Mailman 3 September 2002 - SciPy-Dev

fftpack2 for review
by Pearu Peterson 08 Oct '02

08 Oct '02

Dear SciPy devels, Please find a scipy.fftpack replacement candidate fftpack2 from http://cens.ioc.ee/~pearu/misc/fftpack2-0.1.tar.gz for review. fftpack2 main features include: - Optional support for high-performance FFT libraries such as FFTW and DJBFFT libraries. By default, Fortran FFTPACK is used and other libraries are automatically detected by the scipy_distutils/system_info.py script. - Support for both real and complex DFT's and their inverse transforms. When used with FFTW and/or DJBFFT libraries then fftpack2 routines are considerably faster than Numeric.FFT and the current scipy.fftpack. Some comparison timings are included at the end of this message. - Implementation of differentiation and integration of periodic sequences, various pseudo-differential operators such as Tilbert transform, Hilbert transform, hyperbolic pseudo-differential operators, their inverses, etc. - Because different FFT libraries use different data storage convention, fftpack2 implements interface to these conventions so that users and developers need not to learn all these conventions, just one is enough. Namely, fftpack2 uses the same data storage specification as Fortran FFTPACK (also used by Numeric.FFT and Matlab, though with somewhat different formal definitions). - Generic convolution routines that allow quick and easy way of introducing new pseudo-differential operators with the same performance as core pseudo-differential operators. - All functions have complete documentation strings. - A rather complete testing site. Note that fftpack2 requires the latest F2PY that you can get from http://cens.ioc.ee/projects/f2py2e/2.x/F2PY-2-latest.tar.gz For testing, fftpack2 uses scipy_test from SciPy CVS repository. For building/testing instructions and for various notes, including open questions, see NOTES.txt file after unpacking fftpack2-0.1.tar.gz. As usual, comments, suggestions, and criticism are most welcome. Regards, Pearu ------------------------------- fftpack2 timing results: ------------------------------- Fast Fourier Transform ======================================================== | real input | complex input -------------------------------------------------------- size |fftpack2| FFT | scipy |fftpack2| FFT | scipy -------------------------------------------------------- 100 | 0.38 | 0.39 | 0.38 | 0.40 | 0.40 | 0.38 (secs for7000calls) 1000 | 0.31 | 0.63 | 0.60 | 0.54 | 0.64 | 0.61 (secs for 2000 256 | 0.60 | 0.75 | 0.62 | 0.71 | 0.78 | 0.66 (secs for 10000 512 | 0.77 | 1.30 | 1.00 | 0.95 | 1.30 | 1.01 (secs for 10000 1024 | 0.14 | 0.26 | 0.18 | 0.17 | 0.25 | 0.19 (secs for 1000 2048 | 0.21 | 0.51 | 0.36 | 0.34 | 0.65 | 0.54 (secs for 1000 4096 | 0.28 | 1.08 | 0.66 | 0.56 | 0.93 | 0.79 (secs for 500 8192 | 1.09 | 3.88 | 3.94 | 2.19 | 4.36 | 3.48 (secs for 500 Inverse Fast Fourier Transform ======================================================== | real input | complex input -------------------------------------------------------- size |fftpack2| FFT | scipy |fftpack2| FFT | scipy -------------------------------------------------------- 100 | 0.17 | 0.26 | 0.63 | 0.45 | 0.87 | 0.85 (secs for 7000 1000 | 0.34 | 1.24 | 1.25 | 0.72 | 1.29 | 1.29 (secs for 2000 256 | 0.62 | 1.57 | 1.44 | 0.69 | 1.62 | 1.47 (secs for 10000 512 | 0.80 | 2.69 | 2.30 | 1.00 | 2.62 | 2.20 (secs for 10000 1024 | 0.12 | 0.51 | 0.41 | 0.18 | 0.54 | 0.44 (secs for 1000 2048 | 0.23 | 1.16 | 1.09 | 0.40 | 1.33 | 1.27 (secs for 1000 4096 | 0.35 | 1.75 | 1.44 | 0.63 | 1.72 | 1.54 (secs for 500 8192 | 1.34 | 5.71 | 6.02 | 2.40 | 6.14 | 5.67 (secs for 500 Multi-dimensional Fast Fourier Transform ======================================================== | real input | complex input -------------------------------------------------------- size |fftpack2| FFT | scipy |fftpack2| FFT | scipy -------------------------------------------------------- 100x100 | 0.43 | 0.87 | 0.81 | 0.48 | 0.88 | 0.82 (secs for 100 1000x100 | 0.54 | 0.78 | 0.72 | 0.56 | 0.73 | 0.75 (secs for 7 256x256 | 0.69 | 0.72 | 0.62 | 0.67 | 0.72 | 0.64 (secs for 10 512x512 | 0.81 | 0.91 | 0.84 | 0.81 | 0.87 | 0.81 (secs for 3 Fast Fourier Transform (real data) ================================== size |fftpack2| FFT | scipy ---------------------------------- 100 | 0.36 | 0.47 | 0.47 (secs for 7000 calls) 1000 | 0.29 | 0.38 | 0.38 (secs for 2000 calls) 256 | 0.55 | 0.76 | 0.81 (secs for 10000 calls) 512 | 0.67 | 1.06 | 1.07 (secs for 10000 calls) 1024 | 0.10 | 0.18 | 0.17 (secs for 1000 calls) 2048 | 0.16 | 0.30 | 0.30 (secs for 1000 calls) 4096 | 0.20 | 0.37 | 0.32 (secs for 500 calls) 8192 | 0.75 | 1.29 | 1.26 (secs for 500 calls) Inverse Fast Fourier Transform (real data) ================================== size |fftpack2| FFT | scipy ---------------------------------- 100 | 0.39 | 0.90 | 0.92 (secs for 7000 calls) 1000 | 0.32 | 0.63 | 0.70 (secs for 2000 calls) 256 | 0.59 | 1.37 | 1.39 (secs for 10000 calls) 512 | 0.73 | 1.70 | 1.80 (secs for 10000 calls) 1024 | 0.11 | 0.27 | 0.27 (secs for 1000 calls) 2048 | 0.20 | 0.45 | 0.44 (secs for 1000 calls) 4096 | 0.24 | 0.65 | 0.68 (secs for 500 calls) 8192 | 0.73 | 1.98 | 2.06 (secs for 500 calls) Shifting periodic functions ============================== size | optimized | naive ------------------------------ 100 | 0.09 | 0.52 (secs for 1500 calls) 1000 | 0.06 | 0.66 (secs for 300 calls) 256 | 0.10 | 0.84 (secs for 1500 calls) 512 | 0.10 | 1.02 (secs for 1000 calls) 1024 | 0.07 | 1.07 (secs for 500 calls) 2048 | 0.06 | 0.80 (secs for 200 calls) 4096 | 0.00 | 0.86 (secs for 100 calls) 8192 | 0.13 | 1.23 (secs for 50 calls) Differentiation of periodic functions ===================================== size | convolve | naive ------------------------------------- 100 | 0.09 | 0.59 (secs for 1500 calls) 1000 | 0.06 | 0.75 (secs for 300 calls) 256 | 0.11 | 0.97 (secs for 1500 calls) 512 | 0.09 | 1.21 (secs for 1000 calls) 1024 | 0.08 | 1.19 (secs for 500 calls) 2048 | 0.06 | 1.11 (secs for 200 calls) 4096 | 0.09 | 1.19 (secs for 100 calls) 8192 | 0.14 | 1.48 (secs for 50 calls) Tilbert transform of periodic functions ========================================= size | optimized | naive ----------------------------------------- 100 | 0.09 | 0.54 (secs for 1500 calls) 1000 | 0.06 | 0.60 (secs for 300 calls) 256 | 0.10 | 0.77 (secs for 1500 calls) 512 | 0.09 | 0.89 (secs for 1000 calls) 1024 | 0.07 | 0.90 (secs for 500 calls) 2048 | 0.05 | 0.83 (secs for 200 calls) 4096 | 0.07 | 0.92 (secs for 100 calls) 8192 | 0.11 | 1.04 (secs for 50 calls) . Hilbert transform of periodic functions ========================================= size | optimized | naive ----------------------------------------- 100 | 0.09 | 0.47 (secs for 1500 calls) 1000 | 0.06 | 0.48 (secs for 300 calls) 256 | 0.10 | 0.68 (secs for 1500 calls) 512 | 0.09 | 0.77 (secs for 1000 calls) 1024 | 0.07 | 0.74 (secs for 500 calls) 2048 | 0.06 | 0.72 (secs for 200 calls) 4096 | 0.07 | 0.79 (secs for 100 calls) 8192 | 0.11 | 0.93 (secs for 50 calls)

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setup.py traceback
by Skip Montanaro 01 Oct '02

01 Oct '02

I just cvsup'd and now get this traceback when executing setup.py (no matter which command I try): /usr/local/lib/python2.3/pre.py:94: DeprecationWarning: Please use the 're' module, not the 'pre' module DeprecationWarning) Traceback (most recent call last): File "setup.py", line 129, in ? install_package() File "setup.py", line 95, in install_package config.extend([get_package_config(x,parent_package)for x in standard_packages]) File "setup.py", line 45, in get_package_config config = mod.configuration(parent) File "linalg/setup_linalg.py", line 33, in configuration atlas_info = get_info('atlas') File "scipy_distutils/system_info.py", line 127, in get_info return cl().get_info() File "scipy_distutils/system_info.py", line 224, in __init__ assert type(self.search_static_first) is type(0) AssertionError Anyone else seeing this? I'm running on Mandrake 8.1 with Python CVS. Skip

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Switch to syncmail for checkins?
by Skip Montanaro 30 Sep '02

30 Sep '02

I *really* like seeing context diffs in the checkin mail (e.g. stuff sent to scipy-cvs(a)scipy.org). As a naive scipy developer it gives me a snippet of code to scan. As a potential code reviewer it makes it dead simple for me to quickly "desk check" the code being checked in. On the python-checkins list mail is sent on a fairly frequent basis (every couple weeks at least) of the sort, "did you mean X where you typed Y?" This catches a fair number of problems before they reach the wider world. The Python gang uses a script I believe Barry Warsaw wrote called syncmail. I'm not entirely sure how the CVS checkin process uses the CVSROOT/loginfo file, but I suspect only a single "ALL" entry is supported. A Perl script named log is already run during the commit process. It appends log info to $CVSROOT/CVSROOT/commitlog and sends the result to scipy-cvs(a)scipy.org (this is the typical scipy-cvs mail you get). Syncmail generates a more substantial message (includes the context diff I spoke of) but doesn't dump any output to the commitlog. Do people use the commitlog file? Neither the log script nor the commitlog file are checked into the CVS repository, so you have to login to scipy.org to view either of them. If people use the commitlog file I will make sure it continues to be generated, but otherwise would like to dump the current log script in favor of syncmail. Let me know your thoughts. -- Skip Montanaro - skip(a)pobox.com "Airplanes don't fly until the paperwork equals the weight of the aircraft. Same with i18N." - from the "Perl, Unicode and i18N FAQ"

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Q: DOES YOUR FOREIGN ACCENT SIMPLY GET IN THE WAY?
by Sarah Benson 29 Sep '02

29 Sep '02

Q: " Would you like to Lose Your Accent ? " - DO YOU FIND OTHERS HAVE A HARD TIME UNDERSTANDING WHAT YOU ARE TRYING TO CONVEY? - DO YOU FIND THE NEED TO REPEAT YOURSELF FOR OTHERS TO UNDERSTAND YOU CLEARLY? - DO YOU FEEL EMBARRASSED OR LESS CONFIDENT WHEN TALKING TO WORK COLLEAGUES? - DO YOU WISH TO COMMUNICATE YOUR THOUGHTS MORE EFFECTIVELY? - DOES YOUR FOREIGN ACCENT SIMPLY GET IN THE WAY? Introducing the Krieger Method, an innovative teaching system, designed to help you develop effective communication skills. Andy Krieger, inventor of this miracle product, originated this revolutionary idea whilst working with actors and their accents within the Hollywood film industry. Contact us to learn about the true benefits you can obtain to communicate with confidence!! "Make your accent simply disappear!" For Accent Reduction Empowerment, visit us on the web today at :- www.nomoreaccent.com Thank you for your time and interest... Sarah J. Benson Marketing Co-ordinator If you feel this is email is not of interest to you, then we sincerely apologize and guarantee you will not receive another email from us, unless you otherwise wish.

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What's this error mean?
by Skip Montanaro 26 Sep '02

26 Sep '02

I just tried a 'cvs up' in my scipy source directory and got this: cvs [server aborted]: could not find desired version 1.130.1506.4149 in /home/cvsroot/world/scipy/__cvs_version__.py,v I removed __cvs_version__.py and ran 'cvs up' again. It then worked. Can someone explain what that error means and what __cvs_version__.py is used for? Thanks, Skip

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未承諾広告※簡単融資
by お金貸します 25 Sep '02

25 Sep '02

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Debugging tidbit
by David C. Morrill 24 Sep '02

24 Sep '02

Just thought I would mention that if anyone does encounter problems running the demo, try looking in the 'debug.log' file to see if there is any information (such as a traceback). If so, posting the contents of the debug.log file along with the problem description would be a big help. The 'debug.log' file is normally created in the current directory when the demo is run. Dave Morrill

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Progress being made on Chaco Linux problem
by David C. Morrill 24 Sep '02

24 Sep '02

Just wanted to let everyone know that I have made some progress on the Chaco Linux problem that several people have reported. It appears that the Linux GTK-based version on wxPython does not implement the wxDC.SetDeviceOrigin and wxDC.SetAxisOrientation methods the same way as the Windows version does. The Kiva layer of Chaco is based on DisplayPDF and has its origin in the lower-left corner. Chaco uses the two calls just mentioned to properly orient the wxDC drawing methods. But in the Linux version, these calls are not behaving as I would expect. By commenting out the body of the 'right_side_up' method in wxplot_window.py in the chaco directory (which calls the two methods described), I was able to get the demo program to work (although all the plots are inverted!). I'm going to start looking at the wxPython source to see if I can figure out what's going wrong. But in the meantime I thought I would post what I had found so far. Dave Morrill

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Chaco discussion on scipy-chaco mailing list
by David C. Morrill 23 Sep '02

23 Sep '02

Just wanted to mention that Chaco has its own mailing list on scipy-chaco(a)scipy.org. To avoid unnecessary cross-posting on the other SciPy lists, hopefully future Chaco discussion will occur there. In particular, I just posted a note there on the progress I've made in fixing the Chaco Linux problem that has been reported by several people. See ya there... Dave Morrill

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Chaco discussion on scipy-chaco mailing list
by David C. Morrill 23 Sep '02

23 Sep '02

Just wanted to mention that Chaco has its own mailing list on scipy-chaco(a)scipy.org. To avoid unnecessary cross-posting on the other SciPy lists, hopefully future Chaco discussion will occur there. In particular, I just posted a note there on the progress I've made in fixing the Chaco Linux problem that has been reported by several people. See ya there... Dave Morrill

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