Mailman 3 October 2012 - SciPy-User

Bessel function of complex order
by Andreas Pritschet Oct. 5, 2012

Oct. 5, 2012

Hi, I have noticed in the docs and some "bug reports" that Bessel functions in SciPy support only real order. But for my work I require a modified Bessel function of second kind of complex(!) order for complex values. Is in SciPy a chance of calculating something like scipy.special.kv(1j*k,1j), whereby k is an array?? Thanks and best regards Andi -- Andreas Pritschet Phone: +49 151 11728439 Homepage: http://www.pritschet.me GPG Pub Key: http://goo.gl/4mOsM

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ANN: WinPython v2.7.3.1
by Pierre Raybaut Oct. 5, 2012

Oct. 5, 2012

Hi all, WinPython v2.7.3.1 has been released and is available for 32-bit and 64-bit Windows platforms: http://code.google.com/p/winpython/ WinPython is a free open-source portable distribution of Python for Windows, designed for scientists. It is a full-featured (see http://code.google.com/p/winpython/wiki/PackageIndex) Python-based scientific environment: * Designed for scientists (thanks to the integrated libraries NumPy, SciPy, Matplotlib, guiqwt, etc.: * Regular *scientific users*: interactive data processing and visualization using Python with Spyder * *Advanced scientific users and software developers*: Python applications development with Spyder, version control with Mercurial and other development tools (like gettext) * *Portable*: preconfigured, it should run out of the box on any machine under Windows (without any installation requirements) and the folder containing WinPython can be moved to any location (local, network or removable drive) * *Flexible*: one can install (or should I write "use" as it's portable) as many WinPython versions as necessary (like isolated and self-consistent environments), even if those versions are running different versions of Python (2.7, 3.x in the near future) or different architectures (32bit or 64bit) on the same machine * *Customizable*: using the integrated package manager (wppm, as WinPython Package Manager), it's possible to install, uninstall or upgrade Python packages (see http://code.google.com/p/winpython/wiki/WPPM for more details on supported package formats). *WinPython is not an attempt to replace Python(x,y)*, this is just something different (see http://code.google.com/p/winpython/wiki/Roadmap): more flexible, easier to maintain, movable and less invasive for the OS, but certainly less user-friendly, with less packages/contents and without any integration to Windows explorer [*]. [*] Actually there is an optional integration into Windows explorer, providing the same features as the official Python installer regarding file associations and context menu entry (this option may be activated through the WinPython Control Panel). Enjoy!

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Re: [SciPy-User] Scipy stack: standard packages (poll)
by Dharhas Pothina Oct. 4, 2012

Oct. 4, 2012

Hi, I just voted on the poll, but i think the issue of whether package will be in epd free or not is kinda orthogonal to this discussion. I realize that having all the 'standard' packages in epd free would be an awesome thing but isn't that a business decision enthought needs to make. Epd is not the only way to get packages installed, but it is a very convenient one and if enthought wants to make epd free with a more limited subset of packages and have the full licensed epd be the standard compliant version, I don't see anything really wrong with that. After all they are providing a value added service by doing the cross platform packaging. Dharhas >>> Thomas Kluyver <takowl(a)gmail.com> 10/04/12 13:41 PM >>> On 4 October 2012 14:27, Thomas Kluyver <takowl(a)gmail.com> wrote: > The biggest remaining question (as I see it) is the hdf5 libraries. > Both have got a somewhat mixed response on the poll, although h5py has > a bit more support than PyTables. This did come up before, but let's > hear more voices on the question. Should we specify neither, one, or > both? Discussion on the numfocus list has come to the conclusion that we should either specify both h5py and PyTables, or neither. Please register your opinion on this new poll: http://www.misterpoll.com/polls/568484 To be clear, I'm using all these polls to gauge what a larger number of people think. It's like Wikipedia's "!voting" model - the option with the most votes doesn't automatically win, but it's used to form a consensus. Thanks, Thomas _______________________________________________ SciPy-User mailing list SciPy-User(a)scipy.org http://mail.scipy.org/mailman/listinfo/scipy-user

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ANN: HDF5 for Python (h5py) 2.1.0-final
by Andrew Collette Oct. 4, 2012

Oct. 4, 2012

Announcing HDF5 for Python (h5py) 2.1.0 ======================================= We are proud to announce the availability of HDF5 for Python (h5py) 2.1.0! This release has been a long time coming. Thanks to everyone who contributed code and filed bug reports! What's new in h5py 2.1 ----------------------- * The HDF5 Dimension Scales API is now available, along with high-level integration with Dataset objects. Thanks to D. Dale for implementing this. * Unicode scalar strings can now be stored in attributes. * Dataset objects now expose a .size property giving the total number of elements. * Many performance improvements and bug fixes About the project ----------------------- HDF5 for Python (h5py) is a general-purpose Python interface to the Hierarchical Data Format library, version 5. HDF5 is a mature scientific software library originally developed at NCSA, designed for the fast, flexible storage of enormous amounts of data. >From a Python programmer's perspective, HDF5 provides a robust way to store data, organized by name in a tree-like fashion. You can create datasets (arrays on disk) hundreds of gigabytes in size, and perform random-access I/O on desired sections. Datasets are organized in a filesystem-like hierarchy using containers called "groups", and accessed using the traditional POSIX /path/to/resource syntax. Downloads, FAQ and bug tracker are available at Google Code: * Google code site: http://h5py.googlecode.com Documentation is available at Alfven.org: * http://h5py.alfven.org

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Dot product of two arrays of vectors
by Alexander Kalinin Oct. 4, 2012

Oct. 4, 2012

Hello, SciPy, Could you, please, explain me, what is the most standard way in NumPy to calculate a dot product of two arrays of vectors, like in MatLab? For example, consider two numpy arrays of vectors: a = np.array([[1, 2, 3], [4, 5, 6]]) b = np.array([[3, 2, 1], [6, 5, 4]]) For the cross product we have convenient function numpy.cross: >>> np.cross(a, b) array([[ -4, 8, -4], [-10, 20, -10]]) But the numpy.dot product for the arrays of vectors do the matrix multiplication: >>> np.dot(a, b) Traceback (most recent call last): File "<stdin>", line 1, in <module> ValueError: objects are not aligned Yes, I can emulate the dot product code like: np.sum(a * b, axis = 1).reshape(-1, 1) but may be there is exist more standard way to do the dot product? Sincerely, Alexander

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Fitting Gaussian in spectra
by Joe Philip Ninan Oct. 4, 2012

Oct. 4, 2012

Hi, I have a spectra with multiple gaussian emission lines over a noisy continuum. My primary objective is to find areas under all the gaussian peaks. For that, the following is the algorithm i have in mind. 1) fit the continuum and subtract it. 2) find the peaks 3) do least square fit of gaussian at the peaks to find the area under each gaussian peaks. I am basically stuck at the first step itself. Simple 2nd or 3rd order polynomial fit is not working because the contribution from peaks are significant. Any tool exist to fit continuum ignoring the peaks? For finding peaks, i tried find_peaks_cwt in signal module of scipy. But it seems to be quite sensitive of the width of peak and was picking up non-existing peaks also. The wavelet used was default mexican hat. Is there any better wavelet i should try? Or is there any other module in python/scipy which i should give a try? Thanking you. -cheers joe -- /--------------------------------------------------------------- "GNU/Linux: because a PC is a terrible thing to waste" - GNU Generation

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[ANN] MDP-3.3 released!
by Tiziano Zito Oct. 4, 2012

Oct. 4, 2012

We are glad to announce release 3.3 of the Modular toolkit for Data Processing (MDP). This a bug-fix release, all current users are invited to upgrade. MDP is a Python library of widely used data processing algorithms that can be combined according to a pipeline analogy to build more complex data processing software. The base of available algorithms includes signal processing methods (Principal Component Analysis, Independent Component Analysis, Slow Feature Analysis), manifold learning methods ([Hessian] Locally Linear Embedding), several classifiers, probabilistic methods (Factor Analysis, RBM), data pre-processing methods, and many others. What's new in version 3.3? -------------------------- - support sklearn versions up to 0.12 - cleanly support reload - fail gracefully if pp server does not start - several bug-fixes and improvements Resources --------- Download: http://sourceforge.net/projects/mdp-toolkit/files Homepage: http://mdp-toolkit.sourceforge.net Mailing list: http://lists.sourceforge.net/mailman/listinfo/mdp-toolkit-users Acknowledgments --------------- We thank the contributors to this release: Philip DeBoer, Yaroslav Halchenko. The MDP developers, Pietro Berkes Zbigniew Jędrzejewski-Szmek Rike-Benjamin Schuppner Niko Wilbert Tiziano Zito

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scipy spiking in Google trends?
by Michael Aye Oct. 4, 2012

Oct. 4, 2012

Hi! I noticed that scipy is spiking for a couple of weeks in Google trends. Anybody would know where this comes from? See the curve here: http://www.google.com/trends/explore#q=scipy&cmpt=q Beautiful long term increase this curve shows! ;) Best, Michael

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Autoblock?
by The Helmbolds Oct. 2, 2012

Oct. 2, 2012

When attempting to install SciPy 0.11.0, Webroot blocks installation with message: Win32.Autoblock.1 detected Autoblock appears to be a virus. Now what? Bob and Paula H

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Re: [SciPy-User] Pylab - standard packages
by William Furnass Oct. 2, 2012

Oct. 2, 2012

Something that could raise awareness and expedite the adoption of the Pylab standard under Linux would be the availability of repositories for some of the most common distributions (e.g. Ubuntu, Fedora, RHEL-a-likes). As a number of distributions take a while to catch up with the latest releases of ipython etc making Ubuntu PPA and repos.fedorapeople.org repositories available could provide people with a familar, quick and easy means to install Pylab. Not sure whether we would want distribution package managers automatically upgrading packages though when new Pylab standards/packages are released. Any thoughts? On a related note it might be a good opportunity to bring the fairly-official-looking Scipy PPA [1] up to date. [1] https://launchpad.net/~scipy/+archive/ppa Cheers, Will

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