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#' Bream bioenergetic spatialized model preprocessor - used inside spatialization loop
#'
#' @param userpath the path where folder containing model inputs and outputs is located
#' @param forcings a list containing forcings used by the model
#' @return a list containing the data used by the main script
#'
#' @import matrixStats plotrix rstudioapi
#'
#' @import grDevices graphics utils stats
#'
Bream_spatial_pre_int<-function(userpath,forcings){
# Extracts forcings values from the list
timeT=forcings[[1]]
Tint=forcings[[2]]
timeG=forcings[[3]]
Gint=forcings[[4]]
# parameters from .csv files
Param_matrix=read.csv(paste0(userpath,"/Bream_spatial/Inputs/parameters//Parameters.csv"),sep=",") # Reading the matrix containing parameters and their description
Food=read.csv(paste0(userpath,"/Bream_spatial/Inputs/Point forcings//Food_characterization.csv"),sep=",",header=FALSE) # Reading the food composition (Proteins, Lipids, Carbohydrates) data
# Extract parameters and forcing values from parameters matrix and convert to type 'double' the vector contents
Param=as.double(as.matrix(Param_matrix[1:21,3])) # Vector containing all parameters
Dates=Param_matrix[22:23,3] # Vector containing the starting and ending date of the simulation
IC=as.double(as.matrix(Param_matrix[24,3])) # Initial weight condition
CS=as.double(as.matrix(Param_matrix[25,3])) # Commercial size
Food=as.double(as.matrix(Food[,1])) # Food composition (Proteins, Lipids, Carbohydrates) data
# Prepare data for ODE solution
t0=min(as.numeric(as.Date(timeT[1], "%d/%m/%Y")), as.numeric(as.Date(timeG[1], "%d/%m/%Y")), as.numeric(as.Date(Dates[1], "%d/%m/%Y"))) # starting minimum starting date for forcings and observations
timestep=1 # Time step for integration [day]
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]
weight=as.vector(matrix(0,nrow=ti)) # Initialize vector weight
weight[ti]=IC # Weight initial value [g]
times<-cbind(ti, tf, timestep)
# Food composition vector
Pcont=Food[1] # [-] Percentage of proteins in the food
Lcont=Food[2] # [-] Percentage of lipids in the food
Ccont=Food[3] # [-] Percentage of carbohydrates in the food
output=list(Param, Tint, Gint, Food, IC, times, Dates, CS)
}
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