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  • Python Pari Library?

    - by silinter
    Pari/GP is an excellent library for functions relating to number theory. The problem is that there doesn't seem to be an up to date wrapper for python anywhere around, (pari-python uses an old version of pari) and I'm wondering if anyone knows of some other library/wrapper that is similar to pari or one that uses pari. I'm aware of SAGE, but it's far too large for my needs. GMPY is excellent as well, but there are some intrinsic pari functions that I miss, and I'd much rather use python than the provided GP environment. NZMATH, mpmath, scipy and sympy were all taken into consideration as well. On a related note, does anyone have any suggestions on loading the pari dll itself and using the functions contained in it? I've tried to very little success, other than loading it and learning about function pointers.

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  • Plotting 3D Polygons in python-matplotlib

    - by Developer
    I was unsuccessful browsing web for a solution for the following simple question: How to draw 3D polygon (say a filled rectangle or triangle) using vertices values? I have tried many ideas but all failed, see: from mpl_toolkits.mplot3d import Axes3D from matplotlib.collections import PolyCollection import matplotlib.pyplot as plt fig = plt.figure() ax = Axes3D(fig) x = [0,1,1,0] y = [0,0,1,1] z = [0,1,0,1] verts = [zip(x, y,z)] ax.add_collection3d(PolyCollection(verts),zs=z) plt.show() I appreciate in advance any idea/comment. Updates based on the accepted answer: import mpl_toolkits.mplot3d as a3 import matplotlib.colors as colors import pylab as pl import scipy as sp ax = a3.Axes3D(pl.figure()) for i in range(10000): vtx = sp.rand(3,3) tri = a3.art3d.Poly3DCollection([vtx]) tri.set_color(colors.rgb2hex(sp.rand(3))) tri.set_edgecolor('k') ax.add_collection3d(tri) pl.show() Here is the result:

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  • Python Library installation

    - by MacPython
    Hi everybody I have two questions regarding python libraries: I would like to know if there is something like a "super" python library which lets me install ALL or at least all scientific useful python libraries, which I can install once and then I have all I need. There is a number of annoying problems when installing different libraries (pythonpath, cant import because it is not installed BUT it is installed). Is there any good documentation about common installation errors and how to avoid them. If there is no total solution I would be interested in numpy, scipy, matplotlib, PIL Thanks a lot for the attention and help Best Z

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  • Rapid spectral analysis of audio file using Python 2.6?

    - by Ephemeralis
    What I want to do is to have a subroutine that analyses every 200 milliseconds of a sound file which it is given and spits out the frequency intensity value (from 0 to 1 as a float) of a specific frequency range into an array which I later save. This value then goes on to be used as the opacity value for a graphic which is supposed to 'strobe' to the audio file. The problem is, I have never ventured into audio analysis before and have no clue where to start. I have looked pymedia and scipy/numpy thinking I would be able to use FFT in order to achieve this, but I am not really sure how I would manipulate this data to end up with the desired result. The documentation on the SpectrAnalyzer class of pymedia is virtually non-existant and the examples on the website do not actually work with the latest release of the library - which isn't exactly making my life easier. How would I go about starting this project? I am at a complete loss as to what libraries I should even be using.

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  • Removing duplicates (within a given tolerance) from a Numpy array of vectors

    - by Brendan
    I have an Nx5 array containing N vectors of form 'id', 'x', 'y', 'z' and 'energy'. I need to remove duplicate points (i.e. where x, y, z all match) within a tolerance of say 0.1. Ideally I could create a function where I pass in the array, columns that need to match and a tolerance on the match. Following this thread on Scipy-user, I can remove duplicates based on a full array using record arrays, but I need to just match part of an array. Moreover this will not match within a certain tolerance. I could laboriously iterate through with a for loop in Python but is there a better Numponic way?

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  • python how to put data on y-axis when plotting histogram

    - by user3041107
    I don't quite understand how to control y - axis when using plt.hist plot in python. I read my .txt data file - it contains 10 columns with various data. If I want to plot distribution of strain on x axis I take column n.5. But what kind of value appears on y axis ??? Don't understand that. here is the code: import numpy import matplotlib.pyplot as plt from pylab import * from scipy.stats import norm import sys strain = [] infile = sys.argv[1] for line in infile: ret = numpy.loadtxt(infile) strain += list(ret[:,5]) fig = plt.figure() plt.hist(strain, bins = 20) plt.show() Thanks for help!

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  • why am i getting an error SyntaxError : invalid syntax for this code

    - by eragon1189
    This is a code in python which calculates f (x) =? ((-1)*x)/(x*x+n*n) n from 1 to infinite.... correct to 0.0001, for the range 1 < x < 100 in steps of 0.1.But i am getting an syntax error,as i am new to programming in python... from scipy import * from matplotlib.pyplot import * x=arange(0.1,100,0.1) f=zeros(len(x)) s=-1 for n in range (1,10000): t=s*x/(x*x+n*n) f +=t s =-s if max(abs(t))< 1e-4 break for xx in c_[x,f]: print "%f %f" % (xx[0],xx[1])

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  • apache pointing to the wrong version of python on ubuntu how do I change?

    - by one
    I am setting up a flask application on and Ubuntu 12.04.3 LTS EC2 instance and everything seemed to be working well (i.e. I could get to the webpage via the publicly available url) until I tried to import a module (e.g. numpy) and realised the apache python differs from the one I used to compile the mod_wsgi and also the one I am using I am running apache2. The apache2 logs show the warnings (specifically the last line shows the path hasnt changed): [warn] mod_wsgi: Compiled for Python/2.7.5. [warn] mod_wsgi: Runtime using Python/2.7.3. [warn] mod_wsgi: Python module path '/usr/lib/python2.7/:/usr/lib/python2.7/plat-linux2:/usr/lib/python2.7/lib-tk:/usr/lib$ I have tried to set the path in my virtual host conf (my python is located in /home/ubuntu/anaconda/bin along with all of the other libraries): WSGIPythonHome /home/ubuntu/anaconda WSGIPythonPath /home/ubuntu/anaconda <VirtualHost *:80> ServerName xx-xx-xxx-xxx-xxx.compute-1.amazonaws.com ServerAdmin [email protected] WSGIScriptAlias / /var/www/microblog/microblog.wsgi <Directory /var/www/microblog/app/> Order allow,deny Allow from all </Directory> Alias /static /var/www/microblog/app/static <Directory /var/www/FlaskApp/FlaskApp/static/> Order allow,deny Allow from all </Directory> ErrorLog ${APACHE_LOG_DIR}/error.log LogLevel warn CustomLog ${APACHE_LOG_DIR}/access.log combined </VirtualHost> But I still get the warnings and the apache python path hasnt changed - where do I need to put the relevant directives to point apache at my python version and modules (e.g. scipy, numpy etc)? Separately, could I have avoided this using virtual environments? Thanks in advance.

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  • Installing Numpy locally

    - by Néstor
    I posted this question originally on StackOverflow, but a user suggested I moved it here so here I go! I have an account in a remote computer without root permissions and I needed to install a local version of Python (the remote computer has a version of Python that is incompatible with some codes I have), Numpy and Scipy there. I've been trying to install numpy locally since yesterday, with no success. I successfully installed a local version of Python (2.7.3) in /home/myusername/.local/, so I access to this version of Python by doing /home/myusername/.local/bin/python. I tried two ways of installing Numpy: I downloaded the lastest stable version of Numpy from the official webpage, unpacked it, got into the unpacked folder and did: /home/myusername/.local/bin/python setup.py install --prefix=/home/myusername/.local. However, I get the following error, which is followed by a series of other errors (deriving from this one): gcc -pthread -shared build/temp.linux-x86_64-2.7/numpy/core/blasdot/_dotblas.o -L/usr/local/lib -Lbuild/temp.linux-x86_64-2.7 -lptf77blas -lptcblas -latlas -o build/lib.linux-x86_64-2.7/numpy/core/_dotblas.so /usr/bin/ld: /usr/local/lib/libptcblas.a(cblas_dptgemm.o): relocation R_X86_64_32 against `a local symbol' can not be used when making a shared object; recompile with -fPIC Not really knowing what this meant (except that the error apparently has to do with the LAPACK library), I just did the same command as above, but now putting LDFLAGS='-fPIC', as suggested by the error i.e., I did LDFLAGS="-fPIC" /home/myusername/.local/bin/python setup.py install --prefix=/home/myusername/.local. However, I got the same error (except that the prefix -fPIC was addeded after the gcc command above). I tried installing it using pip, i.e., doing /home/myusername/.local/bin/pip install numpy /after successfully instaling pip in my local path). However, I get the exact same error. I searched on the web, but none of the errors seemed to be similar to mine. My first guess is that this has to do with some piece of code that needs root permissions to be executed, or maybe with some problem with the version of the LAPACK libraries or with gcc (gcc version 4.1.2 is installed on the remote computer). Help, anyone?

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  • How to write PIL image filter for plain pgm format?

    - by Juha
    How can I write a filter for python imaging library for pgm plain ascii format (P2). Problem here is that basic PIL filter assumes constant number of bytes per pixel. My goal is to open feep.pgm with Image.open(). See http://netpbm.sourceforge.net/doc/pgm.html or below. Alternative solution is that I find other well documented ascii grayscale format that is supported by PIL and all major graphics programs. Any suggestions? br, Juha feep.pgm: P2 # feep.pgm 24 7 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 3 3 3 0 0 7 7 7 7 0 0 11 11 11 11 0 0 15 15 15 15 0 0 3 0 0 0 0 0 7 0 0 0 0 0 11 0 0 0 0 0 15 0 0 15 0 0 3 3 3 0 0 0 7 7 7 0 0 0 11 11 11 0 0 0 15 15 15 15 0 0 3 0 0 0 0 0 7 0 0 0 0 0 11 0 0 0 0 0 15 0 0 0 0 0 3 0 0 0 0 0 7 7 7 7 0 0 11 11 11 11 0 0 15 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 edit: Thanks for the answer, I works... but I need a solution that uses Image.open(). Most of python programs out there use PIL for graphics manipulation (google: python image open). Thus, I need to be able to register a filter to PIL. Then, I can use any software that uses PIL. I now think mostly scipy, pylab, etc. dependent programs.

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  • How to compile Python scripts for use in FORTRAN?

    - by Vincent Poirier
    Hello, Although I found many answers and discussions about this question, I am unable to find a solution particular to my situation. Here it is: I have a main program written in FORTRAN. I have been given a set of python scripts that are very useful. My goal is to access these python scripts from my main FORTRAN program. Currently, I simply call the scripts from FORTRAN as such: CALL SYSTEM ('python pyexample.py') Data is read from .dat files and written to .dat files. This is how the python scripts and the main FORTRAN program communicate to each other. I am currently running my code on my local machine. I have python installed with numpy, scipy, etc. My problem: The code needs to run on a remote server. For strictly FORTRAN code, I compile the code locally and send the executable to the server where it waits in a queue. However, the server does not have python installed. The server is being used as a number crunching station between universities and industry. Installing python along with the necessary modules on the server is not an option. This means that my “CALL SYSTEM ('python pyexample.py')” strategy no longer works. Solution?: I found some information on a couple of things in thread http://stackoverflow.com/questions/138521/is-it-feasible-to-compile-python-to-machine-code Shedskin, Psyco, Cython, Pypy, Cpython API These “modules”(? Not sure if that's what to call them) seem to compile python script to C code or C++. Apparently not all python features can be translated to C. As well, some of these appear to be experimental. Is it possible to compile my python scripts with my FORTRAN code? There exists f2py which converts FORTRAN code to python, but it doesn't work the other way around. Any help would be greatly appreciated. Thank you for your time. Vincent PS: I'm using python 2.6 on Ubuntu

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  • Bibliography behaves strange in lyx.

    - by Orjanp
    Hi! I have created a Bibliography section in my document written in lyx. It uses a book layout. For some reason it did start over again when I added some more entries. The new entries was made some time later than the first ones. I just went down to key-27 and hit enter. Then it started on key-1 again. Does anyone know why it behaves like this? The lyx code is below. \begin{thebibliography}{34} \bibitem{key-6}Lego mindstorms, http://mindstorms.lego.com/en-us/default.aspx \bibitem{key-7}C.A.R. Hoare. Communicating sequential processes. Communications of the ACM, 21(8):666-677, pages 666\textendash{}677, August 1978. \bibitem{key-8}C.A.R. Hoare. Communicating sequential processes. Prentice-Hall, 1985. \bibitem{key-9}CSPBuilder, http://code.google.com/p/cspbuilder/ \bibitem{key-10}Rune Møllegård Friborg and Brian Vinter. CSPBuilder - CSP baset Scientific Workflow Modelling, 2008. \bibitem{key-11}Labview, http://www.ni.com/labview \bibitem{key-12}Robolab, http://www.lego.com/eng/education/mindstorms/home.asp?pagename=robolab \bibitem{key-13}http://code.google.com/p/pycsp/ \bibitem{key-14}Paparazzi, http://paparazzi.enac.fr \bibitem{key-15}Debian, http://www.debian.org \bibitem{key-16}Ubuntu, http://www.ubuntu.com \bibitem{key-17}GNU, http://www.gnu.org \bibitem{key-18}IVY, http://www2.tls.cena.fr/products/ivy/ \bibitem{key-19}Tkinter, http://wiki.python.org/moin/TkInter \bibitem{key-20}pyGKT, http://www.pygtk.org/ \bibitem{key-21}pyQT4, http://wiki.python.org/moin/PyQt4 \bibitem{key-22}wxWidgets, http://www.wxwidgets.org/ \bibitem{key-23}wxPython GUI toolkit, http://www.wxPython.org \bibitem{key-24}Python programming language, http://www.python.org \bibitem{key-25}wxGlade, http://wxglade.sourceforge.net/ \bibitem{key-26}http://numpy.scipy.org/ \bibitem{key-27}http://www.w3.org/XML/ \bibitem{key-1}IVY software bus, http://www2.tls.cena.fr/products/ivy/ \bibitem{key-2}sdas \bibitem{key-3}sad \bibitem{key-4}sad \bibitem{key-5}fsa \bibitem{key-6}sad \bibitem{key-7} \end{thebibliography}

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  • vtk glyphs 3D, indenpently color and rotation

    - by user3684219
    I try to display thanks to vtk (python wrapper) several glyphs in a scene with each their own colour and rotation. Unfortunately, just the rotation (using vtkTensorGlyph) is taken in consideration by vtk. Reversely, just color is taken in consideration when I use a vtkGlyph3D. Here is a ready to use piece of code with a vtkTensorGlyph. Each cube should have a random color but there all will be in the same color. I read and read again the doc of vtk but I found no solution. Thanks in advance for any idea #!/usr/bin/env python # -*- coding: utf-8 -*- import vtk import scipy.linalg as sc import random as ra import numpy as np import itertools points = vtk.vtk.vtkPoints() # where to locate each glyph in the scene tensors = vtk.vtkDoubleArray() # rotation for each glyph tensors.SetNumberOfComponents(9) colors = vtk.vtkUnsignedCharArray() # should be the color for each glyph colors.SetNumberOfComponents(3) # let's make 10 cubes in the scene for i in range(0, 50, 5): points.InsertNextPoint(i, i, i) # position of a glyph colors.InsertNextTuple3(ra.randint(0, 255), ra.randint(0, 255), ra.randint(0, 255) ) # pick random color rot = list(itertools.chain(*np.reshape(sc.orth(np.random.rand(3, 3)).transpose(), (1, 9)).tolist())) # random rotation matrix (row major) tensors.InsertNextTuple9(*rot) polydata = vtk.vtkPolyData() # create the polydatas polydata.SetPoints(points) polydata.GetPointData().SetTensors(tensors) polydata.GetPointData().SetScalars(colors) cubeSource = vtk.vtkCubeSource() cubeSource.Update() glyphTensor = vtk.vtkTensorGlyph() glyphTensor.SetColorModeToScalars() # is it really work ? try: glyphTensor.SetInput(polydata) except AttributeError: glyphTensor.SetInputData(polydata) glyphTensor.SetSourceConnection(cubeSource.GetOutputPort()) glyphTensor.ColorGlyphsOn() # should not color all cubes independently ? glyphTensor.ThreeGlyphsOff() glyphTensor.ExtractEigenvaluesOff() glyphTensor.Update() # next is usual vtk code mapper = vtk.vtkPolyDataMapper() mapper.SetInputConnection(glyphTensor.GetOutputPort()) actor = vtk.vtkActor() actor.SetMapper(mapper) ren = vtk.vtkRenderer() ren.SetBackground(0.2, 0.5, 0.3) ren.AddActor(actor) renwin = vtk.vtkRenderWindow() renwin.AddRenderer(ren) iren = vtk.vtkRenderWindowInteractor() iren.SetInteractorStyle(vtk.vtkInteractorStyleTrackballCamera()) iren.SetRenderWindow(renwin) renwin.Render() iren.Initialize() renwin.Render() iren.Start()

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  • List of objects or parallel arrays of properties?

    - by Headcrab
    The question is, basically: what would be more preferable, both performance-wise and design-wise - to have a list of objects of a Python class or to have several lists of numerical properties? I am writing some sort of a scientific simulation which involves a rather large system of interacting particles. For simplicity, let's say we have a set of balls bouncing inside a box so each ball has a number of numerical properties, like x-y-z-coordinates, diameter, mass, velocity vector and so on. How to store the system better? Two major options I can think of are: to make a class "Ball" with those properties and some methods, then store a list of objects of the class, e. g. [b1, b2, b3, ...bn, ...], where for each bn we can access bn.x, bn.y, bn.mass and so on; to make an array of numbers for each property, then for each i-th "ball" we can access it's 'x' coordinate as xs[i], 'y' coordinate as ys[i], 'mass' as masses[i] and so on; To me it seems that the first option represents a better design. The second option looks somewhat uglier, but might be better in terms of performance, and it could be easier to use it with numpy and scipy, which I try to use as much as I can. I am still not sure if Python will be fast enough, so it may be necessary to rewrite it in C++ or something, after initial prototyping in Python. Would the choice of data representation be different for C/C++? What about a hybrid approach, e.g. Python with C++ extension?

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  • Purge complete Python installation on OS X

    - by Konrad Rudolph
    I’m working on a recently-upgraded OS X Snow Leopard and MacPorts and I’m running into problems at every corner. The first problem is the sheer number of installed Python versions: altogether, there are four: 2.5, 2.6 and 3.0 in /Library/Frameworks/Python.framework 2.6 in /opt/local/Library/Frameworks/Python.framework/ (MacPorts installation) So there are at least two useless/redundant versions: 2.5 and the redundant 2.6. Additionally, the pre-installed Python is giving me severe problems because some of the pre-installed libraries (in particular, scipy, numpy and matplotlib) don’t work properly. I am sorely tempted to purge the complete /Library/Frameworks/Python.framework path, as well as the MacPorts Python installation. After that, I’ll start from a clean slate by installing a properly configured Python, e.g. that from Enthought. Am I running headlong into trouble? Or is this a sane undertaking? (In particular, I need a working Python in the next few days and if I end up with a non-working Python this would be a catastrophe of medium proportions. On the other hand, some features I need from matplotlib aren’t working now.)

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  • Python on Mac: Fink? MacPorts? Builtin? Homebrew? Binary installer?

    - by BastiBechtold
    For the last few days, I have been trying to use Python for some audio development. The thing is, Mac OSX does not handle uninstalling stuff well. Actually, there is no way to uninstall anything. Once it is on your system, you better pray that it didn't do any funny stuff. Hence, I don't really want to rely on installer packages for Python. So I turn to Homebrew and install Python using Homebrew. Works fabulously. Using pip, Numpy, SciPy, Matplotlib were no (big) problem, either. Now I want to play audio. There is a host of different packages out there, but pip does not seem willing to install any. But, there is a binary distribution for PyGame, which I guess should work with the built-in Python. Hence my question: What would you do? Would you just install the binary distributions and hope that they interoperate well and never need uninstalling? Would you hack your way through whichever package control management system you prefer and deal with its problems? Something else?

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  • Helping install mrcwa and solve problems with f2py in Ubuntu 14.04 LTS

    - by user288160
    I am sorry if this is the wrong section but I am starting to get desperate, please someone help me... I need to install the program mrcwa-20080820 (sourceforge.net/projects/mrcwa/) because a summer project that I am involved. I need to use it together with anaconda (store.continuum.io/cshop/anaconda/), I already installed Anaconda and apparently it is working. When I type: conda --version I got the expected answer. conda 3.5.2 If I tried to import numpy or scipy with python or simple type f2py there are no errors. So far so good. But when I tried to install this program sudo python setup.py install I got these errors: running install running build sh: 1: f2py: not found cp: cannot stat ‘mrcwaf.so’: No such file or directory running build_py running install_lib running install_egg_info Removing /usr/local/lib/python2.7/dist-packages/mrcwa-20080820.egg-info Writing /usr/local/lib/python2.7/dist-packages/mrcwa-20080820.egg-info Obs: I am trying to use intel fortran 64-bits and Ubuntu 14.04 LTS. So I was checking f2py and tried to execute the program hello world f2py -c -m hello hello.f from here: cens.ioc.ee/projects/f2py2e/index.html#usage and I had some problems too: running build running config_cc unifing config_cc, config, build_clib, build_ext, build commands --compiler options running config_fc unifing config_fc, config, build_clib, build_ext, build commands --fcompiler options running build_src build_src building extension "hello" sources f2py options: [] f2py:> /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/hellomodule.c creating /tmp/tmpf8P4Y3/src.linux-x86_64-2.7 Reading fortran codes... Reading file 'hello.f' (format:fix,strict) Post-processing... Block: hello Block: foo Post-processing (stage 2)... Building modules... Building module "hello"... Constructing wrapper function "foo"... foo(a) Wrote C/API module "hello" to file "/tmp/tmpf8P4Y3/src.linux-x86_64-2.7 /hellomodule.c" adding '/tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.c' to sources. adding '/tmp/tmpf8P4Y3/src.linux-x86_64-2.7' to include_dirs. copying /home/felipe/.local/lib/python2.7/site-packages/numpy/f2py/src/fortranobject.c -> /tmp/tmpf8P4Y3/src.linux-x86_64-2.7 copying /home/felipe/.local/lib/python2.7/site-packages/numpy/f2py/src/fortranobject.h -> /tmp/tmpf8P4Y3/src.linux-x86_64-2.7 build_src: building npy-pkg config files running build_ext customize UnixCCompiler customize UnixCCompiler using build_ext customize Gnu95FCompiler Could not locate executable gfortran Could not locate executable f95 customize IntelFCompiler Found executable /opt/intel/composer_xe_2013_sp1.3.174/bin/intel64/ifort customize LaheyFCompiler Could not locate executable lf95 customize PGroupFCompiler Could not locate executable pgfortran customize AbsoftFCompiler Could not locate executable f90 Could not locate executable f77 customize NAGFCompiler customize VastFCompiler customize CompaqFCompiler Could not locate executable fort customize IntelItaniumFCompiler customize IntelEM64TFCompiler customize IntelEM64TFCompiler customize IntelEM64TFCompiler using build_ext building 'hello' extension compiling C sources C compiler: gcc -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -Wstrict-prototypes -fPIC creating /tmp/tmpf8P4Y3/tmp creating /tmp/tmpf8P4Y3/tmp/tmpf8P4Y3 creating /tmp/tmpf8P4Y3/tmp/tmpf8P4Y3/src.linux-x86_64-2.7 compile options: '-I/tmp/tmpf8P4Y3/src.linux-x86_64-2.7 -I/home/felipe/.local/lib/python2.7/site-packages/numpy/core/include -I/home/felipe/anaconda/include/python2.7 -c' gcc: /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/hellomodule.c In file included from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1761:0, from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:17, from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:4, from /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.h:13, from /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/hellomodule.c:17: /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp] #warning "Using deprecated NumPy API, disable it by " \ ^ gcc: /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.c In file included from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/ndarraytypes.h:1761:0, from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/ndarrayobject.h:17, from /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/arrayobject.h:4, from /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.h:13, from /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.c:2: /home/felipe/.local/lib/python2.7/site-packages/numpy/core/include/numpy/npy_1_7_deprecated_api.h:15:2: warning: #warning "Using deprecated NumPy API, disable it by " "#defining NPY_NO_DEPRECATED_API NPY_1_7_API_VERSION" [-Wcpp] #warning "Using deprecated NumPy API, disable it by " \ ^ compiling Fortran sources Fortran f77 compiler: /opt/intel/composer_xe_2013_sp1.3.174/bin/intel64/ifort -FI -fPIC -xhost -openmp -fp-model strict Fortran f90 compiler: /opt/intel/composer_xe_2013_sp1.3.174/bin/intel64/ifort -FR -fPIC -xhost -openmp -fp-model strict Fortran fix compiler: /opt/intel/composer_xe_2013_sp1.3.174/bin/intel64/ifort -FI -fPIC -xhost -openmp -fp-model strict compile options: '-I/tmp/tmpf8P4Y3/src.linux-x86_64-2.7 -I/home/felipe/.local /lib/python2.7/site-packages/numpy/core/include -I/home/felipe/anaconda/include/python2.7 -c' ifort:f77: hello.f /opt/intel/composer_xe_2013_sp1.3.174/bin/intel64/ifort -shared -shared -nofor_main /tmp/tmpf8P4Y3/tmp/tmpf8P4Y3/src.linux-x86_64-2.7/hellomodule.o /tmp/tmpf8P4Y3 /tmp/tmpf8P4Y3/src.linux-x86_64-2.7/fortranobject.o /tmp/tmpf8P4Y3/hello.o -L/home/felipe /anaconda/lib -lpython2.7 -o ./hello.so Removing build directory /tmp/tmpf8P4Y3 Please help me I am new in ubuntu and python. I really need this program, my advisor is waiting an answer. Thank you very much, Felipe Oliveira.

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  • matplotlib and python multithread file processing

    - by Napseis
    I have a large number of files to process. I have written a script that get, sort and plot the datas I want. So far, so good. I have tested it and it gives the desired result. Then I wanted to do this using multithreading. I have looked into the doc and examples on the internet, and using one thread in my program works fine. But when I use more, at some point I get random matplotlib error, and I suspect some conflict there, even though I use a function with names for the plots, and iI can't see where the problem could be. Here is the whole script should you need more comment, i'll add them. Thank you. #!/usr/bin/python import matplotlib matplotlib.use('GTKAgg') import numpy as np from scipy.interpolate import griddata import matplotlib.pyplot as plt import matplotlib.colors as mcl from matplotlib import rc #for latex import time as tm import sys import threading import Queue #queue in 3.2 and Queue in 2.7 ! import pdb #the debugger rc('text', usetex=True)#for latex map=0 #initialize the map index. It will be use to index the array like this: array[map,[x,y]] time=np.zeros(1) #an array to store the time middle_h=np.zeros((0,3)) #x phi c #for the middle of the box current_file=open("single_void_cyl_periodic_phi_c_middle_h_out",'r') for line in current_file: if line.startswith('# === time'): map+=1 np.append(time,[float(line.strip('# === time '))]) elif line.startswith('#'): pass else: v=np.fromstring(line,dtype=float,sep=' ') middle_h=np.vstack( (middle_h,v[[1,3,4]]) ) current_file.close() middle_h=middle_h.reshape((map,-1,3)) #3d array: map, x, phi,c ##### def load_and_plot(): #will load a map file, and plot it along with the corresponding profile loaded before while not exit_flag: print("fecthing work ...") #try: if not tasks_queue.empty(): map_index=tasks_queue.get() print("----> working on map: %s" %map_index) x,y,zp=np.loadtxt("single_void_cyl_growth_periodic_post_map_"+str(map_index),unpack=True, usecols=[1, 2,3]) for i,el in enumerate(zp): if el<0.: zp[i]=0. xv=np.unique(x) yv=np.unique(y) X,Y= np.meshgrid(xv,yv) Z = griddata((x, y), zp, (X, Y),method='nearest') figure=plt.figure(num=map_index,figsize=(14, 8)) ax1=plt.subplot2grid((2,2),(0,0)) ax1.plot(middle_h[map_index,:,0],middle_h[map_index,:,1],'*b') ax1.grid(True) ax1.axis([-15, 15, 0, 1]) ax1.set_title('Profiles') ax1.set_ylabel(r'$\phi$') ax1.set_xlabel('x') ax2=plt.subplot2grid((2,2),(1,0)) ax2.plot(middle_h[map_index,:,0],middle_h[map_index,:,2],'*r') ax2.grid(True) ax2.axis([-15, 15, 0, 1]) ax2.set_ylabel('c') ax2.set_xlabel('x') ax3=plt.subplot2grid((2,2),(0,1),rowspan=2,aspect='equal') sub_contour=ax3.contourf(X,Y,Z,np.linspace(0,1,11),vmin=0.) figure.colorbar(sub_contour,ax=ax3) figure.savefig('single_void_cyl_'+str(map_index)+'.png') plt.close(map_index) tasks_queue.task_done() else: print("nothing left to do, other threads finishing,sleeping 2 seconds...") tm.sleep(2) # except: # print("failed this time: %s" %map_index+". Sleeping 2 seconds") # tm.sleep(2) ##### exit_flag=0 nb_threads=2 tasks_queue=Queue.Queue() threads_list=[] jobs=list(range(map)) #each job is composed of a map print("inserting jobs in the queue...") for job in jobs: tasks_queue.put(job) print("done") #launch the threads for i in range(nb_threads): working_bee=threading.Thread(target=load_and_plot) working_bee.daemon=True print("starting thread "+str(i)+' ...') threads_list.append(working_bee) working_bee.start() #wait for all tasks to be treated tasks_queue.join() #flip the flag, so the threads know it's time to stop exit_flag=1 for t in threads_list: print("waiting for threads %s to stop..."%t) t.join() print("all threads stopped")

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