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Commit f9b1b1a6 authored by Delaigue Olivier's avatar Delaigue Olivier
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v1.2.14.3 UPDATE: ErrorCrit_KGE2 now calls .ErrorCrit fun

parent 20b44fc4
dev 115-add-pcict-date-format-managment 118-plot-outputsmodel-remove-case-sensitivity-to-the-which-argument 136-decreased-performance-of-calibration-execution-time 161-runmodel_lag-proposal-for-a-better-transformation-and-screening-of-the-parameters 165-add-missing-isintstore-argument-in-createcaliboptions 171-check-error-direct-call-of-as-data-frame-posixct-is-deprecated-use-as-data-frame-vector-or-as 191-speed-up-runmodel_lag-when-it-is-used-alone 33-merge-airgr-and-airgrplus-functions 60-migrate-transfoparam-functions-and-createcaliboptions-to-s3-methods 96-parallelize-the-grid-screening-step-during-calibration airGRplus master rmOptions CRAN_v1.7.6 CRAN_v1.7.5 CRAN_v1.7.4 CRAN_v1.7.3 CRAN_v1.7.2 CRAN_v1.7.1 CRAN_v1.7.0 CRAN_v1.6.12 CRAN_v1.6.11 CRAN_v1.6.10.4 CRAN_v1.6.9.27 CRAN_v1.6.9.24 CRAN_v1.6.9.23 CRAN_v1.6.9.21 CRAN_v1.4.3.65 CRAN_v1.4.3.60 CRAN_v1.4.3.52 CRAN_v1.3.2.42 CRAN_v1.3.2.41 CRAN_v1.3.2.40 CRAN_v1.3.2.39 CRAN_v1.3.2.23 CRAN_v1.3.2.17
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DESCRIPTION
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Package: airGR
Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.2.14.2
Version: 1.2.14.3
Date: 2019-04-16
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
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NEWS.rmd
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......@@ -14,7 +14,7 @@ output:
### 1.2.14.2 Release Notes (2019-04-16)
### 1.2.14.3 Release Notes (2019-04-16)
#### New features
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R/ErrorCrit_KGE2.R
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ErrorCrit_KGE2 <- 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 KGE'")
}
## Arguments check
if (!inherits(OutputsModel, "OutputsModel")) {
stop("'OutputsModel' must be of class 'OutputsModel'")
}
OutputsCritCheck <- .ErrorCrit(InputsCrit = InputsCrit, crit = "RMSE")
##Initialisation_________________________________
CritName <- NA
CritVar <- InputsCrit$VarObs
if (InputsCrit$transfo == "") {
CritName <- "KGE'[CritVar]"
}
if (InputsCrit$transfo == "sqrt") {
CritName <- "KGE'[sqrt(CritVar)]"
}
if (InputsCrit$transfo == "log") {
CritName <- "KGE'[log(CritVar)]"
}
if (InputsCrit$transfo == "inv") {
CritName <- "KGE'[1/CritVar]"
}
if (InputsCrit$transfo == "sort") {
CritName <- "KGE'[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])
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 (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 (sum(!TS_ignore) == 1) {
OutputsCrit <- list(NA)
names(OutputsCrit) <- c("CritValue")
return(OutputsCrit)
} ### to avoid a problem in standard deviation computation
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])
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
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 {
Crit <- 0
CVsim <- sd(VarSim[!TS_ignore]) / meanVarSim
}
} 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
if (meanVarObs == 0) {
if (sd(VarObs[!TS_ignore]) == 0) {
CVobs <- 1
} else {
CVobs <- 99999
}
} else {
CVsim <- 99999
CVobs <- sd(VarObs[!TS_ignore]) / meanVarObs
}
if (CVsim == 0 &
CVobs == 0) {
Crit <- 1
} else {
Crit <- CVsim / CVobs
}
if (is.numeric(Crit) & is.finite(Crit)) {
SubCritValues[iCrit] <- Crit
}
} else {
CVsim <- sd(VarSim[!TS_ignore]) / meanVarSim
}
if (meanVarObs == 0) {
if (sd(VarObs[!TS_ignore]) == 0) {
CVobs <- 1
## SubErrorCrit KGE beta
iCrit <- iCrit + 1
SubCritPrint[iCrit] <- paste(CritName, " mean(sim)/mean(obs) =", sep = "")
SubCritValues[iCrit] <- NA
SubCritNames[iCrit] <- "beta"
if (meanVarSim == 0 & meanVarObs == 0) {
Crit <- 1
} else {
CVobs <- 99999
Crit <- meanVarSim / meanVarObs
}
if (is.numeric(Crit) & is.finite(Crit)) {
SubCritValues[iCrit] <- Crit
}
## ErrorCrit
if (sum(is.na(SubCritValues)) == 0) {
CritValue <- (1 - sqrt((SubCritValues[1] - 1)^2 + (SubCritValues[2] - 1)^2 + (SubCritValues[3] - 1)^2))
}
## Verbose
if (verbose) {
message("Crit. ", CritName, " = ", sprintf("%.4f", CritValue))
message(paste("\tSubCrit.", SubCritPrint, sprintf("%.4f", SubCritValues), "\n", sep = " "))
}
} else {
CVobs <- sd(VarObs[!TS_ignore]) / meanVarObs
}
if (CVsim == 0 &
CVobs == 0) {
Crit <- 1
} else {
Crit <- CVsim / CVobs
}
if (is.numeric(Crit) & is.finite(Crit)) {
SubCritValues[iCrit] <- Crit
}
##SubErrorCrit_____KGE_beta______________________
iCrit <- iCrit + 1
SubCritPrint[iCrit] <- paste(CritName, " mean(sim)/mean(obs) =", sep = "")
SubCritValues[iCrit] <- NA
SubCritNames[iCrit] <- "beta"
if (meanVarSim == 0 & meanVarObs == 0) {
Crit <- 1
} else {
Crit <- meanVarSim / meanVarObs
}
if (is.numeric(Crit) & is.finite(Crit)) {
SubCritValues[iCrit] <- Crit
}
##ErrorCrit______________________________________
if (sum(is.na(SubCritValues)) == 0) {
CritValue <- (1 - sqrt((SubCritValues[1] - 1)^2 + (SubCritValues[2] - 1)^2 + (SubCritValues[3] - 1)^2))
}
##Verbose______________________________________
if (verbose) {
message("Crit. ", CritName, " = ", sprintf("%.4f", CritValue))
message(paste("\tSubCrit.", SubCritPrint, sprintf("%.4f", SubCritValues), "\n", sep = " "))
}
##Output_________________________________________
## Output
OutputsCrit <- list(CritValue = CritValue,
CritName = CritName,
SubCritValues = SubCritValues,
SubCritNames = SubCritNames,
CritBestValue = CritBestValue,
Multiplier = Multiplier,
Ind_notcomputed = Ind_TS_ignore
)
Ind_notcomputed = Ind_TS_ignore)
class(OutputsCrit) <- c("KGE2", "ErrorCrit")
return(OutputsCrit)
......
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