cbcpost - a postprocessing framework for FEniCS

cbcpost is developed to simplify the postprocessing of simulation results, produced by FEniCS solvers.

The framework is designed to take any given solution, and compute and save any derived data. Derived data can easily be made highly complex, due to the modular design and implementation of computations of quantities such as integrals, derivatives, magnitude etc, and the ability to chain these.

The interface is designed to be simple, with minimal cluttering of a typical solver code. This is illustrated by the following simple example:

# ... problem set up ...

# Set up postprocessor
solution = SolutionField("Displacement", dict(save=True))
postprocessor = PostProcessor(dict(casedir="Results/"))

# Add derived fields
    Maximum("Displacement", dict(save=True)),
    TimeAverage("Displacement", dict(save=True, start_time=1.0,

t = 0.0
timestep = 0
while t < T:
    timestep += 1
    # ... solve equation ...

    # Update postprocessor
    postprocessor.update_all(dict("Displacement"=lambda: u), timestep, t)

    # continue

cbcpost is developed at the Center for Biomedical Computing, at Simula Research Laboratory by Øyvind Evju and Martin Sandve Alnæs.