Mailman 3 September 2008 - NumPy-Discussion

Getting a numpy array from a ctype pointer
by Paulo J. S. Silva Sept. 4, 2008

Sept. 4, 2008

Hello, I am writing some code interfacing C and Python using ctypes. In a callback function (in Python) I get in a parameter x which is c_double pointer and a parameter n which is c_int representing the length of the array. How can I transform this information into a numpy array? Paulo

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How to import data where the decimal separator is a comma ?
by oc-spam66 Sept. 4, 2008

Sept. 4, 2008

Hello, I have data files where the decimal separator is a comma. Can I import this data with numpy.loadtxt ? Notes : - I tried to set the locale LC_NUMERIC="fr_FR.UTF-8" but it didn't change anything. - Python 2.5.2, Numpy 1.1.0 Have a nice day, O.C. Créez votre adresse électronique prenom.nom(a)laposte.net 1 Go d'espace de stockage, anti-spam et anti-virus intégrés.

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`out` argument to ufuncs
by Stéfan van der Walt Sept. 4, 2008

Sept. 4, 2008

Hey all, Gael just asked me why `add`, `subtract` etc. didn't have out arguments like `cos` and `sin`. I couldn't give him a good answer. Could we come to an agreement to add a uniform interface to ufuncs for 1.3? Either all or none of them should support the out argument. I see a couple of "deg" (for degrees) flags floating around as well, so we could consider adding those to all ufuncs that accept angles. Thanks for your input, Stéfan

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test results of 1.2.0rc1
by Andrew Straw Sept. 4, 2008

Sept. 4, 2008

Hi, with numpy 1.2.0rc1 running 'python -c "import numpy; numpy.test()"' on my Ubuntu Hardy amd64 machine results in 1721 tests being run and 1 skipped. So far, so good. However, if I run numpy.test(10,10,all=True), I get 1846 tests with: the message "FAILED (SKIP=1, errors=8, failures=68)" Furthermore, there are several matplotlib windows that pop up, many of which are non-reassuringly blank: Bartlett window frequency response (twice -- I guess the 2nd is actually for the Blackman window), Hamming window frequency response, Kaiser window, Kaiser window frequency response, sinc function. Additionally, the linspace and logspace tests each generate a plots with green and blue dots at Y values of 0.0 and 0.5, but it would be nice to have an axes title. Should I be concerned that there are so many errors and failures with the numpy test suite? Or am I just running it with unintended settings? If these tests should pass, I will attempt to find time to generate bug reports for them, although I don't think there's anything particularly weird about my setup. -Andrew

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numpy 1.3: cleaning the math configuration, toward a warning free build
by David Cournapeau Sept. 4, 2008

Sept. 4, 2008

Hi, For numpy 1.3, there are several things I would like to work on, which I have already hinted previously. The two big things are: - cleaning the math configuration - making numpy buildable warning-free with a good set a warning flags. For the warning-free build, I have started a nep, since some decisions are not obvious. Is this appropriate ? For the first part, I want to clean-up the current umath module, mainly the configuration: we have quite a big mess ATM with several intervened configurations, and everytime I am trying to touch it, I break something (adding trunc, modifying mingw configuration, etc...). I think it would be nice to clean-up, have a per-function check (instead of the HAVE_LONGDOUBLE heuristic); I noticed for example that depending on the configuration, we have different implementations for the same function, etc... Robert mentioned the configuration time cost increase, but I think I have a solution to make it as fast as before for most configurations, the ones which work today, and it will be longer only for platforms which need a better configuration (mingw, etc...). Should I write a nep for that too ? Or a patch is enough ? cheers, David

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Updated Numpy reference guide
by Pauli Virtanen Sept. 4, 2008

Sept. 4, 2008

Hi all, I finished the first iteration of incorporating material from Travis Oliphant's "Guide to Numpy" to the Sphinxy reference guide we were constructing in the Doc marathon. Result is here: (the PDF is a bit ugly, though, some content is almost randomly scattered there) http://www.iki.fi/pav/tmp/numpy-refguide/index.xhtml http://www.iki.fi/pav/tmp/numpy-refguide/NumPy.pdf Source is here: (Stéfan, if it looks ok to you, could you pull and check if it builds for you when you have time?) https://code.launchpad.net/~pauli-virtanen/scipy/numpy-refguide What I did with the "Guide to Numpy" material was: - Collapsed each of the reference Chapters 3, 6, 8, 9 (ndarrays, scalars, dtypes, ufuncs) with the more introductory material in Chapter 2. - As this was supposed to be a reference guide, I tried to compress the text from Chapter 2 as much as possible, by sticking to definitions and dropping some more tutorial-oriented parts. This may have reduced readability at some points... - I added some small bits or rewrote parts in the above sections in places where I thought it would improve the result. - I did not include material that I thought was better to be put into appropriate docstrings in Numpy. What to do with class docstrings and obscure __xxx__ attributes was not so clear a decision, so what I did for these varies. - The sections about Ufuncs and array indexing are taken almost verbatim from the "Guide to Numpy". The ndarray, scalar and dtype sections somewhat follow the structure of the Guide, but the text is more heavily edited from the original. Some things to do: - Descriptions about constructing items with __new__ methods should probably still be clarified; I just replaced references to __new__ with references to the corresponding classes. - What to do with the material from numpy.doc.* should be decided, as the text there doesn't look like it should go into a reference manual. Some questions: - Is this good enough to go into Numpy SVN at some point? Or should we redo it and base the work closer to the original "Guide to Numpy"? - Does it build for you? (I'd recommend using the development 0.5 version of Sphinx, so that you get the nifty Inter-Sphinx links to the Python documentation.) We are unfortunately beating the Sphinx with a big stick to make it place the documentation of each function or class into a separate file, and to convert the Numpy docstring format to something the Sphinx can fathom. There's also some magic in place to make toctrees:: of function listings more pleasant to the eye. Any comments of what should be improved are welcome. (Even better: clone the bzr branch, make the changes yourself, and put the result somewhere available! E.g. as a bzr bundle or a branch on the launchpad.) -- Pauli Virtanen

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numpy 1.1.1 fails because of missing md5
by Charles Doutriaux Sept. 3, 2008

Sept. 3, 2008

Joseph, Ok all failed because numpy couldn't build... It's looking for md5 on my machine i type: whereis md5 md5: /usr/include/md5.h /usr/share/man/man1/md5.1ssl.gz /usr/share/man/man3/md5.3ssl.gz I'm ccing the numpy discussion list on this. The numpy we're trying to build is 1.1.1 I'm attaching the numpy log. Is it fixed in 1.2 ? Joseph in the mean time you might want to try to install md5 on your system. C. Joseph Hargitai wrote: > here are the logs - > > OS: > 2.6.9-55.ELsmp #1 SMP Fri Apr 20 16:36:54 EDT 2007 x86_64 x86_64 x86_64 GNU/Linux > > Rocks 4.3 with Redhat installation cluster. > > >

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at my wits end over an error message...
by Alan Jackson Sept. 3, 2008

Sept. 3, 2008

I been beating myself up over this bit of code for far too long now - I know I must be missing something really simple, but what is it? TYPICALLY_UINT_COLUMNS = ['Track', 'Bin', 'code', 'horizon'] ...... dtypes = [ ] for i in range(0, len(self.var_list)) : if TYPICALLY_UINT_COLUMNS.count(self.var_list[i]) > 0: dtypes.append((self.var_list[i], '<i8')) else : dtypes.append((self.var_list[i], '<f8')) print "dtypes = ", dtypes print outdata[0] outdata = np.array(outdata, dtype=dtypes) dtypes = [('Track', '<i8'), ('Bin', '<i8'), ('Depth', '<f8'), ('extrema', '<f8'), ('code', '<i8'), ('horizon', '<i8')] (345, 615, 4826.0, 470.588012695, 47, 636) Exception occurred in traits notification handler. Please check the log file for details. Exception occurred in traits notification handler for object: <__main__.MaplEdit object at 0x8bb54dc>, trait: Run, old value: <undefined>, new value: 0 Traceback (most recent call last): File "/usr/local/lib/python2.5/site-packages/enthought.traits-2.0.4-py2.5-linux-i686.egg/enthought/traits/trait_notifiers.py", line 325, in call_1 self.handler( object ) File "TrimMapl_1.py", line 98, in _Run_fired outdata = np.array(outdata, dtype=dtypes) TypeError: expected a readable buffer object Thanks, Alan -- ----------------------------------------------------------------------- | Alan K. Jackson | To see a World in a Grain of Sand | | alan(a)ajackson.org | And a Heaven in a Wild Flower, | | www.ajackson.org | Hold Infinity in the palm of your hand | | Houston, Texas | And Eternity in an hour. - Blake | -----------------------------------------------------------------------

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NumPy 1.2.0rc1 to be tagged in 5 hours
by Jarrod Millman Sept. 2, 2008

Sept. 2, 2008

Hello, I am planning to tag 1.2.0rc1 in 5 hours. The tests are passing on the buildbots and I don't know of anything else that needs to be fixed before making the final 1.2.0 release, which will come out after the release candidate has been more widely tested. If you know of any release blockers, please let me know ASAP. 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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Problem building NumPy with information from ~/.numpy-site.cfg
by Berthold "Höllmann" Sept. 2, 2008

Sept. 2, 2008

I am trying to build numpy 1.1.1 with ATLAS support. the f77blas library I am trying to use is named f77blas_gfortran to distinguish it From builds for other compilers. First from the documentation it is unclear whether the default section is named DEFAULT or ALL (I tried both). So I set [DEFAULT] library_dirs = /usr/local/gltools/kinux/lib:/usr/local/gltools/linux_x86_64/lib include_dirs = /usr/local/gltools/include:/usr/local/gltools/linux/include:/usr/local/gltools/linux_x86_64/include [blas_opt] libraries = f77blas_gfortran, cblas, atlas [lapack_opt] libraries = lapack_gfortran, f77blas_gfortran, cblas, atlas in my ~/.numpy-site.cfg but the build process does not find LAPACK support and builds lapack_lite.so with the built in slow lapack. /usr/local/gltools/linux_x86_64/lib/libf77blas_**.so /usr/local/gltools/linux_x86_64/lib/libf77blas_g77.so /usr/local/gltools/linux_x86_64/lib/libf77blas_gfortran.so /usr/local/gltools/linux_x86_64/lib/libf77blas_ifc100.so /usr/local/gltools/linux_x86_64/lib/libf77blas_ifc101.so /usr/local/gltools/linux_x86_64/lib/libf77blas_ifc90.so /usr/local/gltools/linux_x86_64/lib/libf77blas_ifc91.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg52.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg60.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg61.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg62.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg70.so /usr/local/gltools/linux_x86_64/lib/libf77blas_pg71.so How do I set the configuration options in ~/.numpy-site.cfg so that the build process finds my libraries? Kind regards Berthold Höllmann -- Germanischer Lloyd AG CAE Development Vorsetzen 35 20459 Hamburg Phone: +49(0)40 36149-7374 Fax: +49(0)40 36149-7320 e-mail: berthold.hoellmann(a)gl-group.com Internet: http://www.gl-group.com

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