Python implementation of the Human and Nature Dynamics (HANDY) model (http://www.atmos.umd.edu/~ekalnay/pubs/2014-03-18-handy1-paper-draft-safa-motesharrei-rivas-kalnay.pdf)
NOTE: The authors of the HANDY model are not associated with this implementation or endorses it.
From source:
$ python setup.py install
pyhandy requires scipy >= 0.10.0 and matplotlib
pyhandy support running and plotting predefined society evolutions from the command line e.g.
$ handy_model_run.py equitable cyclic 1000
resulting in the following plot being shown:
To see the full set of supported society types supported by the command line tool run
$ handy_model_run.py -h
pyhandy supports custom society calculations by using the Society class from pyhandy.handy
The Society class takes the following arguments as initial conditions for a society:
- min_required_consumption
- output_division
- salary
- commoner_population
- elite_population
- nature
- nature_regeneration
- nature_capacity
- depletion
- wealth
- commoner_birth_rate,
- elite_birth_rate
- normal_death_rate
- famine_death_rate
- year
It should be straight forward to match the variable names with the notation used in http://www.atmos.umd.edu/~ekalnay/pubs/2014-03-18-handy1-paper-draft-safa-motesharrei-rivas-kalnay.pdf
Variable values for the scenarios shown in the article can be found in the dict pyhandy.handy.socity_types
First initialize society:
>>> from pyhandy import handy
>>> my_soc = handy.Society(*handy.socity_types['unequal']['soft'])
then run the society simulation for a specified number of years
>>> time, commoner_population, elite_population, nature, wealth, carrying_capacity = my_soc.evolve(1000)
all of the result variables are lists with a value for each simulation timestep.
The result can be plotted using:
>>> handy.plot_society(time, commoner_population, elite_population, nature, wealth, carrying_capacity)
Copyright (C) 2014 Esben S. Nielsen
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