\name{Histo2Hindcast}
\alias{Histo2Hindcast}
\title{
Chunks Long Simulations For Comparison With Hindcasts
}
\description{
This function reorganizes a long run (historical typically) with only one start date into chunks corresponding to a set of start dates. The expected input structure is the one output from \code{Load()} with 4 to 7 dimensions.
}
\usage{
Histo2Hindcast(varin, sdatesin, sdatesout, nleadtimesout)
}
\arguments{
  \item{varin}{
Array of model or observational data with dimensions:\cr
  c(nmod/nexp/nobs, nmemb/nparam, nsdates, nltimes) up to\cr
  c(nmod/nexp/nobs, nmemb/nparam, nsdates, nltimes, nlevel, nlat, nlon)
  }
  \item{sdatesin}{
Start date of the input matrix 'YYYYMMDD'.
  }
  \item{sdatesout}{
List of start dates of the output matrix c('YYYYMMDD', 'YYYYMMDD', ...).
  }
  \item{nleadtimesout}{
Number of leadtimes in the output matrix.
  }
}
\value{
An array with the same number of dimensions as varin, the same dimensions 1 and 2 and potentially the same dimensions 5 to 7. Dimensions 3 and 4 are set by the arguments sdatesout and nleadtimesout.
}
\examples{
# See examples on Load() to understand the first lines in this example
  \dontrun{
data_path <- system.file('sample_data', package = 's2dverification')
exp <- list(
         name = 'experiment',
         path = file.path(data_path, 'model/$EXP_NAME$/monthly_mean',
                          '$VAR_NAME$_3hourly/$VAR_NAME$_$START_DATES$.nc')
       )
obs <- list(
         name = 'observation',
         path = file.path(data_path, 'observation/$OBS_NAME$/monthly_mean',
                          '$VAR_NAME$/$VAR_NAME$_$YEAR$$MONTH$.nc')
       )
# Now we are ready to use Load().
startDates <- c('19851101', '19901101', '19951101', '20001101', '20051101')
sampleData <- Load('tos', list(exp), list(obs), startDates,
                   leadtimemin = 1, leadtimemax = 4, output = 'lonlat',
                   latmin = 27, latmax = 48, lonmin = -12, lonmax = 40)
  }
  \dontshow{
startDates <- c('19901101')
sampleData <- s2dverification:::.LoadSampleData('tos', c('experiment'),
                                                c('observation'), startDates,
                                                leadtimemin = 1,
                                                leadtimemax = 4,
                                                output = 'areave',
                                                latmin = 27, latmax = 48,
                                                lonmin = -12, lonmax = 40)
  }


start_dates_out <- c('19901101', '19911101', '19921101', '19931101', '19941101')
leadtimes_per_startdate <- 12
experimental_data <- Histo2Hindcast(sampleData$mod, startDates[1], 
                                    start_dates_out, leadtimes_per_startdate)
observational_data <- Histo2Hindcast(sampleData$obs, startDates[1], 
                                     start_dates_out, leadtimes_per_startdate)
PlotAno(experimental_data, observational_data, start_dates_out, 
        toptitle = paste('anomalies reorganized into shorter chunks'), 
        ytitle = 'K', fileout='tos_histo2hindcast.eps')
}
\author{
History:\cr
0.1  -  2012-11  (V. Guemas, \email{vguemas at ic3.cat})  -  Original code\cr
1.0  -  2013-09  (N. Manubens, \email{nicolau.manubens at ic3.cat})  -  Formatting to CRAN
}
\keyword{datagen}
