Mailman 3 October 2007 - SciPy-User

Help required regding Eigenvectors
by Sudheer Phani March 14, 2022

March 14, 2022

Hello All, I have been encountering some strange problems with the calculation of eigen vectors using python. The problem is with the sign of the eigen vectors calculated. On Very few occasions the eigen vectors calculated using python have an opposite sign than the actual eigenvectors, though the magnitude is correct. Can any one of you plz help me in this regard and suggest me some solution if you have encoutered similar problems . Any help in this regd is appreciated Thanks in Advace regds Sudheer

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3D plotting
by Robert Cimrman Sept. 10, 2009

Sept. 10, 2009

Hi, I need to do some simple 3D plots, so I tried the two Cookbook recipes (xplt, mplot3d) and failed: * xplt: does not work when using a custom installation directory such as python setup.py install --root=/home/share/software apparently the gistdata directory path is wrong: gist.error: failed to create drawing -- Gist work.gs style sheet missing * mplot3d: does not work with my version of matplotlib (0.80). I have made the changes mentioned in the Cookbook to no avail. (Axes.__init__() args apparently changed, as well as some other matplotlib object attributes) Any ideas? mplot3d looks great, I would really like to use it! thanks, r.

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Is numpy's argsort lying about its numpy.int32 types?
by Rob Clewley May 15, 2009

May 15, 2009

Hi, I'm having a problem comparing some types when using numpy's argsort. I'm using numpy 1.0.2. I can reproduce it simply: Python 2.4.4 (#71, Oct 18 2006, 08:34:43) [MSC v.1310 32 bit (Intel)] << snip >> In [1]: from numpy import argsort, sort, int32, array In [2]: x=array([1,3,2]) In [3]: aa=argsort(x) In [4]: as=sort(x) In [5]: type(aa[0]) Out[5]: <type 'numpy.int32'> In [6]: type(as[0]) Out[6]: <type 'numpy.int32'> In [7]: int32 Out[7]: <type 'numpy.int32'> In [8]: type(as[0])==int32 Out[8]: True In [9]: type(aa[0])==int32 Out[9]: False Any of the three indices in aa give me the same problem. Can someone explain if I should be doing this a different way, and if this is a bug?! Thanks, Rob

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sparse matrix dtype
by Robin Dec. 18, 2007

Dec. 18, 2007

Hi, I am trying to make a large sparse matrix - the values are all integers (in fact all non-zeros will be 1) so it would save me a lot of memory if I could use dtype=byte. However: In [23]: test=sparse.lil_matrix((10,10),dtype=byte) In [24]: test.dtype Out[24]: dtype('float64') Is this correct or is there something up here? Thanks Robin

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scipy.sparse problem
by Donald Fredkin Dec. 18, 2007

Dec. 18, 2007

I am unable to import the scipy.sparse module. When I try, here is what happens: C:\Documents and Settings\drf\My Documents>python Python 2.5.1 (r251:54863, Apr 18 2007, 08:51:08) [MSC v.1310 32 bit (Intel)] on win32 Type "help", "copyright", "credits" or "license" for more information. >>> import scipy >>> import scipy.sparse Traceback (most recent call last): File "<stdin>", line 1, in <module> File "C:\Python25\Lib\site-packages\scipy\sparse\__init__.py", line 5, in <module> from sparse import * File "C:\Python25\lib\site-packages\scipy\sparse\sparse.py", line 21, in <module> from scipy.sparse.sparsetools import cscmux, csrmux, \ ImportError: cannot import name cscmux >>> print scipy.__version__ 0.6.0 >>> Can anyone tell me how to fix this? It was OK with an earlier version of scipy. This is, by the way, on Windows XP. Thanks, Don -- Donald R. Fredkin drfredkin(a)ucsd.edu

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New example
by Anne Archibald Nov. 22, 2007

Nov. 22, 2007

Hi, I just wrote up a calculation using scipy: http://www.scipy.org/Trinity It's a fluid dynamics calculation describing the evolution of a spherical blast wave. There's some theory there, though I skimmed it as much as possible, and a reasonable calculation using scipy; specifically, it uses odeint, simps, and pylab. Is this a useful sort of tutorial/example? Do we want more things like this? Anne

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Specifying fortran compiler
by Adam Mercer Nov. 18, 2007

Nov. 18, 2007

Hi I'm trying to build SciPy on Mac OS 10.5 using gfortran from MacPorts gcc-4.2.2, which gets installed as gfortran-mp-4.2. When I build I get the following error: Command output: customize IbmFCompiler customize GnuFCompiler Could not locate executable g77 Could not locate executable f77 customize Gnu95FCompiler Could not locate executable gfortran Could not locate executable f95 customize G95FCompiler customize GnuFCompiler Could not locate executable g77 Could not locate executable f77 customize Gnu95FCompiler Could not locate executable gfortran Could not locate executable f95 customize NAGFCompiler customize NAGFCompiler using build_clib building 'dfftpack' library compiling Fortran sources Fortran f77 compiler: f95 -fixed -O4 -target=native Fortran f90 compiler: f95 -O4 -target=native Fortran fix compiler: f95 -fixed -O4 -target=native creating build/temp.macosx-10.3-i386-2.5 creating build/temp.macosx-10.3-i386-2.5/scipy creating build/temp.macosx-10.3-i386-2.5/scipy/fftpack creating build/temp.macosx-10.3-i386-2.5/scipy/fftpack/dfftpack compile options: '-c' f95:f77: scipy/fftpack/dfftpack/dcosqb.f sh: f95: command not found sh: f95: command not found error: Command "f95 -fixed -O4 -target=native -c -c scipy/fftpack/dfftpack/dcosqb.f -o build/temp.macosx-10.3-i386-2.5/scipy/fftpack/dfftpack/dcosqb.o" failed with exit status 127 >From this error it looks like SciPy is trying to use f95 as the fortran compiler executable, not gfortran-mp-4.2. Is there a way that I can specify which fortran compiler to use? Cheers Adam

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nullclines for nonlinear ODEs
by John Hunter Nov. 12, 2007

Nov. 12, 2007

In a workshop on scientific computing in python I ran with Andrew Straw last weekend at the Claremont Colleges, I presented a unit on ODEs, numerically integrating the Lotka-Volterra equations, drawing a direction field, plotting a trajectory in the phase plane, and plotting the nullclines. For the nullclines, I used matplotlib's contouring routine with levels=[0], but I was wondering if there was a better/more direct route. The example script is included below (and attached) import numpy as n import pylab as p import scipy.integrate as integrate def dr(r, f): return alpha*r - beta*r*f def df(r, f): return gamma*r*f - delta*f def derivs(state, t): """ Map the state variable [rabbits, foxes] to the derivitives [deltar, deltaf] at time t """ #print t, state r, f = state # rabbits and foxes deltar = dr(r, f) # change in rabbits deltaf = df(r, f) # change in foxes return deltar, deltaf alpha, delta = 1, .25 beta, gamma = .2, .05 # the initial population of rabbits and foxes r0 = 20 f0 = 10 t = n.arange(0.0, 100, 0.1) y0 = [r0, f0] # the initial [rabbits, foxes] state vector y = integrate.odeint(derivs, y0, t) r = y[:,0] # extract the rabbits vector f = y[:,1] # extract the foxes vector p.figure() p.plot(t, r, label='rabbits') p.plot(t, f, label='foxes') p.xlabel('time (years)') p.ylabel('population') p.title('population trajectories') p.grid() p.legend() p.savefig('lotka_volterra.png', dpi=150) p.savefig('lotka_volterra.eps') p.figure() p.plot(r, f) p.xlabel('rabbits') p.ylabel('foxes') p.title('phase plane') # make a direction field plot with quiver rmax = 1.1 * r.max() fmax = 1.1 * f.max() R, F = n.meshgrid(n.arange(-1, rmax), n.arange(-1, fmax)) dR = dr(R, F) dF = df(R, F) p.quiver(R, F, dR, dF) R, F = n.meshgrid(n.arange(-1, rmax, .1), n.arange(-1, fmax, .1)) dR = dr(R, F) dF = df(R, F) p.contour(R, F, dR, levels=[0], linewidths=3, colors='black') p.contour(R, F, dF, levels=[0], linewidths=3, colors='black') p.ylabel('foxes') p.title('trajectory, direction field and null clines') p.savefig('lotka_volterra_pplane.png', dpi=150) p.savefig('lotka_volterra_pplane.eps') p.show()

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Scipy + Vision = LabView ?
by Stef Mientki Nov. 6, 2007

Nov. 6, 2007

hello, I found this demo (5 min) of Vision today http://www.osc.edu/~unpingco/Tutorial1.html If we combine this with Scipy, we've an almost complete replacement of LabView. Or am I dreaming ? cheers, Stef Mientki

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Re: [SciPy-user] Subject: Re: Scientific Python publications
by Nicolas Pettiaux Nov. 4, 2007

Nov. 4, 2007

2007/10/28, Tony Mannucci <Tony.Mannucci(a)jpl.nasa.gov>: > >From: jaropis <jaropis(a)gazeta.pl> > >I use Python a lot - for example this paper: > > > >http://www.iop.org/EJ/abstract/0967-3334/28/3/005 > > > >has an animation done in SciPy+pylab, and all the calculations are in > >Python. I give Matlab code for the same calculations in an appendix, but > >they were originally done in SciPy and then translated to Matlab. Maybe Jarek could send us or post on his website a copy of a previous version of the paper. These are not covered usually by the (abusive) copyright of the Journal THanks, Nicolas -- Nicolas Pettiaux - email: nicolas.pettiaux(a)ael.be Utiliser des formats ouverts et des logiciels libres - http://www.passeralinux.org. Pour la bureautique, les seuls formats ISO sont ceux de http://fr.openoffice.org

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