Utilities to set up and analyze Modelica simulation experiments
Project description
Utilities to set up and analyze Modelica simulation experiments
ModelicaRes is a free, open-source tool to conveniently manage Modelica simulations, interpret results, and create publishable figures. It is possible to
auto-generate simulation scripts,
browse data,
perform custom calculations,
produce various plots and diagrams, and
export data to various formats via pandas.
The figures are generated via matplotlib, which offers a rich set of plotting routines. ModelicaRes includes functions to automatically pre-format and label some figures, like xy plots, Bode and Nyquist plots, and Sankey diagrams. ModelicaRes can be scripted or used in an interactive Python session with math and matrix functions from NumPy.
Please see the tutorial, which is available as an IPython notebook or online as a static page. For the full documentation and many more examples, see the main website.
Installation
The easiest way to install this package is to use pip:
pip install modelicares
On Linux, it may be necessary to have root privileges:
sudo pip install modelicares
Another way is to download and extract a copy of the package. The main website and the release branch at GitHub have copies with built documentation and compiled examples. The copy on the PyPI page only has the files to install the package, build the documentation, and execute the examples. Once you have a copy, run the following command from the base folder:
python setup.py install
Or, on Linux:
sudo python setup.py install
Some of the required packages may not install automatically.
The SciPy stack, including matplotlib and pandas, can be installed according to the instructions at http://www.scipy.org/install.html.
PyQt4 can be downloaded from http://www.riverbankcomputing.co.uk/software/pyqt/download.
wxPython can be downloaded from http://www.wxpython.org/download.php. However, it is only required for the variable browser.
The matplotlibrc file in the base folder has some recommended revisions to matplotlib’s defaults. To use it, copy it to the working directory or matplotlib’s configuration directory. See http://matplotlib.org/users/customizing.html for details.
Credits
The main author is Kevin Davies. Code has been included from:
Richard Murray (python-control, as repackaged by James Goppert),
Joerg Raedler (method to expand a Modelica variable tree—from DyMat),
Jason Grout (ArrowLine class), and
Jason Heeris (efficient base-10 logarithm),
Suggestions and bug fixes have been provided by Arnout Aertgeerts, Kevin Bandy, Thomas Beutlich, Martin Sjölund, Mike Tiller, and Michael Wetter.
License terms and development
ModelicaRes is published under a BSD-compatible license. The development site is https://github.com/kdavies4/ModelicaRes. Please share any modifications you make (preferably as a pull request to the master branch at that site) in order to help others. If you find a bug, please report it. If you have suggestions, please share them.
See also
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
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