cbc.block is a python library for block operations in DOLFIN (http://fenicsproject.org). The headline features are:
Block operators may be defined from standard DOLFIN matrices and vectors:
A = assemble(...); B = assemble(...); # etc AA = block_mat([[A,B], [C,D]])
Preconditioners, inverses, and inner solvers are supported:
AAprec = AA.scheme('gauss-seidel', inverse=ML)
A good selection of iterative solvers:
AAinv = SymmLQ(AA, precond=AAprec) x = AAinv*b
Matrix algebra is supported both through composition of operators...
S = C*ILU(A)*B-D Sprec = ConjGrad(S)
...and through explicit matrix calculation via PyTrilinos:
S = C*InvDiag(A)*B-D Sprec = ML(collapse(S))
There is no real documentation apart from the python doc-strings, but an (outdated) introduction is found in doc/blockdolfin.pdf. Familiarity with the DOLFIN python interface is required. For more details of use, I recommend looking at the demos (start with demo/mixedpoisson.py), and the comments therein.
Bugs, questions, contributions: Visit http://bitbucket.org/fenics-apps/cbc.block.
The code is licensed under the GNU Lesser Public License, found in COPYING, version 2.1 or later. Some files under block/iterative/ use the BSD license, this is noted in the individual files.
Joachim Berdal Haga <email@example.com>, March 2011.
- K.-A. Mardal, and J. B. Haga (2012). Block preconditioning of systems of PDEs. In A. Logg, K.-A. Mardal, G. N. Wells et al. (ed) Automated Solution of Differential Equations by the Finite Element Method, Springer. doi:10.1007/978-3-642-23099-8, http://fenicsproject.org/book