comparison MsDbOutputDataFrameStream.R @ 1:45e985cd8e9e draft

planemo upload for repository https://github.com/workflow4metabolomics/lcmsmatching.git commit d4048accde6bdfd5b3e14f5394902d38991854f8-dirty

0:3afe41d3e9e7

if ( ! exists('MsDbOutputDataFrameStream')) { # Do not load again if already loaded

	library(methods)
	library(plyr)
	source('MsDbOutputStream.R')
	source('dfhlp.R', chdir = TRUE)

	#####################
	# CLASS DECLARATION #

	##################
	# GET DATA FRAME #
	##################
	
	MsDbOutputDataFrameStream$methods( getDataFrame = function(...) {

		# Put at least a column name if empty
		if (nrow(.self$.df) == 0)
			.self$.df[[.self$.output.fields[[MSDB.TAG.MZ]]]] <- numeric()

		return(.self$.df)
	})
	
	#################
	# MATCHED PEAKS #
	#################
	
	MsDbOutputDataFrameStream$methods( matchedPeaks = function(mz, rt = NULL, unused = NULL, peaks = NULL) {

		# Set input values
		x <- data.frame(mz = mz)
		if ( ! is.null(rt))
			x <- cbind(x, data.frame(rt = rt))

		# Merge input values with matched peaks
		if ( ! is.null(peaks)) {

			# No rows

					}

				# Concatenate results in one line
				if (.self$.one.line) {
 					# For each column, concatenate all values in one string.
					for (c in seq(peaks))
						peaks[1, c] <- paste0(peaks[[c]], collapse = .self$.match.sep, FUN.VALUE = '')
					peaks <- peaks[1, ] # Keep only first line
				}
			}

			# Merge

1:45e985cd8e9e

if ( ! exists('MsDbOutputDataFrameStream')) { # Do not load again if already loaded

	library(methods)
	source('MsDbOutputStream.R')
	source('dfhlp.R', chdir = TRUE)

	#####################
	# CLASS DECLARATION #

	##################
	# GET DATA FRAME #
	##################
	
	MsDbOutputDataFrameStream$methods( getDataFrame = function() {

		# Put at least a column name if empty
		if (nrow(.self$.df) == 0)
			.self$.df[[.self$.output.fields[[MSDB.TAG.MZ]]]] <- numeric()

		return(.self$.df)
	})
	
	# Move columns to beginning {{{1
	
	MsDbOutputDataFrameStream$methods( moveColumnsToBeginning = function(cols) {
		all.cols <- colnames(.self$.df)
		other.cols <- all.cols[ ! all.cols %in% cols]
		cols <- cols[cols %in% all.cols]
		.df <<- .self$.df[c(cols, other.cols)]
	})

	#################
	# MATCHED PEAKS #
	#################
	
	MsDbOutputDataFrameStream$methods( matchedPeaks = function(mz, rt = NULL, unused = NULL, peaks = NULL) {

		library(plyr)

		# Set input values
		x <- data.frame(mz = mz)
		colnames(x) <- MSDB.TAG.MZ
		if ( ! is.null(rt)) {
			x.rt <- data.frame(rt = rt)
			colnames(x.rt) <- MSDB.TAG.RT
			x <- cbind(x, x.rt)
		}

		# Merge input values with matched peaks
		if ( ! is.null(peaks)) {

			# No rows

					}

				# Concatenate results in one line
				if (.self$.one.line) {
 					# For each column, concatenate all values in one string.
					for (c in seq(peaks)) {
						v <- peaks[[c]]
						v <- v[ ! is.na(v)] # remove NA values
						v <- v[ ! duplicated(v)] # remove duplicates
						peaks[1, c] <- paste0(v, collapse = .self$.match.sep, FUN.VALUE = '')
					}
					peaks <- peaks[1, ] # Keep only first line
				}
			}

			# Merge