jsf_simulate

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jsf_simulate()

Simulate a compartmental model using JSF

Usage

jsf_simulate(
  x0,
  rates,
  reactant,
  product,
  do_disc,
  t_max,
  dt,
  switching_threshold,
  tau_threshold = NULL,
  tau_epsilon = 0.03,
  critical_threshold = 10,
  tau_debug = FALSE,
  tau_debug_every = 20,
  tau_debug_max = 30,
  species_names = NULL,
  enforce_do = NULL,
  method = "operator-splitting",
  return_type = c("data.frame", "JSFResult")
)

Arguments

Argument	Description
x0	Numeric vector of initial states.
rates	Python callable rate function, usually created with reticulate::py_eval().
reactant	Matrix where each row gives the reactants for one reaction.
product	Matrix where each row gives the products for one reaction.
do_disc	Integer vector indicating which species may be treated discretely/stochastically.
t_max	Final simulation time.
dt	Time step for the continuous/ODE part of JSF.
switching_threshold	Switching threshold. Can be a scalar or one value per species.
tau_threshold	Threshold controlling when species are handled by the tau-leaping component. May be NULL, a scalar, or one value per species. If NULL, defaults to switching_threshold.
tau_epsilon	Positive numeric scalar specifying the tau-leaping epsilon parameter passed to the Python JSF backend.
critical_threshold	Non-negative numeric scalar specifying the critical-reaction threshold passed to the Python JSF backend.
tau_debug	Logical. If TRUE, enables diagnostic output from the tau-leaping simulator.
tau_debug_every	Integer controlling how often tau-leaping diagnostic information is printed.
tau_debug_max	Integer giving the maximum number of tau-leaping diagnostic messages to print.
species_names	Optional character vector of species names.
enforce_do	Integer vector controlling enforced discrete behaviour. Defaults to zero for all species.
method	JSF simulation method. Supported values include "exact", "operator-splitting", and "tau-operator-splitting".
return_type	Output type. Either "data.frame" or "JSFResult".

Value

If return_type = "data.frame", a data frame with a time column and one column per species. If return_type = "JSFResult", a JSFResult object.

Description

This is a general R wrapper around the Python jsf simulator. It accepts an initial state, a Python rate function, reactant and product stoichiometry matrices, and JSF configuration options.

Examples

if (interactive() && jsf_available()) {
  rates_lv <- reticulate::py_eval(
    "lambda x, t: [2.0 * x[0], 1.5 * x[1], 0.05 * x[0] * x[1]]"
  )

  result <- jsf_simulate(
    x0 = c(prey = 50, predator = 10),
    rates = rates_lv,
    reactant = matrix(
      c(
        1, 0,
        0, 1,
        1, 1
      ),
      ncol = 2,
      byrow = TRUE
    ),
    product = matrix(
      c(
        2, 0,
        0, 0,
        0, 2
      ),
      ncol = 2,
      byrow = TRUE
    ),
    do_disc = c(1, 1),
    t_max = 1,
    dt = 0.01,
    switching_threshold = c(30, 30),
    species_names = c("prey", "predator"),
    return_type = "JSFResult"
  )

  result
  summary(result)
  plot(result)
}