R/plots.R

In amei: Adaptive Management of Epidemiological Interventions

`plot.epiman` <-
function (x, type = c("epi", "costs", "params", "fracs", "stops"), 
    showd = FALSE, showv=FALSE, prior=FALSE, main = NULL, ylim=NULL, tp = NULL, ...) 
{
    type <- match.arg(type)
    if (type == "epi") {
        if (is.null(main)) 
            main <- "Evolution of Epidemic"
        PlotEpi(x$soln, showd = showd, showv=showv, main = main)
    }
    else if (type == "costs") {
      if(is.null(x$pols)) stop("no vaccination strategy used")
      if (is.null(main)) 
        main <- "Evolution of Costs"
      PlotCosts(x$soln, main = main,ylim=ylim)
    }
    else if (type == "params") {
      if (is.null(main)) 
        main <- "MCMC Inference"
      if(prior) hyper <- x$hyper
      else hyper <- NULL
      PlotParams(x$samp, NULL, tp, hyper)
    }
    else if (type == "fracs") {
      if(is.null(x$vachist)) stop("no vaccination strategy used")
      ylab <- "vaccination fraction"
      TimeSeriesOfDensities(x$vachist$fracs, x$vactimes, 
                            c(-0.1, 1.1), ylab)
      if (!is.null(main)) 
        title(main)
    }
    else {
      if(is.null(x$vachist)) stop("no vaccination strategy used")
      ylim <- "stop number"
      TimeSeriesOfDensities(x$vachist$stops, x$vactimes, 
                            c(0, x$soln$S[1]), ylim)
      if (!is.null(main)) 
        title(main)
    }
}



`plot.optvac` <-
function (x, main = NULL, ...) 
{
  mylayout <- matrix(1,4,5)
  mylayout[,5] <- 2
  layo <- layout(mylayout)
  cmin <- min(x$C)
  cmax <- max(x$C)
  cmat <- matrix(seq(cmin,cmax,length=100),1,100)
  
  if (is.null(main)) 
        main <- "Optimal vaccination policy surface"
    image(x$vacgrid$fracs, x$vacgrid$stops, x$C, main = main, 
        xlab = "fraction", ylab = "stop number",col=heat.colors(100), ...)
    grid(length(x$vacgrid$fracs), length(x$vacgrid$stops), lty = 1, 
        col = "black")
    best <- getpolicy(x)
    worst <- getpolicy(x, "worst")
  text(best$frac, best$stop, best$cost,cex=1)
  text(worst$frac, worst$stop, worst$cost,cex=1)

  image(1,seq(cmin,cmax,length=100),cmat,axes=FALSE,xlab='',ylab='',main='',col=heat.colors(100))
  axis(2,at=floor(seq(cmin,cmax,length=10)),lwd=0,las=1)
  mtext('legend',line=1)
  
}


`plot.MCepi` <-
function (x, type = c("epi", "costs", "fracs", "stops"), showd = FALSE, 
    showv = FALSE, main = NULL, ylim = NULL, ...) 
{
  type <- match.arg(type)
  if (type == "epi") {
    if (is.null(main)) main <- "Monte Carlo Epidemics"
    PlotEpi(x$Median, showd = showd, showv = showv, main = main, 
            ...)
    PlotEpi(x$Q1, add = TRUE, showd = showd, showv = showv)
    PlotEpi(x$Q3, add = TRUE, showd = showd, showv = showv)
  }
  else if (type == "costs") {
    if (is.null(main)) main <- "Monte Carlo Costs"
    if(is.null(ylim)) ylim <- c(min(x$Q1$C),max(x$Q3$C))
    PlotCosts(x$Median, ylim = ylim,
              main = main, ...)
    PlotCosts(x$Q1, add = TRUE)
    PlotCosts(x$Q3, add = TRUE)
  }
  else if (type == "fracs") {
    if (is.null(main)) main <- "Monte Carlo Fraction Vaccinated"
    plot(x$Median$frac, type = "l", lty = 1, lwd = 2, 
         xlab = "time", ylab = "fraction",
         ylim = c(min(x$Q1$frac), max(x$Q3$frac)), main = main, ...)
    lines(x$Q1$frac, lty = 2, lwd = 2)
    lines(x$Q3$frac, lty = 2, lwd = 2)
  }
  else {
    if (is.null(main)) main <- "Monte Carlo Stopping Threshold"
    plot(x$Median$stop, type = "l", lty = 1, lwd = 2, 
         xlab = "time", ylab = "stop time",
         ylim = c(min(x$Q1$stop), max(x$Q3$stop)), main=main, ...)
    lines(x$Q1$stop, lty = 2, lwd = 2)
    lines(x$Q3$stop, lty = 2, lwd = 2)
  }
}