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research: Dütsch analysis — Morison fit per force candidate, explicit --reference

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Co-Authored-By: Claude Opus 5.5 <noreply@anthropic.com>
This commit is contained in:
Claude
2026-10-30 10:58:48 +00:00
co-authored by Claude Opus 5.5
parent b31a6141b3
commit 73c2f507f4
1 changed files with 25 additions and 7 deletions
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research/duetsch_re100_kc5/analyze.py
+25 -7
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@@ -62,11 +62,18 @@ def common_points(dicts):
return sorted(keys)
def cycle_morison(case, ks):
def candidates(case):
"""Per-step Fx of each reported force candidate (none is selected as an RHS)."""
d = case["diag"]
return {"cme": d[:, 0], "cme_wen": d[:, 0] + d[:, 2], "cme_node": d[:, 0] + d[:, 6] - d[:, 9]}
def cycle_morison(case, ks, fx=None):
T = case["T"]
idx = np.concatenate([np.arange(len(case["force"]))[cycle_slices(case)[k]] for k in ks])
fx = case["force"][:, 0] if fx is None else fx
idx = np.concatenate([np.arange(len(fx))[cycle_slices(case)[k]] for k in ks])
b = np.array([p.interval_bases(int(m), T) for m in idx])
return p.morison_fit(case["force"][idx, 0] / case["F_ref"], b[:, 0], b[:, 1])
return p.morison_fit(fx[idx] / case["F_ref"], b[:, 0], b[:, 1])
def pair_metrics(case, k):
@@ -91,7 +98,14 @@ def ledger(case):
return pairs, p.settled_start({k: v["pass"] for k, v in pairs.items()})
def main(paths):
def main(argv):
"""argv: CASE_DIR ... [--reference CASE_DIR]; the reference defaults to the
largest D (resolution ladder); domain runs name the 60 D case explicitly."""
ref_path = None
if "--reference" in argv:
i = argv.index("--reference")
ref_path, argv = argv[i + 1], argv[:i] + argv[i + 2:]
paths = argv if ref_path is None or ref_path in argv else argv + [ref_path]
cases = [load(path) for path in paths]
ledgers = [ledger(c) for c in cases]
window = p.common_window([k for _, k in ledgers],
@@ -104,15 +118,19 @@ def main(paths):
coverage={k: coverage(case, k) for k in sorted(cycle_slices(case)) if k > p.DISCARD},
no_donor=float(case["diag"][:, 13].sum()), eq_only=float(case["diag"][:, 12].sum()))
if window:
entry["morison"] = cycle_morison(case, window)
entry["morison_obs"] = cycle_morison(case, window)
entry["morison"] = {name: cycle_morison(case, window, fx)
for name, fx in candidates(case).items()}
entry["fy_mean"] = float(np.mean(np.concatenate(
[case["force"][cycle_slices(case)[k], 1] for k in window])) / case["F_ref"])
report["cases"].append(entry)
if window and len(cases) > 1: # cross-resolution waveform against the finest case
fine = max(cases, key=lambda c: c["D"])
fine = (next(c for c in cases if c["path"] == ref_path) if ref_path
else max(cases, key=lambda c: c["D"]))
report["reference"] = fine["path"]
ref = np.concatenate([coarse_wave(fine, k) for k in window])
for case, entry in zip(cases, report["cases"]):
r = fine["T"] // case["T"]
r = fine["T"] // case["T"] # 1 for equal-D domain runs
ref_c = ref.reshape(-1, r).mean(axis=1)
own = np.concatenate([coarse_wave(case, k) for k in window])
entry["wave_rms_vs_finest"] = float(np.sqrt(np.mean((own - ref_c) ** 2)))