#April 2016

# High level function to normalize flat scores matrix w.r.t. MaxNorm or Quantile Normalization (Qnorm)
# INPUT: 
# norm.type: it must be a normalization method:
#			 - MaxNorm: each score is divided w.r.t. the max of each class
# 			 - Qnorm: a quantile normalization is applied. Library preprocessCore is used.
# flat.file: name of the flat scores matrix (without rda extension). 
# ann.file: name of the target labels (without rda extension). It must be  an .rda file containing the label matrix of the examples (def: ann.file)
# dag.file: name of the graph that represents the hierarchy of the classes. 
# flat.dir: relative path to folder where flat normalized scores matrix is stored
# ann.dir: relative path to folder where annotation matrix is stored
# dag.dir: relative path to folder where graph is stored
# OUTPUT:
# the matrix of the scores flat normalized w.r.t. MaxNorm or Qnorm
Do.FLAT.scores.normalization <- function(	norm.type= "MaxNorm", flat.file=flat.file, ann.file=ann.file, 																		 
								 			dag.file=dag.file, flat.dir=flat.dir, ann.dir=ann.dir, 
								 			dag.dir=dag.dir, flat.norm.dir=flat.norm.dir
										){
	## Loading Data ############
	## loading hpo dag
	dag.path <- paste0(dag.dir, dag.file,".rda");
	hpo <- get(load(dag.path));
	
	##root node
	root <- root.node(hpo);

	## loading flat scores matrix relative to a specific subontology
	flat.path <- paste0(flat.dir, flat.file,".rda");
	S.flat <- get(load(flat.path));
	gc();	##in order to save ram memory..
	
	## removing root node from flat matrix if it exists
	if(root %in% colnames(S.flat)){
		S.flat <- S.flat[,-which(colnames(S.flat)==root)];
	}

	## loading annotation matrix
	ann.path <- paste0(ann.dir, ann.file,".rda");
	hpo.ann <- get(load(ann.path));
	gc();

	## removing root node from annotation table 
	ann.no.root <- target <- hpo.ann[,-which(colnames(hpo.ann)==root)];

	## normalization
	if(norm.type=="MaxNorm"){
		## Max Normalization
		S.norm <- normalize.max(S.flat);		
	}else{
		## Quantile Normalization
		S.norm <- normalize.quantiles(S.flat);
		dimnames(S.norm) <- list(rownames(S.flat),colnames(S.flat));	
	}

	## Storing results
	save(S.norm, file=paste0(flat.norm.dir, norm.type, ".", flat.file, ".rda"));
}