Mailman 3 November 2000 - NumPy-Discussion

simple array help?
by Pete Shinners 17 Sep '01

17 Sep '01

i have a simple array with floating values >>> print a array([ 0. , 0.2, 0.4, 0.6, 0.8]) what i need to do is change each index into another dimension with 3 indices. hmm, kind of confusing, an example will explain better >>> b = array(zip(a,a,a)) >>> print b array([[ 0. , 0. , 0. ], [ 0.2, 0.2, 0.2], [ 0.4, 0.4, 0.4], [ 0.6, 0.6, 0.6], [ 0.8, 0.8, 0.8]]) ok, this does the job, but once i start using large arrays, the back-n-forth conversion between arrays and python lists is costing me quite a bit. is there a way i can reshape the array this way without the call to python's 'zip'? (no, 'map' doesn't count either) i've tried much fooling with NewAxis, resize, and friends. but either i haven't stumbled upon the correct combination or i'm not trying the correct tools. i'd like to keep this as quick as possible, so hopefully it can be done without anything too elaborate. thanks (doh, sorry for the previous distutils related post... hit the wrong mailing list)

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Numpy install problems
by Michael D. Risser 27 Jul '01

27 Jul '01

When attempting to install Numeric 17.0 with Python 1.5.2 and Distutils 1.0 on Red Hat 7.0, I get the following error after issuing the command 'python setup.py install' Traceback (innermost last): File "setup.py", line 15, in ? vs = map(string.atoi, v.groups()) AttributeError: 'None' object has no attribute 'groups' This error occurs regardless of whether or not I am root. I have also tried uninstalling the Red Hat Python packages and installing all from source, but I get the same error. Any help would be appreciated. Thanks.

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[Q]Best way for an array operation?
by Daehyok Shin 04 May '01

04 May '01

What is the best Numpy way for the following work? for i in range(len(x)): if x[i] > 0: y[i] = v[i] z[i] = u[i]+2 Daehyok Shin (Peter)

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Re: [Numpy-discussion] Da Blas
by Frank Horowitz 02 Jan '01

02 Jan '01

At 3:14 PM -0700 14/9/00, <dubois(a)users.sourceforge.net> wrote: >Well, I certainly didn't mean to flame anyone in particular, so I'm sorry >that Frank was offended. Publicly apologized, and publicly accepted. I'm sorry I lost my cool. Ray Beausoleil and I are having a look at this too. He's coming at the problem from a Windows perspective, and I'm coming at it from a Linux/Unix perspective. It's going to be a little slow going for me at first, since it appears that I'm going to have to get my head around the distutils way of doing things.... Just in case it saves anyone else following a false lead, yes, there is a bug in the (Linux Mandrake 7.1; but probably any unix-ish box) compile line for building the lapack_lite.so shared library (i.e. what is generated on my box is "-L/usr/lib-llapack" which obviously is missing a blank before the "-llapack" substring). However, when I coerced the distutils system to get around that bug (by specifying "/usr/lib " with a trailing blank for the BLASLIBDIR and LAPACKLIBDIR variables in setup.py) the same problem (i.e. an "ImportError: /usr/lib/liblapack.so.3: undefined symbol: e_wsfe" in importing lapack_lite) ultimately manifested itself. So my advice is not to bother tracking that one down (although it probably should be reported as a bug in distutils, since adding that trailing blank algorithmically instead of in a user modifiable configuration string is the "right thing to do", TM.). I'm still puzzled by Thomas Breul's report of preloading an f2c library squashing the bug under RedHat 6.2(?). That does not work under Mandrake, although clearly there is some bloody symbol table missing from somewhere. The trouble is to find out where, and then to coerce distutils to deal with that in a portable way... Frank -- -- Frank Horowitz frank(a)ned.dem.csiro.au CSIRO-Exploration & Mining, PO Box 437, Nedlands, WA 6009, AUSTRALIA Direct: +61 8 9284 8431; FAX: +61 8 9389 1906; Reception: +61 8 9389 8421

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(no subject)
by szport＠runet.com 01 Dec '00

01 Dec '00

> I had another look at the definition of \"ones\" and of another routine > > I frequently use: arange. It appears that even without rewriting them > > in C, some speedup can be achieved: > > > > - in ones(), the + 1 should be done \"in place\", saving about 15%, more > > if you run out of processor cache: > > I\'d also try assignment in place: > > def ones(shape, typecode=\'l\', savespace=0): > a = zeros(shape, typecode, savespace) > a[len(shape)*[slice(0, None)]] = 1 > return a > > Konrad. Is the following definition faster or not? def ones(shape, typecode=\'l\', savespace=0): a = zeros( (product(shape),), typecode, savespace) a[:] = 1 a.shape = shape return a Zaur

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Freezing Numeric Python code problem under Linux
by Nor Pirzkal 30 Nov '00

30 Nov '00

Hi, i am having troubles freezing some python code with call the Numeric 17.1.1 module. Here is an example of what happens under Linux Red Hat 6.2 and Python 2.0: $ cat t.py import Numeric a = Numeric.ones([10,10]) b = a * 10 print b $ python ~/Python-2.0/Tools/freeze/freeze.py -o tt t.py ... $ cd tt $ ./t Traceback (most recent call last): File "t.py", line 1, in ? File "/scisoft/python/lib/python2.0/site-packages/Numeric/Numeric.py", line 79, in ? import multiarray ImportError: /scisoft/python/lib/python2.0/site-packages/Numeric/multiarray.so: undefined symbol: _Py_NoneStruct The very same code, under Solaris 2.6 and Python 2.0 works just fine. Code which does not use the Numeric package freeze just fine under Linux, so I think that this point to some problem/incompatibility of Numeric with freeze.py. Does anybody have a suggestion, or a work-around?? Nor

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Re: [Numpy-discussion] 17.2 source release
by hoel＠germanlloyd.org 28 Nov '00

28 Nov '00

"Paul F. Dubois" <pauldubois(a)home.com> writes: > I have released 17.2. This is essentially a catch-up-to-CVS release. If you > don't upgrade nothing astonishing will be missing from your life, unless you > are using MA, which has been worked on some since 17.1. > > I installed a performance enhancement submitted by Pete Shinners, who said: > "I've got a quick optimization for the arrayobject.c source. > it speeds my usage of numpy up by about 100%. i've tested with > other numpy apps and noticed a minimum of about 20% speed." Hello, Is it 17.1.2 or is it missing on Sourceforge? O only see a 17.1.2 which has a corresponding file date, but no 10.2 Greetings Berthold -- email: hoel(a)GermanLloyd.org ) tel. : +49 (40) 3 61 49 - 73 74 ( C[_] These opinions might be mine, but never those of my employer.

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17.2 source release
by Paul F. Dubois 28 Nov '00

28 Nov '00

I have released 17.2. This is essentially a catch-up-to-CVS release. If you don't upgrade nothing astonishing will be missing from your life, unless you are using MA, which has been worked on some since 17.1. I installed a performance enhancement submitted by Pete Shinners, who said: "I've got a quick optimization for the arrayobject.c source. it speeds my usage of numpy up by about 100%. i've tested with other numpy apps and noticed a minimum of about 20% speed."

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quick optimization
by Pete Shinners 27 Nov '00

27 Nov '00

i've got a quick optimization for the arrayobject.c source. it speeds my usage of numpy up by about 100%. i've tested with other numpy apps and noticed a minimum of about 20% speed. anyways, in "do_sliced_copy", change out the following block: if (src_nd == 0 && dest_nd == 0) { for(j=0; j<copies; j++) { memcpy(dest, src, elsize); dest += elsize; } return 0; } with this slightly larger one: if (src_nd == 0 && dest_nd == 0) { switch(elsize) { case sizeof(char): memset(dest, *src, copies); break; case sizeof(short): for(j=copies; j; --j, dest += sizeof(short)) *(short*)dest = *(short*)src; break; case sizeof(long): for(j=copies; j; --j, dest += sizeof(int)) *(int*)dest = *(int*)src; break; case sizeof(double): for(j=copies; j; --j, dest += sizeof(double)) *(double*)dest = *(double*)src; break; default: for(j=copies; j; --j, dest += elsize) memcpy(dest, src, elsize); } return 0; } anyways, you can see it's no brilliant algorithm change, but for me, getting a free 2X speedup is a big help. i'm hoping something like this can get merged into the next releases? after walking through the numpy code, i was surprised how almost every function falls back to do_sliced_copy (guess that's why it's at the top of the source?). that made it a quick target for making optimization changes.

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multiarray=a standard type in python?
by Daehyok Shin 23 Nov '00

23 Nov '00

Would you tell me what's going on recently in making multiarray as a standard type of python? Daehyok Shin (Peter)

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