Using Python modules for in-situ data analytics with OpenFOAM. NOTE that this is NOT PyFOAM which is an automation tool for running OpenFOAM cases. What you see in this repository, is OpenFOAM calling Python functions and classes for in-situ data analytics. You may offload some portion of your compute task to Python for a variety of reasons (chiefly data-driven tasks using the Python ML ecosystem and quick prototyping of algorithms).
OpenFOAM versions that should compile without changes:
- openfoam.com versions: v2012, v2106
- openfoam.org versions: 8
- OpenFOAM
- numpy (python) with devel headers
- tensorflow (python)
- matplotlib.pyplot (python)
-
PODFoam/: ApimpleFoamsolver with in-situ collection of snapshot data for a streaming singular value decomposition. Python bindings are used to utilize a Python Streaming-SVD class object from OpenFOAM. -
APMOSFoam/: ApimpleFoamsolver with in-situ collection of snapshot data for a parallelized singular value decomposition. While the previous example performs the SVD on data only on one rank - this solver performs a global, but distributed, SVD. However, SVD updates are not streaming.
Use standard procedure to compile a new solver in OpenFOAM, i.e., use wmake from within PODFoam/.
To run cases, it is assumed that you have a Python virtual environment that is linked to during compile and run time. The relevant lines are
PY_INCS
PY_LIBS
within Make/options.
Replace these with the include/lib paths to your personal Python environments. The Python module within Run_Case/ directories require the use of numpy, matplotlib, and tensorflow so ensure that your environment has these installed. The best way to obtain these is to pip install tensorflow==2.1 which will automatically find the right numpy dependency and then pip install matplotlib to obtain plot capability. You will also need to install mpi4py which you can using pip install mpi4py.
A Docker container with the contents of this repo is available here. You can use docker pull romitmaulik1/pythonfoam_docker:reproduced on a machine with docker in it, or singularity build pythonfoam.img docker://romitmaulik1/pythonfoam_docker:reproduced. Do not forget to ensure OpenFOAM is sourced and available in your path by using source /opt/openfoam8/etc/bashrc. For a quick crash course on using Docker, see this tutorial by Jean Rabault. Singularity resources may be found here.
Points of contact for further assistance - Romit Maulik (rmaulik@anl.gov). This work was performed by using the resources of the Argonne Leadership Computing Facility, a U.S. Department of Energy (Office of Science) user facility at Argonne National Laboratory, Lemont, IL, USA.
Argonne open source for the Python integration