Mailman 3 March 2013 - SciPy-User

Invitation to connect on LinkedIn
by Harshad Surdi via LinkedIn March 10, 2013

March 10, 2013

LinkedIn ------------ Harshad Surdi requested to add you as a connection on LinkedIn: ------------------------------------------ Jose, I'd like to add you to my professional network on LinkedIn. - Harshad Accept invitation from Harshad Surdi http://www.linkedin.com/e/-3wy1w2-he3sdqrd-33/Q6WKH0LACopGJkAw_6fSqajo6R7VM… View profile of Harshad Surdi http://www.linkedin.com/e/-3wy1w2-he3sdqrd-33/rso/235918465/oHlG/name/21555… ------------------------------------------ You are receiving Invitation emails. This email was intended for Jose Gomez-Dans. Learn why this is included: http://www.linkedin.com/e/-3wy1w2-he3sdqrd-33/plh/http%3A%2F%2Fhelp%2Elinke… (c) 2012, LinkedIn Corporation. 2029 Stierlin Ct, Mountain View, CA 94043, USA.

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SciPy John Hunter Excellence in Plotting Contest
by Michael Droettboom March 8, 2013

March 8, 2013

Apologies for any accidental cross-posting. Email not displaying correctly? View it in your browser. <http://us1.campaign-archive1.com/?u=e91b4574d5d1709a9dc4f7ab7&id=999d7ba343…> Scientific Computing with Python-Austin, Texas-June 24-29, 2013 SciPy John Hunter Excellence in Plotting Contest In memory of John Hunter, we are pleased to announce the first SciPy John Hunter Excellence in Plotting Competition. This open competition aims to highlight the importance of quality plotting to scientific progress and showcase the capabilities of the current generation of plotting software. Participants are invited to submit scientific plots to be judged by a panel. The winning entries will be announced and displayed at the conference. NumFOCUS is graciously sponsoring cash prizes for the winners in the following amounts: * 1st prize: $500 * 2nd prize: $200 * 3rd prize: $100 Instructions * Entries must be submitted by April 3 via e-mail <mailto:plotting-contest@scipy.org>. * Plots may be produced with any combination of Python-based tools (it is not required that they use matplotlib, for example). * Source code for the plot must be provided, along with a rendering of the plot in a vector format (PDF, PS, etc.). If the data can not be shared for reasons of size or licensing, "fake" data may be substituted, along with an image of the plot using real data. * Entries will be judged on their clarity, innovation and aesthetics, but most importantly for their effectiveness in illuminating real scientific work. Entrants are encouraged to submit plots that were used during the course of research, rather than merely being hypothetical. * SciPy reserves the right to display the entry at the conference, use in any materials or on its website, providing attribution to the original author(s). Important dates: * April 3rd: Plotting submissions due * Monday-Tuesday, June 24 - 25: SciPy 2013 Tutorials, Austin TX * Wednesday-Thursday, June 26 - 27: SciPy 2013 Conference, Austin TX * Winners will be announced during the conference days * Friday-Saturday, June 27 - 28: SciPy 2013 Sprints, Austin TX & remote We look forward to exciting submissions that push the boundaries of plotting, in this, our first attempt at this kind of competition. The SciPy Plotting Contest Organizer -Michael Droettboom, Space Telescope Science Institute You are receiving this email because you subscribed to the mailing list or registered for the SciPy 2010 or SciPy 2011 conference in Austin, TX. Unsubscribe <http://scipy.us1.list-manage.com/unsubscribe?u=e91b4574d5d1709a9dc4f7ab7&id…> mdboom(a)gmail.com <mailto:mdboom@gmail.com> from this list | Forward to a friend <http://us1.forward-to-friend1.com/forward?u=e91b4574d5d1709a9dc4f7ab7&id=99…> | Update your profile <http://scipy.us1.list-manage.com/profile?u=e91b4574d5d1709a9dc4f7ab7&id=069…> *Our mailing address is:* Enthought, Inc. 515 Congress Ave. Austin, TX 78701 Add us to your address book <http://scipy.us1.list-manage.com/vcard?u=e91b4574d5d1709a9dc4f7ab7&id=069dc…> /Copyright (C) 2013 Enthought, Inc. All rights reserved./ -- Michael Droettboom http://www.droettboom.com/

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Question about the position and orientation of the 2dcircle in Mayavi's quiver3d plotting function
by Martin van Leeuwen March 8, 2013

March 8, 2013

Dear Python users, I am using the Mayavi toolkit quite a bit, because it is a very nicely packaged 3D visualization toolkit. I use it mainly for displaying triangle meshes and point cloud data, but recently I found it necessary to visualize disks as well. The mayavi.mlab.quiver3d() function seems to be adequate for this, however its '2dcircles' are oriented contrary to what I expected. I expected that these 2dcircles would be oriented so that their normal vectors would point in the direction that a normal '2darrow' would point to, but it doesn't. Instead, the normal vector of the 2dcircle is orthogonal to the direction of the 2darray. In addition the 2dcircle is not centered on the 3D point (specified by the x,y,z input arrays), but touches it. Is there a way around this? Or is there another function I overlooked that centers the circles onto a 3D coordinate? Thanks in advance! Any help is appreciated. Martin

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Efficiently adding a vector to every row of a sparse CSR matrix?
by Brendan Dolan-Gavitt March 8, 2013

March 8, 2013

Hi, As part of implementing a batch calculation of Jensen-Shannon divergence, I need to take a (sparse) 65536-element vector "V" and add it to every row of a (sparse) 500000x65536 matrix "O" of observations. Is there any way to do this that is both space and time efficient? The usual O+V tries to convert O to a dense matrix, which fails because O is too big to fit in memory (it would take up ~120 GB!). I also can't do it slowly via iteration, because it looks like it's not possible to update a sparse matrix in place. My current solution is to tile V into a new 500000x65536 matrix and then add: import numpy as np import sparse as sp [...] V = sp.csr_matrix(V) # Create the CSR matrix directly Vindptr = np.arange(0, len(V.indices)*O.shape[0]+1, len(V.indices), dtype=np.int32) Vindices = np.tile(V.indices, O.shape[0]) Vdata = np.tile(V.data, O.shape[0]) mV = sp.csr_matrix((Vdata, Vindices, Vindptr), shape=O.shape) result = O+mV This is reasonably fast (though creating mV takes around 6 seconds on its own), but takes up a lot of memory to store even though there's a ton of duplicate data. Is there any way to do this efficiently? It seems like there ought to be... -Brendan

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A NonLinearModelFit algorithm
by Martin Harrison March 7, 2013

March 7, 2013

Hi All - I am very new to scipy so bare with me please :-) I have been using mathematica recently to mess around with my data. I have a method of calculating an x,y coordinate from 2 or more distance measurements coming from static devices (also x,y coords). The function I use to do this most effectively with the data I have is the mathematica function: NonlinearModelFit[data, Norm[{x, y} - {x0, y0}], {x0, y0}, {x, y}, Weights -> 1/observations^2] where... data = {{548189.217202, 5912779.96059, 93}, {548236.967784, 5912717.80716, 39}, {548359.406452, 5912752.54022, 88}, {548358.636206, 5912690.89573, 97}}; observations = {93, 39, 88, 97}; x0, y0 is my solution The mathematica output to the above is: FittedModel[{"Nonlinear", {x0 -> *548334.5910278788*, y0 -> * 5.912703316316227*^6*}, {{x, y}, Sqrt[Abs[x - x0]^2 + Abs[y - y0]^2]}}, {{1/9604, 1/16900, 1/3249, 1/676, 1/900}}, {{548236.967784, 5.91271780716*^6, 98}, {548236.967784, 5.91271780716*^6, 130}, {548359.406452, 5.91275254022*^6, 57}, {548358.636206, 5.91269089573*^6, 26}, {548358.636206, 5.91269089573*^6, 30}}, Function[Null, Internal`LocalizedBlock[{x, x0, y, y0}, #1], {HoldAll}]] Figures in bold are my x0,y0 solution. So I am not fitting a curve but fitting to a point (with weights inversely proportional to the squared distance). I have looked around on google but am simply not sure where to start with this. Any help with this would be very much appreciated. So why am I doing this if mathematica does it? Well to call mathematicascript (using subprocess module) from python code is too slow for what I want to do with live data so want to try rewriting in python to see if the speed can be improved....

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pupynere/scipy.io.netcdf
by Ryan May March 6, 2013

March 6, 2013

Hi, Anyone know if pupynere (a version of which is in scipy.io.netcdf) supports writing files with 64-bit offsets? This allows writing files larger than 2GB. Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma

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Announcement: Release of scikits-image 0.8.0
by Johannes Schönberger March 4, 2013

March 4, 2013

Announcement: scikits-image 0.8.0 ================================= We're happy to announce the 8th version of scikit-image! scikit-image is an image processing toolbox for SciPy that includes algorithms for segmentation, geometric transformations, color space manipulation, analysis, filtering, morphology, feature detection, and more. For more information, examples, and documentation, please visit our website: http://scikit-image.org New Features ------------ - New rank filter package with many new functions and a very fast underlying local histogram algorithm, especially for large structuring elements `skimage.filter.rank.*` - New function for small object removal `skimage.morphology.remove_small_objects` - New circular hough transformation `skimage.transform.hough_circle` - New function to draw circle perimeter `skimage.draw.circle_perimeter` and ellipse perimeter `skimage.draw.ellipse_perimeter` - New dense DAISY feature descriptor `skimage.feature.daisy` - New bilateral filter `skimage.filter.denoise_bilateral` - New faster TV denoising filter based on split-Bregman algorithm `skimage.filter.denoise_tv_bregman` - New linear hough peak detection `skimage.transform.hough_peaks` - New Scharr edge detection `skimage.filter.scharr` - New geometric image scaling as convenience function `skimage.transform.rescale` - New theme for documentation and website - Faster median filter through vectorization `skimage.filter.median_filter` - Grayscale images supported for SLIC segmentation - Unified peak detection with more options `skimage.feature.peak_local_max` - `imread` can read images via URL and knows more formats `skimage.io.imread` Additionally, this release adds lots of bug fixes, new examples, and performance enhancements. Contributors to this release ---------------------------- This release was only possible due to the efforts of many contributors, both new and old. - Adam Ginsburg - Anders Boesen Lindbo Larsen - Andreas Mueller - Christoph Gohlke - Christos Psaltis - Colin Lea - François Boulogne - Jan Margeta - Johannes Schönberger - Josh Warner (Mac) - Juan Nunez-Iglesias - Luis Pedro Coelho - Marianne Corvellec - Matt McCormick - Nicolas Pinto - Olivier Debeir - Paul Ivanov - Sergey Karayev - Stefan van der Walt - Steven Silvester - Thouis (Ray) Jones - Tony S Yu

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EuroSciPy 2013 Call for Abstracts
by Tiziano Zito March 4, 2013

March 4, 2013

Dear Scientist using Python, EuroSciPy 2013, the Sixth Annual Conference on Python in Science, takes place in Brussels on 21 - 24 August 2013. The conference features two days of tutorials followed by two days of scientific talks that start with our keynote speakers, Cameron Neylon and Peter Wang. The topics presented at EuroSciPy are very diverse, with a focus on advanced software engineering and original uses of Python and its scientific libraries, either in theoretical or experimental research, from both academia and the industry. The program includes contributed talks and posters. Submissions for talks and posters are welcome on our website (http://www.euroscipy.org/). Authors must use the web interface to submit an abstract to the conference. In your abstract, please provide details on what Python tools are being employed, and how. The deadline for submission is 28 April 2013. Until 31 March 2013, you can apply for a sprint session on 25 August 2013. Also, potential organizers for EuroSciPy 2014 are welcome to contact the conference committee. SciPythonic Regards, The EuroSciPy 2013 Committee http://www.euroscipy.org/ Conference Chairs: Pierre de Buyl and Nicolas Pettiaux, Université libre de Bruxelles, Belgium Tutorial Chair: Nicolas Rougier, INRIA, Nancy, France Program Chair: Tiziano Zito, Humboldt-Universität zu Berlin, Germany Program Committee Ralf Gommers, ASML, The Netherlands Emmanuelle Gouillart, Joint Unit CNRS/Saint-Gobain, France Kael Hanson, Université Libre de Bruxelles, Belgium Konrad Hinsen, Centre National de la Recherche Scientifique (CNRS), France Hans Petter Langtangen, Simula and University of Oslo, Norway Mike Müller, Python Academy, Germany Raphael Ritz, International Neuroinformatics Coordinating Facility, Stockholm, Sweden Stéfan van der Walt, Applied Mathematics, Stellenbosch University, South Africa Gaël Varoquaux, INRIA Parietal, Saclay, France Nelle Varoquaux, Mines ParisTech, France Pauli Virtanen, Aalto University, Finland Organizing Committee Nicolas Chauvat, Logilab, France Emmanuelle Gouillart, Joint Unit CNRS/Saint-Gobain, France Kael Hanson, Université Libre de Bruxelles, Belgium Renaud Lambiotte, University of Namur, Belgium Thomas Lecocq, Royal Observatory of Belgium Mike Müller, Python Academy, Germany Didrik Pinte, Enthought Europe Gaël Varoquaux, INRIA Parietal, Saclay, France Nelle Varoquaux, Mines ParisTech, France

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Invitation to connect on LinkedIn
by Harshad Surdi via LinkedIn March 3, 2013

March 3, 2013

LinkedIn ------------ Harshad Surdi requested to add you as a connection on LinkedIn: ------------------------------------------ Jose, I'd like to add you to my professional network on LinkedIn. - Harshad Accept invitation from Harshad Surdi http://www.linkedin.com/e/-3wy1w2-hdtmo3b0-4v/Q6WKH0LACopGJkAw_6fSqajo6R7VM… View profile of Harshad Surdi http://www.linkedin.com/e/-3wy1w2-hdtmo3b0-4v/rso/235918465/oHlG/name/21555… ------------------------------------------ You are receiving Invitation emails. This email was intended for Jose Gomez-Dans. Learn why this is included: http://www.linkedin.com/e/-3wy1w2-hdtmo3b0-4v/plh/http%3A%2F%2Fhelp%2Elinke… (c) 2012, LinkedIn Corporation. 2029 Stierlin Ct, Mountain View, CA 94043, USA.

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Survey for framework and library developers: "Information needs in software ecosystems"
by Nicole Haenni March 3, 2013

March 3, 2013

Hi, I’m Nicole Haenni and I'm doing research for my thesis at the University of Berne (scg.unibe.ch) with Mircea Lungu and Niko Schwarz. We are researching on monitoring the activity in software ecosystems. This is a study about information needs that arise in such software ecosystems. I need your help to fill out the survey below. It takes about 10 minutes to complete it. A software ecosystem can be a project repository like GitHub, an open source community (e.g. the Apache community) or a language-based community (e.g. Smalltalk has Squeaksource, Ruby has Rubyforge). We formulate our research question as follows: "What information needs arise when developers use code from other projects, or see their own code used elsewhere." Survey link: http://bit.ly/14Zc71N or original link: https://docs.google.com/spreadsheet/viewform?formkey=dFBJUmVodVU1V3BMMGRPRW… Thank you for your support! Nicole Haenni ----------------------------------------- Software Composition Group Institut für Informatik Universität Bern Neubrückstrasse 10 CH-3012 Bern SWITZERLAND

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