RROMPy -- Rational Reduced Order Modeling in Python

Module for the solution and rational model order reduction of parametric PDE-based problem. Coded in Python 3.

Prerequisites

RROMPy requires

• numpy and scipy;
• fenics and mshr;
• matplotlib;
• scikit-learn;
• and other standard Python3 modules (os, typing, time, datetime, abc, pickle, traceback, itertools, ...).

Testing requires

• pytest.

Fenics

Most of the high fidelity problem engines already provided rely on FEniCS. If you do not have FEniCS installed, you may want to create an Anaconda3/Miniconda3 environment using the command

conda create -n fenicsenv -c conda-forge pytest pytest-runner scipy matplotlib scikit-learn fenics=2019.1.0=py38_9 mshr=2019.1.0=py38hf9f41d3_3

This will create an environment where FEniCS (and all other required modules) can be used. In order to use FEniCS, the environment must be activated through

conda activate fenicsenv

See the Anaconda documentation for more information.

Fenics and mshr versions

More recent versions of FEniCS and mshr may be preferred, but one should be careful of inconsistent dependencies. If the following code snippet runs successfully, then your environment *should* have been created correctly:

from mshr import *

Installing

Clone the repository

git clone http://c4science.ch/source/RROMPy.git

enter the main folder and install the package by typing

python setup.py install

The installation can be tested with

python setup.py test

License

This project is licensed under the GNU GENERAL PUBLIC LICENSE license - see the LICENSE file for details.

Acknowledgments

Part of the funding that made this module possible has been provided by the Swiss National Science Foundation through the FNS Research Project 182236.