CreateInputsModel <- function(FUN_MOD,
DatesR,
Precip, PrecipScale = TRUE,
PotEvap = NULL,
TempMean = NULL, TempMin = NULL, TempMax = NULL,
ZInputs = NULL, HypsoData = NULL, NLayers = 5,
verbose = TRUE) {
ObjectClass <- NULL
##check_FUN_MOD
BOOL <- FALSE
if (identical(FUN_MOD, RunModel_GR4H)) {
ObjectClass <- c(ObjectClass, "hourly", "GR")
TimeStep <- as.integer(60 * 60)
BOOL <- TRUE
}
if (identical(FUN_MOD, RunModel_GR4J) |
identical(FUN_MOD, RunModel_GR5J) |
identical(FUN_MOD, RunModel_GR6J)) {
ObjectClass <- c(ObjectClass, "daily", "GR")
TimeStep <- as.integer(24 * 60 * 60)
BOOL <- TRUE
}
if (identical(FUN_MOD, RunModel_GR2M)) {
ObjectClass <- c(ObjectClass, "GR", "monthly")
TimeStep <- as.integer(c(28, 29, 30, 31) * 24 * 60 * 60)
BOOL <- TRUE
}
if (identical(FUN_MOD, RunModel_GR1A)) {
ObjectClass <- c(ObjectClass, "GR", "yearly")
TimeStep <- as.integer(c(365, 366) * 24 * 60 * 60)
BOOL <- TRUE
}
if (identical(FUN_MOD, RunModel_CemaNeige)) {
ObjectClass <- c(ObjectClass, "daily", "CemaNeige")
TimeStep <- as.integer(24 * 60 * 60)
BOOL <- TRUE
}
if (identical(FUN_MOD, RunModel_CemaNeigeGR4J) |
identical(FUN_MOD, RunModel_CemaNeigeGR5J) |
identical(FUN_MOD, RunModel_CemaNeigeGR6J)) {
ObjectClass <- c(ObjectClass, "daily", "GR", "CemaNeige")
TimeStep <- as.integer(24 * 60 * 60)
BOOL <- TRUE
}
if (!BOOL) {
stop("Incorrect FUN_MOD for use in CreateInputsModel")
}
##check_arguments
if ("GR" %in% ObjectClass | "CemaNeige" %in% ObjectClass) {
if (is.null(DatesR)) {
stop("DatesR is missing")
}
if ("POSIXlt" %in% class(DatesR) == FALSE & "POSIXct" %in% class(DatesR) == FALSE) {
stop("DatesR must be defined as POSIXlt or POSIXct")
}
if ("POSIXlt" %in% class(DatesR) == FALSE) {
DatesR <- as.POSIXlt(DatesR)
}
if (difftime(tail(DatesR, 1), tail(DatesR, 2), units = "secs")[[1]] %in% TimeStep == FALSE) {
TimeStepName <- grep("hourly|daily|monthly|yearly", ObjectClass, value = TRUE)
stop(paste0("The time step of the model inputs must be ", TimeStepName, "\n"))
}
if (any(duplicated(DatesR))) {
stop("DatesR must not include duplicated values")
}
LLL <- length(DatesR)
}
if ("GR" %in% ObjectClass) {
if (is.null(Precip)) {
stop("Precip is missing")
}
if (is.null(PotEvap)) {
stop("PotEvap is missing")
}
if (!is.vector(Precip) | !is.vector(PotEvap)) {
stop("Precip and PotEvap must be vectors of numeric values")
}
if (!is.numeric(Precip) | !is.numeric(PotEvap)) {
stop("Precip and PotEvap must be vectors of numeric values")
}
if (length(Precip) != LLL | length(PotEvap) != LLL) {
stop("Precip, PotEvap and DatesR must have the same length")
}
}
if ("CemaNeige" %in% ObjectClass) {
if (is.null(Precip)) {
stop("Precip is missing")
}
if (is.null(TempMean)) {
stop("TempMean is missing")
}
if (!is.vector(Precip) | !is.vector(TempMean)) {
stop("Precip and TempMean must be vectors of numeric values")
}
if (!is.numeric(Precip) | !is.numeric(TempMean)) {
stop("Precip and TempMean must be vectors of numeric values")
}
if (length(Precip) != LLL | length(TempMean) != LLL) {
stop("Precip, TempMean and DatesR must have the same length")
}
if (is.null(TempMin) != is.null(TempMax)) {
stop("TempMin and TempMax must be both defined if not null")
}
if (!is.null(TempMin) & !is.null(TempMax)) {
if (!is.vector(TempMin) | !is.vector(TempMax)) {
stop("TempMin and TempMax must be vectors of numeric values")
}
if (!is.numeric(TempMin) | !is.numeric(TempMax)) {
stop("TempMin and TempMax must be vectors of numeric values")
}
if (length(TempMin) != LLL | length(TempMax) != LLL) {
stop("TempMin, TempMax and DatesR must have the same length")
}
}
if (!is.null(HypsoData)) {
if (!is.vector(HypsoData)) {
stop("HypsoData must be a vector of numeric values if not null")
}
if (!is.numeric(HypsoData)) {
stop("HypsoData must be a vector of numeric values if not null")
}
if (length(HypsoData) != 101) {
stop("HypsoData must be of length 101 if not null")
}
if (sum(is.na(HypsoData)) != 0 & sum(is.na(HypsoData)) != 101) {
stop("HypsoData must not contain any NA if not null")
}
}
if (!is.null(ZInputs)) {
if (length(ZInputs) != 1) {
stop("\t ZInputs must be a single numeric value if not null")
}
if (is.na(ZInputs) | !is.numeric(ZInputs)) {
stop("\t ZInputs must be a single numeric value if not null")
}
}
if (is.null(HypsoData)) {
if (verbose) {
warning("\t HypsoData is missing => a single layer is used and no extrapolation is made")
}
HypsoData <- as.numeric(rep(NA, 101))
ZInputs <- as.numeric(NA)
NLayers <- as.integer(1)
}
if (is.null(ZInputs)) {
if (verbose & !identical(HypsoData, as.numeric(rep(NA, 101)))) {
warning("\t ZInputs is missing => HypsoData[51] is used")
}
ZInputs <- HypsoData[51L]
}
if (NLayers <= 0) {
stop("NLayers must be a positive integer value")
}
if (NLayers != as.integer(NLayers)) {
warning("Coerce NLayers to be of integer type (", NLayers, " => ", as.integer(NLayers), ")")
NLayers <- as.integer(NLayers)
}
}
##check_NA_values
BOOL_NA <- rep(FALSE, length(DatesR))
if ("GR" %in% ObjectClass) {
BOOL_NA_TMP <- (Precip < 0) | is.na(Precip)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < 0 or NA values detected in Precip series")
}
}
BOOL_NA_TMP <- (PotEvap < 0) | is.na(PotEvap)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < 0 or NA values detected in PotEvap series")
}
}
}
if ("CemaNeige" %in% ObjectClass) {
BOOL_NA_TMP <- (Precip < 0) | is.na(Precip)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < 0 or NA values detected in Precip series")
}
}
BOOL_NA_TMP <- (TempMean < (-150)) | is.na(TempMean)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < -150) or NA values detected in TempMean series")
}
}
if (!is.null(TempMin) & !is.null(TempMax)) {
BOOL_NA_TMP <- (TempMin < (-150)) | is.na(TempMin)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < -150) or NA values detected in TempMin series")
}
}
BOOL_NA_TMP <- (TempMax < (-150)) | is.na(TempMax)
if (sum(BOOL_NA_TMP) != 0) {
BOOL_NA <- BOOL_NA | BOOL_NA_TMP
if (verbose) {
warning("\t Values < -150) or NA values detected in TempMax series")
}
}
}
}
if (sum(BOOL_NA) != 0) {
WTxt <- NULL
WTxt <- paste(WTxt, "\t Missing values are not allowed in InputsModel", sep = "")
Select <- (max(which(BOOL_NA)) + 1):length(BOOL_NA)
if (Select[1L] > Select[2L]) {
stop("Time series could not be trunced since missing values were detected at the list time-step")
}
if ("GR" %in% ObjectClass) {
Precip <- Precip[Select]
PotEvap <- PotEvap[Select]
}
if ("CemaNeige" %in% ObjectClass) {
Precip <- Precip[Select]
TempMean <- TempMean[Select]
if (!is.null(TempMin) & !is.null(TempMax)) {
TempMin <- TempMin[Select]
TempMax <- TempMax[Select]
}
}
DatesR <- DatesR[Select]
WTxt <- paste(WTxt, "\t -> Data were trunced to keep the most recent available time-steps", sep = "")
WTxt <- paste(WTxt, "\t -> ", length(Select), " time-steps were kept", sep = "")
if (!is.null(WTxt) & verbose) {
warning(WTxt)
}
}
##DataAltiExtrapolation_Valery
if ("CemaNeige" %in% ObjectClass) {
RESULT <- DataAltiExtrapolation_Valery(DatesR = DatesR,
Precip = Precip, PrecipScale = PrecipScale,
TempMean = TempMean, TempMin = TempMin, TempMax = TempMax,
ZInputs = ZInputs, HypsoData = HypsoData, NLayers = NLayers,
verbose = verbose)
if (verbose) {
if (NLayers == 1) {
message("\t Input series were successfully created on 1 elevation layer for use by CemaNeige")
} else {
message( "\t Input series were successfully created on ", NLayers, " elevation layers for use by CemaNeige")
}
}
}
##Create_InputsModel
InputsModel <- list(DatesR = DatesR)
if ("GR" %in% ObjectClass) {
InputsModel <- c(InputsModel, list(Precip = as.double(Precip), PotEvap = as.double(PotEvap)))
}
if ("CemaNeige" %in% ObjectClass) {
InputsModel <- c(InputsModel, list(LayerPrecip = RESULT$LayerPrecip,
LayerTempMean = RESULT$LayerTempMean,
LayerFracSolidPrecip = RESULT$LayerFracSolidPrecip,
ZLayers = RESULT$ZLayers))
}
class(InputsModel) <- c("InputsModel", ObjectClass)
return(InputsModel)
}