Add check_consistency.py, correct two stale figures in comments

check_consistency.py asserts every headline number against its raw CSV,
so a stale quoted value fails loudly instead of surviving a revision. It
skips the manuscript-side assertions when main.tex is absent, which is
the case in this package.

The blind-versus-permutation agreement is 0.002, not 0.0015, and the
resource-matched OMA is undefined below L=16 rather than wherever 16/L
is not an integer.

code/check_consistency.py

@@ -0,0 +1,93 @@
+# -*- coding: utf-8 -*-
+"""Final consistency check: every headline number vs its raw CSV."""
+import csv
+import math
+import re
+from pathlib import Path
+
+base = Path(__file__).resolve().parents[1]
+# The manuscript is not part of the reproducibility package, so the
+# tex-side assertions are skipped when it is absent and the data-side
+# assertions still run.
+_tex_path = base / "main.tex"
+HAVE_TEX = _tex_path.exists()
+tex = _tex_path.read_text(encoding="utf-8") if HAVE_TEX else ""
+
+
+def rows(name):
+    with open(base / "data" / name) as f:
+        return list(csv.DictReader(f))
+
+
+def col(name, k):
+    return [float(r[k]) for r in rows(name) if r[k] != "nan"]
+
+
+ok = True
+
+
+def chk(label, cond, detail, needs_tex=False):
+    global ok
+    if needs_tex and not HAVE_TEX:
+        print("  SKIP  " + label + " :: main.tex not in this package")
+        return
+    print(("  PASS  " if cond else "  FAIL  ") + label + " :: " + detail)
+    if not cond:
+        ok = False
+
+
+print("headline numbers vs raw data")
+
+# 1.27x key-length ratio
+k = rows("sec_keylen.csv")
+r64 = [x for x in k if int(x["L"]) == 64][0]
+ratio = float(r64["oma"]) / float(r64["legit_ser"])
+chk("key-length ratio 1.27", round(ratio, 2) == 1.27, "%.4f" % ratio)
+chk("1.27 in tex", tex.count("1.27") >= 2, "%d occurrences" % tex.count("1.27"), needs_tex=True)
+
+# blind-jammer gap
+g = col("sec_jam_gap.csv", "gap_db")
+chk("gap 7.4-8.1 dB", round(min(g), 1) == 7.4 and round(max(g), 1) == 8.1,
+    "%.3f to %.3f" % (min(g), max(g)))
+chk("no stale 8.5 dB", "8.5$~dB" not in tex, "searched tex", needs_tex=True)
+lin = (10 ** (min(g) / 10), 10 ** (max(g) / 10))
+chk("about six times power", lin[0] < 6.5 and lin[1] > 5.5,
+    "%.2f to %.2f" % lin)
+
+# blind vs permutation
+j = rows("sec_jam_cmp.csv")
+dmax = max(abs(float(r["blind"]) - float(r["perm_blind"])) for r in j)
+chk("within 0.002", dmax <= 0.002, "%.5f" % dmax)
+chk("no stale 0.0015 in jamming", "$0.0015$ of the proposed" not in tex, "ok", needs_tex=True)
+
+# brute force
+b = rows("sec_brute_cmp.csv")
+sm = float(b[-1]["ser_mask"])
+chk("brute 0.76 both places", tex.count("$0.76$") >= 2, "%.4f measured" % sm, needs_tex=True)
+chk("no stale 0.75 in summary",
+    "$0.75$ after $10^{6}$" not in tex, "summary row", needs_tex=True)
+
+# refresh
+rs = {r["scheme"]: r for r in rows("refresh_summary.csv")}
+chk("refresh 64.8 bits",
+    round(float(rs["Invariant"]["entropy_bits"]), 1) == 64.8,
+    "%.3f" % float(rs["Invariant"]["entropy_bits"]))
+chk("fixed key 15.0 bits",
+    round(float(rs["None (fixed key)"]["entropy_bits"]), 1) == 15.0,
+    "%.4f" % float(rs["None (fixed key)"]["entropy_bits"]))
+
+# permutation KPA
+pk = rows("pkpa.csv")
+p6 = float([r for r in pk if r["n_frames"] == "6"][0]["eve_ser"])
+chk("perm KPA at N=6 near 0.303", abs(p6 - 0.303) < 0.005, "%.4f" % p6)
+
+# abstract
+a = (tex.split(r"\begin{abstract}")[1].split(r"\end{abstract}")[0].strip()
+     if HAVE_TEX else "")
+w = len(re.split(r"\s+", a)) if a else 0
+chk("abstract <= 250 words", w <= 250, "%d words" % w, needs_tex=True)
+chk("abstract has no abbreviations",
+    not re.findall(r"\b[A-Z]{2,}\b", a), str(re.findall(r"\b[A-Z]{2,}\b", a)), needs_tex=True)
+
+print()
+print("ALL CONSISTENT" if ok else "INCONSISTENCIES FOUND")

code/replot_security.py

@@ -136,7 +136,7 @@ def fig_snr():
 
 def fig_keylen():
     """The OMA reference is the resource-matched one of oma_ser_keylen,
-    which is undefined at key lengths where 16/L is not an integer; those
+    which is undefined below L=16 unless 16/L is an integer; those
     rows carry nan and are skipped."""
     r = load("sec_keylen.csv")
     x = col(r, "L", int)
@@ -169,7 +169,7 @@ def fig_jam():
             markevery=me, label=LBL["mask"] + ", matched")
     ax.plot(x, col(r, "oma_targeted"), color=C_PUB, marker="^", ls=":",
             markevery=me, label=LBL["oma"] + ", targeted")
-    # the two blind curves agree to 0.0015; deliberate layering
+    # the two blind curves agree to 0.002; deliberate layering
     ax.plot(x, col(r, "blind"), color=C_LEGIT, marker="o", ls="-",
             markevery=me, label=LBL["mask"] + ", blind", **UNDER)
     ax.plot(x, col(r, "perm_blind"), color=C_EVE, marker="s", ls="-.",