R/ensScatterPlot.R

In hydrosolutions/ftimeseries: Timeseries generation

#' A Timeseries Function
#' 
#' This function creates a scatter plot from time series data.
#' @param predictions DESCRIPTION
#' @param observations DESCRIPTION
#' @param h DESCRIPTION
#' @param pointS DESCRIPTION
#' @param title of the plot DESCRIPTION 
#' @param labels for x- and DESCRIPTION
#' @param y-axis DESCRIPTION
#' @param nRuns Ensemble size 
#' @export
#' @examples 
#' ensScatterPlot() 
ensScatterPlot <- function(predD,obsD,h,pointS,plotTitle,xlabel,ylabel,nRuns)
{
  le.p <-  length(predD$pred[[1]]);
  qZ.Da.pred.ens <- data.frame(matrix(nrow=le.p*nRuns,ncol = 2))
  for(idx in 1:nRuns){
    qZ.Da.pred.ens[((idx-1)*le.p+1):((idx-1)*le.p+le.p),1] <- (1:le.p) #rep((1:1332),each=nRuns)
    qZ.Da.pred.ens[((idx-1)*le.p+1):((idx-1)*le.p+le.p),2] <- predD$pred[[idx]]
  }
  qZ.Da.pred.ens.summary <- qZ.Da.pred.ens %>% group_by(X1) %>%
    summarize(ymin = min(X2),
              ymax = max(X2),
              ymean = mean(X2))
  ggplot(qZ.Da.pred.ens.summary, aes(x = obsD$y[h$ts], y = ymean)) +
    geom_point(size = pointS) +
    geom_errorbar(aes(ymin = ymin, ymax = ymax)) +
    ggtitle(plotTitle) +
    xlab(xlabel) +
    ylab(ylabel) +
    coord_cartesian(xlim = c(-1,.5), ylim = c(-1,.5)) +
    coord_fixed(ratio=1) +
    geom_abline(intercept = 0 , slope = 1, col="red")
}