Mailman 3 September 2007 - SciPy-Dev

ANN: Reminder - Texas Python Regional Unconference
by Travis Vaught Sept. 12, 2007

Sept. 12, 2007

Greetings, Just a reminder for those in the area... http://pycamp.python.org/Texas/HomePage The Unconference is to be held this weekend (Saturday and Sunday, September 15, 16) at the Texas Learning & Computing Center at the University of Houston main campus. It's free. Sign up by adding your name to the wiki page. Travis

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problems with login/register in scikits page
by dmitrey Sept. 12, 2007

Sept. 12, 2007

hi all, once again I can't neither login with any my accounts I ever done in scikits page nor register. It prompts to enter login and password from scipy page, but despite I can login to that one with name DmitreyKroshko and password <mypassw> it didn't help to login to scikits page in the prompt window, it appears again and again. If I press cancel, I get Authorization Required This server could not verify that you are authorized to access the document requested. Either you supplied the wrong credentials (e.g., bad password), or your browser doesn't understand how to supply the credentials required. ------------------------------------------------------------------------ Apache/2.0.54 (Fedora) Server at scipy.org Port 80 Please fin the issues ASAP. http://scipy.org/scipy/scikits/login http://scipy.org/scipy/scikits/register If it's essential, I use Mozilla Firefox, Ubuntu. I have removed cookies but the problem remains. Regards, D.

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First alpha release of PySUNDIALS
by James Dominy Sept. 12, 2007

Sept. 12, 2007

Hi Everyone, The first alpha release of PySUNDIALS (a python package providing python bindings for SUNDIALS) has been released. It's not a SciPy module, but is likely to be of interest to many on this list. It is considered alpha, as it has yet to undergo extensive testing. CVODE, CVODES, KINSOL, and IDA have a complete set of bindings. Work has begun on the examples provided with SUNDIALS to compare against the results of their C counterparts, and of course to weed out any blatant bugs in the python modules. It is available on SourceForge at http://www.sourceforge.net/projects/pysundails for anyone who is interested in giving it a test run. Bug reports and feature requests can be submitted through SourceForge too. Enjoy! James P.S. If anyone feels like giving me a hand translating the comments in the C code to python doc-strings, let me know...

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sandbox package arpack
by Nils Wagner Sept. 11, 2007

Sept. 11, 2007

Hi all, The sandbox package *arpack* has no entry in setup.py (from svn). Is this a bug ? Nils

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FAIL: test_imresize
by Nils Wagner Sept. 11, 2007

Sept. 11, 2007

Hi all, Can someone reproduce the following failures with latest svn versions of numpy/scipy ? scipy.test(1) yields ====================================================================== FAIL: test_imresize (scipy.misc.tests.test_pilutil.test_pilutil) ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib64/python2.5/site-packages/scipy/misc/tests/test_pilutil.py", line 18, in test_imresize assert_equal(im1.shape,(11,22)) File "/usr/local/lib64/python2.5/site-packages/numpy/testing/utils.py", line 137, in assert_equal assert_equal(len(actual),len(desired),err_msg,verbose) File "/usr/local/lib64/python2.5/site-packages/numpy/testing/utils.py", line 145, in assert_equal assert desired == actual, msg AssertionError: Items are not equal: ACTUAL: 0 DESIRED: 2 ====================================================================== FAIL: testip_fromimage (scipy.misc.tests.test_pilutil.test_pilutil) ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib64/python2.5/site-packages/numpy/testing/parametric.py", line 67, in exec_test test(*args) File "/usr/local/lib64/python2.5/site-packages/scipy/misc/tests/test_pilutil.py", line 29, in tst_fromimage assert img.min() >= imin AssertionError ====================================================================== FAIL: testip_fromimage (scipy.misc.tests.test_pilutil.test_pilutil) ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib64/python2.5/site-packages/numpy/testing/parametric.py", line 67, in exec_test test(*args) File "/usr/local/lib64/python2.5/site-packages/scipy/misc/tests/test_pilutil.py", line 29, in tst_fromimage assert img.min() >= imin AssertionError ====================================================================== FAIL: testip_fromimage (scipy.misc.tests.test_pilutil.test_pilutil) ---------------------------------------------------------------------- Traceback (most recent call last): File "/usr/local/lib64/python2.5/site-packages/numpy/testing/parametric.py", line 67, in exec_test test(*args) File "/usr/local/lib64/python2.5/site-packages/scipy/misc/tests/test_pilutil.py", line 29, in tst_fromimage assert img.min() >= imin AssertionError Nils

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_cs_matrix._matvec()
by Robert Cimrman Sept. 10, 2007

Sept. 10, 2007

hi again, looking at _cs_matrix class in sparse.py, I noticed def _matvec(self, other, fn): if isdense(other): # This check is too harsh -- it prevents a column vector from # being created on-the-fly like dense matrix objects can. #if len(other) != self.shape[1]: # raise ValueError, "dimension mismatch" oth = numpy.ravel(other) y = fn(self.shape[0], self.shape[1], \ self.indptr, self.indices, self.data, oth) if isinstance(other, matrix): y = asmatrix(y) if other.ndim == 2 and other.shape[1] == 1: # If 'other' was an (nx1) column vector, transpose the result # to obtain an (mx1) column vector. y = y.T return y I do not see a reason for the commenting out of the lines #if len(other) != self.shape[1]: # raise ValueError, "dimension mismatch" as the function silently passes with wrong input. Could anybody explain this? I would uncomment the lines, but maybe there is a reason... r.

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sparse matrix indexing (__getitem__ or not?)
by Robert Cimrman Sept. 10, 2007

Sept. 10, 2007

Hi, I have added a function to fill in the gap in the CSR matrix indexing capabilities into sparsetools. It extracts a submatrix (makes a new matrix) using row and column slices. For the moment it has been made accessible by adding a new method get_submatrix( self, slice0, slice1 ) to csr_matrix class - the method returns a new matrix and not a view, as indexing via [] (__getitem__()) currently does. Note that it could be easily extended for general indexing by index arrays. It is not possible for a sparse matrix to return a view of a general submatrix, therefore I would like to discuss here which of the following two possibilities suit the other sparse matrix users better: 1. __getitem__() returns views only, other submatrix extraction functionality is accessed via another method (e.g. get_submatrix()). This case is compatible with the behaviour of dense arrays, but IMHO a bit clumsy. 2. __getitem__() returns views or new matrices as necessary (properly documented for each sparse matrix kind). This case differs in behaviour from the dense arrays but, pragmatically, I like this case more. As a side-note, even if the second item gets implemented, I see a niche for the get_submatrix() method - it could have additional arguments specifying for example that it should return a dense array instead of the sparse one. r.

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Usage of enabled_packages.txt with recent svn
by Nils Wagner Sept. 9, 2007

Sept. 9, 2007

Hi all, I have created a file "enabled_packages.txt" in the directory scipy/scipy/sandbox. Now I can't build scipy from svn. config = setup_module.configuration(*args) File "scipy/sandbox/setup.py", line 24, in configuration config.add_subpackage(p) File "/usr/local/lib64/python2.5/site-packages/numpy/distutils/misc_util.py", line 835, in add_subpackage caller_level = 2) File "/usr/local/lib64/python2.5/site-packages/numpy/distutils/misc_util.py", line 818, in get_subpackage caller_level = caller_level + 1) File "/usr/local/lib64/python2.5/site-packages/numpy/distutils/misc_util.py", line 765, in _get_configuration_from_setup_py config = setup_module.configuration(*args) File "scipy/sandbox/arpack/setup.py", line 9, in configuration lapack_opt = get_info('lapack_opt') File "/usr/local/lib64/python2.5/site-packages/numpy/distutils/system_info.py", line 256, in get_info return cl().get_info(notfound_action) File "/usr/local/lib64/python2.5/site-packages/numpy/distutils/system_info.py", line 424, in get_info return copy.deepcopy(res) File "/usr/lib64/python2.5/copy.py", line 162, in deepcopy y = copier(x, memo) File "/usr/lib64/python2.5/copy.py", line 254, in _deepcopy_dict y[deepcopy(key, memo)] = deepcopy(value, memo) File "/usr/lib64/python2.5/copy.py", line 162, in deepcopy y = copier(x, memo) File "/usr/lib64/python2.5/copy.py", line 227, in _deepcopy_list y.append(deepcopy(a, memo)) File "/usr/lib64/python2.5/copy.py", line 192, in deepcopy _keep_alive(x, memo) # Make sure x lives at least as long as d File "/usr/lib64/python2.5/copy.py", line 271, in _keep_alive memo[id(memo)].append(x) RuntimeError: maximum recursion depth exceeded in cmp Nils

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new release
by Ondrej Certik Sept. 8, 2007

Sept. 8, 2007

Hi, are there any problems with the new release? I thought it was planned a week ago, but suddenly it was quiet on the mailinglist about it. If there are still things to fix, let's do a sprint, fix problems and release. Jarrod? :) Ondrej

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openopt (prelimenary) announce
by dmitrey Sept. 7, 2007

Sept. 7, 2007

Hi all, here's a message that I intend to publish in Python and scipy-user mail lists, some changes were made by Alan Isaac. If you don't mind I want to publish it before in scipy-dev mail-list, maybe you would like to propose some changes. Regards, D. Announcing: OpenOpt (a SciPy scikit) ==================================== OpenOpt is new open source optimization framework, provided as a SciPy scikit. Goal: provide an essential open source alternative to TomOpt TOMLAB <http://tomopt.com/tomlab/> (optimization framework for MATLAB) and related commercial optimization frameworks and solvers. key features are: a unified calling interface for all solvers, a variety of pure Python solvers, graphic output <http://openopt.blogspot.com/2007/09/examples-of-openopt-graphics-output.html> and connections to numerous external solvers. Example:: from scikits.openopt import NLP p = NLP(lambda x: (x-1)**2, 4) r = p.solve('ralg') In this example, the objective function is (x-1)2, the start point is x0=4, and 'ralg' specifies the name of solver involved. See much more detailed example here <URL:http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/o…> License ------- OpenOpt itself is released under the BSD license. It provides connections to various solvers, which may have licenses (first of all we are interested in connecting opensource ones). In contrast to SciPy, the related scikits may host any OSI-approved licensed code. OpenOpt provides several solvers (ralg, lincher, ShorEllipsoid), and provides connections to still more. (For the latter, it provides URLs for download.) Our own solvers are 100% Python with a single dependency: NumPy, so no problems with installation Fortran or C code will be encountered. Solvers available for now -------------------------- Non-linear problems (NLP) ~~~~~~~~~~~~~~~~~~~~~~~~~ - ALGENCAN <http://www.ime.usp.br/%7Eegbirgin/tango/py.php> (GPL) - lincher (BSD) (all types of constraints and 1st derivatives), - ralg (BSD) (currently unconstrained only) - scipy_tnc and scipy_lbfgsb (box-bounded, requires scipy installed, BSD) Non-smooth problems (NSP) ~~~~~~~~~~~~~~~~~~~~~~~~~ - ralg (BSD) (for medium-scaled problems with nVars = 1...1000) - ShorEllipsoid (BSD) (for small-scale problems with nVars = 1..10, requires r0) (both are unconstrained for now). Linear problems (LP) ~~~~~~~~~~~~~~~~~~~~ - lp_solve <http://sourceforge.net/projects/lpsolve> (LGPL) - glpk <http://www.gnu.org/software/glpk/> (GPL) - CVXOPT <http://www.ee.ucla.edu/%7Evandenbe/cvxopt/> (GPL) (currently glpk requires CVXOPT installed) Mixed-integer problems (MILP) ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ - lp_solve <http://sourceforge.net/projects/lpsolve> Quadratic problems (QP) ~~~~~~~~~~~~~~~~~~~~~~~ - CVXOPT <http://www.ee.ucla.edu/%7Evandenbe/cvxopt/> (GPL) (please note - NLP lincher solver requires QP solver, and the only one for now is CVXOPT one) Here you can look at examples for NLP <http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/openo…>, NSP <http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/openo…>, QP <http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/openo…>, LP <http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/openo…>, MILP <http://projects.scipy.org/scipy/scikits/browser/trunk/openopt/scikits/openo…> usage GenericOpt ========== Of related interest is GenericOpt, a package that is connected to OpenOpt but is also available as separate module "optimizers". The primary author is Matthieu Brucher. GenericOpt allows users who want detailed control to construct their own solvers by choosing among a variety of algorithm components (currently, most choices are among step and line-search algorithms.) Usage: see Matthieu's tutorial <URL:https://projects.scipy.org/scipy/scikits/wiki/Optimization/tutorial>. Limitation: currently GenericOpt provides only unconstrained solvers. Acknowledgements ================ The OpenOpt project was sponsored by Google throught the GSoC program (Google Summer of Code). Most of code was written by GSoC student Dmitrey Kroshko (Optimization Department, Cybernetics Institute, Ukrainian Science Academy, and the dept staff suggestions were very useful) under the mentoring of SciPy developers Alan G Isaac and Jarrod Milman. Appeal ====== scikits.openopt development is intended to continue but to keep it intensive OpenOpt requires a new sponsor (since google Summer of Code 2007 program is finished), since in Ukraine interest in the use of Python for scientific programming is lagging. Ideas or leads are very welcome.

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