Mailman 3 October 2004 - SciPy-User

g2c-pic
by David Grant 28 Oct '04

28 Oct '04

Does anyone know where the g2c-pic library is from? I'm trying to build the arpack python extension but it needs g2c-pic. I have g2c on my computer but not g2c-pic. It builds fine with just g2c but I'm not sure what the difference is between the two. Thanks, David -- David J. Grant http://www.davidgrant.ca:81

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(no subject)
by Mingyue Zheng 27 Oct '04

27 Oct '04

Hi All! I am trying to install scipy on a SGI workstation running IRIX 6.5, python-2.3.4 and gcc 3.2. On linking xplt lib, it reported the following errors: ld32: FATAL 12 : Expecting n32 objects: /usr/lib/libX11.so is o32. ld32: FATAL 12 : Expecting n32 objects: /usr/lib/libX11.so is o32. Does anyone know how to fix it? =================================================== Mingyue Zheng Drug Discovery and Design Center,SIMM Chinese Academy of Sciences #555 Rd.Zuchongzhi,Zhangjiang Hi-Tech. Park Shanghai 201203, China Tel: +86-21-50806600-1201(ext) E-mail: myzheng(a)mail.shcnc.ac.cn;　 myzheng(a)iris3.simm.ac.cn; ===================================================

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Mixing different type-codes in iterative solvers
by Nils Wagner 27 Oct '04

27 Oct '04

Hi all, It seems to be invalid to use different type-codes (e.g. complex coefficient matrix and double -precision real right-hand-side) within iterative solvers. However this is no problem in case of direct solvers. Any pointer would be appreciated. Nils

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More problems with Sparse
by Nils Wagner 27 Oct '04

27 Oct '04

Hi Travis, A few days ago I have reported on the following bug in sparse. (recent Bug tracker entries) It would be nice if this problem could be fixed. Thanks in advance. Nils >>> from scipy import * >>> A = sparse.dok_matrix() >>> A[0,0] = 1j >>> A.todense() Traceback (most recent call last): File "<stdin>", line 1, in ? File "/usr/lib/python2.3/site-packages/scipy/sparse/Sparse.py", line 1326, in todense new[ikey0,ikey1] = self[key] TypeError: can't convert complex to float; use abs(z)

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Sparse class not working
by David Grant 26 Oct '04

26 Oct '04

Has anyone been able to get scipy.sparse to work? Just running the Sparse.py file I get the following: Representation of a matrix: Traceback (most recent call last): File "E:\My Documents\working_dir\python\mm\testSparse.py", line 26, in ? print repr(a) File "D:\Python23\Lib\site-packages\scipy\sparse\Sparse.py", line 126, in __repr__ return "<%dx%d sparse matrix of type '%s' with %d stored "\ AttributeError: spmatrix instance has no attribute 'shape' I get the same problem if I run my own test code, which looks something like this: from scipy_base import * from scipy_base.fastumath import * import types, sys from scipy.sparse import sparsetools, _superlu from scipy.sparse.Sparse import * from Numeric import * a = spmatrix(arange(1,9),[0,1,1,2,2,3,3,4],[0,1,3,0,2,3,4,4]) print "Representation of a matrix:" print repr(a) print "How a matrix prints." print a print "Adding two matrices." b = a+a print b print "Subtracting two matrices." c = b - a print c print "Multiplying a sparse matrix by a dense vector." d = a*[1,2,3,4,5] print d print [1,2,3,4,5]*a If I comment out the repr(a) line which is causing the problem, b=a+a fails as well, because it says "AttributeError: spmatrix instance has no attribute 'tocsc'" What is going on here? -- David J. Grant

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sparse matrix formats
by David Grant 26 Oct '04

26 Oct '04

I am a bit boggled by all these sparse matrix types in the sparse class. Can anyone recommend which are the standard one I should use (when in doubt)? I know that one of my matrices is a diagonal matrix and the other matrix is 100% dense, however, it is tensor-producted with the identity matrix, so it becomes less dense. Some elements will be close to zero and can be truncated as well. Most values will be around the diagonals close to the main diagonal. _formats = {'csc':[0,"Compressed Sparse Column"], 'csr':[1,"Compressed Sparse Row"], 'dok':[2,"Dictionary Of Keys"], 'lil':[3,"LInked List"], 'dod':[4,"Dictionary of Dictionaries"], 'sss':[5,"Symmetric Sparse Skyline"], 'coo':[6,"COOrdinate"], 'lba':[7,"Linpack BAnded"], 'egd':[8,"Ellpack-itpack Generalized Diagonal"], 'dia':[9,"DIAgonal"], 'bsr':[10,"Block Sparse Row"], 'msr':[11,"Modified compressed Sparse Row"], 'bsc':[12,"Block Sparse Column"], 'msc':[13,"Modified compressed Sparse Column"], 'ssk':[14,"Symmetric SKyline"], 'nsk':[15,"Nonsymmetric SKyline"], 'jad':[16,"JAgged Diagonal"], 'uss':[17,"Unsymmetric Sparse Skyline"], 'vbr':[18,"Variable Block Row"], 'und':[19,"Undefined"] } -- David J. Grant Scientific Officer Intellectual Property D-Wave Systems Inc. tel: 604.732.6604 fax: 604.732.6614 ************************** CONFIDENTIAL COMMUNICATION This electronic transmission, and any documents attached hereto, is confidential. The information is intended only for use by the recipient named above. If you have received this electronic message in error, please notify the sender and delete the electronic message. Any disclosure, copying, distribution, or use of the contents of information received in error is strictly prohibited.

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the meaning of c_ and r_
by Gerald Richter 25 Oct '04

25 Oct '04

Hi everybody. Sorry for such a basic question, or maybe two: shouldn't c_[...] result in something like array([ [ . ], [ . ] ]) while r_ results in array([ ... ]) ? why does: In [23]: a = r_[1:3:5j] In [24]: b = c_[2:6:5j] In [25]: b Out[25]: array([ 2., 3., 4., 5., 6.]) In [26]: a Out[26]: array([ 1. , 1.5, 2. , 2.5, 3. ]) In [27]: transpose a -------> transpose(a) Out[27]: array([ 1. , 1.5, 2. , 2.5, 3. ]) In [28]: transpose b -------> transpose(b) Out[28]: array([ 2., 3., 4., 5., 6.]) not allow transposition in the above mentioned way? And: if I got some functions that might be useful to others, and want to contribute them, where do I turn to? I got some interp2() function, modeled after (translated from) the octave algorithm, and a polyfit() more or less woven from same wool... Also I had to implement a Log-likelyhood fitting algorithm, and with some work it could be generalized to be included in scipy, and there's a 2d-integral() on a grid of given surface. I'm working in high-energy physics, and found out, what a beatiful tool for algorithm prototyping scipy can be... AND I think (and one of my colleagues knows already ;) it will work even better in data-analysis, together with the bindings to ROOT (PyROOT) - http://root.cern.ch where Python can provide a really reasonable shell and scripting environment, instead of ROOT's C++ interpreter(!!!), and scipy can do the necessary data manipulations. Cheers, Gerald. -- Gerald Richter <richter(a)hephy.oeaw.ac.at> phone: +43 1 5447328/27 Institute of high energy physics (HEPHY) http://wwwhephy.oeaw.ac.at/ Vienna/Austria

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Versions question from kasparov
by Janet Swisher 22 Oct '04

22 Oct '04

I just noticed that "kasparov" added a comment a few days ago to the Troubleshooting wiki on scipy.org, with the following question: "Is it possible to run scipy 0.3.2 with python 2.3 and numeric 23.5. I have this two versions and i don't arrive to run correctly a program that use interpolate.linear_1d" I don't think anybody's monitoring that wiki closely, so it's probably not the best place for tech support questions. ------------------------- Janet Swisher Senior Technical Writer Enthought, Inc. 1-512-536-1057

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optimize.leastsq()
by Francesc Alted 22 Oct '04

22 Oct '04

Hi, Sorry for the bunch of questions, but I'm preparing some 'hands-on' on scipy, and I'm excercising many parts of it. I've tried to follow the Travis' tutorial for finding the best fit of a series of data, but my results are different from those stated there: In [96]: x = arange(0,6e-2,6e-2/30) In [97]: A,k,theta = 10, 1.0/3e-2, pi/6 In [98]: y_true = A*sin(2*pi*k*x+theta) In [99]: y_meas = y_true + 2*randn(len(x)) In [100]: def residuals(p, y, x): .....: A,k,theta = p .....: err = y-A*sin(2*pi*k*x+theta) .....: return err .....: In [101]: p0 = [8, 1/2.3e-2, pi/3] In [107]: optimize.leastsq(residuals, p0, args=(y_meas, x)) Out[107]: (array([ -2.17634575, 57.4116454 , -3.03266312]), 'Both actual and predicted relative reductions in the sum of squares\n are at most 0.000000') this results are quite different from the 'true' values: [ 10. 33.3333 0.5236] Do you have any idea about this error? I suppose that the message should indicate it, but I can't understand it. I'm using scipy 0.3.2 on Linux. BTW, thanks for clearifying the question about derivative() parameters. It's much more clear now. -- Francesc Alted

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Problems with complex matrices
by Nils Wagner 22 Oct '04

22 Oct '04

Hi all, Another bug is revealed Traceback (most recent call last): File "complex_it.py", line 6, in ? res=dot(A,x)-r File "/usr/lib/python2.3/site-packages/Numeric/dotblas/__init__.py", line 55, in dot if multiarray.array(a).shape == () or multiarray.array(b).shape == (): TypeError: a float is required Nils

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