Index: doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.README.txt
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--- doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.README.txt	(revision eeefc0ce7b34d6158108a35960cd5f58cbed09fa)
+++ doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.README.txt	(revision eeefc0ce7b34d6158108a35960cd5f58cbed09fa)
@@ -0,0 +1,22 @@
+The overhead-amount numbers are produced in MS Excel, to fast-track a data exploration result "into production."
+The python script overlays them onto the data that gives the location at which they should be drawn.
+
+[string-separate-compilation-overhead.xlsx]
+'Raw' tab
+- side-by-side pastes of
+  A-I, b.*: result-allocate-speed-cfa.csv
+  J-R, ns.*: result-allocate-speed-cfa-NOSEPCOMP.csv
+- with calculated columns in S+
+- cmp.chk verifies the pastes line up
+- cmp.DeltaOpDur is the key output: nanoseconds by which NoSepCmp beats Baseline
+'Agg' tab
+- power query on raw: group by {corp-len-grp, tun}; each group has 5 repeat runs
+- a group's mean cmp.DeltaOpDur is the NoSepCmp advantage at this corpus length and tuning choice
+last tab
+- pick just the two overhead cases that the graph uses; project only the overhead delta
+- the groups (50, 0.2) and (200, 0.2) correspond to the pair of CFA configurations in plot-string-allocn-attrib
+- export as %.csv 
+
+[string-separate-compilation-overhead.csv]
+- export of %.xlsx, last tab
+- input to the "usual" Python script
Index: doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.csv
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--- doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.csv	(revision eeefc0ce7b34d6158108a35960cd5f58cbed09fa)
+++ doc/theses/mike_brooks_MMath/benchmarks/string/string-separate-compilation-overhead.csv	(revision eeefc0ce7b34d6158108a35960cd5f58cbed09fa)
@@ -0,0 +1,3 @@
+size,tuning,key,mean DeltaOpDur
+50,0.2,50:0.2,1.935964369
+200,0.2,200:0.2,4.526384769