line is kept in memory at a time. If you can write your code in this manner, this might solve your memory problem. For instance, here is a generator that opens two files and will return the current line of each file each time it's next() method is called def read(): a = open('filea', 'r') b = open('fileb', 'r') la = a.readline() lb = b.readline() while (la and lb): yield la,lb la = a.readline() lb = b.readline() for a, b in read(): some operation on a,b HTH, David

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