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