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This is an internal function used by the user-facing project() function. It is of potential interest only to mizer extension authors.

Usage

project_simple(
  params,
  n = params@initial_n,
  n_pp = params@initial_n_pp,
  n_other = params@initial_n_other,
  effort = params@initial_effort,
  t = 0,
  dt = 0.1,
  steps,
  resource_dynamics_fn = get(params@resource_dynamics),
  other_dynamics_fns = lapply(params@other_dynamics, get),
  rates_fns = lapply(params@rates_funcs, get),
  ...
)

Arguments

params

A MizerParams object.

n

An array (species x size) with the number density at start of simulation.

n_pp

A vector (size) with the resource number density at start of simulation.

n_other

A named list with the abundances of other components at start of simulation.

effort

The fishing effort to be used throughout the simulation. This must be a vector or list with one named entry per fishing gear.

t

Time at the start of the simulation.

dt

Size of time step.

steps

The number of time steps by which to project.

resource_dynamics_fn

The function for the resource dynamics. See Details.

other_dynamics_fns

List with the functions for the dynamics of the other components. See Details.

rates_fns

List with the functions for calculating the rates. See Details.

...

Other arguments that are passed on to the rate functions.

Value

List with the final values of n, n_pp and n_other, rates.

Details

The function does not check its arguments because it is meant to be as fast as possible to allow it to be used in a loop. For example, it is called in project() once for every saved value. The function also does not save its intermediate results but only returns the result at time t + dt * steps. During this time it uses the constant fishing effort effort.

The functional arguments can be calculated from slots in the params object with

resource_dynamics_fn <- get(params@resource_dynamics)
other_dynamics_fns <- lapply(params@other_dynamics, get)
rates_fns <- lapply(params@rates_funcs, get)

The reason the function does not do that itself is to shave 20 microseconds of its running time, which pays when the function is called hundreds of times in a row.

This function is also used in steady(). In between calls to project_simple() the steady() function checks whether the values are still changing significantly, so that it can stop when a steady state has been approached. Mizer extension packages might have a similar need to run a simulation repeatedly for short periods to run some other code in between. Because this code may want to use the values of the rates at the final time step, these too are included in the returned list.