Mailman 3 March 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 10 Sep '09

10 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 07 Jul '09

07 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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Installing Scipy
by David Arnold 10 Apr '08

10 Apr '08

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 09 Apr '08

09 Apr '08

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 04 Apr '08

04 Apr '08

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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Estimation of parameters while fitting data
by Doreen Mbabazi 04 Apr '08

04 Apr '08

Hullo, I have as my fitting function a system of differential equations(3) and I am supposed to get the optimal parameters to use by fitting data to this system. I tried to use scipy.optimize.leastsq. The difficulty is with the function that calculates the difference between the data and the values from the fitting function. The result of the fitting function is a list with three values and yet I only need one of the values to be subtracted from the data value. I have tried to get something from PyDSTool but all in vain. If you can propose something for me to use or suggest a better method, I will be very grateful. Regards, Doreen.

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Re: [SciPy-user] FITS images with header-supplied axes?
by Perry Greenfield 02 Apr '08

02 Apr '08

On Mar 28, 2008, at 8:28 PM, Keflavich wrote: > Is there any plotting routine in scipy / matplotlib that can plot a > fits image with correct WCS coordinates on the axes? I know pyfits > can load fits files, astLib has routines to interpret header coordinates, and I think you can make the axes different using > matplotlib transforms, but is there anything that puts all three > together currently available? > Thanks, > Adam Well, we (STScI) recently wrapped WCSLIB to obtain a mapping function between pixel and sky coordinates for python (you can find it as pywcs in astrolib on scipy; that may have been what you were referring to). But I'm not sure you understand what you are asking for with regard to matplotlib. The new transforms stuff should make it much easier to display the sky coordinates in the interactive display. The axis labeling is a different matter. Suppose your image (let's say it's 1Kx1K for the sake of discussion) is rotated 45 degrees with regard to north (either way, it doesn't really matter). What would you expect to see for axis labels? I don't think it is at all obvious how people would want labeling to be done along the edges of the image. I can imagine someone wanting axes or grids superimposed on the image itself, but that's not quite the same thing. Do you want the image rotated so that it is resampled on to RA and Dec and displayed that way? In any event, no we haven't yet done anything to try to integrate all three things. Among other things we wanted to make sure that the api for the wcs info was suitable before doing a lot with it (and in the meantime, Mike is working on rewriting drizzle which is taking a lot of his time). Perry

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kmeans2 random initialization
by Alec Solway 01 Apr '08

01 Apr '08

Hello, In using kmeans2 with the "random" initialization method, I often get: numpy.linalg.linalg.LinAlgError: Matrix is not positive definite - Cholesky decomposition cannot be computed I haven't dug too deeply into the implementation; I'm wondering if there's a gotcha someone can point out quickly here. What exactly is the "random" initialization method doing with the data set, and what constraints must the data have so as to keep whatever intermediate matrix it computes to be positive definite? Thanks.

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