[Returnanalytics-commits] r2735 - pkg/PortfolioAnalytics/R

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Wed Aug 7 00:18:06 CEST 2013


Author: rossbennett34
Date: 2013-08-07 00:18:06 +0200 (Wed, 07 Aug 2013)
New Revision: 2735

Added:
   pkg/PortfolioAnalytics/R/charts.PSO.R
Log:
adding chart methods for pso optimization method

Added: pkg/PortfolioAnalytics/R/charts.PSO.R
===================================================================
--- pkg/PortfolioAnalytics/R/charts.PSO.R	                        (rev 0)
+++ pkg/PortfolioAnalytics/R/charts.PSO.R	2013-08-06 22:18:06 UTC (rev 2735)
@@ -0,0 +1,165 @@
+#' boxplot of the weights in the portfolio
+#' 
+#' @param pso object created by \code{\link{optimize.portfolio}}
+#' @param neighbors set of 'neighbor' portfolios to overplot
+#' @param las numeric in \{0,1,2,3\}; the style of axis labels
+#'       \describe{
+#'         \item{0:}{always parallel to the axis [\emph{default}],}
+#'         \item{1:}{always horizontal,}
+#'         \item{2:}{always perpendicular to the axis,}
+#'         \item{3:}{always vertical.}
+#'       }
+#' @param xlab a title for the x axis: see \code{\link{title}}
+#' @param cex.lab The magnification to be used for x and y labels relative to the current setting of \code{cex}
+#' @param cex.axis The magnification to be used for axis annotation relative to the current setting of \code{cex}
+#' @param element.color color for the default plot lines
+#' @param ... any other passthru parameters 
+#' @param main an overall title for the plot: see \code{\link{title}}
+#' @seealso \code{\link{optimize.portfolio}}
+#' @author Ross Bennett
+#' @export
+chart.Weights.pso <- function(pso, neighbors = NULL, ..., main="Weights", las = 3, xlab=NULL, cex.lab = 1, element.color = "darkgray", cex.axis=0.8){
+  
+  if(!inherits(pso, "optimize.portfolio.pso")) stop("pso must be of class 'optimize.portfolio.pso'")
+  
+  columnnames = names(pso$weights)
+  numassets = length(columnnames)
+  
+  constraints <- get_constraints(pso$portfolio)
+  
+  if(is.null(xlab))
+    minmargin = 3
+  else
+    minmargin = 5
+  if(main=="") topmargin=1 else topmargin=4
+  if(las > 1) {# set the bottom border to accommodate labels
+    bottommargin = max(c(minmargin, (strwidth(columnnames,units="in"))/par("cin")[1])) * cex.lab
+    if(bottommargin > 10 ) {
+      bottommargin<-10
+      columnnames<-substr(columnnames,1,19)
+      # par(srt=45) #TODO figure out how to use text() and srt to rotate long labels
+    }
+  }
+  else {
+    bottommargin = minmargin
+  }
+  par(mar = c(bottommargin, 4, topmargin, 2) +.1)
+  plot(pso$weights, type="b", col="blue", axes=FALSE, xlab='', ylim=c(0,max(constraints$max)), ylab="Weights", main=main, pch=16, ...)
+  points(constraints$min, type="b", col="darkgray", lty="solid", lwd=2, pch=24)
+  points(constraints$max, type="b", col="darkgray", lty="solid", lwd=2, pch=25)
+  #     if(!is.null(neighbors)){ 
+  #         if(is.vector(neighbors)){
+  #             xtract=extractStats(ROI)
+  #             weightcols<-grep('w\\.',colnames(xtract)) #need \\. to get the dot 
+  #             if(length(neighbors)==1){
+  #                 # overplot nearby portfolios defined by 'out'
+  #                 orderx = order(xtract[,"out"])
+  #                 subsetx = head(xtract[orderx,], n=neighbors)
+  #                 for(i in 1:neighbors) points(subsetx[i,weightcols], type="b", col="lightblue")
+  #             } else{
+  #                 # assume we have a vector of portfolio numbers
+  #                 subsetx = xtract[neighbors,weightcols]
+  #                 for(i in 1:length(neighbors)) points(subsetx[i,], type="b", col="lightblue")
+  #             }      
+  #         }
+  #         if(is.matrix(neighbors) | is.data.frame(neighbors)){
+  #             # the user has likely passed in a matrix containing calculated values for risk.col and return.col
+  #             nbweights<-grep('w\\.',colnames(neighbors)) #need \\. to get the dot
+  #             for(i in 1:nrow(neighbors)) points(as.numeric(neighbors[i,nbweights]), type="b", col="lightblue")
+  #             # note that here we need to get weight cols separately from the matrix, not from xtract
+  #             # also note the need for as.numeric.  points() doesn't like matrix inputs
+  #         }
+  #     }
+  #     points(ROI$weights, type="b", col="blue", pch=16)
+  axis(2, cex.axis = cex.axis, col = element.color)
+  axis(1, labels=columnnames, at=1:numassets, las=las, cex.axis = cex.axis, col = element.color)
+  box(col = element.color)
+}
+
+
+#' classic risk return scatter of random portfolios
+#' 
+#' 
+#' \code{return.col} must be the name of a function used to compute the return metric on the portfolio weights
+#' \code{risk.col} must be the name of a function used to compute the risk metric on the portfolio weights
+#' 
+#' @param pso object created by \code{\link{optimize.portfolio}}
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns, used to recalulate the risk and return metric
+#' @param return.col string matching the objective of a 'return' objective, on vertical axis
+#' @param risk.col string matching the objective of a 'risk' objective, on horizontal axis
+#' @param ... any other passthru parameters 
+#' @param cex.axis The magnification to be used for axis annotation relative to the current setting of \code{cex}
+#' @param element.color color for the default plot scatter points
+#' @seealso \code{\link{optimize.portfolio}}
+#' @author Ross Bennett
+#' @export
+chart.Scatter.pso <- function(pso, R, return.col="mean", risk.col="StdDev", ..., element.color = "darkgray", cex.axis=0.8, main=""){
+  if(!inherits(pso, "optimize.portfolio.pso")) stop("pso must be of class 'optimize.portfolio.pso'")
+  
+  # Object with the "out" value in the first column and the normalized weights
+  # The first row is the optimal "out" value and the optimal weights
+  tmp <- extractStats(pso)
+  
+  # Get the weights
+  wts <- tmp[,-1]
+  
+  returnpoints <- applyFUN(R=R, weights=wts, FUN=return.col, ...=...)
+  riskpoints <- applyFUN(R=R, weights=wts, FUN=risk.col, ...=...)
+  
+  plot(x=riskpoints, y=returnpoints, xlab=risk.col, ylab=return.col, col="darkgray", axes=FALSE, main=main)
+  points(x=riskpoints[1], y=returnpoints[1], col="blue", pch=16) # optimal
+  axis(1, cex.axis = cex.axis, col = element.color)
+  axis(2, cex.axis = cex.axis, col = element.color)
+  box(col = element.color)
+}
+
+#' scatter and weights chart for portfolios
+#' 
+#' \code{return.col} must be the name of a function used to compute the return metric on the random portfolio weights
+#' \code{risk.col} must be the name of a function used to compute the risk metric on the random portfolio weights
+#' 
+#' @param pso object created by \code{\link{optimize.portfolio}}
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns, used to recalulate the risk and return metric
+#' @param return.col string matching the objective of a 'return' objective, on vertical axis
+#' @param risk.col string matching the objective of a 'risk' objective, on horizontal axis
+#' @param ... any other passthru parameters 
+#' @param cex.axis The magnification to be used for axis annotation relative to the current setting of \code{cex}
+#' @param element.color color for the default plot scatter points
+#'  @param neighbors set of 'neighbor' portfolios to overplot
+#' @param main an overall title for the plot: see \code{\link{title}}
+#' @seealso \code{\link{optimize.portfolio}}
+#' @author Ross Bennett
+#' @export
+charts.pso <- function(pso, R, return.col="mean", risk.col="StdDev",
+                       cex.axis=0.8, element.color="darkgray", neighbors=NULL, main="PSO.Portfolios", ...){
+  # Specific to the output of the optimize_method=pso
+  op <- par(no.readonly=TRUE)
+  layout(matrix(c(1,2)),height=c(2,2),width=1)
+  par(mar=c(4,4,4,2))
+  chart.Scatter.pso(pso=pso, R=R, return.col=return.col, risk.col=risk.col, element.color=element.color, cex.axis=cex.axis, main=main, ...=...)
+  par(mar=c(2,4,0,2))
+  chart.Weights.pso(pso=pso, neighbors=neighbors, las=3, xlab=NULL, cex.lab=1, element.color=element.color, cex.axis=cex.axis, ...=..., main="")
+  par(op)
+}
+
+#' scatter and weights chart for portfolios
+#' 
+#' \code{return.col} must be the name of a function used to compute the return metric on the random portfolio weights
+#' \code{risk.col} must be the name of a function used to compute the risk metric on the random portfolio weights
+#' 
+#' @param pso object created by \code{\link{optimize.portfolio}}
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns, used to recalulate the risk and return metric
+#' @param return.col string matching the objective of a 'return' objective, on vertical axis
+#' @param risk.col string matching the objective of a 'risk' objective, on horizontal axis
+#' @param ... any other passthru parameters 
+#' @param cex.axis The magnification to be used for axis annotation relative to the current setting of \code{cex}
+#' @param element.color color for the default plot scatter points
+#'  @param neighbors set of 'neighbor' portfolios to overplot
+#' @param main an overall title for the plot: see \code{\link{title}}
+#' @seealso \code{\link{optimize.portfolio}}
+#' @author Ross Bennett
+#' @export
+plot.optimize.portfolio.pso <- function(pso, R, return.col="mean", risk.col="StdDev",
+                       cex.axis=0.8, element.color="darkgray", neighbors=NULL, main="PSO.Portfolios", ...){
+  charts.pso(pso=pso, R=R, return.col=return.col, risk.col=risk.col, cex.axis=cex.axis, element.color=element.color, neighbors=neighbors, main=main, ...=...)
+}



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