Re: [Numpy-discussion] NumPy trunk is frozen for upcoming 1.0.4 release
Emanuel Woiski wrote: Thanks. I will try them later and let you know. Any chance to have those for 2.4 as well?:) If it works, I will be able to upgrade to matplotlib 0.90.1 Well, you will have to find someone else. Using windows is already painful enough: I don't have the motivation to build for every supported python versions :) cheers, David ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] NumPy trunk is frozen for upcoming 1.0.4 release
yep I have no choice - those are a bunch of lab machines:) thanks anyway regards woiski On Nov 6, 2007 9:59 AM, David Cournapeau [EMAIL PROTECTED] wrote: Emanuel Woiski wrote: Thanks. I will try them later and let you know. Any chance to have those for 2.4 as well?:) If it works, I will be able to upgrade to matplotlib 0.90.1 Well, you will have to find someone else. Using windows is already painful enough: I don't have the motivation to build for every supported python versions :) cheers, David ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://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] boolean masks lists
On Nov 6, 2007 7:22 AM, Lisandro Dalcin [EMAIL PROTECTED] wrote: Mmm... It looks as it 'mask' is being inernally converted from [True, False, False, False, True] to [1, 0, 0, 0, 1] so your are finally getting x[1], x[0], x[0], x[0], x[1] That would be my guess as well. And, it looks wrong to me. Given that array(mask) gives you the boolean mask, there's every expectation to expect the the list and array cases should be the same. I would file a bug report. On 11/5/07, John Hunter [EMAIL PROTECTED] wrote: A colleague of mine just asked for help with a pesky bug that turned out to be caused by his use of a list of booleans rather than an array of booleans as his logical indexing mask. I assume this is a feature and not a bug, but it certainly surprised him: In [58]: mask = [True, False, False, False, True] In [59]: maska = n.array(mask, n.bool) In [60]: x = arange(5) In [61]: x[mask] Out[61]: array([1, 0, 0, 0, 1]) In [62]: x[maska] Out[62]: array([0, 4]) ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion -- Lisandro Dalcín --- Centro Internacional de Métodos Computacionales en Ingeniería (CIMEC) Instituto de Desarrollo Tecnológico para la Industria Química (INTEC) Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET) PTLC - Güemes 3450, (3000) Santa Fe, Argentina Tel/Fax: +54-(0)342-451.1594 ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion -- . __ . |-\ . . [EMAIL PROTECTED] ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] boolean masks lists
On Nov 6, 2007 8:22 AM, Lisandro Dalcin [EMAIL PROTECTED] wrote: Mmm... It looks as it 'mask' is being inernally converted from [True, False, False, False, True] to [1, 0, 0, 0, 1] Yep, clearly. The question is: is this the desired behavior because it leads to a silent failure for people who are expecting sequences of booleans to behave like arrays of booleans. JDH ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] boolean masks lists
John Hunter wrote: A colleague of mine just asked for help with a pesky bug that turned out to be caused by his use of a list of booleans rather than an array of booleans as his logical indexing mask. I assume this is a feature and not a bug, but it certainly surprised him: In [58]: mask = [True, False, False, False, True] In [59]: maska = n.array(mask, n.bool) In [60]: x = arange(5) In [61]: x[mask] Out[61]: array([1, 0, 0, 0, 1]) In [62]: x[maska] Out[62]: array([0, 4]) The issues is how to determine what behavior is desired and how to manage that with all the possibilities. Right now the rule is that only boolean arrays are treated as masks and integer arrays mean indexing. Lists are always interpreted as integer indexing (except in certain special cases where the list has slice objects in it).Changing this to something like: lists are interpreted either as boolean or integer arrays, may be reasonable, but I don't see how we can change it until 1.1 because the rule has already been specified and is consistent if not obvious in this simple case. The question is: is anybody using boolean lists specifically according to the rule in place now? -Travis ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
[Numpy-discussion] Assessing the use of packages
All, It's evaluation time in my department (Bio. Ag. Engng, UGA), and I'd need to document the impact of my Python contributions on the scientific community at large, or more realistically on the numpy/scipy user community... * Is there a way to estimate how many people installed one particular package from the SVN ? * if it's too tricky, would anybody using maskedarray and/or timeseries and/or pyloess (the SVN packages I helped implementing) mind dropping me a line off-list, with a very short description of the main field of research/use ? I'd basically need some kind of numbers to give to the People-In-Charge. Thanks a lot in advance for your time. P. PS: Sorry for the cross-posting.. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
Re: [Numpy-discussion] Assessing the use of packages
Pierre GM wrote: All, It's evaluation time in my department (Bio. Ag. Engng, UGA), and I'd need to document the impact of my Python contributions on the scientific community at large, or more realistically on the numpy/scipy user community... * Is there a way to estimate how many people installed one particular package from the SVN ? No. We could only record who has checked them out from SVN. However, everyone who has checked out the scipy trunk will have gotten the packages you are concerned with. Whether or not they've built them or used them is another matter which we cannot determine. -- 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] Making a minimalist NumPy
Benjamin M. Schwartz wrote: -BEGIN PGP SIGNED MESSAGE- Hash: SHA1 NumPy is included in the OLPC operating system, which is very constrained in space. Therefore, it would be nice to remove some subpackages to save a few megabytes. For example, the system does not include any Fortran code or compiler, so f2py (3.6 MB) seems superfluous. I also think the distutils subpackage (1.9M) is probably not necessary. Therefore, I have two questions. 1. Which packages do you think are necessary to have a functioning NumPy? 2. What is the easiest way to make (or get) a minimal NumPy installation? For example, would the scons/autoconf branch make this easier? * You can get rid of f2py, oldnumeric, numarray, and testing. * If you don't need to support building of c-extensions then distutils can also be tossed. To make it, you should be able to just edit the numpy/numpy/setup.py script to remove adding those sub-packages. Then, python setup.py install should work. Let me know if you need further help. -Travis O. ___ Numpy-discussion mailing list Numpy-discussion@scipy.org http://projects.scipy.org/mailman/listinfo/numpy-discussion
