Add small example.

2 files changed, 139 insertions, 0 deletions

diff --git a/README b/README
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+This is a simple, quick-n-dirty wrapper for plotting .csv files with
+Gnuplot.
+
+The tool will remove comments (lines starting with a '#' character) before
+passing the data to Gnuplot. This makes it possible to have experimental
+setup and date information encoded in the .csv file, which is beneficial
+for archival reasons.
+
+You can plot the example file to a PNG graph using the following command:
+
+./gnuplot.py -o example -f png --xlabel "Time" --ylabel "Supply Bound" \
+     example.csv 1 2 "Supply Bound Function"
+
+
+In general, each curve that you want to plot in a graph is defined by four
+arguments:
+
+./gnuplot.py [OPTIONS] \
+   <file1> <xcolumn1> <ycolumn1> <title1> \
+   <file2> <xcolumn2> <ycolumn2> <title2> \
+   ... and so on ...
+
+For large experiments with many graphs, it is more convenient to wrap gnuplot.py
+in a project-specific plotting script. Have a look at plot.py and plot_ohead.py
+to see how I did it. Basically, the scrips infer what to plot and how to name
+and label the graphs from the name of each .csv file. 
+
+For example, the file name 'hard_rtss09_dist=uni_medium_250.csv' encodes the
+following information: 1) it uses hard real-time schedulability tests, it was
+using the RTSS'09 experimental setup and overheads, the task sets were generated
+with uniform utilization from the range [0.1, 0.4] (medium), and periods were
+distributed uniformly in [50, 250]. This is parsed by plot.py, which then 
+calls gnuplot.py to generate a graph with the correct labels and settings.
diff --git a/example.csv b/example.csv
new file mode 100644
index 0000000..0c70bd7
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+++ b/example.csv
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+# This is the result of sampling a simple supply bound function.
+# As defined in Sanjoy's G-EDF paper.
+
+# first column: time
+# second column: supply bound
+0, 0.000000
+1, 0.000000
+2, 0.000000
+3, 0.000000
+4, 0.000000
+5, 0.000000
+6, 0.000000
+7, 0.000000
+8, 0.000000
+9, 0.000000
+10, 0.000000
+11, 0.000000
+12, 0.000000
+13, 0.000000
+14, 0.000000
+15, 1.000000
+16, 5.000000
+17, 9.000000
+18, 9.000000
+19, 9.000000
+20, 9.000000
+21, 9.000000
+22, 9.000000
+23, 9.000000
+24, 9.000000
+25, 10.000000
+26, 14.000000
+27, 18.000000
+28, 18.000000
+29, 18.000000
+30, 18.000000
+31, 18.000000
+32, 18.000000
+33, 18.000000
+34, 18.000000
+35, 19.000000
+36, 23.000000
+37, 27.000000
+38, 27.000000
+39, 27.000000
+40, 27.000000
+41, 27.000000
+42, 27.000000
+43, 27.000000
+44, 27.000000
+45, 28.000000
+46, 32.000000
+47, 36.000000
+48, 36.000000
+49, 36.000000
+50, 36.000000
+51, 36.000000
+52, 36.000000
+53, 36.000000
+54, 36.000000
+55, 37.000000
+56, 41.000000
+57, 45.000000
+58, 45.000000
+59, 45.000000
+60, 45.000000
+61, 45.000000
+62, 45.000000
+63, 45.000000
+64, 45.000000
+65, 46.000000
+66, 50.000000
+67, 54.000000
+68, 54.000000
+69, 54.000000
+70, 54.000000
+71, 54.000000
+72, 54.000000
+73, 54.000000
+74, 54.000000
+75, 55.000000
+76, 59.000000
+77, 63.000000
+78, 63.000000
+79, 63.000000
+80, 63.000000
+81, 63.000000
+82, 63.000000
+83, 63.000000
+84, 63.000000
+85, 64.000000
+86, 68.000000
+87, 72.000000
+88, 72.000000
+89, 72.000000
+90, 72.000000
+91, 72.000000
+92, 72.000000
+93, 72.000000
+94, 72.000000
+95, 73.000000
+96, 77.000000
+97, 81.000000
+98, 81.000000
+99, 81.000000
+