compile_reactions: Precompile the reactions
In GillespieSSA2: Gillespie's Stochastic Simulation Algorithm for Impatient People

Description Usage Arguments Value Examples

By precompiling the reactions, you can run multiple SSA simulations repeatedly without having to recompile the reactions every time.

compile_reactions(
  reactions,
  state_ids,
  params,
  buffer_ids = NULL,
  hardcode_params = FALSE,
  fun_by = 10000L
)

`reactions`	'reaction' A list of multiple `reaction()` objects.
`state_ids`	`[character]` The names of the states in the correct order.
`params`	`[named numeric]` Constants that are used in the propensity functions.
`buffer_ids`	`[character]` The order of any buffer calculations that are made as part of the propensity functions.
`hardcode_params`	`[logical]` Whether or not to hardcode the values of `params` in the compilation of the propensity functions. Setting this to `TRUE` will result in a minor sacrifice in accuracy for a minor increase in performance.
`fun_by`	`[integer]` Combine this number of propensity functions into one function.

A list of objects solely to be used by ssa().

x[["state_change"]]: A sparse matrix of reaction effects.
x[["reaction_ids"]]: The names of the reactions.
x[["buffer_ids"]]: A set of buffer variables found in the propensity functions.
x[["buffer_size"]]: The minimum size of the buffer required.
x[["function_pointers"]]: A list of compiled propensity functions.
x[["hardcode_params"]]: Whether the parameters were hard coded into the source code.'

initial_state <- c(prey = 1000, predators = 1000)
params <- c(c1 = 10, c2 = 0.01, c3 = 10)
reactions <- list(
  #        propensity function     effects                       name for reaction
  reaction(~c1 * prey,             c(prey = +1),                 "prey_up"),
  reaction(~c2 * prey * predators, c(prey = -1, predators = +1), "predation"),
  reaction(~c3 * predators,        c(predators = -1),            "pred_down")
)

compiled_reactions <- compile_reactions(
  reactions = reactions,
  state_ids = names(initial_state),
  params = params
)

out <-
  ssa(
    initial_state = initial_state,
    reactions = compiled_reactions,
    params = params,
    method = ssa_exact(),
    final_time = 5,
    census_interval = .001,
    verbose = TRUE
  )

plot_ssa(out)