Mailman 3 July 2008 - NumPy-Discussion

Debian: numpy not building _dotblas.so
by Ondrej Certik 08 Jul '08

08 Jul '08

Hi, we have this problem in Debian: http://bugs.debian.org/cgi-bin/bugreport.cgi?bug=489726 The problem is that numpy should not depend on atlas unconditionally, yet it should allow it for users that have it. I am not an expert in blas/lapack/atlas and it's Debian packaging much (I know some people say that atlas packaging in Debian is not very good, actually pretty bad), so I am just forwarding the question here. The problem is with this patch: http://projects.scipy.org/scipy/numpy/changeset/3854 and the question that we have is: <doko> I'd like to know, if the code was changed to only work with atlas, or if was never working. if it's the latter, then we should use atlas Matthias, Tiziano, feel free to clarify this more. See the above Debian bug for more information and background. Thanks, Ondrej

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numpy with fftw
by Frédéric Bastien 08 Jul '08

08 Jul '08

Hi, I want to compile numpy so that it use the optimized fftw librairy. In the site.cfg.example their is a section [fftw3] that I fill with: [fftw3] include_dirs = /usr/include library_dirs = /usr/lib64 fftw3_libs = fftw3, fftw3f fftw3_opt_libs = fftw3_threads, fftw3f_threads when I compile it, their is no message that it found it like for the atlas librairy(optimized blas librairy). numpy.show_config() don't tell which version of fft it use. How can I know it was well compiled? I tried comparing the speed of the numpy version in FC9 and the one I built, but they have the same speed. Here is the code I used to do my timing: time python -c "import numpy.fft;a=numpy.random.rand(30000); for i in xrange(10000): numpy.fft.fft(a); numpy.show_config()" thanks for your time Frédéric Bastien

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Patch for `numpy.doc`
by Stéfan van der Walt 08 Jul '08

08 Jul '08

Hi all, Please review http://codereview.appspot.com/2485 which adds `numpy.doc` as a way of documenting topics such as indexing and broadcasting. The corresponding trac ticket is http://scipy.org/scipy/numpy/ticket/846 Regards Stéfan

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removing and replacing certain values in arrays
by Tim Michelsen 07 Jul '08

07 Jul '08

Hello, how do I remove all rows (or column) from an array which contain a certain value or sting? some like: array.delte_row_from_array_wich_contains('March') array.delte_row_from_array_wich_contains(-333) Is there also possibility to replace all occurences of a certain value in a array by nothing or another one? I am not looking to masking the values under question in this case here. I will appreciate any help. Kind regards, Timmie

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Tip: Backporting the latest numpy release in Ubuntu Hardy (8.04)
by Tim Michelsen 07 Jul '08

07 Jul '08

Hello, due to fixed release cycles Ubuntu 8.04 still lacks the latest numpy 1.1. I succeeded backporting the package python-numpy from the upcoming release Intrepid 8.10 with the help of the automatic tool Prevu. Instructions can be found here: * https://wiki.ubuntu.com/Prevu * http://ubuntuforums.org/showthread.php?t=268687 Information on the package: http://packages.ubuntu.com/search?keywords=python-numpy I can encourage other Ubuntu users to do the same because it is not difficult. Just follow the instructions on the wiki. Regards, Timmie

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array_equal returns True and 0
by Keith Goodman 07 Jul '08

07 Jul '08

I'm writing the doc string for array_equal. From the existing one-line doc string I expect array_equal to return True or False. But I get this: >> np.array_equal([1,2], [1,2]) True >> np.array_equal([1,2], [1,2,3]) 0 >> np.array_equal(np.array([1,2]), np.array([1,2,3])) 0 >> np.__version__ '1.1.0'

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Schedule for the SciPy08 conferencez
by Gael Varoquaux 06 Jul '08

06 Jul '08

We have received a large number of excellent contributions for papers for the SciPy 2008 conference. The program committee has had to make a difficult selection and we are happy to bring to you a preliminary schedule: Thursday ========= **8:00** Registration/Breakfast **8:55** Welcome (Travis Vaught) **9:10** Keynote (Alex Martelli) **10:00** State of SciPy (Travis Vaught, Jarrod Millman) **10:40** -- Break -- **11:00** Sympy - Python library for symbolic mathematics: introduction and applications (Ondřej Čertik) **11:40** Interval arithmetic: Python implementation and applications (Stefano Taschini) **12:00** Experiences Using Scipy for Computer Vision Research (Damian Eads) **12:20** -- Lunch -- **1:40** The new NumPy documentation framework (Stéfan Van der Walt) **2:00** Matplotlib solves the riddle of the sphinx (Michael Droettboom) **2:40** The SciPy documentation project (Joe Harrington) **3:00** -- Break -- **3:40** Sage: creating a viable free Python-based open source alternatice to Magma, Maple, Mathematica and Matlab (William Stein) **4:20** Open space for lightning talks Friday ======== **8:30** Breakfast **9:00** Pysynphot: A Python Re-Implementation of a Legacy App in Astronomy (Perry Greenfield) **9:40** How the Large Synoptic Survey Telescope (LSST) is using Python (Robert Lupton) **10:00** Real-time Astronomical Time-series Classification and Broadcast Pipeline (Dan Starr) **10:20** Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy (Matthew Turk) **10:40** -- Break -- **11:00** Exploring network structure, dynamics, and function using NetworkX (Aric Hagberg) **11:40** Mayavi: Making 3D data visualization reusable (Prabhu Ramachandran, Gaël Varoquaux) **12:00** Finite Element Modeling of Contact and Impact Problems Using Python (Ryan Krauss) **12:20** -- Lunch -- **2:00** PyCircuitScape: A Tool for Landscape Ecology (Viral Shah) **2:20** Summarizing Complexity in High Dimensional Spaces (Karl Young) **2:40** UFuncs: A generic function mechanism in Python (Travis Oliphant) **3:20** -- Break -- **3:40** NumPy Optimization: Manual tuning and automated approaches (Evan Patterson) **4:00** Converting Python functions to dynamically-compiled C (Ilan Schnell) **4:20** unPython: Converting Python numerical programs into C (Rahul Garg) **4:40** Implementing the Grammar of Graphics for Python (Robert Kern) **5:00** Ask the experts session. A more detailled booklet including the abstract text will be available soon. We are looking forward to seeing you in Caltech, Gaël Varoquaux, on behalf of the program committee. -- SciPy2008 conference. Program committee Anne Archibald, McGill University Matthew Brett Perry Greenfield, Space Telescope Science Institute Charles Harris Ryan Krauss, Southern Illinois University Gaël Varoquaux Stéfan van der Walt, University of Stellenbosch

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Re: [Numpy-discussion] Numpy-discussion Digest, Vol 22, Issue 21
by Marek Wojciechowski 06 Jul '08

06 Jul '08

> Message: 4 > Date: Sun, 06 Jul 2008 13:36:24 +0900 > From: David Cournapeau <david(a)ar.media.kyoto-u.ac.jp> > Subject: Re: [Numpy-discussion] Numpy on AIX 5.3 > To: Discussion of Numerical Python <numpy-discussion(a)scipy.org> > Message-ID: <48704BC8.6070900(a)ar.media.kyoto-u.ac.jp> > Content-Type: text/plain; charset=ISO-8859-1 > > Marek Wojciechowski wrote: > > Hi! > > > > I'm trying to install numpy-1.1 on AIX 5.3 but i'm getting an error: > > > > running build > > running scons > > customize UnixCCompiler > > Found executable /usr/bin/cc_r > > customize IBMFCompiler > > Found executable /usr/bin/xlf90 > > Found executable /usr/bin/xlf > > Found executable /usr/bin/xlf95 > > Creating /tmp/tmp5j_OiW/qV0MJ4_xlf.cfg > > customize IBMFCompiler > > Creating /tmp/tmp5j_OiW/-LWcxB_xlf.cfg > > customize UnixCCompiler > > customize UnixCCompiler using scons > > Traceback (most recent call last): > > File "setup.py", line 96, in <module> > > setup_package() > > File "setup.py", line 89, in setup_package > > configuration=configuration ) > > File "/home/marek/tmp/numpy-1.1.0/numpy/distutils/core.py", line 184, > > in setup > > return old_setup(**new_attr) > > File "/home/marek/apython/lib/python2.5/distutils/core.py", line 151, > > in setup > > dist.run_commands() > > File "/home/marek/apython/lib/python2.5/distutils/dist.py", line 974, > > in run_commands > > self.run_command(cmd) > > File "/home/marek/apython/lib/python2.5/distutils/dist.py", line 994, > > in run_command > > cmd_obj.run() > > File "/home/marek/tmp/numpy-1.1.0/numpy/distutils/command/build.py", > > line 38, in run > > self.run_command('scons') > > File "/home/marek/apython/lib/python2.5/distutils/cmd.py", line 333, in > > run_command > > self.distribution.run_command(command) > > File "/home/marek/apython/lib/python2.5/distutils/dist.py", line 993, > > in run_command > > cmd_obj.ensure_finalized() > > File "/home/marek/apython/lib/python2.5/distutils/cmd.py", line 117, in > > ensure_finalized > > self.finalize_options() > > File "/home/marek/tmp/numpy-1.1.0/numpy/distutils/command/scons.py", > > line 289, in finalize_options > > self.cxxcompiler = cxxcompiler.cxx_compiler() > > File "/home/marek/tmp/numpy-1.1.0/numpy/distutils/ccompiler.py", line > > 303, in CCompiler_cxx_compiler > > + cxx.linker_so[2:] > > TypeError: can only concatenate list (not "str") to list > > Just by reading at the code, the line > > [cxx.linker_so[0]] + cxx.compiler_cxx[0] + cxx.linker_so[2:] > > Cannot work unless cxx.compiler_cxx is a nested list. Since AIX is not > that common, it is well possible that this mistake was hidden for a long > time. So I would first try something like: > > cxx.linker_so = [cxx.linker_so[0], cxx.compiler_cxx[0]] +cxx.linker_so[2:] > Yeah, this pushed building further. However there's another bug: creating build/temp.aix-5.3-2.5/build creating build/temp.aix-5.3-2.5/build/src.aix-5.3-2.5 creating build/temp.aix-5.3-2.5/build/src.aix-5.3-2.5/numpy creating build/temp.aix-5.3-2.5/build/src.aix-5.3-2.5/numpy/core creating build/temp.aix-5.3-2.5/build/src.aix-5.3-2.5/numpy/core/src compile options: '-Ibuild/src.aix-5.3-2.5/numpy/core/src -Inumpy/core/include -Ibuild/src.aix-5.3-2.5/numpy/core -Inumpy/core/src -Inumpy/core/include -I/home/marek/apython/include/python2.5 -I/home/marek/apython/include/python2.5 -c' cc_r: build/src.aix-5.3-2.5/numpy/core/src/umathmodule.c "numpy/core/src/umathmodule.c.src", line 1518.29: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.30: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.28: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.29: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.33: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.30: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.31: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.35: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.29: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.30: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.28: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.29: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.33: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.30: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.31: 1506-046 (S) Syntax error. "numpy/core/src/umathmodule.c.src", line 1518.35: 1506-046 (S) Syntax error. error: Command "cc_r -DNDEBUG -O -Ibuild/src.aix-5.3-2.5/numpy/core/src -Inumpy/core/include -Ibuild/src.aix-5.3-2.5/numpy/core -Inumpy/core/src -Inumpy/core/include -I/home/marek/apython/include/python2.5 -I/home/marek/apython/include/python2.5 -c build/src.aix-5.3-2.5/numpy/core/src/umathmodule.c -o build/temp.aix-5.3-2.5/build/src.aix-5.3-2.5/numpy/core/src/umathmodule.o" failed with exit status 1 The solution is to change line 1518 of umathmodule.c from: *((@typ@ *)op) += 0; // clear sign-bit to *((@typ@ *)op) += 0; /* clear sign-bit */ Generally IBM C compiler doesn't like // style commenting. I found similar problems also in scipy. Now numpy-1.1.0 compiles on AIX 5.3 (with ActivePython 2.5). Greetings, Marek -- Marek Wojciechowski

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Enthought Python Distribution
by Travis Vaught 06 Jul '08

06 Jul '08

Greetings, We're pleased to announce the beta release of the Enthought Python Distribution for *Mac OS X*. http://www.enthought.com/products/epd.php This release should safely install alongside other existing Python installations on your Mac. With the Mac OS X platform support, EPD now provides a consistent scientific application tool set across three major platforms (Windows, RedHat Linux (32 and 64 bit) and OS X). This is a _beta_ release, so install at your own risk. Please provide any feedback to info(a)enthought.com. See the included EPD Readme.txt for instructions and known issues. About EPD --------- The Enthought Python Distribution (EPD) is a "kitchen-sink-included" distribution of the Python™ Programming Language, including over 60 additional tools and libraries. The EPD bundle includes the following major packages: Python Core Python NumPy Multidimensional arrays and fast numerics for Python SciPy Scientific Library for Python Enthought Tool Suite (ETS) A suite of tools including: Traits Manifest typing, validation, visualization, delegation, etc. Mayavi 3D interactive data exploration environment. Chaco Advanced 2D plotting toolkit for interactive 2D visualization. Kiva 2D drawing library in the spirit of DisplayPDF. Enable Object-based canvas for interacting with 2D components and widgets. Matplotlib 2D plotting library wxPython Cross-platform windowing and widget library. Visualization Toolkit (VTK) 3D visualization framework There are many more included packages as well. There's a complete list here: http://www.enthought.com/products/epdlibraries.php License ------- EPD is a bundle of software--every piece of which is available for free under various open-source licenses. The bundle itself is offered as a free download to academic and individual hobbyist use. Commercial and non-degree granting institutions and agencies may purchase individual subscriptions for the bundle (http://www.enthought.com/products/order.php?ver=MacOSX ) or contact Enthought to discuss an Enterprise license (http://www.enthought.com/products/enterprise.php ). Please see the FAQ for further explanation about how the software came together. (http://www.enthought.com/products/epdfaq.php) Thanks, Travis

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NumPy, buffers (PEP 3118), complex floats, and Cython
by Dag Sverre Seljebotn 06 Jul '08

06 Jul '08

I'd like some advice for what way people feel would be the best for supporting complex datatypes in NumPy in Cython; as well as ask in what way it is likely that NumPy will make use of PEP 3118. It seems like NumPy defines its complex data to be a struct of two doubles, for instance: typedef struct { double real, imag; } npy_cdouble; According to PEP 3118 [1], it would be natural to export this as "dd" (record of two doubles) rather than "Zd" (complex double), when exporting ndarrays through a buffer interface. Right? I'm implementing native Cython support/syntax candy for PEP 3118 [2] and at the same time a backwards-compatability wrapper so that Cython can access NumPy through PEP 3118 for Python <= 2.5 (essentially I implement PyObject_GetBuffer etc. on behalf of NumPy for Python <= 2.5). Then the question arise about how to deal with complex datatypes. For Cython, it seems most user-friendly to use the C99 standard for complex numbers (not currently supported, but it wouldn't be much work) and have code like this: cdef ndarray[complex double, 2] arr = ... cdef complex double item item = arr[34, 23] So the natural questions then are: - Is it ok to assume that (complex double*) can be safely casted to (npy_cdouble*) on all platforms which both a) NumPy compiles and runs on, and b) supports complex double? (It seems to be ok with GCC but I wouldn't know about other compilers.) - Will NumPy ever be rewritten to use the C99 complex datatype if available? (I.e. #ifdef how npy_cdouble is defined, and define corresponding #ifdef-ed macros for all complex operations). This would remove the need for such a cast. - Does NumPy plan to support PEP3118, and if so, will complex numbers be exported as "dd" or "Zd"? - [1]: http://www.python.org/dev/peps/pep-3118/ [2]: http://wiki.cython.org/enhancements/buffer -- Dag Sverre

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NumPy-Discussion July 2008