FAME-Io
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 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.
1 maintainer
Metadata
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Release files for fameio 4.0.1
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| fameio-4.0.1.tar.gz | 89.1 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| fameio-4.0.1-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 225.1 kB
Release files / fameio-4.0.1.tar.gz
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| Download URL | fameio-4.0.1-py3-none-any.whl |
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