World3¶
State¶
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class
whynot.simulators.world3.
State
[source]¶ World3 state.
Default values correspond to the initial state in 1900 of the standard run.
Examples
>>> # Construct initial state with 800 land fertility. >>> world3.State(arable_land=800)
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arable_land
= 900000000.0¶
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industrial_capital
= 210000000000.0¶
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land_fertility
= 600.0¶
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nonrenewable_resources
= 1000000000000.0¶
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persistent_pollution
= 25000000.0¶
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population_0_to_14
= 650000000.0¶
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population_15_to_44
= 700000000.0¶
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population_45_to_64
= 190000000.0¶
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population_65_and_over
= 60000000.0¶
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potentially_arable_land
= 2300000000.0¶
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service_capital
= 144000000000.0¶
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total_population
¶ Return the aggregate population.
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urban_industrial_land
= 8200000.0¶
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Config¶
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class
whynot.simulators.world3.
Config
[source]¶ World3 simulation dynamics parameters.
Default values correspond to the standard run of World3.
Examples
>>> # Configuration of a run from 1910-1950 >>> world3.Config(start_time=1910, end_time=1950)
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average_lifetime_of_industrial_capital
= 14¶
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average_lifetime_of_service_capital
= 20¶
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delta_t
= 1.0¶ Granularity of the simulation (step size in the forward Euler method).
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end_time
= 2100¶ Year to end the simulation.
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fraction_of_industrial_output_allocated_to_consumption_constant
= 0.43¶
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industrial_capital_output_ratio
= 3¶
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land_yield_factor
= 1¶
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nonrenewable_resource_usage_factor
= 1¶
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persistent_pollution_generation_factor
= 1¶
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service_capital_output_ratio
= 1¶
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start_time
= 1900¶ Year to start the simulation.
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Interventions¶
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class
whynot.simulators.world3.
Intervention
(time=1975, **kwargs)[source]¶ Parameterization of an intervention in the World3 model.
An intervention is a subset of the configuration variables, and only variables passed into the constructor are modified.
Examples
>>> # Semantics: Starting in year 1975, double land_yield. All >>> # other parameters are unchanged. >>> Intervention(time=1975, land_yield_factor=2)
Experiments¶
Experiments for world3 simulator.
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whynot.simulators.world3.experiments.
PollutionRCT
= PollutionRCT¶ An RCT experiment to study the effect of decreases in pollution generation on population.
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whynot.simulators.world3.experiments.
PollutionConfounding
= PollutionConfounding¶ An observational experiment with confounding. Polluted states are more likely to be treated.
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whynot.simulators.world3.experiments.
PollutionUnobservedConfounding
= PollutionUnobservedConfounding¶ An observational experiment with unobserved confounding.
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whynot.simulators.world3.experiments.
PollutionMediation
= PollutionMediation¶ An observational experiment with mediation from states after intervention.