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There is no real documentation apart from the python doc-strings, but an (outdated) introduction is found in doc/blockdolfin.pdf.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 <jobh@simula.no>, March 2011.

1. 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