Symbulation is an artificial life software tool for agent-based modeling of the evolution of biological symbiosis, which can occur along the spectrum between parasitism and mutualism.
Try out our browser-based GUI. See our documentation at https://symbulation.readthedocs.io.
Interested in starting a new project with Symbulation? We have a cookiecutter template here: https://github.com/anyaevostinar/SymbulationProjectTemplate.
Symbulation is built with the Empirical platform and the cookiecutter includes our recommended directory layout and example analysis files.
Install the latest Cookiecutter:
pip install -U cookiecutter
Generate an Symbulation project:
cookiecutter https://github.com/anyaevostinar/SymbulationProjectTemplate.git
Move into the new project directory and the SymbulationEmp directory and make:
cd SymbulationProject/SymbulationEmp
make
Make any changes that you wish to the file SymSettings.cfg and then run:
./symbulation_default
By default, your data will be output to the files HostVals_data__SEED10.data and SymVals_data__SEED10.data.
We recommend that you copy your symbulation executable to your Data folders:
cp symbulation_default ../Data/sample_treatment
cd ../Data/sample_treatment
You can then use the provided Python script to run several replicates:
python3 simple_repeat.py
You can also then use the provided Python script to transform your data into a format more easily used by R:
cd ../../Analysis/sample_treatment
python3 munge_data.py
And then open our provided R script SampleAnalysis.R in R, set your working directory to the Analysis directory and then run all lines to observe the effect of vertical transmission rate on the interaction value evolved.
SGP-mode is a prototype and untested.
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Vostinar et al. (2024). Empirical: A scientific software library for research, education, and public engagement. Journal of Open Source Software, 9(98), 6617. https://doi.org/10.21105/joss.06617.
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Moreno, Matthew Andres, et al. "SignalGP-Lite: Event Driven Genetic Programming Library for Large-Scale Artificial Life Applications." arXiv preprint arXiv:2108.00382 (2021). https://arxiv.org/pdf/2108.00382
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Dolson, Emily, Santiago Rodriguez-Papa, and Matthew Andres Moreno. "Phylotrack: C++ and python libraries for in silico phylogenetic tracking." arXiv preprint arXiv:2405.09389 (2024) https://arxiv.org/pdf/2405.09389
Anya Vostinar, Piper Welch, K-Johnson-Horrigan, Alison Cameron, Lilith Orion Hafner, Emily Dolson, dorchens, Caroline Gormely, renztim, Charles Ofria, Yi Qin, & mkmmnn. (2022). anyaevostinar/SymbulationEmp: Modes (v0.2). Zenodo. https://doi.org/10.5281/zenodo.6380543
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