Mailman 3 November 2008 - SciPy-User

Installing on Ubuntu with mkl 10.0.2: libimf.so not found
by Anand Patil 04 Nov '08

04 Nov '08

Hi all, Sorry to post again for help installing. I recently got numpy installed with mkl 10.0.2. I pared the site.cfg file down to just [mkl] library_dirs = /opt/intel/mkl/10.0.2.018/lib/em64t lapack_libs = mkl, mkl_lapack mkl_libs = mkl, guide and everything seems to work fine. Now I'm trying to install scipy with the Intel compilers. The build went fine, but when I go to do python setup.py install I get: /working_copies/scipy$ sudo python setup.py install [sudo] password for anand: Traceback (most recent call last): File "setup.py", line 92, in <module> setup_package() File "setup.py", line 63, in setup_package from numpy.distutils.core import setup File "/usr/lib/python2.5/site-packages/numpy/__init__.py", line 130, in <module> import add_newdocs File "/usr/lib/python2.5/site-packages/numpy/add_newdocs.py", line 9, in <module> from lib import add_newdoc File "/usr/lib/python2.5/site-packages/numpy/lib/__init__.py", line 152, in <module> from type_check import * File "/usr/lib/python2.5/site-packages/numpy/lib/type_check.py", line 8, in <module> import numpy.core.numeric as _nx File "/usr/lib/python2.5/site-packages/numpy/core/__init__.py", line 5, in <module> import multiarray ImportError: libimf.so: cannot open shared object file: No such file or directory I'm having a hard time debugging this because first, I can import setup from numpy.distutils.core directly in Python: /working_copies/scipy$ python Python 2.5.2 (r252:60911, Jul 31 2008, 17:31:22) [GCC 4.2.3 (Ubuntu 4.2.3-2ubuntu7)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> from numpy.distutils.core import setup >>> Second, libimf.so is on my LD_LIBRARY_PATH; /working_copies/scipy$ echo $LD_LIBRARY_PATH :/usr/lib64:/lib64:/usr/local/lib64:/usr/lib:/usr/local/lib:/lib:/opt/intel/fce/10.1.018/lib:/opt/intel/ipp/ 5.3.4.080/em64t/sharedlib:/opt/intel/cce/10.1.018/lib:/opt/intel/mkl/10.0.2.018/lib/em64t /working_copies/scipy$ ls /opt/intel/ipp/5.3.4.080/em64t/sharedlib/libimf.so /opt/intel/ipp/5.3.4.080/em64t/sharedlib/libimf.so Has anyone seen anything like this before? Thanks, ANand

3 6

Problem with mkl 10.0.2: undefined symbol: mkl_blas_xdgemm_1_thr_htn
by Anand Patil 03 Nov '08

03 Nov '08

Hi all, I'm trying to build numpy from svn on Ubuntu with mkl 10.0.2.018, as it looks like mkl 10.0.3 and above won't work with numpy (I got the i_free error). I get the following problem, which I can't find on Google: In [1]: from numpy import * In [2]: A=asmatrix(eye(6000)) In [3]: A=A*A /opt/intel/mkl/10.0.2.018/lib/em64t/libmkl_mc.so: undefined symbol: mkl_blas_xdgemm_1_thr_htn /opt/intel/mkl/10.0.2.018/lib/em64t/libmkl_mc.so: undefined symbol: mkl_blas_xdgemm_1_thr_htn More confusingly, I can't find where the symbol is defined: $ nm /opt/intel/mkl/10.0.2.018/lib/em64t/*.so | grep mkl_blas_xdgemm_1_thr_htn nm: /opt/intel/mkl/10.0.2.018/lib/em64t/libmkl.so: File format not recognized $ Anyone know how I can fix this? Thanks, Anand

2 7

documentation on scipy.interpolate
by Timmie 03 Nov '08

03 Nov '08

Hello, is there a documentation on the interpolation functions included within scipy? I am particular interested in the kinds of interpolation available in http://www.scipy.org/doc/api_docs/SciPy.interpolate.interpolate.interp1d.ht… The same functionality is used by the timeseries scikit: http://pytseries.sourceforge.net/lib/interpolation.html#scikits.timeseries.… What does cubic, quintic mean? Kind regards,

2 1

interp1d problem
by Ben Webber 03 Nov '08

03 Nov '08

Hi, In CDAT I have been trying to use the interp1d class from the scipy.interpolate package to interpolate 3-dimensional oceanographic data along the time axis using cubic splines. This works fine for 1 or 2 dimensional data but fails for 3 dimensional data. However, using linear interpolation works no matter what the dimensions. I have tried to simplify the problem as much as possible and have created the following simplified script: import scipy from scipy.interpolate import interp1d test_array = [[[2,6],[10,7]],[[4,8],[12,9]],[[2,6],[10,7]],[[4,8],[12,9]]] test_array = scipy.array(test_array) test_axis = scipy.array(range(0,31,10)) myInterp = interp1d(test_axis,test_array,kind='cubic',axis = 0) #-----------------fails here---------------------- new_axis = scipy.array(range(0,31)) new_data = myInterp(new_axis) If kind is specified as 'linear' this script works. However, with kind as 'cubic', I get the following error: Traceback (most recent call last): File "cubic_interp.py", line 11, in <module> myInterp = interp1d(timeax_array,theta_array,kind = 'cubic',axis = 0) File "/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py", line 235, in __init__ self._spline = splmake(x,oriented_y,order=order) File "/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py", line 697, in splmake coefs = func(xk, yk, order, conds, B) File "/cvos/apps/CDAT-5.0.b1/lib/python2.5/site-packages/scipy/interpolate/interpolate.py", line 431, in _find_smoothest return dot(tmp, yk) ValueError: objects are not aligned The shape of the array is (4,2,2). The time axis is length 4, so it should work. Can anybody explain this error? Cheers, Ben Webber

2 1

f2py "Segmentation fault"-revisited, please help
by Kimberly Artita 03 Nov '08

03 Nov '08

Hi, Can someone please tell me why I keep getting a segmentation fault? my fortran script (gfortran_test.f90): subroutine readin_test implicit none character(len=4) :: title (60) character (len=13) :: bigsub, sbsout, rchout, rsvout, lwqout, wtrout open (2,file="gfortran.txt", delim='none') print *, "title" read (2,5100) title print *, title read (2,5000) bigsub, sbsout, rchout, rsvout, lwqout, wtrout print *, "bigsub, sbsout, rchout, rsvout, lwqout, wtrout" print *, bigsub, sbsout, rchout, rsvout, lwqout, wtrout close(2) 5100 format (20a4) 5000 format (6a) end subroutine readin_test my python script (gfortran_test.py): import gfortran_test gfortran_test.readin_test() my text file (gfortran.txt): General Input/Output section (file.cio): Thu Mar 13 17:32:19 2008 AVSWAT2000 - SWAT interface MDL basins.bsb basins.sbs basins.rch basins.rsv basins.lqo basins.wtr using this version of gfortran: i686-pc-linux-gnu-4.1.2 with either numpy-1.0.4-r2 or numpy-1.2.0 I can compile gfortran_test.f90 as a standalone program and it works! BUT, when I call it as a subroutine from python using f2py, it fails! I type: f2py --fcompiler=gfortran -c -m gfortran_test gfortran_test.f90 Why?????? -- Kimberly S. Artita PhD Intern, CDM Graduate Student, Engineering Science Southern Illinois University Carbondale Carbondale, Illinois 62901-6603 (618)-528-0349 e-mail: kartita(a)gmail.com, kartita(a)siu.edu web: http://civil.engr.siu.edu/GraduateStudents/artita/index.html

3 4

odeint parameter
by Nils Wagner 03 Nov '08

03 Nov '08

Hi all, I have a question wrt. odeint(func, y0, t, args=(), Dfun=None, col_deriv=0, full_output=0, ml=None, mu=None, rtol=None, atol=None, tcrit=None, h0=0.0, hmax=0.0, hmin=0.0, ixpr=0, mxstep=0, mxhn il=0, mxordn=12, mxords=5, printmessg=0) h0 : float, (0: solver-determined) The step size to be attempted on the first step. hmax : float, (0: solver-determined) The maximum absolute step size allowed. hmin : float, (0: solver-determined) The minimum absolute step size allowed. Is it really useful to start with the default values h0=0.0, hmax= 0.0 and hmin=0.0 ? Nils

2 1

guassian_kde and kernel regression
by Frank Lagor 02 Nov '08

02 Nov '08

This question is probably for Robert Kern, because I believe the he wrote the gaussian_kde class in scipy.stats.kde, however I would very much appreciate a response from anyone else who could help. My question is: Is there currently any way to perform weighted kernel density estimation using the gaussian_kde class? If not, what needs to be done, and how do I get started? Just for clarity sake-- by weighted KDE I mean that I have more than just the distribution of points for the density estimate. I also have an associated probability with each point. In this case, I believe it becomes a regression problem and I think is referred to as kernel regression. I would very much like to use the class to perform both KDE and wKDE. Thanks in advance, Frank

3 3

[ Python(x,y) ] New release : 2.1.4
by Pierre Raybaut 01 Nov '08

01 Nov '08

Hi all, Release 2.1.4 is now available on http://www.pythonxy.com. (Full Edition, Basic Edition, Light Edition, Custom Edition and Update) Changes history Version 2.1.4 (11-01-2008) * Added: o ReportLab 2.2, the PDF generation library o Windows explorer integration: added a "Run in interactive mode" (python -i) option on Python files contextual menu * Updated: o The *-components listed below are not included in Python(x,y) Update 2.1.4 because of the huge size of this update installer which is very close to the Google Code per-file size limit (100MB). Even though these updates are quite minor, note that you can download them individually on here. o NumPy 1.2.1 o SciPy 0.6.0.2 (minor update regarding deprecation warnings with NumPy 1.2.x) o matplotlib 0.98.3.3 (new 660-pages PDF documentation) o Enthought Tool Suite 3.0.2.3 o VTK 5.2.0.4 o *ITK 3.8.0.2 o *wxPython 2.8.9.1 o MDP 2.4 o PySQlite 2.5.0 o *Eclipse 3.4.1 o Pydev 1.3.23 o CDT 5.0.1 o xy 1.0.9 o Console 2.0.140.6 o Notepad++ 5.0.3.5 Regards, Pierre Raybaut

1 0