Mailman 3 December 2010 - SfePy

preparing 2010.4
by Robert Cimrman 06 Dec '10

06 Dec '10

Hi, next week I would like to release a new version to the unsuspecting world to show that sfepy is alive, so if there is somebody willing to test the code, grab it as usual at [1], see [2] or [3] if you forgot how :) I am attaching an updated test script, so that you can just compile the extension modules, and run it. It might be too picky in cases as it expects the exact output I get on my computer... r. [1] https://github.com/sfepy/sfepy [2] http://docs.sfepy.org/doc-devel/developer_guide.html#how-to-contribute [3] http://docs.sfepy.org/doc-devel/dev/gitwash/index.html#using-git

4 11

bad convergence of examples/diffusion/subdomains.py
by Robert Cimrman 02 Dec '10

02 Dec '10

Hi Vlada, In the 'ori' branch, I have update FieldVariable.get_global_node_tab() but noticed a bad convergence of examples/diffusion/subdomains.py. It was present even before the massive changes of the 'ori' branch - master (ec602a8162a96926afe09864adfe2e58a08c2503) version behaves in the same manner: sfepy: nls: iter: 0, residual: 6.173330e+00 (rel: 1.000000e+00) sfepy: nls: iter: 1, residual: 2.606163e-03 (rel: 4.221649e-04) If you put "'check' : 2" in the newton solver options, you will see that the tangent matrix is wrong. Can you check this? If it's a deeper problem, create a new issue, please. Thanks, r.

1 0

higher order elements
by Robert Cimrman 01 Dec '10

01 Dec '10

Hi, I have finally reimplemented some of the core functionality to allow higher order elements (uniform order), see the 'ori' branch [1] (the name stands for 'orientation', because the key part that was missing had been the orientation of faces allowing to define face degrees of freedom). I tested only the very basic things, so bugs are to be expected. Any testing is more than welcome, You can try, for example, to modify examples/diffusion/poisson.py as follows: - use P3 (cubic) elements ... field_1 = { 'name' : 'temperature', 'dtype' : 'real', 'shape' : (1,), 'region' : 'Omega', 'approx_order' : 3, } ... - increase quadrature order to 3 ... equations = { 'Temperature' : """dw_laplace.3.Omega( coef.val, s, t ) = 0""" } ... Similarly, other examples can be tried out. There are still things missing for it to be really useful: - higher order quadratures - try to set 'approx_order' : 4 in the example above and you get 'warp violation' error. This is because the approximation order is too high w.r.t. the quadrature (3 is currently our highest order for tetrahedrons). - proper visualization - the higher order degrees of freedom are just thrown away now - only vertex values are used (or cell values for zero-order approximations). - hierarchical finite element basis - the Lagrange polynomial basis that is used now has very bad properties when the approximation order is increasing, leading to a matrix with a large condition number. Any comments/suggestions/help welcome! r. [1] https://github.com/rc/sfepy/tree/ori

1 0

Fwd: [SciPy-User] Announcement: Self-contained Python module to write binary VTK files.
by Robert Cimrman 01 Dec '10

01 Dec '10

Hi, could this be useful? I do not see license at the package site... r. -------- Original Message -------- Subject: [SciPy-User] Announcement: Self-contained Python module to write binary VTK files. Date: Mon, 29 Nov 2010 09:45:29 +0100 From: Paulo Herrera <pauloa....(a)gmail.com> Reply-To: SciPy Users List <scipy...(a)scipy.org> To: scipy...(a)scipy.org Hello everyone, This is my first post to this list. I would like to announce the first release of a Python module I wrote to export scientific data to binary VTK files. The source code for the module can be downloaded from its Mercurial repository at bitbucket. To get a copy, type on terminal window: hg clone https://pauloh@bitbucket.org/pauloh/pyevtk PyEVTK (Python Export VTK) package allows exporting data to binary VTK files for visualization and data analysis with any of the visualization packages that support VTK files, e.g. Paraview, VisIt and Mayavi. EVTK does not depend on any external library (e.g. VTK), so it is easy to install in different systems. The package is composed of a set of Python files and a small C/Cython library that provides performance critical routines. PyEVTK provides low and high level interfaces. While the low level interface can be used to export data that is stored in any type of container, the high level functions make easy to export data stored in Numpy arrays. In addition, it provides a helper class to create pvd files that can be imported into Paraview to visualize time dependent data series. PyEVTK is released under the GPL 3 open source license. A copy of the license is included in the src directory. Please see below for an example of how to use the high level routines. More examples are included in the package. I hope you will find this package useful and I look forward to getting your feedback. Paulo High-level interface example: ============================= from evtk.hl import imageToVTK import numpy as np # Dimensions nx, ny, nz = 6, 6, 2 ncells = nx * ny * nz npoints = (nx + 1) * (ny + 1) * (nz + 1) # Variables pressure = np.random.rand(ncells).reshape( (nx, ny, nz), order = 'C') temp = np.random.rand(npoints).reshape( (nx + 1, ny + 1, nz + 1)) imageToVTK("./image", cellData = {"pressure" : pressure}, pointData = {"temp" : temp} ) _______________________________________________ SciPy-User mailing list SciPy...(a)scipy.org http://mail.scipy.org/mailman/listinfo/scipy-user

2 2