---
title: "Converting from GillespieSSA to GillespieSSA2"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{Converting from GillespieSSA to GillespieSSA2}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

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rmarkdown::render("vignettes/converting_from_GillespieSSA.Rmd", output_format = "github_document")
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```{r, setseed, echo=FALSE}
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](https://CRAN.R-project.org/package=GillespieSSA/vignettes/lotka_predator_prey.html)
* `vignette("lotka_predator_prey", package = "GillespieSSA")`

The model consists of the following objects:
```{r gssa1}
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)
```



```{r, setseed2, echo=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](https://CRAN.R-project.org/package=GillespieSSA2/vignettes/lotka_predator_prey.html)
* `vignette("lotka_predator_prey", package = "GillespieSSA2")`

```{r gssa2}
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.
```{r port}
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)
```