FAME-Io: Tools for input preparation and output digestion of FAME models

Prepare input and digest output from simulation models

FAME-Io compiles input for FAME models and extracts model output to human-readable files. Model data is handled in the efficient protobuf format.
FAME is the open Framework for distributed Agent-based Models of Energy systems. Check out the full FAME-Io documentation.

What is FAME-Io?

FAME-Io is the input-output toolkit for FAME-based simulation models. The relationship to other components can be seen below.

FAME-Io (orange) combines model data (purple) and user input data (green) for the computation (blue). After the computation, FAME-Io returns the results in a readable format.

Thus, with FAME-Io you can:

• Compile input binaries for simulation models built with FAME,
• Extract output binaries to human-readable formats like CSV and JSON,
• Edit large CSV files to enhance compilation speed.

Who is FAME-Io for?

FAME-Io is a vital file-conversion component for FAME-based workflows. If your model is not built with FAME, you will probably not profit from FAME-Io.

Applications

FAME-Io is used with any model that is based on FAME. An example of its application is the electricity market model AMIRIS.

Community

FAME-Io is mainly developed by the German Aerospace Center, Institute of Networked Energy Systems. We provide support via the dedicated email address fame@dlr.de.

We welcome all contributions: bug reports, feature requests, documentation enhancements, and code.
For substantial enhancements, we recommend that you contact us via fame@dlr.de for working together on the code in common projects or towards common publications and thus further develop FAME-Io.
Please see our Contribution Guidelines.

Citing FAME-Io

If you use FAME-Io in academic work, please cite: DOI 10.21105/joss.04958

@article{fameio2023joss,
  author  = {Felix Nitsch and Christoph Schimeczek and Ulrich Frey and Benjamin Fuchs},
  title   = {FAME-Io: Configuration tools for complex agent-based simulations},
  journal = {Journal of Open Source Software},
  year    = {2023},
  doi     = {doi: https://doi.org/10.21105/joss.04958}
}

In other contexts, please include a link to our Gitlab repository.