[R] error "variable names are limited to 256 bytes" when sourcing code

[Erik Iverson]

Is the '`' character supposed to be there before the ## Add error bars 
comment?

If that is the problem, let it be a good lesson    to use an editor with 
syntax highlighting. :) 
 
 
 


Brian Frizzelle wrote:
> All,
> 
> I think there may be some misunderstanding about my problem. In my code,
> which is written as an R function, all of my variable names are short. I get
> that error when I try to source the function so I can call it. I just do not
> know why I'm getting the error, especially since I have written other very
> similar functions that all work.
> 
> So I have chosen to post the code below. I welcome any ideas about where in
> this code the error is occurring.
> 
> ##########################################################
> ###  SCRIPT: graph_hh_wealth_function.R
> ###  DATE: April 22, 2010
> ###  AUTHOR: Brian Frizzelle
> ###                                 
> ###  This function draws two line graphs of household-level wealth from a
> variable 
> ###  in a dataset output from an agent-based model run.
> ###
> ###  The two graphs are:
> ###  	1)	a line graph showing change in Wealth over time for each individual
> ###     	household
> ###   2) 	a line graph of summary statistics of Wealth for the households
> (min,
> ###     	max, mean, and error bars)
> ###
> ###  Required Arguments:
> ###   * inpath - 	The path to the directory containing the village-level
> statistics
> ###			file
> ###		NOTE: Use the UNIX forward slash (/) convention when entering the path
> ###			and do not include a slash at the end of the path.
> ###			OK: 		"D:/data"
> ###			Not OK: 	"D:\data"
> ###			Not OK: 	"D:/data/"
> ###	* infile - 	The name of the village-level statistics file
> ###	* outpath -	The path to the directory where you want the output graphics
> to
> ###			be saved
> ###	* outpref - The prefix that you want for the output PNG graphics files
> ###		NOTE: Do not include underscores (_) or spaces in the output prefix.
> ###			Instead, please use dashes (-). Your prefix will be separated
> ###			from the remainder of the file names by a dash.
> ###
> ###  Optional Arguments:
> ###	* log.plot - Logical. Default is FALSE.
> ###			If TRUE, then the individual household wealth graph is plotted
> ###			with a logarithmic Y-axis.
> ###			If FALSE, then the individual household wealth graph is plotted
> ###			with a standard Y-axis.
> ###	* err.bar -	Logical. Default is TRUE.
> ###			If TRUE, then error bars of 1 standard deviation will be drawn
> ###			around the mean.
> ###			If FALSE, then no error bars will be drawn.
> ###	* n.quantiles - Integer. Value between 3 and 10. Default is 0, meaning
> no
> ###			quantile lines will be drawn.
> ###			This is the number of bins into which you would like the variable
> ###			separated. One line for each will be drawn, with the exception of
> ###			the min and max, which are already drawn.
> ##########################################################
> 
> graph.hh.wealth <- function(inpath, infile, outpath, outpref,
> log.plot=FALSE, 
> 				    err.bar=TRUE, n.quantiles=0)
> 
> {
> 
> 	##*************************************************
> 	## Set the path and name of the input file
> 	##  - The 'paste' command concatenates the two
> 	##  - The 'skiplines' var sets the number of lines
> 	##      to skip when reading in the dataset.
> 	##*************************************************
> 	if (substr(inpath, nchar(inpath), nchar(inpath)) == "/")
> 		inpath <- substr(inpath, 0, nchar(inpath)-1)
> 	if (substr(outpath, nchar(outpath), nchar(outpath)) == "/")
> 		outpath <- substr(outpath, 0, nchar(outpath)-1)
> 	pathfile <- paste(inpath, infile, sep="/")
> 	skiplines <- 1
> 
> 	##*************************************************
> 	## Set the names of the output file graphics
> 	##*************************************************
> 	fnout.wlth <- "hhwealth.png"
> 	fnout.wlthss <- "hhwealth-sumstats.png"
> 	output.png.wlth <- paste(outpath, "/", outpref, fnout.wlth, sep="")
> 	output.png.wlthss <- paste(outpath, "/", outpref, fnout.wlthss, sep="")
> 
> 	##*************************************************
> 	## Read in the household-level output dataset
> 	##*************************************************
> 	hhstats <- read.delim(file=pathfile, header=TRUE, sep ="\t", dec=".",
> skip=skiplines)
> 
> 	##*************************************************
> 	## Get some information from the household-level
> 	## dataset for use in plotting.
> 	##  - the village number
> 	##  - a vector of the unique HH IDs
> 	##  - the maximum number of model run years
> 	##  - the maximum wealth among all households
> 	##*************************************************
> 	villnum <- mean(hhstats$V84ID)
> 	uniq.hh.ids <- unique(hhstats$HHID00)
> 	max.yr <- max(hhstats$Year)
> 	max.wlth <- max(hhstats$Wealth)
> 
> 	##*************************************************
> 	## Extract out the vars needed for the individual
> 	## household line graph
> 	## Vars: Year, HHID00, Wealth, Status
> 	##*************************************************
> 	hh.wealth <- hhstats[,c("Year","HHID00","Wealth","Status")]
> 	hh.wealth.pos <- hh.wealth[hh.wealth$Wealth >= 0,]
> 	hh.wealth.plot <- hh.wealth.pos[hh.wealth.pos$Status == 0 |
> hh.wealth.pos$Status == 1,]
> 
> 	##*************************************************
> 	## Get the summary statistics by year for Wealth
> 	##*************************************************
> 	## Get a list of unique years for iterating
> 	unqyrlist <- unique(hh.wealth.plot$Year)
> 
> 	## Determine the divisor for the quantiles
> 	div.q <- 1.0 / n.quantiles
> 
> 	## Loop through years to extract summary statistics
> 	for (yr in min(unqyrlist):max(unqyrlist)) {
> 		# Get records for current year
> 		this.yr <- hh.wealth.plot[hh.wealth.plot$Year == yr,]
> 		# Calc summary statistics by statistic
> 		this.n <- dim(this.yr)[1]
> 		this.min <- min(this.yr$Wealth)
> 		this.max <- max(this.yr$Wealth)
> 		this.mean <- mean(this.yr$Wealth)
> 		this.med <- median(this.yr$Wealth)
> 		this.sd <- sd(this.yr$Wealth)
> 		this.ebneg <- this.mean-this.sd
> 		this.ebpos <- this.mean+this.sd
> 		this.sumstats <- c(yr, this.n, this.min, this.max, this.mean, 
> 					this.med, this.sd, this.ebneg, this.ebpos)
> 		# Convert vector to 1-row data frame
> 		this.df <- as.data.frame(t(as.matrix(this.sumstats)))
> 		colnames(this.df) <- c("Year", "Count", "Min", "Max", "Mean", "Median", 
> 						"SD", "EB.Low", "EB.High")
> 		# Now, calculate the specified quantiles for this year
> 		names(yr) <- "Year"
> 		this.q <- as.data.frame(t(as.matrix(c( 
> 				quantile(this.yr$Wealth, probs=seq(0, 1, div.q)), yr))))
> 		# Append the data frame to the output data frame
> 		if (yr == min(unqyrlist)) {
> 			hh.wealth.plot.ss <- this.df
> 			hh.wealth.quantiles <- this.q
> 		} else {
> 			hh.wealth.plot.ss <- rbind.data.frame(hh.wealth.plot.ss, this.df)
> 			hh.wealth.quantiles <- rbind.data.frame(hh.wealth.quantiles, this.q)
> 		}
> 	}
> 
> 	##*************************************************
> 	## Set up parameters for quantile plots
> 	##*************************************************
> 	q.names <- c("", "", "Terciles", "Quantiles", "Quintiles",
> 			"Sextiles", "Septiles", "Octiles", "Noniles", "Deciles")
> 	q.labs <- c("1st", "2nd", "3rd", "4th", "5th", "6th", "7th", "8th", "9th")
> 	# Determine if median will be plotted
> 	if (n.quantiles %% 2) plot.med <- FALSE else plot.med <- TRUE
> 	# Determine which non-median quantile columns will be plotted
> 	if (n.quantiles %% 2) {			# If the number of quantiles is odd
> 		cols.q <- c(2:n.quantiles)
> 	} else {					# If the number of quantiles is even
> 		cols.q <- c(2:(n.quantiles/2), (2+(n.quantiles/2)):n.quantiles)
> 		col.med <- (n.quantiles/2) + 1
> }
> 
> 	##*************************************************
> 	## Set up plotting parameters for the summary
> 	## statistics graph
> 	##*************************************************
> 	# Set y axis limits
> 	ylim.min <- min(hh.wealth.plot.ss)
> 	ylim.max <- max(hh.wealth.plot.ss)
> 	# Set title
> 	ttl.ss <- paste("Summary Statistics of Household Wealth Change Over Time\n
> (Village", 
> 		villnum, ")", sep="")
> 	# Set legend based on arguments
> 	leg.txt.ss <- c("Mean", "Min", "Max", "Error Bars", "# of HHs")
> 	if (err.bars == TRUE & n.quantiles == 0) {
> 		leg.txt.ss <- c("Mean", "Min", "Max", "Error Bars", "# of HHs")
> 		leg.lty.ss <- c(1,2,4,5,0)
> 		leg.lwd.ss <- c(2,1,1,1,0)
> 		leg.pch.ss <- c(-1,-1,-1,-1,16)
> 		leg.col.ss <- c("black","darkolivegreen4","chartreuse4","red","blue")
> 	} else if (err.bars == FALSE & n.quantiles >= 3) {
> 		if (n.quantiles %% 2) {				# Odd number of quantiles
> 			leg.txt.ss <- c("Mean", "Min", "Max", q.names[n.quantiles], "# of HHs")
> 			leg.lty.ss <- c(1,2,4,3,0)
> 			leg.lwd.ss <- c(2,1,1,1,0)
> 			leg.pch.ss <- c(-1,-1,-1,-1,16)
> 			leg.col.ss <- c("black","darkolivegreen4","chartreuse4","orange","blue")
> 		} else {						# Even number of quantiles
> 			leg.txt.ss <- c("Mean", "Min", "Max", "Median", q.names[n.quantiles], 
> 						"# of HHs")
> 			leg.lty.ss <- c(1,2,4,3,3,0)
> 			leg.lwd.ss <- c(2,1,1,2,1,0)
> 			leg.pch.ss <- c(-1,-1,-1,-1,-1,16)
> 			leg.col.ss <- c("black", "darkolivegreen4", "chartreuse4", "orange", 
> 						"orange", "blue")
> 		}
> 	} else if (err.bars == TRUE & n.quantiles >= 3) {
> 		if (n.quantiles %% 2) {				# Odd number of quantiles
> 			leg.txt.ss <- c("Mean", "Min", "Max", "Error Bars", q.names[n.quantiles], 
> 						"# of HHs")
> 			leg.lty.ss <- c(1,2,4,5,3,0)
> 			leg.lwd.ss <- c(2,1,1,1,1,0)
> 			leg.pch.ss <- c(-1,-1,-1,-1,-1,16)
> 			leg.col.ss <- c("black", "darkolivegreen4", "chartreuse4", "red",
> "orange",
> 						"blue")
> 		} else {						# Even number of quantiles
> 			leg.txt.ss <- c("Mean", "Min", "Max", "Error Bars", "Median", 
> 						q.names[n.quantiles], "# of HHs")
> 			leg.lty.ss <- c(1,2,4,5,3,3,0)
> 			leg.lwd.ss <- c(2,1,1,1,2,1,0)
> 			leg.pch.ss <- c(-1,-1,-1,-1,-1,-1,16)
> 			leg.col.ss <- c("black", "darkolivegreen4", "chartreuse4", "red",
> "orange",
> 						"orange","blue")
> 		}
> 	} else {
> 		leg.txt.ss <- c("Mean", "Min", "Max", "# of HHs")
> 		leg.lty.ss <- c(1,2,4,0)
> 		leg.lwd.ss <- c(2,1,1,0)
> 		leg.pch.ss <- c(-1,-1,-1,16)
> 		leg.col.ss <- c("black", "darkolivegreen4", "chartreuse4", "blue")
> 	}
> 
> 
> 	##*************************************************
> 	## Set up vector of possible colors for the lines
> 	##*************************************************
> 	colorset <- c(3:12, 26:62, 67:79, 81, 83:137, 139, 142:151)
> 
> 	##*************************************************
> 	## Set up plotting parameters for the individual
> 	## household graph
> 	##*************************************************
> 	## Create a vector of colors from the colorset
> 	## above, one for every HHID00
> 	colors.id <- sample(colorset, length(uniq.hh.ids), replace=TRUE)
> 	## Other parameters
> 	ttl.hh <- paste("Change in Household Wealth Over Time\n (Village", 
> 		villnum, ")", sep="")
> 	leg.txt.hh <- c("Old Households", "Split Households")
> 
> 	##*************************************************
> 	## Plot household-level summary statistics
> 	##*************************************************
> 	png(filename=output.png.wlthss, width=10, height=7, units="in", res=300)
> 
> 	## Set initial plot with mean
> 	plot(hh.wealth.plot.ss$Year,		# x var
> 		hh.wealth.plot.ss$Mean,		# y var (MEAN)
> 		type="l",				# line graph
> 		xlim=c(0,max.yr),			# x-axis limits
> 		ylim=c(ylim.min, ylim.max),	# y-axis limits
> 		lty=1,				# solid line
> 		lwd=2,				# line thickness
> 		xlab="",
> 		ylab="Wealth",			# y-axis label
> 		main=ttl.ss)
> 	## Add MIN
> 	lines(hh.wealth.plot.ss$Year,		# x var
> 		hh.wealth.plot.ss$Min,		# y var (MIN)
> 		type="l",				# line graph
> 		col="darkolivegreen4",
> 		lty=2)
> 	## Add MAX
> 	lines(hh.wealth.plot.ss$Year,		# x var
> 		hh.wealth.plot.ss$Max,		# y var (MAX)
> 		type="l",				# line graph
> 		col="chartreuse4",
> 		lty=4)
> 
> `	## Add ERROR BARS if Argument 'err.bars' is TRUE
> 	if (err.bars == TRUE) {
> 		## Add LOW ERROR BAR
> 		lines(hh.wealth.plot.ss$Year,			# x var
> 			hh.wealth.plot.ss$EB.Low,		# y var (EB LOW)
> 			type="l",					# line graph
> 			col="red",
> 			lty=3)
> 		## Add HIGH ERROR BAR
> 		lines(hh.wealth.plot.ss$Year,			# x var
> 			hh.wealth.plot.ss$EB.High,		# y var (EB HIGH)
> 			type="l",					# line graph
> 			col="red",
> 			lty=3)
> 	}
> 	## Add QUANTILES if Argument 'n.quantiles' is >= 3
> 	if (n.quantiles >= 3) {
> 		# Cycle through column numbers and draw quantile lines
> 		for (qcol in 1:length(cols.q)) {
> 			lines(hh.wealth.quantiles$Year,	# Plot quantile lines
> 				hh.wealth.quantiles[,cols.q[qcol]],
> 				type="l",
> 				col="orange",
> 				lty=3)
> 			}
> 		# Add MEDIAN line
> 		if (plot.med == TRUE) {
> 			lines(hh.wealth.quantiles$Year,	# Plot median
> 				hh.wealth.quantiles[,col.med],
> 				type="l",
> 				col="orange",
> 				lty=3,
> 				lwd=2)
> 		}
> 	}
> 	## Add COUNT
> 	points(hh.wealth.plot.ss$Year,	# x var
> 		hh.wealth.plot.ss$Count,	# y var (COUNT)
> 		type="p",				# line graph
> 		pch=16,
> 		col="blue",
> 		cex=0.5)
> 	## Add LEGEND
> 	legend(x="topright",
> 		leg.txt.ss,
> 		lty=leg.lty.ss,
> 		lwd=leg.lwd.ss,
> 		pch=leg.pch.ss,
> 		col=leg.col.ss,
> 		cex=1)
> 
> 	dev.off()
> 
> 
> 	##*************************************************
> 	## Plot wealth for individual households
> 	##*************************************************
> 	png(filename=output.png.wlth, width=10, height=7, units="in", res=300)
> 
> 	## Create an empty plot
> 	if (log.plot == FALSE) {
> 		plot(hh.wealth.plot$Year, hh.wealth.plot$Wealth,
> 			type="n",
> 			xlim=c(0,max.yr),
> 			main=ttl.hh,
> 			xlab="",
> 			ylab="Wealth")
> 	} else {
> 		plot(hh.wealth.plot$Year, hh.wealth.plot$Wealth,
> 			log="y",
> 			type="n",
> 			xlim=c(0,max.yr),
> 			main=ttl.hh,
> 			xlab="",
> 			ylab="Wealth (log scale)")
> 	}
> 
> 	#legend(x=leg.x.coord, y=leg.y.coord, 	# Sets the location for the legend
> 	legend(x="topright",
> 		leg.txt.hh, 				# text in the legent
> 		col=c("red", "red"), 			# sets the line colors in the legend
> 		lty=c(1,3), 				# draws lines
> 		lwd=c(1,1), 				# sets line thickness
> 	#	bty="n", 					# no border on the legend
> 		ncol=2, 					# makes it a 2-column legend
> 		cex=0.8)					# sets the legend text size
> 
> 	## Loop through IDs and add a line for each
> 	for (id in 1:length(uniq.hh.ids)) {
> 		## Get the current HH ID
> 		this.id <- uniq.hh.ids[id]
> 
> 		## Extract the records for the current ID
> 		this.sub <- hh.wealth.plot[hh.wealth.plot$HHID00 == this.id,]
> 
> 		if (dim(this.sub)[1] > 0) {
> 
> 			## Set line type
> 			if (mean(this.sub$Status) == 0) {
> 				ltype <- 1
> 			} else {
> 				ltype <- 3
> 			}
> 
> 			## Add the line for this ID
> 			lines(this.sub$Year, this.sub$Wealth,
> 				type="l", 
> 				col= colors.id[id],
> 				lwd=1,
> 				lty=ltype)
> 		}
> 
> 	}
> 
> 	dev.off()
> 
> }