From 336d5e9b423804869940a736f3ccb7774a753235 Mon Sep 17 00:00:00 2001
From: unknown <olivier.delaigue@ANPI1430.antony.irstea.priv>
Date: Wed, 18 Jan 2017 08:28:43 +0100
Subject: [PATCH] v1.0.4.1 function Calibration_Michel() cleaned
---
DESCRIPTION | 4 +-
R/Calibration_Michel.R | 542 ++++++++++++++++++++++++++---------------
inst/CITATION | 8 +-
3 files changed, 346 insertions(+), 208 deletions(-)
diff --git a/DESCRIPTION b/DESCRIPTION
index b77b7e2a..68420ade 100644
--- a/DESCRIPTION
+++ b/DESCRIPTION
@@ -1,8 +1,8 @@
Package: airGR
Type: Package
Title: Suite of GR hydrological models for precipitation-runoff modelling
-Version: 1.0.3
-Date: 2016-12-09
+Version: 1.0.4.1
+Date: 2017-01-18
Authors@R: c(
person("Laurent", "Coron", role = c("aut", "trl")),
person("Charles", "Perrin", role = c("aut", "ths")),
diff --git a/R/Calibration_Michel.R b/R/Calibration_Michel.R
index 73ebc3b9..d5d154db 100644
--- a/R/Calibration_Michel.R
+++ b/R/Calibration_Michel.R
@@ -1,57 +1,116 @@
-Calibration_Michel <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FUN_MOD,FUN_CRIT,FUN_TRANSFO=NULL, verbose = TRUE){
+Calibration_Michel <- function(InputsModel, RunOptions, InputsCrit, CalibOptions, FUN_MOD, FUN_CRIT, FUN_TRANSFO = NULL, verbose = TRUE) {
##_____Arguments_check_____________________________________________________________________
- if(inherits(InputsModel,"InputsModel")==FALSE){ stop("InputsModel must be of class 'InputsModel' \n"); return(NULL); }
- if(inherits(RunOptions,"RunOptions")==FALSE){ stop("RunOptions must be of class 'RunOptions' \n"); return(NULL); }
- if(inherits(InputsCrit,"InputsCrit")==FALSE){ stop("InputsCrit must be of class 'InputsCrit' \n"); return(NULL); }
- if(inherits(CalibOptions,"CalibOptions")==FALSE){ stop("CalibOptions must be of class 'CalibOptions' \n"); return(NULL); }
- if(inherits(CalibOptions,"HBAN")==FALSE){ stop("CalibOptions must be of class 'HBAN' if Calibration_Michel is used \n"); return(NULL); }
+ if (!inherits(InputsModel, "InputsModel")) {
+ stop("InputsModel must be of class 'InputsModel' \n")
+ return(NULL)
+ }
+ if (!inherits(RunOptions, "RunOptions")) {
+ stop("RunOptions must be of class 'RunOptions' \n")
+ return(NULL)
+ }
+ if (!inherits(InputsCrit, "InputsCrit")) {
+ stop("InputsCrit must be of class 'InputsCrit' \n")
+ return(NULL)
+ }
+ if (!inherits(CalibOptions, "CalibOptions")) {
+ stop("CalibOptions must be of class 'CalibOptions' \n")
+ return(NULL)
+ }
+ if (!inherits(CalibOptions, "HBAN")) {
+ stop("CalibOptions must be of class 'HBAN' if Calibration_Michel is used \n")
+ return(NULL)
+ }
##_check_FUN_TRANSFO
- if(is.null(FUN_TRANSFO)){
- if(identical(FUN_MOD,RunModel_GR4H )){ FUN_TRANSFO <- TransfoParam_GR4H ; }
- if(identical(FUN_MOD,RunModel_GR4J )){ FUN_TRANSFO <- TransfoParam_GR4J ; }
- if(identical(FUN_MOD,RunModel_GR5J )){ FUN_TRANSFO <- TransfoParam_GR5J ; }
- if(identical(FUN_MOD,RunModel_GR6J )){ FUN_TRANSFO <- TransfoParam_GR6J ; }
- if(identical(FUN_MOD,RunModel_GR2M )){ FUN_TRANSFO <- TransfoParam_GR2M ; }
- if(identical(FUN_MOD,RunModel_GR1A )){ FUN_TRANSFO <- TransfoParam_GR1A ; }
- if(identical(FUN_MOD,RunModel_CemaNeige )){ FUN_TRANSFO <- TransfoParam_CemaNeige; }
- if(identical(FUN_MOD,RunModel_CemaNeigeGR4J) | identical(FUN_MOD,RunModel_CemaNeigeGR5J) | identical(FUN_MOD,RunModel_CemaNeigeGR6J)){
- if(identical(FUN_MOD,RunModel_CemaNeigeGR4J)){ FUN1 <- TransfoParam_GR4J; FUN2 <- TransfoParam_CemaNeige; }
- if(identical(FUN_MOD,RunModel_CemaNeigeGR5J)){ FUN1 <- TransfoParam_GR5J; FUN2 <- TransfoParam_CemaNeige; }
- if(identical(FUN_MOD,RunModel_CemaNeigeGR6J)){ FUN1 <- TransfoParam_GR6J; FUN2 <- TransfoParam_CemaNeige; }
- FUN_TRANSFO <- function(ParamIn,Direction){
- Bool <- is.matrix(ParamIn);
- if(Bool==FALSE){ ParamIn <- rbind(ParamIn); }
- ParamOut <- NA*ParamIn;
- NParam <- ncol(ParamIn);
- ParamOut[, 1:(NParam-2)] <- FUN1(ParamIn[, 1:(NParam-2)],Direction);
- ParamOut[,(NParam-1):NParam ] <- FUN2(ParamIn[,(NParam-1):NParam ],Direction);
- if(Bool==FALSE){ ParamOut <- ParamOut[1,]; }
- return(ParamOut);
+ if (is.null(FUN_TRANSFO)) {
+ if (identical(FUN_MOD, RunModel_GR4H )) {
+ FUN_TRANSFO <- TransfoParam_GR4H
+ }
+ if (identical(FUN_MOD, RunModel_GR4J )) {
+ FUN_TRANSFO <- TransfoParam_GR4J
+ }
+ if (identical(FUN_MOD, RunModel_GR5J )) {
+ FUN_TRANSFO <- TransfoParam_GR5J
+ }
+ if (identical(FUN_MOD, RunModel_GR6J )) {
+ FUN_TRANSFO <- TransfoParam_GR6J
+ }
+ if (identical(FUN_MOD, RunModel_GR2M )) {
+ FUN_TRANSFO <- TransfoParam_GR2M
+ }
+ if (identical(FUN_MOD, RunModel_GR1A )) {
+ FUN_TRANSFO <- TransfoParam_GR1A
+ }
+ if (identical(FUN_MOD, RunModel_CemaNeige )) {
+ FUN_TRANSFO <- TransfoParam_CemaNeige
+ }
+ if (identical(FUN_MOD, RunModel_CemaNeigeGR4J) | identical(FUN_MOD, RunModel_CemaNeigeGR5J) | identical(FUN_MOD, RunModel_CemaNeigeGR6J)) {
+ if (identical(FUN_MOD, RunModel_CemaNeigeGR4J)) {
+ FUN1 <- TransfoParam_GR4J
+ FUN2 <- TransfoParam_CemaNeige
}
+ if (identical(FUN_MOD, RunModel_CemaNeigeGR5J)) {
+ FUN1 <- TransfoParam_GR5J
+ FUN2 <- TransfoParam_CemaNeige
+ }
+ if (identical(FUN_MOD,RunModel_CemaNeigeGR6J)) {
+ FUN1 <- TransfoParam_GR6J
+ FUN2 <- TransfoParam_CemaNeige
+ }
+ FUN_TRANSFO <- function(ParamIn, Direction) {
+ Bool <- is.matrix(ParamIn)
+ if (Bool == FALSE) {
+ ParamIn <- rbind(ParamIn)
+ }
+ ParamOut <- NA*ParamIn
+ NParam <- ncol(ParamIn)
+ ParamOut[, 1:(NParam-2)] <- FUN1(ParamIn[, 1:(NParam-2)], Direction)
+ ParamOut[, (NParam-1):NParam ] <- FUN2(ParamIn[, (NParam-1):NParam ], Direction)
+ if (Bool == FALSE) {
+ ParamOut <- ParamOut[1, ]
+ }
+ return(ParamOut)
+ }
+ }
+ if (is.null(FUN_TRANSFO)) {
+ stop("FUN_TRANSFO was not found (in Calibration function) \n")
+ return(NULL)
}
- if(is.null(FUN_TRANSFO)){ stop("FUN_TRANSFO was not found (in Calibration function) \n"); return(NULL); }
}
##_variables_initialisation
- ParamFinalR <- NULL; ParamFinalT <- NULL; CritFinal <- NULL;
- NRuns <- 0; NIter <- 0;
- if("StartParamDistrib" %in% names(CalibOptions)){ PrefilteringType <- 2; } else { PrefilteringType <- 1; }
- if(PrefilteringType==1){ NParam <- ncol(CalibOptions$StartParamList); }
- if(PrefilteringType==2){ NParam <- ncol(CalibOptions$StartParamDistrib); }
- if(NParam>20){ stop("Calibration_Michel can handle a maximum of 20 parameters \n"); return(NULL); }
- HistParamR <- matrix(NA,nrow=500*NParam,ncol=NParam);
- HistParamT <- matrix(NA,nrow=500*NParam,ncol=NParam);
- HistCrit <- matrix(NA,nrow=500*NParam,ncol=1);
- CritName <- NULL;
- CritBestValue <- NULL;
- Multiplier <- NULL;
- CritOptim <- +1E100;
+ ParamFinalR <- NULL
+ ParamFinalT <- NULL
+ CritFinal <- NULL
+ NRuns <- 0
+ NIter <- 0
+ if ("StartParamDistrib" %in% names(CalibOptions)) {
+ PrefilteringType <- 2
+ } else {
+ PrefilteringType <- 1
+ }
+ if (PrefilteringType == 1) {
+ NParam <- ncol(CalibOptions$StartParamList)
+ }
+ if (PrefilteringType == 2) {
+ NParam <- ncol(CalibOptions$StartParamDistrib)
+ }
+ if (NParam > 20) {
+ stop("Calibration_Michel can handle a maximum of 20 parameters \n")
+ return(NULL)
+ }
+ HistParamR <- matrix(NA, nrow = 500*NParam, ncol = NParam)
+ HistParamT <- matrix(NA, nrow = 500*NParam, ncol = NParam)
+ HistCrit <- matrix(NA, nrow = 500*NParam, ncol = 1)
+ CritName <- NULL
+ CritBestValue <- NULL
+ Multiplier <- NULL
+ CritOptim <- +1E100
##_temporary_change_of_Outputs_Sim
- RunOptions$Outputs_Sim <- RunOptions$Outputs_Cal; ### this reduces the size of the matrix exchange with fortran and therefore speeds the calibration
+ RunOptions$Outputs_Sim <- RunOptions$Outputs_Cal ### this reduces the size of the matrix exchange with fortran and therefore speeds the calibration
@@ -59,98 +118,128 @@ Calibration_Michel <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FU
##Definition_of_the_function_creating_all_possible_parameter_sets_from_different_values_for_each_parameter
- ProposeCandidatesGrid <- function(DistribParam){
+ ProposeCandidatesGrid <- function(DistribParam) {
##Managing_matrix_sizes
- Nvalmax <- nrow(DistribParam);
- NParam <- ncol(DistribParam);
+ Nvalmax <- nrow(DistribParam)
+ NParam <- ncol(DistribParam)
##we_add_columns_to_MatDistrib_until_it_has_20_columns
- DistribParam2 <- matrix(NA,nrow=Nvalmax,ncol=20);
- DistribParam2[1:Nvalmax,1:NParam] <- DistribParam;
+ DistribParam2 <- matrix(NA, nrow = Nvalmax, ncol = 20)
+ DistribParam2[1:Nvalmax, 1:NParam] <- DistribParam
##we_check_the_number_of_values_to_test_for_each_param
- NbDistrib <- rep(1,20);
- for(iC in 1:20){ NbDistrib[iC] <- max( 1 , Nvalmax-sum(is.na(DistribParam2[,iC])) ); }
+ NbDistrib <- rep(1, 20)
+ for (iC in 1:20) {
+ NbDistrib[iC] <- max(1, Nvalmax-sum(is.na(DistribParam2[, iC])))
+ }
##Loop_on_the_various_values_to_test ###(if 4 param and 3 values for each => 3^4 sets)
##NB_we_always_do_20_loops ###which_is_here_the_max_number_of_param_that_can_be_optimised
- VECT <- NULL;
- for(iL01 in 1:NbDistrib[01]){ for(iL02 in 1:NbDistrib[02]){ for(iL03 in 1:NbDistrib[03]){ for(iL04 in 1:NbDistrib[04]){ for(iL05 in 1:NbDistrib[05]){
- for(iL06 in 1:NbDistrib[06]){ for(iL07 in 1:NbDistrib[07]){ for(iL08 in 1:NbDistrib[08]){ for(iL09 in 1:NbDistrib[09]){ for(iL10 in 1:NbDistrib[10]){
- for(iL11 in 1:NbDistrib[11]){ for(iL12 in 1:NbDistrib[12]){ for(iL13 in 1:NbDistrib[13]){ for(iL14 in 1:NbDistrib[14]){ for(iL15 in 1:NbDistrib[15]){
- for(iL16 in 1:NbDistrib[16]){ for(iL17 in 1:NbDistrib[17]){ for(iL18 in 1:NbDistrib[18]){ for(iL19 in 1:NbDistrib[19]){ for(iL20 in 1:NbDistrib[20]){
+ VECT <- NULL
+ for (iL01 in 1:NbDistrib[01]) { for (iL02 in 1:NbDistrib[02]) { for (iL03 in 1:NbDistrib[03]) { for (iL04 in 1:NbDistrib[04]) { for (iL05 in 1:NbDistrib[05]) {
+ for (iL06 in 1:NbDistrib[06]) { for (iL07 in 1:NbDistrib[07]) { for (iL08 in 1:NbDistrib[08]) { for (iL09 in 1:NbDistrib[09]) { for (iL10 in 1:NbDistrib[10]) {
+ for (iL11 in 1:NbDistrib[11]) { for (iL12 in 1:NbDistrib[12]) { for (iL13 in 1:NbDistrib[13]) { for (iL14 in 1:NbDistrib[14]) { for (iL15 in 1:NbDistrib[15]) {
+ for (iL16 in 1:NbDistrib[16]) { for (iL17 in 1:NbDistrib[17]) { for (iL18 in 1:NbDistrib[18]) { for (iL19 in 1:NbDistrib[19]) { for (iL20 in 1:NbDistrib[20]) {
VECT <- c(VECT,
DistribParam2[iL01,01],DistribParam2[iL02,02],DistribParam2[iL03,03],DistribParam2[iL04,04],DistribParam2[iL05,05],
DistribParam2[iL06,06],DistribParam2[iL07,07],DistribParam2[iL08,08],DistribParam2[iL09,09],DistribParam2[iL10,10],
DistribParam2[iL11,11],DistribParam2[iL12,12],DistribParam2[iL13,13],DistribParam2[iL14,14],DistribParam2[iL15,15],
- DistribParam2[iL16,16],DistribParam2[iL17,17],DistribParam2[iL18,18],DistribParam2[iL19,19],DistribParam2[iL20,20]);
+ DistribParam2[iL16,16],DistribParam2[iL17,17],DistribParam2[iL18,18],DistribParam2[iL19,19],DistribParam2[iL20,20])
} } } } }
} } } } }
} } } } }
} } } } }
- MAT <- matrix(VECT,ncol=20,byrow=TRUE)[,1:NParam];
- if(is.matrix(MAT)==FALSE){ MAT <- cbind(MAT); }
- Output <- NULL;
- Output$NewCandidates <- MAT;
- return(Output);
+ MAT <- matrix(VECT, ncol = 20, byrow = TRUE)[, 1:NParam]
+ if (!is.matrix(MAT)) {
+ MAT <- cbind(MAT)
+ }
+ Output <- NULL
+ Output$NewCandidates <- MAT
+ return(Output)
}
##Creation_of_new_candidates_______________________________________________
OptimParam <- is.na(CalibOptions$FixedParam)
- if(PrefilteringType==1){ CandidatesParamR <- CalibOptions$StartParamList; }
- if(PrefilteringType==2){ DistribParamR <- CalibOptions$StartParamDistrib; DistribParamR[,!OptimParam] <- NA; CandidatesParamR <- ProposeCandidatesGrid(DistribParamR)$NewCandidates; }
+ if (PrefilteringType == 1) {
+ CandidatesParamR <- CalibOptions$StartParamList
+ }
+ if (PrefilteringType == 2) {
+ DistribParamR <- CalibOptions$StartParamDistrib
+ DistribParamR[,!OptimParam] <- NA
+ CandidatesParamR <- ProposeCandidatesGrid(DistribParamR)$NewCandidates
+ }
##Remplacement_of_non_optimised_values_____________________________________
- CandidatesParamR <- apply(CandidatesParamR,1,function(x){ x[!OptimParam] <- CalibOptions$FixedParam[!OptimParam]; return(x); });
- if(NParam>1){ CandidatesParamR <- t(CandidatesParamR); } else { CandidatesParamR <- cbind(CandidatesParamR); }
+ CandidatesParamR <- apply(CandidatesParamR, 1, function(x) {
+ x[!OptimParam] <- CalibOptions$FixedParam[!OptimParam]
+ return(x)})
+ if (NParam>1) {
+ CandidatesParamR <- t(CandidatesParamR)
+ } else { CandidatesParamR <- cbind(CandidatesParamR)
+ }
##Loop_to_test_the_various_candidates______________________________________
- iNewOptim <- 0;
- Ncandidates <- nrow(CandidatesParamR);
- if(verbose & Ncandidates>1){
- if(PrefilteringType==1){ message("List-Screening in progress (", appendLF = FALSE) }
- if(PrefilteringType==2){ message("Grid-Screening in progress (", appendLF = FALSE) }
+ iNewOptim <- 0
+ Ncandidates <- nrow(CandidatesParamR)
+ if (verbose & Ncandidates > 1) {
+ if (PrefilteringType == 1) {
+ message("List-Screening in progress (", appendLF = FALSE)
+ }
+ if (PrefilteringType == 2) {
+ message("Grid-Screening in progress (", appendLF = FALSE)
+ }
message("0%", appendLF = FALSE)
}
- for(iNew in 1:nrow(CandidatesParamR)){
- if(verbose & Ncandidates>1){
- for(k in c(2,4,6,8)){ if(iNew==round(k/10*Ncandidates)){ message(" ", 10*k, "%",appendLF = FALSE) } }
+ for (iNew in 1:nrow(CandidatesParamR)) {
+ if (verbose & Ncandidates > 1) {
+ for (k in c(2, 4, 6, 8)) {
+ if (iNew == round(k/10*Ncandidates)) {
+ message(" ", 10*k, "%", appendLF = FALSE)
+ }
+ }
}
##Model_run
- Param <- CandidatesParamR[iNew,];
- OutputsModel <- FUN_MOD(InputsModel,RunOptions,Param);
+ Param <- CandidatesParamR[iNew, ]
+ OutputsModel <- FUN_MOD(InputsModel, RunOptions, Param)
##Calibration_criterion_computation
- OutputsCrit <- FUN_CRIT(InputsCrit,OutputsModel, verbose = FALSE);
- if(!is.na(OutputsCrit$CritValue)){ if(OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim){
- CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier;
- iNewOptim <- iNew;
- } }
+ OutputsCrit <- FUN_CRIT(InputsCrit, OutputsModel, verbose = FALSE)
+ if (!is.na(OutputsCrit$CritValue)) {
+ if (OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim) {
+ CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier
+ iNewOptim <- iNew
+ }
+ }
##Storage_of_crit_info
- if(is.null(CritName) | is.null(CritBestValue) | is.null(Multiplier)){
- CritName <- OutputsCrit$CritName;
- CritBestValue <- OutputsCrit$CritBestValue;
- Multiplier <- OutputsCrit$Multiplier;
+ if (is.null(CritName) | is.null(CritBestValue) | is.null(Multiplier)) {
+ CritName <- OutputsCrit$CritName
+ CritBestValue <- OutputsCrit$CritBestValue
+ Multiplier <- OutputsCrit$Multiplier
}
}
- if(verbose & Ncandidates>1){ message(" 100%)\n", appendLF = FALSE) }
+ if (verbose & Ncandidates > 1) {
+ message(" 100%)\n", appendLF = FALSE)
+ }
##End_of_first_step_Parameter_Screening____________________________________
- ParamStartR <- CandidatesParamR[iNewOptim,]; if(!is.matrix(ParamStartR)){ ParamStartR <- matrix(ParamStartR,nrow=1); }
- ParamStartT <- FUN_TRANSFO(ParamStartR,"RT");
- CritStart <- CritOptim;
- NRuns <- NRuns+nrow(CandidatesParamR);
- if(verbose){
- if(Ncandidates> 1){
+ ParamStartR <- CandidatesParamR[iNewOptim, ]
+ if (!is.matrix(ParamStartR)) {
+ ParamStartR <- matrix(ParamStartR, nrow = 1)
+ }
+ ParamStartT <- FUN_TRANSFO(ParamStartR, "RT")
+ CritStart <- CritOptim
+ NRuns <- NRuns+nrow(CandidatesParamR)
+ if (verbose) {
+ if (Ncandidates > 1) {
message("\t Screening completed (", NRuns, " runs):")
}
- if(Ncandidates==1){
+ if (Ncandidates == 1) {
message("\t Starting point for steepest-descent local search:")
}
message("\t Param = ", paste(formatC(ParamStartR, format = "f", width = 8, digits = 3), collapse = " , "))
message("\t Crit ", format(CritName, width = 12, justify = "left"), " = ", formatC(CritStart*Multiplier, format = "f", digits = 4))
}
##Results_archiving________________________________________________________
- HistParamR[1,] <- ParamStartR;
- HistParamT[1,] <- ParamStartT;
- HistCrit[1,] <- CritStart;
+ HistParamR[1, ] <- ParamStartR
+ HistParamT[1, ] <- ParamStartT
+ HistCrit[1, ] <- CritStart
@@ -159,186 +248,235 @@ Calibration_Michel <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FU
##Definition_of_the_function_creating_new_parameter_sets_through_a_step_by_step_progression_procedure
- ProposeCandidatesLoc <- function(NewParamOptimT,OldParamOptimT,RangesT,OptimParam,Pace){
+ ProposeCandidatesLoc <- function(NewParamOptimT, OldParamOptimT, RangesT, OptimParam,Pace) {
##Format_checking
- if(nrow(NewParamOptimT)!=1 | nrow(OldParamOptimT)!=1){ stop("each input set must be a matrix of one single line \n"); return(NULL); }
- if(ncol(NewParamOptimT)!=ncol(OldParamOptimT) | ncol(NewParamOptimT)!=length(OptimParam)){ stop("each input set must have the same number of values \n"); return(NULL); }
+ if (nrow(NewParamOptimT) != 1 | nrow(OldParamOptimT) != 1) {
+ stop("each input set must be a matrix of one single line \n")
+ return(NULL)
+ }
+ if (ncol(NewParamOptimT)!=ncol(OldParamOptimT) | ncol(NewParamOptimT) != length(OptimParam)) {
+ stop("each input set must have the same number of values \n")
+ return(NULL)
+ }
##Proposal_of_new_parameter_sets ###(local search providing 2*NParam-1 new sets)
- NParam <- ncol(NewParamOptimT);
- VECT <- NULL;
- for(I in 1:NParam){
+ NParam <- ncol(NewParamOptimT)
+ VECT <- NULL
+ for (I in 1:NParam) {
##We_check_that_the_current_parameter_should_indeed_be_optimised
- if(OptimParam[I]==TRUE){
- for(J in 1:2){
- Sign <- 2*J-3; #Sign can be equal to -1 or +1
+ if (OptimParam[I] == TRUE) {
+ for (J in 1:2) {
+ Sign <- 2 * J - 3 #Sign can be equal to -1 or +1
##We_define_the_new_potential_candidate
- Add <- TRUE;
- PotentialCandidateT <- NewParamOptimT;
- PotentialCandidateT[1,I] <- NewParamOptimT[I]+Sign*Pace;
+ Add <- TRUE
+ PotentialCandidateT <- NewParamOptimT
+ PotentialCandidateT[1, I] <- NewParamOptimT[I] + Sign * Pace
##If_we_exit_the_range_of_possible_values_we_go_back_on_the_boundary
- if(PotentialCandidateT[1,I]<RangesT[1,I]){ PotentialCandidateT[1,I] <- RangesT[1,I]; }
- if(PotentialCandidateT[1,I]>RangesT[2,I]){ PotentialCandidateT[1,I] <- RangesT[2,I]; }
+ if (PotentialCandidateT[1, I] < RangesT[1, I] ) {
+ PotentialCandidateT[1,I] <- RangesT[1, I]
+ }
+ if (PotentialCandidateT[1, I] > RangesT[2, I]) {
+ PotentialCandidateT[1,I] <- RangesT[2,I]
+ }
##We_check_the_set_is_not_outside_the_range_of_possible_values
- if( NewParamOptimT[I]==RangesT[1,I] & Sign<0 ){ Add <- FALSE; }
- if( NewParamOptimT[I]==RangesT[2,I] & Sign>0 ){ Add <- FALSE; }
+ if (NewParamOptimT[I] == RangesT[1, I] & Sign < 0) {
+ Add <- FALSE
+ }
+ if (NewParamOptimT[I] == RangesT[2, I] & Sign > 0) {
+ Add <- FALSE
+ }
##We_check_that_this_set_has_not_been_tested_during_the_last_iteration
- if(identical(PotentialCandidateT,OldParamOptimT)){ Add <- FALSE; }
+ if (identical(PotentialCandidateT, OldParamOptimT)) {
+ Add <- FALSE
+ }
##We_add_the_candidate_to_our_list
- if(Add==TRUE){ VECT <- c(VECT,PotentialCandidateT); }
+ if (Add == TRUE) {
+ VECT <- c(VECT, PotentialCandidateT)
+ }
}
}
}
- Output <- NULL;
- Output$NewCandidatesT <- matrix(VECT,ncol=NParam,byrow=TRUE);
- return(Output);
+ Output <- NULL
+ Output$NewCandidatesT <- matrix(VECT, ncol = NParam, byrow = TRUE)
+ return(Output)
}
##Initialisation_of_variables
- if(verbose){
+ if (verbose) {
message("Steepest-descent local search in progress")
}
- Pace <- 0.64;
- PaceDiag <- rep(0,NParam);
- CLG <- 0.7^(1/NParam);
- Compt <- 0;
- CritOptim <- CritStart;
+ Pace <- 0.64
+ PaceDiag <- rep(0, NParam)
+ CLG <- 0.7^(1/NParam)
+ Compt <- 0
+ CritOptim <- CritStart
##Conversion_of_real_parameter_values
- RangesR <- CalibOptions$SearchRanges;
- RangesT <- FUN_TRANSFO(RangesR,"RT");
- NewParamOptimT <- ParamStartT;
- OldParamOptimT <- ParamStartT;
+ RangesR <- CalibOptions$SearchRanges
+ RangesT <- FUN_TRANSFO(RangesR, "RT")
+ NewParamOptimT <- ParamStartT
+ OldParamOptimT <- ParamStartT
##START_LOOP_ITER_________________________________________________________
- for(ITER in 1:(100*NParam)){
+ for (ITER in 1:(100*NParam)) {
##Exit_loop_when_Pace_becomes_too_small___________________________________
- if(Pace<0.01){ break; }
+ if (Pace < 0.01) {
+ break
+ }
##Creation_of_new_candidates______________________________________________
- CandidatesParamT <- ProposeCandidatesLoc(NewParamOptimT,OldParamOptimT,RangesT,OptimParam,Pace)$NewCandidatesT;
- CandidatesParamR <- FUN_TRANSFO(CandidatesParamT,"TR");
+ CandidatesParamT <- ProposeCandidatesLoc(NewParamOptimT, OldParamOptimT, RangesT, OptimParam, Pace)$NewCandidatesT
+ CandidatesParamR <- FUN_TRANSFO(CandidatesParamT, "TR")
##Remplacement_of_non_optimised_values_____________________________________
- CandidatesParamR <- apply(CandidatesParamR,1,function(x){ x[!OptimParam] <- CalibOptions$FixedParam[!OptimParam]; return(x); });
- if(NParam>1){ CandidatesParamR <- t(CandidatesParamR); } else { CandidatesParamR <- cbind(CandidatesParamR); }
+ CandidatesParamR <- apply(CandidatesParamR, 1, function(x) {
+ x[!OptimParam] <- CalibOptions$FixedParam[!OptimParam]
+ return(x)})
+ if (NParam > 1) {
+ CandidatesParamR <- t(CandidatesParamR)
+ } else {
+ CandidatesParamR <- cbind(CandidatesParamR)
+ }
##Loop_to_test_the_various_candidates_____________________________________
- iNewOptim <- 0;
- for(iNew in 1:nrow(CandidatesParamR)){
+ iNewOptim <- 0
+ for (iNew in 1:nrow(CandidatesParamR)) {
##Model_run
- Param <- CandidatesParamR[iNew,];
- OutputsModel <- FUN_MOD(InputsModel,RunOptions,Param);
+ Param <- CandidatesParamR[iNew, ]
+ OutputsModel <- FUN_MOD(InputsModel, RunOptions, Param)
##Calibration_criterion_computation
- OutputsCrit <- FUN_CRIT(InputsCrit,OutputsModel, verbose = FALSE);
- if(!is.na(OutputsCrit$CritValue)){ if(OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim){
- CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier;
- iNewOptim <- iNew;
- } }
+ OutputsCrit <- FUN_CRIT(InputsCrit, OutputsModel, verbose = FALSE)
+ if (!is.na(OutputsCrit$CritValue)) {
+ if (OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim) {
+ CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier
+ iNewOptim <- iNew
+ }
+ }
}
- NRuns <- NRuns+nrow(CandidatesParamR);
+ NRuns <- NRuns + nrow(CandidatesParamR)
##When_a_progress_has_been_achieved_______________________________________
- if(iNewOptim!=0){
+ if (iNewOptim != 0) {
##We_store_the_optimal_set
- OldParamOptimT <- NewParamOptimT;
- NewParamOptimT <- matrix(CandidatesParamT[iNewOptim,1:NParam],nrow=1);
- Compt <- Compt+1;
+ OldParamOptimT <- NewParamOptimT
+ NewParamOptimT <- matrix(CandidatesParamT[iNewOptim, 1:NParam], nrow = 1)
+ Compt <- Compt+1
##When_necessary_we_increase_the_pace ### if_successive_progress_occur_in_a_row
- if(Compt>2*NParam){
- Pace <- Pace*2;
- Compt <- 0;
+ if (Compt > 2*NParam) {
+ Pace <- Pace * 2
+ Compt <- 0
}
##We_update_PaceDiag
- VectPace <- NewParamOptimT-OldParamOptimT;
- for(iC in 1:NParam){ if(OptimParam[iC]){
- if(VectPace[iC]!=0){ PaceDiag[iC] <- CLG*PaceDiag[iC]+(1-CLG)*VectPace[iC]; }
- if(VectPace[iC]==0){ PaceDiag[iC] <- CLG*PaceDiag[iC]; }
- } }
+ VectPace <- NewParamOptimT-OldParamOptimT
+ for (iC in 1:NParam) {
+ if (OptimParam[iC]) {
+ if (VectPace[iC] != 0) {
+ PaceDiag[iC] <- CLG * PaceDiag[iC] + (1-CLG) * VectPace[iC]
+ }
+ if (VectPace[iC] == 0) {
+ PaceDiag[iC] <- CLG*PaceDiag[iC]
+ }
+ }
+ }
} else {
##When_no_progress_has_been_achieved_we_decrease_the_pace_________________
- Pace <- Pace/2;
- Compt <- 0;
+ Pace <- Pace / 2
+ Compt <- 0
}
##Test_of_an_additional_candidate_using_diagonal_progress_________________
- if(ITER>4*NParam){
-
- NRuns <- NRuns+1;
- iNewOptim <- 0; iNew <- 1;
- CandidatesParamT <- NewParamOptimT+PaceDiag; if(!is.matrix(CandidatesParamT)){ CandidatesParamT <- matrix(CandidatesParamT,nrow=1); }
- ##If_we_exit_the_range_of_possible_values_we_go_back_on_the_boundary
- for(iC in 1:NParam){ if(OptimParam[iC]){
- if(CandidatesParamT[iNew,iC]<RangesT[1,iC]){ CandidatesParamT[iNew,iC] <- RangesT[1,iC]; }
- if(CandidatesParamT[iNew,iC]>RangesT[2,iC]){ CandidatesParamT[iNew,iC] <- RangesT[2,iC]; }
- } }
- CandidatesParamR <- FUN_TRANSFO(CandidatesParamT,"TR");
- ##Model_run
- Param <- CandidatesParamR[iNew,];
- OutputsModel <- FUN_MOD(InputsModel,RunOptions,Param);
- ##Calibration_criterion_computation
- OutputsCrit <- FUN_CRIT(InputsCrit,OutputsModel, verbose = FALSE);
- if(OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim){
- CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier;
- iNewOptim <- iNew;
- }
- ##When_a_progress_has_been_achieved
- if(iNewOptim!=0){
- OldParamOptimT <- NewParamOptimT;
- NewParamOptimT <- matrix(CandidatesParamT[iNewOptim,1:NParam],nrow=1);
+ if (ITER > 4*NParam) {
+ NRuns <- NRuns + 1
+ iNewOptim <- 0
+ iNew <- 1
+ CandidatesParamT <- NewParamOptimT+PaceDiag
+ if (!is.matrix(CandidatesParamT)) {
+ CandidatesParamT <- matrix(CandidatesParamT, nrow = 1)
+ }
+ ##If_we_exit_the_range_of_possible_values_we_go_back_on_the_boundary
+ for (iC in 1:NParam) {
+ if (OptimParam[iC]) {
+ if (CandidatesParamT[iNew, iC] < RangesT[1, iC]) {
+ CandidatesParamT[iNew, iC] <- RangesT[1, iC]
+ }
+ if (CandidatesParamT[iNew, iC] > RangesT[2, iC]) {
+ CandidatesParamT[iNew, iC] <- RangesT[2, iC]
+ }
}
+ }
+ CandidatesParamR <- FUN_TRANSFO(CandidatesParamT, "TR")
+ ##Model_run
+ Param <- CandidatesParamR[iNew, ]
+ OutputsModel <- FUN_MOD(InputsModel, RunOptions, Param)
+ ##Calibration_criterion_computation
+ OutputsCrit <- FUN_CRIT(InputsCrit, OutputsModel, verbose = FALSE)
+ if (OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim) {
+ CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier
+ iNewOptim <- iNew
+ }
+ ##When_a_progress_has_been_achieved
+ if (iNewOptim != 0) {
+ OldParamOptimT <- NewParamOptimT
+ NewParamOptimT <- matrix(CandidatesParamT[iNewOptim, 1:NParam], nrow = 1)
+ }
}
##Results_archiving_______________________________________________________
- NewParamOptimR <- FUN_TRANSFO(NewParamOptimT,"TR");
- HistParamR[ITER+1,] <- NewParamOptimR;
- HistParamT[ITER+1,] <- NewParamOptimT;
- HistCrit[ITER+1,] <- CritOptim;
- ### if(verbose){ cat(paste("\t Iter ",formatC(ITER,format="d",width=3)," Crit ",formatC(CritOptim,format="f",digits=4)," Pace ",formatC(Pace,format="f",digits=4),"\n",sep="")); }
+ NewParamOptimR <- FUN_TRANSFO(NewParamOptimT, "TR")
+ HistParamR[ITER+1, ] <- NewParamOptimR
+ HistParamT[ITER+1, ] <- NewParamOptimT
+ HistCrit[ITER+1, ] <- CritOptim
+ ### if (verbose) { cat(paste("\t Iter ",formatC(ITER,format="d",width=3), " Crit ",formatC(CritOptim,format="f",digits=4), " Pace ",formatC(Pace,format="f",digits=4), "\n",sep=""))}
} ##END_LOOP_ITER_________________________________________________________
- ITER <- ITER-1;
+ ITER <- ITER-1
##Case_when_the_starting_parameter_set_remains_the_best_solution__________
- if(CritOptim==CritStart & verbose){
- message("\t No progress achieved");
+ if (CritOptim == CritStart & verbose) {
+ message("\t No progress achieved")
}
##End_of_Steepest_Descent_Local_Search____________________________________
- ParamFinalR <- NewParamOptimR;
- ParamFinalT <- NewParamOptimT;
- CritFinal <- CritOptim;
- NIter <- 1+ITER;
- if(verbose){
+ ParamFinalR <- NewParamOptimR
+ ParamFinalT <- NewParamOptimT
+ CritFinal <- CritOptim
+ NIter <- 1 + ITER
+ if (verbose) {
message("\t Calibration completed (", NIter, " iterations, ", NRuns, " runs)")
message("\t Param = ", paste(formatC(ParamFinalR, format = "f", width = 8, digits = 3), collapse = " , "))
message("\t Crit ", format(CritName, width = 12, justify = "left"), " = ", formatC(CritFinal*Multiplier, format = "f", digits = 4))
}
##Results_archiving_______________________________________________________
- HistParamR <- cbind(HistParamR[1:NIter,]); colnames(HistParamR) <- paste("Param",1:NParam,sep="");
- HistParamT <- cbind(HistParamT[1:NIter,]); colnames(HistParamT) <- paste("Param",1:NParam,sep="");
- HistCrit <- cbind(HistCrit[1:NIter,]); ###colnames(HistCrit) <- paste("HistCrit");
+ HistParamR <- cbind(HistParamR[1:NIter, ])
+ colnames(HistParamR) <- paste0("Param", 1:NParam)
+ HistParamT <- cbind(HistParamT[1:NIter, ])
+ colnames(HistParamT) <- paste0("Param", 1:NParam)
+ HistCrit <- cbind(HistCrit[1:NIter, ])
+ ###colnames(HistCrit) <- paste("HistCrit")
- BoolCrit_Actual <- InputsCrit$BoolCrit; BoolCrit_Actual[OutputsCrit$Ind_notcomputed] <- FALSE;
- MatBoolCrit <- cbind( InputsCrit$BoolCrit , BoolCrit_Actual );
- colnames(MatBoolCrit) <- c("BoolCrit_Requested","BoolCrit_Actual");
+ BoolCrit_Actual <- InputsCrit$BoolCrit
+ BoolCrit_Actual[OutputsCrit$Ind_notcomputed] <- FALSE
+ MatBoolCrit <- cbind(InputsCrit$BoolCrit, BoolCrit_Actual)
+ colnames(MatBoolCrit) <- c("BoolCrit_Requested", "BoolCrit_Actual")
##_____Output______________________________________________________________________________
- OutputsCalib <- list(as.double(ParamFinalR),CritFinal*Multiplier,NIter,NRuns,HistParamR,HistCrit*Multiplier,MatBoolCrit,CritName,CritBestValue);
- names(OutputsCalib) <- c("ParamFinalR","CritFinal","NIter","NRuns","HistParamR","HistCrit","MatBoolCrit","CritName","CritBestValue");
- class(OutputsCalib) <- c("OutputsCalib","HBAN");
- return(OutputsCalib);
+ OutputsCalib <- list(ParamFinalR = as.double(ParamFinalR), CritFinal = CritFinal*Multiplier,
+ NIter = NIter, NRuns = NRuns,
+ HistParamR = HistParamR, HistCrit = HistCrit*Multiplier, MatBoolCrit = MatBoolCrit,
+ CritName = CritName, CritBestValue = CritBestValue)
+ class(OutputsCalib) <- c("OutputsCalib", "HBAN")
+ return(OutputsCalib)
diff --git a/inst/CITATION b/inst/CITATION
index f655e189..f33701d6 100644
--- a/inst/CITATION
+++ b/inst/CITATION
@@ -17,14 +17,14 @@ citEntry(entry="Manual",
title = "airGR: Suite of GR hydrological models for precipitation-runoff modelling",
author = personList(as.person("L. Coron"), as.person("C. Perrin"), as.person("C. Michel")),
journal = "R News",
- year = "2016",
- note = "R package version 1.0.3",
+ year = "2017",
+ note = "R package version 1.0.4",
url = "https://webgr.irstea.fr/airGR/?lang=en",
textVersion =
paste("Coron, L., Perrin, C. and Michel, C.",
- "(2016).",
+ "(2017).",
"airGR: Suite of GR hydrological models for precipitation-runoff modelling.",
- "R package version 1.0.3.",
+ "R package version 1.0.4.",
"https://webgr.irstea.fr/airGR/?lang=en.",
sep = " ")
)
--
GitLab