Mailman 3 September 2010 - SciPy-User

Re: [SciPy-User] Error in scipy.ndimage documentation
by moscardi Sept. 20, 2010

Sept. 20, 2010

Nobody has tried to extend ndimage with C...? On Sep 10, 2010, at 7:18 PM, Matthieu Brucher wrote: > Hi, > > The following function is referenced on the scipy.ndimage page > (http://docs.scipy.org/doc/scipy/reference/tutorial/ndimage.html#ndimage-cca…) > : > > static int > _shift_function(int *output_coordinates, double* input_coordinates, > int output_rank, int input_rank, void *callback_data) > { > int ii; > /* get the shift from the callback data pointer: */ > double shift = *(double*)callback_data; > /* calculate the coordinates: */ > for(ii = 0; ii < irank; ii++) > icoor[ii] = ocoor[ii] - shift; > /* return OK status: */ > return 1; > } > > It obviously cannot be compiled (irank -> input_rank, icoor -> > input_coordinates, ocoor -> output_coordinates) > > Matthieu > -- > Information System Engineer, Ph.D. > Blog: http://matt.eifelle.com > LinkedIn: http://www.linkedin.com/in/matthieubrucher > _______________________________________________ > SciPy-Dev mailing list > SciPy-Dev(a)scipy.org > http://mail.scipy.org/mailman/listinfo/scipy-dev Eric MOSCARDI INRIA - Virtual Plants CIRAD, Avenue Agropolis 34398 Montpellier Cedex 5, France 04 67 61 58 00 (ask number 60 09) email : eric.moscardi(a)sophia.inria.fr

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performant envelope follower
by henry lindsay smith Sept. 17, 2010

Sept. 17, 2010

I have the following code backported from C envelope follower and converted into python code (using numpy arrays) for i in range(len(self.m_signal)): envIn=np.abs(self.m_signal[i]**2)#square for energy if(self.envelope < envIn): self.envelope *= self.m_ga self.envelope +=(1-self.m_ga)*envIn else: self.envelope *= self.m_gr self.envelope +=(1-self.m_gr)*envIn self.sigEnv[i]=self.envelope it runs but slowly as I am iterating through the whole signal which is pretty slow in python (but super fast in C) Can anyone think of a more efficient way to run this possibly as as a filtering operation? I need the same result as I'm going to port back into C at somepoint. thanks

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Re: [SciPy-User] weighted griddata
by Jonathan Stickel Sept. 17, 2010

Sept. 17, 2010

On 9/16/10 22:41 , scipy-user-request(a)scipy.org wrote: >> You may need to fiddle with the smoothing parameter `s=...` for >> > SmoothBivariateSpline. > I was using interpolate.SmoothBivariateSpline previously and had good > results when it worked, but I struggled with the smoothing parameter > for so long I had to put it down. I could not figure out how to > consistently calculate/estimate/predict a smoothing factor (from the > data) that was not too low (and never return) or too high (and give > blocky results). > > Is there a way to calculate an optimal smoothing factor from a data set? > I know your problem is 2-D, but for 1-D I have written the scikit "datasmooth" that implements smoothing by regularization and includes generalized cross validation for determining the optimal regularization parameter (aka smoothing factor): http://pypi.python.org/pypi/scikits.datasmooth/0.5 I know the method can be extended to 2-D, but I don't have a need or the time to do it myself. Jonathan

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ANN: new version of pylint (in fact, astng)
by David Douard Sept. 17, 2010

Sept. 17, 2010

Hi all, a few days ago, we (at Logilab) took time (well, Sylvain did) to fix a long outstanding bug in astng (which is the heart of pylint): http://www.logilab.org/ticket/23008 The result is that, at last, pylint can be used with numpy. Thank you Sylvain! So go and get the latest version of astng and enjoy pylint on your numpy-based projects! http://www.logilab.org/project/logilab-astng Regards, David

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optimization routines can not handle infinity values
by enrico avventi Sept. 16, 2010

Sept. 16, 2010

hello all, i am trying out some of the optimization routines for a problem of mine that is on the form: min f(x) s.t M(x) is positive semidefinite where f is strictly convex in the feasible region with compact sublevel sets, M is linear and takes value in some subspace of hermitian matrices. the problem is convex but the costraint can not be handled directly by any of the optimization routines in scipy. So i choose to change it to an uncostrained problem with objective function: f1(x) = f(x) for M(x) pos semi def f1(x) = Inf otherwise the problem is that it seems the routines can not handle the infinity values correctly. Some of the routines (fmin_cg comes to mind) wants to check the gradient at points where the objective function is infinite. Clearly in such cases the gradient is not defined - i.e the calculations fail - and the algorithm terminates. Others (like fmin_bfgs) strangely converge to a point where the objective is infinite despite the fact that the initial point was not. Do you have any suggestion to fix this problem? regards, Enrico

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Building problem - scipy/sparse/sparsetools/csr_wrap.cxx:2917: error: expected `)' before ‘PRIdPTR’
by Nicolau Werneck Sept. 15, 2010

Sept. 15, 2010

Hello, I am trying to build numpy and scipy for my newly built Python 2.7, and I am getting this error message that seems to be a classic problem happening again: compile options: '-I/usr/local/lib/python2.7/site-packages/numpy/core/include -I/usr/local/include/python2.7 -c' g++: scipy/sparse/sparsetools/csr_wrap.cxx scipy/sparse/sparsetools/csr_wrap.cxx: In function ‘int require_size(PyArrayObject*, npy_intp*, int)’: scipy/sparse/sparsetools/csr_wrap.cxx:2910: error: expected `)' before ‘PRIdPTR’ scipy/sparse/sparsetools/csr_wrap.cxx:2910: warning: spurious trailing ‘%’ in format scipy/sparse/sparsetools/csr_wrap.cxx:2910: warning: too many arguments for format scipy/sparse/sparsetools/csr_wrap.cxx:2917: error: expected `)' before ‘PRIdPTR’ scipy/sparse/sparsetools/csr_wrap.cxx:2917: warning: spurious trailing ‘%’ in format scipy/sparse/sparsetools/csr_wrap.cxx:2917: warning: too many arguments for format scipy/sparse/sparsetools/csr_wrap.cxx: In function ‘int require_size(PyArrayObject*, npy_intp*, int)’: scipy/sparse/sparsetools/csr_wrap.cxx:2910: error: expected `)' before ‘PRIdPTR’ scipy/sparse/sparsetools/csr_wrap.cxx:2910: warning: spurious trailing ‘%’ in format scipy/sparse/sparsetools/csr_wrap.cxx:2910: warning: too many arguments for format scipy/sparse/sparsetools/csr_wrap.cxx:2917: error: expected `)' before ‘PRIdPTR’ scipy/sparse/sparsetools/csr_wrap.cxx:2917: warning: spurious trailing ‘%’ in format scipy/sparse/sparsetools/csr_wrap.cxx:2917: warning: too many arguments for format error: Command "g++ -pthread -fno-strict-aliasing -g -O2 -DNDEBUG -g -fwrapv -O3 -Wall -fPIC -I/usr/local/lib/python2.7/site-packages/numpy/core/include -I/usr/local/include/python2.7 -c scipy/sparse/sparsetools/csr_wrap.cxx -o build/temp.linux-x86_64-2.7/scipy/sparse/sparsetools/csr_wrap.o" failed with exit status 1 Numpy seems to have compiled fine. Any ideas of how to fix that? Thanks, ++nicolau -- Nicolau Werneck <nwerneck(a)gmail.com> 25A1 1BCB 714C 29E7 D84C http://www.lti.pcs.usp.br/~nwerneck 8514 152D 103F B001 8740 Linux user #460716

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Replace duplicates in a monotonically increasing array with linearly interpolated values.
by Dharhas Pothina Sept. 15, 2010

Sept. 15, 2010

Hi, I have an monotonically increasing array with duplicates in it. e.g. x = np.array([1.0,1.0,1.0,2.0,2.0,3.0,3.0,3.0,4.0,4.0,5.0,5.0,5.0,5.0,6.0]) I need a new array of the same size with linearly interpolated values i.e something like np.array([1.0, 1.33, 1.67, 2.0, 2.5, 3.0, 3.33, 3.67, 4.0, 4.5, 5.0, 5.25, 5.5, 5.75, 6.0]) Is there an efficient way to do this. Right now I'm looping through the array and maintaining position flags of when the value changes and then doing linear interpolation between the start and end flags before resetting the flags moving to the next section. This is pretty slow. I realize there will be a problem on how to deal with duplicates at the end of the array. thanks - dharhas

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ANN: OpenOpt 0.31, FuncDesigner 0.21, DerApproximator 0.21
by Dmitrey Sept. 15, 2010

Sept. 15, 2010

Hi all, I'm glad to inform you about new releases: OpenOpt 0.31, FuncDesigner 0.21, DerApproximator 0.21 For details see http://forum.openopt.org/viewtopic.php?id=299 or visit our homepage http://openopt.org Regards, Dmitrey

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cannot find -llapack
by pepe_emspin Sept. 15, 2010

Sept. 15, 2010

Hello I am sorry for previous incomplete email! I am using pythonxy distribution (windows) including numpy/scipy. I am installing SLYCOT wrapper http://github.com/avventi/Slycot Installation process is halted >python setup.py install build -compiler=mingw32 I am getting this message: c:/mingw/bin/../lib/gcc/mingw32/4.5.0/../../../../mingw32/bin/ld.exe: cannot find -llapack Any idea how to fix it? Thanks! Regards, pepe

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cannot find -llapack
by pepe_emspin Sept. 15, 2010

Sept. 15, 2010

http://github.com/avventi/Slycot c:/mingw/bin/../lib/gcc/mingw32/4.5.0/../../../../mingw32/bin/ld.exe: cannot find -llapack I am trying to find out how to fix this...

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