ErrorCrit_KGE2.R

ErrorCrit_KGE2 <- function(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE) {
  
  ## Arguments check
  if (!inherits(OutputsModel, "OutputsModel")) {
    stop("'OutputsModel' must be of class 'OutputsModel'")
  }
  
  EC <- .ErrorCrit(InputsCrit = InputsCrit, Crit = "KGE2",  OutputsModel = OutputsModel, warnings = warnings)
  
  CritValue <- NA
  SubCritValues <- rep(NA, 3)
  SubCritNames  <- c("r", "gamma", "beta")
  SubCritPrint  <- rep(NA, 3)
  
  if (EC$CritCompute) {
    ## Other variables preparation
    meanVarObs <- mean(EC$VarObs[!EC$TS_ignore])
    meanVarSim <- mean(EC$VarSim[!EC$TS_ignore])
    
    ## SubErrorCrit KGE rPearson
    SubCritPrint[1L] <- paste0(EC$CritName, " cor(sim, obs, \"pearson\") =")
    
    Numer <- sum((EC$VarObs[!EC$TS_ignore] - meanVarObs) * (EC$VarSim[!EC$TS_ignore] - meanVarSim))
    Deno1 <- sqrt(sum((EC$VarObs[!EC$TS_ignore] - meanVarObs)^2))
    Deno2 <- sqrt(sum((EC$VarSim[!EC$TS_ignore] - meanVarSim)^2))
    
    if (Numer == 0) {
      if (Deno1 == 0 & Deno2 == 0) {
        Crit <- 1
      } else {
        Crit <- 0
      }
    } else {
      Crit  <- Numer / (Deno1 * Deno2)
    }
    if (is.numeric(Crit) & is.finite(Crit)) {
      SubCritValues[1L] <- Crit
    }
    
    ## SubErrorCrit KGE gamma
    SubCritPrint[2L] <- paste0(EC$CritName, " cv(sim)/cv(obs)          =")
    
    if (meanVarSim == 0) {
      if (sd(EC$VarSim[!EC$TS_ignore]) == 0) {
        CVsim <- 1
      } else {
        CVsim <- 99999
      }
    } else {
      CVsim <- sd(EC$VarSim[!EC$TS_ignore]) / meanVarSim
      
    }
    if (meanVarObs == 0) {
      if (sd(EC$VarObs[!EC$TS_ignore]) == 0) {
        CVobs <- 1
      } else {
        CVobs <- 99999
      }
    } else {
      CVobs <- sd(EC$VarObs[!EC$TS_ignore]) / meanVarObs
    }
    if (CVsim == 0 &
        CVobs == 0) {
      Crit <- 1
    } else {
      Crit <- CVsim / CVobs
    }
    if (is.numeric(Crit) & is.finite(Crit)) {
      SubCritValues[2L] <- Crit
    }