FAME-Io

Prepare input and digest output from simulation models

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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 component workflow

FAME-Io combines model data and user's agent configurations to create a simulation input file for computations with FAME-Core. Once these computations have finished, FAME-Io converts the simulation output file and returns its contents 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.

Installation

FAME-Io requires Python 3.10 or higher. We recommend installing fameio using PyPI: pip install fameio

Usage

FAME-Io offers three command-line scripts:

  • compile: compiles a protobuf file for FAME applications using YAML definition files and CSV files,
  • extract: takes an output file in protobuf format of FAME-based applications and converts it into files in CSV / JSON format,
  • transform: takes CSV time series files and reformats them into FAME time format to speed up the first command.

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 and Code of Conduct.

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.

Acknowledgements

The development of FAME-Io was funded by the German Aerospace Center (DLR). We express our gratitude to all contributors.

Project links

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PyPI data
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Credits

Author/Maintainer: Felix Nitsch

License expression

Apache-2.0
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Requires

Python <3.15, >=3.10

Tags

FAME fameio agent-based modelling energy systems

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