Mailman 3 April 2009 - SciPy-User

Help required regding Eigenvectors
by Sudheer Phani 14 Mar '22

14 Mar '22

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

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pupynere/scipy.io.netcdf
by Ryan May 06 Mar '13

06 Mar '13

Hi, Anyone know if pupynere (a version of which is in scipy.io.netcdf) supports writing files with 64-bit offsets? This allows writing files larger than 2GB. Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma

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scipy/numpy on CentOS 5/ Dependency problem
by Matthias Blaicher 08 Dec '10

08 Dec '10

Hello, I want to install SciPy and numpy on a CentOS 5 system. It contains a fresh install with up-to-date packages. I use the "official" Suse Build repos by DavidCournapeau. It fails with a conflict between refblas3 and blas. [root@localhost yum.repos.d]# yum install python-numpy python-scipy Loading "fastestmirror" plugin Loading mirror speeds from cached hostfile * home_ashigabou: download.opensuse.org * extras: mirrors.tummy.com * updates: dds.gina.alaska.edu * base: mirror.hmc.edu * addons: mirrors.tummy.com extras 100% |=========================| 1.1 kB 00:00 updates 100% |=========================| 951 B 00:00 base 100% |=========================| 1.1 kB 00:00 addons 100% |=========================| 951 B 00:00 Setting up Install Process Parsing package install arguments Resolving Dependencies --> Running transaction check ---> Package python-scipy.i386 0:0.6.0-2.1 set to be updated --> Processing Dependency: libblas.so.3 for package: python-scipy --> Processing Dependency: libblas.so.3 for package: python-scipy --> Processing Dependency: liblapack.so.3 for package: python-scipy --> Processing Dependency: libgfortran.so.1 for package: python-scipy --> Processing Dependency: liblapack.so.3 for package: python-scipy ---> Package python-numpy.i386 0:1.2.0-1.1 set to be updated --> Processing Dependency: gcc-gfortran for package: python-numpy --> Processing Dependency: refblas3 for package: python-numpy --> Processing Dependency: lapack3 < 3.1 for package: python-numpy --> Running transaction check ---> Package gcc-gfortran.i386 0:4.1.2-42.el5 set to be updated --> Processing Dependency: gcc = 4.1.2-42.el5 for package: gcc-gfortran ---> Package blas.i386 0:3.0-37.el5 set to be updated ---> Package lapack3.i386 0:3.0-19.1 set to be updated ---> Package lapack.i386 0:3.0-37.el5 set to be updated ---> Package refblas3.i386 0:3.0-11.1 set to be updated ---> Package libgfortran.i386 0:4.1.2-42.el5 set to be updated --> Running transaction check ---> Package gcc.i386 0:4.1.2-42.el5 set to be updated --> Processing Dependency: libgomp.so.1 for package: gcc --> Processing Dependency: glibc-devel >= 2.2.90-12 for package: gcc --> Processing Dependency: libgomp = 4.1.2-42.el5 for package: gcc --> Running transaction check ---> Package glibc-devel.i386 0:2.5-24 set to be updated --> Processing Dependency: glibc-headers for package: glibc-devel --> Processing Dependency: glibc-headers = 2.5-24 for package: glibc-devel ---> Package libgomp.i386 0:4.1.2-42.el5 set to be updated --> Running transaction check ---> Package glibc-headers.i386 0:2.5-24 set to be updated --> Processing Dependency: kernel-headers for package: glibc-headers --> Processing Dependency: kernel-headers >= 2.2.1 for package: glibc-headers --> Running transaction check ---> Package kernel-headers.i386 0:2.6.18-92.1.13.el5 set to be updated --> Processing Conflict: refblas3 conflicts blas --> Finished Dependency Resolution Error: refblas3 conflicts with blas Is there anything I'm doing wrong here, as I don't want to compile all dependencies by myself.. Sincerly, Matthias Blaicher

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64 bit on Mac?
by Keflavich 26 Sep '10

26 Sep '10

Hi folks, I'd really like to work with some of the large images I have; I work on a galactic plane survey that has lots of images with ~10^8 floating point pixels. I'm also using a mac. Unfortunately I can't get a 64-bit version of python compiled and google has been unhelpful in resolving the problem. Is there a workaround to get 64 bit numpy working without 64 bit python installed? I doubt that, but if anyone has tips I'd appreciate them. On a related note, I also use a linux machine with 64 bit python installed, but it crashes with large arrays giving a segfault where my mac spits out the "ValueError: dimensions too large." error. Any ideas there? Thanks, Adam

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problems with splrep,splev
by Christian K. 08 Jun '10

08 Jun '10

Hi, I am having problems with the spline functions from scipy.interpolate. Reading the doc strings I expected the following to work: from scipy.interpolate import splev,splrep import numpy as N x = N.linspace(-4,10,5) y = x**2 t,c,l = splrep(x,y,xb=0,xe=4) Traceback (most recent call last): File "C:\pythonxy\python\lib\site-packages\scipy\interpolate\fitpack.py", line 406, in splrep n,c,fp,ier = dfitpack.curfit(task, x, y, w, t, wrk, iwrk, xb, xe, k, s) error: (xb<=x[0]) failed for 1st keyword xb Second, I want to fit several curves using the same knots, thus I tried the following: y2 = x**2-3*x+4 t2,c2,l2 = splrep(x,y2,t=t) Traceback (most recent call last): File "C:\pythonxy\python\lib\site-packages\scipy\interpolate\fitpack.py", line 418, in splrep raise _iermess[ier][1],_iermess[ier][0] ValueError: Error on input data Are those bugs or am I misunderstanding something? Eventually I would like to morph one spline into another, therefor I want to stick with the knots. If anyone has experiences with splines and morphing I would be very interested to hear about it. Regards, Christian

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3D plotting
by Robert Cimrman 10 Sep '09

10 Sep '09

Hi, I need to do some simple 3D plots, so I tried the two Cookbook recipes (xplt, mplot3d) and failed: * xplt: does not work when using a custom installation directory such as python setup.py install --root=/home/share/software apparently the gistdata directory path is wrong: gist.error: failed to create drawing -- Gist work.gs style sheet missing * mplot3d: does not work with my version of matplotlib (0.80). I have made the changes mentioned in the Cookbook to no avail. (Axes.__init__() args apparently changed, as well as some other matplotlib object attributes) Any ideas? mplot3d looks great, I would really like to use it! thanks, r.

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assign to diagonal values?
by Carlos Scheidegger 07 Jul '09

07 Jul '09

Say I have a matrix m whose diagonal values I want to replace with the contents of vector new_diagonal. Right now, I'm using m -= diag(m) m += diag(new_diagonal) but that seems pretty wasteful (especially if diag() creates new arrays, which I suspect it does). Is there a standard (or any efficient) way to assign the diagonal values directly without an explicit for loop? Googling for "site:www.scipy.org assign diagonal" only returned results for sparse matrices, which is not the case here - these are plain numpy arrays. Thanks in advance, -carlos

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scipy.signal.firwin
by Jan Rauberg 19 May '09

19 May '09

I'm missing the functionality of firwin like in matlab/octave fir1, so that I can give a 'low', 'high' and 'stop' option. I don't know how to create a FIR window based high pass filter. Or is there something planned for the future? Thank you Jan

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Looking for a way to cluster data
by Gary Ruben 16 May '09

16 May '09

Hi all, I'm looking for some advice on how to order data points so that I can visualise them. I've been looking at scipy.cluster for this purpose but I'm not sure whether it is suitable so I thought I'd see whether anyone had suggestions for a simpler suggestion of how to order the coordinates. I have a binary 3D array containing 1's that form a shape in a 3D volume against a background of 0's - they form a skeleton of a connected, branched structure. Furthermore, the points are all 26-connected to each other, i.e. there are no gaps in the skeleton. The longest chains may be 1000's of points long. It would be nice to visualise these using the mayavi mlab plot3d function, which draws tubes and which requires ordered coordinates as input, so I need to get ordered coordinate lists that traverse the points along the branches of the skeleton. It would also be nice to preferentially cluster long chains since then I can cull very short chains from the visualisation. scipy.cluster seems to be able to cluster the points but I'm not sure how to get the x,y,z coordinates of the original points out of its linkage data. This may not be possible. Maybe the scipy.spatial module is a better match to my problem. Any suggestions? Gary

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Is numpy's argsort lying about its numpy.int32 types?
by Rob Clewley 15 May '09

15 May '09

Hi, I'm having a problem comparing some types when using numpy's argsort. I'm using numpy 1.0.2. I can reproduce it simply: Python 2.4.4 (#71, Oct 18 2006, 08:34:43) [MSC v.1310 32 bit (Intel)] << snip >> In [1]: from numpy import argsort, sort, int32, array In [2]: x=array([1,3,2]) In [3]: aa=argsort(x) In [4]: as=sort(x) In [5]: type(aa[0]) Out[5]: <type 'numpy.int32'> In [6]: type(as[0]) Out[6]: <type 'numpy.int32'> In [7]: int32 Out[7]: <type 'numpy.int32'> In [8]: type(as[0])==int32 Out[8]: True In [9]: type(aa[0])==int32 Out[9]: False Any of the three indices in aa give me the same problem. Can someone explain if I should be doing this a different way, and if this is a bug?! Thanks, Rob

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