Commit 29f7bfc7 authored by Delaigue Olivier's avatar Delaigue Olivier
Browse files

v1.2.14.4 UPDATE: ErrorCrit_NSE now calls .ErrorCrit fun

Showing with 28 additions and 132 deletions
+28 -132
Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.2.14.3
Version: 1.2.14.4
Date: 2019-04-16
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
......
......@@ -14,7 +14,7 @@ output:
### 1.2.14.3 Release Notes (2019-04-16)
### 1.2.14.4 Release Notes (2019-04-16)
#### New features
......
ErrorCrit_NSE <- 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' or 'Compo' with NSE")
}
## Arguments check
if (!inherits(OutputsModel, "OutputsModel")) {
stop("'OutputsModel' must be of class 'OutputsModel'")
}
OutputsCritCheck <- .ErrorCrit(InputsCrit = InputsCrit, crit = "NSE")
##Initialisation_________________________________
CritName <- NA
CritVar <- InputsCrit$VarObs
if (InputsCrit$transfo == "") {
CritName <- "NSE[CritVar]"
}
if (InputsCrit$transfo == "sqrt") {
CritName <- "NSE[sqrt(CritVar)]"
}
if (InputsCrit$transfo == "log") {
CritName <- "NSE[log(CritVar)]"
}
if (InputsCrit$transfo == "inv") {
CritName <- "NSE[1/CritVar]"
}
if (InputsCrit$transfo == "sort") {
CritName <- "NSE[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$epsilon) & warnings) {
if (any(VarObs %in% 0)) {
warning("zeroes detected in 'Qobs': the corresponding time-steps will be excluded from the criteria computation if the epsilon argument of 'CreateInputsCrit' = NULL")
if (!OutputsCritCheck$CritCompute) {
CritValue <- NA
} else {
## Other variables preparation
meanVarObs <- mean(VarObs[!TS_ignore])
meanVarSim <- mean(VarSim[!TS_ignore])
## ErrorCrit
Emod <- sum((VarSim[!TS_ignore] - VarObs[!TS_ignore])^2)
Eref <- sum((VarObs[!TS_ignore] - mean(VarObs[!TS_ignore]))^2)
if (Emod == 0 & Eref == 0) {
Crit <- 0
} else {
Crit <- (1 - Emod / Eref)
}
if (is.numeric(Crit) & is.finite(Crit)) {
CritValue <- Crit
}
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")
}
##Other_variables_preparation
meanVarObs <- mean(VarObs[!TS_ignore])
meanVarSim <- mean(VarSim[!TS_ignore])
##ErrorCrit______________________________________
Emod <- sum((VarSim[!TS_ignore] - VarObs[!TS_ignore])^2)
Eref <- sum((VarObs[!TS_ignore] - mean(VarObs[!TS_ignore]))^2)
if (Emod == 0 & Eref == 0) {
Crit <- 0
} else {
Crit <- (1 - Emod / Eref)
}
if (is.numeric(Crit) & is.finite(Crit)) {
CritValue <- Crit
}
##Verbose______________________________________
if (verbose) {
message("Crit. ", CritName, " = ", sprintf("%.4f", CritValue), "\n")
## Verbose
if (verbose) {
message("Crit. ", CritName, " = ", sprintf("%.4f", CritValue), "\n")
}
}
##Output_________________________________________
## Output
OutputsCrit <- list(CritValue = CritValue,
CritName = CritName,
CritBestValue = CritBestValue,
......@@ -148,4 +43,5 @@ ErrorCrit_NSE <- function(InputsCrit, OutputsModel, warnings = TRUE, verbose = T
class(OutputsCrit) <- c("NSE", "ErrorCrit")
return(OutputsCrit)
}
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