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```
#' Function that loads forcings data for Seabass population model and performs the interpolation
#'
#' @param userpath the path where folder containing model inputs and outputs is located
#' @return a list containing the time series in the odd positions and realted forcings in the even positions. Forcings returned are: Water temperature [Celsius degrees] and feeding rate [g/individual x d]
#' @export
#'
#' @import matrixStats plotrix rstudioapi
#'
#' @import stats utils
#'
Bass_pop_dataloader<-function(userpath) {
# Reads forcing files
Ttem=read.csv(paste0(userpath,"/Bass_population/Inputs/Forcings//Water_temperature.csv"),sep=",",header=FALSE) # Reading the temperature time series (daily series) data
DaF=read.csv(paste0(userpath,"/Bass_population/Inputs/Forcings//Feeding.csv"),sep=",",header=FALSE) # Reading the individual feeding dose time series (daily series) data
# Reads integration extremes
Param_matrix=read.csv(paste0(userpath,"/Bass_population/Inputs/Parameters//Parameters.csv"),sep=",") # Reading the matrix containing parameters and their description
#Extracts vectors from the forcing files
timeT=as.matrix(Ttem[,1]) # Vector of the times of Temperature measurements
Temperature=as.double(as.matrix(Ttem[,2])) # Vector of water temperature time series (daily series)
timeG=as.matrix(DaF[,1]) # Vector of the times of feeding dose
G=as.double(as.matrix(DaF[,2])) # Vector of the individual feeding dose time series (daily series)
Dates=Param_matrix[22:23,3] # Vector containing the starting and ending date of the simulation
# Times needed to perform interpolation
t0=min(as.numeric(as.Date(timeT[1], "%d/%m/%Y")), as.numeric(as.Date(timeG[1], "%d/%m/%Y")))
ti=as.numeric(as.Date(Dates[1], "%d/%m/%Y"))-t0 # Start of integration [day]
tf=as.numeric(as.Date(Dates[2], "%d/%m/%Y"))-t0 # End of integration [day]
# Prepare t data for Temperature and Feeding interpolation
timeTseries=as.numeric(as.Date(timeT, "%d/%m/%Y"))-t0 # Days at which temperature measurements are available
timeGseries=as.numeric(as.Date(timeG, "%d/%m/%Y"))-t0 # Days at which food measurements are available
# Interpolation of Temperature and Feeding forcings
Ttem=as.vector(matrix(0,nrow=ti-1)) # Initialize vector Tint
Gtem=as.vector(matrix(0,nrow=ti-1)) # Initialize vector Gint
i=ti:tf+1 # Interpolation base points
Ttem2=approx(timeTseries,Temperature,xout=i) # T interpolation according to base points
Gtem2=approx(timeGseries,G,xout=i) # G interpolation according to base points
Tint=c(Ttem, Ttem2$y) # Interpolated T values starting at t0
Gint=c(Gtem, Gtem2$y) # Interpolated G values starting at t0
# Prepare dates vector
daysT <- seq(as.Date(timeT[1], format = "%d/%m/%Y"), by = "days", length = length(Tint))
daysG <- seq(as.Date(timeG[1], format = "%d/%m/%Y"), by = "days", length = length(Tint))
# Check if forcings are Ok with integration extremes
if ((ti<(as.numeric(as.Date(timeT[1], "%d/%m/%Y"))-t0))|(ti<(as.numeric(as.Date(timeG[1], "%d/%m/%Y"))-t0))) {
cat("ERROR: forcings are beginning after the specified integration start\n")
cat("Impossible to proceed with interpolation\n")
}
if ((ti>(as.numeric(as.Date(timeT[length(timeT)], "%d/%m/%Y"))-t0))|(ti>(as.numeric(as.Date(timeG[length(timeG)], "%d/%m/%Y"))-t0))) {
cat("ERROR: forcing are ending before the specified integration end\n")
cat("Impossible to proceed with interpolation\n")
}
forcings=list(daysT,Tint,daysG,Gint)
return(forcings)
}
```

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