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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

- 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`_.


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 install

Or, on Linux::

sudo python 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
- PyQt4_ can be downloaded from
- wxPython_ can be downloaded from
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 for details.


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 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_

.. _main website:
.. _release branch at GitHub:
.. _PyPI page:

.. _Modelica:
.. _Python:
.. _pandas:
.. _matplotlib:
.. _NumPy:
.. _SciPy:
.. _PyQt4:
.. _wxPython:
.. _pip:
.. _awesim:
.. _BuildingsPy:
.. _DyMat:
.. _PyFMI:
.. _PySimulator:
.. _Gnuplot:
.. _CSV:
.. _netCDF:
.. _FMI:
.. _python-control:
.. _ArrowLine:
.. _efficient base-10 logarithm:

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ModelicaRes-0.11.0.tar.gz (858.9 kB) Copy SHA256 hash SHA256 Source None May 21, 2014

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