Beispiel #1
0
def main(parameters):
    simulation = Simulation(processes=1)
    simulation.declare_round_endowment(resource='adult',
                                       units=1,
                                       product='labor')
    simulation.declare_perishable(good='labor')

    firms = simulation.build_agents(Firm,
                                    'firm',
                                    number=parameters['num_firms'])
    households = simulation.build_agents(Household,
                                         'household',
                                         number=1,
                                         parameters=parameters)

    try:
        for rnd in range(parameters['rounds']):
            simulation.advance_round(rnd)
            households.sell_labor()
            firms.buy_labor()
            firms.production()
            firms.panel_log(possessions=['money', 'GOOD'],
                            variables=['price', 'inventory'])
            firms.quotes()
            households.buy_goods()
            firms.sell_goods()
            households.agg_log(possessions=['money', 'GOOD'],
                               variables=['current_utiliy'])
            households.consumption()
            firms.adjust_price()
    except Exception as e:
        print(e)
Beispiel #2
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def main():
    parameters = {'name': 'name', 'rounds': 300}

    s = Simulation(rounds=parameters['rounds'], cores=8)
    action_list = [  # (('myagent', 'youragent'), 'compute'),
        ('youragent', 's'), ('myagent', 'g')
    ]
    s.add_action_list(action_list)

    s.build_agents(MyAgent, 50000)
    s.build_agents(YourAgent, 50000)

    s.run()
Beispiel #3
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def main():
    parameters = {'name': 'name', 'num_rounds': 10}

    s = Simulation(parameters)
    action_list = [  # (('myagent', 'youragent'), 'compute'),
        ('youragent', 's'), ('myagent', 'g')
    ]
    s.add_action_list(action_list)

    s.build_agents(MyAgent, 50000)
    s.build_agents(YourAgent, 50000)

    s.run(parallel=True)
Beispiel #4
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def main(parameters):
    simulation = Simulation(processes=1)

    firms = simulation.build_agents(Firm,
                                    'firm',
                                    number=parameters['num_firms'])
    households = simulation.build_agents(Household,
                                         'household',
                                         number=1,
                                         parameters=parameters)

    try:
        for rnd in range(parameters['rounds']):
            simulation.advance_round(rnd)
            households.refresh_services('labor', derived_from='adult', units=1)
            households.sell_labor()
            firms.buy_labor()
            firms.production()
            firms.panel_log(possessions=['money', 'GOOD'],
                            variables=['price', 'inventory'])
            firms.quotes()
            households.buy_goods()
            firms.sell_goods()
            households.agg_log(possessions=['money', 'GOOD'],
                               variables=['current_utiliy'])
            households.consumption()
            firms.adjust_price()
    except Exception as e:
        print(e)
    simulation.finalize()
Beispiel #5
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def main():
    for params in simulation_parameters:
        s = Simulation(params)

        s.declare_round_endowment('field', 60, 'corn')
        s.declare_round_endowment('shares', 60, 'money')

        f = s.build_agents(Firm, 'firm', 1)
        h = s.build_agents(Household, 'household', 1)
        for r in s.next_round():
            for i in range(60):
                f.do('selling')
                h.do('buying')
                h.do('checking')

        s.run()
Beispiel #6
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def main(simulation_parameters):
    simulation = Simulation(
        rounds=simulation_parameters['rounds'], processes=2)

    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)

    for round in simulation.next_round():
        print('one')
        (firms + households).do('one')
        #pprint({k: str(v) for k, v in simulation.mlist.items()})
        print('two')
        (firms + households).do('two')
Beispiel #7
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def main():
    """ Demonstration of the simulation.advance_round function, which can
    take arbitrary values """
    simulation = Simulation()
    agents = simulation.build_agents(Agent, 'agent', number=1)

    weekday = 0
    for year in range(2000, 2010):
        for month in range(12):
            for day in range(30):
                simulation.advance_round((year, month, day))
                weekday = (weekday + 1) % 7
                print(weekday)
                if weekday == 3:
                    agents.wednessday()
                if day == 1:
                    agents.first()
                if month == 12 and day == 31:
                    agents.newyearseve()
                if day <= 7 and weekday == 5:
                    agents.firstfriday()
                if day == 15:
                    agents.fiveteens()
        agents.panel_log(goods=['money'])
        agents.agg_log(goods=['labor'])
    simulation.finalize()
Beispiel #8
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def main():
    s = Simulation()

    a = s.build_agents(MyAgent, 'myagent', 10000)
    for r in range(50):
        s.advance_round(r)
        a.do("compute")
    s.finalize()
def main():
    parameters = {
        'name': 'name',
        'num_rounds': 10
    }

    s = Simulation(parameters)
    action_list = [  # (('myagent', 'youragent'), 'compute'),
        ('youragent', 's'),
        ('myagent', 'g')]
    s.add_action_list(action_list)

    s.build_agents(MyAgent, 50000)
    s.build_agents(YourAgent, 50000)

    s.run(parallel=True)
Beispiel #10
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def main():
    parameters = {
        'name': 'name',
        'rounds': 300
    }

    s = Simulation(rounds=parameters['rounds'], cores=8)
    action_list = [  # (('myagent', 'youragent'), 'compute'),
        ('youragent', 's'),
        ('myagent', 'g')]
    s.add_action_list(action_list)

    s.build_agents(MyAgent, 50000)
    s.build_agents(YourAgent, 50000)

    s.run()
Beispiel #11
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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.finalize()
Beispiel #12
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def main(simulation_parameters):
    simulation = Simulation(rounds=simulation_parameters['rounds'],
                            processes=2)

    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)

    for round in simulation.next_round():
        print('one')
        (firms + households).do('one')
        #pprint({k: str(v) for k, v in simulation.mlist.items()})
        print('two')
        (firms + households).do('two')
Beispiel #13
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def main():
    s = Simulation(processes=1)

    myagents = s.build_agents(MyAgent, 'myagent', 500000)
    youragents = s.build_agents(YourAgent, 'youragent', 500000)

    for r in range(100):
        print('Round: %i' % r)
        s.advance_round(r)
        # (myagents+youragents).do('compute')
        youragents.s()
        myagents.g()
    s.finalize()
Beispiel #14
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def main(simulation_parameters):

    s = Simulation(name=simulation_parameters['name'])

    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'
                      ])

        (household + firms).refresh_services('labor',
                                             'labor_endowment',
                                             units=1)
    s.finalize()
Beispiel #15
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def main(simulation_parameters):
    s = Simulation()

    firms = s.build_agents(Firm, 'firm', 10)
    households = s.build_agents(Household, 'household', 10)
    for r in range(int(simulation_parameters['rounds'])):
        s.advance_round(r)
        firms.panel_log(possessions=['cookies'])
        firms.quote()
        households.buying()
        firms.selling()
        households.panel_log(possessions=['cookies'])
        households.consumption()
    s.finalize()
def main(processes, rounds):
    s = Simulation(processes=processes, name='unittest', trade_logging='group')

    print('build Buy')
    buy = s.build_agents(Buy, 'buy', 1000, rounds=rounds)
    print('build Sell')
    sell = s.build_agents(Sell, 'sell', 1000, rounds=rounds)
    print('build Give')
    give = s.build_agents(Give, 'give', 2, rounds=rounds)
    print('build LoggerTest')
    loggertest = s.build_agents(LoggerTest, 'loggertest', 1, rounds=rounds)

    all = buy + sell + give + loggertest

    for r in range(rounds):
        s.advance_round(r)
        for _ in range(5):
            buy.one()
            buy.two()
            buy.three()
            buy.clean_up()
        buy.panel_log(variables=['price'])
        for _ in range(5):
            sell.one()
            sell.two()
            sell.three()
            sell.clean_up()
        for _ in range(5):
            give.one()
            give.two()
            give.three()
            give.clean_up()
        for _ in range(5):
            loggertest.one()
            loggertest.two()
            loggertest.three()
            loggertest.clean_up()

        all.all_tests_completed()
    s.finalize()
Beispiel #17
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def main():
    s = Simulation(name='Sticky Prices Microfoundations')
    s.declare_perishable('labor')

    firms = s.build_agents(Firm, 'firm', 1)
    market = s.build_agents(Market, 'market', 1)
    labormarket = s.build_agents(LaborMarket, 'labormarket', 1)
    for r in range(20):
        s.advance_round(r)
        firms.do('quote_hire')
        labormarket.do('accepting')
        firms.do('hire')
        firms.do('my_production')
        firms.do('selling')
        market.do('buying')
        firms.do('adjust_price')
        firms.do('adjust_quantity')
        market.do('consumption')
def main(processes, rounds):
    s = Simulation(processes=processes, name='unittest')

    print('build Buy')
    buy = s.build_agents(Buy, 'buy', 1000, rounds=rounds)
    print('build Sell')
    sell = s.build_agents(Sell, 'sell', 1000, rounds=rounds)
    print('build Give')
    give = s.build_agents(Give, 'give', 2, rounds=rounds)
    print('build LoggerTest')
    loggertest = s.build_agents(
        LoggerTest, 'loggertest', 1, rounds=rounds)

    all = buy + sell + give + loggertest

    for r in range(rounds):
        s.advance_round(r)
        for _ in range(5):
            buy.one()
            buy.two()
            buy.three()
            buy.clean_up()
        buy.panel_log(variables=['price'])
        for _ in range(5):
            sell.one()
            sell.two()
            sell.three()
            sell.clean_up()
        for _ in range(5):
            give.one()
            give.two()
            give.three()
            give.clean_up()
        for _ in range(5):
            loggertest.one()
            loggertest.two()
            loggertest.three()
            loggertest.clean_up()

        all.all_tests_completed()
    s.finalize()
Beispiel #19
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def main(simulation_parameters):
    s = Simulation()

    firms = s.build_agents(Firm,
                           'firm',
                           parameters=simulation_parameters,
                           number=1)
    market = s.build_agents(Market,
                            'market',
                            parameters=simulation_parameters,
                            number=1)
    for r in range(simulation_parameters['rounds']):
        s.advance_round(r)
        firms.my_production()
        firms.selling()
        market.buying()
        firms.adjust_price()
        firms.adjust_quantity()
        market.consumption()
    s.finalize()
Beispiel #20
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def main(simulation_parameters):
    w = Simulation()

    firms = w.build_agents(Firm, 'firm', 2)
    households = w.build_agents(Household, 'household', 2)

    for r in range(simulation_parameters['rounds']):
        w.advance_round(r)
        households.refresh_services('labor',
                                    derived_from='labor_endowment',
                                    units=5)
        # to access round, just get the value of w.round
        # to access its datetime version, use w._round # todo, better naming
        households.sell_labor()
        firms.buy_inputs()
        firms.production()
        firms.panel_log(goods=['consumption_good', 'intermediate_good'])
        firms.sell_intermediary_goods()
        households.buy_intermediary_goods()
        households.panel_log(goods=['consumption_good'])
        households.consumption()
    w.finalize()
Beispiel #21
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def main():
    s = Simulation()
    buy = s.build_agents(Buy, group_name='buy', number=2,
                         parameters=simulation_parameters)
    sell = s.build_agents(Sell, group_name='sell', number=2,
                          parameters=simulation_parameters)

    all = buy + sell

    for r in range(simulation_parameters['num_rounds']):
        s.advance_round(r)
        for r in range(20000):
            all.one()
            all.two()
            all.three()
            all.clean_up()

        all.all_tests_completed()
Beispiel #22
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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.finalize()
Beispiel #23
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def main(simulation_parameters):
    sam = Sam(
        'climate_square.sam.csv',
        inputs=[
            'col', 'ele', 'gas', 'o_g', 'oil', 'eis', 'trn', 'roe', 'lab',
            'cap'
        ],
        outputs=['col', 'ele', 'gas', 'o_g', 'oil', 'eis', 'trn', 'roe'],
        output_tax='tax',
        consumption=['col', 'ele', 'gas', 'o_g', 'oil', 'eis', 'trn', 'roe'],
        consumers=['hoh'])
    """ reads the social accounting matrix and returns coefficients of a cobb-douglas model """
    carbon_prod = defaultdict(float)
    carbon_prod.update({
        'col': 2112 * 1e-4,
        'oil': 2439.4 * 1e-4,
        'gas': 1244.3 * 1e-4
    })
    """ this is the co2 output per sector at the base year """
    print(sam.output_tax_shares())

    simulation_parameters.update({
        'name':
        'cce',
        'random_seed':
        None,
        'num_household':
        1,
        'num_firms':
        1,
        'endowment_FFcap':
        sam.endowment('cap'),
        'endowment_FFlab':
        sam.endowment('lab'),
        'final_goods':
        sam.consumption,
        'capital_types': ['cap', 'lab'],
        'dividends_percent':
        0.0,
        'production_functions':
        sam.production_functions(),
        'consumption_functions':
        sam.utility_function(),
        'output_tax_shares':
        sam.output_tax_shares(),
        'money':
        2691.2641884030372,
        'inputs':
        sam.inputs,
        'outputs':
        sam.outputs,
        'balance_of_payment':
        sam.balance_of_payment('nx', 'inv'),
        'sam':
        sam,
        'carbon_prod':
        carbon_prod,
        'wage_stickiness':
        0.5,
        'price_stickiness':
        0.5,
        'network_weight_stickiness':
        0.5
    })

    simulation = Simulation(trade_logging='group', processes=1)

    declare_service('endowment_FFcap', 1, 'cap')
    simulation.declare_service('endowment_FFlab', 1, 'lab')
    """ every round for every endowment_FFcap the owner gets one good of lab
    similar for cap"""

    firms = {
        good:
        simulation.build_agents(Firm,
                                number=simulation_parameters['num_firms'],
                                group_name=good,
                                parameters=simulation_parameters)
        for good in sam.outputs
    }
    household = simulation.build_agents(Household,
                                        'household',
                                        simulation_parameters['num_household'],
                                        parameters=simulation_parameters)
    netexport = simulation.build_agents(NetExport,
                                        'netexport',
                                        1,
                                        parameters=simulation_parameters)
    government = simulation.build_agents(Government,
                                         'government',
                                         1,
                                         parameters=simulation_parameters)

    firms_and_household = sum(firms.values()) + household
    all_firms = sum(firms.values())

    try:
        for r in range(simulation_parameters['rounds']):
            simulation.advance_round(r)
            all_firms.taxes_intervention()
            firms_and_household.send_demand()
            firms_and_household.selling()
            firms_and_household.buying()
            household.money_to_nx()
            all_firms.production()
            all_firms.carbon_taxes()
            all_firms.sales_tax()
            government.taxes_to_household()
            all_firms.international_trade()
            all_firms.invest()
            netexport.invest()
            household.sales_accounting()
            all_firms.dividends()
            all_firms.change_weights()
            all_firms.stats()
            household.agg_log(variables=['welfare'])
            (firms['col'] + firms['gas'] +
             firms['oil']).agg_log(variables=['price', 'produced', 'co2'])

            (firms['ele'] + firms['o_g'] + firms['eis'] + firms['trn'] +
             firms['roe']).agg_log(variables=['price', 'produced'])
            household.consuming()
    except Exception as e:
        print(e)

    simulation.finalize()
    # raise  # put raise for full traceback but no graphs in case of error
    iotable.to_iotable(simulation.path,
                       [99, simulation_parameters['rounds'] - 1])
    mean_price = iotable.average_price(simulation.path, 99)
    print('mean price', mean_price)
    # simulation.graphs()
    return mean_price
Beispiel #24
0
def main():
    for params in simulation_parameters:
        s = Simulation(params)

        s.declare_round_endowment('field', 60, 'corn')
        s.declare_round_endowment('shares', 60, 'money')

        f = s.build_agents(Firm, 'firm', 1)
        h = s.build_agents(Household, 'household', 1)
        for r in s.next_round():
            for i in range(60):
                f.do('selling')
                h.do('buying')
                h.do('checking')

        s.run()