Mailman 3 January 2006 - NumPy-Discussion

Re: [SciPy-user] Strange behaviour of dot function
by Travis Oliphant 31 Jan '06

31 Jan '06

Johannes Löhnert wrote: >Hi, > >I just found out that the dot function which multiplies matrices gives >strange results for a 3-dimensional array. Consider the following example: > > You just found two bugs in numpy.dot one of which is also there in Numeric. I just committed a fix to both bugs by using the ever-useful N-d array iterator (it sure makes it easier to write algorithms for strided arrays...). All three of your tests now produce the same answer. Thank you for finding this problem. -Travis

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numpy 0.9.4 for OSX
by Christopher Fonnesbeck 31 Jan '06

31 Jan '06

I have added a OS X 10.4 build of numpy 0.9.4 to the sourceforge site. For (approximately) bi-weekly builds of numpy and scipy for OS X, go to http://trichech.us. Chris -- Christopher J. Fonnesbeck Population Ecologist, Marine Mammal Section Fish & Wildlife Research Institute (FWC) St. Petersburg, FL Adjunct Assistant Professor Warnell School of Forest Resources University of Georgia Athens, GA T: 727.235.5570 E: chris at trichech.us

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Casting RecArray fields?
by dHering 31 Jan '06

31 Jan '06

Hi all, I need to cast fields of type 'Bool' to type 'Int32'. I'm not sure how to do this. Thank you, Dieter import numarray.records as rec b = rec.array([[23, 0],[45, 1]], names=' integer, boolean',formats='Int32, Bool') print b.field(1).type() # following line is not permissable # b.field(1) = b.field(1).astype('Int32') b.field(1)[:] = b.field(1).astype('Int32') print b.field(1).type() ########################## ########################## /usr/bin/python -u Bool Bool

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NumPy installed but aborted when do import
by Lito Kusnadi 31 Jan '06

31 Jan '06

Hi, I'm running RHEL 4.0 2.6.9-5.EL with Python 2.3.4. I managed to compile NumPy from src.rpm and make an i386 rpm from it. Version of NumPy is numpy-0.9.4-1. When I run Python interactive line and try to import NumPy, it aborts and kicks me to the command prompt. The following error is generated: Python 2.3.4 (#1, Nov 4 2004, 14:06:56) [GCC 3.4.2 20041017 (Red Hat 3.4.2-6.fc3)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from numpy import * import core -> failed: /usr/lib/python2.3/site-packages/numpy/core/multiarray.so: undefined symbol: PyOS_ascii_strtod import random -> failed: 'module' object has no attribute 'dtype' import lib -> failed: /usr/lib/python2.3/site-packages/numpy/core/multiarray.so: undefined symbol: PyOS_ascii_strtod Fatal Python error: can't initialize module lapack_lite Aborted Anyone knows what package I am missing? Thanks.

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performance problem
by Gerard Vermeulen 31 Jan '06

31 Jan '06

Hi Travis, thanks for your incredible quick fixes. numpy is about 5 times slower than numarray (on my numarray-friendly bi-pentium): >>> from timeit import Timer >>> import numarray; print numarray.__version__ 1.5.0 >>> import numpy; print numpy.__version__ 0.9.5.2021 >>> t1 = Timer('a <<= 8', 'import numarray as NX; a = NX.ones(10**6, NX.UInt32)') >>> t2 = Timer('a <<= 8', 'import numpy as NX; a = NX.ones(10**6, NX.UInt32)') >>> t1.timeit(100) 0.21813011169433594 >>> t2.timeit(100) 1.1523458957672119 >>> Numeric-23.1 is about as fast as numarray for inplace left shifts. Gerard

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Re: [Numpy-discussion] Numerical Mathematics Consortium vs. scipy and numpy
by Joe Harrington 30 Jan '06

30 Jan '06

Currently the NMC membership is tiny. Likely the linalg focus is due to the biases of that group. Getting an open-source project involved in something like this isn't so terrible, if the vendors allow it (i.e., if it isn't a sham for one set of vendors to gang up on another, as the Open Software Foundation was about 15 years ago). I notice that Research Systems (IDL) conspicuously isn't on their list (they'd definitely be more array-oriented). Also conspicuous by their absences are prominent groups like NAG and netlib. As for coming up with the fee, I think that it wouldn't be a huge investment for STScI and Enthought to split. If successful, NMC will impact both organizations quite a bit, so it should be worth it to them. Of course, I don't work for either organization so that's easy for me to say. Note that these people expect their members to do a lot of work, so the greater commitment might be time. However, the group is conveniently located in Austin... Alternatively, we could petition for a waiver based on our lack of profit. That's been done successfully in the past, too, for example by the Gutenprint folks (who then proceeded to teach the developers at Lexmark et al. a thing or two about dithering). XFree86.org had to beat on the X Consortium (or whatever they were called then) a bit, but eventually got in. I'm not sure what the deal was with fees for them. --jh--

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Re: Status of 1.0 release and website?
by Travis Oliphant 30 Jan '06

30 Jan '06

Jonathan Taylor wrote: > I am wondering what needs to happen before a 1.0 release of both numpy > and scipy? For a 1.0 release of numpy: In terms of features. The only thing I see as necessary is that array scalars have their own math defined so that they don't go through the full ufunc machinery. This is probably about 20-40 hours of work. I would also like to see a numcompat module that allows numarray users to compile their C-extensions with a simple include file change. Also, a convert_numarraycode.py module would be useful for converting Python code. Mostly, though, I would like to see more people using NumPy in different circumstances so that we get the bugs worked out and needed C-API changes before going to 1.0. This is the process that may take several months as I see it. -Travis

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Verbose output from setup.py --help intentional?
by Matthew Brett 30 Jan '06

30 Jan '06

Hi, Sorry if this is low priority, but I noticed that the output from setup.py --help is more than 400 lines. Also the output of (e.g) setup.py --help install and setup.py install --help differ (also more than 400 lines). Best, Matthew

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(some) generalized eigenvalues in numpy
by Sven Schreiber 30 Jan '06

30 Jan '06

Hi, in econometrics/statistics it's relatively common to solve a special generalized eigenvalue problem, where the matrices are real, symmetric, and positive definite. It bothered me to depend on scipy just because of that. Also, scipy.linalg.eig is much more general and returns complex types which is inconvenient for sorting etc. So I've written the workaround function below, but it's probably not very efficient (at least I hope the algebra is right). I'd be happy to hear your comments, suggestions; first with respect to the function itself, but also whether you agree that the implemented functionality would be useful enough to include in official numpy (in a more professional way than I have done). cheers, Sven def geneigsympos(A, B): """ Solves symmetric-positive-definite generalized eigenvalue problem Az=lBz. Takes two real-valued symmetric matrices A and B (B must also be positive-definite) and returns the corresponding generalized (but also real-valued) eigenvalues and eigenvectors. Return format: as in scipy.linalg.eig, tuple (l, Z); l is directly taken from eigh output (a 1-dim array of length A.shape[0] ?), and Z is an array or matrix (depending on type of input A) with the corresponding eigenvectors in columns (hopefully). Eigenvalues are ordered ascending (thanks to eigh). """ from numpy import asmatrix, asarray, linalg #fixme: input checks on the matrices LI = asmatrix(linalg.cholesky(B)).I C = LI * asmatrix(A) * LI.T evals, evecs = linalg.eigh(C) if type(A) == type(asarray(A)): output = "array" # A was passed as numpy-array else: output = "matrix" #but the evecs need to be transformed back: evecs = LI.T * asmatrix(evecs) if output == "array": return evals, asarray(evecs) else: return asmatrix(evals), evecs

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Your Paypal Account.
by Paypal 30 Jan '06

30 Jan '06

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