Mailman 3 May 2014 - NumPy-Discussion

Renaming OSX wheels on pypi to make them more general
by Matthew Brett 01 Jun '14

01 Jun '14

Hi, This is actually for both of numpy and scipy. I would like to rename the current OSX wheels on pypi so that they will be installed by default on system python, homebrew, macports, as well as Python.org Python. At the moment, they will only be found and installed by default by Python.org Python. For reasons explained here: https://github.com/MacPython/wiki/wiki/Spinning-wheels and confirmed with testing here: https://travis-ci.org/matthew-brett/scipy-stack-osx-testing/builds/25131865 - OSX wheels built for Python.org python do in fact work correctly for the homebrew, macports and system python. In fact, future versions of pip will very likely offer the Python.org OSX wheels for installation on these other systems by default: https://github.com/pypa/pip/pull/1465 Renaming the wheels just adds the 'platform tag' for these other versions of Python to the wheel name, so pip sees they are compatible. For example, I propose to rename the current numpy wheel from: numpy-1.8.1-cp27-none-macosx_10_6_intel.whl to: numpy-1.8.1-cp27-none-macosx_10_6_intel.macosx_10_9_intel.macosx_10_9_x86_64.whl I think this is only an improvement to the current situation, in that users of pip on these other OSX systems will get a fast binary install rather than a slow compiled install. Any comments? Cheers, Matthew

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ANN: Pandas 0.14.0 released
by Jeff Reback 31 May '14

31 May '14

Hello, We are proud to announce v0.14.0 of pandas, a major release from 0.13.1. This release includes a small number of API changes, several new features, enhancements, and performance improvements along with a large number of bug fixes. This was 4 months of work with 1014 commits by 121 authors encompassing 757 issues. We recommend that all users upgrade to this version. *Highlights:* - Officially support Python 3.4 - SQL interfaces updated to use sqlalchemy - Display interface changes - MultiIndexing Using Slicers - Ability to join a singly-indexed DataFrame with a multi-indexed DataFrame - More consistency in groupby results and more flexible groupby specifications - Holiday calendars are now supported in CustomBusinessDay - Several improvements in plotting functions, including: hexbin, area and pie plots - Performance doc section on I/O operations See a full description of Whatsnew for v0.14.0 here: http://pandas.pydata.org/pandas-docs/stable/whatsnew.html *What is it:* *pandas* is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. Documentation: http://pandas.pydata.org/pandas-docs/stable/ Source tarballs, windows binaries are available on PyPI: https://pypi.python.org/pypi/pandas windows binaries are courtesy of Christoph Gohlke and are built on Numpy 1.8 macosx wheels will be available soon, courtesy of Matthew Brett Please report any issues here: https://github.com/pydata/pandas/issues Thanks The Pandas Development Team Contributors to the 0.14.0 release - Acanthostega - Adam Marcus - agijsberts - akittredge - Alex Gaudio - Alex Rothberg - AllenDowney - Andrew Rosenfeld - Andy Hayden - ankostis - anomrake - Antoine Mazières - anton-d - bashtage - Benedikt Sauer - benjamin - Brad Buran - bwignall - cgohlke - chebee7i - Christopher Whelan - Clark Fitzgerald - clham - Dale Jung - Dan Allan - Dan Birken - danielballan - Daniel Waeber - David Jung - David Stephens - Douglas McNeil - DSM - Garrett Drapala - Gouthaman Balaraman - Guillaume Poulin - hshimizu77 - hugo - immerrr - ischwabacher - Jacob Howard - Jacob Schaer - jaimefrio - Jason Sexauer - Jeff Reback - Jeffrey Starr - Jeff Tratner - John David Reaver - John McNamara - John W. O'Brien - Jonathan Chambers - Joris Van den Bossche - jreback - jsexauer - Julia Evans - Júlio - Katie Atkinson - kdiether - Kelsey Jordahl - Kevin Sheppard - K.-Michael Aye - Matthias Kuhn - Matt Wittmann - Max Grender-Jones - Michael E. Gruen - michaelws - mikebailey - Mike Kelly - Nipun Batra - Noah Spies - ojdo - onesandzeroes - Patrick O'Keeffe - phaebz - Phillip Cloud - Pietro Battiston - PKEuS - Randy Carnevale - ribonoous - Robert Gibboni - rockg - sinhrks - Skipper Seabold - SplashDance - Stephan Hoyer - Tim Cera - Tobias Brandt - Todd Jennings - TomAugspurger - Tom Augspurger - unutbu - westurner - Yaroslav Halchenko - y-p - zach powers

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Fortran 90 Library and .mod files numpy.distutils
by Onur Solmaz 30 May '14

30 May '14

I am building a Fortran 90 library and its extension. .mod files get generated inside the build/temp.linux-x86_64-2.7/ directory, and stay there; so when building the extension, the compiler complains that it cannot find the modules This is because the include paths do not have the temp directory. I can work this around by adding that to the include paths for the extension, but this is not a clean solution. What is the best solution to this? I also want to be able to use the modules later, because I will distribute the library. It is some other issue whether the modules should be distributed with the library under /usr/lib or /usr/include, refer to this<https://gcc.gnu.org/bugzilla/show_bug.cgi?id=49138>bug. Also one can refer to this<https://gcc.gnu.org/ml/fortran/2011-06/msg00117.html>thread. This is what convinced me to distribute the modules, rather than putting module definitions into header files, which the user can include in their code to recreate the modules. Yet another way is to use submodules, but that feature is not available in Fortran 90.

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Reordering indices
by Bob Dowling 30 May '14

30 May '14

Is there a clean way to create a view on an existing ND-array with its axes in a different order. For example, suppose I have an array of shape (100,200,300,3) and I want to create a view of this where the vector coordinate is axis 0, not axis 3. (So the view will have shape (3,100,200,300).) Reading the help(numpy.ndarray) output I can't find anything better than repeated calls to swapaxes(): >>> B = A.swapaxes(0,3).swapaxes(1,3).swapaxes(2,3) Is there a "reorder_axes()" method that would let me write something like this: >>> B = A.reorder_axes((3,0,1,2)) Apologies in advance if I've missed the obvious method in the docs.

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Arguments silently ignored (kwargs) in meshgrid etc.
by Michael McNeil Forbes 29 May '14

29 May '14

I just noticed that meshgrid() silently ignore extra arguments. It just burned me (I forgot that it is meshgrid(indexing='ij') and tried meshgrid(indices='ij') which subtly broke my code.) Is this intentional? I don't see why `meshgrid` does not have explicit arguments. If this is not a design decision, I will open an issue and PR. Michael.

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100 Numpy exercices
by Nicolas Rougier 29 May '14

29 May '14

Hi all, I've updated the numpy exercices collection and made it available on github at: https://github.com/rougier/numpy-100 These exercices mainly comes from this mailing list and also from stack overflow. If you have other examples in mind, do not hesitate to make a pull request. The master and archmaster sections still need to be populated... Once finished, I'll make an ipython notebook as well. Nicolas

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simple way to denote unchanged dimension in reshape?
by Chao YUE 29 May '14

29 May '14

Dear all, I have a simple question. Is there a way to denote the unchanged dimension in the reshape function? like suppose I have an array named "arr" having three dims with the first dimension length as 48, I want to reshape the first dim into 12*4, but keeping all the other dimension length unchanged. like when we slice the array, we can use: arr[10:40, ... ], "...' represents all remaining dimesions. however when doing reshape, we must use: arr.reshape(12,-1,arr.shape(1),arr.shape(2)) Is there something allowing more flexible reshape, like: arr.reshape(12,-1,...)? thanks a lot in advance, best, Chao -- please visit: http://www.globalcarbonatlas.org/ *********************************************************************************** Chao YUE Laboratoire des Sciences du Climat et de l'Environnement (LSCE-IPSL) UMR 1572 CEA-CNRS-UVSQ Batiment 712 - Pe 119 91191 GIF Sur YVETTE Cedex Tel: (33) 01 69 08 29 02; Fax:01.69.08.77.16 ************************************************************************************

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f2py and string arrays (need help)
by Siegfried Gonzi 28 May '14

28 May '14

Hi all Given the following pseudo code: == SUBROUTINE READ_B( FILENAME, ix,iy,iz,nx, OUT_ARRAY, out_cat) IMPLICIT NONE INTEGER*4, INTENT(IN) :: IX, iy, iz, nx REAL*4, INTENT(OUT) :: OUT_ARRAY(nx,IX, iy, iz) CHARACTER, dimension(nx,40),intent(out) ::OUT_CAT CHARACTER(LEN=40) :: CATEGORY integer :: i .... do i=1,nx READ( IU_FILE, IOSTAT=IOS) data, category, lon, lat,.... !!! category = 'IJVG=$' !!! or category = 'CHEM=$' out_cat(i,:) = category(:) enddo end subroutine read_b == I'd like to fill 'out_cat' with the names of the fields. As you guess my code does not work properly. How can I do it with f2py? I don't even know if my code is legal Fortran 90 at all. Thanks, Siegfried -- The University of Edinburgh is a charitable body, registered in Scotland, with registration number SC005336.

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Possible bug in linalg.matrix_rank
by Darlan Cavalcante Moreira 23 May '14

23 May '14

After updating Ubuntu to 14.04 and thus numpy to version 1.8.1 I'm having problems with the linalg.matrix_rank function that I didn't have before (as far as I know). More specifically, I get the error "TypeError: No loop matching the specified signature was found for ufunc svd_m" when I try to calculate the rank of a non-square complex matrix, but it does not happen for any non-square matrix. Below you can find the cases tyhat work and the case that doesn't work. --8<---------------cut here---------------start------------->8--- # Real matrices A = np.random.randn(3,3); A = np.random.randn(4,3); A = np.random.randn(3,4); np.linalg.matrix_rank(A) # Works for any of the previous 'A' matrices # Complex matrices A = np.random.randn(3,3) + 1j*np.random.randn(3,3); A = np.random.randn(4,3) + 1j*np.random.randn(4,3); np.linalg.matrix_rank(A) # Works for any of the previous 'A' matrices # For the matrix below I get the error A = np.random.randn(3,4) + 1j*np.random.randn(3,4); np.linalg.matrix_rank(A) # Does not work and gives me the TypeError --8<---------------cut here---------------end--------------->8--- -- Darlan Cavalcante Moreira darcamo(a)gmail.com

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ANN: SfePy 2014.2
by Robert Cimrman 23 May '14

23 May '14

I am pleased to announce release 2014.2 of SfePy. Description ----------- SfePy (simple finite elements in Python) is a software for solving systems of coupled partial differential equations by the finite element method. The code is based on NumPy and SciPy packages. It is distributed under the new BSD license. This release brings a preliminary support for isogeometric analysis - a recently developed computational approach that allows using the NURBS-based domain description from CAD design tools also for approximation purposes similar to the finite element method. Home page: http://sfepy.org Mailing list: http://groups.google.com/group/sfepy-devel Git (source) repository, issue tracker, wiki: http://github.com/sfepy Highlights of this release -------------------------- - preliminary support for isogeometric analysis - improved post-processing and visualization script for time-dependent problems with adaptive time steps - three new terms For full release notes see http://docs.sfepy.org/doc/release_notes.html#id1 (rather long and technical). Best regards, Robert Cimrman and Contributors (*) (*) Contributors to this release (alphabetical order): Vladimír Lukeš

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