def main():
s = Simulation(processes=1)
grid = MultiGrid(50, 50, True)
# build sugar and spice
sugar_distribution = pylab.genfromtxt("sugar-map.txt")
spice_distribution = sugar_distribution.T
sugars = []
spices = []
for _, x, y in grid.coord_iter():
max_sugar = sugar_distribution[x, y]
max_spice = spice_distribution[x, y]
sugar = SugarPatch((x, y), max_sugar)
spice = SpicePatch((x, y), max_spice)
sugars.append(sugar)
spices.append(spice)
grid.place_agent(sugar, (x, y))
grid.place_agent(spice, (x, y))
# build agents
agents = s.build_agents(SsAgent, 'SsAgent', 100, parameters={'grid': grid})
# prices = []
for r in range(100):
s.advance_round(r)
for sugar in sugars:
sugar.step()
for spice in spices:
spice.step()
agents.move()
agents.eat()
print(',', len(agents.trade_with_neighbors()))
agents.trade()
agents.agg_log(possessions=['sugar', 'spice'])
s.graphs()
def main():
simulation_parameters = {
'name': 'direct_optimization',
'random_seed': None,
'rounds': 500,
'trade_logging': 'off',
'num_firms': 250,
'alpha': 0.3,
'gamma': 0.8,
'price_stickiness': 0.0,
'network_weight_stickiness': 0.0,
'wage_stickiness': 0.0,
'dividends_percent': 0.0,
'percentage_beneficiaries': 0.25,
'percentage_injection': 0.25,
'time_of_intervention': 250
}
s = Simulation(name=simulation_parameters['name'])
network = create_network(simulation_parameters['num_firms'])
network = [{
'neighbors': network.neighbors(neighbor)
} for neighbor in range(simulation_parameters['num_firms'])]
firms = s.build_agents(Firm,
'firm',
**simulation_parameters,
agent_parameters=[n for n in network])
household = s.build_agents(
Household,
'household',
1,
num_firms=simulation_parameters['num_firms'],
wage_stickiness=simulation_parameters['wage_stickiness'])
centralbank = s.build_agents(
CentralBank,
'centralbank',
1,
time_of_intervention=simulation_parameters['time_of_intervention'],
percentage_injection=simulation_parameters['percentage_injection'],
percentage_beneficiaries=simulation_parameters[
'percentage_beneficiaries'])
for rnd in range(simulation_parameters['rounds']):
s.advance_round(rnd)
(firms + household).send_demand()
(firms + household).selling()
(firms + household).buying()
firms.production()
firms.dividends()
household.consuming()
firms.change_weights()
firms.stats()
centralbank.intervention()
household.agg_log(goods=['money'], variables=['utility', 'rationing'])
firms.agg_log(goods=['money'],
variables=[
'produced', 'profit', 'price', 'dead', 'inventory',
'rationing'
])
(household + firms).refresh_services('labor',
'labor_endowment',
units=1)
s.graphs()