--- /dev/null
+#-------------------------------------------------------------------------------
+# Copyright (c) 2012 University of Illinois, NCSA.
+# All rights reserved. This program and the accompanying materials
+# are made available under the terms of the
+# University of Illinois/NCSA Open Source License
+# which accompanies this distribution, and is available at
+# http://opensource.ncsa.illinois.edu/license.html
+#-------------------------------------------------------------------------------
+##--------------------------------------------------------------------------------------------------#
+##' Variable-width (dagonally cut) histogram
+##'
+##'
+##' When constructing a histogram, it is common to make all bars the same width.
+##' One could also choose to make them all have the same area.
+##' These two options have complementary strengths and weaknesses; the equal-width histogram oversmooths in regions of high density, and is poor at identifying sharp peaks; the equal-area histogram oversmooths in regions of low density, and so does not identify outliers.
+##' We describe a compromise approach which avoids both of these defects. We regard the histogram as an exploratory device, rather than as an estimate of a density.
+##' @name dhist
+##' @title Diagonally Cut Histogram
+##' @param x is a numeric vector (the data)
+##' @param a is the scaling factor, default is 5 * IQR
+##' @param nbins is the number of bins, default is assigned by the Stuges method
+##' @param rx is the range used for the left of the left-most bin to the right of the right-most bin
+##' @param eps used to set artificial bound on min width / max height of bins as described in Denby and Mallows (2009) on page 24.
+##' @param xlab is label for the x axis
+##' @param plot = TRUE produces the plot, FALSE returns the heights, breaks and counts
+##' @param lab.spikes = TRUE labels the \% of data in the spikes
+##' @return list with two elements, heights of length n and breaks of length n+1 indicating the heights and break points of the histogram bars.
+##' @author Lorraine Denby, Colin Mallows
+##' @references Lorraine Denby, Colin Mallows. Journal of Computational and Graphical Statistics. March 1, 2009, 18(1): 21-31. doi:10.1198/jcgs.2009.0002.
+dhist <- function(x, a=5*iqr(x),
+ nbins=nclass.Sturges(x), rx = range(x,na.rm = TRUE),
+ eps=.15, xlab = "x", plot = TRUE,lab.spikes = TRUE)
+{
+
+ if(is.character(nbins))
+ nbins <- switch(casefold(nbins),
+ sturges = nclass.Sturges(x),
+ fd = nclass.FD(x),
+ scott = nclass.scott(x),
+ stop("Nclass method not recognized"))
+ else if(is.function(nbins))
+ nbins <- nbins(x)
+
+ x <- sort(x[!is.na(x)])
+ if(a == 0)
+ a <- diff(range(x))/100000000
+ if(a != 0 & a != Inf) {
+ n <- length(x)
+ h <- (rx[2] + a - rx[1])/nbins
+ ybr <- rx[1] + h * (0:nbins)
+ yupper <- x + (a * (1:n))/n
+ # upper and lower corners in the ecdf
+ ylower <- yupper - a/n
+ #
+ cmtx <- cbind(cut(yupper, breaks = ybr), cut(yupper, breaks =
+ ybr, left.include = TRUE), cut(ylower, breaks = ybr),
+ cut(ylower, breaks = ybr, left.include = TRUE))
+ cmtx[1, 3] <- cmtx[1, 4] <- 1
+ # to replace NAs when default r is used
+ cmtx[n, 1] <- cmtx[n, 2] <- nbins
+ #
+ #checksum <- apply(cmtx, 1, sum) %% 4
+ checksum <- (cmtx[, 1] + cmtx[, 2] + cmtx[, 3] + cmtx[, 4]) %%
+ 4
+ # will be 2 for obs. that straddle two bins
+ straddlers <- (1:n)[checksum == 2]
+ # to allow for zero counts
+ if(length(straddlers) > 0) {
+ counts <- table(c(1:nbins, cmtx[ - straddlers, 1]))
+ } else {
+ counts <- table(c(1:nbins, cmtx[, 1]))
+ }
+ counts <- counts - 1
+ #
+ if(length(straddlers) > 0) {
+ for(i in straddlers) {
+ binno <- cmtx[i, 1]
+ theta <- ((yupper[i] - ybr[binno]) * n)/a
+ counts[binno - 1] <- counts[binno - 1] + (
+ 1 - theta)
+ counts[binno] <- counts[binno] + theta
+ }
+ }
+ xbr <- ybr
+ xbr[-1] <- ybr[-1] - (a * cumsum(counts))/n
+ spike<-eps*diff(rx)/nbins
+ flag.vec<-c(diff(xbr)<spike,F)
+ if ( sum(abs(diff(xbr))<=spike) >1) {
+ xbr.new<-xbr
+ counts.new<-counts
+ diff.xbr<-abs(diff(xbr))
+ amt.spike<-diff.xbr[length(diff.xbr)]
+ for (i in rev(2:length(diff.xbr))) {
+ if (diff.xbr[i-1] <= spike&diff.xbr[i] <= spike &
+ !is.na(diff.xbr[i])) {
+ amt.spike <- amt.spike+diff.xbr[i-1]
+ counts.new[i-1] <- counts.new[i-1]+counts.new[i]
+ xbr.new[i] <- NA
+ counts.new[i] <- NA
+ flag.vec[i-1] <- T
+ }
+ else amt.spike<-diff.xbr[i-1]
+ }
+ flag.vec<-flag.vec[!is.na(xbr.new)]
+ flag.vec<-flag.vec[-length(flag.vec)]
+ counts<-counts.new[!is.na(counts.new)]
+ xbr<-xbr.new[!is.na(xbr.new)]
+
+ }
+ else flag.vec<-flag.vec[-length(flag.vec)]
+ widths <- abs(diff(xbr))
+ ## N.B. argument "widths" in barplot must be xbr
+ heights <- counts/widths
+ }
+ bin.size <- length(x)/nbins
+ cut.pt <- unique(c(min(x) - abs(min(x))/1000,
+ approx(seq(length(x)), x, (1:(nbins - 1)) * bin.size, rule = 2)$y, max(x)))
+ aa <- hist(x, breaks = cut.pt, plot = FALSE, probability = TRUE)
+ if(a == Inf) {
+ heights <- aa$counts
+ xbr <- aa$breaks
+ }
+ amt.height<-3
+ q75<-quantile(heights,.75)
+ if (sum(flag.vec)!=0) {
+ amt<-max(heights[!flag.vec])
+ ylim.height<-amt*amt.height
+ ind.h<-flag.vec&heights> ylim.height
+ flag.vec[heights<ylim.height*(amt.height-1)/amt.height]<-F
+ heights[ind.h] <- ylim.height
+ }
+ amt.txt<-0
+ end.y<-(-10000)
+ if(plot) {
+ barplot(heights, abs(diff(xbr)), space = 0, density = -1, xlab =
+ xlab, plot = TRUE, xaxt = "n",yaxt='n')
+ at <- pretty(xbr)
+ axis(1, at = at - xbr[1], labels = as.character(at))
+ if (lab.spikes) {
+ if (sum(flag.vec)>=1) {
+ usr<-par('usr')
+ for ( i in seq(length(xbr)-1)) {
+ if (!flag.vec[i]) {
+ amt.txt<-0
+ if (xbr[i]-xbr[1]<end.y) amt.txt<-1
+ }
+ else {
+ amt.txt<-amt.txt+1
+ end.y<-xbr[i]-xbr[1]+3*par('cxy')[1]
+ }
+ if (flag.vec[i]) {
+ txt<-paste(' ',format(round(counts[i]/
+ sum(counts)*100)),'%',sep='')
+ par(xpd = TRUE)
+ text(xbr[i+1]-xbr[1],ylim.height-par('cxy')[2]*(amt.txt-1),txt, adj=0)
+ }}
+ }
+ else print('no spikes or more than one spike')
+ }
+ invisible(list(heights = heights, xbr = xbr))
+ }
+ else {
+ return(list(heights = heights, xbr = xbr,counts=counts))
+ }
+}
+#==================================================================================================#
+
+
+#--------------------------------------------------------------------------------------------------#
+##' Calculate interquartile range
+##'
+##' Calculates the 25th and 75th quantiles given a vector x; used in function \link{dhist}.
+##' @name iqr
+##' @title Interquartile range
+##' @param x vector
+##' @return numeric vector of length 2, with the 25th and 75th quantiles of input vector x.
+iqr <- function(x){
+ return(diff(quantile(x, c(0.25, 0.75), na.rm = TRUE)))
+}
+##==================================================================================================#
+
+##--------------------------------------------------------------------------------------------------#
+##' Creates empty ggplot object
+##'
+##' An empty base plot to which layers created by other functions
+##' (\code{\link{plot.data}}, \code{\link{plot.prior.density}},
+##' \code{\link{plot.posterior.density}}) can be added.
+##' @name create.base.plot
+##' @title Create Base Plot
+##' @return empty ggplot object
+##' @export
+##' @author David LeBauer
+create.base.plot <- function() {
+ base.plot <- ggplot()
+ return(base.plot)
+}
+#==================================================================================================#
+
+
+
+
+##--------------------------------------------------------------------------------------------------#
+##' Add data to an existing plot or create a new one from \code{\link{create.base.plot}}
+##'
+##' Used to add raw data or summary statistics to the plot of a distribution.
+##' The height of Y is arbitrary, and can be set to optimize visualization.
+##' If SE estimates are available, tehse wil be plotted
+##' @name plot.data
+##' @title Add data to plot
+##' @param trait.data data to be plotted
+##' @param base.plot a ggplot object (grob),
+##' created by \code{\link{create.base.plot}} if none provided
+##' @param ymax maximum height of y
+##' @seealso \code{\link{create.base.plot}}
+##' @return updated plot object
+##' @author David LeBauer
+##' @export
+##' @examples
+##' \dontrun{plot.data(data.frame(Y = c(1, 2), se = c(1,2)), base.plot = NULL, ymax = 10)}
+plot.data <- function(trait.data, base.plot = NULL, ymax, color = 'black') {
+ if(is.null(base.plot)) base.plot <- create.base.plot()
+ n.pts <- nrow(trait.data)
+ if(n.pts == 1){
+ ymax <- ymax/8
+ } else if (n.pts < 5) {
+ ymax <- ymax / 4
+ } else {
+ ymax <- ymax / 2
+ }
+ y.pts <- seq(0, ymax, length.out = 1 + n.pts)[-1]
+ plot.data <- data.frame(x = trait.data$Y,
+ y = y.pts,
+ se = trait.data$se,
+ control = !trait.data$trt == 1 & trait.data$ghs == 1)
+ new.plot <- base.plot +
+ geom_point(data = plot.data,
+ aes(x = x, y = y,
+ color = control)) +
+ geom_segment(data = plot.data,
+ aes(x = x - se, y = y, xend = x + se, yend = y,
+ color = control)) +
+ scale_color_manual(values = c('black', 'grey')) +
+ opts(legend_position = "none")
+ return(new.plot)
+}
+##==================================================================================================#
+
+
+#--------------------------------------------------------------------------------------------------#
+##' Add borders to .. content for \description{} (no empty lines) ..
+##'
+##' Has ggplot2 display only specified borders, e.g. ("L"-shaped) borders, rather than a rectangle or no border. Note that the order can be significant; for example, if you specify the L border option and then a theme, the theme settings will override the border option, so you need to specify the theme (if any) before the border option, as above.
+##' @name theme_border
+##' @title Theme border for plot
+##' @param type
+##' @param colour
+##' @param size
+##' @param linetype
+##' @return adds borders to ggplot as a side effect
+##' @author Rudolf Cardinal
+##' @author \url{ggplot2 google group}{https://groups.google.com/forum/?fromgroups#!topic/ggplot2/-ZjRE2OL8lE}
+##' @examples
+##' \dontrun{
+##' df = data.frame( x=c(1,2,3), y=c(4,5,6) )
+##' ggplot(data=df, aes(x=x, y=y)) + geom_point() + theme_bw() +
+##' opts(panel.border = theme_border(c("bottom","left")) )
+##' ggplot(data=df, aes(x=x, y=y)) + geom_point() + theme_bw() +
+##' opts(panel.border = theme_border(c("b","l")) )
+##' }
+theme_border <- function(type = c("left", "right", "bottom", "top",
+ "none"), colour = "black", size = 1, linetype = 1) {
+ type <- match.arg(type, several.ok=TRUE)
+ structure(
+ function(x = 0, y = 0, width = 1, height = 1, ...) {
+ xlist <- c()
+ ylist <- c()
+ idlist <- c()
+ if ("bottom" %in% type) { # bottom
+ xlist <- append(xlist, c(x, x+width))
+ ylist <- append(ylist, c(y, y))
+ idlist <- append(idlist, c(1,1))
+ }
+ if ("top" %in% type) { # top
+ xlist <- append(xlist, c(x, x+width))
+ ylist <- append(ylist, c(y+height, y+height))
+ idlist <- append(idlist, c(2,2))
+ }
+ if ("left" %in% type) { # left
+ xlist <- append(xlist, c(x, x))
+ ylist <- append(ylist, c(y, y+height))
+ idlist <- append(idlist, c(3,3))
+ }
+ if ("right" %in% type) { # right
+ xlist <- append(xlist, c(x+width, x+width))
+ ylist <- append(ylist, c(y, y+height))
+ idlist <- append(idlist, c(4,4))
+ }
+ polylineGrob(
+ x=xlist, y=ylist, id=idlist, ..., default.units = "npc",
+ gp=gpar(lwd=size, col=colour, lty=linetype),
+ )
+ },
+ class = "theme",
+ type = "box",
+ call = match.call()
+ )
+}
+#==================================================================================================#
+
+
+####################################################################################################
+### EOF. End of R script file.
+####################################################################################################
