Index: doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.d
===================================================================
--- doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.d	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
+++ doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.d	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
@@ -0,0 +1,2 @@
+plots/string-peq-cppemu.gp.INPUTS: build/plot-string-peq-cppemu.dat | build
+plots/string-peq-cppemu.py.INPUTS: benchmarks/string/result-append-pbv.csv
Index: doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.gp
===================================================================
--- doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.gp	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
+++ doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.gp	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
@@ -0,0 +1,25 @@
+set terminal pdf color enhanced size 6.0in,3.0in font "Times,17"
+#set terminal postscript portrait enhanced size 7.5, 10. color solid 9.5;
+#set terminal wxt size 950,1250
+
+INDIR="build"
+OUTDIR="build"
+
+set macros
+set output OUTDIR."/plot-string-peq-cppemu.pdf"
+#set pointsize 2.0
+set grid
+set key top left
+set xtics (1,2,5,10,20,50,100,200,500)
+set logscale x
+set logscale y
+set yrange [10:200]
+set xlabel "String Length being appended (mean, geo. dist.), log scale" offset 2,0
+set ylabel "Time per append (ns, mean)"
+set linetype 2 dashtype 2
+set linetype 4 dashtype 2
+plot INDIR."/plot-string-peq-cppemu.dat" \
+	   i 0 using 1:2 title columnheader(1) with linespoints lt rgb "red"	pt  2  ps 1 lw 1, \
+	'' i 1 using 1:2 title columnheader(1) with linespoints lt rgb "red"	pt  3  ps 1 lw 1, \
+	'' i 2 using 1:2 title columnheader(1) with linespoints lt rgb "blue"	pt  6  ps 1 lw 1, \
+	'' i 3  using 1:2 title columnheader(1) with linespoints lt rgb "blue"	pt  8  ps 1 lw 1
Index: doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.py
===================================================================
--- doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.py	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
+++ doc/theses/mike_brooks_MMath/plots/string-peq-cppemu.py	(revision f85de474d7bae82407a8ea5f1551da282d77d9bd)
@@ -0,0 +1,89 @@
+# Read thesis-append-pbv.csv
+# Output for string-graph-peq-cppemu.dat
+
+# Project details
+# Filter operation=peq
+# Split "series" goups of sut; only those in the "pretty" list
+# Assert one row per string-length
+# output:
+# string-len op-duration
+# in chunks, each headed by pertty(sut)
+
+import pandas as pd
+import numpy as np
+import os
+
+infile = os.path.dirname(os.path.abspath(__file__)) + '/../benchmarks/string/result-append-pbv.csv'
+
+prettyFieldNames = {
+    "cfa-ll-noshare-fresh": "{/Helvetica=15 C{/Symbol \\42} +=} noshare fresh",
+    "cfa-ll-noshare-reuse": "{/Helvetica=15 C{/Symbol \\42} +=} noshare reuse",
+    "stl-na-na-fresh": "STL {/Helvetica=15 +=} fresh",
+    "stl-na-na-reuse": "STL {/Helvetica=15 +=} reuse",
+}
+
+timings = pd.read_csv(
+    infile,
+    names=['test', 'corpus', 'concatsPerReset', 'corpusItemCount', 'corpusMeanLenChars', 'concatDoneActualCount', 'execTimeActualSec'],
+    dtype={'test':                  str,
+           'corpus':                str,
+           'concatsPerReset':       'Int64', # allows missing; https://stackoverflow.com/a/70626154
+           'corpusItemCount':       np.int64,
+           'corpusMeanLenChars':    np.float64,
+           'concatDoneActualCount': np.int64,
+           'execTimeActualSec':     np.float64},
+    na_values=['xxx'],
+)
+# print(timings.head())
+
+
+# project: parse executable and corpus names
+
+timings[['test-slug',
+     'sut-platform',
+     'operation',
+     'sut-cfa-level',
+     'sut-cfa-sharing',
+     'op-alloc']] = timings['test'].str.strip().str.split('-', expand=True)
+timings['sut'] = timings[['sut-platform',
+                    'sut-cfa-level',
+                    'sut-cfa-sharing',
+                    'op-alloc']].agg('-'.join, axis=1)
+
+timings[['corpus-basename',
+     'corpus-ext']] = timings['corpus'].str.strip().str.split('.', expand=True)
+timings[['corpus-slug',
+     'corpus-nstrs',
+     'corpus-meanlen',
+     'corpus-runid']] = timings['corpus-basename'].str.strip().str.split('-', expand=True)
+timings["corpus-nstrs"] = pd.to_numeric(timings["corpus-nstrs"])
+timings["corpus-meanlen"] = pd.to_numeric(timings["corpus-meanlen"])
+timings["corpus-runid"] = pd.to_numeric(timings["corpus-runid"])
+
+
+# project: calculate fact
+
+timings['op-duration-s'] = timings['execTimeActualSec'] / timings['concatDoneActualCount']
+timings['op-duration-ns'] = timings['op-duration-s'] * 1000 * 1000 * 1000
+
+
+# Filter operation=peq
+
+groupedOp = timings.groupby('operation')
+tgtOpTimings = groupedOp.get_group('peq')
+
+
+# Emit in groups
+
+groupedSut = tgtOpTimings.groupby('sut')
+
+for sut, sgroup in groupedSut:
+
+    if sut in prettyFieldNames:
+
+        sgroup_sorted = sgroup.sort_values(by='corpus-meanlen')
+
+        print('"{header}"'.format(header=prettyFieldNames[sut]))
+        text = sgroup_sorted[['corpus-meanlen', 'op-duration-ns']].to_csv(header=False, index=False, sep='\t')
+        print(text)
+        print()