Ensembles

Ensembles

This module provides the main function run_dynamics. This serves to run multiple trajectories for a given simulation type, sampling from an initial distribution.

EnsembleSaver{F<:Tuple}

Store a tuple of functions with the signature f(sol) where sol is a DiffEq solution object. EnsembleSaver will evaluate each of these functions and return the result in a Dictionary.

Average the outputs over all trajectories.

Select the initial conditions from the distribution in order.

Obtain initial conditions by randomly sampling the distribution.

Sum the outputs from each trajectory.

run_dynamics(sim::AbstractSimulation, tspan, distribution;
    output,
    selection::Union{Nothing,AbstractVector}=nothing,
    reduction=AppendReduction(),
    ensemble_algorithm=SciMLBase.EnsembleSerial(),
    algorithm=DynamicsMethods.select_algorithm(sim),
    trajectories=1,
    kwargs...
    )

Run trajectories for timespan tspan sampling from distribution.

Keywords

• output either a single function or a Tuple of functions with the signature f(sol, i) that takes the DifferentialEquations solution and returns the desired output quantity.
• selection should be an AbstractVector containing the indices to sample from the distribution. By default, nothing leads to random sampling.
• reduction defines how the data is reduced across trajectories. Options are AppendReduction(), MeanReduction(), SumReduction and FileReduction(filename).
• ensemble_algorithm is the algorithm from DifferentialEquations which determines which form of parallelism is used.
• algorithm is the algorithm used to integrate the equations of motion.
• trajectories is the number of trajectories to perform.
• savetime saves the simulation time-steps, useful when usings with integrators with variable time-stepping.
• precompile_dynamics runs a single step of the dynamics simulation in order to optimise the full run, exploits a strange issue with the Julia compiler.
• kwargs... any additional keywords are passed to DifferentialEquations solve`.