ErrorCrit_RMSE <- function(InputsCrit, OutputsModel, warnings = TRUE, verbose = TRUE) { ##Arguments_check________________________________ if (!inherits(InputsCrit, "InputsCrit")) { stop("'InputsCrit' must be of class 'InputsCrit'") } if (inherits(InputsCrit, "Multi") | inherits(InputsCrit, "Compo")) { stop("'InputsCrit' must be of class 'Single'. Use the 'ErrorCrit' function on objects of class 'Multi' with RMSE") } if (!inherits(OutputsModel, "OutputsModel")) { stop("'OutputsModel' must be of class 'OutputsModel'") } ##Initialisation_________________________________ CritName <- NA CritVar <- InputsCrit$VarObs if (InputsCrit$transfo == "") { CritName <- "RMSE[CritVar]" } if (InputsCrit$transfo == "sqrt") { CritName <- "RMSE[sqrt(CritVar)]" } if (InputsCrit$transfo == "log") { CritName <- "RMSE[log(CritVar)]" } if (InputsCrit$transfo == "inv") { CritName <- "RMSE[1/CritVar]" } if (InputsCrit$transfo == "sort") { CritName <- "RMSE[sort(CritVar)]" } CritName <- gsub(pattern = "CritVar", replacement = CritVar, x = CritName) CritValue <- NA CritBestValue <- +1 Multiplier <- +1 ### must be equal to -1 or +1 only ##Data_preparation_______________________________ VarObs <- InputsCrit$Obs VarObs[!InputsCrit$BoolCrit] <- NA if (InputsCrit$VarObs == "Q") { VarSim <- OutputsModel$Qsim } if (InputsCrit$VarObs == "SCA") { VarSim <- rowMeans(sapply(OutputsModel$CemaNeigeLayers[InputsCrit$idLayer], FUN = "[[", "Gratio")) } if (InputsCrit$VarObs == "SWE") { VarSim <- rowMeans(sapply(OutputsModel$CemaNeigeLayers[InputsCrit$idLayer], FUN = "[[", "SnowPack")) } VarSim[!InputsCrit$BoolCrit] <- NA ##Data_transformation if (InputsCrit$transfo %in% c("log", "inv") & is.null(InputsCrit$epsilon) & warnings) { if (any(VarObs %in% 0)) { warning("zeroes detected in 'Qobs': the corresponding time-steps will be excluded from the criteria computation if the epsilon argument of 'CreateInputsCrit' = NULL") } if (any(VarSim %in% 0)) { warning("zeroes detected in 'Qsim': the corresponding time-steps will be excluded from the criteria computation if the epsilon argument of 'CreateInputsCrit' = NULL") } } if ("epsilon" %in% names(InputsCrit) & !is.null(InputsCrit$epsilon)) { VarObs <- VarObs + InputsCrit$epsilon VarSim <- VarSim + InputsCrit$epsilon } if (InputsCrit$transfo == "sqrt") { VarObs <- sqrt(VarObs) VarSim <- sqrt(VarSim) } if (InputsCrit$transfo == "log") { VarObs <- log(VarObs) VarSim <- log(VarSim) VarSim[VarSim < -1e100] <- NA } if (InputsCrit$transfo == "inv") { VarObs <- 1 / VarObs VarSim <- 1 / VarSim VarSim[abs(VarSim) > 1e+100] <- NA } if (InputsCrit$transfo == "sort") { VarSim[is.na(VarObs)] <- NA VarSim <- sort(VarSim, na.last = TRUE) VarObs <- sort(VarObs, na.last = TRUE) InputsCrit$BoolCrit <- sort(InputsCrit$BoolCrit, decreasing = TRUE) } ##TS_ignore TS_ignore <- !is.finite(VarObs) | !is.finite(VarSim) | !InputsCrit$BoolCrit Ind_TS_ignore <- which(TS_ignore) if (length(Ind_TS_ignore) == 0) { Ind_TS_ignore <- NULL } if (sum(!TS_ignore) == 0) { OutputsCrit <- list(NA) names(OutputsCrit) <- c("CritValue") return(OutputsCrit) } if (inherits(OutputsModel, "hourly")) { WarningTS <- 365 } if (inherits(OutputsModel, "daily")) { WarningTS <- 365 } if (inherits(OutputsModel, "monthly")) { WarningTS <- 12 } if (inherits(OutputsModel, "yearly")) { WarningTS <- 3 } if (sum(!TS_ignore) < WarningTS & warnings) { warning("\t criterion computed on less than ", WarningTS, " time-steps") } ##ErrorCrit______________________________________ Numer <- sum((VarSim - VarObs)^2, na.rm = TRUE) Denom <- sum(!is.na(VarObs)) if (Numer == 0) { Crit <- 0 } else { Crit <- sqrt(Numer / Denom) } if (is.numeric(Crit) & is.finite(Crit)) { CritValue <- Crit } ##Verbose______________________________________ if (verbose) { message("Crit. ", CritName, " = ", sprintf("%.4f", CritValue), "\n") } ##Output_________________________________________ OutputsCrit <- list(CritValue = CritValue, CritName = CritName, CritBestValue = CritBestValue, Multiplier = Multiplier, Ind_notcomputed = Ind_TS_ignore ) class(OutputsCrit) <- c("RMSE", "ErrorCrit") return(OutputsCrit) }