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11-ColorTablePlots.R
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11-ColorTablePlots.R
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load("dataFiles/summ.RData")
library(reshape2)
library(dplyr)
library(ggplot2)
library(grid)
library(RColorBrewer)
#--------------------------------------------------------------
#--------------------------------------------------------------
scoreIt = function(X,metric){
pts = matrix(NA,length(X),1)
if(metric=='ME'){
boundary = c(.1,.15)
}
if(metric=='RMSE'){
boundary = c(.1,.15)
}
if(metric=='cov'){
boundary = c(.01,.02)
}
if(metric=='pow'){
boundary = c(.5,.8)
}
for(i in 1:length(X)){
if(!is.na(X[i])){
if(X[i] < boundary[1]){pts[i]=2}
if(X[i] >= boundary[1] & X[i] < boundary[2]){pts[i]=1}
if(X[i] >= boundary[2]){pts[i]=0}
}else{pts[i]=0}
}
return(pts)
}
#selectedMethods = c("RE", "TF", "PT", "PE", "PP", "PC", "PU", "3P")
colorTable = function(metric, cens, positive=FALSE, selectedMethods = c("RE", "TF", "PP", "PC", "PU", "3P", "WA")){
Delta = c(0,.2,.5,.8)
Tau = c(0,.2,.4)
finalOut = data.frame()
for(i in 1:length(Delta)){
for(j in 1:length(Tau)){
k_set=c(10, 30, 60, 100)
delta_set=Delta[i]
qrpEnv_set=c("none", "med", "high")
censor_set=cens
tau_set=Tau[j]
params <- expand.grid(k=k_set,
delta=delta_set,
qrpEnv=qrpEnv_set,
censor=censor_set,
tau=tau_set)
rownames(params) <- NULL
print(paste0(nrow(params), " fully crossed experimental conditions have been generated."))
conLab = paste(params[, "k"],
params[, "delta"],
params[, "qrpEnv"],
params[, "tau"],
params[, "censor"])
performScore = data.frame(matrix(NA,nrow(params),9))
colnames(performScore)=c("RE","TF","PT","PE","PP","PC","PU","3P", "WA")
pb = txtProgressBar(min = 1, max = nrow(params), style = 3)
for(iCon in 1:nrow(params)){
#load a given condition
if(metric=='pow'){
check = summ %>% filter(delta==params[iCon, "delta"],
tau==params[iCon, "tau"],
k==params[iCon, "k"],
censor==as.character(params[iCon, "censor"]), # kludge to deal w/ factor level trickery
qrpEnv==params[iCon, "qrpEnv"],
method != 'Tau',
method != 'fill',
method != 'pcurve', #remove pcurve, use pcurve.evidence
method != 'pcurve.hack',
method != 'pcurve.lack',
method != 'topN.fixed')
}else{
check = summ %>% filter(delta==params[iCon, "delta"],
tau==params[iCon, "tau"],
k==params[iCon, "k"],
censor==as.character(params[iCon, "censor"]), # kludge to deal w/ factor level trickery
qrpEnv==params[iCon, "qrpEnv"],
method != 'Tau',
method != 'fill',
method != 'pcurve.evidence', #remove pcurve.evidence, use pcurve
method != 'pcurve.hack',
method != 'pcurve.lack',
method != 'topN.fixed')
}
if(positive==TRUE){
condition = data.frame(check$delta,
check$tau,
check$k,
check$method,
check$ME.pos,
check$RMSE.pos,
check$coverage.pos,
check$H0.reject.pos.rate)
}else{
condition = data.frame(check$delta,
check$tau,
check$k,
check$method,
check$ME,
check$RMSE,
check$coverage,
check$H0.reject.rate)
}
colnames(condition)=c("delta","tau","k","method","ME","RMSE","cov","pow")
#recode as power
#condition$pow = 1 - condition$cons0
#Make sure each method is represented. If not, leave as NA.
if(metric=='pow'){
methodNames2 = c("reMA","TF","PET","PEESE","PETPEESE","pcurve.evidence","puniform","3PSM", "WAAP-WLS")
}else{
methodNames2 = c("reMA","TF","PET","PEESE","PETPEESE","pcurve","puniform","3PSM", "WAAP-WLS")
}
for(iMethod in 1:length(methodNames2)){
if(sum(methodNames2[iMethod]==condition[,"method"])>0){
methodInd = which(condition$method==methodNames2[iMethod])
performScore[iCon,iMethod] = condition[methodInd,metric]
}
}
setTxtProgressBar(pb, iCon)
}
close(pb)
out = cbind(round(performScore,digit=2),id = factor(1:length(conLab)))
outMelt = melt(out)
outMelt$Delta = i
outMelt$Tau = j
finalOut = rbind(finalOut,outMelt)
}
}
#recode based on metric
if(metric=='ME'){
X = abs(finalOut$value)
}
if(metric=='RMSE'){
X = abs(finalOut$value)
}
if(metric=='cov'){
X = abs(finalOut$value-.95)
}
if(metric=='pow'){
X = finalOut$value
}
finalOut$brks = factor(scoreIt(X,metric))
#get the colors for the table
colorCnt = 3
getPalette = colorRampPalette(brewer.pal(3, 'Blues'))
brkColors = getPalette(colorCnt)
# reduce to relevant methods
finalOut <- finalOut %>% filter(variable %in% selectedMethods)
#Break it up by each to-be-ploted data set
plotList = list()
plotCount = matrix(1:(length(Delta)*length(Tau)),length(Tau),length(Delta))
for(i in 1:length(Delta)){
for(j in 1:length(Tau)){
toPlot = subset(finalOut, finalOut$Delta==i & finalOut$Tau==j)
plot = ggplot(toPlot, aes(variable, id)) +
geom_tile(aes(fill = brks), colour = "white") +
scale_fill_manual(values = c("0" = brkColors[1], "1" = brkColors[2], "2" = brkColors[3] )) +
geom_text(aes(variable, label = value),
color = "black", size = 3) +
#ggtitle("test") +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.y = element_blank(),
panel.grid.major = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.ticks = element_blank(),
legend.position = 'none',
plot.title = element_text(lineheight=.8),
axis.text = element_text(colour="black"))
iP = plotCount[j,i]
plotList[[iP]] = plot
}
}
#make the legend
params <- expand.grid(k=c(10,30,60,100),
qrpEnv=c(0,1,2))
rownames(params) <- NULL
conLab = paste(params[, "k"],
params[, "qrpEnv"])
leg = cbind(params,id = factor(1:length(conLab)))
meltLeg = melt(leg)
legendPlot = ggplot(meltLeg, aes(variable, id)) +
geom_text(aes(variable, label = value),
color = "black", size = 4) +
#ggtitle("legend") +
theme(axis.title.x = element_blank(),
axis.title.y = element_blank(),
axis.text.y = element_blank(),
panel.grid.major = element_blank(),
panel.border = element_blank(),
panel.background = element_blank(),
axis.ticks = element_blank(),
legend.position = 'none',
plot.title = element_text(lineheight=.8),
axis.text = element_text(colour="black"))
#Create and save PDF
delta1 = expression(paste(delta,' = 0.0'))
delta2 = expression(paste(delta,' = 0.2'))
delta3 = expression(paste(delta,' = 0.5'))
delta4 = expression(paste(delta,' = 0.8'))
tau1 = expression(paste(tau,' = 0.0'))
tau2 = expression(paste(tau,' = 0.2'))
tau3 = expression(paste(tau,' = 0.4'))
adjX = -.05
adjY = -.0125
W = .28
#mark if posified
if(positive == TRUE){
posif = "_Posified"
}else{
posif = "_NotPosified"
}
plotFileName=paste0("ColorTablePlots/", metric,'_sel',cens,posif,'.pdf')
pdf(file=plotFileName,12,10)
print(plotList[[1]],vp = viewport(width = W, height = 0.25, x = .38, y = .0, just = c("right","bottom")))
print(plotList[[4]],vp = viewport(width = W, height = 0.25, x = .38, y = .25 + adjY/2, just = c("right","bottom")))
print(plotList[[7]],vp = viewport(width = W, height = 0.25, x = .38, y = .50 + adjY, just = c("right","bottom")))
print(plotList[[10]],vp = viewport(width = W, height = 0.25, x = .38, y = .75 + adjY*1.5, just = c("right","bottom")))
print(plotList[[2]],vp = viewport(width = W, height = 0.25, x = .68 + adjX/2, y = .0, just = c("right","bottom")))
print(plotList[[5]],vp = viewport(width = W, height = 0.25, x = .68 + adjX/2, y = .25 + adjY/2, just = c("right","bottom")))
print(plotList[[8]],vp = viewport(width = W, height = 0.25, x = .68 + adjX/2, y = .50 + adjY, just = c("right","bottom")))
print(plotList[[11]],vp = viewport(width = W, height = 0.25, x = .68 + adjX/2, y = .75 + adjY*1.5, just = c("right","bottom")))
print(plotList[[3]],vp = viewport(width = W, height = 0.25, x = .98 + adjX, y = .0, just = c("right","bottom")))
print(plotList[[6]],vp = viewport(width = W, height = 0.25, x = .98 + adjX, y = .25 + adjY/2, just = c("right","bottom")))
print(plotList[[9]],vp = viewport(width = W, height = 0.25, x = .98 + adjX, y = .50 + adjY, just = c("right","bottom")))
print(plotList[[12]],vp = viewport(width = W, height = 0.25, x = .98 + adjX, y = .75 + adjY*1.5, just = c("right","bottom")))
print(legendPlot,vp = viewport(width = .1, height = 0.25, x = .1, y = 0, just = c("right","bottom")))
print(legendPlot,vp = viewport(width = .1, height = 0.25, x = .1, y = .25 + adjY/2, just = c("right","bottom")))
print(legendPlot,vp = viewport(width = .1, height = 0.25, x = .1, y = .5 + adjY, just = c("right","bottom")))
print(legendPlot,vp = viewport(width = .1, height = 0.25, x = .1, y = .75 + adjY*1.5, just = c("right","bottom")))
grid.text(delta1, x=.95, y=.25-.125,gp=gpar(fontsize=15),just=c("center","bottom"))
grid.text(delta2, x=.95, y=.5-.125 + adjY/2,gp=gpar(fontsize=15),just=c("center","bottom"))
grid.text(delta3, x=.95, y=.75-.125 + adjY,gp=gpar(fontsize=15),just=c("center","bottom"))
grid.text(delta4, x=.95, y=.99-.125 + adjY*1.5,gp=gpar(fontsize=15),just=c("center","bottom"))
grid.text(tau1, x=.38-.3/2, y=.99,gp=gpar(fontsize=15),just=c("center","center"))
grid.text(tau2, x=.68 -.3/2 + adjX/2, y=.99,gp=gpar(fontsize=15),just=c("center","center"))
grid.text(tau3, x=.98 -.3/2 + adjX, y=.99,gp=gpar(fontsize=15),just=c("center","center"))
dev.off()
}
#not posified
colorTable(metric='ME', cens="none")
colorTable(metric='RMSE', cens="none")
colorTable(metric='cov', cens="none")
colorTable(metric='pow', cens="none") #p-curve and p-uniform will be NA. See note in 3-resultsFramework
colorTable('ME', "med")
colorTable('RMSE',"med")
colorTable('cov', "med")
colorTable('pow', "med") #p-curve and p-uniform will be NA. See note in 3-resultsFramework
colorTable('ME', "high")
colorTable('RMSE',"high")
colorTable('cov', "high")
colorTable('pow', "high") #p-curve and p-uniform will be NA. See note in 3-resultsFramework
#posified
# colorTable('ME', "none", positive=TRUE)
# colorTable('RMSE', "none", positive=TRUE)
# colorTable('cov', "none", positive=TRUE)
# colorTable('pow', "none", positive=TRUE)
#
# colorTable('ME', "med", positive=TRUE)
# colorTable('RMSE',"med", positive=TRUE)
# colorTable('cov', "med", positive=TRUE)
# colorTable('pow', "med", positive=TRUE)
#
# colorTable('ME', "high", positive=TRUE)
# colorTable('RMSE',"high", positive=TRUE)
# colorTable('cov', "high", positive=TRUE)
# colorTable('pow', "high", positive=TRUE)