b'The time step for the simulation.' """ return 0.125 _smooth_functionsstep__datatime_potential_isolation_effectiveness_import_time_isolation_reaction_time_functionsstep__datatime_potential_isolation_effectiveness_import_time_3 = functions.Smooth( lambda: functions.step(__data['time'], potential_isolation_effectiveness(), import_time()), lambda: isolation_reaction_time(), lambda: functions.step(__data['time'], potential_isolation_effectiveness(), import_time()), lambda: 3) _smooth_1functionsstep__datatime_behavioral_risk_reduction_import_time_behavior_reaction_time_1functionsstep__datatime_behavioral_risk_reduction_import_time_3 = functions.Smooth( lambda: 1 - functions.step(__data['time'], behavioral_risk_reduction(), import_time()), lambda: behavior_reaction_time(), lambda: 1 - functions.step( __data['time'], behavioral_risk_reduction(), import_time()), lambda: 3) _integ_deaths = functions.Integ(lambda: dying(), lambda: 0) _integ_exposed = functions.Integ(lambda: infecting() - advancing(), lambda: 0) _integ_recovered = functions.Integ(lambda: recovering(), lambda: 0) _integ_infected = functions.Integ( lambda: advancing() + importing_infected() - dying() - recovering(), lambda: 0) _integ_susceptible = functions.Integ(lambda: -infecting(), lambda: initial_population())
@cache('step') def population(): """ Real Name: b'Population' Original Eqn: b'Additions' Units: b'' Limits: (None, None) Type: component b'' """ return integ_population() integ_population = functions.Integ(lambda: additions(), lambda: 1000) @cache('run') def initial_time(): """ Real Name: b'INITIAL TIME' Original Eqn: b'1' Units: b'Months' Limits: None Type: constant b'The initial time for the simulation.' """ return 1
Real Name: b'SAVEPER' Original Eqn: b'TIME STEP' Units: b'Month' Limits: (0.0, None) Type: component b'The frequency with which output is stored.' """ return time_step() @cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.0078125' Units: b'Month' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.0078125 integ_infected = functions.Integ(lambda: ir() - rr(), lambda: 1) integ_recovered = functions.Integ(lambda: rr(), lambda: 0) integ_susceptible = functions.Integ(lambda: -ir(), lambda: 9999)
@cache('run') def time_step(): """ Real Name: TIME STEP Original Eqn: 0.0625 Units: Month Limits: (0.0, None) Type: constant The time step for the simulation. """ return 0.0625 integ_total_cumulative_sales = functions.Integ(lambda: accumulating_sales(), lambda: 0) integ_tenure = functions.Integ(lambda: accumulating_tenure(), lambda: 0) integ_total_cumulative_income = functions.Integ(lambda: accumulating_income(), lambda: 0) integ_months_of_buffer = functions.Integ(lambda: income() - expenses(), lambda: initial_buffer()) integ_tier_2_clients = functions.Integ(lambda: tier_2_sales() - tier_2_client_turnover(), lambda: 0) integ_tier_2_leads = functions.Integ( lambda: tier_2_lead_aquisition() + tier_2_sales() - tier_2_leads_going_stale(), lambda: 0) integ_tier_1_leads = functions.Integ( lambda: tier_1_lead_aquisition() + tier_1_sales() - tier_1_leads_going_stale(), lambda: 100)
component The frequency with which output is stored. """ return time_step() @cache('run') def time_step(): """ TIME STEP Month [0,?] constant The time step for the simulation. """ return 0.0625 integ_total_cumulative_income = functions.Integ(lambda: accumulating_income(), lambda: 0) integ_total_cumulative_sales = functions.Integ(lambda: accumulating_sales(), lambda: 0) integ_tenure = functions.Integ(lambda: accumulating_tenure(), lambda: 0) integ_motivation = functions.Integ(lambda: motivation_adjustment(), lambda: 1)
@cache('run') def time_step(): """ TIME STEP Year [0,?] constant The time step for the simulation. """ return 0.015625 integ_capabilities = functions.Integ(lambda: capability_increase() - capability_decrease(), lambda: initial_capabilities()) initial_initial_required_outputinitial_laborstandard_workweekreference_fraction_of_effort_to_output = functions.Initial(lambda: initial_required_output()/(initial_labor()*standard_workweek()*reference_fraction_of_effort_to_output())) initial_initial_capabilitiesaverage_capability_loss_ratemaximum_capabilitiesmaximum_capabilities1initial_laborstandard_workweek1reference_fraction_of_effort_to_output = functions.Initial(lambda: initial_capabilities()*average_capability_loss_rate()*(maximum_capabilities()/(maximum_capabilities()-1))/(initial_labor()*standard_workweek()*(1-reference_fraction_of_effort_to_output()))) integ_time_spent_working = functions.Integ( lambda: change_in_time_spent_working(), lambda: standard_workweek() * reference_fraction_of_effort_to_output()) integ_required_improvement_effort = functions.Integ( lambda: change_in_required_improvement_effort(), lambda: standard_workweek() * (1 - reference_fraction_of_effort_to_output()))
@cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.125' Units: b'Week' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.125 integ_d_expected_customer_orders = functions.Integ(lambda: d_ceco(), lambda: 100) integ_d_stock = functions.Integ( lambda: d_acquisition_rate() - d_shipment_rate(), lambda: 400) integ_d_supply_line = functions.Integ( lambda: d_order_rate() - d_acquisition_rate(), lambda: 400) integ_f_expected_customer_orders = functions.Integ(lambda: f_ceco(), lambda: 100) integ_f_stock = functions.Integ( lambda: f_acquisition_rate() - f_shipment_rate(), lambda: 400) integ_f_supply_line = functions.Integ( lambda: f_order_rate() - f_acquisition_rate(), lambda: 400)
@cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.125' Units: b'Month' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.125 integ_afv_travel_range = functions.Integ( lambda: development_in_afv_travel_range(), lambda: 10) integ_expected_charging_station_discards = functions.Integ( lambda: change_in_ecsd(), lambda: 0) integ_number_of_afv_charging_stations = functions.Integ( lambda: new_charging_stations() - discarded_charging_stations(), lambda: 10) delay_effect_of_price_on_attractiveness_on_ice_lag_constant_07_1 = functions.Delay( lambda: effect_of_price_on_attractiveness_on_ice(), lambda: lag_constant(), lambda: 0.7, lambda: 1) delay_effect_of_price_on_attractiveness_on_afv_lag_constant_03_1 = functions.Delay( lambda: effect_of_price_on_attractiveness_on_afv(), lambda: lag_constant(), lambda: 0.3, lambda: 1)
def saveper(): """ Real Name: b'SAVEPER' Original Eqn: b'TIME STEP' Units: b'Year' Limits: (0.0, None) Type: component b'The frequency with which output is stored.' """ return time_step() @cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'1' Units: b'Year' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 1 _integ_marsh_elevation = functions.Integ(lambda: sed_increase() - sed_decrease(), lambda: 1) _integ_spartina = functions.Integ(lambda: plant_growth() - plant_death(), lambda: 2)
@cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.02' Units: b'year' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.02 smooth_b0_identifier_time_step_b0_identifier_1 = functions.Smooth( lambda: b0_identifier(), lambda: time_step(), lambda: b0_identifier(), lambda: 1) smooth_b1_identifier_time_step_b1_identifier_1 = functions.Smooth( lambda: b1_identifier(), lambda: time_step(), lambda: b1_identifier(), lambda: 1) integ_business_structures = functions.Integ( lambda: business_construction() - business_demolition(), lambda: 200) smooth_r1_identifier_time_step_r1_identifier_1 = functions.Smooth( lambda: r1_identifier(), lambda: time_step(), lambda: r1_identifier(), lambda: 1)
@cache('run') def time_step(): """ TIME STEP Year [0,?] constant The time step for the simulation. """ return 0.0078125 integ_current_safety_standard = functions.Integ( lambda: (current_safety_standard() * fractional_difference()) / planning_horizon(), lambda: 7) integ_perceived_current_safety = functions.Integ( lambda: informed_opinion_adjustment() - loss_of_perceived_safety_by_flooding(), lambda: length_safety()) integ_anticipated_flood_level = functions.Integ( lambda: anticipated_flood_level() * (fractional_change_in_anticipated_flood_level() + effect_of_size_of_flood( )), lambda: current_safety_standard() * 0.98) integ_safety_ol = functions.Integ( lambda: change_in_safety_of_standard_levees() - change_in_safety_due_to_renovation() - decrease_in_safety_of_old_levees(), lambda: 5)
""" Real Name: b'SAVEPER' Original Eqn: b'TIME_STEP' Units: b'Day' Limits: (0.0, None) Type: component b'The frequency with which output is stored.' """ return time_step() @cache('run') def time_step(): """ Real Name: b'TIME_STEP' Original Eqn: b'0.25' Units: b'Day' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.25 _integ_predators = functions.Integ(lambda: predator_growth() - predator_loss(), lambda: initial_predators()) _integ_prey = functions.Integ(lambda: prey_growth() - prey_loss(), lambda: initial_prey())
@cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.015625' Units: b'Day' Limits: (0.0, None) Type: constant b'' """ return 0.015625 _integ_accumulated_cases = functions.Integ(lambda: new_cases(), lambda: init_accumulated_cases()) _integ_available_test_kits = functions.Integ( lambda: produced_test_kits() - used_test_kits(), lambda: init_available_test_kits()) _integ_critical_cases = functions.Integ( lambda: infected_critical_case_rate() - critical_cases_recovery_rate( ) - death_rate() + isolated_critical_case_rate(), lambda: init_critical_cases()) _integ_diseased = functions.Integ(lambda: death_rate(), lambda: init_diseased()) _integ_infected_asymptomatic = functions.Integ( lambda: infection_rate() - infected_asymptomatic_recovery_rate(
@cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.125' Units: b'Year' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.125 integ_expected_retirement_rate = functions.Integ(lambda: cerr(), lambda: 100) integ_general_practitioners = functions.Integ( lambda: recruitment_rate() - retirement_rate(), lambda: 4000) integ_patients_being_treated = functions.Integ( lambda: patient_visits() - completed_visits(), lambda: 2.4e+07) integ_population_aged_014 = functions.Integ(lambda: births() - rate_c1_to_c2(), lambda: 1e+06) integ_population_aged_1539 = functions.Integ( lambda: rate_c1_to_c2() - rate_c2_to_c3(), lambda: 1.5e+06) integ_population_aged_4064 = functions.Integ( lambda: rate_c2_to_c3() - rate_c3_to_c4(), lambda: 2e+06)
b'The frequency with which output is stored.' """ return time_step() @cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.0078125' Units: b'Day' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.0078125 _integ_infected = functions.Integ(lambda: infection_rate() - recovery_rate(), lambda: 1) _integ_susceptible = functions.Integ(lambda: recovery_rate() - infection_rate(), lambda: 10) _integ_clean_particles = functions.Integ( lambda: clean_particle_recovery_due_to_vent_and_virus_decay() + exhalation_of_clean_particles( ) - breathing(), lambda: air_density() * room_volume()) _integ_virus_particles = functions.Integ( lambda: virus_production() - virus_decay() - virus_loss_due_to_ventilation(), lambda: 0)
Real Name: SAVEPER Original Eqn: TIME STEP Units: year Limits: (0.0, None) Type: component The frequency with which output is stored. """ return time_step() @cache('run') def time_step(): """ Real Name: TIME STEP Original Eqn: 1 Units: year Limits: (0.0, None) Type: constant The time step for the simulation. """ return 1 integ_customer = functions.Integ(lambda: adoption_rate(), lambda: total_population() * 0.1) integ_potential_adopters = functions.Integ(lambda: -adoption_rate(), lambda: total_population() * 0.9)
@cache('step') def saveper(): """ Real Name: SAVEPER Original Eqn: TIME STEP Units: Minute Limits: (0.0, None) Type: component The frequency with which output is stored. """ return time_step() @cache('run') def time_step(): """ Real Name: TIME STEP Original Eqn: 0.125 Units: Minute Limits: (0.0, None) Type: constant The time step for the simulation. """ return 0.125 integ_teacup_temperature = functions.Integ(lambda: -heat_loss_to_room(), lambda: 180)
@cache('step') def saveper(): """ Real Name: b'SAVEPER' Original Eqn: b'TIME STEP' Units: b'Year' Limits: (0.0, None) Type: component b'The frequency with which output is stored.' """ return time_step() @cache('run') def time_step(): """ Real Name: b'TIME STEP' Original Eqn: b'0.125' Units: b'Year' Limits: (0.0, None) Type: constant b'The time step for the simulation.' """ return 0.125 _integ_population = functions.Integ(lambda: number_added(), lambda: initial_population())
@cache('step') def lago(): """ Real Name: Lago Original Eqn: Flujo río - Evaporación Units: m3 Limits: (0.0, None) Type: component La cantidad de agua en el lago. """ return integ_lago() integ_lago = functions.Integ(lambda: flujo_río() - evaporación(), lambda: nivel_lago_inicial()) @cache('run') def initial_time(): """ Real Name: INITIAL TIME Original Eqn: 0 Units: mes Limits: None Type: constant The initial time for the simulation. """ return 0
""" Real Name: SAVEPER Original Eqn: TIME STEP Units: Meses Limits: (0.0, None) Type: component The frequency with which output is stored. """ return time_step() @cache('run') def time_step(): """ Real Name: TIME STEP Original Eqn: 1 Units: Meses Limits: (0.0, None) Type: constant The time step for the simulation. """ return 1 integ_bosques = functions.Integ(lambda: regeneración() - deforestación(), lambda: máx_bosques()) integ_agua_en_lago = functions.Integ(lambda: río() - evaporación(), lambda: 10)