autofmu

Python package Documentation Status Coverage status Black code style

Automatic FMU approximation tool.

Installation

Compilers

To correctly build an FMU this program needs to compile the generated C source into a shared library, therefore it requires the installation of C compilers.

If you are using the provided docker image to run the program then you are already able to cross compile the generated FMU to linux32, linus64, win32 and win64 platforms.

Otherwise if you are using a Linux distribution, you probably already have gcc installed, so you should be able to compile FMUs for your system. If you want to share the generated FMU it is advisable to also install a cross compiler to produce the binaries for Windows platforms (like MinGW). Below are the instructions to install with apt and dnf:

Debian/Ubuntu:

sudo apt install gcc-x86-64-linux-gnu gcc-i686-linux-gnu gcc-mingw-w64 gcc-mingw-w64-i686

Fedora:

sudo dnf install gcc-x86_64-linux-gnu mingw64-gcc mingw32-gcc

Usage

autofmu process a dataset

autofmu "dataset.csv" --inputs "x" "y" --outputs "z" -o "My Awesome Model.fmu"

This will read the dataset.csv file, select the x, y and z columns and find an approximation of the relation between the inputs and the outputs. Based on this relation, the sources files for the FMU will be generated and compiled, resulting in the My Awesome Model.fmu file ready to be used for simulations.

Contributing

License

This project is licensed under MIT license.


Table of contents

Indices and tables