Bugfix plotting of jobs. More details in paper.

paper/main.tex

@@ -239,12 +239,219 @@ Potentially, analyze how the rankings of different similarities look like.
 \end{subfigure}
 \centering
 \caption{Histogram for the number of jobs (bin width: 2.5\%, numbers are the actual job counts)}
-\label{fig:ecdf}
+\label{fig:hist}
+\end{figure}
+
+\subsection{Quantitative Analysis of Selected Jobs}
+
+\begin{table}
+\caption{User and Group Information}
+\end{table}
+
+\begin{figure}
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/jobs-nodes}
+\caption{Job-S} \label{fig:nodes-job-S}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/jobs-nodes}
+\caption{Job-M} \label{fig:nodes-job-M}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_7488914-out/jobs-nodes}
+\caption{Job-L} \label{fig:nodes-job-L}
+\end{subfigure}
+\centering
+\caption{Distribution of node counts}
+\label{fig:nodes-job}
+\end{figure}
+
+
+\begin{figure}
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/jobs-elapsed}
+\caption{Job-S} \label{fig:runtime-job-S}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/jobs-elapsed}
+\caption{Job-M} \label{fig:runtime-job-M}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_7488914-out/jobs-elapsed}
+\caption{Job-L} \label{fig:runtime-job-L}
+\end{subfigure}
+\centering
+\caption{Distribution of elapsed runtime}
+\label{fig:runtime-job}
+\end{figure}
+
+Different algorithms ...
+
+
+\begin{figure}
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/intersection-heatmap}
+\caption{Job-S} \label{fig:heatmap-job-S}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/intersection-heatmap}
+\caption{Job-M} \label{fig:heatmap-job-M}
+\end{subfigure}
+
+\begin{subfigure}{0.5\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_7488914-out/intersection-heatmap}
+\caption{Job-L} \label{fig:heatmap-job-L}
+\end{subfigure}
+\centering
+\caption{Intersection of the top 100 jobs for the different algorithms}
+\label{fig:heatmap-job}
+\end{figure}
+
+\section{Assessing Timelines for Similar Jobs}
+
+\subsection{Job-S}
+
+
+\begin{figure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_lev-0.9615-timeseries4297102}
+\caption{Rank 2, SIM=0.9615}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_lev-0.9017-timeseries4570701}
+\caption{Rank 15, SIM=0.9017}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_lev-0.7901-timeseries4693267}
+\caption{Rank\,100, SIM=0.790}
+\end{subfigure}
+
+\caption{Job-S with Hex-Lev, selection of similar jobs}
+\label{fig:job-S-hex-lev}
+\end{figure}
+
+
+\begin{figure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_native-0.9808-timeseries4567314}
+\caption{Rank 2, SIM=}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_native-0.9375-timeseries4709700}
+\caption{Rank 15, SIM=}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_native-0.9001-timeseries4527630}
+\caption{Rank\,100, SIM=}
+\end{subfigure}
+
+\caption{Job-S with Hex-Native, selection of similar jobs}
+\label{fig:job-S-hex-native}
 \end{figure}
 
 
 
-\section{Summary and Conclusion}
+\begin{figure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_phases-0.9153-timeseries4567314}
+\caption{Rank 2, $SIM=$ (same job as hex native Top1)}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_native-0.9268-timeseries4557849}
+\caption{Rank 15, $SIM=$}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_4296426-out/hex_phases-0.7382-timeseries4693267}
+\caption{Rank\,100, $SIM=$ }
+\end{subfigure}
+
+\caption{Job-S with Hex-Phases, selection of similar jobs}
+\label{fig:job-S-hex-phases}
+\end{figure}
+
+% \ContinuedFloat
+
+Bin aggzeros works quite well here too.
+
+
+\subsection{Job-M}
+
+
+
+\begin{figure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.7755-timeseries7907734}
+\caption{Rank 2, $SIM=$}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.7347-timeseries4244400}
+\caption{$SIM=$}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.5306-timeseries8038026}
+\caption{$SIM=$ }
+\end{subfigure}
+
+\caption{Job-M with Bin-Aggzero, selection of similar jobs}
+\label{fig:job-M-bin-aggzero}
+\end{figure}
+
+
+
+\begin{figure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.7755-timeseries7907734}
+\caption{Rank 2, $SIM=$}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.7347-timeseries4244400}
+\caption{$SIM=$}
+\end{subfigure}
+\begin{subfigure}{0.3\textwidth}
+\centering
+\includegraphics[width=\textwidth]{job_similarities_5024292-out/bin_aggzeros-0.5306-timeseries8038026}
+\caption{$SIM=$ }
+\end{subfigure}
+
+\caption{Job-M with Bin-Aggzero, selection of similar jobs}
+\label{fig:job-M-bin-aggzero}
+\end{figure}
+
+
+\subsection{Job-L}
+
+
+
+
+\section{Conclusion}
 \label{sec:summary}
 
 %\printbibliography

scripts/analyse-all.sh

@@ -1,7 +1,23 @@
 #!/bin/bash
 
 # call me from the parent directory
+
+echo "This script performs the complete analysis steps"
+
+function prepare(){
+  pushd datasets
+  ./decompress.sh
+  popd
+
+  for I in datasets/*.csv ; do
+    ln -s $I
+  done
+}
+
+# prepare
+
 for I in job_similarities_*.csv ; do
+  rm *.png *.pdf
   ./scripts/plot.R $I > description.txt
   OUT=${I%%.csv}-out
   mkdir $OUT

scripts/plot-single-job.py

@@ -12,7 +12,9 @@ prefix = sys.argv[2].split(",")
 
 fileformat = ".png"
 
-print("Plotting the job: " + str(jobs))
+print("Plotting the job: " + str(sys.argv[1]))
+print("Plotting with prefix: " + str(sys.argv[2]))
+
 
 # Color map
 colorMap = { "md_file_create": cm.tab10(0),
@@ -120,15 +122,14 @@ def plot(prefix, header, row):
 with open('job-io-datasets/datasets/job_codings.csv') as csv_file:
     csv_reader = csv.reader(csv_file, delimiter=',')
     line_count = 0
-    job = 0
     for row in csv_reader:
       if line_count == 0:
         header = row
         line_count += 1
         continue
-
+      job = row[0].strip()
-      if not row[0].strip() in jobs:
+      if not job in jobs:
         continue
       else:
-        plot(prefix[job], header, row)
+        index = jobs.index(job)
-        job += 1
+        plot(prefix[index] + "-" + str(index), header, row)

scripts/plot.R

@@ -4,7 +4,7 @@ library(ggplot2)
 library(dplyr)
 require(scales)
 
-plotjobs = FALSE
+plotjobs = TRUE
 
 # Color scheme
 plotcolors <- c("#CC0000", "#FFA500", "#FFFF00", "#008000", "#9999ff", "#000066")
@@ -53,7 +53,7 @@ plotJobs = function(jobs){
     r = e[ordered, ]
 
     if (plotjobs) {
-      prefix = do.call("sprintf", list("%s-%.0f-", level, r$similarity))
+      prefix = do.call("sprintf", list("%s-%.4f-", level, r$similarity))
       system(sprintf("scripts/plot-single-job.py %s %s", paste(r$jobid, collapse=","), paste(prefix, collapse=",")))
     }
   }
@@ -96,7 +96,7 @@ for (l1 in levels(data$alg_name)){
 print(res.intersect)
 
 # Plot heatmap about intersection
-ggplot(tbl.intersect, aes(first, second, fill=intersect)) + geom_tile() + geom_text(aes(label = round(intersect, 1))) + scale_fill_gradientn(colours = rev(plotcolors))
+ggplot(tbl.intersect, aes(first, second, fill=intersect)) + geom_tile() + geom_text(aes(label = round(intersect, 1))) + scale_fill_gradientn(colours = rev(plotcolors)) + xlab("") + ylab("")
 ggsave("intersection-heatmap.png", width=6, height=5)
 
 # Collect the metadata of all jobs in a new table
@@ -105,11 +105,11 @@ for (alg_name in levels(data$alg_name)){
   res.jobs = rbind(res.jobs, cbind(alg_name, metadata[metadata$jobid %in% result[, alg_name],]))
 }
 
-ggplot(res.jobs, aes(alg_name, total_nodes, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x)))
+ggplot(res.jobs, aes(alg_name, total_nodes, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log2", function(x) 2^x), labels = trans_format("log2", math_format(2^.x))) + theme(legend.position = "none")
-ggsave("jobs-nodes.png")
+ggsave("jobs-nodes.png", width=6, height=4)
 
-ggplot(res.jobs, aes(alg_name, elapsed, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log10", function(x) 10^x), labels = trans_format("log10", math_format(10^.x))) + ylab("Runtime in s") + xlab("Algorithm")
+ggplot(res.jobs, aes(alg_name, elapsed, fill=alg_name)) + geom_boxplot() + scale_y_continuous(trans = log2_trans(), breaks = trans_breaks("log10", function(x) 10^x), labels = trans_format("log10", math_format(10^.x))) + ylab("Runtime in s") + xlab("Algorithm")  + theme(legend.position = "none")
-ggsave("jobs-elapsed.png")
+ggsave("jobs-elapsed.png", width=6, height=4)