Mailman 3 May 2001 - 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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PS: underflow array([2.9e-131+0j])**3 (why complex give a different result? bug?)
by Jean-Bernard Addor 12 Jun '01

12 Jun '01

Hey Numpy people! This a PS from my previous message. I just tried the underflow with complex : >>> Numeric.array([2.9e-131])**3 Traceback (most recent call last): File "<stdin>", line 1, in ? OverflowError: math range error >>> 2.9e-131**3 0.0 >>> Numeric.array([2.9e-131+0j])**3 array([ 0.+0.j]) Now I have a quick solution for my problem, but I have the impression that this is a bug, at least I don't understand the underlying logic. If somebody can explain it to me? Jean-Bernard

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underflow array([2.9e-131])**3
by Jean-Bernard Addor 12 Jun '01

12 Jun '01

Hey Numpy people! Do anyone know how to disable underflow exception errors in Numeric? I have a lot of these in my code. It is now a very important problem in my calculations. The only solution I see is to make a for loop and make the arithmetic in python instead of Numeric. Thanks for your help, Jean-Bernard Python 2.0 (#9, Feb 2 2001, 12:17:02) [GCC 2.95.2 19991024 (release)] on linux2 Type "copyright", "credits" or "license" for more information. Hello from .pythonrc.py >>> import Numeric >>> Numeric.__version__ '17.2.0' >>> Numeric.array([2.9e-131])**3 Traceback (most recent call last): File "<stdin>", line 1, in ? OverflowError: math range error >>> 2.9e-131**3 0.0

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Array values sometimes have "<type 'array'>"
by Edward C. Jones 31 May '01

31 May '01

I use Numeric 20.0.0, Python 2.1, and RedHat 7.1 on a PC. Here is a small Python program: import Numeric a = Numeric.zeros((2,2), 'b') print a[0,0], type(a[0,0]) print a[0][0], type(a[0][0]) a = Numeric.zeros((2,2), 'i') print a[0,0], type(a[0,0]) print a[0][0], type(a[0][0]) a = Numeric.zeros((2,2), 'f') print a[0,0], type(a[0,0]) print a[0][0], type(a[0][0]) The output is: 0 <type 'array'> 0 <type 'int'> 0 <type 'array'> 0 <type 'int'> 0.0 <type 'array'> 0.0 <type 'float'> This can't be correct. "a[0,0]" and "a[0][0]" should have the same type. A quick check of my old Python code shows that this problem may have appeared since Numeric version 17. Thanks, Ed Jones

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numpyio
by karshi.hasanov＠utoronto.ca 30 May '01

30 May '01

I am having a problem to download the numpyio.py file. Does any one knows whereand how to get it? Thanks.

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Re: The future of Numpy
by Perry Greenfield 29 May '01

29 May '01

> Mark Esplin wrote: > > > > What is the plan for the future development of Numerical Python? For > > example, will additional special functions be included in numpy, or is > > NumPy to be a building block for other applications? I guess the big > > question is "Will Numerical Python become a complete computing > > environment like Matlab or IDL?" > > > > There is an interesting series of article on Numerical Python by Eric > > Hagemann on O'Reilly network (www.oreillynet.com) where Eric Hagemann > > is using NumPy with other python modules as a computing environment > > more than as a software development framework. > > > > I think NumPy could become a lot like the development of linux. Linux > > strictly speaking is only the operating system kernel. However, a > > linux system has come to includes a whole set of packages that work > > together to make up a whole system. > > See PEP 209: Multi-dimensional Arrays > > http://python.sourceforge.net/peps/pep-0209.html > > -- > Paul Barrett, PhD Space Telescope Science Institute > We at STScI have been working on a new implementation of Numeric. We are far enough along to release an incomplete version for evaluation by the Numeric (the current version) developers in about 2 weeks. The existing PEP (209) doesn't address all the details of the implementation and there are some differences from the PEP, but it does give a general idea of what our goals are. We have been more concerned at this point in implementation than keeping the PEP up to date. The PEP will be revised when we release a preliminary version. The preliminary version will be 0) Called something else. Probably numarray. 1) Not completely backwards compatible with the existing Numeric. (I don't have time to detail the differences, but they will be listed when we make it availble). 2) Incomplete. It will be missing functionality, especially with regard to structural operations (choose, where, nonzero, put, take, compress...). It will have most types (excepting complex) and most standard Ufuncs. We do not expect this version will be usuable for most projects because of this. We are looking for feedback on the interface and design approach rather than advertising it as a usuable version. We also are interested in collaborators in implementing the rest of the functionality. It probably will be moved to sourceforge soon after. 3) Slower for smaller arrays. We expect that performance for large arrays (>100,000 elements) should be fairly respectable, but since most of the original implementation is in Python, the overhead for smaller arrays is substantially increased over the existing Numeric. While we did benchmarking for determining what design approaches were efficient enough, we have eschewed benchmarks until we have completed all the important functionality (soon). At that point we will begin to work on optimization to improve the performance. I'll stop here, but you should be hearing more about it in the near future. Perry Greenfield Space Telescope Science Institute Science Software Group

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fromfunction documentation
by Kevin Turner 28 May '01

28 May '01

Quoting from numdoc.pdf, dated March 31, 2001, in section "Creating an array from a function: fromfunction()" > The implementation of fromfunction consists of: > > def fromfunction(function, dimensions): > return apply(function, tuple(indices(dimensions))) > > which means that the function function is called for each element in > the sequence indices(dimensions) [...] This is wholly incorrect. apply() does not call a function for each element in the sequence, apply calls a function exactly *once*, using the elements of the sequence for arguments. Also, that same section of the documentation refers to "the first example below [...] works" and "the second array [...] fails", but there is only one example, which apparently is the failing one (as it's named "buggy"). Having a *working* example would be nice. =) Perhaps this is a formatting glitch in the documentation processor, but I couldn't find the documentation's source format. and then... there's always the possibility that I'm barking up the wrong tree. What I'm trying to achieve is this: I've got a function which, given a vector describing a point in n-dimensional space, returns a value for that point. I want a matrix of the shape I specify, filled these values, with the array indicies as coordinates for the points. Is that too much to ask? ;) Thanks, - Kevin Turner [using Python version 2.0, PyNum 19.0.0] -- Kevin Turner <acapnotic(a)users.sf.net> | OpenPGP encryption welcome here http://www.purl.org/wiki/python/KevinTurner

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The future of Numpy
by Mark Esplin 25 May '01

25 May '01

What is the plan for the future development of Numerical Python? For example, will additional special functions be included in numpy, or is NumPy to be a building block for other applications? I guess the big question is "Will Numerical Python become a complete computing environment like Matlab or IDL?" There is an interesting series of article on Numerical Python by Eric Hagemann on O'Reilly network (www.oreillynet.com) where Eric Hagemann is using NumPy with other python modules as a computing environment more than as a software development framework. I think NumPy could become a lot like the development of linux. Linux strictly speaking is only the operating system kernel. However, a linux system has come to includes a whole set of packages that work together to make up a whole system. -Mark Esplin _________________________________________________________ Do You Yahoo!? Get your free @yahoo.com address at http://mail.yahoo.com

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Win32 binary of ScientificPython
by Grant Callis 25 May '01

25 May '01

Does have an updated Win32 binary of Konrad Hinsen's ScientificPython? I've been using Robert Kern's version, but it's only good up to Python 1.5.2. Now that the main modules I use have been compiled for Python 2.1 (dislin & mxTools) I have upgraded. The only other binary extension I use often is ScientificPython, especially the netcdf portion. I'm not really a computer person so compiling myself is a scary option. Any help? Thank you, Grant Callis __________________________________________________ Do You Yahoo!? Yahoo! Auctions - buy the things you want at great prices http://auctions.yahoo.com/

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