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Commit 9c282325 authored by Delaigue Olivier's avatar Delaigue Olivier
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v1.6.3.45 style: format RunModel_CemaNeigeGR5H 

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Refs #14
parent d0f3169f
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 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
2 merge requests!26CRAN v1.6.9.21,!17Resolve "Clean the RunModel functions"
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DESCRIPTION
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Package: airGR Package: airGR
Type: Package Type: Package
Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling Title: Suite of GR Hydrological Models for Precipitation-Runoff Modelling
Version: 1.6.3.44 Version: 1.6.3.45
Date: 2020-11-11 Date: 2020-11-11
Authors@R: c( Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")), person("Laurent", "Coron", role = c("aut", "trl"), comment = c(ORCID = "0000-0002-1503-6204")),
......
NEWS.md
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...@@ -4,7 +4,7 @@ ...@@ -4,7 +4,7 @@
### 1.6.3.44 Release Notes (2020-11-11) ### 1.6.3.45 Release Notes (2020-11-11)
#### New features #### New features
......
R/RunModel_CemaNeigeGR5H.R
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RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){ RunModel_CemaNeigeGR5H <- function(InputsModel, RunOptions, Param) {
## Initialization of variables
IsHyst <- inherits(RunOptions, "hysteresis") IsHyst <- inherits(RunOptions, "hysteresis")
NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L) NParam <- ifelse(test = IsHyst, yes = 9L, no = 7L)
NParamCN <- NParam - 5L NParamCN <- NParam - 5L
NStates <- 4L NStates <- 4L
FortranOutputs <- .FortranOutputs(GR = "GR5H", isCN = TRUE) FortranOutputs <- .FortranOutputs(GR = "GR5H", isCN = TRUE)
IsIntStore <- inherits(RunOptions, "interception") IsIntStore <- inherits(RunOptions, "interception")
if(IsIntStore) { if (IsIntStore) {
Imax <- RunOptions$Imax Imax <- RunOptions$Imax
} else { } else {
Imax <- -99 Imax <- -99
} }
##Arguments_check
if(!inherits(InputsModel,"InputsModel")){ stop("'InputsModel' must be of class 'InputsModel'") } ## Arguments_check
if(!inherits(InputsModel,"hourly" )){ stop("'InputsModel' must be of class 'hourly' ") } if (!inherits(InputsModel, "InputsModel")) {
if(!inherits(InputsModel,"GR" )){ stop("'InputsModel' must be of class 'GR' ") } stop("'InputsModel' must be of class 'InputsModel'")
if(!inherits(InputsModel,"CemaNeige" )){ stop("'InputsModel' must be of class 'CemaNeige' ") } }
if(!inherits(RunOptions,"RunOptions" )){ stop("'RunOptions' must be of class 'RunOptions' ") } if (!inherits(InputsModel, "hourly")) {
if(!inherits(RunOptions,"GR" )){ stop("'RunOptions' must be of class 'GR' ") } stop("'InputsModel' must be of class 'hourly'")
if(!inherits(RunOptions,"CemaNeige" )){ stop("'RunOptions' must be of class 'CemaNeige' ") } }
if(!is.vector(Param) | !is.numeric(Param)){ stop("'Param' must be a numeric vector") } if (!inherits(InputsModel, "GR")) {
if(sum(!is.na(Param))!=NParam){ stop(paste("'Param' must be a vector of length ",NParam," and contain no NA",sep="")) } stop("'InputsModel' must be of class 'GR'")
Param <- as.double(Param); }
if (!inherits(InputsModel, "CemaNeige")) {
stop("'InputsModel' must be of class 'CemaNeige'")
}
if (!inherits(RunOptions, "RunOptions")) {
stop("'RunOptions' must be of class 'RunOptions'")
}
if (!inherits(RunOptions, "GR")) {
stop("'RunOptions' must be of class 'GR'")
}
if (!inherits(RunOptions, "CemaNeige")) {
stop("'RunOptions' must be of class 'CemaNeige'")
}
if (!is.vector(Param) | !is.numeric(Param)) {
stop("'Param' must be a numeric vector")
}
if (sum(!is.na(Param)) != NParam) {
stop(paste("'Param' must be a vector of length", NParam, "and contain no NA"))
}
Param <- as.double(Param)
Param_X1X3_threshold <- 1e-2 Param_X1X3_threshold <- 1e-2
Param_X4_threshold <- 0.5 Param_X4_threshold <- 0.5
...@@ -39,108 +61,131 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){ ...@@ -39,108 +61,131 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
Param[4L] <- Param_X4_threshold Param[4L] <- Param_X4_threshold
} }
##Input_data_preparation ## Input_data_preparation
if(identical(RunOptions$IndPeriod_WarmUp,as.integer(0))){ RunOptions$IndPeriod_WarmUp <- NULL; } if (identical(RunOptions$IndPeriod_WarmUp, as.integer(0))) {
IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp,RunOptions$IndPeriod_Run); RunOptions$IndPeriod_WarmUp <- NULL
}
IndPeriod1 <- c(RunOptions$IndPeriod_WarmUp, RunOptions$IndPeriod_Run)
LInputSeries <- as.integer(length(IndPeriod1)) LInputSeries <- as.integer(length(IndPeriod1))
if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs)); if ("all" %in% RunOptions$Outputs_Sim) {
} else { IndOutputsMod <- which(FortranOutputs %in% RunOptions$Outputs_Sim); } IndOutputsMod <- as.integer(1:length(FortranOutputs))
} else {
ParamCemaNeige <- Param[(length(Param)-1-2*as.integer(IsHyst)):length(Param)]; IndOutputsMod <- which(FortranOutputs %in% RunOptions$Outputs_Sim)
NParamMod <- as.integer(length(Param)-(2+2*as.integer(IsHyst))); }
ParamMod <- Param[1:NParamMod];
NLayers <- length(InputsModel$LayerPrecip); ParamCemaNeige <- Param[(length(Param) - 1 - 2 * as.integer(IsHyst)):length(Param)]
NStatesMod <- as.integer(length(RunOptions$IniStates)-NStates*NLayers); NParamMod <- as.integer(length(Param) - (2 + 2 * as.integer(IsHyst)))
ParamMod <- Param[1:NParamMod]
##Output_data_preparation NLayers <- length(InputsModel$LayerPrecip)
IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries; NStatesMod <- as.integer(length(RunOptions$IniStates) - NStates * NLayers)
ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim;
ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim;
## Output_data_preparation
##SNOW_MODULE________________________________________________________________________________## IndPeriod2 <- (length(RunOptions$IndPeriod_WarmUp)+1):LInputSeries
if(inherits(RunOptions,"CemaNeige")){ ExportDatesR <- "DatesR" %in% RunOptions$Outputs_Sim
if("all" %in% RunOptions$Outputs_Sim){ IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN)); ExportStateEnd <- "StateEnd" %in% RunOptions$Outputs_Sim
} else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim); }
CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- "CemaNeigeLayers"; ## SNOW_MODULE________________________________________________________________________________
if (inherits(RunOptions, "CemaNeige")) {
if ("all" %in% RunOptions$Outputs_Sim) {
IndOutputsCemaNeige <- as.integer(1:length(FortranOutputs$CN))
} else { IndOutputsCemaNeige <- which(FortranOutputs$CN %in% RunOptions$Outputs_Sim)
}
CemaNeigeLayers <- list()
CemaNeigeStateEnd <- NULL
NameCemaNeigeLayers <- "CemaNeigeLayers"
##Call_DLL_CemaNeige_________________________ ## Call_DLL_CemaNeige_________________________
for(iLayer in 1:NLayers){ for(iLayer in 1:NLayers) {
if (!IsHyst) { if (!IsHyst) {
StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)] StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers)]
} else { } else {
StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)] StateStartCemaNeige <- RunOptions$IniStates[(7 + 20*24 + 40*24) + c(iLayer, iLayer+NLayers, iLayer+2*NLayers, iLayer+3*NLayers)]
} }
RESULTS <- .Fortran("frun_cemaneige",PACKAGE="airGR", RESULTS <- .Fortran("frun_cemaneige",PACKAGE="airGR",
##inputs ## inputs
LInputs=LInputSeries, ### length of input and output series LInputs = LInputSeries, ### length of input and output series
InputsPrecip=InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h] InputsPrecip = InputsModel$LayerPrecip[[iLayer]][IndPeriod1], ### input series of total precipitation [mm/h]
InputsFracSolidPrecip=InputsModel$LayerFracSolidPrecip[[iLayer]][IndPeriod1], ### input series of fraction of solid precipitation [0-1] InputsFracSolidPrecip = InputsModel$LayerFracSolidPrecip[[iLayer]][IndPeriod1], ### input series of fraction of solid precipitation [0-1]
InputsTemp=InputsModel$LayerTemp[[iLayer]][IndPeriod1], ### input series of air mean temperature [degC] InputsTemp = InputsModel$LayerTemp[[iLayer]][IndPeriod1], ### input series of air mean temperature [degC]
MeanAnSolidPrecip=RunOptions$MeanAnSolidPrecip[iLayer], ### value of annual mean solid precip [mm/y] MeanAnSolidPrecip = RunOptions$MeanAnSolidPrecip[iLayer], ### value of annual mean solid precip [mm/y]
NParam=as.integer(NParamCN), ### number of model parameters = 2 or 4 NParam = as.integer(NParamCN), ### number of model parameters = 2 or 4
Param=as.double(ParamCemaNeige), ### parameter set Param = as.double(ParamCemaNeige), ### parameter set
NStates=as.integer(NStates), ### number of state variables used for model initialisation = 4 NStates = as.integer(NStates), ### number of state variables used for model initialisation = 4
StateStart=StateStartCemaNeige, ### state variables used when the model run starts StateStart = StateStartCemaNeige, ### state variables used when the model run starts
IsHyst = as.integer(IsHyst), ### use of hysteresis IsHyst = as.integer(IsHyst), ### use of hysteresis
NOutputs=as.integer(length(IndOutputsCemaNeige)), ### number of output series NOutputs = as.integer(length(IndOutputsCemaNeige)), ### number of output series
IndOutputs=IndOutputsCemaNeige, ### indices of output series IndOutputs = IndOutputsCemaNeige, ### indices of output series
##outputs ## outputs
Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsCemaNeige)), ### output series [mm] Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputsCemaNeige)), ### output series [mm]
StateEnd=rep(as.double(-999.999),as.integer(NStates)) ### state variables at the end of the model run StateEnd = rep(as.double(-999.999), as.integer(NStates)) ### state variables at the end of the model run
) )
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA; RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA; RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
##Data_storage ## Data_storage
CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]); CemaNeigeLayers[[iLayer]] <- lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i])
names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]; names(CemaNeigeLayers[[iLayer]]) <- FortranOutputs$CN[IndOutputsCemaNeige]
IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt"); IndPliqAndMelt <- which(names(CemaNeigeLayers[[iLayer]]) == "PliqAndMelt")
if(iLayer==1){ CatchMeltAndPliq <- RESULTS$Outputs[,IndPliqAndMelt]/NLayers; } if (iLayer == 1) {
if(iLayer >1){ CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[,IndPliqAndMelt]/NLayers; } CatchMeltAndPliq <- RESULTS$Outputs[, IndPliqAndMelt] / NLayers
if(ExportStateEnd){ CemaNeigeStateEnd <- c(CemaNeigeStateEnd,RESULTS$StateEnd); } }
rm(RESULTS); if (iLayer > 1) {
} ###ENDFOR_iLayer CatchMeltAndPliq <- CatchMeltAndPliq + RESULTS$Outputs[, IndPliqAndMelt] / NLayers
}
if (ExportStateEnd) {
CemaNeigeStateEnd <- c(CemaNeigeStateEnd, RESULTS$StateEnd)
}
rm(RESULTS)
} ### ENDFOR_iLayer
names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers)) names(CemaNeigeLayers) <- sprintf("Layer%02i", seq_len(NLayers))
} ###ENDIF_RunSnowModule } ### ENDIF_RunSnowModule
if(!inherits(RunOptions,"CemaNeige")){ if (!inherits(RunOptions, "CemaNeige")) {
CemaNeigeLayers <- list(); CemaNeigeStateEnd <- NULL; NameCemaNeigeLayers <- NULL; CemaNeigeLayers <- list()
CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]; } CemaNeigeStateEnd <- NULL
NameCemaNeigeLayers <- NULL
CatchMeltAndPliq <- InputsModel$Precip[IndPeriod1]
}
##MODEL______________________________________________________________________________________## ## MODEL______________________________________________________________________________________
if("all" %in% RunOptions$Outputs_Sim){ IndOutputsMod <- as.integer(1:length(FortranOutputs$GR)); if ("all" %in% RunOptions$Outputs_Sim) {
} else { IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim); } IndOutputsMod <- as.integer(1:length(FortranOutputs$GR))
} else {
IndOutputsMod <- which(FortranOutputs$GR %in% RunOptions$Outputs_Sim)
}
##Use_of_IniResLevels ## Use_of_IniResLevels
if(!is.null(RunOptions$IniResLevels)){ if (!is.null(RunOptions$IniResLevels)) {
RunOptions$IniStates[1] <- RunOptions$IniResLevels[1]*Param[1]; ### production store level (mm) RunOptions$IniStates[1] <- RunOptions$IniResLevels[1] * Param[1] ### production store level (mm)
RunOptions$IniStates[2] <- RunOptions$IniResLevels[2]*Param[3]; ### routing store level (mm) RunOptions$IniStates[2] <- RunOptions$IniResLevels[2] * Param[3] ### routing store level (mm)
if(IsIntStore) { if (IsIntStore) {
RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax; ### interception store level (mm) RunOptions$IniStates[4] <- RunOptions$IniResLevels[4] * Imax ### interception store level (mm)
} }
} }
##Call_fortan ## Call_fortan
RESULTS <- .Fortran("frun_gr5h",PACKAGE="airGR", RESULTS <- .Fortran("frun_gr5h",PACKAGE="airGR",
##inputs ## inputs
LInputs=LInputSeries, ### length of input and output series LInputs = LInputSeries, ### length of input and output series
InputsPrecip=InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h] InputsPrecip = InputsModel$Precip[IndPeriod1], ### input series of total precipitation [mm/h]
InputsPE=InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h] InputsPE = InputsModel$PotEvap[IndPeriod1], ### input series potential evapotranspiration [mm/h]
NParam=as.integer(length(Param)), ### number of model parameter NParam = as.integer(length(Param)), ### number of model parameter
Param=Param, ### parameter set Param = Param, ### parameter set
NStates=as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising NStates = as.integer(length(RunOptions$IniStates)), ### number of state variables used for model initialising
StateStart=RunOptions$IniStates, ### state variables used when the model run starts StateStart = RunOptions$IniStates, ### state variables used when the model run starts
Imax=Imax, ### maximal capacity of interception store Imax = Imax, ### maximal capacity of interception store
NOutputs=as.integer(length(IndOutputsMod)), ### number of output series NOutputs = as.integer(length(IndOutputsMod)), ### number of output series
IndOutputs=IndOutputsMod, ### indices of output series IndOutputs = IndOutputsMod, ### indices of output series
##outputs ## outputs
Outputs=matrix(as.double(-999.999),nrow=LInputSeries,ncol=length(IndOutputsMod)), ### output series [mm or mm/h] Outputs = matrix(as.double(-999.999), nrow = LInputSeries, ncol = length(IndOutputsMod)), ### output series [mm or mm/h]
StateEnd=rep(as.double(-999.999),length(RunOptions$IniStates)) ### state variables at the end of the model run StateEnd = rep(as.double(-999.999), length(RunOptions$IniStates)) ### state variables at the end of the model run
) )
RESULTS$Outputs[ round(RESULTS$Outputs ,3)==(-999.999)] <- NA; RESULTS$Outputs[ round(RESULTS$Outputs , 3) == -999.999] <- NA
RESULTS$StateEnd[round(RESULTS$StateEnd,3)==(-999.999)] <- NA; RESULTS$StateEnd[round(RESULTS$StateEnd, 3) == -999.999] <- NA
if (ExportStateEnd) { if (ExportStateEnd) {
RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location RESULTS$StateEnd[-3L] <- ifelse(RESULTS$StateEnd[-3L] < 0, 0, RESULTS$StateEnd[-3L]) ### remove negative values except for the ExpStore location
idNStates <- seq_len(NStates*NLayers) %% NStates idNStates <- seq_len(NStates*NLayers) %% NStates
...@@ -154,45 +199,51 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){ ...@@ -154,45 +199,51 @@ RunModel_CemaNeigeGR5H <- function(InputsModel,RunOptions,Param){
GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]], GlocmaxCemaNeigeLayers = CemaNeigeStateEnd[seq_len(NStates*NLayers)[idNStates == 0]],
verbose = FALSE) verbose = FALSE)
} }
if(inherits(RunOptions,"CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim){ RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]; } if (inherits(RunOptions, "CemaNeige") & "Precip" %in% RunOptions$Outputs_Sim) {
RESULTS$Outputs[,which(FortranOutputs$GR[IndOutputsMod]=="Precip")] <- InputsModel$Precip[IndPeriod1]
##Output_data_preparation }
##OutputsModel_only
##OutputsModel_only ## Output_data_preparation
if(!ExportDatesR & !ExportStateEnd){ ## OutputsModel_only
OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]), ## OutputsModel_only
list(CemaNeigeLayers) ); if (!ExportDatesR & !ExportStateEnd) {
names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); } OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
##DatesR_and_OutputsModel_only list(CemaNeigeLayers))
if( ExportDatesR & !ExportStateEnd){ names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]), }
lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]), ## DatesR_and_OutputsModel_only
list(CemaNeigeLayers) ); if ( ExportDatesR & !ExportStateEnd) {
names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers); } OutputsModel <- c(list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
##OutputsModel_and_SateEnd_only lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
if(!ExportDatesR & ExportStateEnd){ list(CemaNeigeLayers))
OutputsModel <- c( lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]), names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers)
list(CemaNeigeLayers), }
list(RESULTS$StateEnd) ); ## OutputsModel_and_SateEnd_only
names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); } if (!ExportDatesR & ExportStateEnd) {
##DatesR_and_OutputsModel_and_SateEnd OutputsModel <- c(lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
if( ExportDatesR & ExportStateEnd){ list(CemaNeigeLayers),
list(RESULTS$StateEnd))
names(OutputsModel) <- c(FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
}
## DatesR_and_OutputsModel_and_SateEnd
if ( ExportDatesR & ExportStateEnd) {
OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]), OutputsModel <- c( list(InputsModel$DatesR[RunOptions$IndPeriod_Run]),
lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2,i]), lapply(seq_len(RESULTS$NOutputs), function(i) RESULTS$Outputs[IndPeriod2, i]),
list(CemaNeigeLayers), list(CemaNeigeLayers),
list(RESULTS$StateEnd) ); list(RESULTS$StateEnd))
names(OutputsModel) <- c("DatesR",FortranOutputs$GR[IndOutputsMod],NameCemaNeigeLayers,"StateEnd"); } names(OutputsModel) <- c("DatesR", FortranOutputs$GR[IndOutputsMod], NameCemaNeigeLayers, "StateEnd")
}
##End ## End
rm(RESULTS); rm(RESULTS)
class(OutputsModel) <- c("OutputsModel","hourly","GR","CemaNeige"); class(OutputsModel) <- c("OutputsModel", "hourly", "GR", "CemaNeige")
if(IsHyst) { if (IsHyst) {
class(OutputsModel) <- c(class(OutputsModel), "hysteresis") class(OutputsModel) <- c(class(OutputsModel), "hysteresis")
} }
if(IsIntStore) { if (IsIntStore) {
class(OutputsModel) <- c(class(OutputsModel), "interception") class(OutputsModel) <- c(class(OutputsModel), "interception")
} }
return(OutputsModel); return(OutputsModel)
} }
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