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Commit eb3f809f authored by Delaigue Olivier's avatar Delaigue Olivier
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Renommage des fonctions avec le suffixe HBAN

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R/Calibration_HBAN.R → R/Calibration_Michel.R
View file @ eb3f809f
......@@ -27,7 +27,7 @@
#' @references
#' Michel, C. (1991),
#' Hydrologie appliquée aux petits bassins ruraux, Hydrology handout (in French), Cemagref, Antony, France.
#' @example tests/example_Calibration_HBAN.R
#' @example tests/example_Calibration_Michel.R
#' @seealso \code{\link{Calibration}}, \code{\link{Calibration_optim}},
#' \code{\link{RunModel_GR4J}}, \code{\link{TransfoParam_GR4J}}, \code{\link{ErrorCrit_RMSE}},
#' \code{\link{CreateInputsModel}}, \code{\link{CreateRunOptions}},
......@@ -57,7 +57,7 @@
#' \emph{$CritBestValue} \tab [numeric] theoretical best criterion value \cr
#' }
#**************************************************************************************************
Calibration_HBAN <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FUN_MOD,FUN_CRIT,FUN_TRANSFO=NULL,quiet=FALSE){
Calibration_Michel <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FUN_MOD,FUN_CRIT,FUN_TRANSFO=NULL,quiet=FALSE){
##_____Arguments_check_____________________________________________________________________
......@@ -65,7 +65,7 @@ Calibration_HBAN <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FUN_
if(inherits(RunOptions,"RunOptions")==FALSE){ stop("RunOptions must be of class 'RunOptions' \n"); return(NULL); }
if(inherits(InputsCrit,"InputsCrit")==FALSE){ stop("InputsCrit must be of class 'InputsCrit' \n"); return(NULL); }
if(inherits(CalibOptions,"CalibOptions")==FALSE){ stop("CalibOptions must be of class 'CalibOptions' \n"); return(NULL); }
if(inherits(CalibOptions,"HBAN")==FALSE){ stop("CalibOptions must be of class 'HBAN' if Calibration_HBAN is used \n"); return(NULL); }
if(inherits(CalibOptions,"HBAN")==FALSE){ stop("CalibOptions must be of class 'HBAN' if Calibration_Michel is used \n"); return(NULL); }
##_check_FUN_TRANSFO
......@@ -101,7 +101,7 @@ Calibration_HBAN <- function(InputsModel,RunOptions,InputsCrit,CalibOptions,FUN_
if("StartParamDistrib" %in% names(CalibOptions)){ PrefilteringType <- 2; } else { PrefilteringType <- 1; }
if(PrefilteringType==1){ NParam <- ncol(CalibOptions$StartParamList); }
if(PrefilteringType==2){ NParam <- ncol(CalibOptions$StartParamDistrib); }
if(NParam>20){ stop("Calibration_HBAN can handle a maximum of 20 parameters \n"); return(NULL); }
if(NParam>20){ stop("Calibration_Michel can handle a maximum of 20 parameters \n"); return(NULL); }
HistParamR <- matrix(NA,nrow=500*NParam,ncol=NParam);
HistParamT <- matrix(NA,nrow=500*NParam,ncol=NParam);
HistCrit <- matrix(NA,nrow=500*NParam,ncol=1);
......
R/DataAltiExtrapolation_HBAN.R → R/DataAltiExtrapolation_Valery.R
View file @ eb3f809f
......@@ -40,7 +40,7 @@
#' \emph{$ZLayers } \tab [numeric] vector of median elevation for each layer \cr
#' }
#*****************************************************************************************************************
DataAltiExtrapolation_HBAN <- function(DatesR,Precip,TempMean,TempMin=NULL,TempMax=NULL,ZInputs,HypsoData,NLayers,quiet=FALSE){
DataAltiExtrapolation_Valery <- function(DatesR,Precip,TempMean,TempMin=NULL,TempMax=NULL,ZInputs,HypsoData,NLayers,quiet=FALSE){
##Altitudinal_gradient_functions_______________________________________________________________
......
man/Calibration_HBAN.Rd → man/Calibration_Michel.Rd
View file @ eb3f809f
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/Calibration_HBAN.R
% Please edit documentation in R/Calibration_Michel.R
\encoding{UTF-8}
\name{Calibration_HBAN}
\alias{Calibration_HBAN}
\title{Calibration algorithm which minimises the error criterion using the Irstea-HBAN procedure}
\name{Calibration_Michel}
\alias{Calibration_Michel}
\title{Calibration algorithm optimises the error criterion selected as objective function using the Irstea-HBAN procedure described by C. Michel}
\usage{
Calibration_HBAN(InputsModel, RunOptions, InputsCrit, CalibOptions, FUN_MOD,
FUN_CRIT, FUN_TRANSFO = NULL, quiet = FALSE)
Calibration_Michel(InputsModel, RunOptions, InputsCrit, CalibOptions,
FUN_MOD, FUN_CRIT, FUN_TRANSFO = NULL, quiet = FALSE)
}
\arguments{
\item{InputsModel}{[object of class \emph{InputsModel}] see \code{\link{CreateInputsModel}} for details}
......@@ -29,95 +29,97 @@ Calibration_HBAN(InputsModel, RunOptions, InputsCrit, CalibOptions, FUN_MOD,
[list] list containing the function outputs organised as follows:
\tabular{ll}{
\emph{$ParamFinalR } \tab [numeric] parameter set obtained at the end of the calibration \cr
\emph{$CritFinal } \tab [numeric] error criterion obtained at the end of the calibration \cr
\emph{$CritFinal } \tab [numeric] error criterion selected as objective function obtained at the end of the calibration \cr
\emph{$NIter } \tab [numeric] number of iterations during the calibration \cr
\emph{$NRuns } \tab [numeric] number of model runs done during the calibration \cr
\emph{$HistParamR } \tab [numeric] table showing the progression steps in the search for optimal set: parameter values \cr
\emph{$HistCrit } \tab [numeric] table showing the progression steps in the search for optimal set: criterion values \cr
\emph{$MatBoolCrit } \tab [boolean] table giving the requested and actual time steps when the model is calibrated \cr
\emph{$CritName } \tab [character] name of the calibration criterion \cr
\emph{$MatBoolCrit } \tab [boolean] table giving the requested and actual time steps over which the model is calibrated \cr
\emph{$CritName } \tab [character] name of the calibration criterion used as objective function \cr
\emph{$CritBestValue} \tab [numeric] theoretical best criterion value \cr
}
}
\description{
Calibration algorithm which minimises the error criterion. \cr
Calibration algorithm optimises the error criterion selected as objective function. \cr
\cr
The algorithm is based on a local search procedure.
First, a screening is performed using either a rough predefined grid or a list of parameter sets
and then a simple steepest descent local search algorithm is performed.
}
\details{
A screening is first performed either from a rough predefined grid (considering various initial
values for each paramete) or from a list of initial parameter sets. \cr
A screening is first performed either based on a rough predefined grid (considering various initial
values for each parameter) or from a list of initial parameter sets. \cr
The best set identified in this screening is then used as a starting point for the steepest
descent local search algorithm. \cr
For this search, the parameters are used in a transformed version, to obtain uniform
variation ranges (and thus a similar pace), while the true ranges might be quite different. \cr
At each iteration, we start from a parameter set of NParam values (NParam being the number of
For this search, since the ranges of parameter values can be quite different,
simple mathematical transformations are applied to parameters to make them vary
in a similar range and get a similar sensitivity to a predefined search step. This is done using the TransfoParam functions. \cr
During the steepest descent method, at each iteration, we start from a parameter set of NParam values (NParam being the number of
free parameters of the chosen hydrological model) and we determine the 2*NParam-1 new candidates
by changing one by one the different parameters (+/- pace). \cr
by changing one by one the different parameters (+/- search step). \cr
All these candidates are tested and the best one kept to be the starting point for the next
iteration. At the end of each iteration, the pace is either increased or decreased to adapt
the progression speed. A diagonal progress can occasionally be done. \cr
The calibration algorithm stops when the pace becomes too small. \cr
To optimise the exploration of the parameter space, transformation functions are used to convert
the model parameters. This is done using the TransfoParam functions.
iteration. At the end of each iteration, the the search step is either increased or decreased to adapt
the progression speed. A composite step can occasionally be done. \cr
The calibration algorithm stops when the search step becomes smaller than a predefined threshold. \cr
}
\examples{
## load of catchment data
require(airGR)
## loading catchment data
library(airGR)
data(L0123001)
## preparation of InputsModel object
InputsModel <- CreateInputsModel(FUN_MOD=RunModel_GR4J,DatesR=BasinObs$DatesR,
Precip=BasinObs$P,PotEvap=BasinObs$E)
InputsModel <- CreateInputsModel(FUN_MOD = RunModel_GR4J, DatesR = BasinObs$DatesR,
Precip = BasinObs$P, PotEvap = BasinObs$E)
## calibration period selection
Ind_Run <- seq(which(format(BasinObs$DatesR,format="\%d/\%m/\%Y \%H:\%M")=="01/01/1990 00:00"),
which(format(BasinObs$DatesR,format="\%d/\%m/\%Y \%H:\%M")=="31/12/1999 00:00"))
Ind_Run <- seq(which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="01/01/1990 00:00"),
which(format(BasinObs$DatesR, format = "\%d/\%m/\%Y \%H:\%M")=="31/12/1999 00:00"))
## preparation of RunOptions object
RunOptions <- CreateRunOptions(FUN_MOD=RunModel_GR4J,InputsModel=InputsModel,IndPeriod_Run=Ind_Run)
RunOptions <- CreateRunOptions(FUN_MOD = RunModel_GR4J, InputsModel = InputsModel,
IndPeriod_Run = Ind_Run)
## calibration criterion: preparation of the InputsCrit object
InputsCrit <- CreateInputsCrit(FUN_CRIT=ErrorCrit_NSE,InputsModel=InputsModel,
RunOptions=RunOptions,Qobs=BasinObs$Qmm[Ind_Run])
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel,
RunOptions = RunOptions, Qobs = BasinObs$Qmm[Ind_Run])
## preparation of CalibOptions object
CalibOptions <- CreateCalibOptions(FUN_MOD=RunModel_GR4J,FUN_CALIB=Calibration_HBAN)
CalibOptions <- CreateCalibOptions(FUN_MOD = RunModel_GR4J, FUN_CALIB = Calibration_Michel)
## calibration
OutputsCalib <- Calibration_HBAN(InputsModel=InputsModel,RunOptions=RunOptions,
InputsCrit=InputsCrit,CalibOptions=CalibOptions,
FUN_MOD=RunModel_GR4J,FUN_CRIT=ErrorCrit_NSE)
OutputsCalib <- Calibration_Michel(InputsModel = InputsModel, RunOptions = RunOptions,
InputsCrit = InputsCrit, CalibOptions = CalibOptions,
FUN_MOD = RunModel_GR4J, FUN_CRIT = ErrorCrit_NSE)
## simulation
Param <- OutputsCalib$ParamFinalR
OutputsModel <- RunModel_GR4J(InputsModel=InputsModel,RunOptions=RunOptions,Param=Param)
OutputsModel <- RunModel_GR4J(InputsModel = InputsModel,
RunOptions = RunOptions, Param = Param)
## results preview
plot_OutputsModel(OutputsModel=OutputsModel,Qobs=BasinObs$Qmm[Ind_Run])
plot_OutputsModel(OutputsModel = OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
## efficiency criterion: Nash-Sutcliffe Efficiency
InputsCrit <- CreateInputsCrit(FUN_CRIT=ErrorCrit_NSE,InputsModel=InputsModel,
RunOptions=RunOptions,Qobs=BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_NSE(InputsCrit=InputsCrit,OutputsModel=OutputsModel)
cat(paste(" Crit ",OutputsCrit$CritName," ",round(OutputsCrit$CritValue,4),"\\n",sep=""))
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_NSE, InputsModel = InputsModel,
RunOptions = RunOptions, Qobs = BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
cat(paste(" Crit ", OutputsCrit$CritName, " ",
round(OutputsCrit$CritValue, 4), "\\n", sep = ""))
## efficiency criterion: Kling-Gupta Efficiency
InputsCrit <- CreateInputsCrit(FUN_CRIT=ErrorCrit_KGE,InputsModel=InputsModel,
RunOptions=RunOptions,Qobs=BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_KGE(InputsCrit=InputsCrit,OutputsModel=OutputsModel)
cat(paste(" Crit ",OutputsCrit$CritName," ",round(OutputsCrit$CritValue,4),"\\n",sep=""))
InputsCrit <- CreateInputsCrit(FUN_CRIT = ErrorCrit_KGE, InputsModel = InputsModel,
RunOptions = RunOptions, Qobs = BasinObs$Qmm[Ind_Run])
OutputsCrit <- ErrorCrit_KGE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
cat(paste(" Crit ", OutputsCrit$CritName, " ",
round(OutputsCrit$CritValue, 4), "\\n", sep = ""))
}
\author{
Laurent Coron (August 2013)
Laurent Coron, Claude Michel (August 2013)
}
\references{
Michel, C. (1991),
Hydrologie appliquée aux petits bassins ruraux, Hydrology handout (in French), Cemagref, Antony, France.
Hydrologie appliquée aux petits bassins ruraux, Hydrology handbook (in French), Cemagref, Antony, France.
}
\seealso{
\code{\link{Calibration}}, \code{\link{Calibration_optim}},
......
man/DataAltiExtrapolation_HBAN.Rd → man/DataAltiExtrapolation_Valery.Rd
View file @ eb3f809f
% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/DataAltiExtrapolation_HBAN.R
% Please edit documentation in R/DataAltiExtrapolation_Valery.R
\encoding{UTF-8}
\name{DataAltiExtrapolation_HBAN}
\alias{DataAltiExtrapolation_HBAN}
\title{Altitudinal extrapolation of precipitation and temperature series}
\name{DataAltiExtrapolation_Valery}
\alias{DataAltiExtrapolation_Valery}
\title{Altitudinal extrapolation of precipitation and temperature series described by A. Valéry}
\usage{
DataAltiExtrapolation_HBAN(DatesR, Precip, TempMean, TempMin = NULL,
DataAltiExtrapolation_Valery(DatesR, Precip, TempMean, TempMin = NULL,
TempMax = NULL, ZInputs, HypsoData, NLayers, quiet = FALSE)
}
\arguments{
......@@ -49,7 +49,7 @@ Forcing data (precipitation and air temperature) are extrapolated using gradient
This function is used by the \emph{CreateInputsModel} function. \cr
}
\author{
Laurent Coron, Pierre Brigode (June 2014)
Laurent Coron, Audrey Valéry, Pierre Brigode (June 2014)
}
\references{
Turcotte, R., L.-G. Fortin, V. Fortin, J.-P. Fortin and J.-P. Villeneuve (2007),
......
tests/example_Calibration_HBAN.R → tests/example_Calibration_Michel.R
View file @ eb3f809f
......@@ -18,10 +18,10 @@ InputsCrit <- CreateInputsCrit(FUN_CRIT=ErrorCrit_NSE,InputsModel=InputsModel,
RunOptions=RunOptions,Qobs=BasinObs$Qmm[Ind_Run])
## preparation of CalibOptions object
CalibOptions <- CreateCalibOptions(FUN_MOD=RunModel_GR4J,FUN_CALIB=Calibration_HBAN)
CalibOptions <- CreateCalibOptions(FUN_MOD=RunModel_GR4J,FUN_CALIB=Calibration_Michel)
## calibration
OutputsCalib <- Calibration_HBAN(InputsModel=InputsModel,RunOptions=RunOptions,
OutputsCalib <- Calibration_Michel(InputsModel=InputsModel,RunOptions=RunOptions,
InputsCrit=InputsCrit,CalibOptions=CalibOptions,
FUN_MOD=RunModel_GR4J,FUN_CRIT=ErrorCrit_NSE)
......
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