Some R Code

DataPlotting.R

# Import necessary packages
library(xts);
library(timeDate);
require(Hmisc);
library(ggplot2);
library(scales);
library(reshape2);
library(gridExtra);
library(grid);

# Set working directory
setwd("/Users/Felix/Documents/University/Maastricht University/Master Thesis/")

# Import code
source("Code/R/Library/additionalFunctions.R")		# We require the color generator

# Receives an xts object with market and model spreads
genericLinePlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- max(na.exclude(ts))
	if(yLimit > 1) {
		yLimit <- round(yLimit + 0.05 * yLimit, -1)
	} else {
		yLimit <- round(yLimit + 0.05 * yLimit, 2)
	}
	
	yMin <- min(na.exclude(ts))
	if(yMin > 0) {
		yMin <- 0
	} else {
		if(yMin < -1) {
			yMin <- round(yMin - 0.05 * yLimit, -1)
		} else {
			yMin <- round(yMin - 0.05 * yLimit, 2)
		}
	}
	
	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- ""
	}
	
	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}
	
	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))
	colnames(data)[1] <- c("Date")
	
	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		colors <- colorPaletteGenerator(length(columnNames))
	}
	
	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)
	
	data <- melt(data, id = "Date")

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
			data, 
			aes(
				x = Date,
				y = value,
				linetype = variable,
				colour = variable,
				size = variable
			)
		) +
		geom_line() +
		labs(x = "", y = yLabel) +
		scale_linetype_manual(
			values = lineStyles,
			labels = columnNames
		) +
		scale_colour_manual(
			values = colors,
			labels = columnNames
		) +
		scale_size_manual(
			values = lineThickness,
			labels = columnNames
		) +
		scale_x_date(
			breaks = date_breaks("2 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		# scale_y_continuous(
		# 	breaks = seq(0, 70, 10),
		#   labels = c(seq(0, 60, 10), "  70")
		# ) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0,0,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank()
		)

	
	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}
	
	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
		                    		labels=legendTitles
		)
	}
	
	# Return plot
	return(p)
}

genericLinePlotWrapper <- function(ts, fileName, legend, colors, ar = c(2,1), title = "", yLabel = "") {
		
		# Filename
		fileName <- paste("Latex/Images/", fileName, ".pdf", sep = "")
		
		if(missing(colors)) {
			plotResult <- genericLinePlot(ts, legend = TRUE, yLabel = yLabel, title = title, ar = ar)
		} else {
			plotResult <- genericLinePlot(ts, legend = TRUE, yLabel = yLabel, colors = colors, title = title, ar = ar)	
		}
		
		# Start PDF devide
		pdf(
					file = fileName,
					width = 6.2,
					height = 2
		)
		
		# Push new viewport containing a grid
		pushViewport(
			viewport(
				layout = grid.layout(
					nrow = 1,
					ncol = 1,
					widths = unit(15, "cm"),
					heights = unit(1, "npc")
				)
			)
		)

		# Add the plots to the viewport's grid
		pushViewport(viewport(layout.pos.col = 1, layout.pos.row = 1))
		print(plotResult, vp = current.viewport())
		
		# Turn off graphics device
		dev.off()
}

multiLinePlotWrapper <- function(tsList, fileName, yLabel, grid, colors, titles, legendTitles) {	
	# Graphics driver and plot size setup
	fileName <- paste("Latex/Images/", fileName, ".pdf", sep = "")
	
	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		numberOfColors <- 0
		for(i in 1:length(tsList)) {
			numberOfColors <- max(numberOfColors, ncol(tsList[[i]]))
		}
		colors <- colorPaletteGenerator(numberOfColors)
	}
	
	# Start PDF devide
	pdf(
				file = fileName,
				width = 6.2,
				height = 5.5
	)
	
	if(missing(yLabel)) {
		yLabel = ""
	}
	
	plots <- list()
	
	# Build plot with corresponding titles
	if(missing(titles)) {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericLinePlot(tsList[[i]], yLabel = yLabel, TRUE, colors)
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericLinePlot(tsList[[i]], yLabel = yLabel, TRUE, colors, legendTitles = legendTitles)
			}
		}
	} else {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericLinePlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i])
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericLinePlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i], legendTitles = legendTitles)
			}
		}
	}
	
	# Extract legend from most recent plot
	tmp <- ggplot_gtable(ggplot_build(plots[[1]]))
	leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
	legend <- tmp$grobs[[leg]]
	
	# Remove legends from plots
	for(i in 1:length(plots)) {
		plots[[i]] <- plots[[i]] + opts(legend.position = "none")
	}
	
	# Push new viewport containing a grid
	pushViewport(
		viewport(
			layout = grid.layout(
				nrow = (length(plots) + 1),
				ncol = 1,
				widths = unit(15, "cm"),
				heights = unit(c(rep(1/length(plots) * 0.95, length(plots)), 0.05), "npc")
			)
		)
	)
	
	# Add the plots to the viewport's grid
	for(i in 1:length(plots)) {
		pushViewport(viewport(layout.pos.col = 1, layout.pos.row = i))
		print(plots[[i]], vp = current.viewport())
		upViewport()
	}
	
	# Paint the legend onto the final element of the grid
	pushViewport(viewport(layout.pos.col = 1, layout.pos.row = (length(plots) + 1)))
	gp <- gpar()
	gp$col <- rgb(0,0,0,0)
	gp$lex  <-  0
	grid.rect(gp = gp)
	grid.draw(legend)
	
	# Turn off graphics device
	dev.off()
}

# Receives an xts object with market and model spreads
genericBarPlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- max(na.exclude(ts))
	if(yLimit > 1) {
		yLimit <- round(yLimit + 0.1 * yLimit, -1)
	} else {
		yLimit <- round(yLimit + 0.1 * yLimit, 2)
	}

	yMin <- min(na.exclude(ts))
	if(yMin > 0) {
		yMin <- 0
	} else {
		if(yMin < -1) {
			yMin <- round(yMin - 0.1 * yLimit, -1)
		} else {
			yMin <- round(yMin - 0.1 * yLimit, 2)
		}
	}

	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- ""
	}

	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}

	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))
	colnames(data)[1] <- c("Date")

	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		print("Generating colors.")
		colors <- colorPaletteGenerator(length(columnNames))
	}

	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)

	data <- melt(data, id = "Date")

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
			data, 
			aes(
				x = Date,
				y = value,
				linetype = variable,
				fill = variable,
				size = variable
			)
		) +
		geom_bar(stat = "identity") +
		labs(x = "", y = yLabel) +
		scale_linetype_manual(
			values = lineStyles,
			labels = columnNames
		) +
		scale_fill_manual(
			values = colors,
			labels = columnNames
		) +
		scale_size_manual(
			values = lineThickness,
			labels = columnNames
		) +
		scale_x_date(
			breaks = date_breaks("4 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		# scale_y_continuous(
		# 	breaks = seq(0, 70, 10),
		#   labels = c(seq(0, 60, 10), "  70")
		# ) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0.3,0,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank()
		)


	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}

	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
														labels=legendTitles
		)
	}

	# Return plot
	return(p)
}

# Receives an xts object with market and model spreads
genericAreaPlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- max(na.exclude(ts))
	if(yLimit > 1) {
		yLimit <- round(yLimit + 0.1 * yLimit, -1)
	} else {
		yLimit <- round(yLimit + 0.1 * yLimit, 2)
	}

	yMin <- min(na.exclude(ts))
	if(yMin > 0) {
		yMin <- 0
	} else {
		if(yMin < -1) {
			yMin <- round(yMin - 0.1 * yLimit, -1)
		} else {
			yMin <- round(yMin - 0.1 * yLimit, 2)
		}
	}

	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- ""
	}

	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}

	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))
	colnames(data)[1] <- c("Date")

	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		print("Generating colors.")
		colors <- colorPaletteGenerator(length(columnNames))
	}

	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)
	
	data <- melt(data, id = "Date")

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
				data, 
				aes(
					x = Date,
					y = value,
					linetype = variable,
					fill = variable,
					size = variable,
					color = variable
				)
			) +
			geom_area(alpha = 0.5) +
			scale_fill_manual(
				values = colors,
				labels = columnNames
			) +
			scale_color_manual(
				values = colors,
				labels = columnNames
			) +
			scale_size_manual(
				values = 0.1,
				labels = columnNames
			) +
		labs(x = "", y = yLabel) +
		scale_x_date(
			breaks = date_breaks("4 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0.3,0,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank()
		)
	
	
	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}
	
	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
														labels=legendTitles
		)
	}

	# Return plot
	return(p)
}

# Receives an xts object with market and model spreads
genericScatterPlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- max(na.exclude(ts))
	if(yLimit > 1) {
		yLimit <- round(yLimit + 0.1 * yLimit, -1)
	} else {
		yLimit <- round(yLimit + 0.1 * yLimit, 2)
	}

	yMin <- min(na.exclude(ts))
	if(yMin > 0) {
		yMin <- 0
	} else {
		if(yMin < -1) {
			yMin <- round(yMin - 0.1 * yLimit, -1)
		} else {
			yMin <- round(yMin - 0.1 * yLimit, 2)
		}
	}
	
	# Ensure the right y axis limits for invertibility plots
	if(max(coredata(ts) == 1 | min(coredata(ts)) == 0)) {
		yMin <- -0.1
		yMax <- 1.1
	}

	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- NULL
	}

	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}

	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))
	colnames(data)[1] <- c("Date")

	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		print("Generating colors.")
		colors <- colorPaletteGenerator(length(columnNames))
	}

	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)

	data <- melt(data, id = "Date")

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
			data, 
			aes(
				x = Date,
				y = value,
				linetype = variable,
				color = variable,
				size = variable
			)
		) +
		geom_point(size = 1) +
		labs(x = NULL, y = yLabel) +
		scale_linetype_manual(
			values = lineStyles,
			labels = columnNames
		) +
		scale_colour_manual(
			values = colors,
			labels = columnNames
		) +
		scale_size_manual(
			values = lineThickness,
			labels = columnNames
		) +
		scale_x_date(
			breaks = date_breaks("4 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		scale_y_continuous(
			breaks = c(0, 1),
		  labels = c(0, 1)
		) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0.03,0.07,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank()
		)


	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}

	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
														labels=legendTitles
		)
	}

	# Return plot
	return(p)
}

# Receives an xts object with market and model spreads
statisticsRibbonPlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- max(na.exclude(ts))
	if(yLimit > 1) {
		yLimit <- round(yLimit + 0.05 * yLimit, -1)
	} else {
		yLimit <- round(yLimit + 0.05 * yLimit, 2)
	}
	
	yMin <- min(na.exclude(ts))
	if(yMin > 0) {
		yMin <- 0
	} else {
		if(yMin < -1) {
			yMin <- round(yMin - 0.05 * yLimit, -1)
		} else {
			yMin <- round(yMin - 0.05 * yLimit, 2)
		}
	}
	
	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- ""
	}
	
	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}

	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))

	colnames(data) <- c("Date", "Mean", "Q1", "Median", "Q3")

	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		print("Generating colors.")
		colors <- colorPaletteGenerator(length(columnNames))
	}

	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
			data, 
			aes(x = Date)
		) +
		geom_ribbon(aes(ymin = Q1, ymax = Q3, fill = "Quartile Range", alpha = "Quartile Range")) +
		geom_line(aes(y = Mean, color = "Mean", linetype = "Mean", size = "Mean")) +
		geom_line(aes(y = Median, colour = "Median", linetype = "Median", size = "Median")) +
		scale_fill_manual(
			values = c("#B5BFBC"),
			labels = c("Quartile Range")
		) +
		scale_alpha_manual(
			values = c(0.5),
			labels = c("Quartile Range")
		) +
		scale_size_manual(
			values = c(0.25, 0.25),
			labels = c("Mean", "Median")
		) +
		scale_linetype_manual(
			values = c(1, 2),
			labels = c("Mean", "Median")
		) +
		scale_color_manual(
			values = c("#B24057", "black"),
			labels = c("Mean", "Median")
		) +
		labs(x = NULL, y = yLabel) +
		scale_x_date(
			breaks = date_breaks("2 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0,0,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank(),
			legend.direction = "horizontal",
			legend.box = "horizontal"
		) +
		coord_equal(ratio = 1/1.4)

	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}

	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
														labels=legendTitles
		)
	}

	# Return plot
	return(p)
}

statisticsRibbonPlotWrapper <- function(ts, fileName, legend, colors, ar = c(2,1), title = "", yLabel = "") {
		
		# Filename
		fileName <- paste("Latex/Images/", fileName, ".pdf", sep = "")
		
		if(missing(colors)) {
			plotResult <- statisticsRibbonPlot(ts, legend = TRUE, yLabel = yLabel, title = title, ar = ar)
		} else {
			plotResult <- statisticsRibbonPlot(ts, legend = TRUE, yLabel = yLabel, colors = colors, title = title, ar = ar)	
		}
		
		# Start PDF devide
		pdf(
					file = fileName,
					width = 6.2,
					height = 2
		)
		
		# Push new viewport containing a grid
		pushViewport(
			viewport(
				layout = grid.layout(
					nrow = 1,
					ncol = 1,
					widths = unit(15, "cm"),
					heights = unit(1, "npc")
				)
			)
		)

		# Add the plots to the viewport's grid
		pushViewport(viewport(layout.pos.col = 1, layout.pos.row = 1))
		print(plotResult, vp = current.viewport())
		
		# Turn off graphics device
		dev.off()
}

multiStatisticsPlotWrapper <- function(tsList, fileName, yLabel, grid, colors, titles, legendTitles) {	
	# Graphics driver and plot size setup
	fileName <- paste("Latex/Images/", fileName, ".pdf", sep = "")
	
	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		numberOfColors <- 0
		for(i in 1:length(tsList)) {
			numberOfColors <- max(numberOfColors, ncol(tsList[[i]]))
		}
		colors <- colorPaletteGenerator(numberOfColors)
	}

	# Start PDF devide
	pdf(
				file = fileName,
				width = 6.2,
				height = 5.5
	)

	if(missing(yLabel)) {
		yLabel = ""
	}
	
	plots <- list()
	
	# Build plot with corresponding titles
	if(missing(titles)) {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- statisticsRibbonPlot(tsList[[i]], yLabel = yLabel, TRUE, colors)
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- statisticsRibbonPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, legendTitles = legendTitles)
			}
		}
	} else {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- statisticsRibbonPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i])
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- statisticsRibbonPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i], legendTitles = legendTitles)
			}
		}
	}
	
	# Extract legend from most recent plot
	tmp <- ggplot_gtable(ggplot_build(plots[[1]]))
	leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
	legend <- tmp$grobs[[leg]]
	
	# Remove legends from plots
	for(i in 1:length(plots)) {
		plots[[i]] <- plots[[i]] + opts(legend.position = "none")
	}
	
	# Push new viewport containing a grid
	pushViewport(
		viewport(
			layout = grid.layout(
				nrow = (length(plots) + 1),
				ncol = 1,
				widths = unit(15, "cm"),
				heights = unit(c(rep(1/length(plots) * 0.95, length(plots)), 0.05), "npc")
			)
		)
	)
	
	# Add the plots to the viewport's grid
	for(i in 1:length(plots)) {
		pushViewport(viewport(layout.pos.col = 1, layout.pos.row = i))
		print(plots[[i]], vp = current.viewport())
		upViewport()
	}
	
	# Paint the legend onto the final element of the grid
	pushViewport(viewport(layout.pos.col = 1, layout.pos.row = (length(plots) + 1)))
	gp <- gpar()
	gp$col <- rgb(0,0,0,0)
	gp$lex  <-  0
	grid.rect(gp = gp)
	grid.draw(legend)
	
	# Turn off graphics device
	dev.off()
}

# Receives an xts object with market and model spreads
genericStackedAreaPlot <- function(ts, legend, colors, title, yLabel, ar = c(1,1), legendTitles) {
	# Set y-axis upper limit
	yLimit <- 1.03
	yMin <- -0.03
	# Set dummy label
	if(missing(yLabel)) {
		yLabel <- ""
	}

	# Check if a title has been provided
	if(missing(title)) {
		title <- ""
	}

	# Convert xts object to data.frame
	data <- data.frame(index(ts), coredata(ts))
	colnames(data)[1] <- c("Date")

	# Backup column names for legend
	columnNames <- colnames(ts)

	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		print("Generating colors.")
		colors <- colorPaletteGenerator(length(columnNames))
	}

	# Clean up column names
	breakBackups <- columnNames
	columnNames <- sub("X", "", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub(".", " ", columnNames, ignore.case = FALSE, fixed = TRUE)
	columnNames <- sub("_", " ", columnNames, ignore.case = FALSE, fixed = TRUE)
	
	data <- melt(data, id = "Date")

	# Data plotting parameters
	lineThickness <- 0.35
	lineThickness <- rep(lineThickness, length(colors))
	lineStyles <- c(1:length(colors))

	# Grid parameters
	refLineType <- 2
	refLineWidth <- 0.2
	refLineColor <- "#c1c0bd"

	# Create basic plot
	p <- ggplot(
				data, 
				aes(
					x = Date,
					y = value,
					# linetype = variable,
					fill = variable,
					size = variable,
					color = variable,
					alpha = variable
				)
			) +
			geom_area(position = 'stack') +
			scale_fill_manual(
				values = colors,
				labels = columnNames
			) +
			scale_alpha_manual(
				values = rep(0.6, length(columnNames)),
				labels = columnNames
			) +
			scale_color_manual(
				values = colors,
				labels = columnNames
			) +
			scale_size_manual(
				values = rep(0.1, length(columnNames)),
				labels = columnNames
			) +
		labs(x = "", y = yLabel) +
		scale_x_date(
			breaks = date_breaks("2 months"),
			labels = date_format("%b-%y"),
			expand = c(0.01,0.01)
		) +
		coord_cartesian(ylim=c(yMin, yLimit)) +
		opts(
			plot.title = theme_text(size = 7 * 1.2, face = "bold", vjust = 1),
			title = title,
			plot.background = theme_blank(),
			plot.margin = unit(c(0,0.3,0,0), "cm"),
			panel.background = theme_rect(fill = "white"),
			panel.margin = unit(c(0,0,0,0), "cm"),
			panel.grid.minor = theme_line(colour = refLineColor, size = refLineWidth/2, linetype = refLineType),
			panel.grid.major = theme_line(colour = refLineColor, size = refLineWidth, linetype = refLineType),
			panel.border = theme_rect(colour = "#333333", size = 0.8),
			axis.line = theme_segment(colour = "#333333", size = 0.3),
			axis.ticks = theme_segment(colour = "#333333", size = 0.4),
			axis.ticks.length = unit(0.05, "cm"),
			axis.text.x = theme_text(family = "Helvetica", size = 7, colour = "#333333"),
			axis.text.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", hjust = 1),
			axis.title.y = theme_text(family = "Helvetica", size = 7, colour = "#333333", angle = 90),
			legend.position = "bottom",
			legend.height = unit(0.5, "cm"),
			legend.background = theme_rect(fill = "#EEEEEE", colour = "#999999"),
			legend.key = theme_rect(colour = NA),
			legend.key.height = unit(0.1, "cm"),
			legend.key.width = unit(0.7, "cm"),
			legend.text = theme_text(family = "Helvetica", size = 6, colour = "black", lineheight = 0.8),
			legend.title = theme_blank()
		)
	
	
	# Correct the legend entries with clean column Names and return plot
	if(legend == FALSE) {
		p <- p + opts(legend.position = "none")
	}
	
	if(!missing(legendTitles)){
		p <- p + scale_fill_hue('my legend', 
														breaks=columnNames,
														labels=legendTitles
		)
	}

	# Return plot
	return(p)
}

multiStackedAreaPlotWrapper <- function(tsList, fileName, yLabel, grid, colors, titles, legendTitles) {	
	# Graphics driver and plot size setup
	fileName <- paste("Latex/Images/", fileName, ".pdf", sep = "")
	
	# Check if color palette has been passed and generate one if necessary
	if(missing(colors)) {
		numberOfColors <- 0
		for(i in 1:length(tsList)) {
			numberOfColors <- max(numberOfColors, ncol(tsList[[i]]))
		}
		colors <- colorPaletteGenerator(numberOfColors)
	}
	
	# Start PDF devide
	pdf(
				file = fileName,
				width = 6.2,
				height = 5.5
	)
	
	if(missing(yLabel)) {
		yLabel = ""
	}
	
	plots <- list()
	
	# Build plot with corresponding titles
	if(missing(titles)) {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericStackedAreaPlot(tsList[[i]], yLabel = yLabel, TRUE, colors)
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericStackedAreaPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, legendTitles = legendTitles)
			}
		}
	} else {
		if(missing(legendTitles)){
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericStackedAreaPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i])
			}
		} else {
			for(i in 1:length(tsList)) {
					plots[[i]] <- genericStackedAreaPlot(tsList[[i]], yLabel = yLabel, TRUE, colors, titles[i], legendTitles = legendTitles)
			}
		}
	}
	
	# Extract legend from most recent plot
	tmp <- ggplot_gtable(ggplot_build(plots[[1]]))
	leg <- which(sapply(tmp$grobs, function(x) x$name) == "guide-box")
	legend <- tmp$grobs[[leg]]
	
	# Remove legends from plots
	for(i in 1:length(plots)) {
		plots[[i]] <- plots[[i]] + opts(legend.position = "none")
	}
	
	# Push new viewport containing a grid
	pushViewport(
		viewport(
			layout = grid.layout(
				nrow = (length(plots) + 1),
				ncol = 1,
				widths = unit(15, "cm"),
				heights = unit(c(rep(1/length(plots) * 0.95, length(plots)), 0.05), "npc")
			)
		)
	)
	
	# Add the plots to the viewport's grid
	for(i in 1:length(plots)) {
		pushViewport(viewport(layout.pos.col = 1, layout.pos.row = i))
		print(plots[[i]], vp = current.viewport())
		upViewport()
	}
	
	# Paint the legend onto the final element of the grid
	pushViewport(viewport(layout.pos.col = 1, layout.pos.row = (length(plots) + 1)))
	gp <- gpar()
	gp$col <- rgb(0,0,0,0)
	gp$lex  <-  0
	grid.rect(gp = gp)
	grid.draw(legend)
	
	# Turn off graphics device
	dev.off()
}