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'")
  }
  
  OutputsCritCheck <- .ErrorCrit(InputsCrit = InputsCrit, crit = "RMSE")
  
  if (!OutputsCritCheck$CritCompute) {
    CritValue <- NA
  } else {
    ## Other variables preparation
    meanVarObs <- mean(VarObs[!TS_ignore])
    meanVarSim <- mean(VarSim[!TS_ignore])
    
    iCrit         <- 0
    SubCritPrint  <- NULL
    SubCritNames  <- NULL
    SubCritValues <- NULL
    
    ## SubErrorCrit KGE rPearson
    iCrit <- iCrit + 1
    SubCritPrint[iCrit]  <- paste(CritName, " cor(sim, obs, \"pearson\") =", sep = "")
    SubCritValues[iCrit] <- NA
    SubCritNames[iCrit]  <- "r"
    
    Numer <- sum((VarObs[!TS_ignore] - meanVarObs) * (VarSim[!TS_ignore] - meanVarSim))
    Deno1 <- sqrt(sum((VarObs[!TS_ignore] - meanVarObs)^2))
    Deno2 <- sqrt(sum((VarSim[!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[iCrit] <- Crit
    }
    
    ## SubErrorCrit KGE gamma
    iCrit <- iCrit + 1
    SubCritPrint[iCrit]  <- paste(CritName, " cv(sim)/cv(obs)          =", sep = "")
    SubCritValues[iCrit] <- NA
    SubCritNames[iCrit]  <- "gamma"
    
    if (meanVarSim == 0) {
      if (sd(VarSim[!TS_ignore]) == 0) {
        CVsim <- 1
      } else {
        CVsim <- 99999
      }
    } else {
      CVsim <- sd(VarSim[!TS_ignore]) / meanVarSim
      
    }
    if (meanVarObs == 0) {
      if (sd(VarObs[!TS_ignore]) == 0) {
        CVobs <- 1
      } else {
        CVobs <- 99999
      }
    } else {
      CVobs <- sd(VarObs[!TS_ignore]) / meanVarObs
    }
    if (CVsim == 0 &