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numpy-discussion@python.org

July 2009

105 participants
162 discussions

Tutorial topics for SciPy'09 Conference
by Fernando Perez 01 Jul '09

01 Jul '09

Hi all, The time for the Scipy'09 conference is rapidly approaching, and we would like to both announce the plan for tutorials and solicit feedback from everyone on topics of interest. Broadly speaking, the plan is something along the lines of what we had last year: one continuous 2-day tutorial aimed at introductory users, starting from the very basics, and in parallel a set of 'advanced' tutorials, consisting of a series of 2-hour sessions on specific topics. We will request that the presenters for the advanced tutorials keep the 'tutorial' word very much in mind, so that the sessions really contain hands-on learning work and not simply a 2-hour long slide presentation. We will thus require that all the tutorials will be based on tools that the attendees can install at least 2 weeks in advance on all platforms (no "I released it last night" software). With that in mind, we'd like feedback from all of you on possible topics for the advanced tutorials. We have space for 8 slots total, and here are in no particular order some possible topics. At this point there are no guarantees yet that we can get presentations for these, but we'd like to establish a first list of preferred topics to try and secure the presentations as soon as possible. This is simply a list of candiate topics that various people have informally suggested so far: - Mayavi/TVTK - Advanced topics in matplotlib - Statistics with Scipy - The TimeSeries scikit - Designing scientific interfaces with Traits - Advanced numpy - Sparse Linear Algebra with Scipy - Structured and record arrays in numpy - Cython - Sage - general tutorial - Sage - specific topics, suggestions welcome - Using GPUs with PyCUDA - Testing strategies for scientific codes - Parallel processing and mpi4py - Graph theory with Networkx - Design patterns for efficient iterator-based scientific codes. - Symbolic computing with sympy We'd like to hear from any ideas on other possible topics of interest, and we'll then run a doodle poll to gather quantitative feedback with the final list of candidates. Many thanks, f

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Advice on converting Numarray C extension?
by Russell E. Owen 01 Jul '09

01 Jul '09

I have an old Numarray C extension (or, rather, a Python package containing a C extension) that I would like to convert to numpy (in a way that is likely to be supported long-term). Options I have found include: - Use the new numpy extension. This seems likely to be fast and future-proof. But I am finding the documentation slow going. Does anyone know of a simple example (e.g. read in an array, create a new array)? - Use the Numarray compatible C API. Simple (and takes advantage of the nice Numarray tutorial example for documentation), but will this be supported in the long term? - Switch to ctypes. Simple in concept. But I'm wondering if I can get distutils to build the resulting package. - Use SWIG. I have some experience with it, but not with numpy arrays. - Use Cython to replace the C code. No idea if this is a long-term supported package. Another option is to try to rewrite in pure python. Perhaps the numpy indexing is sophisticated enough to allow an efficient solution. The C extension computes a radial profile from a 2-d masked array: radProf(r)= sum of all unmasked pixels at radius r about some specified center index I can easily generate (and cache) a 2-d array of radius index, but is it possible to use that to efficiently generate the desired sum? Any opinions? -- Russell

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