Python library for Rational Reduced Order Modeling
Diffusion RationalROMPy (master)
Recent Commits
Recent Commits
| Commit | Author | Details | Committed | ||||
|---|---|---|---|---|---|---|---|
| 4cc6ac15d19c | pradovera | Version 2.6 | Apr 1 | ||||
| a9d849586c87 | pradovera | Bumped version to 2.6 | Apr 1 | ||||
| d70b108a7710 | pradovera | Added empty parameter sampler to simplify initialization of NN approximants. | Apr 1 | ||||
| 4dd4e40c3c9e | pradovera | Merging branch for snapshot storage into develop branch. | Apr 1 | ||||
| 26b5e900c13d | pradovera | Improved NN approximant with support-value structure for compatibility with… | Apr 1 | ||||
| a415fe2091d0 | pradovera | Bug fixes. Added sample load from list of filenames. Pivoted approximants can… | Apr 1 | ||||
| 900b7652ad20 | pradovera | Fixed naming issue in HDF5 file creation for fenics mesh serialization. | Apr 1 | ||||
| 115d485aaa9c | pradovera | Added support for snapshot storage from approximants. Storage for pivoted… | Apr 1 | ||||
| b3fb8983f0fd | pradovera | Changed sampling engines so that samples always contains non-orthogonalized… | Apr 1 | ||||
| 1482cb3bfb4a | pradovera | Ordered test folders for consistency. | Mar 31 | ||||
| 99c9db10ec8f | pradovera | Forced approximants to have no sample memory. Fixed broken imports of sampling… | Mar 31 | ||||
| d0fa1960b013 | pradovera | Erased pivoted sampling engines. Added storage functionality for sampling… | Mar 31 | ||||
| a35824b905df | pradovera | Improved parallelism in approximants by using v-communications if possible. | Mar 31 | ||||
| 22f2e4dda93d | pradovera | Improved parallelism efficiency with v-communications. Removed option to… | Mar 31 | ||||
| 5be0ac5adcd1 | pradovera | Minor bug fixes. | Mar 31 |
README.md
README.md
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;
- and other standard Python3 modules (os, typing, time, datetime, abc, pickle, traceback, and 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 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.
Installing
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
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.
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