Make seperate plots for each model compartment. Assumes model output is structured
as that produced from `solve_ode`

.

plot_model(sim, prev_sim = NULL, model_labels = NULL, facet = TRUE)

sim | A tibble of model output as formated by |
---|---|

prev_sim | A second tibble of model output formated as for |

model_labels | A character vector of model names. Defaults to |

facet | Logical, defaults to |

A Plot of each model compartments population over time.

## Intialise N = 100000 I_0 = 1 S_0 = N - I_0 R_0 = 1.1 beta = R_0 ##Time for model to run over tbegin = 0 tend = 50 times <- seq(tbegin, tend, 1) ##Vectorise input parameters <- as.matrix(c(beta = beta)) inits <- as.matrix(c(S = S_0, I = I_0)) sim <- solve_ode(model = SI_ode, inits, parameters, times, as.data.frame = TRUE) plot_model(sim, facet = FALSE)plot_model(sim, facet = TRUE)## Compare with an updated model run #'## Intialise R_0 = 1.3 beta = R_0 parameters <- as.matrix(c(beta = beta)) new_sim <- solve_ode(model = SI_ode, inits, parameters, times, as.data.frame = TRUE) plot_model(new_sim,sim, facet = FALSE)plot_model(new_sim, sim, facet = TRUE)## Passing in the simulations as a list plot_model(list("Current" = new_sim, "Previous" = sim), facet = TRUE)