Re: [Numpy-discussion] Citing Numeric and numpy
Thank you Ryan Alan for the feedback - the three references are summarized here for anyone searching for the citations in future. The recent overview was: Travis E. Oliphant, Python for Scientific Computing, Computing in Science Engineering, vol. 9, no. 3, May/June 2007, pp. 10-20. Numerical Python citation, available online at: http://numpy.scipy.org/numpydoc/numpy.html D. Ascher et al., Numerical Python, tech. report UCRL-MA-128569, Lawrence Livermore National Laboratory, 2001; http://numpy.scipy.org. NumPy book citation, see also http://www.tramy.us for details: Travis E. Oliphant (2006) Guide to NumPy, Trelgol Publishing, USA; http://numpy.scipy.org. Cheers, Peter ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Error code of NumpyTest()
On Fri, August 24, 2007 11:41 am, Matthieu Brucher wrote: Hi, I wondered if there was a way of returning another error code than 0 when executing the test suite so that a parent process can immediately know if all the tests passed or not. The numpy buildbot seems to have the same behaviour BTW. I don't know if it is possible, but it would be great. The svn version of test() function now returns TestResult object. So, test() calls in buildbot should read: import numpy,sys; sys.exit(not numpy.test(verbosity=,level=).wasSuccessful()) Hopefully buildbot admins can update the test commands accordingly. Pearu ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Error code of NumpyTest()
Thank you for the answer The svn version of test() function now returns TestResult object. Numpy 1.3.x does not provide this ? I can't upgrade the numpy packages on the Linux boxes (on the Windows box, I suppose that I could use an Enthought egg). So, test() calls in buildbot should read: import numpy,sys; sys.exit(not numpy.test(verbosity=,level=).wasSuccessful()) Hopefully buildbot admins can update the test commands accordingly. I'll be able to do this as the tests are located on the repository. Matthieu ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Units; was Bug or surprising undocumented behaviour in irfft
Do you know if there's a current package to associate units with numpy arrays? For my purposes it would usually be sufficient to have arrays of quantities with uniform units. Conversions need only be multiplicative (I don't care about Celsius-to-Fahrenheit style conversions) and need not even be automatic, though of course that would be convenient. Right now I use Frink for that sort of thing, but it would have saved me from making a number of minor mistakes in several pieces of python code I've written. Anne, We have an enthought.units package in ETS, and for unit-ed numpy arrays we have (fairly new) UnitArray and UnitScalar in enthought.numerical_modeling.units.api Automatic conversions on arithmetic expressions are not performed; however, we do have a @has_units function decorator that will perform unit conversions on function inputs automatically (and will label--but not convert--the outputs of a function) If you are interested in checking it out I can get you more information/examples. Bryan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Accessing a numpy array in a mmap fashion
Hello all, I'm wondering if there is a way to use a numpy array that uses disk as a memory store rather than ram. I'm looking for something like mmap but which can be used like a numpy array. The general idea is this. I'm simulating a system which produces a large dataset over a few hours of processing time. Rather than store the numpy array in memory during processing I'd like to write the data directly to disk but still be able to treat the array as a numpy array. Is this possible? Any ideas? Thanks, Brian -- Brian Donovan Research Assistant Microwave Remote Sensing Lab UMass Amherst ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] numpy build fails on powerpc ydl
My build of numpy fails under Yellow Dog Linux 2.1, running on a powerpc multiprocessor board from Curtiss-Wright. Its kernel is 2.4.19-Asmp tailored by the vendor. The gcc compiler is configured as ppc-yellowdog-linux with version number 2.95.3 20010111. The python I'm using is Python 2.5.1 (r251:54863) installed as python2. Plain /usr/bin/python is 1.5.x . The numpy version I'm trying to build is r4003 for v1.0.4 . The setup fails compiling build/src.linux-ppc-2.5/numpy/core/src/umathmodule.c with a long list of error messages of the following two kinds. warning: conflicting types for built-in function `sinl' repeated for `cosl', `fabsl', and `sqrtl', triggered by line 442. inconsistent operand constraints in an `asm', triggered by lines 1100, 1124, 1150, 1755, 1785, and 1834. I cannot see on those source lines what causes such a message; I suspect there is some long complicated cpp macro or asm statement in some include file which I don't find. Has anyone tried building numpy on Yellow Dog Linux or on a PowerPC with gcc? Vincent Broman [EMAIL PROTECTED] ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Accessing a numpy array in a mmap fashion
Brian Donovan wrote: Hello all, I'm wondering if there is a way to use a numpy array that uses disk as a memory store rather than ram. I'm looking for something like mmap but which can be used like a numpy array. The general idea is this. I'm simulating a system which produces a large dataset over a few hours of processing time. Rather than store the numpy array in memory during processing I'd like to write the data directly to disk but still be able to treat the array as a numpy array. Is this possible? Any ideas? What you're looking for is numpy.memmap, though the documentation is eluding me at the moment. Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Accessing a numpy array in a mmap fashion
On 30/08/2007, Brian Donovan [EMAIL PROTECTED] wrote: Hello all, I'm wondering if there is a way to use a numpy array that uses disk as a memory store rather than ram. I'm looking for something like mmap but which can be used like a numpy array. The general idea is this. I'm simulating a system which produces a large dataset over a few hours of processing time. Rather than store the numpy array in memory during processing I'd like to write the data directly to disk but still be able to treat the array as a numpy array. Is this possible? Any ideas? You want numpy.memmap: http://mail.python.org/pipermail/python-list/2007-May/443036.html This will do exactly what you want (though you may have problems with arrays bigger than a few gigabytes, particularly on 32-bit systems) and there may be a few rough edges. You will probably need to create the file first. Keep in mind that if the array is actually temporary, the virtual memory system will push unused parts out to disk as memory fills up, so there's no need to use memmap explicitly. If you want the array permanently on disk, though, memmap is probably the most convenient way to do it - though if your access patterns are not local it may involve a lot of thrashing. Sequential disk writes have the advantage (?) of forcing you to write code that accesses disks in a local fashion. Anne ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Error code of NumpyTest()
On Thu, Aug 30, 2007 at 12:48:44PM +0300, Pearu Peterson wrote: The svn version of test() function now returns TestResult object. So, test() calls in buildbot should read: import numpy,sys; sys.exit(not numpy.test(verbosity=,level=).wasSuccessful()) Hopefully buildbot admins can update the test commands accordingly. Thanks, Pearu. I forwarded your instructions to the relevant parties. Cheers Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
