Mailman 3 May 2007 - NumPy-Discussion

diagonal
by Charles R Harris 06 May '07

06 May '07

Hi All, Just noting an oddity when the diagonal method is called on arrays with ndim > 2 In [1]: a = arange(8).reshape(2,2,2) In [2]: a.diagonal() Out[2]: array([[0, 6], [1, 7]]) The diagonal is taken over the first two indices while the rightmost indices vary the slowest. I would expect things to be the other way around. In particular, it would work better with the arrays of matrices proposed by Tim. I suppose another logical extrapolation from two dimensions would be to take the "diagonal" on all three indices. But the current behaviour strikes me as a bit unexpected. Chuck

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Difference in the number of elements in a fromfile() between Windows and Linux
by Matthieu Brucher 04 May '07

04 May '07

Hi, I'm trying to test my code on several platforms, Windows and Linux, and I'm using some data files that where saved with a tofile(sep=' ') under Linux. Those files can be loaded without a problem under Linux, but under Windows with the latest numpy, these data cannot be loaded, some numbers are not considered - eg +inf or -inf). Is this a known behaviour ? How could I load these correctly under both platforms (I don't want to save them in binary form, I'm using the files for other purpose - Matthieu

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PyArray_FromDimsAndData weird seg fault
by Trevor M Cickovski 04 May '07

04 May '07

Hi, I'm using SWIG to wrap a function that calls the NumPy routine PyArray_FromDimsAndData. PyObject* toArray() { int dims = 5; double* myH; myH = (double*)malloc(dims*sizeof(double)); myH[0] = 0; myH[1] = 1; myH[2] = 2; myH[3] = 3; myH[4] = 4; return PyArray_FromDimsAndData(1,&dims,PyArray_FLOAT,(char*)myH); } However, for some reason when I call this from Python, the PyArray_FromDimsAndData() seg faults everytime. Does anybody see something wrong with my use of the function itself? Thanks! -Trevor -- ************************************************************* Trevor M. Cickovski Laboratory For Computational Life Sciences University of Notre Dame 325 Cushing Hall Notre Dame, IN 46556 T: (574) 631-3906 F: (574) 631-9260 "Settle never, strive always." *************************************************************

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linux cluster installation
by John Washakie 03 May '07

03 May '07

From: "John Washakie" <washakie(a)gmail.com> To: numpy-discussion(a)lists.sourceforge.net Date: Tue, 1 May 2007 17:38:52 +0200 Subject: linux cluster installation What is the best way to install numpy and ultimately scipy on a cluster of linux machines so that you just install it once? I imagine you have to be root to do the installation for everyone, but what if you just want to install it to your home directory? I have done: [wash@wyo ~]$ setup.py install prefix=~ ... [wash@wyo ~]$ python Python 2.4.3 (#1, Jun 13 2006, 16:41:18) [GCC 4.0.2 20051125 (Red Hat 4.0.2-8)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from numpy import * Traceback (most recent call last): File "<stdin>", line 1, in ? ImportError: No module named numpy >>> Suggestions?

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Possible Numeric bug with python-2.5
by Darren Dale 03 May '07

03 May '07

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

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problem: I get an array that doesn't have a length
by mark 02 May '07

02 May '07

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 "<pyshell#20>", line 1, in ? len(b) TypeError: len() of unsized object

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sort bug
by Anton Sherwood 02 May '07

02 May '07

This code -- adj = [ [eval(y) for y in x.split()] for x in infile ] val,vec = numpy.linalg.eig(adj) master = zip( val, vec.transpose() ) master.sort() *sometimes* gives this error: Traceback (most recent call last): File "3work.py", line 14, in <module> master.sort() ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() What does sort() care about truth values?! numpy.linalg.eig() sometimes returns complex values, which may not have a natural ordering, but I get this error (sometimes) even when it returns reals. -- Anton Sherwood, http://www.ogre.nu/ "How'd ya like to climb this high *without* no mountain?" --Porky Pine

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bug in scipy.io.mmio
by koara 02 May '07

02 May '07

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.

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reporting scipy.sparse bug
by koara 02 May '07

02 May '07

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 :( Easily resolved by rewriting the function, e.g. def __mul__(self, other): # self * other if isscalarlike(other): if other == 0: # Multiply by zero: return the zero matrix return lil_matrix(self.shape, dtype = self.dtype) # Multiply this scalar by every element. new = self.copy() new.data = [[val * other for val in rowvals] for rowvals in new.data] return new else: return self.dot(other)

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ctypes TypeError. What I am doing wrong?
by Guillem Borrell i Nogueras 01 May '07

01 May '07

Hi I wrote the next function just to learn how ctypes work with numpy arrays. I am not trying to write yet another wrapper to lapack, it's just an experiment. (you can cut and paste the code) from ctypes import c_int from numpy import array,float64 from numpy.ctypeslib import load_library,ndpointer def dgesv(N,A,B): # A=array([[1,2],[3,4]],dtype=float64,order='FORTRAN') # B=array([1,2],dtype=float64,order='FORTRAN') cN=c_int(N) NRHS=c_int(1) LDA=c_int(N) IPIV=(c_int * N)() LDB=c_int(N) INFO=c_int(1) lapack=load_library('liblapack.so','/usr/lib/') lapack.argtypes=[c_int,c_int, ndpointer(dtype=float64, ndim=2, flags='FORTRAN'), c_int,c_int, ndpointer(dtype=float64, ndim=1, flags='FORTRAN'), c_int,c_int] lapack.dgesv_(cN,NRHS,A,LDA,IPIV,B,LDB,INFO) return B And... In [2]: from lapackw import dgesv In [3]: from numpy import array In [4]: dgesv(2,array([[1,2],[3,4]]),array([1,2])) ... ArgumentError: argument 3: exceptions.TypeError: Don't know how to convert parameter 3 Maybe I am sooo dumb but I just don't know what I am doing wrong. numpy-1.0.1, ctypes 1.0.1, python 2.4.3. thanks guillem

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