Mailman 3 April 2008 - NumPy-Discussion

Python Student Internship - National Renewable Energy Laboratory
by Chris Perkins 28 Apr '08

28 Apr '08

Student Intern – Scientific Computing Group 5900 5900-7259 A student internship is available in the National Renewable Energy Laboratory's (NREL) Scientific Computing Group. NREL is the nation's primary laboratory for research, development and deployment of renewable energy and energy efficiency technologies. The intern will be supporting work concerning management of scientific and technical data. Our data group is cutting-edge with respect to capturing rapidly changing scientific metadata and allowing the scientists to relate different kinds of data in a meaningful way. We have an immediate opening for a summer student internship with possible extension to one year in our Golden, Colorado office. The position would be part-time (15 - 25 hours per week) during the school year and/or full time during the summer. DUTIES: Will include working with researchers on techniques to enable the capture and storage of technical data in a scientific setting. Your role in our development team would be to support data harvesting using existing software, and develop new visualization techniques for existing data sets. DESIRED QUALIFICATIONS: Undergraduate or graduate student in computer science or related field, with demonstrated experience in programming, databases and software development. Experience using agile techniques and test-driven development. Demonstrated of Unit Testing. Experience with major dynamic languages like Python, Ruby, or C#. PREFERRED: Demonstrated good writing skills and computer skills, specifically including programming in python and database use. Experience with systems related to management of scientific data. Candidate must be a US citizen. Qualified candidates should e-mail their resume to: Laura Davis NREL, Human Resources Office Reference: Req. #5900-7259 E-Mail: laura_da...<http://groups.google.com/groups/unlock?msg=4f53e5a7a50c49c5&_done=/group/tu…> @nrel.gov ========================================= feel free to email me with any questions. cheers. -chris

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Linear Interpolation Question
by Andrea Gavana 28 Apr '08

28 Apr '08

Hi All, I have 2 matrices coming from 2 different simulations: the first column of the matrices is a date (time) at which all the other results in the matrix have been reported (simulation step). In these 2 matrices, very often the simulation steps do not coincide, so I just want to interpolate the results in the second matrix using the dates in the first matrix. The problem is, I have close to 13,000 columns in every matrices, and repeating interp1d all over the columns is quite expensive. An example of what I am doing is as follows: # Loop over all the columns for indx in indices: # Set up a linear interpolation with: # x = dates in the second simulation # y = single column in the second matrix simulation function = interp1d(secondaryMatrixDates, secondaryMatrixResults[:, indx], kind='linear') # Interpolate the second matrix results using the first simulation dates interpolationResults = function(mainMatrixDates) # I need the difference between the first simulation and the second newMatrix[:, indx] = mainMatrixResults[:, indx] - interpolationResults This is somehow a costly step, as it's taking up a lot of CPU (increasing at every iteration) and quite a long time (every column has about 350 data). Is there anything I can do to speed up this loop? Or may someone suggest a better approach? Thank you very much for your suggestions. Andrea. "Imagination Is The Only Weapon In The War Against Reality." http://xoomer.alice.it/infinity77/

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673
by Jarrod Millman 28 Apr '08

28 Apr '08

This has a patch: http://projects.scipy.org/scipy/numpy/ticket/673 Could someone review, comment or commit? Thanks, -- Jarrod Millman Computational Infrastructure for Research Labs 10 Giannini Hall, UC Berkeley phone: 510.643.4014 http://cirl.berkeley.edu/

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To wrap or not to wrap.
by Charles R Harris 28 Apr '08

28 Apr '08

Hi All, I'm working through the linalg module. There is currently variation as to whether or not eigenvalues/singular_values/residuals, are returned as arrays or as matrices. I'm leaning towards making them all matrices. But I expect masked arrays will also be preserved and I don't know what that will mean to people. What should be the standard here? Chuck

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What is __array_wrap__ supposed to do?
by Charles R Harris 27 Apr '08

27 Apr '08

Because it doesn't do what it says it does. In [31]: b.__array_wrap__(a).dtype Out[31]: dtype('float64') In [32]: a.__array_wrap__(b).dtype Out[32]: dtype('int8') In [33]: a Out[33]: array([[ 1., 1., 1.], [ 1., 1., 1.], [ 1., 1., 1.]]) In [34]: b Out[34]: array([[1, 1, 1], [1, 1, 1], [1, 1, 1]], dtype=int8) Here is what the docstring says: Help on method_descriptor: __array_wrap__(...) a.__array_wrap__(obj) -> Object of same type as a from ndarray obj. Chuck

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Threading question for Travis
by Charles R Harris 27 Apr '08

27 Apr '08

Travis, Is this correct? NPY_LOOP_BEGIN_THREADS; switch(loop->meth) { case ONE_UFUNCLOOP: /* * Everything is contiguous, notswapped, aligned, * and of the right type. -- Fastest. * Or if not contiguous, then a single-stride * increment moves through the entire array. */ /*fprintf(stderr, "ONE...%d\n", loop->size);*/ loop->function((char **)loop->bufptr, &(loop->size), loop->steps, loop->funcdata); UFUNC_CHECK_ERROR(loop); break; Note that UFUNC_CHECK_ERROR calls PyErr_Occurred. That doesn't seem thread safe to me. Or maybe there is something special about that function I'm missing. Chuck

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Request for advice: project to get NumPy working in IronPython
by Giles Thomas 26 Apr '08

26 Apr '08

Hi, At Resolver Systems, we have a product that is written in IronPython - the .NET Python implementation - and allows users to use that language to script a spreadsheet-like interface. Because they're using IronPython, they can access their existing .NET objects and libraries, which has worked out really well for us and for them. But there's an increasing number of users who would like access to CPython C extensions - in particular, NumPy. We *don't* want to just hack something together that would just allow users of our own product to access NumPy; what we'd really like to do is work on an OSS solution that will allow all IronPython users to access NumPy transparently, just as if they were using CPython. My question is, is this something that the readers of this list would like to get involved in, either in terms of contibuting, or even in terms on advice? We're under no illusions; this is a significant undertaking. And we're very keen on hearing from those who know NumPy better about how this should be structured, even if people don't have the time to write code for it. In particular: * How do people feel about a source-code-compatible solution, where (perhaps) we would maintain a project that basically provided an alternative makefile for NumPy - or, even better, we could work with the NumPy developers to contribute a .NET/IronPython package. * Would it be better to try for some kind of "binary compatibility", where we'd write some kind of "glue" that sat between the existing C extension .pyd files and the IronPython engine? Our gut feeling is that this would be much more work, but we might be missing something. * What should the work's relationship to the NumPy project be? Any thoughts, comments, or advice would be very much appreciated. Regards, Giles -- Giles Thomas MD & CTO, Resolver Systems Ltd. giles.thomas(a)resolversystems.com +44 (0) 20 7253 6372 We're hiring! http://www.resolversystems.com/jobs/ 17a Clerkenwell Road, London EC1M 5RD, UK VAT No.: GB 893 5643 79 Registered in England and Wales as company number 5467329. Registered address: 843 Finchley Road, London NW11 8NA, UK

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reshape docstrings conflicting
by Pauli Virtanen 26 Apr '08

26 Apr '08

Hi all, The ndarray.reshape docstring claims: "Also always returns a view or raises a ValueError if that is impossible." whereas fromnumeric.reshape claims: "This will be a new view object if possible; otherwise, it will be a copy." while the code paths for both functions are the same. So, which one of these is correct? Or, does ndarray.reshape always return a view? This is not immediately obvious looking at the code... I'll fix up the docstrings once I know. -- Pauli Virtanen

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tests in distutils/exec_command.py
by Zbyszek Szmek 26 Apr '08

26 Apr '08

Hi, while looking at test coverage statistics published Stéfan van der Walt at http://mentat.za.net/numpy/coverage/, I noticed that the least-covered file, numpy/distutils/exec_command.py has it's own test routines, e.g.: def test_svn(**kws): s,o = exec_command(['svn','status'],**kws) assert s,(s,o) print 'svn ok' called as if __name__ == "__main__": test_svn(use_tee=1) The sense of this test seems reversed (svn status runs just fine): Traceback (most recent call last): File "numpy/distutils/exec_command.py", line 591, in <module> test_svn(use_tee=1) File "numpy/distutils/exec_command.py", line 567, in test_svn assert s,(s,o) AssertionError: (0, '') Should the test be cleaned up and moved into a seperate file in numpy/distutils/tests/ ? Regard, Zbyszek

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Movement of ma breaks matplotlib
by Anne Archibald 26 Apr '08

26 Apr '08

Hi, In the upcoming release of numpy. numpy.core.ma ceases to exist. One must use numpy.ma (for the new interface) or numpy.oldnumeric.ma (for the old interface). This has the unfortunate effect of breaking matplotlib(which does "from numpy.core.ma import *") - I cannot even "import pylab" with a stock matplotlib (0.90.1) and an SVN numpy. Is this an intended effect? Anne

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