eval script wrangeling
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@ -1,10 +1,10 @@
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import csv
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import os
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def_flags="--no-default-features --features std,snapshot_restore,singlecore,restarting"
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remote="mnt/"
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RUNTIME=21600
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TARGET_REPS_A=20
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TARGET_REPS_B=10
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def_flags="--no-default-features --features std,snapshot_restore,singlecore,restarting,run_until_saturation"
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remote="timedump_253048_1873f6_all/"
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RUNTIME=10
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TARGET_REPS_A=2
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TARGET_REPS_B=2
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NUM_NODES=2
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REP_PER_NODE_A=int(TARGET_REPS_A/NUM_NODES)
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REP_PER_NODE_B=int(TARGET_REPS_B/NUM_NODES)
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@ -48,6 +48,12 @@ rule build_state:
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shell:
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"cargo build --target-dir {output} {def_flags},feed_systemtrace"
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rule build_nohashstate:
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output:
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directory("bins/target_nohashstate")
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shell:
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"cargo build --target-dir {output} {def_flags},feed_systemtrace,no_hash_state"
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rule build_graph:
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output:
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directory("bins/target_graph")
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@ -72,6 +78,12 @@ rule build_state_int:
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shell:
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"cargo build --target-dir {output} {def_flags},feed_systemtrace,fuzz_int"
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rule build_nohashstate_int:
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output:
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directory("bins/target_nohashstate_int")
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shell:
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"cargo build --target-dir {output} {def_flags},feed_systemtrace,fuzz_int,no_hash_state"
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rule build_frafl_int:
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output:
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directory("bins/target_frafl_int")
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@ -12,7 +12,7 @@ args = commandArgs(trailingOnly=TRUE)
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if (length(args)==0) {
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runtype="timedump_253048_1873f6_all/timedump"
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target="waters"
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target="waters_int"
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outputpath="~/code/FRET/LibAFL/fuzzers/FRET/benchmark/"
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#MY_SELECTION <- c('state', 'afl', 'graph', 'random')
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SAVE_FILE=TRUE
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@ -38,9 +38,9 @@ PATTERNS="%s.[0-9]*$"
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#RIBBON='span'
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RIBBON='both'
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DRAW_WC = worst_case > 0
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LEGEND_POS="topleft"
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LEGEND_POS="topright"
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#LEGEND_POS="bottomright"
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CONTINUE_LINE_TO_END=TRUE
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CONTINUE_LINE_TO_END=FALSE
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# https://www.r-bloggers.com/2013/04/how-to-change-the-alpha-value-of-colours-in-r/
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alpha <- function(col, alpha=1){
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@ -103,6 +103,9 @@ trace2maxpoints <- function(tr) {
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minval = tr[i,1]
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}
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}
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tmp = tr[dim(tr)[1],]
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tmp[1] = minval[1]
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collect = rbind(collect,tmp)
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return(collect)
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}
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@ -170,8 +173,8 @@ all_maxlines <- foreach (rtt=all_runtypetables) %do% {
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}
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#runtypetables_sampled = lapply(rtt, function(v) sample_maxpoints(v, all_points)[1])
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tmp_frame <- Reduce(cbind, runtypetables_sampled)
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statframe <- data.frame(rowMeans(tmp_frame),apply(tmp_frame, 1, sd),apply(tmp_frame, 1, min),apply(tmp_frame, 1, max))
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names(statframe) <- c(bn, sprintf("%s_sd",bn), sprintf("%s_min",bn), sprintf("%s_max",bn))
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statframe <- data.frame(rowMeans(tmp_frame),apply(tmp_frame, 1, sd),apply(tmp_frame, 1, min),apply(tmp_frame, 1, max), apply(tmp_frame, 1, median))
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names(statframe) <- c(bn, sprintf("%s_sd",bn), sprintf("%s_min",bn), sprintf("%s_max",bn), sprintf("%s_med",bn))
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#statframe[sprintf("%s_times",bn)] = all_points
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round(statframe)
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#all_maxlines = c(all_maxlines, list(round(statframe)))
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@ -182,6 +185,7 @@ names(one_frame)[length(one_frame)] <- 'time'
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typenames = names(one_frame)[which(names(one_frame) != 'time')]
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typenames = typenames[which(!endsWith(typenames, "_sd"))]
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typenames = typenames[which(!endsWith(typenames, "_med"))]
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ylow=min(one_frame[typenames])
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yhigh=max(one_frame[typenames],worst_case)
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typenames = typenames[which(!endsWith(typenames, "_min"))]
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@ -205,6 +209,7 @@ plotting <- function(selection, filename, MY_COLORS_) {
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# filter out names of iters and sd cols
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typenames = names(one_frame)[which(names(one_frame) != 'times')]
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typenames = typenames[which(!endsWith(typenames, "_sd"))]
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typenames = typenames[which(!endsWith(typenames, "_med"))]
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typenames = typenames[which(!endsWith(typenames, "_min"))]
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typenames = typenames[which(!endsWith(typenames, "_max"))]
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typenames = selection[which(selection %in% typenames)]
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@ -220,34 +225,61 @@ par(oma=c(0,0,0,0))
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plot(c(1,max(one_frame['time'])),c(ylow,yhigh), col='white', xlab="Time [h]", ylab="WORT [insn]", pch='.')
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for (t in seq_len(length(typenames))) {
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proj = one_frame[seq(1, dim(one_frame)[1], by=max(1, length(one_frame[[1]])/(10*w_))),]
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#proj = one_frame[seq(1, dim(one_frame)[1], by=max(1, length(one_frame[[1]])/(10*w_))),]
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#points(proj[c('iters',typenames[t])], col=MY_COLORS_[t], pch='.')
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avglines = ml2lines(one_frame[c(typenames[t],'time')],all_max_points[typenames[t]])
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lines(avglines, col=MY_COLORS_[t])
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if (exists("RIBBON") && ( RIBBON=='both' || RIBBON=='span')) {
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#lines(avglines, col=MY_COLORS_[t])
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medlines = ml2lines(one_frame[c(sprintf("%s_med",typenames[t]),'time')],all_max_points[typenames[t]])
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lines(medlines, col=MY_COLORS_[t], lty='solid')
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milines = NULL
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malines = NULL
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milines = ml2lines(one_frame[c(sprintf("%s_min",typenames[t]),'time')],all_max_points[typenames[t]])
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malines = ml2lines(one_frame[c(sprintf("%s_max",typenames[t]),'time')],all_max_points[typenames[t]])
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lines(milines, col=MY_COLORS_[t], lty='dashed')
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if (exists("RIBBON") && ( RIBBON=='max' )) {
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#lines(milines, col=MY_COLORS_[t], lty='dashed')
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lines(malines, col=MY_COLORS_[t], lty='dashed')
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#points(proj[c('iters',sprintf("%s_min",typenames[t]))], col=MY_COLORS_[t], pch='.')
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#points(proj[c('iters',sprintf("%s_max",typenames[t]))], col=MY_COLORS_[t], pch='.')
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}
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if (exists("RIBBON") && RIBBON != '') {
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for (i in seq_len(dim(proj)[1])) {
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row = proj[i,]
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x_ <- row['time'][[1]]
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y_ <- row[typenames[t]][[1]]
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sd_ <- row[sprintf("%s_sd",typenames[t])][[1]]
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min_ <- row[sprintf("%s_min",typenames[t])][[1]]
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max_ <- row[sprintf("%s_max",typenames[t])][[1]]
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if (exists("RIBBON")) {
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switch (RIBBON,
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'sd' = arrows(x_, y_-sd_, x_, y_+sd_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.03)),
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'both' = arrows(x_, y_-sd_, x_, y_+sd_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.05)),
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'span' = #arrows(x_, min_, x_, max_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.03))
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)
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for (i in seq_len(dim(avglines)[1]-1)) {
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if (RIBBON=='both') {
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# draw boxes
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x_l <- milines[i,][['X']]
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x_r <- milines[i+1,][['X']]
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y_l <- milines[i,][['Y']]
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y_h <- malines[i,][['Y']]
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rect(x_l, y_l, x_r, y_h, col=alpha(MY_COLORS_[t], alpha=0.1), lwd=0)
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}
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#arrows(x_, y_-sd_, x_, y_+sd_, length=0.05, angle=90, code=3, col=alpha(MY_COLORS[t], alpha=0.1))
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if (FALSE && RIBBON=='span') {
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# draw boxes
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x_l <- milines[i,][['X']]
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x_r <- milines[i+1,][['X']]
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y_l <- milines[i,][['Y']]
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y_h <- malines[i,][['Y']]
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rect(x_l, y_l, x_r, y_h, col=alpha(MY_COLORS_[t], alpha=0.1), lwd=0)
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}
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#if (FALSE && RIBBON=='both' || RIBBON=='sd') {
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# # draw sd
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# x_l <- avglines[i,][['X']]
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# x_r <- avglines[i+1,][['X']]
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# y_l <- avglines[i,][['Y']]-one_frame[ceiling(i/2),][[sprintf("%s_sd",typenames[t])]]
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# y_h <- avglines[i,][['Y']]+one_frame[ceiling(i/2),][[sprintf("%s_sd",typenames[t])]]
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# if (x_r != x_l) {
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# rect(x_l, y_l, x_r, y_h, col=alpha(MY_COLORS_[t], alpha=0.1), lwd=0)
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# }
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#}
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#sd_ <- row[sprintf("%s_sd",typenames[t])][[1]]
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#min_ <- row[sprintf("%s_min",typenames[t])][[1]]
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#max_ <- row[sprintf("%s_max",typenames[t])][[1]]
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#if (exists("RIBBON")) {
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# switch (RIBBON,
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# 'sd' = arrows(x_, y_-sd_, x_, y_+sd_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.03)),
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# 'both' = arrows(x_, y_-sd_, x_, y_+sd_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.05)),
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# 'span' = #arrows(x_, min_, x_, max_, length=0, angle=90, code=3, col=alpha(MY_COLORS_[t], alpha=0.03))
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# )
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#}
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##arrows(x_, y_-sd_, x_, y_+sd_, length=0.05, angle=90, code=3, col=alpha(MY_COLORS[t], alpha=0.1))
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}
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}
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}
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@ -266,20 +298,30 @@ stopCluster(cl)
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par(mar=c(3.8,3.8,0,0))
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par(oma=c(0,0,0,0))
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#RIBBON='both'
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#MY_SELECTION = c('state_int','generation100_int')
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#MY_SELECTION = c('state_int','frafl_int')
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if (exists("MY_SELECTION")) {
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plotting(MY_SELECTION, 'custom', MY_COLORS)
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plotting(MY_SELECTION, 'custom', MY_COLORS[c(1,2)])
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} else {
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MY_SELECTION=c('state', 'afl', 'random', 'feedlongest', 'feedgeneration', 'feedgeneration10')
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# MY_SELECTION=c('state', 'afl', 'random', 'feedlongest', 'feedgeneration', 'feedgeneration10')
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#MY_SELECTION=c('state_int', 'afl_int', 'random_int', 'feedlongest_int', 'feedgeneration_int', 'feedgeneration10_int')
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#MY_SELECTION=c('state', 'frAFL', 'statenohash', 'feedgeneration10')
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#MY_SELECTION=c('state_int', 'frAFL_int', 'statenohash_int', 'feedgeneration10_int')
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MY_SELECTION=typenames
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RIBBON='span'
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RIBBON='both'
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for (i in seq_len(length(MY_SELECTION))) {
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n <- MY_SELECTION[i]
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plotting(c(n), n, c(MY_COLORS[i]))
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}
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RIBBON='span'
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RIBBON='max'
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plotting(MY_SELECTION,'all', MY_COLORS)
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}
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for (t in seq_len(length(typenames))) {
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li = one_frame[dim(one_frame)[1],]
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pear = (li[[typenames[[t]]]]-li[[sprintf("%s_med",typenames[[t]])]])/li[[sprintf("%s_sd",typenames[[t]])]]
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print(sprintf("%s pearson: %g",typenames[[t]],pear))
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}
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