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)
