Mailman 3 December 2008 - NumPy-Discussion

Excluding index in numpy like negative index in R?
by Bab Tei 09 Dec '08

09 Dec '08

Hi I can exclude a list of items by using negative index in R (R-project) ie myarray[-excludeindex]. As negative indexing in numpy (And python) behave differently ,how can I exclude a list of item in numpy? Regards, Teimourpour

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numpy build error on Solaris, No module named _md5
by Gong, Shawn (Contractor) 09 Dec '08

09 Dec '08

hi list, I tried to build numpy 1.2.1 on Solaris 9 with gcc 3.4.6 when I typed "python setup.py build", I got error from hashlib.py File "/home/sgong/dev181/dist/lib/python2.5/hashlib.py", line 133, in <module> md5 = __get_builtin_constructor('md5') File "/home/sgong/dev181/dist/lib/python2.5/hashlib.py", line 60, in __get_builtin_constructor import _md5 ImportError: No module named _md5 I then tried python 2.6.1 instead of 2.5.2, but got the same error. I did not get the error while building on Linux. But I performed steps on Linux: 1) copy *.a Atlas libraries to my local_install/atlas/ 2) ranlib *.a 3) created a site.cfg Do I need to do the same on Solaris? Any help is appreciated. thanks, Shawn

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Line of best fit!
by James 09 Dec '08

09 Dec '08

Hi, I am trying to plot a line of best fit for some data i have, is there a simple way of doing it? Cheers

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Please help prepare the SciPy 0.7 release notes
by Jarrod Millman 09 Dec '08

09 Dec '08

We are almost ready for SciPy 0.7.0rc1 (we just need to sort out the Numerical Recipes issues and I haven't had time to look though them yet). So I wanted to ask once more for help with preparing the release notes: http://projects.scipy.org/scipy/scipy/browser/trunk/doc/release/0.7.0-notes… There have been numerous improvements and changes. As always I would appreciate any feedback about mistakes or omissions. It would also be nice to know how many tests were in the last release and how many are there now. Highlighting major bug fixes or pointing out know issues would be very useful. I would also like to ask if anyone would be interested in stepping forward to work on something like Andrew Kuchling's "What's New in Python ....": http://docs.python.org/whatsnew/2.6.html This would be a great area to contribute. The release notes provide visibility for our developers' immense contributions of time and effort. They help provide an atmosphere of momentum, maturity, and excitement to a project. It is also a great service to users who haven't been following the trunk closely as well as other developer's who have missed what is happening in other areas of the code. It is also becomes a nice historical artifact for the future. It would be great if someone wanted to contribute in this way. Ideally, I would like to have someone who be interested in doing this for several releases of scipy and numpy. Such a person could develop a standard template for this and write some scripts to gather specific statistics (e.g., how many lines of code have changed, how many unit tests were added, what is the test coverage, what is the docstring coverage, who were the top contributors, who has increased their code contributions the most, how many new developers, etc.) Just a thought. Figure it won't happen, if I don't ask. 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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when will osx linker option -bundle be reflected in distutils
by Garry Willgoose 09 Dec '08

09 Dec '08

I was just wondering what plans there were to reflect the different linker options (i.e. -bundle instead of -shared) that are required on OSX in the fcompiler files within distutils. While its a minor thing it always catches the users of my software when they either install fresh or update numpy ... and sometimes on a bad day it even catches me ;-) ==================================================================== Prof Garry Willgoose, Australian Professorial Fellow in Environmental Engineering, Director, Centre for Climate Impact Management (C2IM), School of Engineering, The University of Newcastle, Callaghan, 2308 Australia. Centre webpage: www.c2im.org.au Phone: (International) +61 2 4921 6050 (Tues-Fri AM); +61 2 6545 9574 (Fri PM-Mon) FAX: (International) +61 2 4921 6991 (Uni); +61 2 6545 9574 (personal and Telluric) Env. Engg. Secretary: (International) +61 2 4921 6042 email: garry.willgoose(a)newcastle.edu.au; g.willgoose(a)telluricresearch.com email-for-life: garry.willgoose(a)alum.mit.edu personal webpage: www.telluricresearch.com/garry ==================================================================== "Do not go where the path may lead, go instead where there is no path and leave a trail" Ralph Waldo Emerson ====================================================================

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checksum on numpy float array
by Brennan Williams 08 Dec '08

08 Dec '08

My app reads in one or more float arrays from a binary file. Sometimes due to network timeouts etc the array is not read correctly. What would be the best way of checking the validity of the data? Would some sort of checksum approach be a good idea? Would that work with an array of floating point values? Or are checksums more for int,byte,string type data?

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ANNOUNCE: EPD with Py2.5 version 4.0.30002 RC2 available for testing
by Travis E. Oliphant 06 Dec '08

06 Dec '08

Hello, We've recently posted the beta1 build of EPD (the Enthought Python Distribution) with Python 2.5 version 4.1.30001 to the EPD website. You may download the beta from here: http://www.enthought.com/products/epdearlyaccess.php You can check out the release notes here: https://svn.enthought.com/epd/wiki/Python2.5.2/4.1.300/Beta1 Please help us test it out and provide feedback on the EPD Trac instance: https://svn.enthought.com/epd or via e-mail to epd-support(a)enthought.com. If everything goes well, we are planning a final release for December. 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 NumPy, SciPy, IPython, 2D and 3D visualization, database adapters, GUI building libraries, and a lot of other tools right out of the box. http://www.enthought.com/products/epd.php It is currently available as a single-click installer for Windows XP (x86), Mac OS X (a universal binary for OS X 10.4 and above), and RedHat 3 and 4 (x86 and amd64). EPD is free for academic use. An annual subscription and installation support are available for individual commercial use. Enterprise subscriptions with support for particular deployment environments are also available for commercial purchase. Enthought Build Team

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subclassing ndarray
by Steve Schmerler 05 Dec '08

05 Dec '08

Hi all I'm subclassing ndarray following [1] and I'd like to know if i'm doing it right. My goals are - ndarray subclass MyArray with additional methods - replacement for np.array, np.asarray on module level returning MyArray instances - expose new methods as functions on module level import numpy as np class MyArray(np.ndarray): def __new__(cls, arr, **kwargs): return np.asarray(arr, **kwargs).view(dtype=arr.dtype, type=cls) # define new methods here ... def print_shape(self): print self.shape # replace np.array() def array(*args, **kwargs): return MyArray(np.array(*args, **kwargs)) # replace np.asarray() def asarray(*args, **kwargs): return MyArray(*args, **kwargs) # expose array method as function def ps(a): asarray(a).print_shape() Would that work? PS: I found a little error in [1]: In section "__new__ and __init__", the class def should read class C(object): def __new__(cls, *args): + print 'cls is:", cls print 'Args in __new__:', args return object.__new__(cls, *args) def __init__(self, *args): + print 'self is:", self print 'Args in __init__:', args [1] http://docs.scipy.org/doc/numpy/user/basics.subclassing.html best, steve

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genloadtxt: second serving
by Pierre GM 05 Dec '08

05 Dec '08

All, Here's the second round of genloadtxt. That's a tad cleaner version than the previous one, where I tried to take into account the different comments and suggestions that were posted. So, tabs should be supported and explicit whitespaces are not collapsed. FYI, in the __main__ section, you'll find 2 hotshot tests and a timeit comparison: same input, no missing data, one with genloadtxt, one with np.loadtxt and a last one with matplotlib.mlab.csv2rec. As you'll see, genloadtxt is roughly twice slower than np.loadtxt, but twice faster than csv2rec. One of the explanation for the slowness is indeed the use of classes for splitting lines and converting values. Instead of a basic function, we use the __call__ method of the class, which itself calls another function depending on the attribute values. I'd like to reduce this overhead, any suggestion is more than welcome, as usual. Anyhow: as we do need speed, I suggest we put genloadtxt somewhere in numpy.ma, with an alias recfromcsv for John, using his defaults. Unless somebody comes with a brilliant optimization. Let me know how it goes, Cheers, P.

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Py3k and numpy
by Erik Tollerud 05 Dec '08

05 Dec '08

I noticed that the Python 3000 final was released today... is there any sense of how long it will take to get numpy working under 3k? I would imagine it'll be a lot to adapt given the low-level change, but is the work already in progress?

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