Mailman 3 October 2011 - SciPy-Dev

error in numpy-1.6.0 install
by akshar bhosale Oct. 21, 2011

Oct. 21, 2011

Hi, i have intel xeon 64 bit machine running rhel 5.2 x86_64. i have intel cluster toolkit installed (11/069) and mkl 10.3 what can be the best options for installing numpy-1.6.0 like what changes are required in site.cfg and intel compilers.py etc? what flags / options to be given while configuring/building/installing the same ? Any patches required? what are the deatail steps for the same?

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Re: [SciPy-Dev] Strange results by eigs
by Jacob VanderPlas Oct. 21, 2011

Oct. 21, 2011

>> The docstring of eigs is misleading in that context. >> >> M must represent a real symmetric matrix. >> > Yep, it should say hermitian instead of real sym. here. Actually, the piece of the documentation quoted here has to do with the second matrix supplied for the general eigenvalue problem. This matrix (M) must be real symmetric, as desribed in the ARPACK function documentation http://www.caam.rice.edu/software/ARPACK/UG/node137.html Jake

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Fw: problem in installing th scipy
by Gopalakrishnan Ravimohan Oct. 21, 2011

Oct. 21, 2011

with this mail i have attached the error file. which i tried to install in my cluster. plz help me in sorting the error as i am unable to find what is causing to exit the program before building. With Regards GOPALAKRISHNAN.R Senior Research Fellow C/o. Dr. V. Subramanian Chemical Laboratory Central Leather Research Institute (CSIR) India

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Strange results by eigs
by Nils Wagner Oct. 21, 2011

Oct. 21, 2011

Hi all, I am confused by the results of the following test from numpy import set_printoptions from numpy.random import seed, rand from scipy.linalg import eig from numpy import dot, diag from scipy.sparse.linalg import eigs from scipy.linalg import norm set_printoptions(precision=6) seed(10) n=5 A = rand(n,n)+ 1j*rand(n,n) B = rand(n,n)+ 1j*rand(n,n) w,vl,vr = eig(A,B,left=True, right=True) print 'Eigenvalues by eig' print w k = n-2 ws,vs = eigs(A,k,B) for i in range(k): r =dot(A,vr[:,i])-w[i]*dot(B,vr[:,i]) res = norm(r) print 'Residual', res print 'Eigenvalues by eigs' k = n-2 ws,vs = eigs(A,k,B) print ws for i in range(k): r =dot(A,vs[:,i])-ws[i]*dot(B,vs[:,i]) res = norm(r) print 'Residual', res Eigenvalues by eig [ 2.093178-1.783532j -0.202628+1.195944j 1.186895+0.56595j 0.014805-0.287354j 0.772942-0.266609j] Residual 1.9173960652e-15 Residual 2.20392640899e-15 Residual 3.21653472875e-15 Eigenvalues by eigs [ 19.064654+27.897369j 15.797549-27.544265j -0.249578-30.673974j] Residual 2.39453499962e-14 Residual 7.33698764801e-14 Residual 1.76193714267e-14 The eigenvalues returned by eig and eigs are completely different. Any idea ? I am using >>> scipy.__version__ '0.11.0.dev-600e81f' Nils

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weird results in frozen distribution fit
by josef.pktd＠gmail.com Oct. 20, 2011

Oct. 20, 2011

Given a report on the scipy-user mailing list http://projects.scipy.org/scipy/ticket/1536 I started for the first time to look at some examples with the frozen fit introduced in scipy 0.9. I just picked randomly some distributions that came to mind, except for the reported lognorm. some cases look ok, maybe. Some cases look "weird" Josef lognorm true 0.25 0.0 20.0 estimated, floc=0, loc=0 [ 2.1221 0. 2.4403] [ 0.2303 -1.8759 21.9986] [ 2.1454 0. 2.3763] [ 0.2446 0.0305 19.9945] [ 2.1274 0. 2.414 ] [ 0.2469 0.0296 19.9415] [ 2.1362 0. 2.3897] [ 0.2525 0.4579 19.4758] [ 2.1334 0. 2.4104] [ 0.2484 0.0298 20.0291] [ 2.1033 0. 2.475 ] [ 2.5335e-01 1.0858e-02 1.9959e+01] [ 2.1266 0. 2.414 ] [ 0.2662 1.3626 18.5458] [ 2.1316 0. 2.4176] [ 0.2491 0.0299 20.0509] [ 2.0897 0. 2.5211] [ 0.276 1.4881 18.5202] [ 2.1382 0. 2.3738] [ 0.2465 0.0301 19.8241] gamma true 2 20 10.0 estimated, floc=0, loc=0 [ 2.0945 20. 9.6182] [ 1.9864 20.0832 10.2119] [ 2.0317 20. 10. ] [ 2.0084 20. 10.101 ] [ 1.9364 20.1738 10.41 ] [ 2.0241 20. 10. ] [ 2.1359 20. 9.1555] [ 2.0353 19.8413 9.8974] [ 1.9937 20. 10. ] [ 2.2296 20. 8.6785] [ 2.152 19.8834 9.1795] [ 1.9948 20. 10. ] [ 1.8822 20. 10.8936] [ 2.0389 19.9836 9.8365] [ 2.0104 20. 10. ] [ 1.8304 20. 11.3802] [ 2.0341 20.169 9.7599] [ 2.0214 20. 10. ] [ 1.972 20. 9.7958] [ 1.9107 20.0777 10.1223] [ 1.9409 20. 10. ] [ 1.6211 20. 13.3028] [ 1.9636 20.1903 10.1156] [ 2.0103 20. 10. ] [ 2.0413 20. 9.8165] [ 2.0238 19.9456 9.9794] [ 2.0121 20. 10. ] [ 2.0087 20. 10.1362] [ 2.0128 20.1212 9.9924] [ 2.0299 20. 10. ] normal true 0.0 2.0 estimated, floc=0, loc=0, fscale=2 [ 0. 2.0024] [-0.0417 2.0024] [-0.0417 2. ] [ 0. 2.0003] [-0.0879 2.0003] [-0.0879 2. ] [ 0. 1.9466] [-0.0133 1.9466] [-0.0133 2. ] [ 0. 1.9726] [-0.036 1.9726] [-0.0359 2. ] [ 0. 2.0007] [-0.0194 2.0007] [-0.0195 2. ] [ 0. 1.9565] [ 0.0338 1.9565] [ 0.0337 2. ] [ 0. 1.9674] [ 0.0288 1.9674] [ 0.0289 2. ] [ 0. 1.9962] [ 0.0051 1.9962] [ 0.0051 2. ] [ 0. 1.8901] [ 0.0179 1.8901] [ 0.0179 2. ] [ 0. 2.0017] [ 0.0307 2.0017] [ 0.0307 2. ] chi2 true 10 0.0 2.0 estimated, floc=0, loc=0 [ 3.8459 0. 6.1457] [ 10.9616 -0.6938 1.8646] [ 3.8314 0. 6.3129] [ 10.4894 -0.295 1.9516] [ 3.7449 0. 6.4353] [ 9.7304 -0.0364 2.0654] [ 3.8094 0. 6.2268] [ 10.4314 -0.3388 1.9283] [ 3.69 0. 6.5633] [ 8.4951 1.1035 2.2316] [ 3.6475 0. 6.6415] [ 8.3315 0.8241 2.3152] [ 3.7288 0. 6.4983] [ 9.4114 0.2128 2.1185] [ 3.8005 0. 6.2852] [ 10.0038 -0.0154 1.9917] [ 3.7384 0. 6.4327] [ 8.4504 1.1931 2.224 ] [ 3.9063 0. 6.0929] [ 10.3413 0.2105 1.902 ] >>>

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Fwd: scipy.test gives error
by akshar bhosale Oct. 20, 2011

Oct. 20, 2011

On Tue, Oct 18, 2011 at 12:23 PM, akshar bhosale <akshar.bhosale(a)gmail.com>wrote: > > > ---------- Forwarded message ---------- > From: akshar bhosale <akshar.bhosale(a)gmail.com> > Date: Mon, Oct 17, 2011 at 11:26 PM > Subject: scipy.test gives error > To: scipy-user(a)scipy.org, scipy-dev-owner(a)scipy.org > > > Hi, > scipy.test gives following error : > MKL FATAL ERROR : can not load libmkl_lapack.so > import numpy;import scipy does not throw any error. > This library is present in the LD_LIBARY_PATH. > What can be the issue? > These modules were installed few days back and used to work. > > -Aksharb > >

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Faster implementation of cluster.hierarchy
by Conrad Lee Oct. 12, 2011

Oct. 12, 2011

A mathematician at Stanford named Daniel Müllner recently came up with a package that implements the hierarchical clustering methods found in scipy.cluster.hierarchy. His implementation is in C++, but includes a python API that uses the same interface as scipy.cluster.hierarchy. Müllner has posted benchmarks as well as algorithmic explanations of why his implementation is faster in a paper on arXiv<http://arxiv.org/abs/1109.2378>. He also has a webpage that describes the package here<http://math.stanford.edu/~muellner/fastcluster.html> . Because the results of the benchmarks look good, I am interested in getting the scikit-learn package to use this implementation for the hierarchical clustering provided by that package. Rather than integrate the code in scikit-learn, it seems more appropriate to integrate it upstream in scipy.cluster.hierarchy. Is there anyone who is interested in this integration? I am inexperienced with integrating C++ code and python code, and also with how things work in the scipy project, so I'm not sure how to proceed. Note: Although Müllner's code is currently under a GPL license, he has stated to me in e-mail that he would be willing to put it under the BSD-2 license it somebody put the time to integrate it into scipy. Best regards, Conrad Lee

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New machine for scipy.org
by Ognen Duzlevski Oct. 11, 2011

Oct. 11, 2011

Hello, I would like to use this email to introduce myself - my name is Ognen and I am Enthought's new IT director/Unix sysadmin. I would like to get your opinion on perhaps moving the scipy.org machine to an Amazon EC2 instance. I feel that such a solution would be more flexible and more accessible to people (not to mention probably faster and more stable). The box is right now (from what I can tell) an OpenVZ container on an older model physical Dell server housed in our data center, the container itself is backed up daily but were there to be connectivity or hardware issues, I am not sure recovery would be instantaneous. The underlying OpenVZ host seems to be low on disk space (and so is the scipy.org container consequently). The box itself runs an old RedHat version (I am not even sure it can be upgraded at this point). None of the above is really critical but I would like to improve the service if I can. Naturally, I would be more than happy to keep administering the new box and keep whoever else has administrative privileges to the old one. Opinions, thoughts...? Thanks! Ognen

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Re: [SciPy-Dev] Scipy Hilbert function in C#
by Subha Raj Oct. 11, 2011

Oct. 11, 2011

> Hello All, > I simply need to port the scipy Hilbert function in C# and > I am looking to use an open-source library (such as > Exocortex) for the FFT component of it. I have the following > code snippet. > float[] trace = new float[] { 1, 2, 3, 4}; > Fourier.FFT(trace, trace.Length/2, > FourierDirection.Forward); > Fourier.FFT(trace, trace.Length/2, > FourierDirection.Forward); > List<float> hilbert = new > List<float>(trace.Length); > for (int i = 0; i < trace.Length; i++) > { > hilbert.Add(0.0f); > } > for(int i=1; i<hilbert.Count/2; i++) > { > hilbert[i] = 2; > } > if(hilbert.Count/2 == 0) > { > hilbert[0] = hilbert[hilbert.Count/2] = 1; > } > List<float> hilbertResult = new List<float>(); > for (int i = 0; i < trace.Length; i++) > { > hilbertResult.Add(trace[i] * hilbert[i]); > } > float[] hilbertResult2 = hilbertResult.ToArray(); > Fourier.FFT(hilbertResult2, hilbertResult.Count/2, > FourierDirection.Backward); > hilbertResult2.Take(trace.Length); > But something doesn't seem to be working right. Can someone > help? > Regards, > Subha >

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numpy with dynamil python
by Grzegorz Brzęczyszczykiewicz Oct. 11, 2011

Oct. 11, 2011

Hi first of all I'm not sure of writeing on this mailing list. The description looked closest to nature of my problem. Soo if y question should be on other mailing ling please let me know and I will post it where it should be :). I need to compile numpy to use python as dynamic library. When you are compiling python from sources, usualy it builds libpython.2.X.a. I had build python2.X.so. My app uses it, the ldd command shows that app is loading libpytho2.X.so. Unfortunatly I have tried using -L and -l in setup.py scipr to add location of my lib and -python2.X flag to gcc. After the build numpy does not load the libpython SO file. For instance this shows ldd on multiarray.so: linux-gate.so.1 => (0x00f90000) libm.so.6 => /lib/tls/i686/cmov/libm.so.6 (0x0033f000) libpthread.so.0 => /lib/tls/i686/cmov/libpthread.so.0 (0x00632000) libc.so.6 => /lib/tls/i686/cmov/libc.so.6 (0x00a8e000) /lib/ld-linux.so.2 (0x00952000) Is there an easy way to tell numpy on build to use libpython2.X.so? Thx for your time :) Greg

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