Python library for Rational Reduced Order Modeling
Bumped version to 2.6
Added empty parameter sampler to simplify initialization of NN approximants.
Merging branch for snapshot storage into develop branch.
Improved NN approximant with support-value structure for compatibility with…
Bug fixes. Added sample load from list of filenames. Pivoted approximants can…
Fixed naming issue in HDF5 file creation for fenics mesh serialization.
Added support for snapshot storage from approximants. Storage for pivoted…
Changed sampling engines so that samples always contains non-orthogonalized…
Ordered test folders for consistency.
Forced approximants to have no sample memory. Fixed broken imports of sampling…
Erased pivoted sampling engines. Added storage functionality for sampling…
Improved parallelism in approximants by using v-communications if possible.
Improved parallelism efficiency with v-communications. Removed option to…
Minor bug fixes.
Module for the solution and rational model order reduction of parametric PDE-based problem. Coded in Python 3.
- numpy and scipy;
- fenics and mshr;
- and other standard Python3 modules (os, typing, time, datetime, abc, pickle, traceback, and itertools).
conda create -n fenicsenv -c conda-forge pytest scipy matplotlib fenics mshr
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.
Clone the repository
git clone http://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 182236.