Re: [Numpy-discussion] reporting scipy.sparse bug
On Tue, May 01, 2007 at 05:36:19PM -0700, koara wrote: > scipy 0.5.2, in scipy.sparse.lil_matrix.__mul__: the optimization for > when multiplying by zero scalar is flawed. A copy of the original > matrix is returned, rather than the correct zero matrix. Nasty bug > because it only manifests itself with special input (zero scalar), > took me some time to nail my unexpected program output down to this > :( You're right -- that *is* nasty! Fixed in r2951. Thanks for the report! http://projects.scipy.org/scipy/scipy/changeset/2951 Cheers Stéfan ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] scipy for centos4.4?
Anyone know where to find usable rpms from scipy on centos4.4? ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] problem: I get an array that doesn't have a length
Hello - I try to convert an input argument to an array of floats. Input can be an array of integers or floats, or scalar integers or floats. The latter seem to give a problem, as they return an array that doesn't have a length. I don't quite understand what b really is in the example below. Doesn't every array have a length? Is this a bug or a feature? Thanks, Mark >>> b = asarray(3,'d') >>> size(b) 1 >>> len(b) Traceback (most recent call last): File "", line 1, in ? len(b) TypeError: len() of unsized object ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] sort bug
Sorry for joining this discussion late. If you are only interested in the four largest eigenvalues, there are more efficient algorithms out there than just eig(). There are algorithms that just give you the N largest. Then again, I don't know of any Python implementations, but I haven't looked, Mark On Apr 29, 11:04 pm, "Matthieu Brucher" <[EMAIL PROTECTED]> wrote: > 2007/4/29, Anton Sherwood <[EMAIL PROTECTED]>: > > > > > > > > Anton Sherwood wrote: > > > > I'm using eigenvectors of a graph's adjacency matrix as "topological" > > > > coordinates of the graph's vertices as embedded in 3space (something I > > > > learned about just recently). Whenever I've done this with a graph > > that > > > > *does* have a good 3d embedding, using the first eigenvector results > > in > > > > a flat model: apparently the first is not independent, at least in > > such > > > > cases. . . . > > > Charles R Harris wrote: > > > . . . the embedding part sounds interesting, > > > I'll have to think about why that works. > > > It's a mystery to me: I never did study enough matrix algebra to get a > > feel for eigenvectors (indeed this is the first time I've had anything > > to do with them). > > > I'll happily share my code with anyone who wants to experiment with it. > > Seems to me that this is much like Isomap and class multidimensional > scaling, no ? > > Matthieu > > ___ > Numpy-discussion mailing list > [EMAIL PROTECTED]://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] bug in scipy.io.mmio
Hello, when saving a sparse matrix via scipy 0.5.2: scipy.io.mmio.mmwrite(), an exception is thrown: scipy.io.mmio.py: line 269: AttributeError: gettypecode not found changing the line to read 269: typecode = a.dtype.char fixes the problem. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] bug in scipy.io.mmio
koara wrote:
> Hello, when saving a sparse matrix via scipy 0.5.2:
> scipy.io.mmio.mmwrite(), an exception is thrown:
>
> scipy.io.mmio.py: line 269: AttributeError: gettypecode not found
>
> changing the line to read
>
> 269: typecode = a.dtype.char
>
> fixes the problem.
>
> ___
> Numpy-discussion mailing list
> Numpy-discussion@scipy.org
> http://projects.scipy.org/mailman/listinfo/numpy-discussion
>
Fixed in svn.
>>> from scipy import *
>>> A = sparse.speye(10,10)
>>> A
<10x10 sparse matrix of type ''
with 10 stored elements (space for 10)
in Compressed Sparse Column format>
>>> help (io.mmwrite)
>>> io.mmwrite('A1',A)
Nils
%%MatrixMarket matrix coordinate real general
%
10 10 10
0 0 1.e+00
1 1 1.e+00
2 2 1.e+00
3 3 1.e+00
4 4 1.e+00
5 5 1.e+00
6 6 1.e+00
7 7 1.e+00
8 8 1.e+00
9 9 1.e+00
___
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Re: [Numpy-discussion] sort bug
mark wrote: > Sorry for joining this discussion late. > If you are only interested in the four largest eigenvalues, there are > more efficient algorithms out there than just eig(). > There are algorithms that just give you the N largest. > Then again, I don't know of any Python implementations, but I haven't > looked, > Mark > > On Apr 29, 11:04 pm, "Matthieu Brucher" <[EMAIL PROTECTED]> > wrote: > >> 2007/4/29, Anton Sherwood <[EMAIL PROTECTED]>: >> >> >> >> >> >> Anton Sherwood wrote: > I'm using eigenvectors of a graph's adjacency matrix as "topological" > coordinates of the graph's vertices as embedded in 3space (something I > learned about just recently). Whenever I've done this with a graph > >>> that >>> > *does* have a good 3d embedding, using the first eigenvector results > >>> in >>> > a flat model: apparently the first is not independent, at least in > >>> such >>> > cases. . . . > >>> Charles R Harris wrote: >>> . . . the embedding part sounds interesting, I'll have to think about why that works. >>> It's a mystery to me: I never did study enough matrix algebra to get a >>> feel for eigenvectors (indeed this is the first time I've had anything >>> to do with them). >>> >>> I'll happily share my code with anyone who wants to experiment with it. >>> >> Seems to me that this is much like Isomap and class multidimensional >> scaling, no ? >> >> Matthieu >> >> ___ >> Numpy-discussion mailing list >> [EMAIL PROTECTED]://projects.scipy.org/mailman/listinfo/numpy-discussion >> > > ___ > Numpy-discussion mailing list > Numpy-discussion@scipy.org > http://projects.scipy.org/mailman/listinfo/numpy-discussion > There are several subroutines in LAPACK for this task. http://www.netlib.org/lapack/double/dsyevx.f http://www.netlib.org/lapack/double/dsygvx.f IIRC symeig provides a wrapper. See http://mdp-toolkit.sourceforge.net/symeig.html Nils ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
Mark, In your example: > >>> b = asarray(3,'d') b is really a numpy scalar, so it doesn't have a length. But it does have a size (1) and a ndim (0). If you need to have arrays with a length, you can force the array to have a dimension 1 with atleast_1d(b) or array(b,copy=False,ndmin=1) ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
On 5/2/07, Pierre GM <[EMAIL PROTECTED]> wrote: Mark, In your example: > >>> b = asarray(3,'d') b is really a numpy scalar, so it doesn't have a length. But it does have a size (1) and a ndim (0). If you need to have arrays with a length, you can force the array to have a dimension 1 with atleast_1d(b) or array(b,copy=False,ndmin=1) Or just array([1],'d') Chuck ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
On Wednesday 02 May 2007 10:00:58 Charles R Harris wrote: > On 5/2/07, Pierre GM <[EMAIL PROTECTED]> wrote: > > Mark, > Or just array([1],'d') Except that in that case you need to know in advance the input is a scalar to put it in a list. The atleast_1d should work better on any input. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
El dc 02 de 05 del 2007 a les 09:52 -0400, en/na Pierre GM va escriure: > Mark, > In your example: > > >>> b = asarray(3,'d') > > b is really a numpy scalar, so it doesn't have a length. But it does have a > size (1) and a ndim (0). Just one correction in terms of the current naming convention: b in this case is a 0-dim array, which is a different beast than a numpy scalar (although they behaves pretty similarly). You can distinguish between them in different ways, but one is using type(): In [24]:type(numpy.asarray(3.)) # a 0-dim array Out[24]: In [25]:type(numpy.float64(3.)) # a numpy scalar Out[25]: Cheers, -- Francesc Altet| Be careful about using the following code -- Carabos Coop. V. | I've only proven that it works, www.carabos.com | I haven't tested it. -- Donald Knuth ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
On Wednesday 02 May 2007 11:39:29 Francesc Altet wrote: > El dc 02 de 05 del 2007 a les 09:52 -0400, en/na Pierre GM va escriure: > > In your example: > > > >>> b = asarray(3,'d') > > > > b is really a numpy scalar, so it doesn't have a length. But it does have > > a size (1) and a ndim (0). > > Just one correction in terms of the current naming convention: b in this > case is a 0-dim array, which is a different beast than a numpy scalar > (although they behaves pretty similarly). Quite true, my bad. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
OK, so in my example, I get a zero dimension array. Apparently a feature, not a bug. What I don't understand is why it isn't an array of lenght one? (or: why it isn't a bug?) Is there any use for a zero dimension array? I would very much like it to be a one dimension array. In my application I don' t know whether an integer, float, or array gets passed to the function. This is my syntax: def test(a): b = asarray(a,'d') do something to b I thought this makes b an array AND a float. The atleast_1d only makes it an array, not necessarily a float. Any more thoughts on how to do this cleanly? Any reason NOT to have asarray(3,'d') return an array of length 1? Thanks, Mark On May 2, 5:47 pm, Pierre GM <[EMAIL PROTECTED]> wrote: > On Wednesday 02 May 2007 11:39:29 Francesc Altet wrote: > > > El dc 02 de 05 del 2007 a les 09:52 -0400, en/na Pierre GM va escriure: > > > In your example: > > > > >>> b = asarray(3,'d') > > > > b is really a numpy scalar, so it doesn't have a length. But it does have > > > a size (1) and a ndim (0). > > > Just one correction in terms of the current naming convention: b in this > > case is a 0-dim array, which is a different beast than a numpy scalar > > (although they behaves pretty similarly). > > Quite true, my bad. > ___ > Numpy-discussion mailing list > [EMAIL PROTECTED]://projects.scipy.org/mailman/listinfo/numpy-discussion ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
mark wrote: > OK, so in my example, I get a zero dimension array. Apparently a > feature, not a bug. > What I don't understand is why it isn't an array of lenght one? (or: > why it isn't a bug?) Because we need a way to get rank-0 arrays. > Is there any use for a zero dimension array? http://projects.scipy.org/scipy/numpy/wiki/ZeroRankArray > I would very much like it to be a one dimension array. > In my application I don' t know whether an integer, float, or array > gets passed to the function. > This is my syntax: > def test(a): >b = asarray(a,'d') >do something to b > I thought this makes b an array AND a float. The atleast_1d only makes > it an array, not necessarily a float. > Any more thoughts on how to do this cleanly? atleast_1d(a).astype(float) Put it into a function if you want that to be more concise. > Any reason NOT to have asarray(3,'d') return an array of length 1? Because we need a way to get a rank-0 array. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
On Wednesday 02 May 2007 12:27:10 mark wrote: > Any reason NOT to have asarray(3,'d') return an array of length 1? Because then, it would be "an array, not necessarily a float" ;) You just noticed yourself that an array of dimension 1 is pretty much like a list, while an array of dimension 0 is pretty much like a scalar. Keeping that in mind, I'm sure that you can see the advantage of 0D arrays: they are indeed arrays AND scalar at the same time... If you need your inputs to be array or scalar and stay that way, then the "asarray" method is the best. You can just perform some additional test on the dimension of the array, before trying to access its length or its size. A 0D array as a size of 1 and a dimension of zero, and therefore no length. A 1D array as a size of n and a dimension of 1. and a length (n). ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Possible Numeric bug with python-2.5
I know Numeric is no longer supported, but I just upgraded to python-2.5 and now I'm having problems indexing Numeric arrays: In [1]: import Numeric In [2]: Numeric.arange(0,10) Out[2]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) In [3]: Numeric.arange(0,10)[:10] Out[3]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) In [4]: Numeric.arange(0,10)[:] Out[4]: zeros((0,), 'l') That last line should yield the same result as the previous command. Can anyone else confirm this behavior? I'm running Numeric-24.2 on 64 bit gentoo linux. Thanks, Darren ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Possible Numeric bug with python-2.5
On 5/2/07, Darren Dale <[EMAIL PROTECTED]> wrote: > I know Numeric is no longer supported, but I just upgraded to python-2.5 and > now I'm having problems indexing Numeric arrays: Fine on 32-bit ubuntu, using Python 2.5: In [4]: Numeric.arange(0,10)[:] Out[4]: array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]) In [5]: Numeric.__version__ Out[5]: '24.2' But I think that Numeric isn't 100% 64-bit safe (perhaps when run under Python 2.5). cheers, f ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Possible Numeric bug with python-2.5
On Wednesday 02 May 2007 14:15:06 Fernando Perez wrote: > On 5/2/07, Darren Dale <[EMAIL PROTECTED]> wrote: > > I know Numeric is no longer supported, but I just upgraded to python-2.5 > > and now I'm having problems indexing Numeric arrays: > > Fine on 32-bit ubuntu, using Python 2.5: > But I think that Numeric isn't 100% 64-bit safe (perhaps when run > under Python 2.5). My understanding is that Python 2.5 started using Py_ssize_t instead of int, to increase the number of data that can be handled on 64b. We just observed that w/ the timeseries package: a int in the C API prevented a dictionary to be initialized properly on Python 2.5, which prevented the package to be loaded properly. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
Pierre GM wrote: > If you need your inputs to be array or scalar and stay that way It didn't sound like the OP wanted that. I suspect that what is wanted if for to always be a 1-d array (i.e. vector). To do that, I'd do: import numpy as N >>> def test(a): ...b = N.asarray(a, dtype=N.float).reshape((-1,)) ...print b.shape ... >>> >>> test(5) (1,) >>> test((5,)) (1,) >>> test((5,6,7,8)) (4,) -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
On Wednesday 02 May 2007 14:45:40 Christopher Barker wrote: > Pierre GM wrote: > > If you need your inputs to be array or scalar and stay that way > > It didn't sound like the OP wanted that. I suspect that what is wanted > if for to always be a 1-d array (i.e. vector). To do that, I'd do: I beg to differ: your option is equivalent to (and I suspect a bit slower than) atleast_1d, which is what the OP complained about... ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] problem: I get an array that doesn't have a length
Pierre GM wrote: >> It didn't sound like the OP wanted that. I suspect that what is wanted >> if for to always be a 1-d array (i.e. vector). To do that, I'd do: > > I beg to differ: your option is equivalent to (and I suspect a bit slower > than) atleast_1d, which is what the OP complained about... There is a difference, but I don't know what the OP wanted. my method (N.asarray(a, dtype-N.float).reshape((-1,)) will ALWAYS create a 1-d array, even if the original is greater than 1-d atleast_1d will let an n-d array pass through. It also doesn't look like you can specify a data type with atleast_1d. I don't think my approach is slower, as it handles the conversion to float, and reshape doesn't copy the data if it doesn't need to. But I doubt speed makes any difference here anyway. -CHB -- Christopher Barker, Ph.D. Oceanographer Emergency Response Division NOAA/NOS/OR&R(206) 526-6959 voice 7600 Sand Point Way NE (206) 526-6329 fax Seattle, WA 98115 (206) 526-6317 main reception [EMAIL PROTECTED] ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] building pynetcdf-0.7 on OS X 10.4 intel
OS X 10.4.9, python 2.5, numpy 1.0.3.dev3726, netcdf 3.6.2 I am trying to build pynetcdf-0.7, so as to be able to read netCDF files from python 2.5/numpy . So far I have not had success. Enclosed is the dump of my most recent failure - the complaint comes from the linker since the linker has both a powerPC (ppc) and an intel (i386) flag. I guess that what is being attempted is a universal build ( both ppc and i386) but failing. Apparently my netcdf build was just i386 - although I did nothing special. I am at a loss as to what to do next - this might be a question for an Mac specialist - but I figured I'd try here first. --Jim [krait:~/Desktop/pynetcdf-0.7] boyle5% python setup.py build running build running config_fc running build_src building extension "pynetcdf._netcdf" sources building data_files sources running build_py creating build creating build/lib.macosx-10.3-fat-2.5 creating build/lib.macosx-10.3-fat-2.5/pynetcdf copying ./__init__.py -> build/lib.macosx-10.3-fat-2.5/pynetcdf copying ./NetCDF.py -> build/lib.macosx-10.3-fat-2.5/pynetcdf copying ./netcdf_demo.py -> build/lib.macosx-10.3-fat-2.5/pynetcdf running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext building 'pynetcdf._netcdf' extension compiling C sources C compiler: gcc -arch ppc -arch i386 -isysroot /Developer/SDKs/ MacOSX10.4u.sdk -fno-strict-aliasing -Wno-long-double -no-cpp-precomp -mno-fused-madd -fPIC -fno-common -dynamic -DNDEBUG -g -O3 -Wall - Wstrict-prototypes creating build/temp.macosx-10.3-fat-2.5 compile options: '-I/Users/boyle5/netcdf-3.6.2/include -I/Library/ Frameworks/Python.framework/Versions/2.5/lib/python2.5/site-packages/ numpy/core/include -I/Library/Frameworks/Python.framework/Versions/ 2.5/include/python2.5 -c' gcc: ./_netcdf.c ./_netcdf.c: In function 'PyNetCDFFile_Close':./_netcdf.c: In function 'PyNetCDFFile_Close': ./_netcdf.c:965: warning: passing argument 2 of 'PyDict_Next' from incompatible pointer type./_netcdf.c:965: warning: passing argument 2 of 'PyDict_Next' from incompatible pointer type ./_netcdf.c: In function 'PyNetCDFVariableObject_subscript': ./_netcdf.c:1822: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1822: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1822: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c: In function 'PyNetCDFVariableObject_subscript': ./_netcdf.c:1822: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1822: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1822: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1842: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c: In function 'PyNetCDFVariableObject_ass_subscript': ./_netcdf.c:1944: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1944: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1944: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c: In function 'PyNetCDFVariableObject_ass_subscript': ./_netcdf.c:1944: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1944: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1944: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 3 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 4 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c:1964: warning: passing argument 5 of 'PySlice_GetIndices' from incompatible pointer type ./_netcdf.c: At top level: ./_netcdf.c:2009: warning: initialization from incompatible pointer type ./_netcdf.c:2011: warning: 'intargfunc' is deprecated ./_netcdf.c:2011: warning:
Re: [Numpy-discussion] building pynetcdf-0.7 on OS X 10.4 intel
James Boyle wrote: > I am trying to build pynetcdf-0.7, so as to be able to read netCDF > files from python 2.5/numpy . Sorry for the shameless plug, but if you only want to read netCDF files from numpy you can use a pure python netcdf reader that I wrote, called pupynere: http://cheeseshop.python.org/pypi/pupynere/ Best, --Rob ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] building pynetcdf-0.7 on OS X 10.4 intel
On Wed, 02 May 2007, Rob De Almeida apparently wrote: > http://cheeseshop.python.org/pypi/pupynere/ I do not think you were "shameless" enough. Pupynere is a PUre PYthon NEtcdf REader. It allows read-access to netCDF files using the same syntax as the Scientific.IO.NetCDF module. Even though it's written in Python, the module is up to 40% faster than Scientific.IO.NetCDF and pynetcdf. Mentioning the MIT license is also worthwhile. Cheers, Alan Isaac ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
