#' CRAN and bioconductor packages install and library loading	
install.packages.if.necessary <- function(CRAN.packages=c(), bioconductor.packages=c()) {
	for (p in CRAN.packages) {	
	  if (!require(p, character.only=T)) { # repo located at IBDML, Marseille Luminy	
		  install.packages(p, repos="http://cran.biotools.fr/") 	
		  library(p, character.only=T)  	
	  }	
	}
	if (length(bioconductor.packages) > 0) {
		source("http://bioconductor.org/biocLite.R")
	}
	for (p in bioconductor.packages) {
	  if (!require(p, character.only=T)) {
		  biocLite(p) 
		  library(p, character.only=T)
		}
	}
}

# packages needed
CRAN.packages <- c("igraph", "tools")
install.packages.if.necessary(CRAN.packages)

#' Build an igraph network	
#' Take df with 2 columns, format "ncol" (one line per interaction, the 2 interactors are separated by a tab)
#' returns a simplified network as an igraph object.	
build.network <- function (raw.network) {	
  net <- igraph::graph.edgelist(raw.network, directed=F)	
  return (igraph::simplify(net)) # simplify	
}

#' ### Build a data.frame from a zipped csv file	
get.data.from.zip <- function (path.to.file, sep=","){		
  internal.file <- tools::file_path_sans_ext(basename(path.to.file))		
  unzipped.file <- unz(path.to.file, internal.file)	
  return(read.table(unzipped.file, header=T, sep=sep, fill=T))	
}

#' ### Download a file from the internet if it doesn't already exist locally	
#' If a local file already exists, do not download unless force is TRUE
#' url: string: url where the file is located  	
#' download.dir: string: path to download directory	
#' force: boolean: do we want to override local file with downloaded file	
download.if.necessary <- function (url, download.dir=".", force=F){		
  filename = basename(url)	
  path.to.file = file.path(download.dir, filename)	
  if(!file.exists(path.to.file) | force){ # if file does not exists or force download	
    download.file(url, path.to.file, mode='w')
    # download.file(url, path.to.file, method="curl", mode='w')	
  }	
  return(path.to.file)	
}

# Take 2 specific columns, remove lines containing incomplete data
clean.network <- function(net) {
  net <- net[, c("Symbol.A", "Symbol.B")]
  net[net == ""] <- NA
  net[net == "-"] <- NA
  return(na.omit(net))
}