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process.clean.analyze.R
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#outputdir -- directory for output (boxplots, etc) and for where you have the aoc and rhino out_results folders
outputdir<-"DIRECTORY HERE"
setwd(outputdir)
#opens library
library(multcomp)
library(multcompView)
#threshhold value, change to whatever
thresh <- 10
#scans directory and creates a list of all files and sub directories for AOC and rhino datasets
directories<-list.dirs(path=paste(outputdir, "/out_results", sep=""), full.names=TRUE, recursive=TRUE)
directories2<-list.dirs(path=paste(outputdir, "/out_results_rhino", sep=""), full.names=TRUE, recursive=TRUE)
#empty vectors to store file information
files<-vector()
files2<-vector()
files3<-vector()
files4<-vector()
#loops to store all files within marked_search and prf_results into the files and files2 vectors (for the AOC set)
#and files3 and files4 for the rhino set
for (i in 1:length(directories)) {
if (grepl("marked_search", directories[i])==TRUE)
files <- append(files, list.files(path=directories[i], full.names=TRUE))
}
for (i in 1:length(directories)) {
if (grepl("prf_results", directories[i])==TRUE)
files2 <- append(files2, list.files(path=directories[i], full.names=TRUE))
}
for (i in 1:length(directories2)) {
if (grepl("marked_search", directories2[i])==TRUE)
files3 <- append(files3, list.files(path=directories2[i], full.names=TRUE))
}
for (i in 1:length(directories2)) {
if (grepl("prf_results", directories2[i])==TRUE)
files4 <- append(files4, list.files(path=directories2[i], full.names=TRUE))
}
#---------------------------------------------------AOC DATASET LOOP
#-------------------------------------------------------------------
#empty data frame to store all prfmap data
prfdataframe<-data.frame()
#loop to read in files from AOC set
for (i in 1:length(files)) {
data<-read.table(files[i], sep="", nrows=thresh, col.names=c(sub(".marked_search.(.*)", "",
files[i]), sub("(.*?)marked_search.", "", files[i])))
data2<-read.table(files2[i], header=F, skip=1, sep="", col.names=c(sub(".prf_results.(.*)", "",
files2[i]), sub("(.*?)prf_results.", "", files2[i]), "tp", "p", "r", "f", "fp", "fp-rate", "tn"))
colnames(data)[1] <- sub("(.*?)out_results.", "", colnames(data)[1])
colnames(data2)[1] <- sub("(.*?)out_results.", "", colnames(data2)[1])
#counters for P/R/F/MAP calculations
counter<-0
lastvalue<-0
rank<-0
map<-0
#loops through data (dataframe) looking for asterisks, keeps track of how many occur within threshhold
for (i in 1:nrow(data)) {
if (pmatch("*", data[1][i,], nomatch=FALSE, duplicates.ok=FALSE)==1) {
counter<-counter + 1
}
}
#calculates MAP via prf files
for (i in 1:nrow(data2)){
if (data2$tp[i] != lastvalue) {
map<-map + ((data2$tp[i]-lastvalue) * data2$p[i])
lastvalue<-data2$tp[i]
rank<-rank + 1
}
}
#adds P/R/F/MAP to the data dataframe
data$P<-(counter/thresh)
if (data$P[1] == "NaN" || data$P[1] == "Inf")
data$P<-0
data$R<-(counter/data2$tp[length(data2$tp)])
if (data$R[1] == "NaN" || data$R[1] == "Inf")
data$R<-0
data$F<-(2*((data$P[1] * data$R[1])/(data$P[1] + data$R[1])))
if (data$F[1] == "NaN" || data$F[1] == "Inf")
data$F<-0
data$MAP<-(map/data2$tp[length(data2$tp)]) / 100
if (data$MAP[1] == "NaN" || data$MAP[1] == "Inf")
data$MAP<-0
#adds concern name to the dataframe
if (grepl("add_text", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "J"
}
if (grepl("create_textfield", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "C"
}
if (grepl("text_field_tool", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "I"
}
if (grepl("textfield", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "N"
}
if (grepl("textfieldReportElement", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "P"
}
if (grepl("textfieldReportElement1", names(data[2])) == TRUE) {
data$Concern <- "Textfield"
data$Subject <- "E"
}
if (grepl("IReportCompiler", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "A"
}
if (grepl("compile", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "M"
}
if (grepl("compile_report", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "P"
}
if (grepl("compile_report1", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "J"
}
if (grepl("compile_report2", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "H"
}
if (grepl("compile_report3", names(data[2])) == TRUE) {
data$Concern <- "Compile"
data$Subject <- "F"
}
if (grepl("add_auction", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "B"
}
if (grepl("add_auction1", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "F"
}
if (grepl("add_auction2", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "H"
}
if (grepl("add_auction3", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "K"
}
if (grepl("add_auction4", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "O"
}
if (grepl("add_auction5", names(data[2])) == TRUE) {
data$Concern <- "Add Auction"
data$Subject <- "R"
}
if (grepl("add_snipe", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "Q"
}
if (grepl("do_you_wish_to_snipe", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "K"
}
if (grepl("set_snipe", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "Q"
}
if (grepl("snipe", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "H"
}
if (grepl("snipe1", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "M"
}
if (grepl("sniping", names(data[2])) == TRUE) {
data$Concern <- "Set Snipe"
data$Subject <- "A"
}
if (grepl("save", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "L"
}
if (grepl("save_auctions", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "I"
}
if (grepl("save_auction", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "E"
}
if (grepl("save_auction1", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "C"
}
if (grepl("save_auction2", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "Q"
}
if (grepl("save_auction3", names(data[2])) == TRUE) {
data$Concern <- "Save Auctions"
data$Subject <- "I"
}
if (grepl("find", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "O"
}
if (grepl("get_theater", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "B"
}
if (grepl("movie", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "P"
}
if (grepl("movie", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "G"
}
if (grepl("theater", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "D"
}
if (grepl("view_listing", names(data[2])) == TRUE) {
data$Concern <- "Theaters"
data$Subject <- "J"
}
if (grepl("search", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "I"
}
if (grepl("search1", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "M"
}
if (grepl("search2", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "A"
}
if (grepl("search3", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "L"
}
if (grepl("search4", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "R"
}
if (grepl("search_file", names(data[2])) == TRUE) {
data$Concern <- "Search"
data$Subject <- "D"
}
if (grepl("open_file", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "F"
}
if (grepl("play", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "R"
}
if (grepl("play_track", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "N"
}
if (grepl("play_file", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "G"
}
if (grepl("play_file1", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "B"
}
if (grepl("start", names(data[2])) == TRUE) {
data$Concern <- "Play"
data$Subject <- "L"
}
#creates a single dataframe with all of the P/R/F/MAP data for each technique/query/concern combo
prfdataframe<-rbind(prfdataframe, data.frame("Technique"=names(data[1]), "Concern"=data$Concern[1],
"Query"=names(data[2]), "Subject"=data$Subject[1], "P"=data$P[1], "R"=data$R[1], "F"=data$F[1], "MAP"=data$MAP[1]))
}
#---------------------------------------------------RHINO DATASET LOOP
#---------------------------------------------------------------------
#empty data frame to store all prfmap data
prfdataframe2<-data.frame()
#loop to read in files from rhino set and formats the names of the columns (this is pretty ghetto but it works)
for (i in 1:length(files3)) {
data3<-read.table(files3[i], sep="", nrows=thresh, col.names=c(sub(".marked_search.(.*)", "",
files3[i]), sub("(.*?)marked_search.", "", files3[i]), sub("(.*?)marked_search.", "", files3[i])))
data4<-read.table(files4[i], header=F, skip=1, sep="", col.names=c(sub(".prf_results.(.*)", "",
files4[i]), sub("(.*?)prf_results.", "", files4[i]), "tp", "rank-rel", "p", "r", "f"))
colnames(data3)[1] <- sub("(.*?)out_results_rhino.", "", colnames(data3)[1])
colnames(data3)[2] <- sub(".[0-9].out", "", colnames(data3)[2])
colnames(data3)[2] <- unlist(strsplit(colnames(data3)[2], ".", TRUE))[[1]]
colnames(data3)[3] <- unlist(strsplit(colnames(data3)[3], colnames(data3)[2], TRUE))[[2]]
colnames(data3)[3] <- sub(".", "", colnames(data3)[3])
colnames(data3)[3] <- sub(".[0-9].out.(.*)", "", colnames(data3)[3])
colnames(data4)[1] <- colnames(data3)[1]
colnames(data4)[2] <- colnames(data3)[2]
colnames(data4)[4] <- colnames(data3)[3]
#counters for P/R/F/MAP calculations
counter<-0
lastvalue<-0
rank<-0
map<-0
lastvalue<-0
#loops through data (dataframe) looking for asterisks, keeps track of how many occur within threshhold
for (i in 1:nrow(data3)) {
if (pmatch("*", data3[2][i,], nomatch=FALSE, duplicates.ok=FALSE)==1) {
counter<-counter + 1
}
}
#calculates MAP via prf files
for (i in 1:nrow(data4)){
if (data4$tp[i] != lastvalue) {
map<-map + ((data4$tp[i]-lastvalue)*data4$p[i])
lastvalue<-data4$tp[i]
rank<-rank + 1
}
}
#adds P/R/F/MAP to the data dataframe
data3$P<-(counter/thresh)
if (data3$P[1] == "NaN" || data3$P[1] == "Inf")
data3$P<-0
data3$R<-(counter/data4$tp[length(data4$tp)])
if (data3$R[1] == "NaN" || data3$R[1] == "Inf")
data3$R<-0
data3$F<-(2*((data3$P[1] * data3$R[1])/(data3$P[1] + data3$R[1])))
if (data3$F[1] == "NaN" || data3$F[1] == "Inf")
data3$F<-0
data3$MAP<-(map/data4$tp[length(data4$tp)]) / 100
if (data3$MAP[1] == "NaN" || data3$MAP[1] == "Inf")
data3$MAP<-0
#creates a single dataframe with all of the P/R/F/MAP data for each technique/query/concern combo
prfdataframe2<-rbind(prfdataframe2, data.frame("Technique"=names(data3[1]), "Concern"=names(data3[3]),
"Query"=names(data3)[2], "P"=data3$P[1], "R"=data3$R[1], "F"=data3$F[1], "MAP"=data3$MAP[1]))
}
#empty data frame for p/r/f/map stats
mapstats<-data.frame()
rhinomapstats<-data.frame()
pstats<-data.frame()
rhinopstats<-data.frame()
rstats<-data.frame()
rhinorstats<-data.frame()
fstats<-data.frame()
rhinofstats<-data.frame()
#calculates mean/std/var/median/quartiles for p/r/f/map AOC data
for (i in c("both_swum_weighted", "sig_swum", "sig_bow_boolean", "sig_bow_tf", "sig_at", "both_bow_tf", "both_bow_boolean_weighted", "body_bow_boolean",
"body_swum", "both_bow_tf_weighted", "body_bow_tf")) {
ci<-subset(prfdataframe, prfdataframe[1]==i)
mapstats<-rbind(mapstats, data.frame("Technique"=i, "Mean"=mean(ci$MAP), "Median"=quantile(ci$MAP,.50),
"First.Quartile"=quantile(ci$MAP,.25), "Third.Quartile"=quantile(ci$MAP,.75),"STD"=sd(ci$MAP),
"Var"=var(ci$MAP), "Min"=min(ci$MAP), "Max"=max(ci$MAP), row.names=NULL))
pstats<-rbind(pstats, data.frame("Technique"=i, "Mean"=mean(ci$P), "Median"=quantile(ci$P,.50),
"First.Quartile"=quantile(ci$P,.25), "Third.Quartile"=quantile(ci$P,.75), "STD"=sd(ci$P),
"Var"=var(ci$P), "Min"=min(ci$P), "Max"=max(ci$P), row.names=NULL))
rstats<-rbind(rstats, data.frame("Technique"=i, "Mean"=mean(ci$R), "Median"=quantile(ci$R,.50),
"First.Quartile"=quantile(ci$R,.25), "Third.Quartile"=quantile(ci$R,.75), "STD"=sd(ci$R),
"Var"=var(ci$R), "Min"=min(ci$R), "Max"=max(ci$R), row.names=NULL))
fstats<-rbind(fstats, data.frame("Technique"=i, "Mean"=mean(ci$F), "Median"=quantile(ci$F,.50),
"First.Quartile"=quantile(ci$F,.25), "Third.Quartile"=quantile(ci$F,.75), "STD"=sd(ci$F),
"Var"=var(ci$F), "Min"=min(ci$F), "Max"=max(ci$F), row.names=NULL))
}
#calculates mean/std/var/median/quartiles for p/r/f/map Rhino data
#for (i in c("body_bow", "body_bow_TF_NoSig", "body_swum", "bow", "bowBooleanNew", "bowTFNew", "sig_at", "sig_bow", "sig_lex", "sig_swum", "swum")) {
for (i in c("both_swum_weighted", "sig_swum", "sig_bow_boolean", "sig_bow_tf", "sig_at", "both_bow_tf", "both_bow_boolean_weighted", "body_bow_boolean",
"body_swum", "both_bow_tf_weighted", "body_bow_tf")) {
ci<-subset(prfdataframe2, prfdataframe2[1]==i)
rhinomapstats<-rbind(rhinomapstats, data.frame("Technique"=i, "Mean"=mean(ci$MAP), "Median"=quantile(ci$MAP,.50),
"First.Quartile"=quantile(ci$MAP,.25), "Third.Quartile"=quantile(ci$MAP,.75),"STD"=sd(ci$MAP),
"Var"=var(ci$MAP), "Min"=min(ci$MAP), "Max"=max(ci$MAP), row.names=NULL))
rhinopstats<-rbind(rhinopstats, data.frame("Technique"=i, "Mean"=mean(ci$P), "Median"=quantile(ci$P,.50),
"First.Quartile"=quantile(ci$P,.25), "Third.Quartile"=quantile(ci$P,.75), "STD"=sd(ci$P),
"Var"=var(ci$P), "Min"=min(ci$P), "Max"=max(ci$P), row.names=NULL))
rhinorstats<-rbind(rhinorstats, data.frame("Technique"=i, "Mean"=mean(ci$R), "Median"=quantile(ci$R,.50),
"First.Quartile"=quantile(ci$R,.25), "Third.Quartile"=quantile(ci$R,.75), "STD"=sd(ci$R),
"Var"=var(ci$R), "Min"=min(ci$R), "Max"=max(ci$R), row.names=NULL))
rhinofstats<-rbind(rhinofstats, data.frame("Technique"=i, "Mean"=mean(ci$F), "Median"=quantile(ci$F,.50),
"First.Quartile"=quantile(ci$F,.25), "Third.Quartile"=quantile(ci$F,.75), "STD"=sd(ci$F),
"Var"=var(ci$F), "Min"=min(ci$F), "Max"=max(ci$F), row.names=NULL))
}
#making body/sig/weighted/swum/bowboolean/bowtf columns and making them all zero in prfdataframe and prfdataframe2
prfdataframe$Location <- "N/A"
prfdataframe$BodyScore <- "N/A"
prfdataframe$BodyType <- "N/A"
prfdataframe$SigScore <- "N/A"
prfdataframe$SigType <- "N/A"
prfdataframe$Weighted <- "N/A"
prfdataframe2$Location <- "N/A"
prfdataframe2$BodyScore <- "N/A"
prfdataframe2$BodyType <- "N/A"
prfdataframe2$SigScore <- "N/A"
prfdataframe2$SigType <- "N/A"
prfdataframe2$Weighted <- "N/A"
for (i in 1:nrow(prfdataframe)) {
if (prfdataframe$Technique[i] == "body_bow_boolean") {
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "boolean"
prfdataframe$Location[i] <- "body"}
if(prfdataframe$Technique[i] == "body_swum") {
prfdataframe$BodyScore[i] <- "swum"
prfdataframe$BodyType[i] <- "normal"
prfdataframe$Location[i] <- "body" }
if(prfdataframe$Technique[i] == "body_bow_tf") {
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "tf"
prfdataframe$Location[i] <- "body" }
if(prfdataframe$Technique[i] == "sig_bow_tf") {
prfdataframe$SigScore[i] <- "bow"
prfdataframe$SigType[i] <- "tf"
prfdataframe$Location[i] <- "sig" }
if(prfdataframe$Technique[i] == "sig_bow_boolean") {
prfdataframe$SigScore[i] <- "bow"
prfdataframe$SigType[i] <- "boolean"
prfdataframe$Location[i] <- "sig" }
if(prfdataframe$Technique[i] == "sig_swum") {
prfdataframe$SigScore[i] <- "swum"
prfdataframe$SigType[i] <- "normal"
prfdataframe$Location[i] <- "sig" }
if(prfdataframe$Technique[i] == "sig_at") {
prfdataframe$SigScore[i] <- "swum"
prfdataframe$SigType[i] <- "at"
prfdataframe$Location[i] <- "sig" }
if (prfdataframe$Technique[i] == "both_swum_weighted") {
prfdataframe$SigScore[i] <- "swum"
prfdataframe$SigType[i] <- "normal"
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "tf"
prfdataframe$Location[i] <- "both"
prfdataframe$Weighted[i] <- "weighted" }
if (prfdataframe$Technique[i] == "both_bow_boolean_weighted") {
prfdataframe$SigScore[i] <- "bow"
prfdataframe$SigType[i] <- "boolean"
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "boolean"
prfdataframe$Location[i] <- "both"
prfdataframe$Weighted[i] <- "weighted" }
if (prfdataframe$Technique[i] == "both_bow_tf") {
prfdataframe$SigScore[i] <- "bow"
prfdataframe$SigType[i] <- "tf"
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "tf"
prfdataframe$Location[i] <- "both" }
if (prfdataframe$Technique[i] == "both_bow_tf_weighted") {
prfdataframe$SigScore[i] <- "bow"
prfdataframe$SigType[i] <- "tf"
prfdataframe$BodyScore[i] <- "bow"
prfdataframe$BodyType[i] <- "tf"
prfdataframe$Location[i] <- "both"
prfdataframe$Weighted[i] <- "weighted" }
}
for (i in 1:nrow(prfdataframe2)) {
if (prfdataframe2$Technique[i] == "body_bow_boolean") {
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "boolean"
prfdataframe2$Location[i] <- "body" }
if(prfdataframe2$Technique[i] == "body_swum") {
prfdataframe2$BodyScore[i] <- "swum"
prfdataframe2$BodyType[i] <- "normal"
prfdataframe2$Location[i] <- "body" }
if(prfdataframe2$Technique[i] == "body_bow_tf") {
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "tf"
prfdataframe2$Location[i] <- "body" }
if(prfdataframe2$Technique[i] == "sig_bow_tf") {
prfdataframe2$SigScore[i] <- "bow"
prfdataframe2$SigType[i] <- "tf"
prfdataframe2$Location[i] <- "sig" }
if(prfdataframe2$Technique[i] == "sig_bow_boolean") {
prfdataframe2$SigScore[i] <- "bow"
prfdataframe2$SigType[i] <- "boolean"
prfdataframe2$Location[i] <- "sig" }
if(prfdataframe2$Technique[i] == "sig_swum") {
prfdataframe2$SigScore[i] <- "swum"
prfdataframe2$SigType[i] <- "normal"
prfdataframe2$Location[i] <- "sig" }
if(prfdataframe2$Technique[i] == "sig_at") {
prfdataframe2$SigScore[i] <- "swum"
prfdataframe2$SigType[i] <- "at"
prfdataframe2$Location[i] <- "sig" }
if (prfdataframe2$Technique[i] == "both_swum_weighted") {
prfdataframe2$SigScore[i] <- "swum"
prfdataframe2$SigType[i] <- "normal"
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "tf"
prfdataframe2$Location[i] <- "both"
prfdataframe2$Weighted[i] <- "weighted" }
if (prfdataframe2$Technique[i] == "both_bow_boolean_weighted") {
prfdataframe2$SigScore[i] <- "bow"
prfdataframe2$SigType[i] <- "boolean"
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "boolean"
prfdataframe2$Location[i] <- "both"
prfdataframe2$Weighted[i] <- "weighted" }
if (prfdataframe2$Technique[i] == "both_bow_tf") {
prfdataframe2$SigScore[i] <- "bow"
prfdataframe2$SigType[i] <- "tf"
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "tf"
prfdataframe2$Location[i] <- "both" }
if (prfdataframe2$Technique[i] == "both_bow_tf_weighted") {
prfdataframe2$SigScore[i] <- "bow"
prfdataframe2$SigType[i] <- "tf"
prfdataframe2$BodyScore[i] <- "bow"
prfdataframe2$BodyType[i] <- "tf"
prfdataframe2$Weighted[i] <- "weighted"
prfdataframe2$Location[i] <- "both" }
}
#prints out summary statistics for aoc and rhino data and saves them to files
sink(paste(outputdir, "/prfdataframe.txt", sep=""))
options(max.print = 99999999, width=999)
print("-----------prfdataframe - aoc set-------------")
prfdataframe
sink()
sink(paste(outputdir, "/prfdataframe2.txt", sep=""))
options(max.print = 99999999, width=999)
print("-----------prfdataframe2 - rhino set-------------")
prfdataframe2
sink()
sink(paste(outputdir, "/precisionStatsAOC.txt", sep=""))
print("-----------precision AOC summary-------------")
pstats
sink()
sink(paste(outputdir, "/precisionStatsRhino.txt", sep=""))
print("-----------precision Rhino summary-------------")
rhinopstats
sink()
sink(paste(outputdir, "/recallStatsAOC.txt", sep=""))
print("------------recall AOC summary--------------")
rstats
sink()
sink(paste(outputdir, "/recallStatsRhino.txt", sep=""))
print("------------recall Rhino summary--------------")
rhinorstats
sink()
sink(paste(outputdir, "/fmeasureStatsAOC.txt", sep=""))
print("-----------f-measure AOC summary-------------")
fstats
sink()
sink(paste(outputdir, "/fmeasureStatsRhino.txt", sep=""))
print("-----------f-measure Rhino summary-------------")
rhinofstats
sink()
sink(paste(outputdir, "/mapStatsAOC.txt", sep=""))
print("-------------map AOC summary---------------")
mapstats
sink()
sink(paste(outputdir, "/mapStatsRhino.txt", sep=""))
print("-------------map Rhino summary---------------")
rhinomapstats
sink()
sink(paste(outputdir, "/TukeyResultsAOC.txt", sep=""))
print("-------------tukeyhsd/aov AOC--------------")
analysis<-aov(formula=MAP~Technique, data=prfdataframe)
summary(analysis)
tukey<-TukeyHSD(analysis)
print(tukey)
tukeyframe<-data.frame(tukey$Technique)
sigresults<-data.frame()
for (i in 1:length(tukeyframe[,1]))
if (tukeyframe$p.adj[i] < .05)
sigresults<-rbind(sigresults, tukeyframe[i,])
print("-------------tukey significant results-------------")
print(sigresults)
sink()
sink(paste(outputdir, "/TukeyResultsRhino.txt", sep=""))
print("-------------tukeyhsd/aov Rhino--------------")
analysis2<-aov(formula=MAP~Technique, data=prfdataframe2)
summary(analysis2)
tukey2<-TukeyHSD(analysis2)
print(tukey2)
tukeyframe2<-data.frame(tukey2$Technique)
sigresults2<-data.frame()
for (i in 1:length(tukeyframe2[,1]))
if (tukeyframe2$p.adj[i] < .05)
sigresults2<-rbind(sigresults2, tukeyframe2[i,])
print("-------------tukey significant results-------------")
print(sigresults2)
sink()
pdf(paste(outputdir, "/RhinoBoxplotWithTukeyGroups.pdf", sep=""))
multcompBoxplot(MAP~Technique, data=prfdataframe2,
horizontal=FALSE, compFn="TukeyHSD",
sortFn="mean", decreasing=FALSE,
plotList=list(
boxplot=list(fig=c(.35, 1, 0, 1), las=2, ylab="MAP", main="MAP~Technique w/ Tukey Groups", col="lightgrey"),
multcompTs=list(fig=c(0.02, 0.15, 0, 1)),
multcompLetters=list(fig=c(0.40, 0.97, 0.03, 0.98), fontsize=0,fontface="bold")))
# means<-tapply(prfdataframe2[[7]], prfdataframe2[,1], mean)
# points(means, col="red")
dev.off()
pdf(paste(outputdir, "/AOCBoxplotWithTukeyGroups.pdf", sep=""))
multcompBoxplot(MAP~Technique, data=prfdataframe,
horizontal=FALSE, compFn="TukeyHSD",
sortFn="mean", decreasing=FALSE,
plotList=list(
boxplot=list(fig=c(.35, 1, 0, 1), las=2, ylab="MAP", main="MAP~Technique w/ Tukey Groups", col="lightgrey"),
multcompTs=list(fig=c(0.02, 0.15, 0, 1)),
multcompLetters=list(fig=c(0.40, 0.97, 0.03, 0.98), fontsize=0,fontface="bold")))
# means<-tapply(prfdataframe[[7]], prfdataframe[,1], mean)
# points(means, col="red")
dev.off()
#----------------------------------------------AOC BOXPLOTS
#----------------------------------------------------------
#creates directory to store boxplots
dir.create(paste(outputdir, "/BoxplotsAOC",sep=""), showWarnings = FALSE)
#loop to create boxplots (map/p/r/f vs technique and concern)
for (i in 5:8) {
for (x in 1:4) {
prfdataframe[,x]<-with(prfdataframe, reorder(prfdataframe[,x], prfdataframe[[i]], mean))
name<-paste(outputdir, "/BoxplotsAOC/", names(prfdataframe[i]), "_",
names(prfdataframe[x]), "boxplot.pdf", sep="")
main<-paste(names(prfdataframe[i]),"~", names(prfdataframe[x]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(prfdataframe[[i]]~prfdataframe[[x]], data=prfdataframe, ylab=names(prfdataframe[i]), col="lightgray",
las=2, main=main, cex.axis=1)
means<-tapply(prfdataframe[[i]], prfdataframe[,x], mean)
points(means, col="red")
dev.off()
}
}
#creates directory to store boxplots
dir.create(paste(outputdir, "/BoxplotsByConcernAOC", sep=""), showWarnings = FALSE)
#loop to create boxplots (map/p/r/f vs technique by one concern at a time)
for (c in c("Textfield", "Compile", "Add Auction", "Set Snipe", "Save Auctions", "Theaters", "Search", "Play")) {
concernframe<-subset(prfdataframe, prfdataframe$Concern == c)
for (i in 5:8) {
concernframe[,1]<-with(concernframe, reorder(concernframe[,1], concernframe[[i]], mean))
name<-paste(outputdir, "/BoxplotsByConcernAOC/", names(concernframe[i]), "_",
names(concernframe[1]), "_", c,"_","boxplot.pdf", sep="")
main<-paste(names(concernframe[i]),"~", names(concernframe[1]), "(", c, ")", sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(concernframe[[i]]~concernframe[[1]], data=concernframe, ylab=names(concernframe[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(concernframe[[i]], concernframe[,1], mean)
points(means, col="red")
dev.off()
}
}
#direcory for paired boxplots
dir.create(paste(outputdir, "/PairedBoxplotsAOC", sep=""), showWarnings = FALSE)
#Sig-Only box plot
sigframe<-subset(prfdataframe, prfdataframe$Technique=="sig_swum" | prfdataframe$Technique == "sig_at"
| prfdataframe$Technique == "sig_bow_tf" | prfdataframe$Technique == "sig_bow_boolean")
for (i in 5:8) {
sigframe[,1]<-with(sigframe, reorder(sigframe[,1], sigframe[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsAOC/", "SigOnly_", names(sigframe[i]), "_",
names(sigframe[1]), "_","boxplot.pdf", sep="")
main<-paste(names(sigframe[i]),"~", names(sigframe[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(sigframe[[i]]~droplevels(sigframe[[1]]), data=sigframe, ylab=names(sigframe[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(sigframe[[i]], sigframe[,1], mean)
points(means, col="red")
dev.off()
}
#Body-Only box plot
bodyframe<-subset(prfdataframe, prfdataframe$Technique=="body_swum" | prfdataframe$Technique == "body_bow_boolean"
| prfdataframe$Technique == "body_bow_tf")
for (i in 5:8) {
bodyframe[,1]<-with(bodyframe, reorder(bodyframe[,1], bodyframe[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsAOC/", "BodyOnly_", names(bodyframe[i]), "_",
names(bodyframe[1]), "_","boxplot.pdf", sep="")
main<-paste(names(bodyframe[i]),"~", names(bodyframe[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(bodyframe[[i]]~droplevels(bodyframe[[1]]), data=bodyframe, ylab=names(bodyframe[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(bodyframe[[i]], bodyframe[,1], mean)
points(means, col="red")
dev.off()
}
#Both box plot
bothframe<-subset(prfdataframe, prfdataframe$Technique=="both_swum_weighted" | prfdataframe$Technique == "both_bow_boolean_weighted"
| prfdataframe$Technique == "both_bow_tf" | prfdataframe$Technique == "both_bow_tf_weigthed")
for (i in 5:8) {
bothframe[,1]<-with(bothframe, reorder(bothframe[,1], bothframe[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsAOC/", "Both_", names(bothframe[i]), "_",
names(bothframe[1]), "_","boxplot.pdf", sep="")
main<-paste(names(bothframe[i]),"~", names(bothframe[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(bothframe[[i]]~droplevels(bothframe[[1]]), data=bothframe, ylab=names(bothframe[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(bothframe[[i]], bothframe[,1], mean)
points(means, col="red")
dev.off()
}
#----------------------------------------------RHINO BOXPLOTS
#------------------------------------------------------------
dir.create(paste(outputdir, "/BoxplotsRhino",sep=""), showWarnings = FALSE)
#loop to create boxplots (map/p/r/f vs technique and concern)
for (i in 4:7) {
for (x in 1:2) {
prfdataframe2[,x]<-with(prfdataframe2, reorder(prfdataframe2[,x], prfdataframe2[[i]], mean))
name<-paste(outputdir, "/BoxplotsRhino/", names(prfdataframe2[i]), "_",
names(prfdataframe2[x]), "boxplot.pdf", sep="")
main<-paste(names(prfdataframe2[i]),"~", names(prfdataframe2[x]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(prfdataframe2[[i]]~prfdataframe2[[x]], data=prfdataframe2, ylab=names(prfdataframe2[i]), col="lightgray",
las=2, main=main, cex.axis=1)
means<-tapply(prfdataframe2[[i]], prfdataframe2[,x], mean)
points(means, col="red")
dev.off()
}
}
#creates directory to store boxplots
dir.create(paste(outputdir, "/BoxplotsByConcernRhino", sep=""), showWarnings = FALSE)
#loop to create boxplots (map/p/r/f vs technique by one concern at a time)
for (c in levels(prfdataframe2$Concern)) {
concernframe2<-subset(prfdataframe2, prfdataframe2$Concern == c)
for (i in 4:7) {
concernframe2[,1]<-with(concernframe2, reorder(concernframe2[,1], concernframe2[[i]], mean))
name<-paste(outputdir, "/BoxplotsByConcernRhino/", names(concernframe2[i]), "_",
names(concernframe2[1]), "_", c,"_","boxplot.pdf", sep="")
main<-paste(names(concernframe2[i]),"~", names(concernframe2[1]), "(", c, ")", sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(concernframe2[[i]]~concernframe2[[1]], data=concernframe2, ylab=names(concernframe2[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(concernframe2[[i]], concernframe2[,1], mean)
points(means, col="red")
dev.off()
}
}
#direcory for paired boxplots
dir.create(paste(outputdir, "/PairedBoxplotsRhino", sep=""), showWarnings = FALSE)
#Sig-Only box plot
sigframe2<-subset(prfdataframe2, prfdataframe2$Technique=="sig_swum" | prfdataframe2$Technique == "sig_at"
| prfdataframe2$Technique == "sig_bow_tf" | prfdataframe2$Technique == "sig_bow_boolean")
for (i in 4:7) {
sigframe2[,1]<-with(sigframe2, reorder(sigframe2[,1], sigframe2[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsRhino/", "SigOnly_", names(sigframe2[i]), "_",
names(sigframe2[1]), "_","boxplot.pdf", sep="")
main<-paste(names(sigframe2[i]),"~", names(sigframe2[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(sigframe2[[i]]~droplevels(sigframe2[[1]]), data=sigframe2, ylab=names(sigframe2[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(sigframe2[[i]], sigframe2[,1], mean)
points(means, col="red")
dev.off()
}
#Body-Only box plot
bodyframe2<-subset(prfdataframe2, prfdataframe2$Technique=="body_swum" | prfdataframe2$Technique == "body_bow_boolean"
| prfdataframe2$Technique == "body_bow_tf")
for (i in 4:7) {
bodyframe2[,1]<-with(bodyframe2, reorder(bodyframe2[,1], bodyframe2[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsRhino/", "BodyOnly_", names(bodyframe2[i]), "_",
names(bodyframe2[1]), "_","boxplot.pdf", sep="")
main<-paste(names(bodyframe2[i]),"~", names(bodyframe2[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(bodyframe2[[i]]~droplevels(bodyframe2[[1]]), data=bodyframe2, ylab=names(bodyframe2[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(bodyframe2[[i]], bodyframe2[,1], mean)
points(means, col="red")
dev.off()
}
#Both box plot
bothframe2<-subset(prfdataframe2, prfdataframe2$Technique=="both_swum_weighted" | prfdataframe2$Technique == "both_bow_boolean_weighted"
| prfdataframe2$Technique == "both_bow_tf" | prfdataframe2$Technique == "both_bow_tf_weighted")
for (i in 4:7) {
bothframe2[,1]<-with(bothframe2, reorder(bothframe2[,1], bothframe2[[i]], mean))
name<-paste(outputdir, "/PairedBoxplotsRhino/", "Both_", names(bothframe2[i]), "_",
names(bothframe2[1]), "_","boxplot.pdf", sep="")
main<-paste(names(bothframe2[i]),"~", names(bothframe2[1]), sep="")
pdf(name)
par(mar=c(13,4,2,1))
boxplot(bothframe2[[i]]~droplevels(bothframe2[[1]]), data=bothframe2, ylab=names(bothframe2[i]),
col="lightgray", las=2, main=main, cex.axis=1)
means<-tapply(bothframe2[[i]], bothframe2[,1], mean)
points(means, col="red")
dev.off()
}
dir.create(paste(outputdir, "/DistributionsAOC",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsAOC/BodyOnly",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsAOC/SigOnly",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsAOC/BodySig",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsRhino",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsRhino/BodyOnly",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsRhino/SigOnly",sep=""), showWarnings = FALSE)
dir.create(paste(outputdir, "/DistributionsRhino/BodySig",sep=""), showWarnings = FALSE)
pdf(paste(outputdir, "/DistributionsAOC/all_F.pdf", sep=""))
hist(prfdataframe$F, main="ALL_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/all_R.pdf", sep=""))
hist(prfdataframe$R, main="ALL_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/all_P.pdf", sep=""))
hist(prfdataframe$P, main="ALL_P", xlab="P")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/all_MAP.pdf", sep=""))
hist(prfdataframe$MAP, main="ALL_MAP", xlab="MAP")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/all_F.pdf", sep=""))
hist(prfdataframe$F, main="ALL_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/all_R.pdf", sep=""))
hist(prfdataframe$R, main="ALL_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/all_P.pdf", sep=""))
hist(prfdataframe$P, main="ALL_P", xlab="P")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/all_MAP.pdf", sep=""))
hist(prfdataframe$MAP, main="ALL_MAP", xlab="MAP")
dev.off()
bodyframe<-subset(prfdataframe, prfdataframe$Location=="body")
pdf(paste(outputdir, "/DistributionsAOC/BodyOnly/F.pdf", sep=""))
hist(bodyframe$F, main="BodyOnly_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodyOnly/R.pdf", sep=""))
hist(bodyframe$R, main="BodyOnly_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodyOnly/P.pdf", sep=""))
hist(bodyframe$P, main="BodyOnly_P", xlab="P")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodyOnly/MAP.pdf", sep=""))
hist(bodyframe$MAP, main="BodyOnly_MAP", xlab="MAP")
dev.off()
sigframe<-subset(prfdataframe, prfdataframe$Location=="sig")
pdf(paste(outputdir, "/DistributionsAOC/SigOnly/F.pdf", sep=""))
hist(sigframe$F, main="SigOnly_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/SigOnly/R.pdf", sep=""))
hist(sigframe$R, main="SigOnly_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/SigOnly/P.pdf", sep=""))
hist(sigframe$P, main="SigOnly_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/SigOnly/MAP.pdf", sep=""))
hist(sigframe$MAP, main="SigOnly_MAP", xlab="MAP")
dev.off()
sigbodyframe<-subset(prfdataframe, prfdataframe$Location=="both")
pdf(paste(outputdir, "/DistributionsAOC/BodySig/F.pdf", sep=""))
hist(sigbodyframe$F, main="BodySig_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodySig/R.pdf", sep=""))
hist(sigbodyframe$R, main="BodySig_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodySig/P.pdf", sep=""))
hist(sigbodyframe$P, main="BodySig_P", xlab="P")
dev.off()
pdf(paste(outputdir, "/DistributionsAOC/BodySig/MAP.pdf", sep=""))
hist(sigbodyframe$MAP, main="BodySig_MAP", xlab="MAP")
dev.off()
#
bodyframe2<-subset(prfdataframe2, prfdataframe2$Location=="body")
pdf(paste(outputdir, "/DistributionsRhino/BodyOnly/F.pdf", sep=""))
hist(bodyframe2$F, main="BodyOnly_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/BodyOnly/R.pdf", sep=""))
hist(bodyframe2$R, main="BodyOnly_R", xlab="R")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/BodyOnly/P.pdf", sep=""))
hist(bodyframe2$P, main="BodyOnly_P", xlab="P")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/BodyOnly/MAP.pdf", sep=""))
hist(bodyframe2$MAP, main="BodyOnly_MAP", xlab="MAP")
dev.off()
sigframe2<-subset(prfdataframe2, prfdataframe2$Location=="sig")
pdf(paste(outputdir, "/DistributionsRhino/SigOnly/F.pdf", sep=""))
hist(sigframe$F, main="SigOnly_F", xlab="F")
dev.off()
pdf(paste(outputdir, "/DistributionsRhino/SigOnly/R.pdf", sep=""))
hist(sigframe2$R, main="SigOnly_R", xlab="R")
dev.off()