aequorin_calibration_function<-function(file_path,rep_type,rep_custom,data_type,plot_offset){
  #Assuming all data is of the same type
  data_file <- read.csv(file_path, header=T)
  if(is.na(data_file[1,dim(data_file)][2])==TRUE){
    data_length<-dim(data_file)[2]-4} else{
      data_length<-dim(data_file)[2]-3}
  rep1<-list()

  if(rep_type=="Numbers"){
    num_u<-unique(data_file[,2])
    for (num_u_i in 1:length(num_u)){
      rep1[[num_u_i]]<-(which(data_file[,2]==num_u[num_u_i]))}

  }else if(rep_type=="Letters"){
    let_u<-unique(data_file[,3])
    for (let_u_i in 1:length(let_u)){
      rep1[[let_u_i]]<-(which(data_file[,3]==let_u[let_u_i]))}

  } else if(rep_type=="Custom"){
    rep1<-rep_custom
  } else{
    return("ERROR: You have not specified replicate type in the second arguement. \"Numbers\" indicate replicates are ordered by numbers, \"Letters\" by letters. Choose \"Custom\" if replicates are ordered by some other means and please specify which in the next argument.")
  }

  # Define constants - Note only works right now if all samples are of the same data type, would need to specify a list of "WT" or "Mut" etc.

  result_mat1_list<-list()
  for (ml1 in 1:length(rep1)){
    if(data_type[ml1]=="WT"){
      KR22<-7330000
      KR37<-KR22*sqrt(2)
      KTR<-120
      Slope<-2.99
      Ratec<-1
    }else if(data_type[ml1]=="Mut"){
      KR22<-1.61*10^7
      KR37<-KR22*sqrt(2)
      KTR<-22008
      Slope<-1.43
      Ratec<-1
    }else if(data_type[ml1]=="Mut_coeln"){
      KR22<-8.47*10^7
      KR37<-KR22*sqrt(2)
      KTR<-165600
      Slope<-1.2038
      Ratec<-0.138
    }else{
      return("ERROR: data type has not been specified, pleas put either \"WT\", \"Mut\" or \"Mut_coeln\".")
    }

    result_mat1<-matrix(0,data_length,4*length(rep1[[ml1]]),)
    for (i in 1:length(rep1[[ml1]])){
      result_mat1[,i]<-as.numeric(data_file[rep1[[ml1]][i],][-c(1:3,184)])
      min_ratio<-min(result_mat1[,i])

      result_mat1[1,i+length(rep1[[ml1]])]<-((result_mat1[1,i]-(min_ratio*Ratec))/(sum(result_mat1[,i])))^(1/Slope)
      result_mat1[1,i+(2*length(rep1[[ml1]]))]<-(result_mat1[1,i+length(rep1[[ml1]])]+(result_mat1[1,i+length(rep1[[ml1]])]*KTR)-1)/(KR37*(1-result_mat1[1,i+length(rep1[[ml1]])]))
      result_mat1[1,i+(3*length(rep1[[ml1]]))]<-result_mat1[1,i+(2*length(rep1[[ml1]]))]*10^6
      for (j in 2:data_length){
        result_mat1[j,i+length(rep1[[ml1]])]<-((result_mat1[j,i]-(min_ratio*Ratec))/(sum(result_mat1[-c(1:(j-1)),i])))^(1/Slope)
        result_mat1[j,i+(2*length(rep1[[ml1]]))]<-(result_mat1[j,i+length(rep1[[ml1]])]+(result_mat1[j,i+length(rep1[[ml1]])]*KTR)-1)/(KR37*(1-result_mat1[j,i+length(rep1[[ml1]])]))
        result_mat1[j,i+(3*length(rep1[[ml1]]))]<-result_mat1[j,i+(2*length(rep1[[ml1]]))]*10^6
      }
    }
    result_mat1_list[[(ml1*2)-1]]<-result_mat1

    a<-plot_offset
    RN<-rep(1,(data_length-a))
    ratio<-result_mat1[c(1:(data_length-a)),length(rep1[[ml1]])+1]
    C2pC<-result_mat1[c(1:(data_length-a)),length(rep1[[ml1]])*3+1]
    for (i1 in 2:length(rep1[[ml1]])){
      RN<-c(RN,rep(i1,(data_length-a)))
      ratio<-c(ratio,result_mat1[c(1:(data_length-a)),length(rep1[[ml1]])+i1])
      C2pC<-c(C2pC,result_mat1[c(1:(data_length-a)),length(rep1[[ml1]])*3+i1])
    }

    DF_plot<-data.frame(time=rep(c(1:(data_length-a)),length(rep1[[ml1]])),ReplicateNumber=RN,Ratio=ratio,Ca2plusConc=C2pC)

    result_mat1_list[[(ml1*2)]]<-ggplot(DF_plot, aes(x=time, y=Ca2plusConc, colour=factor(ReplicateNumber), group=factor(ReplicateNumber)))+
      scale_colour_brewer(palette="Set1")+
      theme_bw()+
      geom_line(size=1) + guides(color=guide_legend(title="Replicates"))+
      geom_point() +ylab("Ca2+ concentration") +xlab("Time") +labs(title=as.character(ml1))

  }
  return(result_mat1_list)
}