Mailman 3 March 2011 - SciPy-User

Help required regding Eigenvectors
by Sudheer Phani 14 Mar '22

14 Mar '22

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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Linear interpolation in 3D
by Hardock, Andreas 13 Jun '13

13 Jun '13

Hi, I'm trying to interpolate a 3D data (from the pic attached) with the interp2d command. What I have, are three vectors f, z, A (x, y, z respectively, A is the percentage data given on the isolines). I first put the f and z in a meshgrid and afterwards in the griddata to get a 3D-grid then started the interpolateion. I plotted the the data after gridding, and I observed that almost all nodes are ignored. Do you have any idea how to prepare data to the interp2d command? Don't hesitate to suggest any other solution. my code so far is: import numpy as np from mpl_toolkits.mplot3d import axes3d from scipy.interpolate import interp2d import matplotlib.pyplot as plt from matplotlib import mlab plt.clf() fig = plt.figure(1) ax = axes3d.Axes3D(fig) #read data (ff,ZZ,A,a) = np.loadtxt("accuracy-map.txt", unpack=True) f=np.log10(ff) z=np.log10(ZZ) ##grid everything fgrid, zgrid=np.meshgrid(f,z) #define grid ef=np.linspace(min(f), max(f), len(f)) ez=np.linspace(min(z), max(z), len(f)) Agrid=mlab.griddata(f,z,A, ef,ez) int2d=interp2d(fgrid, zgrid, Agrid, kind='linear') ax.plot(f, z, A, 'ok', markerfacecolor='w') ax.plot_surface(fgrid, zgrid, Agrid) ax.set_xlim3d((min(f), max(f))) ax.set_ylim3d(min(z), max(z)) ax.set_zlim3d(0,100) plt.show()

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pupynere/scipy.io.netcdf
by Ryan May 06 Mar '13

06 Mar '13

Hi, Anyone know if pupynere (a version of which is in scipy.io.netcdf) supports writing files with 64-bit offsets? This allows writing files larger than 2GB. Ryan -- Ryan May Graduate Research Assistant School of Meteorology University of Oklahoma

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Reading TDM/TDMS Files with scipy
by Nils Wagner 20 Feb '13

20 Feb '13

Hi all, Is it possible to read TDM/TDMS files with scipy ? I found a tool for Matlab http://zone.ni.com/devzone/cda/epd/p/id/5957 Nils

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Request for usage examples on scipy.stats.rv_continuous and scipy.ndimage.grey_dilate(structure)
by Christoph Deil 05 Dec '12

05 Dec '12

Hi, I am having some trouble figuring out how to use the following two aspects of scipy: 1) How can I create a random distribution given by some python formula, e.g. pdf(x) = x**2 in the range x = 1 to 2. The example given in the rv_continuous docstring doesn't work for me: In [1]: import matplotlib.pyplot as plt In [2]: numargs = generic.numargs AttributeError: type object 'numpy.generic' has no attribute 'numargs' Is it also possible to use rv_continuous for multidimensional distributions, say pdf(x,y)=x*y in the range x = 1 to 2 and y = 0 to 3? Or for pdfs that are just given numerically on a grid (say as the result of a gaussian_kde() ), not by a python function? It would be nice if someone could add a few examples that show rv_continuous usage to the docstring or tutorial. 2) How to use the 'structure' argument of scipy.ndimage.grey_dilate() correctly? There are some explanations at http://docs.scipy.org/doc/scipy/reference/tutorial/ndimage.html but I think they are inconsistent with the implementation: -------------------------------------------------------------- In [98]: a = zeros((7,7)); a[3,3]=1; a Out[98]: array([[ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 1., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.]]) In [100]: s = generate_binary_structure(2,2); s Out[100]: array([[ True, True, True], [ True, True, True], [ True, True, True]], dtype=bool) In [101]: grey_dilation(a,size=(3,3)) Out[101]: array([[ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.]]) In [102]: grey_dilation(a,size=(3,3),structure=s) Out[102]: array([[ 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 2., 2., 2., 1., 1.], [ 1., 1., 2., 2., 2., 1., 1.], [ 1., 1., 2., 2., 2., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1.], [ 1., 1., 1., 1., 1., 1., 1.]]) In [103]: grey_dilation(a,structure=s) --------------------------------------------------------------------------- TypeError Traceback (most recent call last) /Users/deil/<ipython console> in <module>() /opt/local/Library/Frameworks/Python.framework/Versions/2.6/lib/python2.6/site-packages/scipy/ndimage/morphology.pyc in grey_dilation(input, size, footprint, structure, output, mode, cval, origin) 354 sz = footprint.shape[ii] 355 else: --> 356 sz = size[ii] 357 if not sz & 1: 358 origin[ii] -= 1 TypeError: 'NoneType' object is unsubscriptable In [104]: grey_dilation(a,footprint=s) Out[104]: array([[ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 1., 1., 1., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.], [ 0., 0., 0., 0., 0., 0., 0.]]) -------------------------------------------------------------- Why doesn't grey_dilation(a,structure=s) work? Why doesn't grey_dilation(a,size=(3,3),structure=s) give the same result as grey_dilation(a,size=(3,3),footprint=s)? I am running on numpy version 1.4.0 and scipy version 0.7.1 Thanks! --Christoph

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Installing issue with python 2.7, numpy 1.5.0b1 in my Mac
by Markus Hubig 05 Sep '12

05 Sep '12

Hi @all, maybe this is a known issue but I didn't find any useful information out there. When I try to install scipy-0.8.0 with pip I get this strange error about missing files ... File "/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/distutils/npy_pkg_config.py", line 276, in parse_config raise PkgNotFound("Could not find file(s) %s" % str(filenames)) numpy.distutils.npy_pkg_config.PkgNotFound: Could not find file(s) ['/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/core/lib/npy-pkg-config/npymath.ini'] The complete error can be found here: http://gist.github.com/527697 Is there a known solution for this? Any help would be nice ... - Markus -- Can't read my mail? Just don't hold it that way!

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Re: [SciPy-User] sinc interpolation
by Travis Oliphant 07 Jun '12

07 Jun '12

On Nov 20, 2009, at 2:26 PM, David Trem wrote: > Hello, > > Is sinc interpolation available in Scipy ? Yes, use scipy.signal.resample which uses a Fourier method to downsample or upsample a signal: from scipy.signal import resample from numpy import r_, sin from pylab import plot x = r_[0:10] y = sin(x) yy = resample(x, 100) # This is a bit tricky to get the x-samples right xx = r_[0:10:101j][:-1] plot(x,y,'ro', xx, yy) -Travis

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inverse function of a spline
by josef.pktd＠gmail.com 02 Oct '11

02 Oct '11

I have a function y = f(x) which is monotonically increasing (a cumulative distribution function) f is defined by piecewise polynomial interpolation, an interpolating spline on some points I would like to get the inverse function (ppf) x = f^{-1} (y) if the spline is of higher order than linear In the linear case it's trivial, because the inverse function is also just a piecewise linear interpolation. If I have a cubic spline, or any other smooth interpolator in scipy, is there a way to get the inverse function directly? I don't know much about general properties of splines, and would appreciate any hints, so I can avoid numerical inversion (fsolve or similar) Thanks, Josef

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scikits timeseries tofile
by Gar Brown 28 Sep '11

28 Sep '11

Hi All, While trying to write a timeseries object to file I the following error: File "C:\Python27\lib\site-packages\scikits\timeseries\tseries.py", line 1527, in tofile return scipy.io.write_array(fileobject, tmpfiller, **optpars) AttributeError: 'module' object has no attribute 'write_array' I noticed that the scipy.io.write_array function has been deprecated for some time, is there a fix or workaround for avoiding this error. I really like the time series functionality of scikits.timeseries timeseries version: __author__ = "Pierre GF Gerard-Marchant & Matt Knox ($Author: mattknox_ca $)" __revision__ = "$Revision: 2213 $" __date__ = '$Date: 2009-08-23 12:43:40 -0400 (Sun, 23 Aug 2009) $'

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computing local extrema
by fred 16 Sep '11

16 Sep '11

Hi, I would like to compute local extrema of an array (2D/3D), ie get a list of points (coords + value). How could I do this? Any hint? TIA. Cheers, -- Fred

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