def main(parameters):
simulation = Simulation(rounds=parameters['rounds'], processes=1)
simulation.declare_round_endowment(resource='adult', units=1, product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('household', possessions=['money', 'GOOD'],
variables=['current_utiliy'])
simulation.panel('firm', possessions=['money', 'GOOD'],
variables=['price', 'inventory'])
firms = simulation.build_agents(Firm, 'firm', number=parameters['num_firms'])
households = simulation.build_agents(Household, 'household', number=1, parameters=parameters)
for r in simulation.next_round():
households.do('sell_labor')
firms.do('buy_labor')
firms.do('production')
firms.do('panel')
firms.do('quotes')
households.do('buy_goods')
firms.do('sell_goods')
households.do('aggregate')
households.do('consumption')
firms.do('adjust_price')
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
simulation.declare_round_endowment(resource={'labor_endowment': 1},
product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('household', possessions=[], # put a list of household possessions to track here
variables=['count']) # put a list of household possessions to track here
simulation.aggregate('firm', possessions=[], # put a list of household possessions to track here
variables=['count']) # put a list of household possessions to track here
firms = simulation.build_agents(Firm, 'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters)
households = simulation.build_agents(Household, 'household',
number=simulation_parameters['households'],
parameters=simulation_parameters)
messengers = simulation.build_agents(Messenger, 'messenger', 1)
for r in simulation.next_round():
messengers.do('messaging')
(firms+households).do('receive_message')
firms.do('add_household')
firms.do('add_firm')
firms.do('print_id')
households.do('print_id')
# this instructs ABCE to save panel data as declared below
(firms+households).do('aggregate')
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
simulation.declare_calendar(2000, 1, 1)
simulation.panel('agent', possessions=['money'])
simulation.aggregate('agent', possessions=['labor'])
agents = simulation.build_agents(Agent, 'agent', number=1)
for r in simulation.next_round():
date = simulation._round
if date.weekday() == 2:
agents.do('wednessday')
if date.day == 1:
agents.do('first')
if date.month == 12 and date.day == 31:
agents.do('newyearseve')
if date.day <= 7 and date.weekday() == 4:
agents.do('firstfriday')
if date.month == 15:
agents.do('fiveteens')
if date.toordinal() % 3 == 0:
agents.do('everythreedays')
agents.do('panel')
agents.do('aggregate')
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
action_list = [('firm', 'one'),
('household', 'two'),
('all', 'three')
('household', 'panel')] # this instructs ABCE to save panel data as declared below
simulation.add_action_list(action_list)
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor'
)
simulation.declare_perishable(good='labor')
simulation.panel('household', possessions=['good1', 'good2'], # put a list of household possessions to track here
variables=['utility']) # put a list of household possessions to track here
simulation.build_agents(Firm, 'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters)
simulation.build_agents(Household, 'household',
number=simulation_parameters['households'],
parameters=simulation_parameters)
simulation.run()
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
action_list = [
('firm', 'one'), ('household', 'two'), ('all', 'three')('household',
'panel')
] # this instructs ABCE to save panel data as declared below
simulation.add_action_list(action_list)
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.panel(
'household',
possessions=['good1', 'good2'
], # put a list of household possessions to track here
variables=['utility'
]) # put a list of household possessions to track here
simulation.build_agents(Firm,
'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters)
simulation.build_agents(Household,
'household',
number=simulation_parameters['households'],
parameters=simulation_parameters)
simulation.run()
simulation.graphs()
def main(parameters):
simulation = Simulation(rounds=parameters['rounds'], cores=1)
action_list = [
('household', 'sell_labor'),
('firm', 'buy_labor'),
('firm', 'production'),
('firm', 'panel'),
('firm', 'quotes'),
('household', 'buy_goods'),
('firm', 'sell_goods'),
('household', 'aggregate'),
('household', 'consumption'),
('firm', 'adjust_price')]
simulation.add_action_list(action_list)
simulation.declare_round_endowment(resource='adult', units=1, product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('household', possessions=['money', 'GOOD'],
variables=['current_utiliy'])
simulation.panel('firm', possessions=['money', 'GOOD'],
variables=['price', 'inventory'])
simulation.build_agents(Firm, 'firm', number=parameters['num_firms'])
simulation.build_agents(Household, 'household', number=1, parameters=parameters)
simulation.run()
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
action_list = [('killer', 'kill'),
('agent', 'am_I_dead'),
('killer', 'send_message'),
('agent', 'aggregate'),
('agent', 'panel')] # this instructs ABCE to save panel data as declared below
simulation.add_action_list(action_list)
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor'
)
simulation.declare_perishable(good='labor')
simulation.aggregate('agent', possessions=[], variables=['count'])
simulation.panel('agent', possessions=[], variables=['idn'])
simulation.build_agents(Agent, 'agent',
number=simulation_parameters['agents'],
parameters=simulation_parameters)
simulation.build_agents(Killer, 'killer',
number=1,
parameters=simulation_parameters)
simulation.run()
simulation.graphs()
def main(parameters):
simulation = Simulation(rounds=parameters['rounds'], processes=1)
simulation.declare_round_endowment(resource='adult',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('household',
possessions=['money', 'GOOD'],
variables=['current_utiliy'])
simulation.panel('firm',
possessions=['money', 'GOOD'],
variables=['price', 'inventory'])
firms = simulation.build_agents(Firm,
'firm',
number=parameters['num_firms'])
households = simulation.build_agents(Household,
'household',
number=1,
parameters=parameters)
for r in simulation.next_round():
households.do('sell_labor')
firms.do('buy_labor')
firms.do('production')
firms.do('panel')
firms.do('quotes')
households.do('buy_goods')
firms.do('sell_goods')
households.do('aggregate')
households.do('consumption')
firms.do('adjust_price')
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('agent', possessions=[], variables=['count'])
simulation.panel('agent', possessions=[], variables=['idn'])
agents = simulation.build_agents(Agent, 'agent',
number=simulation_parameters['agents'],
parameters=simulation_parameters)
killers = simulation.build_agents(Killer, 'killer',
number=1,
parameters=simulation_parameters)
for r in simulation.next_round():
killers.do('kill')
agents.do('am_I_dead')
killers.do('send_message')
agents.do('aggregate')
agents.do('panel')
simulation.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'])
s.declare_service('labor_endowment', 1, 'labor')
network = create_network(simulation_parameters['num_firms'])
network = [
network.neighbors(neighbor)
for neighbor in range(simulation_parameters['num_firms'])
]
firms = s.build_agents(Firm,
'firm',
parameters=simulation_parameters,
agent_parameters=network)
household = s.build_agents(Household,
'household',
1,
parameters=simulation_parameters)
centralbank = s.build_agents(CentralBank,
'centralbank',
1,
parameters=simulation_parameters)
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(possessions=['money'],
variables=['utility', 'rationing'])
firms.agg_log(possessions=['money'],
variables=[
'produced', 'profit', 'price', 'dead', 'inventory',
'rationing'
])
s.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate(
'household',
possessions=[], # put a list of household possessions to track here
variables=['count'
]) # put a list of household possessions to track here
simulation.aggregate(
'firm',
possessions=[], # put a list of household possessions to track here
variables=['count'
]) # put a list of household possessions to track here
firms = simulation.build_agents(Firm,
'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters)
households = simulation.build_agents(
Household,
'household',
number=simulation_parameters['households'],
parameters=simulation_parameters)
messengers = simulation.build_agents(Messenger, 'messenger', 1)
for r in simulation.next_round():
messengers.do('messaging')
(firms + households).do('receive_message')
firms.do('add_household')
firms.do('add_firm')
firms.do('print_id')
households.do('print_id')
# this instructs ABCE to save panel data as declared below
(firms + households).do('aggregate')
simulation.graphs()
def main():
simulation = Simulation(name="NORI Token Market Simulation v0.1")
print(simulation)
# simulation.declare_round_endowment() IS THIS NECESSARY?
suppliers = simulation.build_agents(
Supplier, 'supplier',
100) # Put these in parameters.csv and use .build_agents_from_file
simulation.build_agents(Spotbuyer, 'spotbuyer', 100)
simulation.build_agents(Speculator, 'speculator', 1000)
simulation.build_agents(Coinex, 'coinex', 1)
# Create supplier_queue from 'crc_supply_sample.csv' in order returned from the code in lines 70-75, above
# Each supplier has an associated marginal_cost and marginal_qty
# For supplier i, if expected_price >= reserve_price,
# list_crc and remove from queue
# else evaluate the next element in list
# LIKE THIS?
# Make 100 suppliers
#for supplier_number in range(100):
# new_supplier = {'marginal_cost': X, 'marginal_qty': Y, 'expected_price': Z}
# supplier_queue.append(new_supplier)
for round in range(360): # Assume 360 trading days per year
simulation.advance_round(round)
Supplier().self.list_crc(
) # IS THIS THE RIGHT WAY TO DO THIS? Supplier lists CRC if expected_price > marginal_cost
spotbuyer.buy_nori() # Spot Buyer buys NORI from Coinex
coinex.exch_sell_nori() # Coinex sells NORI to Spot Buyer
spotbuyer.buy_crc() # Spot Buyer purchases CRC
spotbuyer.retire_crc() # Spot Buyer (smart contract) retires CRC
(supplier + spotbuyer()).panel_log(...) # Log CRC trades
speculator.trade_nori() # Speculators trade
supplier.sell_nori() # Supplier sells NORI to Coinex
speculator.sell_nori() # Speculator sells NORI to Coinex
coinex.exch_buy_nori() # Coinex buys
coinex.panel_log(...) # Log NORI trades
# Do we need to clear trades? If so, how?
simulation.graphs()
simulation.finalize()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['scheduledEndTime'],
processes=1)
insurancefirms = simulation.build_agents(
InsuranceFirm,
'insurancefirm',
number=simulation_parameters['numberOfInsurers'],
parameters=simulation_parameters)
insurancecustomers = simulation.build_agents(
InsuranceCustomer,
'insurancecustomer',
number=simulation_parameters['numberOfRiskholders'],
parameters=simulation_parameters)
allagents = insurancefirms + insurancecustomers
#pdb.set_trace()
events = defaultdict(list)
for round in simulation.next_round():
new_events = insurancecustomers.do('randomAddRisk')
for risk in events[round]:
new_events += [risk.explode(round)]
for event_time, risk in new_events:
if event_time is not None:
event_time = math.ceil(event_time)
events[event_time].append(risk)
assert isinstance(event_time, int)
assert risk is not None
assert event_time >= round
(insurancefirms + insurancecustomers).do('mature_contracts')
insurancefirms.do('quote')
insurancecustomers.do('subscribe_coverage')
insurancefirms.do('add_contract')
allagents.do('filobl')
insurancecustomers.do('check_risk')
simulation.graphs()
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):
simulation = Simulation(rounds=simulation_parameters['rounds'],
name='ABCEsimulation_name')
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.panel(
'household',
possessions=['good1', 'good2'
], # put a list of household possessions to track here
variables=['utility'
]) # put a list of household possessions to track here
firms = simulation.build_agents(Firm,
'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters)
households = simulation.build_agents(
Household,
'household',
number=simulation_parameters['households'],
parameters=simulation_parameters)
allagents = firms + households
try: # makes sure that graphs are displayed even when the simulation fails
for round_number in simulation.next_round():
firms.do('one')
households.do('two')
allagents.do('three')
households.do('panel')
except Exception as e:
print(e)
finally:
simulation.graphs()
def main(simulation_parameters):
simulation = Simulation(rounds=simulation_parameters['rounds'])
action_list = [('messenger', 'messaging'),
(('firm', 'household'), 'receive_message'),
('firm', 'add_household'),
('firm', 'add_firm'),
('firm', 'print_id'),
('household', 'print_id'),
(('firm', 'household'), 'aggregate')] # this instructs ABCE to save panel data as declared below
simulation.add_action_list(action_list)
simulation.declare_round_endowment(resource='labor_endowment',
units=1,
product='labor')
simulation.declare_perishable(good='labor')
simulation.aggregate('household', possessions=[], # put a list of household possessions to track here
variables=['count']) # put a list of household possessions to track here
simulation.aggregate('firm', possessions=[], # put a list of household possessions to track here
variables=['count']) # put a list of household possessions to track here
simulation.build_agents(Firm, 'firm',
number=simulation_parameters['firms'],
parameters=simulation_parameters, expandable=True)
simulation.build_agents(Household, 'household',
number=simulation_parameters['households'],
parameters=simulation_parameters, expandable=True)
simulation.build_agents(Messenger, 'messenger', 1)
simulation.run()
simulation.graphs()