Mailman 3 February 2007 - NumPy-Discussion

Greek Letters
by Mark Janikas 21 Feb '07

21 Feb '07

Hello all, I was wondering how I could print the chi-squared symbol in python. I have been looking at the Unicode docs, but I figured I would ask for assistance here while I delve into it. Thanks for any help in advance. Mark Janikas Product Engineer ESRI, Geoprocessing 380 New York St. Redlands, CA 92373 909-793-2853 (2563) mjanikas(a)esri.com

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Request for porting pycdf to NumPy
by Andre Gosselin 21 Feb '07

21 Feb '07

Hi everybody. I have just released version 0.6-3 of pycdf, which finally supports the NumPy array package (along Numeric and numarray). Here is the announcement. ================================== Project "pysclint" ('pysclint') has released the new version of package 'pycdf'. You can download it from SourceForge.net by following this link: <https://sourceforge.net/project/showfiles.php? group_id=143145&release_id=485773 > or browse Release Notes and ChangeLog by visiting this link: <https://sourceforge.net/project/shownotes.php?release_id=485773> ================================== I was pleased to follow this thread about pycdf, and see the number of people who are pleased with it. In case anybody doubts it, I will still actively maintain pycdf. Best regards, André Gosselin gosselina(a)dfo-mpo.gc.ca

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Forcing the use of unoptimized blas/lapack even when atlas is present
by David Cournapeau 19 Feb '07

19 Feb '07

Hi there, I am developing a building tool to automatically build the whole numpy/scipy/matplotlib set from sources including dependencies, and one of the problem I got is to force which blas/lapack version to use when building numpy and scipy. I thought that doing a BLAS=blaslib LAPACK=lapacklib python setup.config was enough when build numpy, but numpy still wants to use atlas. I would like to avoid using site.cfg if possible, as I want to build everything automatically, cheers, David

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linalg.eigh orders eigenvalues/eigenvectors differently than linalg.eig
by Zachary Pincus 19 Feb '07

19 Feb '07

Hello all, It seems that the 'eigh' routine from numpy.linalg does not follow the same convention as numpy.linalg.eig in terms of the order of the returned eigenvalues. (And thus eigenvectors as well...) Specifically, eig returns eigenvalues in order from largest to smallest, while eigh returns them from smallest to largest. Example: >>> a = numpy.array([[21, 28, 35],[28, 38, 48],[35, 48, 61]]) >>> numpy.linalg.eigh(a) (array([ -1.02825542e-14, 7.04131679e-01, 1.19295868e+02]), array([[ 0.40824829, -0.81314396, -0.41488581], [-0.81649658, -0.12200588, -0.56431188], [ 0.40824829, 0.56913221, -0.71373795]])) >>> numpy.linalg.eig(a) (array([ 1.19295868e+02, 7.04131679e-01, 4.62814557e-15]), array([[-0.41488581, -0.81314396, 0.40824829], [-0.56431188, -0.12200588, -0.81649658], [-0.71373795, 0.56913221, 0.40824829]])) Is this a bug? If it is, though, fixing it now might break code that depends on this 'wrong' order. (This is also present in scipy.linalg.) If not a bug, or not-fixable-now, then at least some documentation as to the convention regarding ordering of eigenvalues is probably worthwhile... Any thoughts? Zach

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Numpy1.0.1 installation problem - urgent :(
by lu yang 19 Feb '07

19 Feb '07

Hi, This is the first time I install Numpy on a linux machine. I have been working on it for several days without luck. I sincerely appreciate if anybody can give any comments. My OS is Red Hat 8. I have downloaded Python 2.5 and Numpy 1.0.1. Python 2.5 has been installed on my machine. However, when I type: "python2.5 setup.py install" to install Numpy in my home directory /home/o6c11/numpy-1.0.1 , I got: [o6c11@chorus numpy-1.0.1]$ python2.5 setup.py install Traceback (most recent call last): File "setup.py", line 89, in <module> setup_package() File "setup.py", line 59, in setup_package from numpy.distutils.core import setup File "numpy/__init__.py", line 36, in <module> import core File "/mnt/storage/home/o6c11/numpy-1.0.1/numpy/core/__init__.py", line 5, in <module> import multiarray ImportError: No module named multiarray I changed the directory to /usr/local/lib/python2.5/site-packages/numpy, I got: [o6c11@chorus numpy]$ python2.5 setup.py install Traceback (most recent call last): File "setup.py", line 28, in <module> from numpy.distutils.core import setup File "/usr/local/lib/python2.5/site-packages/numpy/__init__.py", line 40, in <module> import linalg File "/usr/local/lib/python2.5/site-packages/numpy/linalg/__init__.py", line 4, in <module> from linalg import * File "/usr/local/lib/python2.5/site-packages/numpy/linalg/linalg.py", line 25, in <module> from numpy.linalg import lapack_lite ImportError: /usr/lib/libblas.so.3: undefined symbol: e_wsfe I also tried to import numpy in this way: [o6c11@chorus numpy]$ python2.5 Python 2.5 (r25:51908, Feb 12 2007, 22:36:33) [GCC 3.2 20020903 (Red Hat Linux 8.0 3.2-7)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> import numpy Traceback (most recent call last): File "<stdin>", line 1, in <module> File "/usr/local/lib/python2.5/site-packages/numpy/__init__.py", line 40, in <module> import linalg File "/usr/local/lib/python2.5/site-packages/numpy/linalg/__init__.py", line 4, in <module> from linalg import * File "/usr/local/lib/python2.5/site-packages/numpy/linalg/linalg.py", line 25, in <module> from numpy.linalg import lapack_lite ImportError: /usr/lib/libblas.so.3: undefined symbol: e_wsfe >>> I have no idea how to solve these problems. Please help a newbie. Thanks a lot.

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Re: [Numpy-discussion] (no subject)
by Nadav Horesh 17 Feb '07

17 Feb '07

It looks like you encountered a fundamental short come of numpy (or in fact any similar system like octave, matlab etc...): The dependence on values calculated in previous iteration can not vectorize easily. If you have an access to C compiler, I urge you to write (at least) the inner loop with pyrex or a similar package that can easily link C code with numpy. It would help you a lot to realize these kind of algorithms with a reasonable execution time without loosing much of the python's benefits. Nadav -----Original Message----- From: numpy-discussion-bounces(a)scipy.org on behalf of gzhu(a)peak6.com Sent: Fri 16-Feb-07 18:34 To: numpy-discussion(a)scipy.org Cc: Subject: [Numpy-discussion] (no subject) Hi Nadav, The code is attached at the end. There is probably still bugs in there but it does not prevent me from showing the difficulty. If you look at the inner loop below, you will see that vector v is updated element by element. The new value of v[i] depends on the new value of v[i-1] and the old value of v[i+1]. Updating an element involves the new values of the already updated elements and the old values of the rest of the elements that we have yet to update. This makes vectorization difficult. for i in range(1,N-1): temp[i]=(1-w)*v[i]+w/D[i]*(q[i]-L[i-1]*v[i-1]-U[i]*v[i+1]) err += (temp[i]-v[i])**2 v[i]=temp[i] Thanks, Geoffrey Complete code here; def sor(v, L, D, U ,q, tol, w): '''solve M*v=q. return v. L, D, U are the sub-diagonal, diagonal, and super-diagonal of the matrix M. ''' err=9999999 N=D.shape[0] #number of elements temp=empty(N) while err> tol : err=0 temp[0]=(1-w)*v[0]+w/D[0]*(q[0]-U[0]*v[1]) err += (temp[0]-v[0])**2 v[0]=temp[0] for i in range(1,N-1): temp[i]=(1-w)*v[i]+w/D[i]*(q[i]-L[i-1]*v[i-1]-U[i]*v[i+1]) err += (temp[i]-v[i])**2 v[i]=temp[i] temp[N-1]=(1-w)*v[N-1]+w/D[N-1]*(q[N-1]-L[N-2]*v[N-2]) err += (temp[N-1]-v[N-1])**2 v[N-1]=temp[N-1] return v -----Original Message----- From: numpy-discussion-bounces(a)scipy.org [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of Nadav Horesh Sent: Friday, February 16, 2007 8:52 AM To: Discussion of Numerical Python Subject: RE: [Numpy-discussion] Numpy and iterative procedures At first glance it doesn't look hard to, at least, avoid looping over i, by replacing [i] by [:-2], [i+1] by [1:-1] and [i+2] by [2:]. But I might be wrong. Can you submit the piece of code with at least the most internal loop? Nadav. -----Original Message----- From: numpy-discussion-bounces(a)scipy.org on behalf of Geoffrey Zhu Sent: Thu 15-Feb-07 18:32 To: Discussion of Numerical Python Cc: Subject: Re: [Numpy-discussion] Numpy and iterative procedures Thanks Chuck. I am trying to use Successive Over-relaxation to solve linear equations defined by M*v=q. There are several goals: 1. Eventually (in production) I need it to be fast. 2. I am playing with the guts of the algorithm for now, to see how it works. that means i need some control for now. 3. Even in production, there is a chance i'd like to have the ability to tinker with the algorithm. _____ From: numpy-discussion-bounces(a)scipy.org [mailto:numpy-discussion-bounces@scipy.org] On Behalf Of Charles R Harris Sent: Thursday, February 15, 2007 10:11 AM To: Discussion of Numerical Python Subject: Re: [Numpy-discussion] Numpy and iterative procedures On 2/15/07, Geoffrey Zhu <gzhu(a)peak6.com> wrote: Hi, I am new to numpy. I'd like to know if it is possible to code efficient iterative procedures with numpy. Specifically, I have the following problem. M is an N*N matrix. Q is a N*1 vector. V is an N*1 vector I am trying to find iteratively from the initial value V_0. The procedure is simply to calculate V_{n+1}[i]=3D1/M[I,i]*(q[i]- (M[i,1]*v_{n+1}[1]+M[I,2]*v_{n+1}[2]+..+M[i,i-1]*v_{n+1}[i-1]) - (M[I,i+1]*v_{n}[i+1]+M[I,i+2]*v_{n}[i+2]+..+M[I,N]*v_{n}[N])) I do not see that this is something that can esaily be vectorized, is it? I think it would be better if you stated what the actual problem is. Is it a differential equation, for instance. That way we can determine what the problem class is and what algorithms are available to solve it. Chuck _______________________________________________ Numpy-discussion mailing list Numpy-discussion(a)scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion

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magic_square
by Alec Mihailovs 16 Feb '07

16 Feb '07

I saw somewhere a comparison between numpy and Matlab/Octave. One of the Matlab/Octave commands that is missing in Numpy is magic(n) for producing n-by- n magic squares. Yesterday I posted a magic_square module in the CheeseShop, containing this missing magic(n) command together with 2 others, ismagic(a) and magic_constant (a), http://www.python.org/pypi/magic_square/0.1 http://mihailovs.com/Alec/Python/magic_square.html I wouldn't object adding them directly to the numpy package. It's, probably, RTFM question, but I couldn't find it on the web and I didn't BTFM yet - what is the standard way of submitting a module for including in numpy? Another question that I have is that I have a link to NumPy on my magic_square page cited above. This is a kind of advertising and I've read that NumPy has a BSD type license including the advertising claim. Do I have to get a written permission from somebody to have a link to NumPy download page on my page? Alec Mihailovs http://mihailovs.com/Alec/

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Different results from repeated calculation
by Keith Goodman 16 Feb '07

16 Feb '07

I get slightly different results when I repeat a calculation. In a long simulation the differences snowball and swamp the effects I am trying to measure. In the attach script there are three tests. In test1, I construct matrices x and y and then repeatedly calculate z = calc(x,y). The result z is the same every time. So this test passes. In test2, I construct matrices x and y each time before calculating z = calc(x,y). Sometimes z is slightly different---of the order of 1e-21 to 1e-18. But the x's test to be equal and so do the y's. This test fails. (It doesn't fail on my friend's windows box; I'm running linux.) test3 is the same as test2 but I calculate z like this: z = calc(100*x ,y) / (100 * 100). This test passes. What is going on? Here is some sample output: >> import repeat >> repeat.all() 4 z different 8.47032947254e-22 5 z different 8.47032947254e-22 7 z different 8.47032947254e-22 9 z different 8.47032947254e-22 10 z different 8.47032947254e-22 16 z different 8.47032947254e-22 24 z different 8.47032947254e-22 25 z different 8.47032947254e-22 26 z different 8.47032947254e-22 27 z different 8.47032947254e-22 30 z different 8.47032947254e-22 32 z different 8.47032947254e-22 34 z different 8.47032947254e-22 35 z different 8.47032947254e-22 36 z different 8.47032947254e-22 39 z different 8.47032947254e-22 40 z different 8.47032947254e-22 41 z different 8.47032947254e-22 45 z different 8.47032947254e-22 46 z different 8.47032947254e-22 50 z different 8.47032947254e-22 52 z different 8.47032947254e-22 53 z different 8.47032947254e-22 55 z different 8.47032947254e-22 56 z different 8.47032947254e-22 58 z different 8.47032947254e-22 66 z different 8.47032947254e-22 67 z different 8.47032947254e-22 71 z different 8.47032947254e-22 73 z different 8.47032947254e-22 74 z different 8.47032947254e-22 83 z different 8.47032947254e-22 86 z different 8.47032947254e-22 87 z different 8.47032947254e-22 88 z different 8.47032947254e-22 89 z different 8.47032947254e-22 90 z different 8.47032947254e-22 92 z different 8.47032947254e-22 test1: 0 differences test2: 38 differences test3: 0 differences Repeated runs tend to give me the same number of differences in test2 for several runs. Then I get a new number of differences which last for severals runs...

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Global Numpy vector with Swig
by Andrea Tomadin 16 Feb '07

16 Feb '07

Hi, I need to pass a Numpy array to a C code wrapped by Swig. The array in the C code is a global variable declared as double *vec and I would like to set it in the calling Python module foo using e.g. foo.cvar.vec = numpy.zeros(10) so that the array is manipulated in place. I found out the examples in the numpy/doc/swig dir and adapted them to my code, so now I can pass a Numpy array to a function. But in the examples I was not able to recognize any suggestion (any typedef?) to translate an array into a variable. I'm just writing an intermediate function that does the job, but I feel like writing a wrapping function that will be wrapped again by Swig... Any practical example is highly appreciated! Regards, Andrea

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Re: [Numpy-discussion] problem installing numpy on OSX
by joris＠ster.kuleuven.ac.be 16 Feb '07

16 Feb '07

Brian, thanks for your answer! I removed and completely reinstalled the Developer Tools. The issue with gcc seems to be resolved now. My python binary is indeed the one of python.org, but nevertheless I also reinstalled Python 2.5. To install numpy I started all over again with svn. The results are, however, exactly the same. Then I tried a version lower: numpy-1.0.1 (instead of 1.0.2 of the trunk). The same error messages during the setup.py procedure, but they don't seem to matter this time: afterwards I can import numpy without any obvious problems. I know that numpy 1.0.2 installs well on my Linux box, but there I use gcc-3.4. instead of gcc-4.0. Might this be a compiler issue? What version of numpy did you install, did you notice any warning or error messages at all? Joris Disclaimer: http://www.kuleuven.be/cwis/email_disclaimer.htm

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