NumPy-Discussion March 2006

numpy-discussion@python.org

106 participants
171 discussions

precedence of '&' and '>' operators
by Michael Sorich 27 Mar '06

27 Mar '06

It seems that the '&' operator has a higher precedence than a comparison operator such as '>'. This does not seem so intuitive to me. Is this correct? eg >>>import numpy as N >>>N.version.version '0.9.6' >>>a = N.arange(10) >>>a>1 & a<4 Traceback (most recent call last): File "<input>", line 1, in ? ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() >>>(a>1) & (a<4) array([False, False, True, True, False, False, False, False, False, False], dtype=bool) Michael

3 2

Re: [Numpy-discussion] order flag again
by Fernando Perez 27 Mar '06

27 Mar '06

On 01:46 PM Tim Hochberg wrote: > As I've mentioned before, I'd like to sweep all of the operations that may > return a view or a copy into a few asXXXarray functions so that these > potentially problematic operations are localized and easily identifiable. +1 on the idea that: asXXXarray: functions which take their input and return always an array, but trying to avoid copies if at all possible. This means that code calling such functions should treat their returned values strictly as /inputs/, never modifying them in place. These functions are provided by numpy strictly for performance reasons. Or something like that. I like being able to tell to users that this kind of problem is solved by a unified familiy of functions in the API, with a clear naming convention. There is a need for them, but they are also a bit dangerous, so they should be clearly labeled. Painting them all in the same bright red helps indicate their 'sharp blade' nature. Cheers, f

3 4

Re: [Numpy-discussion] arrays and iterators.
by Travis Oliphant 27 Mar '06

27 Mar '06

Tim Hochberg wrote: > Travis Oliphant wrote: > >> Tim Hochberg wrote: >> >>> >>> Lest everybody think that I'm only about ripping things out, let me >>> propose adding a feature. Well, sort of. I propose that we make: >>> >>> array(someiterator) >>> >>> an value error for right now instead of returning a rank-0 object >>> array. >> >> >> >> I'm O.K. with that. >> -Travis > > > OK, if no one else objects in the next day or so, I'll look into doing > it. You might also look at having array(generator object) actually run the generator instead of return a rank-0 object array. -Travis

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Re: [Numpy-discussion] arrays and iterators.
by Travis Oliphant 27 Mar '06

27 Mar '06

Tim Hochberg wrote: > Travis Oliphant wrote: > >> Tim Hochberg wrote: >> >>> >>> Lest everybody think that I'm only about ripping things out, let me >>> propose adding a feature. Well, sort of. I propose that we make: >>> >>> array(someiterator) >>> >>> an value error for right now instead of returning a rank-0 object >>> array. >> >> >> >> I'm O.K. with that. >> -Travis > > > OK, if no one else objects in the next day or so, I'll look into doing > it. Just to be clear. You are only going to change the case which does presently return a rank-0 object array, right? someiterator could be an array, or a list in which case array(someiterator) already does an intelligible thing. -Travis

1 0

making a character array from numeric array
by Michael Sorich 27 Mar '06

27 Mar '06

<Numpy-discussion(a)lists.sourceforge.net>Hi, I am trying to convert an int or float ndarray into a string ndarray. Using astype this is possible, but only if you explicity set the number of characters (see eg below). It would be nice if just setting type='S' (or N.str_) would automatically make an a character array of sufficient size to hold the string representation. Is there a way to do this? thanks, michael import numpy as N N.version.version '0.9.6' N.arange(20).astype(N.str_) array([, , , , , , , , , , , , , , , , , , , ], dtype='|S0') N.arange(20).astype('S') array([, , , , , , , , , , , , , , , , , , , ], dtype='|S0') N.arange(20).astype('S1') array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1], dtype='|S1') N.arange(20).astype('S2') array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19], dtype='|S2')

2 1

Bug in scipy.linalg.svd?
by Webb Sprague 27 Mar '06

27 Mar '06

Hi all, scipy.__version__: 0.3.2 numpy.__version__: 0.9.4 OS: Gentoo. Maybe I am missing something key here, but my Numerical Recipes book says: "Any M x N matrix A whose number of rows M is greater than or equal to its number of columns N, can be written as the product of of an *M x N* column orthogonal matrix U, an N x N diagonal matrix W, ... and the transpose of an N x N orthogh matrix V." So... why do I get the following behavior: (u, x, v) = scipy.linalg.svd(RandomArray.normal(0,1,[10,4]) u.shape == (10,10) By the way, if you run this from Numeric, U[:, 0:4] are the same, but Numeric doesn't generate the additional columns. I think we should write a unit test such that matrixmultipy(matrixmultiply(u,diag(x)), transpose(v)) == A.

2 1

arrays and iterators.
by Tim Hochberg 27 Mar '06

27 Mar '06

Lest everybody think that I'm only about ripping things out, let me propose adding a feature. Well, sort of. I propose that we make: array(someiterator) an value error for right now instead of returning a rank-0 object array. Then, in Python 2.5, we can use the _length_hint protocol to efficiently create arrays from iterator objects without any extra copying. The exact details don't need to be worked out right now, after all we're all too tied up with reshape, but I'd like to reserve that syntax for that purpose. Regards, -tim

1 0

A newbie question: How to get the "rank" of an 1-d array
by CL 27 Mar '06

27 Mar '06

Hi, group, I need to get the "rank" of an 1-D array (ie. a vector). Note that "rank" here is not the value returned from "rank(a_array)". It is the order of the item in its sorted arrray. For example, I have a python function called "listrank" to return the "rank" as below: In [19]: x Out[19]: array([1, 2, 5, 3, 3, 2]) In [20]: listrank(x) Out[20]: [6, 4, 1, 2, 2, 4] Somebody suggested me to use "argsort(argsort(x))". But the problem is it does not handle ties. See the output: In [21]: argsort(argsort(x)) Out[21]: array([0, 1, 5, 3, 4, 2]) I am wondering if there is a solution in numpy/numarray/numeric to get this done nicely. Thanks. CL

2 3

scipy.sparse + umfpack + system_info
by Robert Cimrman 27 Mar '06

27 Mar '06

Hi all, I have added a basic umfpack detection support to numpy.distutils.system_info() - see example site.cfg below (and replace <UMFPACKv4.4_root>...). The Umfpack wrapper still resides in the sandbox, but its setup.py now uses the detection stuff. Now I would like to move the wrapper somewhere under scipy.sparse and I hit a problem: umpfack.py depends on scipy.sparse, since it uses the CSR/CSC matrix formats, but also scipy.sparse uses umfpack.py for solving linear equations.if present. How to get out of this circular dependency problem? Do you have any suggestions on how to organize the files? r. -- site.cfg: [umfpack] library_dirs = <UMFPACKv4.4_root>/UMFPACK/Lib:<UMFPACKv4.4_root>/AMD/Lib include_dirs = <UMFPACKv4.4_root>/UMFPACK/Include umfpack_libs = umfpack, amd

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Re: [Numpy-discussion] (offlist) Numpy implementation of IDL & pdl's rebin?
by Gary Ruben 26 Mar '06

26 Mar '06

Recently a question was asked about whether numpy/scipy had a data rebin command similar to IDL's rebin. IDL's rebin can rebin data to smaller or larger arrays whose dimensions are factors or multiples of the original size. I have had a play and placed some code which takes care of the reducing case for ndarrays on the wiki here: <http://scipy.org/Cookbook/Rebinning> Gary R.

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NumPy-Discussion March 2006