Mailman 3 March 2013 - NumPy-Discussion

embedding numpy ImportError: numpy.core.multiarray failed to import
by Sunghwan Choi 06 Mar '13

06 Mar '13

Hi, I tried to embedding numpy in C++ but I got ImportError: numpy.core.multiarray failed to import Do you know any ways to solve this problem? I copy my codes and error message Makefile CXX= icpc all: exe clean: rm -rf *.o exe exe: test.o $(CXX) -o exe test.o -L/home/shchoi/program/epd/lib/ -lpython2.7 test.o : test.cpp $(CXX) -c test.cpp -I/home/shchoi/program/epd/lib/python2.7/site-packages/numpy/core/include/nu mpy/ -I/home/shchoi/program/epd/include/python2.7 tmp.cpp #include "Python.h" #include "arrayobject.h" #include <stdio.h> #include <iostream> extern "C" void Py_Initialize(); extern "C" void PyErr_Print(); using namespace std; int main(int argc, char* argv[]) { double answer = 0; PyObject *modname, *mod, *mdict, *func, *stringarg, *args, *rslt; Py_Initialize(); import_array(); modname = PyString_FromString("numpy"); mod = PyImport_Import(modname); PyErr_Print(); cout << mod << endl; Py_Finalize(); return 0; } $ make icpc -c test.cpp -I/home/shchoi/program/epd/lib/python2.7/site-packages/numpy/core/include/nu mpy/ -I/home/shchoi/program/epd/include/python2.7 test.cpp(15): warning #117: non-void function "main" should return a value import_array(); ^ icpc -o exe test.o -L/home/shchoi/program/epd/lib/ -lpython2.7 #-L/home/shchoi/program/epd/lib/python2.7/site-packages/numpy/core/ $ ./exe ImportError: numpy.core.multiarray failed to import Sunghwan Choi

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scipy_distutils.fcompiler
by Gergely Buday 05 Mar '13

05 Mar '13

Hi there, I try to compile a program developed with scipy. It is installed on my Ubuntu 12.04 box but upon make I get: Traceback (most recent call last): File "/usr/local/bin/f2py", line 4, in <module> f2py2e.main() File "/usr/local/lib/python2.7/dist-packages/f2py2e/f2py2e.py", line 677, in main run_compile() File "/usr/local/lib/python2.7/dist-packages/f2py2e/f2py2e.py", line 536, in run_compile import scipy_distutils.fcompiler ImportError: No module named scipy_distutils.fcompiler What should I do to fix this? I have scipy Version: 0.9.0+dfsg1-1ubuntu2 - Gergely

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Remove interactive setup
by Charles R Harris 05 Mar '13

05 Mar '13

In distutils there are three files that provide some interactive setup: 1. numpy/distutils/core.py 2. numpy/distutils/fcompiler/gnu.py 3. numpy/distutils/interactive.py In Python3 `raw_input` has been renamed 'input' and python2 'input' is gone. I propose that the easiest solution to this compatibility problem is to remove all support for interactive numpy setup. Thoughts? Chuck

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Adding .abs() method to the array object
by Till Stensitzki 04 Mar '13

04 Mar '13

Hello, i know that the array object is already crowded, but i would like to see the abs method added, especially doing work on the console. Considering that many much less used functions are also implemented as a method, i don't think adding one more would be problematic. greetings Till

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step paramter for linspace
by Sebastian Berg 04 Mar '13

04 Mar '13

Hi, there has been a request on the issue tracker for a step parameter to linspace. This is of course tricky with the imprecision of floating point numbers. As a trade off, I was thinking of a step parameter that is used to calculate the integer number of steps. However to be certain that it never misbehaves, doing this strict up to the numerical precision of the (float) numbers. Effectively this means: In [9]: np.linspace(0, 1.2, step=0.3) Out[9]: array([ 0. , 0.3, 0.6, 0.9, 1.2]) In [10]: np.linspace(0, 1.2+5-5, step=0.3) Out[10]: array([ 0. , 0.3, 0.6, 0.9, 1.2]) In [11]: np.linspace(0, 1.2+500-500, step=0.3) ValueError: could not determine exact number of samples for given step I.e. the last fails, because 1.2 + 500 - 500 == 1.1999999999999886, which is an error that is larger then the imprecision of floating point numbers. Is this considered useful, or as it can easily fail for calculated numbers, and is thus only a convenience, it is not? Regards, Sebastian

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EuroSciPy 2013 Call for Abstracts
by Tiziano Zito 04 Mar '13

04 Mar '13

Dear Scientist using Python, EuroSciPy 2013, the Sixth Annual Conference on Python in Science, takes place in Brussels on 21 - 24 August 2013. The conference features two days of tutorials followed by two days of scientific talks that start with our keynote speakers, Cameron Neylon and Peter Wang. The topics presented at EuroSciPy are very diverse, with a focus on advanced software engineering and original uses of Python and its scientific libraries, either in theoretical or experimental research, from both academia and the industry. The program includes contributed talks and posters. Submissions for talks and posters are welcome on our website (http://www.euroscipy.org/). Authors must use the web interface to submit an abstract to the conference. In your abstract, please provide details on what Python tools are being employed, and how. The deadline for submission is 28 April 2013. Until 31 March 2013, you can apply for a sprint session on 25 August 2013. Also, potential organizers for EuroSciPy 2014 are welcome to contact the conference committee. SciPythonic Regards, The EuroSciPy 2013 Committee http://www.euroscipy.org/ Conference Chairs: Pierre de Buyl and Nicolas Pettiaux, Université libre de Bruxelles, Belgium Tutorial Chair: Nicolas Rougier, INRIA, Nancy, France Program Chair: Tiziano Zito, Humboldt-Universität zu Berlin, Germany Program Committee Ralf Gommers, ASML, The Netherlands Emmanuelle Gouillart, Joint Unit CNRS/Saint-Gobain, France Kael Hanson, Université Libre de Bruxelles, Belgium Konrad Hinsen, Centre National de la Recherche Scientifique (CNRS), France Hans Petter Langtangen, Simula and University of Oslo, Norway Mike Müller, Python Academy, Germany Raphael Ritz, International Neuroinformatics Coordinating Facility, Stockholm, Sweden Stéfan van der Walt, Applied Mathematics, Stellenbosch University, South Africa Gaël Varoquaux, INRIA Parietal, Saclay, France Nelle Varoquaux, Mines ParisTech, France Pauli Virtanen, Aalto University, Finland Organizing Committee Nicolas Chauvat, Logilab, France Emmanuelle Gouillart, Joint Unit CNRS/Saint-Gobain, France Kael Hanson, Université Libre de Bruxelles, Belgium Renaud Lambiotte, University of Namur, Belgium Thomas Lecocq, Royal Observatory of Belgium Mike Müller, Python Academy, Germany Didrik Pinte, Enthought Europe Gaël Varoquaux, INRIA Parietal, Saclay, France Nelle Varoquaux, Mines ParisTech, France

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Array indexing and repeated indices
by Nicolas Rougier 01 Mar '13

01 Mar '13

Hi, I'm trying to increment an array using indexing and a second array for increment values (since it might be a little tedious to explain, see below for a short example). Using "direct" indexing, the values in the example are incremented by 1 only while I want to achieve the alternative behavior. My question is whether there is such function in numpy or if there a re better way to achieve the same result ? (I would like to avoid the while statement) I found and adapted the alternative solution from: http://stackoverflow.com/questions/2004364/increment-numpy-array-with-repea… but it is only for a fixed increment from what I've understood. Nicolas # ------------------------ import numpy as np n,p = 5,100 nodes = np.zeros( n, [('value', 'f4', 1)] ) links = np.zeros( p, [('source', 'i4', 1), ('target', 'i4', 1)]) links['source'] = np.random.randint(0, n, p) links['target'] = np.random.randint(0, n, p) targets = links['target'] # Indices can be repeated K = np.ones(len(targets)) # Note K could be anything # Direct indexing nodes['value'] = 0 nodes['value'][targets] += K print nodes # "Alternative" indexing nodes['value'] = 0 B = np.bincount(targets) while B.any(): I = np.argwhere(B>=1) nodes['value'][I] += K[I] B = np.maximum(B-1,0) print nodes

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