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From: <ben...@id...> - 2004-05-25 09:14:13
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Dear Open Source developer I am doing a research project on "Fun and Software Development" in which I kindly invite you to participate. You will find the online survey under http://fasd.ethz.ch/qsf/. The questionnaire consists of 53 questions and you will need about 15 minutes to complete it. With the FASD project (Fun and Software Development) we want to define the motivational significance of fun when software developers decide to engage in Open Source projects. What is special about our research project is that a similar survey is planned with software developers in commercial firms. This procedure allows the immediate comparison between the involved individuals and the conditions of production of these two development models. Thus we hope to obtain substantial new insights to the phenomenon of Open Source Development. With many thanks for your participation, Benno Luthiger PS: The results of the survey will be published under http://www.isu.unizh.ch/fuehrung/blprojects/FASD/. We have set up the mailing list fa...@we... for this study. Please see http://fasd.ethz.ch/qsf/mailinglist_en.html for registration to this mailing list. _______________________________________________________________________ Benno Luthiger Swiss Federal Institute of Technology Zurich 8092 Zurich Mail: benno.luthiger(at)id.ethz.ch _______________________________________________________________________ |
From: Alexander P. <Ale...@no...> - 2004-04-01 13:09:11
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All scientific python users, Pypspline 0.13 has been released! Pypspline allows python users to perform spline interpolations faster than Matlab's spline toolbox. A factor 6 faster was observed for 3D grid-array interpolation, a higher factor for point interpolation (loops are known to be very slow in Matlab). Some of Pypspline's features are: * support for cubic spline, bi-cubic spline and tri-cubic spline * control of boundary conditions (not-a-knot, periodic, 1st derivative, or 2nd derivative) * Float64 or Float32 * compute derivatives up to second order (mixed derivatives in 2 and 3D) * methods come in 3 flavors: single point, cloud (scattered points) or array interpolation. Array interpolation is fastest but applies to interpolating onto a structured mesh. Cloud interpolation can be used to interpolate from a structured to an unstructured mesh, for instance. * easy to use and flexible * fast (millions of interpolations per second) Pypspline is free and is based on PSPLINE (http://w3.pppl.gov/rib/repositories/NTCC/catalog/Asset/pspline.html), which requires a fortran 90 and C compiler. Tested with Intel 8.0 ifort, pg90, Lahey-Futjitsu on Linux and native SGi f90 on IRIX, and gcc. Enjoy, --Alex. |