Mailman 3 June 2006 - NumPy-Discussion

byteorder question
by Jonathan Taylor 02 Jul '06

02 Jul '06

In some earlier code (at least one of) the following worked fine. I just want to get a new type that is a byteswap of, say, float64 because I want to memmap an array with a non-native byte order. Any suggestions? Thanks, Jonathan ------------------------------------------ Python 2.4.3 (#2, Apr 27 2006, 14:43:58) [GCC 4.0.3 (Ubuntu 4.0.3-1ubuntu5)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy >>> numpy.__version__ '0.9.9.2716' >>> d=numpy.float64 >>> swapped=d.newbyteorder('big') Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: descriptor 'newbyteorder' requires a 'genericscalar' object but received a 'str' >>> swapped=d.newbyteorder('>') Traceback (most recent call last): File "<stdin>", line 1, in ? TypeError: descriptor 'newbyteorder' requires a 'genericscalar' object but received a 'str' >>> -- ------------------------------------------------------------------------ Jonathan Taylor Tel: 650.723.9230 Dept. of Statistics Fax: 650.725.8977 Sequoia Hall, 137 www-stat.stanford.edu/~jtaylo 390 Serra Mall Stanford, CA 94305

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problem building Numeric on python 2.5
by Russell E. Owen 02 Jul '06

02 Jul '06

I just installed python 2.5b1 on my Mac (10.4 ppc) and can't seem to get Numeric 24.2 installed. It seems to build fine (no obvious error messages), but when I try to import it I get: Python 2.5b1 (r25b1:47038M, Jun 20 2006, 16:17:55) [GCC 4.0.1 (Apple Computer, Inc. build 5341)] on darwin Type "help", "copyright", "credits" or "license" for more information. >>> import Numeric __main__:1: ImportWarning: Not importing directory '/Library/Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-pac kages/Numeric': missing __init__.py >>> Any ideas? Is it somehow incompatible with python 2.5b1? For what it's worth, numarray builds and installs fine. I've not tried numpy or any other packages yet. -- Russell

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ANN: SciPy 2006 Conference Reminder
by Travis N. Vaught 30 Jun '06

30 Jun '06

The *SciPy 2006 Conference* is scheduled for Thursday and Friday, August 17-18, 2006 at CalTech with Sprints and Tutorials Monday-Wednesday, August 14-16. Conference details are at http://www.scipy.org/SciPy2006 The deadlines for submitting abstracts and early registration are approaching... Call for Presenters ------------------- If you are interested in presenting at the conference, you may submit an abstract in Plain Text, PDF or MS Word formats to abstracts at scipy.org <http://mail.python.org/mailman/listinfo/python-announce-list> -- the deadline for abstract submission is July 7, 2006. Papers and/or presentation slides are acceptable and are due by August 4, 2006. Registration: ------------- Early registration ($100.00) is still available through July 14. You may register online at http://www.enthought.com/scipy06. Registration includes breakfast and lunch Thursday & Friday and a very nice dinner Thursday night. After July 14, 2006, registration will cost $150.00. Tutorials and Sprints --------------------- This year the Sprints (Monday and Tuesday, August 14-15) and Tutorials (Wednesday, August 16) are no additional charge (you're on your own for food on those days, though). Remember to include these days in your travel plans. The following topics are presented as Tutorials Wednesday (more info here: http://www.scipy.org/SciPy2006/TutorialSessions): - "3D visualization in Python using tvtk and MayaVi" - "Scientific Data Analysis and Visualization using IPython and Matplotlib." - "Building Scientific Applications using the Enthought Tool Suite (Envisage, Traits, Chaco, etc.)" - "NumPy (migration from Numarray & Numeric, overview of NumPy)" The Sprint topics are under discussion here: http://www.scipy.org/SciPy2006/CodingSprints See you in August! Travis

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Matrix print plea
by Keith Goodman 30 Jun '06

30 Jun '06

When an array is printed, the numbers line up in nice columns (if you're using a fixed-width font): array([[0, 0], [0, 0]]) But for matrices the columns do not line up: matrix([[0, 0], [0, 0]])

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A. Martelli on Numeric/Numpy
by Mark Heslep 30 Jun '06

30 Jun '06

FYI, posted Sunday on python: "...even if the hard-core numeric-python people are all evangelizing for migration to numpy (for reasons that are of course quite defensible!), I think it's quite OK to stick with good old Numeric for the moment (and that's exactly what I do for my own personal use!)" "...Numeric has pretty good documentation (numpy's is probably even better, but it is not available for free, so I don't know!), and if you don't find that documentation sufficient you might want to have a look to my book "Python in a Nutshell" which devotes a chapter to Numeric..." http://groups.google.com/group/comp.lang.python/tree/browse_frm/thread/e547… Mark

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Setuptools leftover junk
by Fernando Perez 30 Jun '06

30 Jun '06

Hi all, I recently noticed one of my in-house projects started leaving aroun .egg-info directories after I ran its setup.py, even though I don't use setuptools for anything at all. For now I just added an extra clean rule to my makefile and forgot about it, but it kind of annoyed me. Today I looked at the temp directory where I've been making my numpy/scipy installs from SVN, and here's what I saw: longs[site-packages]> d /home/fperez/tmp/local/lib/python2.4/site-packages total 228 drwxr-xr-x 2 fperez 4096 2006-06-21 22:16 dateutil/ drwxr-xr-x 7 fperez 4096 2006-06-28 02:50 matplotlib/ drwxr-xr-x 13 fperez 4096 2006-06-28 02:38 numpy/ drwxr-xr-x 2 fperez 4096 2006-06-21 21:28 numpy-0.9.9.2660-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-22 21:29 numpy-0.9.9.2665-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-24 11:33 numpy-0.9.9.2674-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-24 15:08 numpy-0.9.9.2675-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-25 12:40 numpy-0.9.9.2677-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-26 23:32 numpy-0.9.9.2691-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-28 02:38 numpy-0.9.9.2696-py2.4.egg-info/ -rw-r--r-- 1 fperez 31 2006-03-18 20:11 pylab.py -rw-r--r-- 1 fperez 178 2006-06-24 13:29 pylab.pyc drwxr-xr-x 20 fperez 4096 2006-06-28 11:20 scipy/ drwxr-xr-x 2 fperez 4096 2006-06-21 21:36 scipy-0.5.0.1990-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-22 21:36 scipy-0.5.0.1998-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-24 15:15 scipy-0.5.0.1999-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-25 12:46 scipy-0.5.0.2000-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-26 23:37 scipy-0.5.0.2004-py2.4.egg-info/ drwxr-xr-x 2 fperez 4096 2006-06-28 02:48 scipy-0.5.0.2012-py2.4.egg-info/ Is it really necessary to have all that setuptools junk left around, for those of us who aren't asking for it explicitly? My personal opinions on setuptools aside, I think it's just a sane practice not to create this kind of extra baggage unless explicitly requested. I scoured my home directory for any .file which might be triggering this inadvertedly, but I can't seem to find any, so I'm going to guess this is somehow being caused by numpy's own setup. If it's my own mistake, I'll be happy to be shown how to coexist peacefully with setuptools. Since this also affects user code (I think via f2py or something internal to numpy, since all I'm calling is f2py in my code), I really think it would be nice to clean it. Opinions? f

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without guilt braiding
by Hope 30 Jun '06

30 Jun '06

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Re: [Numpy-discussion] Time for beta1 of NumPy 1.0 (fwd)
by Louis Cordier 30 Jun '06

30 Jun '06

> While it is hard to read too much into numbers, this tells me that there > are about 10,000 current users of Numeric/Numarray who have not even > *tried* NumPy. In fact, Numarray downloads of 1.5.1 went up > significantly from its earlier releases. Why is that? It could be > that many of the downloads are "casual" users who need it for some other > application (in which case they wouldn't feel inclined to try NumPy). Secondary dependency of other projects maybe ? http://www.google.com/search?q=requires+Numeric+python My money is on Spambayes... On the other hand ;) isn't small numbers a good thing, thus the people using NumPy over Numeric/numarray knows that some things in NumPy might still change and thus their code as well. I'll risk to say their projects are probably also still under active development. So now would probably be the best time to make these type of changes. Stated differently, how would we like NumPy to function 2 years from now ? With float64's or with int's ? Then we should rather change it now. Then again where are NumPy in a crossing the chasm (http://en.wikipedia.org/wiki/Crossing_the_Chasm) sense of way, visionary or pragmatist ? Just a few random thoughts. Regards, Louis. -- Louis Cordier <lcordier(a)point45.com> cell: +27721472305 Point45 Entertainment (Pty) Ltd. http://www.point45.org

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MDP-2.0 released
by Tiziano Zito 30 Jun '06

30 Jun '06

MDP version 2.0 has been released! What is it? ----------- Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP consists of a collection of trainable supervised and unsupervised algorithms that can be combined into data processing flows. The base of readily available algorithms includes Principal Component Analysis, two flavors of Independent Component Analysis, Slow Feature Analysis, Gaussian Classifiers, Growing Neural Gas, Fisher Discriminant Analysis, and Factor Analysis. From the developer's perspective, MDP is a framework to make the implementation of new algorithms easier. MDP takes care of tedious tasks like numerical type and dimensionality checking, leaving the developer free to concentrate on the implementation of the training and execution phases. The new elements then automatically integrate with the rest of the library. As its user base is increasing, MDP might be a good candidate for becoming a common repository of user-supplied, freely available, Python implemented data processing algorithms. Resources --------- Download: http://sourceforge.net/project/showfiles.php?group_id=116959 Homepage: http://mdp-toolkit.sourceforge.net Mailing list: http://sourceforge.net/mail/?group_id=116959 What's new in version 2.0? -------------------------- MDP 2.0 introduces some important structural changes. It is now possible to implement nodes with multiple training phases and even nodes with an undetermined number of phases. This allows for example the implementation of algorithms that need to collect some statistics on the whole input before proceeding with the actual training, or others that need to iterate over a training phase until a convergence criterion is satisfied. The ability to train each phase using chunks of input data is maintained if the chunks are generated with iterators. Nodes that require supervised training can be defined in a very straightforward way by passing additional arguments (e.g., labels or a target output) to the 'train' method. New algorithms have been added, expanding the base of readily available basic data processing elements. MDP is now based exclusively on the NumPy Python numerical extension. -- Tiziano Zito Institute for Theoretical Biology Humboldt-Universitaet zu Berlin Invalidenstrasse, 43 D-10115 Berlin, Germany Pietro Berkes Gatsby Computational Neuroscience Unit Alexandra House, 17 Queen Square London WC1N 3AR, United Kingdom

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Bug in digitize function
by David Huard 30 Jun '06

30 Jun '06

Hi, Here is something I noticed with digitize() that I guess would qualify as a small but annoying bug. In [165]: x = rand(10); bin = linspace(x.min(), x.max(), 10); print x.min(); print bin[0]; digitize(x,bin) 0.0925030184144 0.0925030184144 Out[165]: array([2, 9, 5, 9, 6, 1, 1, 1, 4, 5]) In [166]: x = rand(10); bin = linspace(x.min(), x.max(), 10); print x.min(); print bin[0]; digitize(x,bin) 0.0209738428066 0.0209738428066 Out[166]: array([ 5, 2, 8, 3, 0, 8, 9, 6, 10, 9]) Sometimes, the smallest number in x is counted in the first bin, and sometimes, it is counted as an outlier (bin number = 0). Moreover, creating the bin with bin = linspace(x.min()-eps, x.max(), 10) doesn't seem to solve the problem if eps is too small (ie 1./2**32). So basically, you can have In [186]: x.min()>bin[0] Out[186]: True and yet digitize() considers x.min() as an outlier. And to actually do something constructive, here is a docstring for digitize """Given an array of values and bin edges, digitize(values, bin_edges) returns the index of the bin each value fall into. The first bin has index 1, and the last bin has the index n, where n is the number of bins. Values smaller than the inferior edge are assigned index 0, while values larger than the superior edge are assigned index n+1. """ Cheers, David P.S. Many mails I send don't make it to the list. Is it gmail related ?

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