Converting from GillespieSSA to GillespieSSA2
In GillespieSSA2: Gillespie's Stochastic Simulation Algorithm for Impatient People

set.seed(1)
knitr::opts_chunk$set(fig.width = 6, fig.height = 4)
if("package:GillespieSSA2" %in% search()) detach("package:GillespieSSA2", unload=TRUE)

In this vignette, we will show how to upgrade the Lotka-predator-prey model from GillespieSSA to GillespieSSA2. First, have a look at the GillespieSSA vignette:

CRAN Vignette
vignette("lotka_predator_prey", package = "GillespieSSA")

The model consists of the following objects:

library(GillespieSSA)
parms <- c(c1 = 10, c2 = .01, c3 = 10)
tf <- 2                                        # Final time
simName <- "Lotka predator-prey model"         # Name
x0 <- c(Y1=1000, Y2=1000)
nu <- matrix(c(+1, -1, 0, 0, 1, -1), nrow = 2, byrow = TRUE)
a  <- c("c1*Y1", "c2*Y1*Y2","c3*Y2")
out <- GillespieSSA::ssa(
  x0 = x0,
  a = a,
  nu = nu,
  parms = parms,
  tf = tf,
  method = ssa.d(),
  simName = simName,
  censusInterval = .001,
  verbose = FALSE,
  consoleInterval = 1
) 
ssa.plot(out, show.title = TRUE, show.legend = FALSE)

set.seed(1)
if("package:GillespieSSA" %in% search()) detach("package:GillespieSSA", unload=TRUE)

In order to port these objects, it is preferable to use the updated notation from the respective GillespieSSA2 vignette:

CRAN Vignette
vignette("lotka_predator_prey", package = "GillespieSSA2")

library(GillespieSSA2)
sim_name <- "Lotka Predator-Prey model"
params <- c(c1 = 10, c2 = .01, c3 = 10)
final_time <- 2
initial_state <- c(Y1 = 1000, Y2 = 1000)
reactions <- list(
  reaction("c1 * Y1",      c(Y1 = +1)),
  reaction("c2 * Y1 * Y2", c(Y1 = -1, Y2 = +1)),
  reaction("c3 * Y2",      c(Y2 = -1))
)
out <- GillespieSSA2::ssa(
  initial_state = initial_state,
  reactions = reactions,
  params = params,
  final_time = final_time,
  method = ssa_exact(),
  census_interval = .001,
  verbose = FALSE,
  sim_name = sim_name
) 
plot_ssa(out)

However, if you want to use the GillespieSSA1 objects directly, you can also transform these programmatically. The interface of GillespieSSA2 is very similar, it only requires you to use different parameter names, and combine the state-change matrix nu and the propensity functions a into one list of reactions.

out <- 
  GillespieSSA2::ssa(
    initial_state = x0,
    reactions = port_reactions(x0 = x0, a = a, nu = nu),
    params = parms,
    method = ssa_exact(),
    final_time = tf,
    census_interval = .001,
    verbose = FALSE,
    sim_name = simName
  )
print(out$stats)
plot_ssa(out)