CreateInputsModel.R

#*************************************************************************************************
#' Creation of the InputsModel object required to the RunModel functions.
#'
#' Users wanting to use FUN_MOD functions that are not included in 
#' the package must create their own InputsModel object accordingly.
#*************************************************************************************************
#' @title  Creation of the InputsModel object required to the RunModel functions
#' @author Laurent Coron (June 2014)
#' @seealso \code{\link{RunModel}}, \code{\link{CreateRunOptions}}, \code{\link{CreateInputsCrit}}, \code{\link{CreateCalibOptions}}, \code{\link{DataAltiExtrapolation_HBAN}}
#' @example tests/example_RunModel.R
#' @encoding UTF-8
#' @export
#_FunctionInputs__________________________________________________________________________________
#' @param  FUN_MOD     [function] hydrological model function (e.g. RunModel_GR4J, RunModel_CemaNeigeGR4J)
#' @param  DatesR      [POSIXlt] vector of dates required to create the GR model and CemaNeige module inputs
#' @param  Precip      [numeric] time series of total precipitation (catchment average) [mm], required to create the GR model and CemaNeige module inputs
#' @param  PotEvap     [numeric] time series of potential evapotranspiration (catchment average) [mm], required to create the GR model inputs
#' @param  TempMean    (optional) [numeric] time series of mean air temperature [degC], required to create the CemaNeige module inputs
#' @param  TempMin     (optional) [numeric] time series of min air temperature [degC], possibly used to create the CemaNeige module inputs
#' @param  TempMax     (optional) [numeric] time series of max air temperature [degC], possibly used to create the CemaNeige module inputs
#' @param  ZInputs     (optional) [numeric] real giving the mean elevation of the Precip and Temp series (before extrapolation) [m]
#' @param  HypsoData   (optional) [numeric] vector of 101 reals: min, q01 to q99 and max of catchment elevation distribution [m], required to create the GR model inputs, if not defined a single elevation is used for CemaNeige
#' @param  NLayers     (optional) [numeric] integer giving the number of elevation layers requested [-], required to create the GR model inputs, default=5
#' @param  quiet       (optional) [boolean] boolean indicating if the function is run in quiet mode or not, default=FALSE
#_FunctionOutputs_________________________________________________________________________________
#' @return  [list] object of class \emph{InputsModel} containing the data required to evaluate the model outputs; it can include the following:
#'          \tabular{ll}{
#'          \emph{$DatesR              }  \tab   [POSIXlt] vector of dates \cr
#'          \emph{$Precip              }  \tab   [numeric] time series of total precipitation (catchment average) [mm] \cr
#'          \emph{$PotEvap             }  \tab   [numeric] time series of potential evapotranspiration (catchment average) [mm], \cr\tab defined if FUN_MOD includes GR4H, GR4J, GR5J, GR6J, GR2M or GR1A \cr \cr
#'          \emph{$LayerPrecip         }  \tab   [list] list of time series of precipitation (layer average) [mm], \cr\tab defined if FUN_MOD includes CemaNeige \cr \cr
#'          \emph{$LayerTempMean       }  \tab   [list] list of time series of mean air temperature (layer average) [degC], \cr\tab defined if FUN_MOD includes CemaNeige \cr \cr
#'          \emph{$LayerFracSolidPrecip}  \tab   [list] list of time series of solid precip. fract. (layer average) [-], \cr\tab defined if FUN_MOD includes CemaNeige \cr \cr
#'          }
#**************************************************************************************************
CreateInputsModel <- function(FUN_MOD,DatesR,Precip,PotEvap=NULL,TempMean=NULL,TempMin=NULL,TempMax=NULL,ZInputs=NULL,HypsoData=NULL,NLayers=5,quiet=FALSE){

  ObjectClass <- NULL;

  ##check_FUN_MOD
    BOOL <- FALSE;
    if(identical(FUN_MOD,RunModel_GR4H)){
      ObjectClass <- c(ObjectClass,"hourly","GR"); 
      TimeStep <- as.integer(60*60);
      BOOL <- TRUE; 
    }
    if(identical(FUN_MOD,RunModel_GR4J) | identical(FUN_MOD,RunModel_GR5J) | identical(FUN_MOD,RunModel_GR6J)){
      ObjectClass <- c(ObjectClass,"daily","GR"); 
      TimeStep <- as.integer(24*60*60);
      BOOL <- TRUE; 
    }
    if(identical(FUN_MOD,RunModel_GR2M)){
      ObjectClass <- c(ObjectClass,"GR","monthly"); 
      TimeStep <- as.integer(c(28,29,30,31)*24*60*60);
      BOOL <- TRUE; 
    }
    if(identical(FUN_MOD,RunModel_GR1A)){
      ObjectClass <- c(ObjectClass,"GR","yearly"); 
      TimeStep <- as.integer(c(365,366)*24*60*60);
      BOOL <- TRUE; 
    }
    if(identical(FUN_MOD,RunModel_CemaNeige)){
      ObjectClass <- c(ObjectClass,"daily","CemaNeige");
      TimeStep <- as.integer(24*60*60);
      BOOL <- TRUE; 
    }
    if(identical(FUN_MOD,RunModel_CemaNeigeGR4J) | identical(FUN_MOD,RunModel_CemaNeigeGR5J) | identical(FUN_MOD,RunModel_CemaNeigeGR6J)){
      ObjectClass <- c(ObjectClass,"daily","GR","CemaNeige");
      TimeStep <- as.integer(24*60*60);
      BOOL <- TRUE;