Mailman 3 February 2010 - SciPy-Dev

SLSQP Constrained Optimizer Status
by Rob Falck Nov. 24, 2013

Nov. 24, 2013

I'm currently implementing the Sequential Least Squares Quadratic Programming (SLSQP) optimizer, by Dieter Kraft, for use in Scipy. The Fortran code being wrapped with F2PY is here: http://www.netlib.org/toms/733 (its use within Scipy has been cleared) SLSQP provides for bounds on the independent variables, as well as equality and inequality constraint functions, which is a capability that doesn't exist in scipy.optimize. Currently the code works, although the constraint normals are being generated by approximation. I'm working on a way to pass these in. I think the most elegant way will be a single function that returns the matrix of constraint normals. For a demonstration of what the code can do, here is an optimization of f(x,y) = 2xy + 2x - x**2 - 2y**2 Example 14.2 in Chapra & Canale gives the maximum as x=2.0, y=1.0. The unbounded optimization tests find this solution. As expected, its faster when derivatives are provided rather than approximated. Unbounded optimization. Derivatives approximated. Elapsed time: 1.45792961121 ms Results [[1.9999999515712266, 0.99999996181577444], -1.9999999999999984, 4, 0, 'Optimization terminated successfully.'] Unbounded optimization. Derivatives provided. Elapsed time: 1.03211402893 ms Results [[1.9999999515712266, 0.99999996181577444], -1.9999999999999984, 4, 0, 'Optimization terminated successfully.'] The following example uses an equality constraint to find the optimal when x=y. Bound optimization. Derivatives approximated. Elapsed time: 1.384973526 ms Results [[0.99999996845920858, 0.99999996845920858], -0.99999999999999889, 4, 0, 'Optimization terminated successfully.'] I've tried to conform to the syntax used by the other optimizers in scipy.optimize. The function definition and doc string are below. If anyone is interested in testing it out, let me know. def fmin_slsqp( func, x0 , eqcons=[], f_eqcons=None, ieqcons=[], f_ieqcons=None, bounds = [], fprime = None, fprime_cons=None,args = (), iter = 100, acc = 1.0E-6, iprint = 1, full_output = 0, epsilon = _epsilon ): """ Minimize a function using Sequential Least SQuares Programming Description: Python interface function for the SLSQP Optimization subroutine originally implemented by Dieter Kraft. Inputs: func - Objective function (in the form func(x, *args)) x0 - Initial guess for the independent variable(s). eqcons - A list of functions of length n such that eqcons[j](x0,*args) == 0.0 in a successfully optimized problem f_eqcons - A function of the form f_eqcons(x, *args) that returns an array in which each element must equal 0.0 in a successfully optimized problem. If f_eqcons is specified, eqcons is ignored. ieqcons - A list of functions of length n such that ieqcons[j](x0,*args) >= 0.0 in a successfully optimized problem f_ieqcons - A function of the form f_ieqcons(x0, *args) that returns an array in which each element must be greater or equal to 0.0 in a successfully optimized problem. If f_ieqcons is specified, ieqcons is ignored. bounds - A list of tuples specifying the lower and upper bound for each independent variable [ (xl0, xu0), (xl1, xu1), ...] fprime - A function that evaluates the partial derivatives of func fprime_cons - A function of the form f(x, *args) that returns the m by n array of constraint normals. If not provided, the normals will be approximated. Equality constraint normals precede inequality constraint normals. args - A sequence of additional arguments passed to func and fprime iter - The maximum number of iterations (int) acc - Requested accuracy (float) iprint - The verbosity of fmin_slsqp. iprint <= 0 : Silent operation iprint == 1 : Print summary upon completion (default) iprint >= 2 : Print status of each iterate and summary full_output - If 0, return only the minimizer of func (default). Otherwise, output final objective function and summary information. epsilon - The step size for finite-difference derivative estimates. Outputs: ( x, { fx, gnorm, its, imode, smode }) x - The final minimizer of func. fx - The final value of the objective function. its - The number of iterations. imode - The exit mode from the optimizer, as an integer. smode - A string describing the exit mode from the optimizer. Exit modes are defined as follows: -1 : Gradient evaluation required (g & a) 0 : Optimization terminated successfully. 1 : Function evaluation required (f & c) 2 : Number of equality constraints larger than number of independent variables 3 : More than 3*n iterations in LSQ subproblem 4 : Inequality constraints incompatible 5 : Singular matrix E in LSQ subproblem 6 : Singular matrix C in LSQ subproblem 7 : Rank-deficient equality constraint subproblem HFTI 8 : Positive directional derivative for linesearch 9 : Iteration limit exceeded -- - Rob Falck

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np.savetxt: apply patch in enhancement ticket 1079 to add headers?
by Skipper Seabold June 8, 2010

June 8, 2010

Hi all, I am assuming that this is ok to request via the list... Could we discuss or could someone apply the patch in enhancement ticket 1079? http://projects.scipy.org/numpy/ticket/1079 I needed this functionality recently, and this is a quick and easy fix that may have been overlooked. There is also another enhancement request about this here: http://projects.scipy.org/numpy/ticket/1236 The only thing that I can think of that might need to be added is a test to see that the header length is the same as the number of columns, but really that might just be up to the user to supply the right headers. It might also be nice to have a header = True, that uses the field names for a structured array, but I can live without that. Cheers, Skipper

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namespace recommendation in scipy tutorial and docs for np.emath
by josef.pktd＠gmail.com May 15, 2010

May 15, 2010

I'm going through some scipy tickets and I found http://projects.scipy.org/scipy/ticket/882 I don't know much about the old usage of mixing (mixed up) namespaces. But I think it would be good if someone could check the namespace convention/recommendation in the basic scipy tutorial http://docs.scipy.org/doc/scipy/reference/tutorial/basic.html When I tried to figure out the difference between scipy.* and numpy.*, I also found that the functions in numpy.emath (numpy.scipy) have good docstrings, but they are not included in the docs (at least I don't find them), because http://docs.scipy.org/numpy/docs/numpy-docs/reference/routines.emath.rst/#n… is still a stub page without function links. http://docs.scipy.org/doc/numpy/reference/routines.emath.html Josef

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build issue on OS X 10.6 - fails on fftpack
by Ralf Gommers March 3, 2010

March 3, 2010

After switching from Apple Python to the python.org version this is the first time I tried to build scipy. I see the same problem when building scipy trunk against numpy trunk or 0.7.x against numpy 1.3. Compilers: $ gcc --version i686-apple-darwin10-gcc-4.2.1 (GCC) 4.2.1 (Apple Inc. build 5646) (dot 1) $ gcc-4.0 --version i686-apple-darwin10-gcc-4.0.1 (GCC) 4.0.1 (Apple Inc. build 5493) $ gfortran --version GNU Fortran (GCC) 4.2.3 (obtained from http://r.research.att.com/tools/) Python: $ python Python 2.6.4 (r264:75821M, Oct 27 2009, 19:48:32) [GCC 4.0.1 (Apple Inc. build 5493)] on darwin Below is the relevant part (I think) of the build output. The "missing required architecture x86_64 in file" complaints happen for numpy builds as well, and seem to be harmless there. Any ideas? Thanks, Ralf $ LDFLAGS="-lgfortran -arch x86_64" FFLAGS="-arch x86_64" python setup.py build Warning: No configuration returned, assuming unavailable.blas_opt_info: FOUND: extra_link_args = ['-Wl,-framework', '-Wl,Accelerate'] define_macros = [('NO_ATLAS_INFO', 3)] extra_compile_args = ['-faltivec', '-I/System/Library/Frameworks/vecLib.framework/Headers'] lapack_opt_info: FOUND: extra_link_args = ['-Wl,-framework', '-Wl,Accelerate'] define_macros = [('NO_ATLAS_INFO', 3)] extra_compile_args = ['-faltivec'] umfpack_info: libraries umfpack not found in /Library/Frameworks/Python.framework/Versions/2.6/lib libraries umfpack not found in /usr/local/lib libraries umfpack not found in /usr/lib /Users/rgommers/Code/numpy/numpy/distutils/system_info.py:459: UserWarning: UMFPACK sparse solver (http://www.cise.ufl.edu/research/sparse/umfpack/) not found. Directories to search for the libraries can be specified in the numpy/distutils/site.cfg file (section [umfpack]) or by setting the UMFPACK environment variable. warnings.warn(self.notfounderror.__doc__) NOT AVAILABLE running build <SNIP> building 'scipy.fftpack._fftpack' extension compiling C sources C compiler: gcc-4.0 -arch ppc -arch i386 -isysroot /Developer/SDKs/MacOSX10.4u.sdk -fno-strict-aliasing -fno-common -dynamic -DNDEBUG -g -O3 creating build/temp.macosx-10.3-fat-2.6/build creating build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6 creating build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy creating build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack creating build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/src compile options: '-Iscipy/fftpack/src -Ibuild/src.macosx-10.3-fat-2.6 -I/Users/rgommers/Code/numpy/numpy/core/include -I/Library/Frameworks/Python.framework/Versions/2.6/include/python2.6 -c' gcc-4.0: scipy/fftpack/src/zrfft.c gcc-4.0: build/src.macosx-10.3-fat-2.6/scipy/fftpack/src/dct.c gcc-4.0: scipy/fftpack/src/zfftnd.c gcc-4.0: build/src.macosx-10.3-fat-2.6/fortranobject.c gcc-4.0: build/src.macosx-10.3-fat-2.6/scipy/fftpack/_fftpackmodule.c gcc-4.0: scipy/fftpack/src/drfft.c gcc-4.0: scipy/fftpack/src/zfft.c /usr/local/bin/gfortran -Wall -lgfortran -arch x86_64 build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/_fftpackmodule.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/drfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zrfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfftnd.o build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/src/dct.o build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/fortranobject.o -L/usr/local/lib/gcc/i686-apple-darwin8/4.2.3/x86_64 -Lbuild/temp.macosx-10.3-fat-2.6 -ldfftpack -lfftpack -lgfortran -o build/lib.macosx-10.3-fat-2.6/scipy/fftpack/_fftpack.so ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/_fftpackmodule.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/drfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zrfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfftnd.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/src/dct.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/fortranobject.o, missing required architecture x86_64 in file Undefined symbols: "_MAIN__", referenced from: _main in libgfortranbegin.a(fmain.o) ld: symbol(s) not found collect2: ld returned 1 exit status ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/_fftpackmodule.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/drfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zrfft.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfftnd.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/src/dct.o, missing required architecture x86_64 in file ld: warning: in build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/fortranobject.o, missing required architecture x86_64 in file Undefined symbols: "_MAIN__", referenced from: _main in libgfortranbegin.a(fmain.o) ld: symbol(s) not found collect2: ld returned 1 exit status error: Command "/usr/local/bin/gfortran -Wall -lgfortran -arch x86_64 build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/_fftpackmodule.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/drfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zrfft.o build/temp.macosx-10.3-fat-2.6/scipy/fftpack/src/zfftnd.o build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/scipy/fftpack/src/dct.o build/temp.macosx-10.3-fat-2.6/build/src.macosx-10.3-fat-2.6/fortranobject.o -L/usr/local/lib/gcc/i686-apple-darwin8/4.2.3/x86_64 -Lbuild/temp.macosx-10.3-fat-2.6 -ldfftpack -lfftpack -lgfortran -o build/lib.macosx-10.3-fat-2.6/scipy/fftpack/_fftpack.so" failed with exit status 1

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GSOC project discussion on improving datasource and its integration.
by Mohit Goyal Feb. 26, 2010

Feb. 26, 2010

I am masters students in data engineering and interested in contributing to scipy. I need some directions to how to start with it. I know python and have worked on projects including data mining , web mining and web crawlers etc. I want to contribute to scipy by improving datasource and its integrations like handling malformed URLs, proxy settings , other file extensions support. http://projects.scipy.org/scipy/wiki/SummerofCodeIdeas http://projects.scipy.org/scipy/numpy/browser/trunk/numpy/lib/_datasource.py Thank You.

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spam filter for scipy-tickets or scipy-tickets-bounces@scipy.org
by josef.pktd＠gmail.com Feb. 26, 2010

Feb. 26, 2010

Is there a spam filter on the scipy ticket mailing list ? Or am I the only one to get spam through it? Josef

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Hello
by pearu.peterson＠gmail.com Feb. 26, 2010

Feb. 26, 2010

The message cannot be represented in 7-bit ASCII encoding and has been sent as a binary attachment.

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implement reorthogonalization method in gmres
by Darcoux Christine Feb. 25, 2010

Feb. 25, 2010

It seems that the vectors produced by the Gram-Schmidt process may not be orthogonal (probably due to the presence of roundoff errors or when the matrix is ill conditionned). I would suggest to add an option to test for loss of orthogonality and reorthogonalize if needed. See http://www4.ncsu.edu/~ctk/newton/SOLVERS/nsoli.m for an example. regards, Christine

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Fwd: [Info] Fwd: Reg: gsoc 2010
by Travis Oliphant Feb. 24, 2010

Feb. 24, 2010

Here is a message we received. Who is handling GSOC mentoring this year? -Travis Begin forwarded message: > From: Aaron River <ariver(a)enthought.com> > Date: February 23, 2010 5:43:45 PM CST > To: info(a)enthought.com > Subject: [Info] Fwd: Reg: gsoc 2010 > Reply-To: info(a)enthought.com > > -------- Original Message -------- > Subject: Reg: gsoc 2010 > Date: Mon, 22 Feb 2010 23:56:17 +0530 > From: Mohit Goyal <mohitiiit(a)gmail.com> > To: scipy-dev-owner(a)scipy.org > > I am a masters student doing research in data engineering. I know > python > and have done projects on data mining and web mining. > I want to contribute to scipy via gsoc 2010. I am interested in > working > on data related projects in scipy like improving data sources and > integrate it into all the numpy/scipy , adding data sets and > examples to > scipy, data analysis etc. Please tell me how to proceed. > > Thank You. > > -- > The Game is Not Over Because i haven't Won Yet. > -Mohit Goyal > _______________________________________________ > Info mailing list > Info(a)enthought.com > https://mail.enthought.com/mailman/listinfo/info -- Travis Oliphant Enthought Inc. 1-512-536-1057 http://www.enthought.com oliphant(a)enthought.com

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SciPy2010 Call for Papers
by Stéfan van der Walt Feb. 23, 2010

Feb. 23, 2010

========================== SciPy 2010 Call for Papers ========================== SciPy 2010, the 9th Python in Science Conference, will be held from June 28th - July 3rd, 2010 in Austin, Texas. At this conference, novel applications and breakthroughs made in the pursuit of science using Python are presented. Attended by leading figures from both academia and industry, it is an excellent opportunity to experience the cutting edge of scientific software development. The conference is preceded by two days of paid tutorials, during which community experts provide training on several scientific Python packages. We invite you to take part by submitting a talk abstract on the conference website at: http://conference.scipy.org Talk/Paper Submission ===================== We solicit talks and accompanying papers (either formal academic or magazine-style articles) that discuss topics regarding scientific computing using Python, including applications, teaching, development and research. Papers are included in the peer-reviewed conference proceedings, published online. Please note that submissions primarily aimed at the promotion of a commercial product or service will not be considered. Important dates for authors include: * 11 April: Talk abstracts due * 20 April: Notification of acceptance * 13 June: Papers due * 15 August: Publication of proceedings Further detail will be made available on http://conference.scipy.org Conference Dates ================ * Friday, 10 May: Early registration ends * Monday-Tuesday, 28-29 June: Tutorials * Wednesday-Thursday, June 30-July 1: Conference * Friday-Saturday, July 2-3: Coding Sprints Executive Committee =================== * Conference: Jarrod Millman & Eric Jones * Program: Stefan van der Walt & Ondrej Certik * Student Sponsorship: Travis Oliphant For more information on Python, visit http://www.python.org.

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