Mailman 3 March 2008 - SciPy-User

Impulse/Step response troubles
by Kumar Appaiah 01 Apr '08

01 Apr '08

Dear SciPy users, (Long mail) I am having several problems in working out the impulse response of a simple function in SciPy. I would request you to please point out whether the fault lies with SciPy or me. The question is to determine (plot) the step and ramp responses of K / (s^2 + 8s + K) for K = 7, 16 and 80 So, the following code is used, and I'll keep changing a line: <code> from scipy import * from pylab import * K = 16.0 # should be redone with 7.0, 16.0 and 80.0 r = signal.impulse(([K],[1.0,8.0,K]), T=r_[0:5:0.001]) plot(r[0], r[1], linewidth=2) show() </code> The above code plots the impulse response of the given function. Now, on to the action: 1. Running the above code with K = 7.0 and K = 16.0 gives expected results. However, running the code with K = 16.0 doesn't work; if K = 16.0, the response should be 16 * t * exp(-4t) * u(t), which it isn't. Changing K to 16 + or - .00000000001 fixes it. There surely is some problem when the value of K is such that a double root is hit. 2. For the step response, I change "impulse" in the above code to "step", things seem all right. Again, for K = 16, it doesn't work. I then switch back to impulse, but make the second (denominator) array [1.0, 8.0, K, 0], and still the same thing is observed. 3. To get the ramp response, I now have the following code in line 8 of the above code. r = signal.step(([K],[1.0,8.0,K, 0]), T=r_[0:5:0.001]) But this causes the error: Traceback (most recent call last): File "<stdin>", line 8, in ? File "/usr/lib/python2.4/site-packages/scipy/signal/ltisys.py", line 498, in step vals = lsim(sys, U, T, X0=X0) File "/usr/lib/python2.4/site-packages/scipy/signal/ltisys.py", line 403, in lsim ATm1 = linalg.inv(AT) File "/usr/lib/python2.4/site-packages/scipy/linalg/basic.py", line 306, in inv if info>0: raise LinAlgError, "singular matrix" numpy.linalg.linalg.LinAlgError: singular matrix So let's switch back to impulse: r = signal.impulse(([K],[1.0,8.0,K, 0.0, 0.0]), T=r_[0:5:0.001]) Now, it seems to work, but I am yet to verify the correctness of the plots. Naturally, for K = 16.0, it doesn't work; I have to use a value close to it. I would really appreciate help in getting this debugged. Thanks a lot! Kumar -- Kumar Appaiah, 458, Jamuna Hostel, Indian Institute of Technology Madras, Chennai - 600 036

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Polyfit may be poorly conditioned
by massimo sandal 31 Mar '08

31 Mar '08

Hi, I am writing an algorithm that determines the best-fitting polynomial to a data set[1]. The algorithm tries to fit polynomials between 1st and 12th degree, and chooses the polynomial with the least mean square error. It works really well now, however when it occurs to prefer high-grade polynomials (say, 8th-9th grade and more), I often see this warning: /usr/lib/python2.5/site-packages/numpy/lib/polynomial.py:305: RankWarning: Polyfit may be poorly conditioned warnings.warn(msg, RankWarning) I have poor knowledge on polynomial fitting, but if I remember correctly, it means that the fit is very sensitive to tiny shifts in the data values (unstable)? Should I worry anyway or, as long as it gives me sensible results, go along? Thanks, Massimo [1]this is needed to "flatten" the data set from systematic, irregular low-frequency interferences. -- Massimo Sandal University of Bologna Department of Biochemistry "G.Moruzzi" snail mail: Via Irnerio 48, 40126 Bologna, Italy email: massimo.sandal(a)unibo.it tel: +39-051-2094388 fax: +39-051-2094387

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Is solving sparse systems of linear equations possible w/o scipy?
by dmitrey 31 Mar '08

31 Mar '08

hi all, is solving sparse systems of linear equations possible w/o scipy, via numpy tools only? For example I have table 3 x n i, j, val that defines sparse matrix A, and I want to solve Ax=b So does numpy/numpy.linalg has tools to solve the sparse problem? (It would allow using d2f and mb d2c, d2h in ralg solver) I don't want to have scipy dependence wrt the issue. Thank you in advance, D.

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Re: [SciPy-user] FITS images with header-supplied axes?
by Eric Emsellem 30 Mar '08

30 Mar '08

> I'm not sure I understand how the transforms would make it easier to > display sky coordinates without labeling axes, though. Are you saying > that if the image is already sampled in RA/DEC (or whatever coordinate > system) space, then it should be easy to display the RA/DEC > coordinates on the axes? yes it is possible of course: I do it by using ax.pcolormesh and first creating the corners of each pixels with the shading='flat' option. I have been trying to make a "clean" automatic routine to do this in a very general way but so far I only ended up with a simple dirty one. If you are interested I can always send it to you, but this does not make really use of the nice wcs functionalities that people at StSci have written up. Eric

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Re: [SciPy-user] FITS images with header-supplied axes?
by Eric Emsellem 29 Mar '08

29 Mar '08

Hi, if you find a solution, please let me know. On my side I had to rewrite some dummy routines to use the CRVAL/CDELT/NAXIS etc headers to do the axes plotting. I am using "extent=", to have a direct access to the coordinates in the plotting (imshow). But of course you first have to use the figure size, and then adapt the format (with some basic calculation) of your image/plot so that the pixels follow the right axis ratio. Eric > 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

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FITS images with header-supplied axes?
by Keflavich 29 Mar '08

29 Mar '08

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

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Re: [SciPy-user] Problem with scipy.optimize.leastsq: Improper input parameters
by Adam Ginsburg 28 Mar '08

28 Mar '08

OK... follow-up... can anyone help me re-compile __minpack.h with the patch in place? I have no idea how to do it, and I can't get scipy itself to compile, I think because it's failing a lot of dependencies. I installed scipy from a .deb package originally, not from source, and I'm really not sure whether it will be worse to try to resolve all those dependencies or just work around the problem. Thanks, Adam

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Numpy/Cython Google Summer of Code project idea
by Fernando Perez 27 Mar '08

27 Mar '08

Hi all, after the Scipy/Sage Days 8 meeting, we were all very impressed by the progress made by Cython. For those not familiar with it, Cython: http://www.cython.org/ is an evolved version of Pyrex (which is used by numpy and scipy) with lots of improvements. We'd like to position Cython as the preferred way of writing most, if not all, new extension code written for numpy and scipy, as it is easier to write, get right, debug (when you still get it wrong) and maintain than writing to the raw Python-C API. A specific project along these lines, that would be very beneficial for numpy could be: - Creating new matrix types in cython that match the cvxopt matrices. The creation of new numpy array types with efficient code would be very useful. - Rewriting the existing ndarray subclasses that ship with numpy, such as record arrays, in cython. In doing this, benchmarks of the relative performance of the new code should be obtained. Another possible project would be the addition to Cython of syntactic support for array expressions, multidimensional indexing, and other features of numpy. This is probably more difficult than the above, as it would require fairly detailed knowledge of both the numpy C API and the Cython internals, but would ultimately be extremely useful. Any student interested in this should quickly respond on the list; such a project would likely be co-mentored by people on the Numpy and Cython teams, since it is likely to require expertise from both ends. Cheers, f

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Re: [SciPy-user] import scipy.io error in debian - SOLVED
by Angus McMorland 26 Mar '08

26 Mar '08

On 26/03/2008, Angus McMorland <amcmorl(a)gmail.com> wrote: > Hi all, > > I'm trying to load a .mat file (my new lab is MatLab-crazy) using > debian-testing (numpy 1.0.4 and scipy 0.6.0. I'm getting an import > error for scipy.io: "No module named numpyio". Is this a known issue > with these versions or a bug? If the former, do I need to update to > svn, or is this fixed in the debian-unstable version? Hi all, Fixed. For some reason, my install of the scipy package was broken, and "apt-get install --reinstall python-scipy "sorted the problem. Sorry for the noise. A. -- AJC McMorland, PhD candidate Physiology, University of Auckland Post-doctoral research fellow Neurobiology, University of Pittsburgh

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ANN: SfePy 00.41.03
by Robert Cimrman 26 Mar '08

26 Mar '08

Greetings, I'm pleased to announce the release 00.41.03 of SfePy (formerly SFE) SfePy is a finite element analysis software in Python, based primarily on Numpy and SciPy. Mailing lists, issue tracking, mercurial repository: http://code.google.com/p/sfepy/ Home page: http://sfepy.kme.zcu.cz Major improvements: - works on 64 bits - support for various mesh formats - Schroedinger equation solver - see http://code.google.com/p/sfepy/wiki/Examples - new solvers: - generic time-dependent problem solver - pysparse, symeig, scipy-based eigenproblem solvers - scipy-based iterative solvers - many new terms For information on this release, see http://sfepy.googlecode.com/svn/web/releases/004103_RELEASE_NOTES.txt Best regards, r.

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