Mailman 3 August 2002 - NumPy-Discussion

QR algorithms in Python
by James G Analytis 13 Aug '02

13 Aug '02

Hi, I'm looking for a QR algorithm that can decompose complex matrices. The LinearAlgebra package from Numeric doesn't seem to have it. SciPy's linalg package is still on the way, so I can't use that either. Matfunc's QR decomposition only works for real matrices. This problem came up two years ago on this same discussion panel, and Konrad Hinsen recommended that the user download PyLapack from ftp://dirac.cnrs-orleans.fr/pub/ I cannot compile PyLapack because I get this problem: [analytis@toomey Modules]$ python2 compile.py Copy Misc/Makefile.pre.in from the Python distribution to this directory and try again. make: Makefile.pre.in: No such file or directory make: *** No rule to make target `Makefile.pre.in'. Stop. make: *** No targets specified and no makefile found. Stop. [analytis@toomey Modules]$ I think the Makefile searched for is one from an earlier version of Numeric (the tar file is 2yrs old). Any suggestions? Cheers, James

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Scientific data - Reading files
by Nils Wagner 12 Aug '02

12 Aug '02

Hi, I have collected acceleration data by a multi-channel data acquisition system. Each file (E1431A*.DAT) contains one column with real numbers. The contents of the i-th file should be stored in the i-th row of a data matrix A. How can I manage this task efficiently ? Are there suitable python modules for this purpose ? A small example would be appreciated. Nils

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floating point exceptions
by bryan cole 12 Aug '02

12 Aug '02

I've just ported a Numeric+Python program from windows to linux and I'm generating floating point exceptions in the linux version which did not occur in windows. I'm trying to generate a gaussian distribution by: Input = Numeric.arange(-1024,1024)/20.0 Output = Numeric.exp(-(Input**2)) At the edges of the distribution the largish negative arguments cause the f.p. exception and prevent calculation of the entire array. On windows the underflow errors are presumably rounded down to 0.0 automatically. Is it possible to get this behaviour on linux/ix86? Anyone got any suggestions on a workarround for this? I see the numpy docs suggest using Masked Arrays, but since I don't know in advance which array items will generate the exceptions, I don't know which items to mask. Can the MA module generate an array mask based on f.p. exceptions from a calculation? any suggestions would be much appreciated. Bryan -- Bryan Cole Teraview Ltd., 302-304 Cambridge Science Park, Milton Road, Cambridge CB4 0WG, United Kingdom. tel: +44 (1223) 435380 / 435386 (direct-dial) fax: +44 (1223) 435382

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Newbie MA question
by Cath Lawrence 08 Aug '02

08 Aug '02

Hi, I'm not sure this is the right list - looking at the archives you guys look more like developers more than users. Any pointers to the proper place, or TFMs to R, are welcome. (Yes, I have & have read the Numerical Python documentation.) That said, I'm trying to use masked arrays (for a bioinformatics app calculating stats on distances between pairs of amino acids, if you want to know) and am having a little trouble printing. One possible bug - "x.__str__()" and "x.__repr__()" show different typecodes. Example: >>> import MA >>> id = MA.identity(20) >>> r = MA.ones((20,20))*1.0 >>> rm = MA.MaskedArray(r, mask=id) >>> rm # ie, call x.__repr__() array(data = array (20,20) , type = d, has 400 elements, mask = array (20,20) , type = 1, has 400 elements, fill_value=[ 1.00000002e+20,]) >>> print rm # ie, call x.__str__() array (20,20) , type = O, has 400 elements >>> Secondly, I can't see how to make this print the whole thing if I want it. Which I do; all my matrices are 20*20 'cause there are 20 amino acids. The Numeric.array2string method can't be used because the data is always masked. The best I've found so far is to make a Numeric array by filling with an impossible number like -1, then use array2string. But visually it would be nicer to see the masked values as "--". Thanks for any help, regards, Cath Cath Lawrence, Cath.Lawrence(a)anu.edu.au Scientific Programmer, Centre for Bioinformation Science, John Curtin School of Medical Research Australian National University, Canberra ACT 0200 ph: Maths (02) 6125 2904; JCSMR (02) 6125 0417; mobile: 0421-902694 fax: (02) 61254712

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more functions for MLab.py: find, unique, union, intersect, etc.
by Mark Histed 07 Aug '02

07 Aug '02

I've written some glue functions along the lines of what's in MLab.py: find unique union intersect setdiff setxor Quick questions: * any opinions on the algorithms used? * are these worth adding to MLab.py? If so, do I need to provide documentation updates? I can send this as a patch to MLab.py too. * Does anyone have opinions on what to do about the optional outputs from matlab functions? Is it worth trying to provide index matrices as second arguments, for example? If so, any opinions on implementation? a matlab user trying to get started with Numeric, Mark

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