Supporting code for paper Efficient solution of parameter identification problems with $H^1$ regularization
- MATLAB R2020b with Symbolic Math Toolbox,
- HSL_MI20 2.0.0,
- Gmsh 4.5.6,
- matlab2tikz f299888.
-
Start Matlab and
cd
to the repository root (where this README resides). -
Run
app_dc.checkerboard_example.short_benchmark;
This step produces some
checkerboard-*.{fig,xdmf,bin,mat}
files in the current directory. This step can take around 900 minutes and needs 15 GB of RAM.To get the full results of the paper, use
app_dc.checkerboard_example.full_benchmark;
instead. This can take around 75 hours (depending on machine) and needs around 250 GB of RAM.
-
Run
app_dc.checkerboard_example.postprocess; app_dc.checkerboard_example.postprocess2; app_dc.checkerboard_example.postprocess3; app_dc.checkerboard_example.postprocess4; app_dc.checkerboard_example.plot_configs;
to produce additional
checkerboard-*.{pdf,tex}
files in the current directory.
The 3d plots are produced by the Python script plot-3d.py
from .xdmf
and .bin
files produced by the aforementioned
steps. The script uses pyvista
and a VTK
build with XDMF3
support, which is not featured on PyPI. One can circumvent this
by using Docker.
docker build -t pyvista dockerfiles/
docker run --rm -v "$PWD":/tmp pyvista python3 -u plot-3d.py
This produces checkerboard-3dfw.svg
and
checkerboard-3dfw-beta.svg
.
- Jan Blechta jan.blechta@math.tu-chemnitz.de
- Mathias Scheunert mathias.scheunert@mailserver.tu-freiberg.de
MIT License
Copyright (C) 2018-2022 Jan Blechta and Mathias Scheunert
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