Utilities to set up and analyze Modelica simulation experiments
- Auto-generate simulation scripts,
- Browse data,
- Perform custom calculations, and
- Produce various plots and diagrams.
The figures are generated via matplotlib, which offers a rich set of plotting routines. ModelicaRes includes convenient functions to automatically pre-format and label some figures, like xy plots, Bode and Nyquist plots, and Sankey diagrams. ModelicaRes can be scripted or run from a Python interpreter with math and matrix functions from NumPy.
An installable copy of this package can be downloaded from the main project site or the PyPI page. After extracting the package, run the set up script (setup.py) from the base folder. On Windows, use the following command:
python setup.py install
On Linux, use:
sudo python setup.py install
The matplotlibrc file in the bin folder has some recommended revisions to matplotlib’s defaults. To use it, move or copy the file to the working directory or matplotlib’s configuration directory. See http://matplotlib.org/users/customizing.html for details.
The main author is Kevin Davies. Kevin Bandy also helped with the development. Third-party code has been included from:
License terms and development
ModelicaRes is published under the terms of the BSD license (see LICENSE.txt). Please share any modifications you make (preferably on a Github fork from https://github.com/kdavies4/ModelicaRes) so that others may benefit from your work. If you find a bug, please report it. If you have suggestions for improvements, please share them here.
The following Python projects are related:
- awesim: helps run simulation experiments and organize results
- BuildingsPy: supports unit testing
- DyMat: exports Modelica simulation data to comma-separated values (CSV), Gnuplot, MATLAB®, and Network Common Data Form (netCDF)
- PyFMI: tools to work with models through the Functional Mock-Up Interface (FMI) standard
- pysimulator: elaborate GUI; supports FMI