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```
#' @title A helper function that takes result from the simulators and produces text output
#'
#' @description This function generates text to be displayed in the Shiny UI.
#' This is a helper function. This function processes results returned from the simulation, supplied as a list.
#' @param res A list structure containing all simulation results that are to be processed.
#' This function is meant to be used together with generate_plots() and requires similar input information.
#' See the generate_plots() function for most details.
#' Specific entries for this function are 'maketext', 'showtext' and 'finaltext'.
#' If 'maketext' is set to TRUE (or not provided) the function processes the data corresponding to each plot
#' and reports min/max/final values (lineplots) or correlation coefficient (scatterplot)
#' If 'maketext' is FALSE, no text based on the data is generated.
#' If the entries 'showtext' or 'finaltext' are present, their values
#' will be returned for each plot or for all together.
#' The overall message of finaltext should be in the 1st plot.
#' @return HTML formatted text for display in a Shiny UI.
#' @details This function is called by the Shiny server to produce output returned to the Shiny UI.
#' @author Andreas Handel
#' @importFrom stats median reshape
#' @export
generate_text <- function(res)
{
#nplots contains the number of plots to be produced.
#for each plot, text output is produced separately
nplots = length(res) #length of list
alltext <- NULL #will hold all text outputs
#each plot will be processed separately and text for each produced and placed in a list entry
#using the same variable groupings as for the plots
for (n in 1:nplots)
{
resnow = res[[n]]
#if a data frame called 'ts' exists, assume that this one is the data to be plotted
#otherwise use the data frame called 'dat'
#one of the 2 must exist, otherwise the function will not work
if (!is.null(resnow$ts))
{
rawdat = resnow$ts
}
else {
rawdat = resnow$dat
}
#if nothing is provided, we assume a line plot. That could lead to silly text returns.
plottype <- if(is.null(resnow$plottype)) {'Lineplot'} else {resnow$plottype}
#if the first column is called 'Time' (as returned from several of the simulators)
#rename to xvals for consistency and so the code below will work
if ( colnames(rawdat)[1] == 'Time' | colnames(rawdat)[1] == 'time' ) {colnames(rawdat)[1] <- 'xvals'}
#for the plotting below, the data need to be in the form xvals/yvals/varnames
#if the data is instead in xvals/var1/var2/var3/etc. - which is what the simulator functions produce
#we need to re-format
#if the data frame already has a column called 'varnames', we assume it's already properly formatted as xvals/yvals/varnames
if ('varnames' %in% colnames(rawdat))
{
dat = rawdat
}
else
{
#using tidyr to reshape
#dat = tidyr::gather(rawdat, -xvals, value = "yvals", key = "varnames")
#using basic reshape function to reformat data
dat = stats::reshape(rawdat, varying = colnames(rawdat)[-1], v.names = 'yvals', timevar = "varnames", times = colnames(rawdat)[-1], direction = 'long', new.row.names = NULL); dat$id <- NULL
}
#code variable names as factor and level them so they show up right
#factor is needed for plotting and text
mylevels = unique(dat$varnames)
dat$varnames = factor(dat$varnames, levels = mylevels)
allvarnames = levels(dat$varnames)
nvars = length(allvarnames)
#labels, only used in correlation plots
xlabel = resnow$xlab
ylabel = resnow$ylab
#if not missing and false, we won't create text based on data as described below
if (!is.null(resnow$maketext) && resnow$maketext == FALSE) {maketext = FALSE} else {maketext = TRUE}
if (maketext == TRUE) #if the app wants text display based on result processing, do the stuff below
{
#for each plot, process each variable by looping over them
for (nn in 1:nvars)
{
#data for a given variable
currentvar = allvarnames[[nn]]
vardat = dplyr::filter(dat, varnames == currentvar)
#for lineplots, we show the min/max/final for each variable
if (plottype == 'Lineplot')
{
#check if multiple runs are done
#unless the data frame has a column indicating the number of runs, assume it's 1
nreps = 1
if ('nreps' %in% colnames(vardat) ) {nreps=max(vardat$nreps)}
resmax = 0; resmin = 0; resfinal = 0;
for (n1 in 1:nreps) #average over reps (if there are any)
{
#pull out each simulation/repetition
currentsim = dplyr::filter(vardat, nreps == n1)
nrows = nrow(currentsim) #number of entries in time-series matrix - can be different for every run
resmax = resmax + max(currentsim$yvals)
resmin = resmin + min(currentsim$yvals)
resfinal = resfinal + currentsim$yvals[nrows]
#browser()
} #finish loop over reps
#store values for each variable
maxvals = format(resmax/nreps, digits =2, nsmall = 2) #mean across simulations (for stochastic models)
minvals = format(resmin/nreps, digits =2, nsmall = 2) #mean across simulations (for stochastic models)
numfinal = format(resfinal/nreps, digits =2, nsmall = 2) #mean for each variable
newtxt <- paste('Minimum / Maximum / Final value of ',currentvar,': ',minvals,' / ', maxvals,' / ',numfinal,"<br/>",sep='')
} #finish creating text outpot for lineplot/time-series
#for scatterplots, report correlation between x and every y-value
if (plottype == 'Scatterplot' )
{
rcc = stats::cor.test(vardat[,1],y=vardat[,2], alternative = c("two.sided"), method = c("spearman"))
newtxt = paste0('Rank Cor. Coef. between ',xlabel,' and ',ylabel,' is: ',format(rcc$estimate, digits = 2, nsmall = 2),".<br/>")
}
if (plottype == 'Boxplot' )
{
mymin = format(min(vardat$yvals), digits =2, nsmall = 2)
mymean = format(mean(vardat$yvals), digits =2, nsmall = 2)
mymedian = format(stats::median(vardat$yvals), digits =2, nsmall = 2)
mymax = format(max(vardat$yvals), digits =2, nsmall = 2)
newtxt = paste('Min/Mean/Median/Max for ',ylabel,': ',mymin,' / ',mymean,' / ', mymedian,' / ',mymax,"<br/>")
}
if (plottype == 'Mixedplot' )
{
newtxt = ""
}
alltext <- paste(alltext, newtxt)
#browser()
} #end loop over all variables for a given plot
} #ends maketext block which is only entered if TRUE
#if the result structure has a text entry for a given plot, use that in addition to the
if (!is.null(resnow$showtext))
{
alltext = paste(alltext, resnow$showtext, "<br/>")
}
} #finishes loop over all plots
#as requested by app, add additional final text at bottom
if (!is.null(res[[1]]$finaltext))
{
finaltext <- res[[1]]$finaltext
alltext <- paste(alltext, finaltext)
}
shiny::HTML(alltext)
} #end function
```

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