Mailman 3 January 2009 - NumPy-Discussion

header option for savetxt
by Nils Wagner Jan. 22, 2009

Jan. 22, 2009

Hi all, Is it possible to add a header option for savetxt ? Nils

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array manipulation
by Nils Wagner Jan. 22, 2009

Jan. 22, 2009

Hi all, what is the best way to check if the entries (integers) of an array are stored in ascending order ? Nils

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new incremental statistics project
by Bradford Cross Jan. 22, 2009

Jan. 22, 2009

This is a new project I just released. I know it is C#, but some of the design and idioms would be nice in numpy/scipy for working with discrete event simulators, time series, and event stream processing. http://code.google.com/p/incremental-statistics/

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genfromtxt
by Brent Pedersen Jan. 21, 2009

Jan. 21, 2009

hi, i'm using the new genfromtxt stuff in numpy svn, looks great pierre any who contributed. is there a way to have the header commented and still be able to have it recognized as the header? e.g. #gender age weight M 21 72.100000 F 35 58.330000 M 33 21.99 if i use np.loadtxt or genfromtxt, it tries to use the 2nd row (first non-commented as the header). and i get an array like: array([('M', 21, 72.099999999999994), ('F', 35, 58.329999999999998), ('M', 33, 21.989999999999998)], dtype=[('f0', '|S1'), ('f1', '<i4'), ('f2', '<f8')]) when i want: array([('M', 21, 72.099999999999994), ('F', 35, 58.329999999999998), ('M', 33, 21.989999999999998)], dtype=[('gender', '|S1'), ('age', '<i4'), ('weight', '<f8')]) i can get that by uncommenting the header, but it's useful to have that for other code. is there anyway to do that? thanks, -brent

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No tests found for numpy 1.2.0
by Brian Granger Jan. 21, 2009

Jan. 21, 2009

Just installed numpy 1.2.0 and got this: $ python -c 'import numpy; numpy.test()' Running unit tests for numpy-1.2.0-py2.5-macosx-10.5-i386.egg.numpy NumPy version 1.2.0 NumPy is installed in /Users/bgranger/Library/Python/2.5/site-packages/numpy-1.2.0-py2.5-macosx-10.5-i386.egg/numpy Python version 2.5.1 (r251:54863, Jul 23 2008, 11:00:16) [GCC 4.0.1 (Apple Inc. build 5465)] nose version 0.10.4 ---------------------------------------------------------------------- Ran 0 tests in 0.017s OK Any thoughts on this? It seems to work though. I have nose 0.10.4 installed.

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line_profiler suggestion
by Neal Becker Jan. 21, 2009

Jan. 21, 2009

Would be handy to not have to add/remove @profile to switch between profiling/normal operation. When run without profiler, @profile is redefined to do nothing. Possible?

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ANN: Numexpr 1.1, an efficient array evaluator
by Francesc Alted Jan. 21, 2009

Jan. 21, 2009

======================== Announcing Numexpr 1.1 ======================== Numexpr is a fast numerical expression evaluator for NumPy. With it, expressions that operate on arrays (like "3*a+4*b") are accelerated and use less memory than doing the same calculation in Python. The expected speed-ups for Numexpr respect to NumPy are between 0.95x and 15x, being 3x or 4x typical values. The strided and unaligned case has been optimized too, so if the expresion contains such arrays, the speed-up can increase significantly. Of course, you will need to operate with large arrays (typically larger than the cache size of your CPU) to see these improvements in performance. This release is mainly intended to put in sync some of the improvements that had the Numexpr version integrated in PyTables. So, this standalone version of Numexpr will benefit of the well tested PyTables' version that has been in production for more than a year now. In case you want to know more in detail what has changed in this version, have a look at ``RELEASE_NOTES.txt`` in the tarball. Where I can find Numexpr? ========================= The project is hosted at Google code in: http://code.google.com/p/numexpr/ Share your experience ===================== Let us know of any bugs, suggestions, gripes, kudos, etc. you may have. Enjoy! -- Francesc Alted

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numpy and bitwise arrays?
by Muhammad Alkarouri Jan. 21, 2009

Jan. 21, 2009

Hi everyone, I need to use a bitwise array, and I wanted to check what is the common practice using numpy. I expect to read binary strings (like '0011000001') of equal length from file and to save and manipulate them using numpy. I know that numpy have good implementations of bitwise operations, but I was wondering how to encode the data in the first place. As a Python long? As an int ndarray? Which int type? How to save and load such data in such a way that when I load it the information that it is a bit array is stored? Any help would be appreciated. Regards, Muhammad Alkarouri

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savetxt and blanks
by Nils Wagner Jan. 21, 2009

Jan. 21, 2009

Hi all, Is it possible to add a certain number of blanks behind the second column in connection with savetxt ? from numpy.random import rand from numpy import savetxt A = rand(100,2) savetxt('noblanks.dat',A,fmt='%10.2f %10.2f') Nils

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Please don't use google code for hosting
by Matthew Brett Jan. 20, 2009

Jan. 20, 2009

Hi, I am just visiting colleagues in the Cuban Neuroscience Center, and of course I'm trying to persuade them that Python and open-source are the way forward. This is made more difficult because several projects - for example pyglet - have their repositories on Google code. Google, unlike any other hoster I've come across, bans code downloads from Cuban addresses with a message that I am trying to download from 'a forbidden country'. I assume they are playing safe with code export regulations. This breaks easy_install and direct downloads. I hope you agree with me that it serves nobody's interest to reduce collaboration with Cuban scientists on free software. So, please, if you are considering google code for hosting, consider other options. Best, Matthew

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