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Set up, analyze, and plot Modelica simulations in Python
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README.md

ModelicaRes

Set up and analyze Modelica simulations in Python

ModelicaRes is a free, open-source tool that can be used to

Plot of Chua circuit with varying parameters  Sankey diagram of three tanks example  Bode diagram of PID with varying parameters

The goal of ModelicaRes is to leverage Python to make these tasks easy and complex tasks feasible. Publication-quality figures can be created with matplotlib using built-in methods that automatically add titles, labels, and legends. 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.

Currently, ModelicaRes only loads Dymola/OpenModelica-formatted binary and text results (*.mat and *.txt), but the interface is modular so that other formats can be added easily.

Installation

First, install the dependencies. Most are installed automatically, but SciPy >= 0.10.0 must be installed according to the instructions at http://www.scipy.org/install.html. The GUIs require Qt, which can be installed via PyQt4, guidata, or PySide.

Then install ModelicaRes. The easiest way is to use pip:

> pip install modelicares

On Linux, it may be necessary to have root privileges:

$ sudo pip install modelicares

The matplotlibrc file 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.

License terms and development

ModelicaRes is published under a BSD-compatible license. Please share any improvements you make, preferably as a pull request to the master branch of the GitHub repository. There are useful development scripts in the hooks folder. If you find a bug, have a suggestion, or just want to leave a comment, please open an issue.

Build Status  Code Health

See also

  • awesim: helps run simulation experiments and organize results
  • BuildingsPy: supports unit testing
  • DyMat: exports Modelica simulation data to 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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