Some scripts for acoustic wave modeling

For now it might be useful for modeling acoustic waves in partially limited environment. Under the hood it's a fenicsx project backends and gmsh for mesh generation. time domain and frequency domain animations is supported

how to run?

Currently I've tried only one-thread mode, and get SEGFAULT in other cases.

mpirun -n 1 python3 -m src

how to setup env?

conda init
conda create -n env3-10-complex -c conda-forge python=3.10 fenics-dolfinx petsc=*=complex* mpich
conda activate env3-10-complex
conda install -c conda-forge ipykernel
python -m ipykernel install --user --name=env3-10-complex
pip install gmsh matplotlib
sudo apt-get -y install gmsh
export PYTHONPATH=path/to/your/directory/acoustics

Quick guide to setup conda:

mkdir -p ~/miniconda3;
wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O ~/miniconda3/miniconda.sh;
bash ~/miniconda3/miniconda.sh -b -u -p ~/miniconda3;
rm ~/miniconda3/miniconda.sh;
source ~/miniconda3/bin/activate;
conda init --all;

after that, reopen your terminal

New version:

sudo add-apt-repository ppa:fenics-packages/fenics;
sudo apt update;
sudo apt install fenicsx;
conda create -n dolfinx-new -c conda-forge fenics-dolfinx petsc mpich mpi4py pugixml spdlog;
pip install matplotlib tqdm gmsh;

For some reasons, versions of fenicsx, distributed via pip and conda, are deprecated now, so let's build them locally!

How hard can it be?

basix

python3 -m venv venv
source venv/bin/activate
python3 -m pip install git+https://github.com/FEniCS/basix.git@main

also, we need to install basicx .so version (to build dolfinx)

git clone https://github.com/FEniCS/basix.git lbasicx
cd lbasicx/cpp/
cmake -DCMAKE_BUILD_TYPE=Release -B build-dir -S .
cmake --build build-dir
sudo cmake --install build-dir

ufl

python3 -m pip install git+https://github.com/FEniCS/ufl.git@main

ffcx

python3 -m pip install git+https://github.com/FEniCS/ffcx.git@main

dolfinx

git clone https://github.com/FEniCS/dolfinx.git ldolfinx
cd ldolfinx/cpp
mkdir build
cd build
cmake ..
sudo make install
source /usr/local/lib/dolfinx/dolfinx.conf
cd ../../python/
export CMAKE_ARGS="-DMPI_C_COMPILER=$(which mpicc) -DMPI_CXX_COMPILER=$(which mpicxx) -DCMAKE_BUILD_TYPE=Release"
add enable_language(C) after project(...) in CMakeLists.txt
pip install -r build-requirements.txt
pip install --check-build-dependencies --no-build-isolation --no-cache-dir -v .

how to run?

Currently I've tried only one-thread mode, and get SEGFAULT in other cases.

mpirun -n 1 python3 -m src

notes

1. You can watch my tries to structure this project properly via commit history )
2. To contribute, installing git-lfs is needed

Concept

/src

Directory for source code. Supposed to run as a module.

config.py

Contains configuration for the project as a set of dataclasses. If needed, you can add your configuration here, and mark it as a typing.Protocol in problem.py for your problem (ex. for a 3D problem). For now, common protocol is defined in config.py(ConfigProtocol)

mesh.py

Contains Mesh generators. Mesh generator must implement IMeshGenerator ABC with the only public methiod ImeshGenerator.generate().

solver.py

Contains solver for the problem. Solver must implement ISolver ABC with the only public methiod ISolver.solve(). I am currently not sure what return type for ISolver.solve() should be, so this behaviour may change in the future.

visualizer.py

This abstraction is actually very useful, mostly because you want to be able to change the visualization and compare different animation methods. Visualizer must implement IVisualizer ABC with the only public methiod IVisualizer.create_animation() and IVisualizer.create_static_plot(). Good idea is to add more flexibility to an interface.

/pic

Directory for pictures / plots.

/animations

Directory for animations. Animations may weight more than 50MiB, for now it's about 70-80 Mib (and we're going to animate in 3D soon!) In that case, using git-lfs is highly recommended.