Mailman 3 May 2009 - SciPy-Dev

Hilbert-matrix
by Stéfan van der Walt May 20, 2009

May 20, 2009

Hi all, The Ill-conditioned Hilbert-matrix is often studied by students in numerical linear algebra, and as such I thought it might deserve a place in scipy.linalg. def hilbert(N): x, y = np.ogrid[1.:N+1, 1.:N+1] return 1 / (x + y - 1) The trickier issue, however, would be calculating the inverse -- does anybody have suggestions on how to implement it accurately? Ideally, we would have made use of Python's very long integers, but that would mean saving the array with dtype object. Regards Stéfan

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test_lgmres.py
by Nils Wagner May 19, 2009

May 19, 2009

Hi all, An import nose is missing in test_lgmres.py It works for me with: if __name__ == "__main__": import nose nose.run(argv=['', __file__]) Cheers, Nils

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SciPy 2009 Call for Papers
by Jarrod Millman May 18, 2009

May 18, 2009

========================== SciPy 2009 Call for Papers ========================== SciPy 2009, the 8th Python in Science conference, will be held from August 18-23, 2009 at Caltech in Pasadena, CA, USA. Each year SciPy attracts leading figures in research and scientific software development with Python from a wide range of scientific and engineering disciplines. The focus of the conference is both on scientific libraries and tools developed with Python and on scientific or engineering achievements using Python. We welcome contributions from the industry as well as the academic world. Indeed, industrial research and development as well academic research face the challenge of mastering IT tools for exploration, modeling and analysis. We look forward to hearing your recent breakthroughs using Python! Submission of Papers ==================== The program features tutorials, contributed papers, lightning talks, and bird-of-a-feather sessions. We are soliciting talks and accompanying papers (either formal academic or magazine-style articles) that discuss topics which center around scientific computing using Python. These include applications, teaching, future development directions, and research. A collection of peer-reviewed articles will be published as part of the proceedings. Proposals for talks are submitted as extended abstracts. There are two categories of talks: Paper presentations These talks are 35 minutes in duration (including questions). A one page abstract of no less than 500 words (excluding figures and references) should give an outline of the final paper. Proceeding papers are due two weeks after the conference, and may be in a formal academic style, or in a more relaxed magazine-style format. Rapid presentations These talks are 10 minutes in duration. An abstract of between 300 and 700 words should describe the topic and motivate its relevance to scientific computing. In addition, there will be an open session for lightning talks during which any attendee willing to do so is invited to do a couple-of-minutes-long presentation. If you wish to present a talk at the conference, please create an account on the website (http://conference.scipy.org). You may then submit an abstract by logging in, clicking on your profile and following the "Submit an abstract" link. Submission Guidelines --------------------- * Submissions should be uploaded via the online form. * Submissions whose main purpose is to promote a commercial product or service will be refused. * All accepted proposals must be presented at the SciPy conference by at least one author. * Authors of an accepted proposal can provide a final paper for publication in the conference proceedings. Final papers are limited to 7 pages, including diagrams, figures, references, and appendices. The papers will be reviewed to help ensure the high-quality of the proceedings. For further information, please visit the conference homepage: http://conference.scipy.org. Important Dates =============== * Friday, June 26: Abstracts Due * Saturday, July 4: Announce accepted talks, post schedule * Friday, July 10: Early Registration ends * Tuesday-Wednesday, August 18-19: Tutorials * Thursday-Friday, August 20-21: Conference * Saturday-Sunday, August 22-23: Sprints * Friday, September 4: Papers for proceedings due Tutorials ========= Two days of tutorials to the scientific Python tools will precede the conference. There will be two tracks: one for introduction of the basic tools to beginners and one for more advanced tools. Tutorials will be announced later. Birds of a Feather Sessions =========================== If you wish to organize a birds-of-a-feather session to discuss some specific area of scientific development with Python, please contact the organizing committee. Executive Committee =================== * Jarrod Millman, UC Berkeley, USA (Conference Chair) * Gaël Varoquaux, INRIA Saclay, France (Program Co-Chair) * Stéfan van der Walt, University of Stellenbosch, South Africa (Program Co-Chair) * Fernando Pérez, UC Berkeley, USA (Tutorial Chair)

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f2py vector valued functions and optimize.fmin_slsqp
by Leon Adams May 18, 2009

May 18, 2009

Hi... I am experiencing some difficulties arriving at a soln for my optimization problem. Background: My problem is cast as a minimizer problem but is very computer intense (lots of loops). My design soln was to wrap the looping parts in FORTRAN using f2py, use python as a steering program and optimize.fmin_slsqp as the optimizer. Everything seems to work well for scalar valued functions but not for vector valued functions involving arrays. Anytime an array is involved SLSQP returns with a success exit status [0] without updating the input vector. That is no change is being made to the input parameters. My question is: is it possible to wrap a vector valued fortran function and still use SLSQP? Thanks in advance -- Leon Adams

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binary compatibility question
by josef.pktd＠gmail.com May 17, 2009

May 17, 2009

I didn't follow the discussion of binary compatibility between different versions very closely. I compiled scipy 0.7.1 against numpy 1.3.0 and ran it in a virtualenv against numpy 1.2.1 and I get an immediate segfault when trying to run scipy.test(). I get the usual 4 failures when I run scipy with numpy 1.3.0 Is this expected? (I didn't do it on purpose, the version mismatch was just a consequence of how I wanted to setup my testing environment for scipy 0.7.1 and is easily fixed) Josef

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ReST tutorial - where should it go?
by Matthew Brett May 16, 2009

May 16, 2009

Hello, I think this one is for the documentation gurus. For a talk I did today, I made a quick introduction to matlab IO in ReST, copy here: https://cirl.berkeley.edu/mb312/nss/matlab_io.html It seemed like a good idea to put it somewhere in the Scipy source tree docs, but I wasn't quite sure where... Thanks a lot, Matthew

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Should ndimage.measurements.* should return lists if index is a list?
by Thouis (Ray) Jones May 15, 2009

May 15, 2009

Current behavior: >>> from scipy import ndimage >>> ndimage.maximum([[1,2], [3,4]], [[1,0],[0,2]], index=[1,2]) [1.0, 4.0] >>> ndimage.maximum([[1,2], [3,4]], [[1,0],[0,2]], index=[1]) 1.0 >>> ndimage.maximum([[1,2], [3,4]], [[1,0],[0,2]], index=1) 1.0 I think the second result should be [1.0]. We're using the ndimage code for image processing, and have to wrap the measurement functions to make the code general for the case where there is only one object in the image. Less important, though it might make sense, is to have this code return [] rather than raising an exception: >>> ndimage.maximum([[1,2], [3,4]], [[1,0],[0,2]], index=[]) Ray Jones

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backporting changes in scipy.stats
by josef.pktd＠gmail.com May 15, 2009

May 15, 2009

Most of the changes in scipy.stats could be backported to scipy 7.1 changesets: 5591, 5592, 5597, 5599, 5601, 5600, 5602, 5604, 5623, 5636, 5637, 5638, 5646, 5672(replay) are (mostly) bugfixes and improvement in numerical precision. changesets: 5598, 5645 are additional tests changesets: 5562, 5564, 5565, 5566, 5567, 5587 are switching to np.mean, np.var and can be backported or not I never did any backporting and I'm currently not set up for it. I would appreciate if someone could backport these changes, otherwise I will try to do it next weekend. Thanks, Josef

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Broken Link in "Getting Started"
by Skipper Seabold May 15, 2009

May 15, 2009

Sorry if this is the wrong place to report this, but I was curious if I'm getting the most out of using ipython and saw a link to an article that is broken on the "Getting Started" page here <http://www.scipy.org/Getting_Started?action=show#head-9aed725bd569d40f62524…> at the end of the second to last bullet point. Was curious if #549 here <http://amath.colorado.edu/activities/preprints/> might be the same article and a more stable link. Cheers, Skipper

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Question about editing docs
by Skipper Seabold May 13, 2009

May 13, 2009

I've been going through scipy.stats.mstats and the tests to get a better feel for masked arrays and how they are handled for statistical functions. I noticed what I believed to be an error in the examples of the docstring for mstats_basic.count_tied_groups, which I corrected here: <http://docs.scipy.org/scipy/docs/scipy.stats.mstats_basic.count_tied_groups/>. My question is (as you can see) I had to also correct some formatting (and there is still some to be done), but I don't think I should be doing this kind of thing incrementally. Or should I? Is there another way I can edit multiple docstrings to get them to conform to the numpy standard and rst when I notice something or is this best left to someone else? I see that mstats_basic "Needs Editing." Sorry if I'm missing something obvious. This wouldn't be the first time...today. Cheers, Skipper

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