Python library for Rational Reduced Order Modeling
Bumped version to 2.2
Fixed shifting issue.
Fixed overflow in ev tolerance check. Added warning management for computation…
Added colormap selection in plotting.
Forced rescaling of derivatives in approximant computation.
Added scaling in derivative sampling.
Allowed for E different from N in rational MOR. Modified tests accordingly.
Added missing parentheses for termination during error computation. Moved…
Fixed placement of scale factor computation routine.
Fixed inconsistent number of columns in projection matrix.
Fixed remaining verbosity levels.
Fixed inconsistent verbosity levels in greedy.
Renamed INTERPOLATORY estimator to LOOK_AHEAD_RES. Simplified estimator…
Fixed minor verbosity issue.
Module for the solution and rational model order reduction of parametric PDE-based problem. Coded in Python 3.6.
- numpy and scipy;
- fenics and mshr;
- and other standard Python3 modules (os, typing, time, datetime, abc, pickle, traceback, and itertools).
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 provided conda-fenics.yml environment file by running the command
conda env create --file conda-fenics.yml
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
source activate fenicsenv
Clone the repository
git clone https://c4science.ch/source/RROMPy.git
enter the main folder and install the package by typing
python3 setup.py install
The installation can be tested with
python3 setup.py test
This project is licensed under the GNU GENERAL PUBLIC LICENSE license - see the LICENSE file for details.
Part of the funding that made this module possible has been provided by the Swiss National Science Foundation through the FNS Research Project No. 182236.