#!/usr/local/public/bin/Rscript --vanilla --slave --no-site-file

################################################################################################
# pca_FactoMiner_galaxy_wrapper                                                                #
#                                                                                              #
# Author : Marie Tremblay-Franco / Jean-Francois MARTIN                                        #
# User : Galaxy                                                                                #
# Original data : --                                                                           #
# Starting date : 24-03-2015                                                                   #
# Version 1 :                                                                                  #
#                                                                                              #
#                                                                                              #
# Input files : dataMatrix.txt                                                                 #
# Output files : graph_output.pdf ;                                                            #
#                                                                                              #
################################################################################################

##------------------------------
## Options
##------------------------------
strAsFacL <- options()$stringsAsFactors
options(stringsAsFactors = FALSE)

##------------------------------
## Libraries laoding
##------------------------------
# For parseCommandArgs function
library(batch) 
library(pcaMethods)
library(FactoMineR)

# R script call
source_local <- function(fname)
{
	argv <- commandArgs(trailingOnly = FALSE)
	base_dir <- dirname(substring(argv[grep("--file=", argv)], 8))
	source(paste(base_dir, fname, sep="/"))
}

#Import the different functions used for PCA
source_local("pca_FactoMiner_galaxy_functions.R")

##------------------------------
## Constants
##------------------------------
topEnvC <- environment()
flagC <- "\n"


##------------------------------
## Lecture parametres
##------------------------------
argLs <- parseCommandArgs(evaluate=FALSE)

log <- argLs[["logOut"]]

  # Inputs
	# Matrice donnees
data <- read.table(argLs[["datafile"]],header=TRUE,sep="\t",dec=".",check.names = FALSE)
rownames(data) <- data[,1]
data <- data[,-1]

	# Facteur biologique
hb=0
if(argLs[["factor"]] != "None")
{
  facteur <- data[,1]
  if(mode(facteur) != 'character')
  {
    stop("\n First column must be a factor (variable qualitative)\n")
  }
  facteur <- as.factor(facteur)
  data[,1] <- as.factor(data[,1])
  hb=1
}

  # Appel de la fonction
eigenplot=0
contribplot=0
scoreplot=0
loadingplot=0

if (argLs[["plotev"]]=="yes")
{
  eigenplot=1
}

if (argLs[["plotcontrib"]]=="yes")
{
  contribplot=1
}


if (argLs[["plotindiv"]]=="yes")
{
  scoreplot=1
}


if (argLs[["plotvar"]]=="yes")
{
  loadingplot=1
}

  # Outputs
nomGraphe <- argLs[["outgraphpdf"]]
res.pca <- pca.main(ids=data,bioFact=facteur,ncp=argLs[["npc"]],hb=hb,scalingMethod=argLs[["scaleoption"]],minContribution=c(argLs[["contribh"]],argLs[["contribv"]]),mainTitle=argLs[["title"]],textSize=argLs[["tc"]],
	 	    principalPlane=c(argLs[["pch"]],argLs[["pcv"]]),eigenplot=eigenplot,contribplot=contribplot,scoreplot=scoreplot,loadingplot=loadingplot,nomGraphe=argLs[["outgraphpdf"]])


################################# fin  ##############################################