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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); } ##_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)){ 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; ##_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##_____Parameter_Grid_Screening____________________________________________________________ ##Definition_of_the_function_creating_all_possible_parameter_sets_from_different_values_for_each_parameter ProposeCandidatesGrid <- function(DistribParam){ ##Managing_matrix_sizes 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; ##we_check_the_number_of_values_to_test_for_each_param NbDistrib <- rep(1,20);7172737475767778798081828384858687888990919293949596979899100101102103104105106107108109110111112113114115116117118119120121122123124125126127128129130131132133134135136137138139140
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 <- 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]);
} } } } }
} } } } }
} } } } }
} } } } }
MAT <- matrix(VECT,ncol=20,byrow=TRUE)[,1:NParam];
if(is.matrix(MAT)==FALSE){ 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)$NewCandidates; }
##Remplacement_of_non_optimised_values_____________________________________
CandidatesParamR <- apply(CandidatesParamR,1,function(x){ x[!OptimParam] <- CalibOptions$FixedParam[!OptimParam]; return(x); });
if(NParam>1){ CandidatesParamR <- t(CandidatesParamR); } else { CandidatesParamR <- cbind(CandidatesParamR); }
##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) }
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) } }
}
##Model_run
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$Multiplier;
iNewOptim <- iNew;
} }
##Storage_of_crit_info
if(is.null(CritName) | is.null(CritBestValue) | is.null(Multiplier)){
CritName <- OutputsCrit$CritName;
CritBestValue <- OutputsCrit$CritBestValue;
Multiplier <- OutputsCrit$Multiplier;
}
}
if(verbose & Ncandidates>1){ message(" 100%)\n", appendLF = FALSE) }
##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){
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if(Ncandidates> 1){
message("\t Screening completed (", NRuns, " runs):")
}
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;
##_____Steepest_Descent_Local_Search_______________________________________________________
##Definition_of_the_function_creating_new_parameter_sets_through_a_step_by_step_progression_procedure
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); }
##Proposal_of_new_parameter_sets ###(local search providing 2*NParam-1 new sets)
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
##We_define_the_new_potential_candidate
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]; }
##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; }
##We_check_that_this_set_has_not_been_tested_during_the_last_iteration
if(identical(PotentialCandidateT,OldParamOptimT)){ Add <- FALSE; }
##We_add_the_candidate_to_our_list
if(Add==TRUE){ VECT <- c(VECT,PotentialCandidateT); }
}
}
}
Output <- NULL;
Output$NewCandidatesT <- matrix(VECT,ncol=NParam,byrow=TRUE);
return(Output);
}
##Initialisation_of_variables
if(verbose){
message("Steepest-descent local search in progress")
}
Pace <- 0.64;
PaceDiag <- rep(0,NParam);
CLG <- 0.7^(1/NParam);
Compt <- 0;
CritOptim <- CritStart;
##Conversion_of_real_parameter_values
RangesR <- CalibOptions$SearchRanges;
RangesT <- FUN_TRANSFO(RangesR,"RT");
NewParamOptimT <- ParamStartT;
OldParamOptimT <- ParamStartT;
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##START_LOOP_ITER_________________________________________________________
for(ITER in 1:(100*NParam)){
##Exit_loop_when_Pace_becomes_too_small___________________________________
if(Pace<0.01){ break; }
##Creation_of_new_candidates______________________________________________
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); }
##Loop_to_test_the_various_candidates_____________________________________
iNewOptim <- 0;
for(iNew in 1:nrow(CandidatesParamR)){
##Model_run
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$Multiplier;
iNewOptim <- iNew;
} }
}
NRuns <- NRuns+nrow(CandidatesParamR);
##When_a_progress_has_been_achieved_______________________________________
if(iNewOptim!=0){
##We_store_the_optimal_set
OldParamOptimT <- NewParamOptimT;
NewParamOptimT <- matrix(CandidatesParamT[iNewOptim,1:NParam],nrow=1);
Compt <- Compt+1;
##When_necessary_we_increase_the_pace ### if_successive_progress_occur_in_a_row
if(Compt>2*NParam){
Pace <- Pace*2;
Compt <- 0;
}
##We_update_PaceDiag
VectPace <- NewParamOptimT-OldParamOptimT;
for(iC in 1:NParam){ if(OptimParam[iC]){
if(VectPace[iC]!=0){ PaceDiag[iC] <- CLG*PaceDiag[iC]+(1-CLG)*VectPace[iC]; }
if(VectPace[iC]==0){ PaceDiag[iC] <- CLG*PaceDiag[iC]; }
} }
} else {
##When_no_progress_has_been_achieved_we_decrease_the_pace_________________
Pace <- Pace/2;
Compt <- 0;
}
##Test_of_an_additional_candidate_using_diagonal_progress_________________
if(ITER>4*NParam){
NRuns <- NRuns+1;
iNewOptim <- 0; iNew <- 1;
CandidatesParamT <- NewParamOptimT+PaceDiag; if(!is.matrix(CandidatesParamT)){ CandidatesParamT <- matrix(CandidatesParamT,nrow=1); }
##If_we_exit_the_range_of_possible_values_we_go_back_on_the_boundary
for(iC in 1:NParam){ if(OptimParam[iC]){
if(CandidatesParamT[iNew,iC]<RangesT[1,iC]){ CandidatesParamT[iNew,iC] <- RangesT[1,iC]; }
if(CandidatesParamT[iNew,iC]>RangesT[2,iC]){ CandidatesParamT[iNew,iC] <- RangesT[2,iC]; }
} }
CandidatesParamR <- FUN_TRANSFO(CandidatesParamT,"TR");
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##Model_run
Param <- CandidatesParamR[iNew,];
OutputsModel <- FUN_MOD(InputsModel,RunOptions,Param);
##Calibration_criterion_computation
OutputsCrit <- FUN_CRIT(InputsCrit,OutputsModel, verbose = FALSE);
if(OutputsCrit$CritValue*OutputsCrit$Multiplier < CritOptim){
CritOptim <- OutputsCrit$CritValue*OutputsCrit$Multiplier;
iNewOptim <- iNew;
}
##When_a_progress_has_been_achieved
if(iNewOptim!=0){
OldParamOptimT <- NewParamOptimT;
NewParamOptimT <- matrix(CandidatesParamT[iNewOptim,1:NParam],nrow=1);
}
}
##Results_archiving_______________________________________________________
NewParamOptimR <- FUN_TRANSFO(NewParamOptimT,"TR");
HistParamR[ITER+1,] <- NewParamOptimR;
HistParamT[ITER+1,] <- NewParamOptimT;
HistCrit[ITER+1,] <- CritOptim;
### if(verbose){ cat(paste("\t Iter ",formatC(ITER,format="d",width=3)," Crit ",formatC(CritOptim,format="f",digits=4)," Pace ",formatC(Pace,format="f",digits=4),"\n",sep="")); }
} ##END_LOOP_ITER_________________________________________________________
ITER <- ITER-1;
##Case_when_the_starting_parameter_set_remains_the_best_solution__________
if(CritOptim==CritStart & verbose){
message("\t No progress achieved");
}
##End_of_Steepest_Descent_Local_Search____________________________________
ParamFinalR <- NewParamOptimR;
ParamFinalT <- NewParamOptimT;
CritFinal <- CritOptim;
NIter <- 1+ITER;
if(verbose){
message("\t Calibration completed (", NIter, " iterations, ", NRuns, " runs)")
message("\t Param = ", paste(formatC(ParamFinalR, format = "f", width = 8, digits = 3), collapse = " , "))
message("\t Crit ", format(CritName, width = 12, justify = "left"), " = ", formatC(CritFinal*Multiplier, format = "f", digits = 4))
}
##Results_archiving_______________________________________________________
HistParamR <- cbind(HistParamR[1:NIter,]); colnames(HistParamR) <- paste("Param",1:NParam,sep="");
HistParamT <- cbind(HistParamT[1:NIter,]); colnames(HistParamT) <- paste("Param",1:NParam,sep="");
HistCrit <- cbind(HistCrit[1:NIter,]); ###colnames(HistCrit) <- paste("HistCrit");
BoolCrit_Actual <- InputsCrit$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);
}
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