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Download the repository institution-evolution on your local machine.
⚠️ Non-values are marked with -99 in output files: Be mindful there when analyzing data! For instance, when technology level is not recorded in the simulation, the corresponding output file will show a mean technology level of -99 for every generation.
Scipy and Numpy for running simulations, Pytest to test code. To install all requirements, run: pip install -r requirements.txt
This code is written under Python 3.7.3
Set parameters as desired in pars folder:
- fitness_parameters.txt: specific to fitness function used. For now, only Public Goods Games (PGG)
- initial_phenotypes.txt: \n for each new trait
- parameters.txt: general parameters
- mutation rate,
- mutation variance,
- migration rate
- initialisation.txt:
- number of demes (i.e. sub-populations)
- initial size of demes (number of individuals in each sub-population)
- number of generations (iterations) to run.
python script_single_simulation.py
python script_parameter_space.py