Calibration_optim.Rd

% Generated by roxygen2 (4.0.1): do not edit by hand
\encoding{UTF-8}
\name{Calibration_optim}
\alias{Calibration_optim}
\title{Calibration algorithm which minimises the error criterion using the stats::optim function}
\usage{
Calibration_optim(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}

\item{RunOptions}{[object of class \emph{RunOptions}] see \code{\link{CreateRunOptions}} for details}

\item{InputsCrit}{[object of class \emph{InputsCrit}] see \code{\link{CreateInputsCrit}} for details}

\item{CalibOptions}{[object of class \emph{CalibOptions}] see \code{\link{CreateCalibOptions}} for details}

\item{FUN_MOD}{[function] hydrological model function (e.g. RunModel_GR4J, RunModel_CemaNeigeGR4J)}

\item{FUN_CRIT}{[function] error criterion function (e.g. ErrorCrit_RMSE, ErrorCrit_NSE)}

\item{FUN_TRANSFO}{(optional) [function] model parameters transformation function, if the FUN_MOD used is native in the package FUN_TRANSFO is automatically defined}

\item{quiet}{(optional) [boolean] boolean indicating if the function is run in quiet mode or not, default=FALSE}
}
\value{
[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{$Nruns        }  \tab   [numeric] number of model runs done during the calibration \cr
         \emph{$CritName     }  \tab   [character] name of the calibration criterion \cr
         \emph{$CritBestValue}  \tab   [numeric] theoretical best criterion value \cr
         }
}
\description{
Calibration algorithm which minimises the error criterion. \cr
\cr
The algorithm is based on the "optim" function from the "stats" R-package
(using method="L-BFGS-B", i.e. a local optimization quasi-Newton method).
}
\details{
To optimise the exploration of the parameter space, transformation functions are used to convert
the model parameters. This is done using the TransfoParam functions.
}
\examples{
## load of catchment data
require(airGR)
data(L0123001)

## preparation of InputsModel object
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"))

## preparation of RunOptions object
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])

## preparation of CalibOptions object
CalibOptions <- CreateCalibOptions(FUN_MOD=RunModel_GR4J,FUN_CALIB=Calibration_optim)

## calibration