# R code developed by:
# International Research Institute for Climate and Society
# Columbia University in the City of New York, USA
# Last update: Jully 3, 2013
# --------------------------------------------------------------------------------

# --------------------------------------------------------------------------------
# FUNCTION : ExtractContinuousScores
# --------------------------------------------------------------------------------
# Dependancies : (see each function for further details)
#		-- File "Directory_Output/XXX_ens_correct_MonthlyMean_Continuous_Skill_Scores_3_Month_Predictions.csv"
#		OR
#		-- File "Directory_Output/XXX_ens_correct_MonthlyMean_Anomalies_Continuous_Skill_Scores_3_Month_Predictions.csv"
# --------------------------------------------------------------------------------
# Results :
#		-- A list of all the selected scores of interest, put in the right order for plotting
# --------------------------------------------------------------------------------
# Parameters :
# 		-- XXX the model
# 		-- L=1 or 2 or 3 the leading time for to consider for the scores
# 		-- ens="ensemble" or "single" the nature of the model
# 		-- correct="corrected_method" or "uncorected" indicate the way the results have been corrected (or not)
# 		-- anomalies=TRUE or FALSE indicate if you want the scores to be extracted for the anomalies (TRUE) or the nominal values (FALSE)
# --------------------------------------------------------------------------------

ExtractContinuousScores <- function(XXX,L,ens,correct,anomalies){
	
	if (!anomalies){ # anomalies=FALSE : extract the continuous scores of the nominal values
		
		Pred<-read.csv(paste(Directory_Output,XXX,"_",ens,"_",correct,"_MonthlyMean_Continuous_Skill_Scores_3_Month_Predictions.csv",sep=""),sep=",")
		
		# In that case, extract MSE, SS, Bias and ACC
		MSE_Pred<-Pred[seq(4,nrow(Pred),by=9),L+1]
		MSE_Pred <-c(MSE_Pred[c(11,12)], MSE_Pred[-c(11,12)]) #Put them back in order (Jan -> Dec)
		SS_Pred<-Pred[seq(7,nrow(Pred),by=9),L+1]
		SS_Pred <-c(SS_Pred[c(11,12)], SS_Pred[-c(11,12)])
		Bias_Pred<-Pred[seq(9,nrow(Pred),by=9),L+1]
		Bias_Pred <-c(Bias_Pred[c(11,12)], Bias_Pred[-c(11,12)])
		ACC_Pred<-Pred[seq(8,nrow(Pred),by=9),L+1]
		ACC_Pred <-c(ACC_Pred[c(11,12)], ACC_Pred[-c(11,12)])
		
		Scores<-list(MSE=MSE_Pred, SS=SS_Pred, Bias=Bias_Pred, ACC=ACC_Pred)
		return(Scores)
		
	} else { # anomalies=TRUE : extract the continuous scores on the anomalies
		
		Pred<-read.csv(paste(Directory_Output,XXX,"_",ens,"_",correct,"_MonthlyMean_Anomalies_Continuous_Skill_Scores_3_Month_Predictions.csv",sep=""),sep=",")
		# In that case, extract MSE and SS
		MSE_Pred<-Pred[seq(4,nrow(Pred),by=7),L+1]
		MSE_Pred <-c(MSE_Pred[c(11,12)], MSE_Pred[-c(11,12)]) #Put them back in order (Jan -> Dec)
		SS_Pred<-Pred[seq(6,nrow(Pred),by=7),L+1]
		SS_Pred <-c(SS_Pred[c(11,12)], SS_Pred[-c(11,12)])
		
		Scores<-list(MSE=MSE_Pred, SS=SS_Pred)
		return(Scores)
	}
}

# --------------------------------------------------------------------------------
# FUNCTION : ExtractProbalisticScores
# --------------------------------------------------------------------------------
# Dependancies : (see each function for further details)
#		-- File "Directory_Output/XXX_ens_correct_Eventev_MonthlyMean_Anomalies_Probabilistic_Skill_Scores_3_Month_Predictions.csv"
# --------------------------------------------------------------------------------
# Results :
#		-- A list of all the selected scores of interest, put in the right order for plotting
# --------------------------------------------------------------------------------
# Parameters :
# 		-- XXX the model
# 		-- L=1 or 2 or 3 the leading time for to consider for the scores
# 		-- correct="corrected_method" or "uncorected" indicate the way the results have been corrected (or not)
# 		-- ev=1 or 2 the reference of the event taken into account for the scores
# --------------------------------------------------------------------------------

ExtractProbalisticScores<-function(XXX,L,correct,ev){
	
	Sco<-read.csv(paste(Directory_Output, XXX, "_", "ensemble", "_", correct, "_", "Event", ev, "_MonthlyMean_Anomalies_Probabilistic_Skill_Scores_3_Month_Predictions.csv", sep = ""),sep=",")
	
	# In that case, extract BS, SS and ROC
	BS<-Sco[seq(2,nrow(Sco),by=4),L+1]
	BS <-c(BS[c(11,12)], BS[-c(11,12)])
	SS<-Sco[seq(4,nrow(Sco),by=4),L+1]
	SS <-c(SS[c(11,12)], SS[-c(11,12)])
	ROC<-Sco[seq(5,nrow(Sco),by=4),L+1]
	ROC <-c(ROC[c(11,12)], ROC[-c(11,12)])
	
	Scores<-list(BS=BS, SS=SS, ROC=ROC)
	return(Scores)
}