diff --git a/.gitignore b/.gitignore
index 600d2d3..f0bad73 100644
--- a/.gitignore
+++ b/.gitignore
@@ -1 +1,4 @@
-.vscode
\ No newline at end of file
+.vscode
+.venv
+__pycache__/
+*.pyc
diff --git a/bench.py b/bench.py
new file mode 100644
index 0000000..ac45592
--- /dev/null
+++ b/bench.py
@@ -0,0 +1,1298 @@
+#!/usr/bin/env python
+"""Test bench for bad-frame detection and gap filling.
+
+Takes a stretch of archive verified to be clean, damages it in known ways, and
+measures how well each detector finds the damage and each filler repairs it.
+
+The archive is never modified.  Corrupted frames are written to a per-case overlay
+directory and every read goes through :class:`suvi.cases.Overlay`, so a bench run
+against live production data is safe.
+
+Workflow::
+
+    bench.py select-window --start 2024-05-05 --end 2024-05-20
+    bench.py vet-window    --name may2024 --start ... --end ...
+    bench.py make-case     --window may2024 --name mixed10 --seed 42
+    bench.py detect        --case mixed10
+    bench.py fill          --case mixed10 --oracle
+    bench.py report        --case mixed10
+
+Each step records its results in the index, so steps are resumable and comparable
+across runs.
+"""
+
+import argparse
+import datetime
+import itertools
+import json
+import os
+import sys
+import time
+from collections import defaultdict
+from multiprocessing import Pool
+
+import numpy as np
+from astropy.io import fits
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import cases, corruptions, db, detectors, fillers, fitsio, metrics, paths, vfs
+
+
+def parse_date(text):
+    """Accept YYYY-MM-DD or YYYY-MM-DDTHH:MM, always UTC."""
+    for fmt in ("%Y-%m-%d", "%Y-%m-%dT%H:%M", "%Y-%m-%d %H:%M"):
+        try:
+            stamp = datetime.datetime.strptime(text, fmt)
+            return int(stamp.replace(tzinfo=datetime.timezone.utc).timestamp())
+        except ValueError:
+            continue
+    raise argparse.ArgumentTypeError(f"Not a date: {text!r}")
+
+
+def format_time(timestamp):
+    return datetime.datetime.fromtimestamp(timestamp, datetime.timezone.utc).strftime(
+        "%Y-%m-%d %H:%M"
+    )
+
+
+def parse_int_list(text):
+    return tuple(int(part) for part in text.split(",") if part.strip())
+
+
+# ------------------------------------------------------------------- select-window
+
+
+def cmd_select_window(args):
+    root = paths.data_root()
+    satellites = parse_int_list(args.satellites)
+    wavelengths = parse_int_list(args.wavelengths)
+    print(f"Scanning {root} from {format_time(args.start)} to {format_time(args.end)}")
+    found = cases.scan_window(root, satellites, wavelengths, args.start, args.end)
+    total = len(cases.timeline(args.start, args.end))
+    print(f"  {len(found)} files across {total} slots\n")
+
+    runs = cases.find_runs(
+        found,
+        satellites,
+        wavelengths,
+        args.start,
+        args.end,
+        minimum=args.min_slots,
+        require_good_label=args.require_legacy_label,
+    )
+    if not runs:
+        print(f"No runs of >= {args.min_slots} slots complete on every requested band.")
+        print("Try fewer bands, one satellite, or a different date range.")
+        return 1
+
+    basis = "labelled good by the legacy filter" if args.require_legacy_label else "present"
+    print(f"Runs where every requested band and satellite is {basis}:")
+    print(f"{'slots':>7} {'hours':>8}  window")
+    for length, start, end in runs[: args.limit]:
+        print(f"{length:>7} {length * paths.CADENCE / 3600:>8.1f}  {format_time(start)} .. {format_time(end)}")
+    if not args.require_legacy_label:
+        print("\nCompleteness only -- run vet-window to verify quality from the headers.")
+    return 0
+
+
+# ---------------------------------------------------------------------- vet-window
+
+
+def _header_vet(path):
+    """Independent check that a frame really is good, from its header."""
+    values, error = fitsio.scan_header(path)
+    if error:
+        return False, f"header unreadable: {error}"
+    if values.get("empty"):
+        return False, "EMPTY set"
+    if values.get("eclipse"):
+        return False, f"ECLIPSE={int(values['eclipse'])}"
+    return True, None
+
+
+def cmd_vet_window(args):
+    root = paths.data_root()
+    satellites = parse_int_list(args.satellites)
+    wavelengths = parse_int_list(args.wavelengths)
+    conn = db.connect(args.db)
+
+    found = cases.scan_window(root, satellites, wavelengths, args.start, args.end)
+    slots = cases.timeline(args.start, args.end)
+    expected = len(slots) * len(satellites) * len(wavelengths)
+    print(f"Window has {len(found)}/{expected} frames present")
+
+    missing = [
+        (satellite, wavelength, time)
+        for time in slots
+        for satellite in satellites
+        for wavelength in wavelengths
+        if (satellite, wavelength, time) not in found
+    ]
+    if missing and not args.allow_missing:
+        print(f"ERROR: {len(missing)} slots have no frame at all; refusing to vet.")
+        print("       Pick a window from select-window, or pass --allow-missing.")
+        return 1
+
+    # Ground truth comes from the headers, which the instrument wrote and which are
+    # independent of any pixel filter.  The legacy filename labels are recorded for
+    # comparison but deliberately do not decide anything: they were written in May
+    # 2024 by a filter that was retuned that July, so they are neither current nor
+    # self-consistent.  Treating them as truth would bake the old filter's mistakes
+    # into every score computed against this window.
+    print("Vetting from headers...")
+    disagreements = []
+    truth = {}
+    reliever = vfs.Reliever(label="vet")
+    for index, (slot, (path, label)) in enumerate(sorted(found.items())):
+        reliever.tick()
+        good_by_header, reason = _header_vet(path)
+        good_by_legacy = label == "f"
+        if good_by_header != good_by_legacy:
+            disagreements.append((slot, label, reason))
+        truth[slot] = (good_by_header, "header")
+        if args.progress and index % 2000 == 0 and index:
+            print(f"  {index}/{len(found)}")
+
+    print(f"  {len(disagreements)} frames where the legacy label disagrees with the header")
+    for slot, label, reason in disagreements[:10]:
+        print(f"    {slot} legacy={label} header={reason or 'good'}")
+
+    good = sum(1 for is_good, _ in truth.values() if is_good)
+    print(f"  {good}/{len(truth)} frames vetted good")
+    if good < len(truth) * args.min_good_fraction:
+        print(f"ERROR: only {good / len(truth):.1%} vetted good; window is not clean enough.")
+        return 1
+
+    conn.execute(
+        """
+        INSERT INTO bench_window (name, t_start, t_end, satellites, wavelengths, vetted_at, notes)
+        VALUES (?, ?, ?, ?, ?, ?, ?)
+        ON CONFLICT (name) DO UPDATE SET
+            t_start = excluded.t_start, t_end = excluded.t_end,
+            satellites = excluded.satellites, wavelengths = excluded.wavelengths,
+            vetted_at = excluded.vetted_at, notes = excluded.notes
+        """,
+        (
+            args.name,
+            args.start,
+            args.end,
+            json.dumps(list(satellites)),
+            json.dumps(list(wavelengths)),
+            time.time(),
+            args.notes,
+        ),
+    )
+    window_id = conn.execute(
+        "SELECT id FROM bench_window WHERE name = ?", (args.name,)
+    ).fetchone()["id"]
+    conn.execute("DELETE FROM bench_truth WHERE window_id = ?", (window_id,))
+
+    for slot, (path, label) in sorted(found.items()):
+        name = paths.parse_frame_filename(os.path.basename(path))
+        relpath = name.relpath()
+        frame_id = db.upsert_frame(
+            conn, name, relpath, os.path.getsize(path), os.path.getmtime(path)
+        )
+        is_good, source = truth[slot]
+        conn.execute(
+            "INSERT OR REPLACE INTO bench_truth (window_id, frame_id, is_good, vet_source)"
+            " VALUES (?, ?, ?, ?)",
+            (window_id, frame_id, int(is_good), source),
+        )
+    conn.commit()
+    print(f"Wrote window '{args.name}' (id {window_id}) with {len(found)} frames")
+
+    if args.contact_sheet:
+        _write_contact_sheet(found, args.contact_sheet, satellites, wavelengths)
+        print(f"Contact sheet: {args.contact_sheet}")
+        print("Review it before trusting this window as ground truth.")
+    return 0
+
+
+def _write_contact_sheet(found, path, satellites, wavelengths, columns=24, size=64):
+    """A downsampled filmstrip of the window, for the one manual review pass."""
+    import matplotlib
+
+    matplotlib.use("Agg")
+    from matplotlib import pyplot as plt
+
+    satellite, wavelength = satellites[0], wavelengths[len(wavelengths) // 2]
+    series = sorted(slot for slot in found if slot[0] == satellite and slot[1] == wavelength)
+    if not series:
+        return
+    step = max(1, len(series) // (columns * 20))
+    picks = series[::step]
+    rows = (len(picks) + columns - 1) // columns
+
+    figure, axes = plt.subplots(rows, columns, figsize=(columns, rows))
+    axes = np.atleast_2d(axes)
+    vmin, vmax, gamma = metrics.DISPLAY_MAPPING[wavelength]
+    for index, slot in enumerate(picks):
+        axis = axes[index // columns][index % columns]
+        image, error = fitsio.read_image(found[slot][0])
+        if image is not None:
+            import cv2 as cv
+
+            thumb = cv.resize(np.nan_to_num(image), (size, size), interpolation=cv.INTER_AREA)
+            axis.imshow(metrics.to_display(thumb, wavelength), cmap="gray", vmin=0, vmax=1)
+        axis.set_title(format_time(slot[2])[5:], fontsize=3)
+        axis.axis("off")
+    for index in range(len(picks), rows * columns):
+        axes[index // columns][index % columns].axis("off")
+    figure.suptitle(f"g{satellite} {wavelength}A - {len(picks)} of {len(series)} frames")
+    figure.tight_layout()
+    figure.savefig(path, dpi=200)
+    plt.close(figure)
+
+
+# ------------------------------------------------------------------------ make-case
+
+
+def _load_window(conn, name):
+    row = conn.execute("SELECT * FROM bench_window WHERE name = ?", (name,)).fetchone()
+    if row is None:
+        raise SystemExit(f"No vetted window named {name!r}; run vet-window first.")
+    return row
+
+
+def _build_overlay(conn, case_row, window_row):
+    """Reconstruct a case's view of the archive from the index."""
+    root = paths.data_root()
+    satellites = tuple(json.loads(window_row["satellites"]))
+    wavelengths = tuple(json.loads(window_row["wavelengths"]))
+    archive = cases.scan_window(
+        root, satellites, wavelengths, window_row["t_start"], window_row["t_end"]
+    )
+    overrides, deleted = {}, set()
+    rows = conn.execute(
+        """
+        SELECT f.satellite, f.wavelength, f.t_start, i.mode, i.overlay_path
+        FROM bench_injection i JOIN frame f ON f.id = i.frame_id
+        WHERE i.case_id = ?
+        """,
+        (case_row["id"],),
+    ).fetchall()
+    for row in rows:
+        slot = (row["satellite"], row["wavelength"], row["t_start"])
+        if row["mode"] == "delete":
+            deleted.add(slot)
+        elif row["overlay_path"]:
+            overrides[slot] = row["overlay_path"]
+    return cases.Overlay(archive=archive, overrides=overrides, deleted=frozenset(deleted))
+
+
+def _write_corrupted(source_path, target_path, injection):
+    """Materialise one corrupted frame into the overlay.  Returns None on success."""
+    os.makedirs(os.path.dirname(target_path), exist_ok=True)
+    corruption = corruptions.CATALOG[injection.mode]
+
+    if corruption.kind == "file":
+        with open(source_path, "rb") as handle:
+            raw = handle.read()
+        damaged = corruptions.apply_file(injection.mode, raw, injection.seed, injection.severity)
+        with open(target_path, "wb") as handle:
+            handle.write(damaged)
+        return None
+
+    image, error = fitsio.read_image(source_path)
+    if image is None:
+        return f"could not read source: {error}"
+
+    donor = None
+    if corruption.needs_donor:
+        donor = np.roll(image, image.shape[0] // 3, axis=0)  # a plausible other frame
+
+    damaged, overrides = corruptions.apply_array(
+        injection.mode, image, injection.seed, injection.severity, donor
+    )
+    if corruption.recompute_stats:
+        overrides = {**overrides, **corruptions.recomputed_stats(damaged)}
+
+    with fits.open(source_path) as hdus:
+        target = next(
+            (h for h in hdus if getattr(h, "data", None) is not None and h.data.ndim == 2), None
+        )
+        if target is None:
+            return "source has no image HDU"
+        target.data = damaged.astype(np.float32)
+        for key, value in overrides.items():
+            target.header[key] = value
+        hdus.writeto(target_path, overwrite=True, checksum=True)
+    return None
+
+
+def _corrupt_one(job):
+    source_path, target_path, injection = job
+    try:
+        return injection.slot, _write_corrupted(source_path, target_path, injection)
+    except Exception as exc:  # a corruption must never take the whole run down
+        return injection.slot, f"{type(exc).__name__}: {exc}"
+
+
+def cmd_make_case(args):
+    conn = db.connect(args.db)
+    window = _load_window(conn, args.window)
+    satellites = tuple(json.loads(window["satellites"]))
+    wavelengths = tuple(json.loads(window["wavelengths"]))
+    root = paths.data_root()
+
+    archive = cases.scan_window(
+        root, satellites, wavelengths, window["t_start"], window["t_end"]
+    )
+    plan = cases.InjectionPlan(
+        fraction=args.fraction,
+        gap_lengths=parse_int_list(args.gap_lengths),
+        satellite_scope=args.satellite_scope,
+        wavelength_scope=args.wavelength_scope,
+        modes=tuple(args.modes.split(",")) if args.modes else cases.InjectionPlan.modes,
+        severity=(args.severity_low, args.severity_high),
+        gaps_per_length=args.gaps_per_length,
+    ).validate()
+
+    window_times = sorted({slot[2] for slot in archive})
+    injections = cases.plan_injections(
+        plan, set(archive), satellites, wavelengths, args.seed
+    )
+    if not injections:
+        print("Plan produced no injections; raise --fraction or widen the window.")
+        return 1
+
+    overlay_dir = args.overlay_dir or os.path.join(
+        os.path.dirname(root), "bench", args.name
+    )
+    os.makedirs(overlay_dir, exist_ok=True)
+
+    conn.execute(
+        """
+        INSERT INTO bench_case (window_id, name, seed, plan_json, overlay_dir, created_at)
+        VALUES (?, ?, ?, ?, ?, ?)
+        ON CONFLICT (name) DO UPDATE SET
+            window_id = excluded.window_id, seed = excluded.seed,
+            plan_json = excluded.plan_json, overlay_dir = excluded.overlay_dir,
+            created_at = excluded.created_at
+        """,
+        (
+            window["id"],
+            args.name,
+            args.seed,
+            json.dumps(plan.as_dict(), sort_keys=True),
+            overlay_dir,
+            time.time(),
+        ),
+    )
+    case_id = conn.execute(
+        "SELECT id FROM bench_case WHERE name = ?", (args.name,)
+    ).fetchone()["id"]
+    conn.execute("DELETE FROM bench_injection WHERE case_id = ?", (case_id,))
+
+    jobs, rows = [], []
+    for injection in injections:
+        source_path = archive[injection.slot][0]
+        name = paths.parse_frame_filename(os.path.basename(source_path))
+        frame_id = db.frame_id_by_slot(conn, *injection.slot)
+        if frame_id is None:
+            frame_id = db.upsert_frame(conn, name, name.relpath())
+        overlay_path = None
+        if injection.mode != "delete":
+            overlay_path = os.path.join(overlay_dir, name.relpath())
+            jobs.append((source_path, overlay_path, injection))
+        rows.append((case_id, frame_id, injection, overlay_path))
+
+    print(f"Planned {len(injections)} injections "
+          f"({sum(1 for i in injections if i.mode == 'delete')} deletions, {len(jobs)} corruptions)")
+
+    failures = {}
+    if jobs:
+        reliever = vfs.Reliever(label="make-case")
+        with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+            for index, (slot, error) in enumerate(pool.imap_unordered(_corrupt_one, jobs, 8)):
+                reliever.tick()
+                if error:
+                    failures[slot] = error
+                if args.progress and index % 200 == 0 and index:
+                    print(f"  wrote {index}/{len(jobs)}")
+    if failures:
+        print(f"WARNING: {len(failures)} corruptions failed:")
+        for slot, error in list(failures.items())[:5]:
+            print(f"    {slot}: {error}")
+
+    conn.executemany(
+        """
+        INSERT INTO bench_injection
+            (case_id, frame_id, mode, severity, params_json, overlay_path, gap_index, gap_length)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        """,
+        [
+            (
+                case_id,
+                frame_id,
+                injection.mode,
+                injection.severity,
+                json.dumps({"seed": injection.seed}),
+                overlay_path,
+                injection.gap_index,
+                injection.gap_length,
+            )
+            for case_id, frame_id, injection, overlay_path in rows
+            if injection.slot not in failures
+        ],
+    )
+    conn.commit()
+
+    affected = len({i.slot[2] for i in injections})
+    print(f"Case '{args.name}' (id {case_id}): {affected}/{len(window_times)} timestamps affected")
+    print(f"Overlay: {overlay_dir}")
+    return 0
+
+
+# --------------------------------------------------------------------------- detect
+
+
+def _read_features(job):
+    """Load one frame's header, thumbnail, and single-frame verdicts."""
+    slot, path = job
+    if path is None:
+        return slot, None, None, None, 0
+    started = time.perf_counter_ns()
+    values, header_error = fitsio.scan_header(path)
+    features = detectors.FrameFeatures(slot=slot, header=values, error=header_error)
+    header_verdict = detectors.header_v1(features)
+    header_us = (time.perf_counter_ns() - started) // 1000
+
+    image, image_error = fitsio.read_image(path)
+
+    started = time.perf_counter_ns()
+    if image is None:
+        geometry_verdict = detectors.Verdict("bad", f"unreadable: {image_error}", {})
+    else:
+        geometry_verdict = detectors.geometry_v1(image, slot[1])
+    geometry_us = (time.perf_counter_ns() - started) // 1000
+
+    started = time.perf_counter_ns()
+    if image is None:
+        disc_verdict = detectors.Verdict("bad", f"unreadable: {image_error}", {})
+    else:
+        disc_verdict = detectors.disc_v1(image, slot[1], values)
+    disc_us = (time.perf_counter_ns() - started) // 1000
+
+    features.thumbnail = detectors.thumbnail(image) if image is not None else None
+    return (
+        slot,
+        features,
+        (header_verdict, header_us),
+        (geometry_verdict, geometry_us),
+        (disc_verdict, disc_us),
+    )
+
+
+def cmd_detect(args):
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db)
+    case = conn.execute("SELECT * FROM bench_case WHERE name = ?", (args.case,)).fetchone()
+    if case is None:
+        raise SystemExit(f"No case named {args.case!r}")
+    window = conn.execute(
+        "SELECT * FROM bench_window WHERE id = ?", (case["window_id"],)
+    ).fetchone()
+    satellites = tuple(json.loads(window["satellites"]))
+    wavelengths = tuple(json.loads(window["wavelengths"]))
+    overlay = _build_overlay(conn, case, window)
+    wanted = tuple(args.detectors.split(",")) if args.detectors else detectors.ALL_DETECTORS
+
+    runs = {}
+    for name in wanted:
+        runs[name] = db.create_detector_run(
+            conn, name, {"case": args.case}, notes=f"bench case {args.case}"
+        )
+
+    results = {name: {} for name in wanted}
+    elapsed = defaultdict(int)
+
+    for wavelength in wavelengths:
+        per_satellite = {}
+        for satellite in satellites:
+            series_slots = [
+                slot for slot in overlay.series(satellite, wavelength)
+                if slot not in overlay.deleted
+            ]
+            jobs = [(slot, overlay.path(slot)) for slot in series_slots]
+            features_by_slot = {}
+            reliever = vfs.Reliever(label="detect")
+            with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+                for slot, features, header, geometry, disc in pool.imap(
+                    _read_features, jobs, 8
+                ):
+                    reliever.tick()
+                    if features is None:
+                        continue
+                    features_by_slot[slot] = features
+                    for name, outcome in (
+                        ("header_v1", header),
+                        ("geometry_v1", geometry),
+                        ("disc_v1", disc),
+                    ):
+                        if name in results:
+                            results[name][slot] = outcome[0]
+                            elapsed[name] += outcome[1]
+
+            ordered = [features_by_slot[s] for s in series_slots if s in features_by_slot]
+            per_satellite[satellite] = ordered
+
+            if "temporal_v1" in results and ordered:
+                started = time.perf_counter_ns()
+                verdicts = detectors.temporal_v1(ordered)
+                elapsed["temporal_v1"] += (time.perf_counter_ns() - started) // 1000
+                for features, verdict in zip(ordered, verdicts):
+                    results["temporal_v1"][features.slot] = verdict
+
+        if "crosssat_v1" in results and len(satellites) >= 2:
+            first, second = satellites[0], satellites[1]
+            by_time = {
+                sat: {f.slot[2]: f for f in per_satellite.get(sat, [])}
+                for sat in (first, second)
+            }
+            temporal = results.get("temporal_v1", {})
+            started = time.perf_counter_ns()
+            for when in sorted(set(by_time[first]) | set(by_time[second])):
+                a, b = by_time[first].get(when), by_time[second].get(when)
+                verdict_a, verdict_b = detectors.crosssat_v1(
+                    a,
+                    b,
+                    temporal.get(a.slot) if a else None,
+                    temporal.get(b.slot) if b else None,
+                )
+                if a is not None:
+                    results["crosssat_v1"][a.slot] = verdict_a
+                if b is not None:
+                    results["crosssat_v1"][b.slot] = verdict_b
+            elapsed["crosssat_v1"] += (time.perf_counter_ns() - started) // 1000
+        print(f"  {wavelength}A done")
+
+    for name, verdicts in results.items():
+        payload = []
+        for slot, verdict in verdicts.items():
+            frame_id = db.frame_id_by_slot(conn, *slot)
+            if frame_id is None:
+                continue
+            payload.append((frame_id, verdict.verdict, verdict.reason, verdict.scores, None))
+        db.record_detections(conn, runs[name], payload)
+        conn.commit()
+        flagged = sum(1 for v in verdicts.values() if v.verdict == "bad")
+        print(f"{name:>14}: {len(verdicts)} frames, {flagged} flagged bad, "
+              f"{elapsed[name] / max(len(verdicts), 1):.0f} us/frame")
+    return 0
+
+
+# ----------------------------------------------------------------------------- fill
+
+
+def _bad_slots(conn, case, source):
+    """Slots the fill step should reconstruct, per oracle or per detector.
+
+    Detector runs are per case, so the run has to be looked up by this case's
+    config.  Taking "the latest run of header_v1" would silently pick up whichever
+    case happened to be processed last.
+    """
+    if source == "oracle":
+        rows = conn.execute(
+            """
+            SELECT f.satellite, f.wavelength, f.t_start
+            FROM bench_injection i JOIN frame f ON f.id = i.frame_id
+            WHERE i.case_id = ?
+            """,
+            (case["id"],),
+        ).fetchall()
+    else:
+        run_id = db.latest_run_id(conn, source, {"case": case["name"]})
+        if run_id is None:
+            raise SystemExit(
+                f"No run of {source!r} for case {case['name']!r}; run detect first."
+            )
+        rows = conn.execute(
+            """
+            SELECT f.satellite, f.wavelength, f.t_start
+            FROM detection d JOIN frame f ON f.id = d.frame_id
+            WHERE d.run_id = ? AND d.verdict = 'bad'
+            """,
+            (run_id,),
+        ).fetchall()
+    return {(row["satellite"], row["wavelength"], row["t_start"]) for row in rows}
+
+
+def cmd_fill(args):
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db)
+    case = conn.execute("SELECT * FROM bench_case WHERE name = ?", (args.case,)).fetchone()
+    if case is None:
+        raise SystemExit(f"No case named {args.case!r}")
+    window = conn.execute(
+        "SELECT * FROM bench_window WHERE id = ?", (case["window_id"],)
+    ).fetchone()
+    satellites = tuple(json.loads(window["satellites"]))
+    wavelengths = tuple(json.loads(window["wavelengths"]))
+    overlay = _build_overlay(conn, case, window)
+
+    source = "oracle" if args.oracle else args.from_detector
+    if source is None:
+        raise SystemExit("Pass either --oracle or --from-detector NAME")
+    bad = _bad_slots(conn, case, source)
+    print(f"Filling {len(bad)} slots identified by '{source}'")
+
+    gap_lengths = {}
+    for row in conn.execute(
+        """
+        SELECT f.satellite, f.wavelength, f.t_start, i.gap_length
+        FROM bench_injection i JOIN frame f ON f.id = i.frame_id WHERE i.case_id = ?
+        """,
+        (case["id"],),
+    ):
+        gap_lengths[(row["satellite"], row["wavelength"], row["t_start"])] = row["gap_length"]
+
+    wanted = tuple(args.fillers.split(",")) if args.fillers else tuple(fillers.FILLERS)
+    reliever = vfs.Reliever(label="fill")
+    scored = defaultdict(list)
+    # A slot whose truth frame will not read cannot be scored.  Count them: silently
+    # dropping them yields metrics computed over whatever subset happened to work,
+    # with nothing in the output to say so.  A degraded mount once reduced this to
+    # 12% coverage while the report looked entirely normal.
+    unreadable = 0
+    attempted = 0
+    payload = []
+
+    for wavelength in wavelengths:
+        truth_cache = {}
+
+        def truth_image(slot):
+            if slot not in truth_cache:
+                path = overlay.truth_path(slot)
+                image, _ = fitsio.read_image(path) if path else (None, None)
+                truth_cache[slot] = image
+            return truth_cache[slot]
+
+        for satellite in satellites:
+            series = overlay.series(satellite, wavelength)
+            good = [s for s in series if s not in bad and overlay.path(s) is not None]
+            good_times = [s[2] for s in good]
+            for slot in series:
+                if slot not in bad:
+                    continue
+                reliever.tick()
+                attempted += 1
+                truth = truth_image(slot)
+                if truth is None:
+                    unreadable += 1
+                    continue
+
+                before = _nearest(good_times, slot[2], before=True)
+                after = _nearest(good_times, slot[2], before=False)
+                counterpart_slot = next(
+                    (
+                        (other, wavelength, slot[2])
+                        for other in satellites
+                        if other != satellite
+                        and (other, wavelength, slot[2]) not in bad
+                        and overlay.path((other, wavelength, slot[2])) is not None
+                    ),
+                    None,
+                )
+
+                context = fillers.FillContext(
+                    before=truth_image((satellite, wavelength, before)) if before else None,
+                    dt_before=slot[2] - before if before else 0.0,
+                    after=truth_image((satellite, wavelength, after)) if after else None,
+                    dt_after=after - slot[2] if after else 0.0,
+                    counterpart=truth_image(counterpart_slot) if counterpart_slot else None,
+                    header=_header_for(overlay, slot),
+                )
+
+                for filler_name in wanted:
+                    filled = fillers.FILLERS[filler_name](context)
+                    if filled is None:
+                        continue
+                    score = metrics.score_fill(
+                        filled, truth, wavelength, gap_lengths.get(slot, context.gap_frames)
+                    )
+                    scored[filler_name].append(score)
+                    frame_id = db.frame_id_by_slot(conn, *slot)
+                    if frame_id is not None:
+                        payload.append(
+                            (case["id"], frame_id, filler_name, source,
+                             json.dumps(score.as_dict()))
+                        )
+            truth_cache.clear()
+        print(f"  {wavelength}A done")
+
+    conn.executemany(
+        """
+        INSERT INTO bench_fill_result (case_id, frame_id, filler, source, scores_json)
+        VALUES (?, ?, ?, ?, ?)
+        ON CONFLICT (case_id, frame_id, filler, source)
+            DO UPDATE SET scores_json = excluded.scores_json
+        """,
+        payload,
+    )
+    conn.commit()
+
+    covered = attempted - unreadable
+    print(f"\nScored {covered}/{attempted} slots"
+          + (f" -- {unreadable} could not be read" if unreadable else ""))
+    if attempted and covered < attempted * 0.95:
+        print(f"  WARNING: only {covered / attempted:.0%} of damaged slots were scored.")
+        print("           These numbers describe that subset, not the case.  A mount")
+        print("           that ran out of file handles is the usual cause; re-run.")
+    print(f"\n{'filler':>16} {'n':>6} {'rmse':>10} {'log rmse':>10} {'psnr':>8} {'ssim':>7}")
+    for filler_name in wanted:
+        summary = metrics.summarise_fills(scored.get(filler_name, []))
+        if not summary:
+            print(f"{filler_name:>16} {'-- not applicable --':>44}")
+            continue
+        print(f"{filler_name:>16} {summary['n']:>6} {summary['rmse']:>10.4g} "
+              f"{summary['log_rmse']:>10.4g} {summary['psnr']:>8.2f} {summary['ssim']:>7.4f}")
+    return 0
+
+
+def _nearest(times, target, before=True):
+    """Closest time in `times` strictly before or after `target`."""
+    if before:
+        candidates = [t for t in times if t < target]
+        return max(candidates) if candidates else None
+    candidates = [t for t in times if t > target]
+    return min(candidates) if candidates else None
+
+
+def _header_for(overlay, slot):
+    path = overlay.truth_path(slot)
+    if path is None:
+        return {}
+    values, _ = fitsio.scan_header(path)
+    return values
+
+
+# --------------------------------------------------------------------------- report
+
+
+def cmd_report(args):
+    conn = db.connect(args.db, readonly=True)
+    case = conn.execute("SELECT * FROM bench_case WHERE name = ?", (args.case,)).fetchone()
+    if case is None:
+        raise SystemExit(f"No case named {args.case!r}")
+    window = conn.execute(
+        "SELECT * FROM bench_window WHERE id = ?", (case["window_id"],)
+    ).fetchone()
+
+    plan = json.loads(case["plan_json"])
+    print(f"Case '{args.case}' on window '{window['name']}' "
+          f"({format_time(window['t_start'])} .. {format_time(window['t_end'])})")
+    print(f"  plan: {plan}\n")
+
+    injected = {}
+    for row in conn.execute(
+        """
+        SELECT f.satellite, f.wavelength, f.t_start, i.mode
+        FROM bench_injection i JOIN frame f ON f.id = i.frame_id WHERE i.case_id = ?
+        """,
+        (case["id"],),
+    ):
+        injected[(row["satellite"], row["wavelength"], row["t_start"])] = row["mode"]
+
+    legacy_good = {
+        (row["satellite"], row["wavelength"], row["t_start"])
+        for row in conn.execute(
+            """
+            SELECT f.satellite, f.wavelength, f.t_start FROM bench_truth t
+            JOIN frame f ON f.id = t.frame_id
+            WHERE t.window_id = ? AND t.is_good = 1
+            """,
+            (window["id"],),
+        )
+    }
+
+    print("DETECTION")
+    print(f"{'detector':>14} {'prec':>7} {'recall':>7} {'F1':>7} {'FPR':>8} "
+          f"{'unknown':>8} {'legacy-dis':>11}")
+    per_detector = {}
+    verdict_maps = {}
+    for name in detectors.ALL_DETECTORS:
+        run_id = db.latest_run_id(conn, name, {"case": args.case})
+        if run_id is None:
+            continue
+        verdicts = {}
+        for row in conn.execute(
+            """
+            SELECT f.satellite, f.wavelength, f.t_start, d.verdict, d.reason
+            FROM detection d JOIN frame f ON f.id = d.frame_id WHERE d.run_id = ?
+            """,
+            (run_id,),
+        ):
+            slot = (row["satellite"], row["wavelength"], row["t_start"])
+            verdicts[slot] = detectors.Verdict(row["verdict"], row["reason"], {})
+        # Deleted slots have no frame to judge, so they cannot be scored here.
+        scoreable = {s: v for s, v in verdicts.items() if injected.get(s) != "delete"}
+        score = metrics.score_detection(
+            scoreable,
+            {s: m for s, m in injected.items() if m != "delete"},
+            legacy_good,
+        )
+        per_detector[name] = score
+        verdict_maps[name] = verdicts
+        print(f"{name:>14} {score.precision:>7.3f} {score.recall:>7.3f} {score.f1:>7.3f} "
+              f"{score.false_positive_rate:>8.4f} {score.unknown:>8} "
+              f"{score.legacy_disagreements:>11}")
+
+    if args.combinations and len(per_detector) > 1:
+        print("\nDETECTOR COMBINATIONS (ranked by false-positive rate, then F1)")
+        print(f"{'policy':>9} {'detectors':>44} {'prec':>7} {'recall':>7} {'F1':>7} {'FPR':>8}")
+        scoreable_injected = {s: m for s, m in injected.items() if m != "delete"}
+        rows = []
+        names = sorted(per_detector)
+        for size in range(2, len(names) + 1):
+            for subset in itertools.combinations(names, size):
+                for policy in metrics.COMBINATION_POLICIES:
+                    combined = metrics.combine_verdicts(
+                        [verdict_maps[name] for name in subset], policy
+                    )
+                    combined = {
+                        s: v for s, v in combined.items() if injected.get(s) != "delete"
+                    }
+                    score = metrics.score_detection(
+                        combined, scoreable_injected, legacy_good
+                    )
+                    rows.append((score.false_positive_rate, -score.f1, policy, subset, score))
+        rows.sort(key=lambda r: (r[0] if np.isfinite(r[0]) else 9e9,
+                                 r[1] if np.isfinite(r[1]) else 9e9))
+        for _, _, policy, subset, score in rows[: args.combination_limit]:
+            label = "+".join(n.replace("_v1", "") for n in subset)
+            print(f"{policy:>9} {label:>44} {score.precision:>7.3f} {score.recall:>7.3f} "
+                  f"{score.f1:>7.3f} {score.false_positive_rate:>8.4f}")
+
+    modes = sorted({m for m in injected.values() if m != "delete"})
+    if modes and per_detector:
+        print("\nRECALL BY CORRUPTION MODE")
+        header = f"{'mode':>18}" + "".join(f"{n[:11]:>13}" for n in per_detector)
+        print(header)
+        for mode in modes:
+            line = f"{mode:>18}"
+            for score in per_detector.values():
+                value = score.recall_by_mode.get(mode)
+                line += f"{value:>13.3f}" if value is not None else f"{'-':>13}"
+            print(line)
+
+    print("\nFILL")
+    rows = conn.execute(
+        "SELECT filler, source, scores_json FROM bench_fill_result WHERE case_id = ?",
+        (case["id"],),
+    ).fetchall()
+    if not rows:
+        print("  (no fill results; run `bench.py fill` first)")
+    else:
+        grouped = defaultdict(list)
+        for row in rows:
+            payload = json.loads(row["scores_json"])
+            grouped[(row["source"], row["filler"])].append(
+                metrics.FillScore(**payload)
+            )
+        print(f"{'source':>10} {'filler':>16} {'n':>6} {'rmse':>10} {'psnr':>8} {'ssim':>7}")
+        for (source, filler_name), scores in sorted(grouped.items()):
+            summary = metrics.summarise_fills(scores)
+            print(f"{source:>10} {filler_name:>16} {summary['n']:>6} "
+                  f"{summary['rmse']:>10.4g} {summary['psnr']:>8.2f} {summary['ssim']:>7.4f}")
+
+        print("\nFILL QUALITY BY GAP LENGTH (psnr, dB)")
+        gaps = sorted({s.gap_frames for scores in grouped.values() for s in scores})
+        print(f"{'source/filler':>28}" + "".join(f"{g:>8}" for g in gaps))
+        for (source, filler_name), scores in sorted(grouped.items()):
+            summary = metrics.summarise_fills(scores)
+            line = f"{source + '/' + filler_name:>28}"
+            for gap in gaps:
+                entry = summary["by_gap"].get(gap)
+                line += f"{entry['psnr']:>8.2f}" if entry else f"{'-':>8}"
+            print(line)
+
+    if args.json:
+        output = {
+            "case": args.case,
+            "window": window["name"],
+            "plan": plan,
+            "detection": {n: s.as_dict() for n, s in per_detector.items()},
+        }
+        with open(args.json, "w") as handle:
+            json.dump(output, handle, indent=2)
+        print(f"\nWrote {args.json}")
+    return 0
+
+
+# --------------------------------------------------------------------------- render
+
+#: Slots the current pipeline will carry forward from the last good frame.  Beyond
+#: this merger_FITS.py gives up and the timestamp produces no composite at all.
+TODAY_MAX_TIME_GAP = 3
+
+
+def _resolve_band(overlay, slot, truth_cache, use_truth=False):
+    """Read one band's pixels, caching, or None if it cannot be read.
+
+    `use_truth` reads the original archive frame rather than what the case left in
+    its place.  The pristine variant needs it: a slot the case *deleted* has no
+    overlay path at all, and resolving those through the overlay silently drops them
+    -- which cost the ground-truth pane 221 of its timestamps, exactly the ones the
+    other panes have to be compared against.
+    """
+    key = (slot, use_truth)
+    if key not in truth_cache:
+        path = overlay.truth_path(slot) if use_truth else overlay.path(slot)
+        image, _ = fitsio.read_image(path) if path else (None, None)
+        truth_cache[key] = image
+    return truth_cache[key]
+
+
+def _render_one(job):
+    """Composite a single timestamp for one satellite.  Runs in a worker."""
+    import merger_FITS
+
+    arrays, timestamp, out_path = job
+    try:
+        image = merger_FITS.composite_from_arrays(arrays, timestamp)
+        image.save(out_path, quality=95)
+        return out_path, None
+    except Exception as exc:
+        return out_path, f"{type(exc).__name__}: {exc}"
+
+
+def cmd_render(args):
+    """Produce the composite stream for one variant of a case.
+
+    Three variants, which together answer 'is the repair visible, and is it better
+    than what we do now':
+
+    * ``pristine`` -- the archive untouched.  Ground truth.
+    * ``today``    -- what the current pipeline does with the injected damage: carry
+      the last good frame across gaps of up to TODAY_MAX_TIME_GAP slots, and emit
+      *nothing at all* for longer ones, which is what leaves ffmpeg_video.py padding
+      with black frames.  A 300-slot gap produces 300 missing composites.
+    * ``new``      -- the chosen method: any(disc_v1 + header_v1) detection, filled
+      with optical_flow at every gap length.
+    """
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db)
+    case = conn.execute("SELECT * FROM bench_case WHERE name = ?", (args.case,)).fetchone()
+    if case is None:
+        raise SystemExit(f"No case named {args.case!r}")
+    window = conn.execute(
+        "SELECT * FROM bench_window WHERE id = ?", (case["window_id"],)
+    ).fetchone()
+    satellites = tuple(json.loads(window["satellites"]))
+    if args.satellites:
+        wanted = parse_int_list(args.satellites)
+        satellites = tuple(s for s in satellites if s in wanted)
+        if not satellites:
+            raise SystemExit(f"none of {wanted} are in this window")
+    wavelengths = tuple(json.loads(window["wavelengths"]))
+    if len(wavelengths) != 6:
+        raise SystemExit(f"a composite needs all six bands; window has {wavelengths}")
+    overlay = _build_overlay(conn, case, window)
+
+    # Pristine shows the window as it really is, so it reads the archive directly and
+    # treats nothing as damaged.
+    pristine = args.variant == "pristine"
+    bad = set() if pristine else _bad_slots(conn, case, args.detector)
+    times = sorted({slot[2] for slot in overlay.archive})
+    print(f"{args.variant}: {len(times)} timestamps x {len(satellites)} satellites, "
+          f"{len(bad)} slots treated as bad")
+
+    for satellite in satellites:
+        out_dir = os.path.join(args.out, args.variant, f"goes{satellite}")
+        os.makedirs(out_dir, exist_ok=True)
+        truth_cache = {}
+        jobs = []
+        skipped = 0
+        reliever = vfs.Reliever(label=f"render g{satellite}")
+
+        for when in times:
+            reliever.tick(len(wavelengths))
+            slots = [(satellite, band, when) for band in wavelengths]
+            arrays = []
+            usable = True
+            for slot in slots:
+                if not pristine and (slot in bad or overlay.path(slot) is None):
+                    replacement, ok = _replacement_band(
+                        args.variant, overlay, slot, bad, truth_cache, wavelengths
+                    )
+                    if not ok:
+                        usable = False
+                        break
+                    arrays.append(replacement)
+                else:
+                    image = _resolve_band(overlay, slot, truth_cache, use_truth=pristine)
+                    if image is None:
+                        usable = False
+                        break
+                    arrays.append(image)
+
+            if not usable:
+                # No composite for this timestamp -- exactly what the current
+                # pipeline does past its gap limit, and what ffmpeg then pads.
+                skipped += 1
+                continue
+            jobs.append((arrays, when, os.path.join(out_dir, f"Composite-{int(when)}.jpg")))
+
+            if len(jobs) >= args.batch:
+                _flush_renders(jobs, args.workers)
+                jobs.clear()
+                truth_cache.clear()
+                print(f"  g{satellite}: {len(os.listdir(out_dir))} rendered, {skipped} skipped")
+
+        if jobs:
+            _flush_renders(jobs, args.workers)
+        print(f"  g{satellite}: {len(os.listdir(out_dir))} composites, {skipped} timestamps skipped")
+    conn.close()
+    return 0
+
+
+def _replacement_band(variant, overlay, slot, bad, truth_cache, wavelengths):
+    """What to substitute for a band the case removed.  Returns (array, usable)."""
+    satellite, band, when = slot
+    series = [s for s in overlay.series(satellite, band) if s not in bad]
+    times = [s[2] for s in series]
+    before = _nearest(times, when, before=True)
+    after = _nearest(times, when, before=False)
+
+    if variant == "today":
+        # merger_FITS carries the last good frame a few slots, then gives up.
+        if before is None or (when - before) // paths.CADENCE > TODAY_MAX_TIME_GAP:
+            return None, False
+        return _resolve_band(overlay, (satellite, band, before), truth_cache), True
+
+    context = fillers.FillContext(
+        before=_resolve_band(overlay, (satellite, band, before), truth_cache) if before else None,
+        dt_before=when - before if before else 0.0,
+        after=_resolve_band(overlay, (satellite, band, after), truth_cache) if after else None,
+        dt_after=after - when if after else 0.0,
+    )
+    filled = fillers.optical_flow(context)
+    return (filled, True) if filled is not None else (None, False)
+
+
+def _flush_renders(jobs, workers):
+    failures = 0
+    with Pool(workers, initializer=fitsio.quiet_astropy) as pool:
+        for _, error in pool.imap_unordered(_render_one, jobs, 4):
+            failures += bool(error)
+    if failures:
+        print(f"  WARNING: {failures} composites failed to render")
+
+
+# ------------------------------------------------------------------------- examples
+
+
+def cmd_examples(args):
+    """Show the frames a detector got wrong, so a number becomes a picture.
+
+    A precision/recall table says how often a detector is wrong; it does not say
+    what it is wrong *about*.  For `header_v1`, whose recall is low but precision
+    perfect, the interesting set is the false negatives -- damage that leaves
+    IMG_MEAN, ECLIPSE and EMPTY all looking normal.
+    """
+    import matplotlib
+
+    matplotlib.use("Agg")
+    from matplotlib import pyplot as plt
+
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db, readonly=True)
+    case = conn.execute("SELECT * FROM bench_case WHERE name = ?", (args.case,)).fetchone()
+    if case is None:
+        raise SystemExit(f"No case named {args.case!r}")
+    window = conn.execute(
+        "SELECT * FROM bench_window WHERE id = ?", (case["window_id"],)
+    ).fetchone()
+    overlay = _build_overlay(conn, case, window)
+
+    run_id = db.latest_run_id(conn, args.detector, {"case": args.case})
+    if run_id is None:
+        raise SystemExit(
+            f"No run of {args.detector!r} for case {args.case!r}; run detect first."
+        )
+
+    injected = {}
+    for row in conn.execute(
+        """
+        SELECT f.satellite, f.wavelength, f.t_start, i.mode, i.severity
+        FROM bench_injection i JOIN frame f ON f.id = i.frame_id WHERE i.case_id = ?
+        """,
+        (case["id"],),
+    ):
+        injected[(row["satellite"], row["wavelength"], row["t_start"])] = (
+            row["mode"], row["severity"]
+        )
+
+    wanted = []
+    for row in conn.execute(
+        """
+        SELECT f.satellite, f.wavelength, f.t_start, d.verdict, d.reason, d.scores_json
+        FROM detection d JOIN frame f ON f.id = d.frame_id WHERE d.run_id = ?
+        """,
+        (run_id,),
+    ):
+        slot = (row["satellite"], row["wavelength"], row["t_start"])
+        mode = injected.get(slot, (None, None))[0]
+        if mode == "delete":
+            continue  # no frame to show
+        corrupted = mode is not None
+        if args.kind == "fn" and corrupted and row["verdict"] == "good":
+            wanted.append((slot, mode, row))
+        elif args.kind == "fp" and not corrupted and row["verdict"] == "bad":
+            wanted.append((slot, None, row))
+
+    print(f"{args.detector} {args.kind.upper()}s on case '{args.case}': {len(wanted)}")
+    if not wanted:
+        print("  none -- nothing to plot.")
+        return 0
+
+    by_mode = defaultdict(int)
+    for _, mode, _ in wanted:
+        by_mode[mode or "(uninjected)"] += 1
+    for mode, count in sorted(by_mode.items(), key=lambda kv: -kv[1]):
+        print(f"    {count:>4}  {mode}")
+
+    wanted = wanted[: args.limit]
+    columns = min(6, len(wanted))
+    rows = (len(wanted) + columns - 1) // columns
+    figure, axes = plt.subplots(rows, columns, figsize=(3 * columns, 3.4 * rows))
+    axes = np.atleast_2d(axes)
+    for index, (slot, mode, row) in enumerate(wanted):
+        axis = axes[index // columns][index % columns]
+        path = overlay.path(slot)
+        image, _ = fitsio.read_image(path) if path else (None, None)
+        if image is not None:
+            axis.imshow(metrics.to_display(image, slot[1]), cmap="gray", vmin=0, vmax=1)
+        scores = json.loads(row["scores_json"] or "{}")
+        shown = ", ".join(f"{k}={v:.3g}" for k, v in list(scores.items())[:3])
+        axis.set_title(
+            f"g{slot[0]} {slot[1]}A {format_time(slot[2])[5:]}\n"
+            f"{mode or 'clean'} -> {row['verdict']}\n{shown}",
+            fontsize=6,
+        )
+        axis.axis("off")
+    for index in range(len(wanted), rows * columns):
+        axes[index // columns][index % columns].axis("off")
+    figure.suptitle(f"{args.detector} {args.kind.upper()}s - case {args.case}")
+    figure.tight_layout()
+    figure.savefig(args.out, dpi=150)
+    plt.close(figure)
+    print(f"  wrote {args.out}")
+    return 0
+
+
+# ------------------------------------------------------------------------------ cli
+
+
+def build_parser():
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--db", default=None, help="SQLite index (default: $SUVI_DB)")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    def add_window_args(sub):
+        sub.add_argument("--start", type=parse_date, required=True)
+        sub.add_argument("--end", type=parse_date, required=True)
+        sub.add_argument("--satellites", default="16,18")
+        sub.add_argument("--wavelengths", default="94,131,171,195,284,304")
+
+    select = subparsers.add_parser("select-window", help="find clean stretches of archive")
+    add_window_args(select)
+    select.add_argument("--min-slots", type=int, default=120)
+    select.add_argument("--limit", type=int, default=10)
+    select.add_argument("--require-legacy-label", action="store_true",
+                        help="also require the stale _f suffix (off by default)")
+    select.set_defaults(func=cmd_select_window)
+
+    vet = subparsers.add_parser("vet-window", help="verify and freeze a ground-truth window")
+    add_window_args(vet)
+    vet.add_argument("--name", required=True)
+    vet.add_argument("--notes", default=None)
+    vet.add_argument("--allow-missing", action="store_true")
+    vet.add_argument("--min-good-fraction", type=float, default=0.98)
+    vet.add_argument("--contact-sheet", default=None, help="write a filmstrip PNG for review")
+    vet.add_argument("--progress", action="store_true")
+    vet.set_defaults(func=cmd_vet_window)
+
+    make = subparsers.add_parser("make-case", help="inject damage into a vetted window")
+    make.add_argument("--window", required=True)
+    make.add_argument("--name", required=True)
+    make.add_argument("--seed", type=int, default=42)
+    make.add_argument("--fraction", type=float, default=0.10)
+    make.add_argument("--gap-lengths", default="1,2,3,5,10,30,60")
+    make.add_argument("--gaps-per-length", type=int, default=None,
+                      help="place exactly this many gaps at each length, instead of "
+                           "sizing the case by --fraction")
+    make.add_argument("--satellite-scope", default="mixed",
+                      choices=("g16", "g18", "both", "mixed"))
+    make.add_argument("--wavelength-scope", default="all", choices=("all", "one"))
+    make.add_argument("--modes", default=None, help="comma-separated; default is all")
+    make.add_argument("--severity-low", type=float, default=0.5)
+    make.add_argument("--severity-high", type=float, default=1.0)
+    make.add_argument("--overlay-dir", default=None)
+    make.add_argument("--workers", type=int, default=8)
+    make.add_argument("--progress", action="store_true")
+    make.set_defaults(func=cmd_make_case)
+
+    detect = subparsers.add_parser("detect", help="run detectors over a case")
+    detect.add_argument("--case", required=True)
+    detect.add_argument("--detectors", default=None, help="comma-separated; default is all")
+    detect.add_argument("--workers", type=int, default=8)
+    detect.set_defaults(func=cmd_detect)
+
+    fill = subparsers.add_parser("fill", help="reconstruct flagged slots and score them")
+    fill.add_argument("--case", required=True)
+    fill.add_argument("--fillers", default=None, help="comma-separated; default is all")
+    group = fill.add_mutually_exclusive_group(required=True)
+    group.add_argument("--oracle", action="store_true",
+                       help="use perfect knowledge of which slots are bad")
+    group.add_argument("--from-detector", default=None,
+                       help="use a detector's output, showing end-to-end error")
+    fill.set_defaults(func=cmd_fill)
+
+    report = subparsers.add_parser("report", help="summarise a case's results")
+    report.add_argument("--case", required=True)
+    report.add_argument("--json", default=None)
+    report.add_argument("--combinations", action="store_true",
+                        help="also score every combination of detectors")
+    report.add_argument("--combination-limit", type=int, default=15)
+    report.set_defaults(func=cmd_report)
+
+    render = subparsers.add_parser(
+        "render", help="produce the composite stream for one variant of a case"
+    )
+    render.add_argument("--case", required=True)
+    render.add_argument("--variant", required=True,
+                        choices=("pristine", "today", "new"))
+    render.add_argument("--out", required=True, help="root directory for the streams")
+    render.add_argument("--detector", default="oracle",
+                        help="which slots to treat as bad ('oracle', or a run name)")
+    render.add_argument("--satellites", default=None,
+                        help="restrict to these satellites (default: all in the window)")
+    render.add_argument("--workers", type=int, default=8)
+    render.add_argument("--batch", type=int, default=48,
+                        help="composites per worker dispatch; bounds peak memory")
+    render.set_defaults(func=cmd_render)
+
+    examples = subparsers.add_parser(
+        "examples", help="plot the frames a detector got wrong"
+    )
+    examples.add_argument("--case", required=True)
+    examples.add_argument("--detector", required=True)
+    examples.add_argument("--kind", choices=("fp", "fn"), required=True)
+    examples.add_argument("--limit", type=int, default=12)
+    examples.add_argument("--out", default="examples.png")
+    examples.set_defaults(func=cmd_examples)
+    return parser
+
+
+def main(argv=None):
+    args = build_parser().parse_args(argv)
+    return args.func(args) or 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/ffmpeg_video.py b/ffmpeg_video.py
index 3c61788..a4a7681 100644
--- a/ffmpeg_video.py
+++ b/ffmpeg_video.py
@@ -1,73 +1,126 @@
-import subprocess
-import os
-import shutil
-import datetime
-import time
-import calendar
-
-import numpy as np
-from sortedcontainers import SortedDict
-import tqdm
-from PIL import Image
-
-years = [2024]
-sources = ["goes16", "goes18"]
-ffmpeg_path = r"..\ffmpeg.exe"
-
-for year in years:
-    for source in sources:
-        path_to_images = f"..\\composite\\{source}"
-        output_file = f"..\\{source}_{year}_nofilt.mp4"
-        interp_file = f"..\\{source}_{year}_interp_nofilt.mp4"
-
-        starttime = calendar.timegm(datetime.datetime(year, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-        stoptime = calendar.timegm(datetime.datetime(year+1, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-        min_file_size = 350000 # Detect and remove corrupted files by filtering by file size
-        max_file_size = 450000
-        encoding_crf = 16
-        max_frame_interp = 120
-
-        # Set up ffmpeg to stream images from an input pipe
-        command_line = f'{ffmpeg_path} -y -f image2pipe -framerate 60 -i - -c:v libx264 -crf {encoding_crf} -preset veryfast {output_file}'
-        print(command_line)
-        p = subprocess.Popen(command_line, shell=True, stdout=subprocess.PIPE, stdin=subprocess.PIPE)
-
-        black_image = Image.fromarray(np.zeros((1080, 1920, 3), dtype='uint8'))
-
-        files_by_time = SortedDict()
-        for root, dirs, files in tqdm.tqdm(os.walk(path_to_images), desc="Finding and filtering files."):
-            for f in files:
-                if f.endswith('.jpg'):
-                    fpath = os.path.join(root, f)
-                    fsize = os.path.getsize(fpath)
-                    time_chunk = f.replace('-', '.').replace('_', '.').split('.')[1]
-                    ftime = int(time_chunk)
-                    if (fsize > min_file_size) and (fsize < max_file_size) and (ftime > starttime) and (ftime < stoptime):
-                        files_by_time[ftime] = fpath
-
-        difftimes = np.diff(files_by_time.keys())
-        unique, counts = np.unique(difftimes, return_counts=True)
-        interval = unique[0]
-        assert np.sum((unique % interval) > 0) == 0 # Ensure all our timestamps align perfectly with our interval
-
-        prevtime = files_by_time.peekitem(0)[0] - interval
-        for t, f in tqdm.tqdm(files_by_time.items(), desc="FFMPEG encoding images", total = len(files_by_time)):
-            framejump = (t - prevtime) // interval
-            if framejump < max_frame_interp:
-                for i in range(framejump - 1): # Fill black frames to fill gaps, these will later be interpolated with ffmpeg
-                    black_image.save(p.stdin, 'jpeg', quality = 95)
-            else: # Skip past intervals that are too large to fill reasonably
-                print(f"Detected a frame gap of: {framejump}!")
-            with open(f, 'rb') as fh:
-                p.stdin.write(fh.read())
-            prevtime = t
-
-        p.stdin.close() # Close the ffmpeg input pipe
-        p.wait() # Wait for ffmpeg to finish encoding
-
-        command_line = f'{ffmpeg_path} -y -i {output_file} -vf blackframe=0,metadata=select:key=lavfi.blackframe.pblack:value=95:function=less,minterpolate=mi_mode=mci:mc_mode=aobmc:me_mode=bidir:vsbmc=1:me=fss -c:a copy -c:v libx264 -crf {encoding_crf} -preset veryfast {interp_file}'
-        print(command_line)
-
-        pipe = subprocess.Popen(command_line, shell=True, stdout=subprocess.PIPE).stdout
-        output = pipe.read().decode()
-        pipe.close()
\ No newline at end of file
+import argparse
+import subprocess
+import os
+import sys
+import datetime
+import shutil as _shutil
+import calendar
+
+import numpy as np
+from sortedcontainers import SortedDict
+import tqdm
+from PIL import Image
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import paths, vfs
+
+
+def find_ffmpeg():
+    """Locate ffmpeg: $FFMPEG first, then PATH, then the bundled Windows binary."""
+    override = os.environ.get("FFMPEG")
+    if override and os.path.exists(override):
+        return override
+    found = _shutil.which("ffmpeg")
+    if found:
+        return found
+    bundled = os.path.join(os.path.dirname(paths.data_root()), "ffmpeg.exe")
+    if os.path.exists(bundled):
+        return bundled
+    raise SystemExit("ffmpeg not found. Install it, or set $FFMPEG to its path.")
+
+
+def encode_videos(args):
+    """Encode composite JPGs into per-satellite videos.
+
+    Gaps are padded with black frames and smoothed by ffmpeg's minterpolate, except
+    where the gap exceeds `max_frame_interp`, which is skipped entirely.  That
+    behaviour is what the bench's "today" variant reproduces.
+    """
+    years = args.years
+    sources = args.sources
+    ffmpeg_path = find_ffmpeg()
+    project_root = args.out or os.path.dirname(paths.data_root())
+    os.makedirs(project_root, exist_ok=True)
+
+    for year in years:
+        for source in sources:
+            path_to_images = args.images or os.path.join(
+            os.path.dirname(paths.data_root()), "composite", source)
+            output_file = os.path.join(project_root, f"{source}_{year}_{args.suffix}.mp4")
+            interp_file = os.path.join(project_root, f"{source}_{year}_interp_{args.suffix}.mp4")
+
+            starttime = calendar.timegm(datetime.datetime(year, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
+            stoptime = calendar.timegm(datetime.datetime(year+1, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
+            min_file_size = 350000 # Detect and remove corrupted files by filtering by file size
+            max_file_size = 450000
+            encoding_crf = 16
+            max_frame_interp = 120
+
+            # Set up ffmpeg to stream images from an input pipe
+            command_line = f'{ffmpeg_path} -y -f image2pipe -framerate 60 -i - -c:v libx264 -crf {encoding_crf} -preset veryfast {output_file}'
+            print(command_line)
+            p = subprocess.Popen(command_line, shell=True, stdout=subprocess.PIPE, stdin=subprocess.PIPE)
+
+            black_image = Image.fromarray(np.zeros((1080, 1920, 3), dtype='uint8'))
+
+            files_by_time = SortedDict()
+            for root, dirs, files in tqdm.tqdm(os.walk(path_to_images), desc="Finding and filtering files."):
+                for f in files:
+                    if f.endswith('.jpg'):
+                        fpath = os.path.join(root, f)
+                        fsize = os.path.getsize(fpath)
+                        time_chunk = f.replace('-', '.').replace('_', '.').split('.')[1]
+                        ftime = int(time_chunk)
+                        if (fsize > min_file_size) and (fsize < max_file_size) and (ftime > starttime) and (ftime < stoptime):
+                            files_by_time[ftime] = fpath
+
+            difftimes = np.diff(files_by_time.keys())
+            unique, counts = np.unique(difftimes, return_counts=True)
+            interval = unique[0]
+            assert np.sum((unique % interval) > 0) == 0 # Ensure all our timestamps align perfectly with our interval
+
+            prevtime = files_by_time.peekitem(0)[0] - interval
+            reliever = vfs.Reliever(label=f"encode {source}")
+            for t, f in tqdm.tqdm(files_by_time.items(), desc="FFMPEG encoding images", total = len(files_by_time)):
+                reliever.tick()
+                framejump = (t - prevtime) // interval
+                if framejump < max_frame_interp:
+                    for i in range(framejump - 1): # Fill black frames to fill gaps, these will later be interpolated with ffmpeg
+                        black_image.save(p.stdin, 'jpeg', quality = 95)
+                else: # Skip past intervals that are too large to fill reasonably
+                    print(f"Detected a frame gap of: {framejump}!")
+                with open(f, 'rb') as fh:
+                    p.stdin.write(fh.read())
+                prevtime = t
+
+            p.stdin.close() # Close the ffmpeg input pipe
+            p.wait() # Wait for ffmpeg to finish encoding
+
+            command_line = f'{ffmpeg_path} -y -i {output_file} -vf blackframe=0,metadata=select:key=lavfi.blackframe.pblack:value=95:function=less,minterpolate=mi_mode=mci:mc_mode=aobmc:me_mode=bidir:vsbmc=1:me=fss -c:a copy -c:v libx264 -crf {encoding_crf} -preset veryfast {interp_file}'
+            print(command_line)
+
+            pipe = subprocess.Popen(command_line, shell=True, stdout=subprocess.PIPE).stdout
+            pipe.read()
+            pipe.close()
+
+def build_parser():
+    parser = argparse.ArgumentParser(
+        description="Encode SUVI composite images into videos.",
+        formatter_class=argparse.RawDescriptionHelpFormatter,
+    )
+    parser.add_argument("--years", type=int, nargs="+", default=[2024])
+    parser.add_argument("--sources", nargs="+", default=["goes16", "goes18"])
+    parser.add_argument("--images", default=None,
+                        help="directory of composites (default: <root>/composite/<source>)")
+    parser.add_argument("--out", default=None, help="directory for the video files")
+    parser.add_argument("--start", type=int, default=None, help="Unix time, inclusive")
+    parser.add_argument("--stop", type=int, default=None, help="Unix time, exclusive")
+    parser.add_argument("--suffix", default="nofilt", help="tag in the output filenames")
+    return parser
+
+
+if __name__ == "__main__":
+    # Guarded: this module is imported for find_ffmpeg(), and without the guard that
+    # import kicked off a full-year encode as a side effect.
+    sys.exit(encode_videos(build_parser().parse_args()) or 0)
diff --git a/filter_FITS.py b/filter_FITS.py
index 742ebf1..b981dab 100644
--- a/filter_FITS.py
+++ b/filter_FITS.py
@@ -1,281 +1,733 @@
-import os
-from collections import defaultdict
-from multiprocessing import Queue, Process
-import re
-import traceback
-import datetime
-import calendar
-
-import tqdm
-import numpy as np
-from matplotlib import pyplot as plt
-from astropy.io import fits
-from skimage.transform import hough_circle, hough_circle_peaks
-from skimage.feature import canny
-from skimage.filters import gaussian
-from skimage.morphology import skeletonize
-import cv2 as cv
-
-def lowpriority():
-    """ Set the priority of the process to lowest possible."""
-
-    import sys
-    try:
-        sys.getwindowsversion()
-    except AttributeError:
-        isWindows = False
-    else:
-        isWindows = True
-
-    if isWindows:
-        import win32api,win32process,win32con # pywin32
-
-        pid = win32api.GetCurrentProcessId()
-        phandle = win32api.OpenProcess(win32con.PROCESS_ALL_ACCESS, True, pid)
-        win32process.SetPriorityClass(phandle, win32process.THREAD_PRIORITY_LOWEST)
-        # win32process.SetPriorityClass(phandle, win32process.IDLE_PRIORITY_CLASS)
-        # tid = win32api.GetCurrentThreadId()
-        # thandle = win32api.OpenThread(win32con.PROCESS_ALL_ACCESS, True, tid)
-        # win32process.SetThreadPriority(thandle, win32process.THREAD_MODE_BACKGROUND_BEGIN)
-    else:
-        import os
-
-        os.nice(19)
-
-measurement_names = ["094", "131", "171", "195", "284", "304"]
-thresholds =        [0.050, 0.10 ,  1.00,  1.40,  1.0,  2.50]
-max_center_skew = 7
-expected_dims = 1280
-half_dims = expected_dims // 2
-valid_radii = [383, 394]
-avg_radius = (valid_radii[0] + valid_radii[1]) // 2
-max_radius_error = 80
-
-ratio_above_thresh_max = 0.4
-ratio_above_thresh_min = 0.07
-
-def filter_fits(work_queue):
-    lowpriority()
-    idealcircle = np.zeros((expected_dims // 2, expected_dims // 2))
-    cv.circle(idealcircle, (expected_dims // 4, expected_dims // 4), avg_radius // 2, 1, -1)
-    idealcircle_axis = np.average(idealcircle, 0)
-    while True:
-        try:
-            job = work_queue.get()
-            if job is None:
-                return
-            measurement = job.split("dr_suvi-l2-")[1].split("_")[0][2:]
-            idx = measurement_names.index(measurement)
-            try:
-                data = fits.getdata(job)
-            except IndexError: # This can happen with a blank or corrupt HDU in the .fits file
-                new_name = job.split(".fits")[0] + "_e.fits"
-                os.rename(job, new_name)
-                continue
-            assert data.shape[0] == expected_dims
-            assert data.shape[1] == expected_dims
-            data = cv.resize(data, dsize=(expected_dims // 2, expected_dims // 2), interpolation=cv.INTER_LINEAR)
-            filtered_data = np.copy(data)
-            above_thresh_indexes = data > thresholds[idx]
-            filtered_data[above_thresh_indexes] = thresholds[idx]
-            filtered_data /= thresholds[idx]
-            ratio_above_thresh = np.count_nonzero(above_thresh_indexes) / data.shape[0] / data.shape[1]
-
-            if ratio_above_thresh > ratio_above_thresh_max:
-                print(f"Exceeded ratio_above_thresh_max, possible data corruption in file: {job}")
-                new_name = job.split(".fits")[0] + "_e.fits"
-                os.rename(job, new_name)
-
-                plt.figure(figsize=[10.24, 7.68])
-                plt.title(f"Exceeded ratio_above_thresh_max [{ratio_above_thresh:0.2f}]")
-                plt.imshow(filtered_data, cmap='jet')
-                plt.savefig(job.split(".fits")[0] + "_e.jpg")
-                plt.close('all')
-
-                continue
-
-            if ratio_above_thresh < ratio_above_thresh_min:
-                print(f"Below ratio_above_thresh_min, possible bad data in file: {job}")
-                new_name = job.split(".fits")[0] + "_e.fits"
-                os.rename(job, new_name)
-
-                plt.figure(figsize=[10.24, 7.68])
-                plt.title(f"Below ratio_above_thresh_min [{ratio_above_thresh:0.2f}]")
-                plt.imshow(filtered_data, cmap='jet')
-                plt.savefig(job.split(".fits")[0] + "_e.jpg")
-                plt.close('all')
-
-                continue
-
-            # Decide whether the data is valid based on solar disc placement and levels.
-            xavg = np.average(filtered_data, 0)
-            yavg = np.average(filtered_data, 1)
-            axis_indices = list(range(half_dims))
-
-            # Center Estimation
-            weighted_avg_center_x = np.average(axis_indices, 0, xavg)
-            weighted_avg_center_y = np.average(axis_indices, 0, yavg)
-
-            good_center = True
-            if (half_dims // 2 - weighted_avg_center_x > max_center_skew) or (half_dims // 2 - weighted_avg_center_y > max_center_skew):
-                print(f"Could not find centered solar disc in file: {job}")
-                good_center = False
-
-            # Radius Estimation
-            edge_thresh = 0.98
-            high_edge_x = np.argmax(np.cumsum(xavg) > (np.sum(xavg) * edge_thresh))
-            low_edge_x = len(xavg) - np.argmax(np.cumsum(np.flip(xavg)) > (np.sum(xavg) * edge_thresh))
-            high_edge_y = np.argmax(np.cumsum(yavg) > (np.sum(yavg) * edge_thresh))
-            low_edge_y = len(yavg) - np.argmax(np.cumsum(np.flip(yavg)) > (np.sum(yavg) * edge_thresh))
-
-            good_radius = True
-            calc_radius_x = (high_edge_x - low_edge_x) # We do not divide by two because our image is downsized by half in each dimension
-            calc_radius_y = (high_edge_y - low_edge_y)
-            calc_radius = (calc_radius_x + calc_radius_y) / 2.0
-            if abs(calc_radius - avg_radius) > max_radius_error:
-                print(f"Could not find correct solar radius in file: {job}")
-                good_radius = False
-
-            # Goodness of fit estimation vs perfect disc
-            gof_x = np.sum(np.abs(xavg - idealcircle_axis)) / half_dims
-            gof_y = np.sum(np.abs(yavg - idealcircle_axis)) / half_dims
-
-            good_fit = True
-            if gof_x > 0.2 or gof_y > 0.2:
-                print(f"Could not find valid solar disc in file: {job}")
-                good_fit = False
-
-
-            if good_center and good_radius and good_fit:
-                # We have validated this file, rename it appropriately
-                new_name = job.split(".fits")[0] + "_f.fits"
-                os.rename(job, new_name)
-            else:
-                new_name = job.split(".fits")[0] + "_e.fits"
-                os.rename(job, new_name)
-
-                # Plot Results
-                fig, axes = plt.subplots(2, 2, width_ratios=(0.2, 1), height_ratios=(0.2, 1), gridspec_kw={"hspace":0.0, "wspace": 0.0}, figsize = [8, 8])
-            
-                axes[0][0].axis('off')
-
-                axes[0][1].plot(axis_indices, xavg)
-                axes[0][1].plot(axis_indices, idealcircle_axis)
-                # axes[0][1].fill_between(axis_indices, xavg, idealcircle_axis, hatch="//", edgecolor="red", facecolor="none")
-
-                axes[1][0].plot(yavg, axis_indices)
-                axes[1][0].plot(idealcircle_axis, axis_indices)
-                axes[1][0].invert_xaxis()
-                axes[1][0].invert_yaxis()
-
-                axes[1][1].imshow(filtered_data, aspect='auto', vmin=0, vmax=1)
-                axes[1][1].vlines([low_edge_x, high_edge_x], 0, half_dims)
-                axes[1][1].hlines([low_edge_y, high_edge_y], 0, half_dims)
-                axes[1][1].scatter(half_dims // 2, half_dims // 2, marker="o", linewidths = 1, alpha = 0.75, edgecolors="black", facecolors = "none")
-                axes[1][1].scatter(weighted_avg_center_x, weighted_avg_center_y, marker = "x", alpha = 0.75, facecolors='red')
-
-                # Set shared x axis between imshow and xdata plots
-                axes[0][1].xaxis.set_ticks_position("top")
-                axes[0][1].yaxis.set_ticks_position("right")
-                axes[0][1].sharex(axes[1][1])
-                axes[1][0].sharey(axes[1][1])
-                axes[1][1].yaxis.set_ticks_position("right")
-
-                plt.savefig(job.split(".fits")[0] + "_e.jpg")
-                plt.close('all')
-                
-
-        except KeyboardInterrupt:
-            return
-        except Exception as e:
-            print(f"Error on file: {job} - {e}")
-            traceback.print_exception(e)
-
-
-if __name__ == "__main__":
-    stored_fits_dirs = [r"..\Data\goes16\l2\data\suvi-l2-ci094\2024",
-                        r"..\Data\goes16\l2\data\suvi-l2-ci131\2024",
-                        r"..\Data\goes16\l2\data\suvi-l2-ci171\2024",
-                        r"..\Data\goes16\l2\data\suvi-l2-ci195\2024",
-                        r"..\Data\goes16\l2\data\suvi-l2-ci284\2024",
-                        r"..\Data\goes16\l2\data\suvi-l2-ci304\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci094\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci131\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci171\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci195\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci284\2024",
-                        r"..\Data\goes18\l2\data\suvi-l2-ci304\2024",]
-    
-    # stored_fits_dirs = [r"..\Data\goes18\l2\data\suvi-l2-ci284\2023\01\10"]
-
-    starttime = calendar.timegm(datetime.datetime(2024, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-    stoptime = calendar.timegm(datetime.datetime(2025, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-
-    reprocess_errors = True
-    nworkers = 16
-
-    regex_filename = r"dr_suvi-l2-ci\d{3}_g(16|18)_s\S*\.fits$"
-
-    work_queue = Queue(maxsize = nworkers)
-    workers = []
-    for i in range(nworkers):
-        p = Process(target = filter_fits, args = (work_queue,), daemon=True)
-        p.start()
-        workers.append(p)
-
-    lowpriority()
-    files_by_timestamp = defaultdict(list)
-    try:
-        for stored_fits_dir in stored_fits_dirs:
-            filename_tester = re.compile(regex_filename)
-
-            found_files = 0
-            print(f"Searching for FITS files in: {stored_fits_dir}")
-            for root, dirs, files in tqdm.tqdm(os.walk(stored_fits_dir), desc="Searching"):
-                for f in files:
-                    if filename_tester.match(f):
-                        file_parts = f.split("_")
-                        file_name_end = file_parts[-1].split(".")[0]
-                        measure_end_time = int(datetime.datetime.strptime(file_parts[4][1:16] + " +0000", "%Y%m%dT%H%M%S %z").timestamp())
-                        if (measure_end_time >= starttime) and (measure_end_time < stoptime):
-                            if file_name_end == "f":
-                                if file_parts[-2] == "f": # We have an accidentally double filtered file...
-                                    new_file_name = "_".join(file_parts[:-1]) + ".fits"
-                                    os.rename(os.path.join(root,f), os.path.join(root,new_file_name))
-                                continue # Already filtered from a previous run
-                            elif file_name_end == "e":
-                                if reprocess_errors:
-                                    # Rename file to remove error designation
-                                    new_file_name = "_".join(file_parts[:-1]) + ".fits"
-                                    os.rename(os.path.join(root,f), os.path.join(root,new_file_name))
-                                    # Check if error image exists and delete if needed
-                                    img_name = new_file_name.split(".fits")[0] + "_e.jpg"
-                                    try:
-                                        os.remove(os.path.join(root, img_name))
-                                    except:
-                                        pass
-                                    # Add job to queue
-                                    files_by_timestamp[measure_end_time].append(os.path.join(root, new_file_name))
-                                else:
-                                    continue
-                            elif file_name_end.startswith("v1-0-"): # This is the normal case for unprocessed data
-                                files_by_timestamp[measure_end_time].append(os.path.join(root,f))
-                            else:
-                                # print(f"Error - Unexpected FITS file name: {f}")
-                                pass
-        sorted_times = sorted(list(files_by_timestamp.keys()))
-        for st in tqdm.tqdm(sorted_times, desc="Filtering files"):
-            for f in files_by_timestamp[st]:
-                work_queue.put(f)
-    except KeyboardInterrupt:
-        print("Finishing current jobs and exiting")
-                
-
-    for _ in range(nworkers):
-        try:
-            work_queue.put(None, timeout=10.0)
-        except:
-            break
-
-    for w in workers:
-        w.join()
+#!/usr/bin/env python
+"""Index the SUVI archive and record per-frame quality verdicts.
+
+Replaces the older version of this script, which encoded its verdict by renaming
+files to ``_f``/``_e`` and wrote a diagnostic JPG next to every reject.  Verdicts now
+go to the SQLite index, so the archive keeps NOAA's filenames, several detectors can
+disagree about a frame, the continuous scores survive for later re-thresholding, and
+nothing has to be re-read to change a threshold.
+
+Subcommands::
+
+    filter_FITS.py index     # sync the index with the archive
+    filter_FITS.py scan      # cache FITS header metadata (~18 KB read per frame)
+    filter_FITS.py detect    # run detectors and record verdicts
+    filter_FITS.py plots     # regenerate diagnostic images for flagged frames
+
+``index`` and ``scan`` are incremental: they skip what they already have, so they can
+be re-run as the puller brings in new data.  ``index`` reads only the day-directories
+whose mtime changed, which is what keeps re-indexing affordable -- see suvi/index.py
+for why traversing this archive in full is something to avoid, not merely optimise.
+
+A caution before using ``detect --detectors geometry_v1`` to gate anything: measured
+over 20 sampled days of 2024, that method rejects 36.9% of frames, and does so
+all-or-nothing -- 0% on most days, 73-100% on days with a large active region, almost
+entirely for "failed centre".  Its centre test uses the intensity-weighted centroid,
+which a bright active region displaces even when the header reports the disc exactly
+centred.  Run bench.py before trusting any detector to discard data.
+"""
+
+import argparse
+import json
+import os
+import sys
+import time
+from collections import defaultdict
+from multiprocessing import Pool
+
+import numpy as np
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import db, detectors, fitsio, index, paths, vfs
+
+
+def parse_int_list(text):
+    return tuple(int(part) for part in text.split(",") if part.strip())
+
+
+# ---------------------------------------------------------------------------- index
+
+
+def cmd_index(args):
+    """Bring the index in step with the archive.
+
+    Reads only the day-directories whose mtime changed since the last run, so a
+    routine re-index costs ~7,400 directory stats rather than 2.65M file lookups.
+    That ratio is not just a speed matter: a full traversal exhausts the file
+    handles of the virtiofs mount this archive lives on.  Use --full only for a cold
+    start or when the index is suspect.
+    """
+    root = args.root or paths.data_root()
+    conn = db.connect(args.db)
+    satellites = parse_int_list(args.satellites)
+    wavelengths = parse_int_list(args.wavelengths)
+
+    print(f"Indexing {root}" + (" (full rescan)" if args.full else " (changed directories only)"))
+    summary = index.reconcile(
+        conn,
+        root,
+        satellites,
+        wavelengths,
+        years=args.year,
+        force=args.full,
+        progress=print if args.progress else None,
+    )
+    total = conn.execute("SELECT count(*) c FROM frame").fetchone()["c"]
+    print(
+        f"  {summary['directories_changed']} of {summary['directories_checked']} "
+        f"directories changed in {summary['seconds']:.0f}s"
+    )
+    print(f"  frames added {summary['frames_added']}, removed {summary['frames_removed']}")
+    if summary["directories_vanished"]:
+        print(f"  directories that disappeared: {summary['directories_vanished']}")
+    dupes = summary.get("duplicate_slots") or []
+    if dupes:
+        print(f"  {len(dupes)} files share an observation slot with another and were "
+              f"left out of the index (see --duplicates to list them)")
+        if args.duplicates:
+            for path in dupes:
+                print(f"    {path}")
+    print(f"  index now holds {total} frames")
+
+    suffixed = conn.execute(
+        "SELECT count(*) c FROM frame WHERE path LIKE '%\\_f.fits' ESCAPE '\\' "
+        "   OR path LIKE '%\\_e.fits' ESCAPE '\\'"
+    ).fetchone()["c"]
+    if suffixed:
+        print(f"\n{suffixed} indexed frames still carry _f/_e suffixes.")
+        print("Run migrate_unrename.py to fold those verdicts into the index.")
+    conn.close()
+    return 0
+
+
+# ----------------------------------------------------------------------------- scan
+
+
+def _scan_one(job):
+    frame_id, path = job
+    values, error = fitsio.scan_header(path)
+    return frame_id, values, error
+
+
+def cmd_scan(args):
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db)
+    root = args.root or paths.data_root()
+    pending = db.unscanned_frames(conn, args.limit)
+    if not pending:
+        print("Every indexed frame already has cached header metadata.")
+        return 0
+
+    print(f"Scanning headers for {len(pending)} frames with {args.workers} workers")
+    jobs = [(row["id"], paths.abspath(row["path"], root)) for row in pending]
+    started = time.time()
+    done = failed = 0
+    batch = []
+    reliever = vfs.Reliever(label="scan")
+    with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+        for frame_id, values, error in pool.imap_unordered(_scan_one, jobs, 32):
+            reliever.tick()
+            batch.append((frame_id, values, error))
+            done += 1
+            failed += bool(error)
+            if len(batch) >= 2000:
+                db.record_headers(conn, batch)
+                conn.commit()
+                batch.clear()
+                rate = done / max(time.time() - started, 1e-6)
+                print(f"  {done}/{len(jobs)} ({rate:.0f}/s, {failed} unreadable)")
+    if batch:
+        db.record_headers(conn, batch)
+        conn.commit()
+    print(f"Scanned {done} frames in {time.time() - started:.0f}s; {failed} unreadable")
+    return 0
+
+
+# --------------------------------------------------------------------------- detect
+
+
+def _detect_one(job):
+    """Run the frame-level detectors on one file."""
+    frame_id, slot, path, wanted = job
+    verdicts = {}
+    values, header_error = fitsio.scan_header(path)
+    features = detectors.FrameFeatures(slot=slot, header=values, error=header_error)
+
+    if "header_v1" in wanted:
+        started = time.perf_counter_ns()
+        verdict = detectors.header_v1(features)
+        verdicts["header_v1"] = (verdict, (time.perf_counter_ns() - started) // 1000)
+
+    pixel_detectors = [n for n in ("geometry_v1", "disc_v1") if n in wanted]
+    if pixel_detectors:
+        image, image_error = fitsio.read_image(path)
+        for name in pixel_detectors:
+            started = time.perf_counter_ns()
+            if image is None:
+                verdict = detectors.Verdict("bad", f"unreadable: {image_error}", {})
+            elif name == "geometry_v1":
+                verdict = detectors.geometry_v1(image, slot[1])
+            else:
+                verdict = detectors.disc_v1(image, slot[1], values)
+            verdicts[name] = (verdict, (time.perf_counter_ns() - started) // 1000)
+
+    return frame_id, verdicts
+
+
+def cmd_detect(args):
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db)
+    root = args.root or paths.data_root()
+    wanted = tuple(args.detectors.split(","))
+    unknown = [name for name in wanted if name not in detectors.ALL_DETECTORS]
+    if unknown:
+        print(f"Unknown detectors: {unknown}.  Available: {list(detectors.ALL_DETECTORS)}")
+        return 1
+
+    frame_detectors = [n for n in wanted if n in detectors.FRAME_DETECTORS]
+    series_detectors = [n for n in wanted if n in detectors.SERIES_DETECTORS]
+    if series_detectors:
+        print(f"NOTE: {series_detectors} need a whole series in memory; use bench.py "
+              "for those, or run them here one band at a time via --wavelengths.")
+
+    where, params = ["1=1"], []
+    if args.start is not None:
+        where.append("t_start >= ?")
+        params.append(args.start)
+    if args.end is not None:
+        where.append("t_start < ?")
+        params.append(args.end)
+    if args.wavelengths:
+        bands = parse_int_list(args.wavelengths)
+        where.append(f"wavelength IN ({','.join('?' * len(bands))})")
+        params.extend(bands)
+    rows = conn.execute(
+        f"SELECT id, path, satellite, wavelength, t_start FROM frame "
+        f"WHERE {' AND '.join(where)} ORDER BY t_start",
+        params,
+    ).fetchall()
+    if not rows:
+        print("No indexed frames match; run `filter_FITS.py index` first.")
+        return 1
+
+    runs = {
+        name: db.create_detector_run(conn, name, {"driver": "filter_FITS"}, notes=args.notes)
+        for name in frame_detectors
+    }
+    print(f"Running {frame_detectors} over {len(rows)} frames with {args.workers} workers")
+
+    jobs = [
+        (
+            row["id"],
+            (row["satellite"], row["wavelength"], row["t_start"]),
+            paths.abspath(row["path"], root),
+            frozenset(frame_detectors),
+        )
+        for row in rows
+    ]
+    started = time.time()
+    pending = defaultdict(list)
+    tallies = {name: defaultdict(int) for name in frame_detectors}
+    done = 0
+    reliever = vfs.Reliever(label="detect")
+
+    with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+        for frame_id, verdicts in pool.imap_unordered(_detect_one, jobs, 16):
+            reliever.tick()
+            for name, (verdict, elapsed) in verdicts.items():
+                pending[name].append(
+                    (frame_id, verdict.verdict, verdict.reason, verdict.scores, elapsed)
+                )
+                tallies[name][verdict.verdict] += 1
+            done += 1
+            if done % 5000 == 0:
+                for name, batch in pending.items():
+                    db.record_detections(conn, runs[name], batch)
+                    batch.clear()
+                conn.commit()
+                print(f"  {done}/{len(jobs)} ({done / max(time.time() - started, 1e-6):.0f}/s)")
+    for name, batch in pending.items():
+        if batch:
+            db.record_detections(conn, runs[name], batch)
+    conn.commit()
+
+    print(f"\nDone in {time.time() - started:.0f}s")
+    for name in frame_detectors:
+        counts = tallies[name]
+        total = sum(counts.values()) or 1
+        print(f"  {name}: run {runs[name]} -- "
+              + ", ".join(f"{v} {c} ({c / total:.1%})" for v, c in sorted(counts.items())))
+    return 0
+
+
+# ------------------------------------------------------------------------ calibrate
+
+#: Absolute floor on each measurement's half-width, so a band whose sample happens to
+#: be unusually tight does not get bounds narrower than the physics justifies.  Set
+#: from the observed cross-band spread of each quantity.
+CALIBRATION_FLOORS = {"limb_contrast": 0.15, "radius_ratio": 0.06, "limb_width": 0.06}
+
+#: Which side of each measurement actually diagnoses a fault.  Bounding the other
+#: side buys nothing and, on a wide-spread quantity, produces a negative limit that
+#: can never trip -- which looks like a rule while being none.
+#:
+#: * limb_contrast falls towards zero as the disc disappears; it cannot exceed 1.
+#: * radius_ratio is diagnostic in both directions -- too small or too large is wrong.
+#: * limb_width grows as the limb smears; a sharper-than-usual limb is not a fault.
+CALIBRATION_SIDES = {
+    "limb_contrast": ("lower", 0.02, 1.0),
+    "radius_ratio": ("both", None, None),
+    "limb_width": ("upper", 0.0, None),
+}
+
+
+def _sample_frames(conn, root, wavelength, count, satellites=(16, 18)):
+    """Pick frames spread evenly across the whole time range of one band.
+
+    Queries the index rather than walking the archive -- which is the point of
+    having an index, and avoids the traversal that exhausts this mount (see
+    suvi/index.py).
+
+    Deliberately does *not* filter on the legacy ``_f``/``_e`` verdicts.  Those were
+    written in May 2024 by a filter retuned that July, so selecting on them would
+    calibrate the new detector against the old one's mistakes -- including the very
+    active-region rejections this detector exists to stop.
+    """
+    placeholders = ",".join("?" * len(satellites))
+    rows = conn.execute(
+        f"SELECT path FROM frame WHERE wavelength = ? AND satellite IN ({placeholders}) "
+        f"ORDER BY t_start",
+        (wavelength, *satellites),
+    ).fetchall()
+    if not rows:
+        return []
+    stride = max(1, len(rows) // count)
+    return [paths.abspath(row["path"], root) for row in rows[::stride]][:count]
+
+
+def _calibration_measure(path):
+    """Measure one frame, skipping any the header already condemns."""
+    values, error = fitsio.scan_header(path)
+    if error or not values:
+        return None
+    if values.get("eclipse") or values.get("empty"):
+        return None  # genuinely bad; must not widen the good-frame bounds
+    diameter = values.get("diam_sun")
+    mean = values.get("img_mean")
+    if not diameter or mean is None:
+        return None
+    low, high = detectors.HEADER_MEAN_BOUNDS.get(
+        int(values.get("wavelnth") or 0), (0.0, float("inf"))
+    )
+    if not (low <= mean <= high):
+        return None  # dropout or blowout
+    image, image_error = fitsio.read_image(path)
+    if image is None:
+        return None
+    return detectors.disc_profile(image, float(diameter) / 4.0)
+
+
+def cmd_calibrate(args):
+    fitsio.quiet_astropy()
+    root = args.root or paths.data_root()
+    conn = db.connect(args.db, readonly=True)
+    wavelengths = parse_int_list(args.wavelengths)
+    margin = args.margin
+    table = {}
+
+    print(f"Calibrating disc_v1 from {root}")
+    print(f"  {args.samples_per_band} frames per band, margin {margin}x the observed span\n")
+
+    for wavelength in wavelengths:
+        candidates = _sample_frames(conn, root, wavelength, args.samples_per_band * 2)
+        if not candidates:
+            print(f"{wavelength:>5}: no frames found")
+            continue
+        results = []
+        reliever = vfs.Reliever(label=f"calibrate {wavelength}A")
+        with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+            for measured in pool.imap_unordered(_calibration_measure, candidates, 8):
+                reliever.tick()
+                if measured is None:
+                    continue
+                if any(v is None for v in measured.values()):
+                    results.append(measured)  # keep, so unmeasurable rate is visible
+                    continue
+                results.append(measured)
+                if len(results) >= args.samples_per_band:
+                    break
+
+        usable = [r for r in results if all(v is not None for v in r.values())]
+        unmeasurable = len(results) - len(usable)
+        if len(usable) < 20:
+            print(f"{wavelength:>5}: only {len(usable)} usable frames; skipping")
+            continue
+
+        bounds = {}
+        print(f"{wavelength:>5}A  n={len(usable)}  unmeasurable={unmeasurable}")
+        for name in ("limb_contrast", "radius_ratio", "limb_width"):
+            values = np.array([r[name] for r in usable], dtype=float)
+            low, high = float(values.min()), float(values.max())
+            span = high - low
+            half = max(margin * span, CALIBRATION_FLOORS[name])
+            side, floor, ceiling = CALIBRATION_SIDES[name]
+
+            lower = low - half if side in ("lower", "both") else floor
+            upper = high + half if side in ("upper", "both") else ceiling
+            # Keep each limit on the physical side of zero.  A negative floor on a
+            # non-negative quantity is not a loose rule, it is no rule at all.
+            if floor is not None:
+                lower = max(lower, floor)
+            if ceiling is not None:
+                upper = min(upper, ceiling)
+            bounds[name] = (round(lower, 4), round(upper, 4))
+            outside = int(((values < lower) | (values > upper)).sum())
+            print(f"        {name:<14} observed {low:.4f}-{high:.4f}  "
+                  f"p50 {np.median(values):.4f}  ->  bounds {lower:.4f}-{upper:.4f}  "
+                  f"sample failures {outside}/{len(values)}")
+        table[wavelength] = bounds
+
+    if not table:
+        print("\nNothing calibrated.")
+        return 1
+
+    print("\n" + "=" * 78)
+    print("Paste into DISC_BOUNDS in suvi/detectors.py:\n")
+    print("DISC_BOUNDS = {")
+    for wavelength, bounds in sorted(table.items()):
+        print(f"    {wavelength}: {{")
+        for name, (lower, upper) in bounds.items():
+            print(f'        "{name}": ({lower}, {upper}),')
+        print("    },")
+    print("}")
+    if args.json:
+        with open(args.json, "w") as handle:
+            json.dump(table, handle, indent=2)
+        print(f"\nAlso written to {args.json}")
+    return 0
+
+
+# --------------------------------------------------------------------------- sample
+
+#: The production combination: a frame is bad if either detector says so.
+SAMPLE_DETECTORS = ("header_v1", "disc_v1")
+
+
+def _judge_timestamp(job):
+    """Read all six bands for one (satellite, timestamp) and judge each.
+
+    Returns (satellite, timestamp, {band: (verdict, reason, scores)}), or None if
+    the set is incomplete -- a composite needs all six.
+    """
+    satellite, timestamp, band_paths = job
+    verdicts = {}
+    for band, path in sorted(band_paths.items()):
+        values, header_error = fitsio.scan_header(path)
+        features = detectors.FrameFeatures(
+            slot=(satellite, band, timestamp), header=values, error=header_error
+        )
+        header = detectors.header_v1(features)
+        image, image_error = fitsio.read_image(path)
+        if image is None:
+            disc = detectors.Verdict("bad", f"unreadable: {image_error}", {})
+        else:
+            disc = detectors.disc_v1(image, band, values)
+
+        bad = [v for v in (header, disc) if v.verdict == "bad"]
+        verdict = "bad" if bad else "good"
+        reason = "; ".join(v.reason for v in bad if v.reason) or None
+        verdicts[band] = (verdict, reason, {**header.scores, **disc.scores})
+    return satellite, timestamp, verdicts
+
+
+def _render_sample(job):
+    """Render one annotated composite for review."""
+    import merger_FITS
+    from PIL import ImageDraw, ImageFont
+
+    satellite, timestamp, band_paths, caption, out_path = job
+    try:
+        arrays = []
+        for band in sorted(band_paths):
+            image, error = fitsio.read_image(band_paths[band])
+            if image is None:
+                return out_path, f"band {band}: {error}"
+            arrays.append(image)
+        picture = merger_FITS.composite_from_arrays(arrays, timestamp)
+
+        font_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
+                                 "OpenSans-Regular.ttf")
+        font = ImageFont.truetype(font_path, size=20)
+        draw = ImageDraw.Draw(picture)
+        # Caption along the bottom, where it covers no solar structure.
+        y = picture.size[1] - 26 * len(caption)
+        for line in caption:
+            draw.text((12, y), line, (255, 235, 120), font=font)
+            y += 26
+        picture.save(out_path, quality=95)
+        return out_path, None
+    except Exception as exc:
+        return out_path, f"{type(exc).__name__}: {exc}"
+
+
+def cmd_sample(args):
+    """Write folders of suspected-good and suspected-bad frames for manual review.
+
+    The bench measures detectors against damage it injected itself, which proves
+    they find what was planted but says nothing about what they do to real frames
+    nobody labelled.  This is that check: a person looks at what the detector kept
+    and what it threw away, and says whether they agree.
+
+    Each image is the full composite for the frame's timestamp and satellite -- which
+    already tiles all six bands down its sides -- captioned with the verdict, the
+    band responsible, and the scores behind it.
+    """
+    fitsio.quiet_astropy()
+    root = args.root or paths.data_root()
+    conn = db.connect(args.db, readonly=True)
+    satellites = parse_int_list(args.satellites)
+
+    # Candidate timestamps spread evenly across whatever the index holds, so the
+    # sample is not a picture of one week.
+    rows = conn.execute(
+        f"SELECT satellite, t_start, wavelength, path FROM frame "
+        f"WHERE satellite IN ({','.join('?' * len(satellites))}) "
+        f"ORDER BY t_start",
+        satellites,
+    ).fetchall()
+    conn.close()
+
+    by_key = defaultdict(dict)
+    for row in rows:
+        by_key[(row["satellite"], row["t_start"])][row["wavelength"]] = paths.abspath(
+            row["path"], root
+        )
+    complete = [k for k, v in by_key.items() if len(v) == 6]
+    if not complete:
+        print("No timestamp has all six bands; cannot build composites.")
+        return 1
+
+    stride = max(1, len(complete) // max(args.scan, 1))
+    candidates = sorted(complete)[::stride][: args.scan]
+    print(f"{len(complete)} complete timestamps in the index; judging {len(candidates)}")
+
+    good, bad = [], []
+    reliever = vfs.Reliever(label="sample")
+    jobs = [(sat, when, by_key[(sat, when)]) for sat, when in candidates]
+
+    with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+        for result in pool.imap_unordered(_judge_timestamp, jobs, 4):
+            reliever.tick(6)
+            if result is None:
+                continue
+            satellite, timestamp, verdicts = result
+            flagged = {b: v for b, v in verdicts.items() if v[0] == "bad"}
+            if flagged and len(bad) < args.n:
+                bad.append((satellite, timestamp, flagged))
+            elif not flagged and len(good) < args.n:
+                good.append((satellite, timestamp, verdicts))
+            if len(good) >= args.n and len(bad) >= args.n:
+                break
+    reliever.finish()
+
+    print(f"  collected {len(bad)} flagged and {len(good)} clean timestamps")
+    if len(bad) < args.n:
+        print(f"  NOTE: only {len(bad)} flagged found in {len(candidates)} scanned; "
+              f"raise --scan for more.")
+
+    render_jobs = []
+    for folder, items in (("bad", bad), ("good", good)):
+        out_dir = os.path.join(args.out, folder)
+        os.makedirs(out_dir, exist_ok=True)
+        for satellite, timestamp, verdicts in items:
+            stamp = time.strftime("%Y%m%dT%H%M%S", time.gmtime(timestamp))
+            if folder == "bad":
+                bands = ",".join(f"{b}A" for b in sorted(verdicts))
+                first = verdicts[sorted(verdicts)[0]]
+                # Lead the filename with the reason so the folder sorts by failure mode.
+                slug = "".join(
+                    ch if ch.isalnum() else "_" for ch in (first[1] or "flagged")
+                )[:40]
+                caption = [
+                    f"FLAGGED  g{satellite}  {stamp}  bands: {bands}",
+                    (first[1] or "")[:110],
+                    " ".join(f"{k}={v:.3g}" for k, v in list(first[2].items())[:5]),
+                ]
+                name = f"{slug}__g{satellite}_{stamp}.jpg"
+            else:
+                sample_scores = verdicts[sorted(verdicts)[0]][2]
+                caption = [
+                    f"CLEAN  g{satellite}  {stamp}  all six bands passed",
+                    " ".join(f"{k}={v:.3g}" for k, v in list(sample_scores.items())[:5]),
+                ]
+                name = f"g{satellite}_{stamp}.jpg"
+            render_jobs.append(
+                (satellite, timestamp, by_key[(satellite, timestamp)], caption,
+                 os.path.join(out_dir, name))
+            )
+
+    print(f"Rendering {len(render_jobs)} composites...")
+    failures = 0
+    with Pool(args.workers, initializer=fitsio.quiet_astropy) as pool:
+        for path, error in pool.imap_unordered(_render_sample, render_jobs, 2):
+            if error:
+                failures += 1
+                if failures <= 3:
+                    print(f"  failed {os.path.basename(path)}: {error}")
+    print(f"  wrote {len(render_jobs) - failures} images to {args.out}")
+    print(f"  review {args.out}/bad  -- nothing here should be a frame you would keep")
+    print(f"  review {args.out}/good -- nothing here should be a frame you would discard")
+    return 0
+
+
+# ---------------------------------------------------------------------------- plots
+
+
+def cmd_plots(args):
+    """Regenerate the diagnostic image the old filter wrote beside every reject.
+
+    Kept as an on-demand tool rather than a side effect of filtering: the plots are
+    derivable from the index plus the FITS, and writing millions of them into the
+    archive was what made the old approach hard to undo.
+    """
+    import matplotlib
+
+    matplotlib.use("Agg")
+    import numpy as np
+    from matplotlib import pyplot as plt
+
+    fitsio.quiet_astropy()
+    conn = db.connect(args.db, readonly=True)
+    root = args.root or paths.data_root()
+    run_id = db.latest_run_id(conn, args.detector)
+    if run_id is None:
+        print(f"No run named {args.detector!r}")
+        return 1
+
+    rows = conn.execute(
+        """
+        SELECT f.path, f.wavelength, d.reason FROM detection d
+        JOIN frame f ON f.id = d.frame_id
+        WHERE d.run_id = ? AND d.verdict = 'bad' ORDER BY f.t_start LIMIT ?
+        """,
+        (run_id, args.limit),
+    ).fetchall()
+    os.makedirs(args.out, exist_ok=True)
+    print(f"Writing {len(rows)} diagnostic plots to {args.out}")
+
+    reference = detectors.ideal_disc_axis()
+    axis = list(range(detectors.HALF_DIMS))
+    for row in rows:
+        path = paths.abspath(row["path"], root)
+        image, error = fitsio.read_image(path)
+        if image is None:
+            continue
+        import cv2 as cv
+
+        threshold = detectors.GEOMETRY_THRESHOLDS[row["wavelength"]]
+        data = cv.resize(
+            np.nan_to_num(image),
+            (detectors.HALF_DIMS, detectors.HALF_DIMS),
+            interpolation=cv.INTER_LINEAR,
+        )
+        shown = np.clip(data, None, threshold) / threshold
+        xavg, yavg = np.average(shown, 0), np.average(shown, 1)
+
+        figure, axes = plt.subplots(
+            2, 2, width_ratios=(0.2, 1), height_ratios=(0.2, 1),
+            gridspec_kw={"hspace": 0.0, "wspace": 0.0}, figsize=(8, 8),
+        )
+        axes[0][0].axis("off")
+        axes[0][1].plot(axis, xavg)
+        axes[0][1].plot(axis, reference)
+        axes[1][0].plot(yavg, axis)
+        axes[1][0].plot(reference, axis)
+        axes[1][0].invert_xaxis()
+        axes[1][0].invert_yaxis()
+        axes[1][1].imshow(shown, aspect="auto", vmin=0, vmax=1)
+        axes[0][1].sharex(axes[1][1])
+        axes[1][0].sharey(axes[1][1])
+        figure.suptitle(f"{os.path.basename(row['path'])}\n{row['reason']}", fontsize=8)
+        figure.savefig(
+            os.path.join(args.out, os.path.basename(row["path"]).replace(".fits", ".jpg")),
+            dpi=110,
+        )
+        plt.close(figure)
+    return 0
+
+
+# ------------------------------------------------------------------------------ cli
+
+
+def build_parser():
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--db", default=None, help="SQLite index (default: $SUVI_DB)")
+    parser.add_argument("--root", default=None, help="archive root (default: $SUVI_DATA_ROOT)")
+    subparsers = parser.add_subparsers(dest="command", required=True)
+
+    index_cmd = subparsers.add_parser(
+        "index", help="sync the index with the archive (only changed directories)"
+    )
+    index_cmd.add_argument("--satellites", default="16,18,19")
+    index_cmd.add_argument("--wavelengths", default="94,131,171,195,284,304")
+    index_cmd.add_argument("--year", type=int, action="append", default=None)
+    index_cmd.add_argument("--full", action="store_true",
+                           help="re-read every directory, ignoring recorded mtimes")
+    index_cmd.add_argument("--progress", action="store_true")
+    index_cmd.add_argument("--duplicates", action="store_true",
+                           help="list files that share an observation slot")
+    index_cmd.set_defaults(func=cmd_index)
+
+    scan = subparsers.add_parser("scan", help="cache FITS header metadata")
+    scan.add_argument("--workers", type=int, default=16)
+    scan.add_argument("--limit", type=int, default=None)
+    scan.set_defaults(func=cmd_scan)
+
+    detect = subparsers.add_parser("detect", help="run detectors and record verdicts")
+    detect.add_argument("--detectors", default="header_v1")
+    detect.add_argument("--wavelengths", default=None)
+    detect.add_argument("--start", type=int, default=None, help="Unix time, inclusive")
+    detect.add_argument("--end", type=int, default=None, help="Unix time, exclusive")
+    detect.add_argument("--workers", type=int, default=16)
+    detect.add_argument("--notes", default=None)
+    detect.set_defaults(func=cmd_detect)
+
+    calibrate = subparsers.add_parser(
+        "calibrate", help="derive per-band disc_v1 bounds from a sample of good frames"
+    )
+    calibrate.add_argument("--wavelengths", default="94,131,171,195,284,304")
+    calibrate.add_argument("--samples-per-band", type=int, default=300)
+    calibrate.add_argument("--margin", type=float, default=1.0,
+                           help="half-width added either side, in multiples of the observed span")
+    calibrate.add_argument("--workers", type=int, default=16)
+    calibrate.add_argument("--json", default=None)
+    calibrate.set_defaults(func=cmd_calibrate)
+
+    sample = subparsers.add_parser(
+        "sample", help="write good/bad frame folders for manual review"
+    )
+    sample.add_argument("--n", type=int, default=100, help="frames per folder")
+    sample.add_argument("--out", required=True)
+    sample.add_argument("--scan", type=int, default=4000,
+                        help="timestamps to judge while looking for N of each")
+    sample.add_argument("--satellites", default="16,18")
+    sample.add_argument("--workers", type=int, default=8)
+    sample.set_defaults(func=cmd_sample)
+
+    plots = subparsers.add_parser("plots", help="regenerate diagnostics for flagged frames")
+    plots.add_argument("--detector", default="geometry_v1")
+    plots.add_argument("--out", default="diagnostics")
+    plots.add_argument("--limit", type=int, default=200)
+    plots.set_defaults(func=cmd_plots)
+    return parser
+
+
+def main(argv=None):
+    args = build_parser().parse_args(argv)
+    return args.func(args) or 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/make_comparison_video.py b/make_comparison_video.py
new file mode 100644
index 0000000..441fe12
--- /dev/null
+++ b/make_comparison_video.py
@@ -0,0 +1,168 @@
+#!/usr/bin/env python
+"""Stack the pristine, current-pipeline and new-pipeline streams side by side.
+
+`bench.py render` writes one composite per timestamp per variant.  This turns three
+such streams into a single video with the panes labelled, so the repair can be judged
+against both the truth and what the pipeline does today:
+
+    bench.py render --case C --variant pristine --out /tmp/streams
+    bench.py render --case C --variant today    --out /tmp/streams
+    bench.py render --case C --variant new      --out /tmp/streams
+    make_comparison_video.py --streams /tmp/streams --satellite 16 --out compare.mp4
+
+The panes must stay in step, which is the whole reason this does not simply hand
+ffmpeg three directories: a variant that produced no composite for a timestamp -- what
+the current pipeline does past its gap limit -- would otherwise shorten that pane and
+slide it out of alignment with the others.  Every stream is emitted against the same
+canonical timeline, with black where a composite is missing, so frame N is the same
+instant in all three panes.  Those black runs are not padding; they are what the
+current pipeline actually shows.
+"""
+
+import argparse
+import os
+import re
+import subprocess
+import sys
+
+import numpy as np
+from PIL import Image
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from ffmpeg_video import find_ffmpeg
+from suvi import paths, vfs
+
+VARIANTS = ("pristine", "today", "new")
+LABELS = {
+    "pristine": "PRISTINE (ground truth)",
+    "today": "TODAY (hold-last + black frames)",
+    "new": "NEW (disc+header, optical flow)",
+}
+_STAMP = re.compile(r"Composite-(\d+)\.jpg$")
+
+
+def stream_frames(directory):
+    """{timestamp: path} for one rendered stream."""
+    frames = {}
+    try:
+        entries = os.listdir(directory)
+    except OSError:
+        return frames
+    for entry in entries:
+        match = _STAMP.search(entry)
+        if match:
+            frames[int(match.group(1))] = os.path.join(directory, entry)
+    return frames
+
+
+def encode_stream(ffmpeg, frames, timeline, out_path, framerate, crf, reliever=None):
+    """Encode one pane, emitting a black frame wherever the variant has nothing.
+
+    Reads every composite in the pane, so it hands file handles back as it goes --
+    three panes of a week-long window is over 7,000 files, enough on its own to
+    exhaust the mount and take unrelated software down with it.
+    """
+    command = (
+        f'{ffmpeg} -y -f image2pipe -framerate {framerate} -i - '
+        f'-c:v libx264 -crf {crf} -preset veryfast -pix_fmt yuv420p "{out_path}"'
+    )
+    process = subprocess.Popen(command, shell=True, stdin=subprocess.PIPE,
+                               stdout=subprocess.DEVNULL, stderr=subprocess.DEVNULL)
+    blank = None
+    present = 0
+    for when in timeline:
+        path = frames.get(when)
+        if path:
+            with open(path, "rb") as handle:
+                process.stdin.write(handle.read())
+            present += 1
+            if reliever is not None:
+                reliever.tick()
+        else:
+            if blank is None:
+                size = Image.open(next(iter(frames.values()))).size if frames else (1920, 1080)
+                blank = Image.fromarray(np.zeros((size[1], size[0], 3), dtype="uint8"))
+            blank.save(process.stdin, "jpeg", quality=95)
+    process.stdin.close()
+    process.wait()
+    return present
+
+
+def main(argv=None):
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--streams", required=True, help="root written by bench.py render")
+    parser.add_argument("--satellite", type=int, default=16)
+    parser.add_argument("--out", required=True)
+    parser.add_argument("--framerate", type=int, default=60)
+    parser.add_argument("--crf", type=int, default=18)
+    parser.add_argument("--keep-panes", action="store_true",
+                        help="keep the intermediate per-pane videos")
+    args = parser.parse_args(argv)
+
+    ffmpeg = find_ffmpeg()
+    streams = {}
+    for variant in VARIANTS:
+        directory = os.path.join(args.streams, variant, f"goes{args.satellite}")
+        streams[variant] = stream_frames(directory)
+        print(f"  {variant:>8}: {len(streams[variant])} composites in {directory}")
+    if not any(streams.values()):
+        print("No composites found; run bench.py render first.")
+        return 1
+
+    # One canonical timeline across every variant, so the panes stay in step.
+    everything = set()
+    for frames in streams.values():
+        everything.update(frames)
+    timeline = list(range(min(everything), max(everything) + paths.CADENCE, paths.CADENCE))
+    print(f"  timeline: {len(timeline)} slots "
+          f"({len(timeline) / args.framerate:.0f}s per pane at {args.framerate}fps)")
+
+    panes = []
+    reliever = vfs.Reliever(label="encode")
+    for variant in VARIANTS:
+        pane = f"{os.path.splitext(args.out)[0]}.{variant}.mp4"
+        present = encode_stream(
+            ffmpeg, streams[variant], timeline, pane, args.framerate, args.crf, reliever
+        )
+        missing = len(timeline) - present
+        print(f"  encoded {variant}: {present} frames"
+              + (f", {missing} black ({missing / len(timeline):.0%})" if missing else ""))
+        panes.append(pane)
+
+    inputs = " ".join(f'-i "{p}"' for p in panes)
+    font = os.path.join(os.path.dirname(os.path.abspath(__file__)), "OpenSans-Regular.ttf")
+    labelled = []
+    for index, variant in enumerate(VARIANTS):
+        labelled.append(
+            f"[{index}:v]scale=960:-2,"
+            f"drawtext=fontfile='{font}':text='{LABELS[variant]}':"
+            f"x=12:y=12:fontsize=22:fontcolor=yellow:box=1:boxcolor=black@0.5[v{index}]"
+        )
+    graph = ";".join(labelled) + ";[v0][v1][v2]hstack=inputs=3[out]"
+    command = (
+        f'{ffmpeg} -y {inputs} -filter_complex "{graph}" -map "[out]" '
+        f'-c:v libx264 -crf {args.crf} -preset veryfast -pix_fmt yuv420p "{args.out}"'
+    )
+    print("  stacking panes...")
+    result = subprocess.run(command, shell=True, stdout=subprocess.DEVNULL,
+                            stderr=subprocess.PIPE)
+    if result.returncode != 0:
+        print(result.stderr.decode()[-1500:])
+        return 1
+
+    if not args.keep_panes:
+        for pane in panes:
+            try:
+                os.remove(pane)
+            except OSError:
+                pass
+    reliever.finish()
+    size = os.path.getsize(args.out) / 1024 / 1024
+    print(f"Wrote {args.out} ({size:.0f} MB)")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/merger.py b/merger.py
deleted file mode 100644
index 48cf5f5..0000000
--- a/merger.py
+++ /dev/null
@@ -1,270 +0,0 @@
-import os
-import time
-import calendar
-import datetime
-from collections import defaultdict
-from multiprocessing import Queue, Process
-
-import tqdm
-from PIL import Image, ImageFont, ImageDraw
-import numpy as np
-from matplotlib import pyplot as plt
-
-def bin_ndarray(ndarray, new_shape, operation='mean'):
-    """
-    Bins an ndarray in all axes based on the target shape, by summing or
-        averaging.
-
-    Number of output dimensions must match number of input dimensions and 
-        new axes must divide old ones.
-
-    Example
-    -------
-    >>> m = np.arange(0,100,1).reshape((10,10))
-    >>> n = bin_ndarray(m, new_shape=(5,5), operation='sum')
-    >>> print(n)
-
-    [[ 22  30  38  46  54]
-     [102 110 118 126 134]
-     [182 190 198 206 214]
-     [262 270 278 286 294]
-     [342 350 358 366 374]]
-
-    """
-    operation = operation.lower()
-    if not operation in ['sum', 'mean']:
-        raise ValueError("Operation not supported.")
-    if ndarray.ndim != len(new_shape):
-        raise ValueError("Shape mismatch: {} -> {}".format(ndarray.shape,
-                                                           new_shape))
-    compression_pairs = [(d, c//d) for d,c in zip(new_shape,
-                                                  ndarray.shape)]
-    flattened = [l for p in compression_pairs for l in p]
-    ndarray = ndarray.reshape(flattened)
-    for i in range(len(new_shape)):
-        op = getattr(ndarray, operation)
-        ndarray = op(-1*(i+1))
-    return ndarray
-
-def gamma_correct(fun):
-    def wrapper(*args, **kwargs):
-        args = list(args)
-        args[0] = np.power(args[0], 2.2)
-        args[1] = np.power(args[1], 2.2)
-        args = tuple(args)
-        result = fun(*args, **kwargs)
-        return np.power(result, 1/2.2)
-    return wrapper
-
-def clip_color(fun):
-    def wrapper(*args, **kwargs):
-        return np.clip(fun(*args, **kwargs), 0.0, 1.0)
-    return wrapper
-
-# linear_srgb_matrix = np.array([[0.4124, 0.3576, 0.1805],
-#                                [0.2126, 0.7152, 0.0722],
-#                                [0.0193, 0.1192, 0.9505]])
-
-# linear_srgb_matrix_inv = np.array([[ 3.2406, -1.5372, -0.4986],
-#                                    [-0.9689,  1.8758,  0.0415],
-#                                    [ 0.0557, -0.2040,  1.0570]])
-
-# def linear_color_correction(fun):
-#     def wrapper(*args, **kwargs):
-#         args = list(args)
-#         inds = args[0] <= 0.04045
-#         ninds = args[0] > 0.04045
-#         for i in range(2):
-#             args[i][inds] = args[i][inds] / 12.92
-#             args[i][ninds] = np.power((args[i][ninds] + 0.055) / 1.055, 2.4)
-#             for x in range(args[i].shape[0]):
-#                 for y in range(args[i].shape[1]):
-#                     args[i][x,y,:] = np.matmul(linear_srgb_matrix, args[i][x,y,:])
-#         args = tuple(args)
-#         result = fun(*args, **kwargs)
-
-#         for x in range(result.shape[0]):
-#             for y in range(result.shape[1]):
-#                 result[x,y,:] = np.matmul(linear_srgb_matrix_inv, result[x,y,:])
-#         inds = result <= 0.0031308
-#         ninds = result > 0.0031308
-#         result[inds] = result[inds] * 12.92
-#         result[ninds] = np.power(result[ninds], 1.0/2.4) * 1.055 - 0.055
-#         return result
-#     return wrapper
-
-
-@gamma_correct
-def composite_alpha_over(F, B, alpha_F, alpha_B = 1):
-    return (F*alpha_F + B*alpha_B*(1-alpha_F)) / (alpha_F + alpha_B*(1-alpha_F))
-
-def composite_alpha_blend(F, B, alpha):
-    return F*alpha + B*(1-alpha)
-
-def linear_burn(F, B):
-    burn = F + B - 1
-    burn[burn < 0.0] = 0.0
-    return burn
-    
-def difference(F, B):
-    return np.abs(F - B)
-
-@clip_color
-def linear_light(F, B):
-    result = np.zeros_like(F)
-    inds = F <= 0.5
-    ninds = F > 0.5
-    result[inds] = B[inds] + 2.0 * F[inds] - 1
-    result[ninds] = 2.0 * (F[ninds] - 0.5) + B[ninds]
-    return result
-
-@clip_color
-def hard_light(F, B):
-    result = np.zeros_like(F)
-    inds = B < 0.5
-    ninds = B >= 0.5
-    result[inds] = 2 * F[inds] * B[inds]
-    result[ninds] = 1 - (2*(1 - F[ninds])*(1 - B[ninds]))
-    return result
-
-@clip_color
-def color_dodge(F, B):
-    return B / (1.000001 - F)
-
-@clip_color
-def exclusion(F, B):
-    return F + B - 2*F*B
-
-@clip_color
-def saturation(img, R, G, B):
-    img[:,:,0] *= R
-    img[:,:,1] *= G
-    img[:,:,2] *= B
-    return img
-
-@clip_color
-def contrast(img, c, b):
-    return (img - 0.5) * c + 0.5 + b*c
-
-def generate_composite(work_queue, result_queue):
-    while True:
-        try:
-            job = work_queue.get()
-            if job is None:
-                break
-            files_this_timestamp, timestamp, processed_images_dir = job
-            filename = f"Composite-{int(timestamp)}.jpg"
-            filepath = os.path.join(processed_images_dir, filename)
-            if os.path.isfile(filepath):
-                result_queue.put(("Exists", timestamp))
-                continue
-
-            # image_names = ["094Å", "131Å", "171Å", "195Å", "284Å", "304Å"]
-            data = []
-            for i in range(6):
-                img = Image.open(files_this_timestamp[i])
-                trimmed_img_data = np.array(img)[40:-40,40:-40,:3] # Trim off edges of image to remove text
-                normalized_img_data = trimmed_img_data / 255.0 # Normalize to float 0.0-1.0 instead of uint8
-                srgb_img_data = np.power(normalized_img_data, 2.2) # Gamma correct to sRGB color space
-                data.append(normalized_img_data)
-
-            # Assemble composite image
-            composite_image_data = data[4] # Start with (284Å)
-            # Do a linear burn with 304Å at 95% alpha
-            composite_image_data = composite_alpha_over(linear_burn(data[5], composite_image_data), composite_image_data, 0.95)
-            # Do a difference operation with 195Å at 95% alpha
-            composite_image_data = composite_alpha_over(exclusion(data[3], composite_image_data), composite_image_data, 0.90)
-            # Do a linear_light layer op with 171Å
-            composite_image_data = linear_light(data[2], composite_image_data)
-            # Do a hard_light layer op with 131Å
-            composite_image_data = composite_alpha_over(hard_light(data[1], composite_image_data), composite_image_data, 0.20)
-            # Do a color_dodge layer op with 094Å
-            composite_image_data = composite_alpha_over(color_dodge(data[0], composite_image_data), composite_image_data, 0.25)
-            # Do an exclusion layer op with 094Å
-            composite_image_data = composite_alpha_over(exclusion(data[0], composite_image_data), composite_image_data, 0.80)
-            # Tweak the colors a little
-            composite_image_data = saturation(composite_image_data, 1.0, 0.95, 1.15)
-            # Boost contrast
-            composite_image_data = contrast(composite_image_data, 1.5, 0.15)
-
-            # Now shrink the component images and assemble them alongside the composite.
-            new_dim = composite_image_data.shape[0] // 3
-            # Enlarge the composite to fit the new images
-            composite_image_data = np.pad(composite_image_data, ((0,0),(new_dim, new_dim),(0,0)))
-            for i in range(6):
-                resized = bin_ndarray(data[i], (new_dim, new_dim, 3))
-                if i < 3:
-                    composite_image_data[i*new_dim:(i+1)*new_dim, :new_dim, :] = resized
-                else:
-                    composite_image_data[(i-3)*new_dim:(i-2)*new_dim, -new_dim:, :] = resized
-
-            img = Image.fromarray((255 * composite_image_data).astype('uint8'))
-            timestring = datetime.datetime.fromtimestamp(timestamp, tz = datetime.UTC).strftime('%Y-%m-%d  %H:%M:%S')
-            ImageDraw.Draw(img).text((655, 15), f"NOAA GOES Sattelite SUVI Composite - {timestring} UTC",(255,255,255), font_size = 24)
-            img.save(filepath, quality = 90)
-            result_queue.put(("Created", timestamp))
-
-            # plt.figure("Composite")
-            # plt.imshow(composite_image_data)
-            # plt.show()
-            # plt.close('all')
-        except Exception as e:
-            result_queue.put((e, timestamp))
-
-
-if __name__ == "__main__":
-    stored_images_dir = r"..\comp"
-    processed_images_dir = r"..\composite"
-    nworkers = 8
-    os.makedirs(processed_images_dir, exist_ok=True)
-
-    files_sorted_by_timestamp = defaultdict(list)
-    for root, dirs, files in os.walk(stored_images_dir):
-        for f in files:
-            if f.endswith(".png"):
-                file_parts = f.split("_")
-                measurement = file_parts[1]
-                sattelite = file_parts[2]
-                measure_end_time = datetime.datetime.strptime(file_parts[4][1:16], "%Y%m%dT%H%M%S")
-                measure_end_time.replace(tzinfo=datetime.timezone.utc)
-                measure_end_time = calendar.timegm(measure_end_time.timetuple())
-                files_sorted_by_timestamp[measure_end_time].append(os.path.join(root,f))
-
-    work_queue = Queue(maxsize = 3)
-    result_queue = Queue()
-    workers = []
-    for i in range(nworkers):
-        p = Process(target = generate_composite, args = (work_queue, result_queue), daemon=True)
-        p.start()
-        workers.append(p)
-    
-    for timestamp in tqdm.tqdm(files_sorted_by_timestamp, desc="Creating Composite Solar Images"):
-        files_this_timestamp = files_sorted_by_timestamp[timestamp]
-        files_this_timestamp = sorted(files_this_timestamp)
-        if not len(files_this_timestamp) == 7:
-            print(f"Detected a file gap at: {timestamp}")
-            continue
-        
-        work_queue.put((files_this_timestamp, timestamp, processed_images_dir))
-
-    ncreated = 0
-    nexists = 0
-    for _ in range(len(files_sorted_by_timestamp)):
-        result = result_queue.get(5.0)
-        if result[0] == "Exists":
-            nexists += 1
-        elif result[0] == "Created":
-            ncreated += 1
-        else:
-            print(f"A worker encountered an exception on job {result[1]}: {result[0]}")
-
-    for _ in range(nworkers):
-        try:
-            work_queue.put(None, timeout=1.0)
-        except:
-            break
-
-    for w in workers:
-        w.join(5.0)
-
-    print("Done")
\ No newline at end of file
diff --git a/merger_FITS.py b/merger_FITS.py
index 9d99fc4..9dc9447 100644
--- a/merger_FITS.py
+++ b/merger_FITS.py
@@ -1,579 +1,657 @@
-import os
-import time
-import calendar
-import datetime
-from collections import defaultdict
-from multiprocessing import Queue, Process
-import re
-import warnings
-import queue
-import traceback
-
-import tqdm
-from PIL import Image, ImageDraw, ImageFont
-import numpy as np
-from matplotlib import pyplot as plt
-from astropy.io import fits
-import palettable
-
-def lowpriority():
-    """ Set the priority of the process to below-normal."""
-
-    import sys
-    try:
-        sys.getwindowsversion()
-    except AttributeError:
-        isWindows = False
-    else:
-        isWindows = True
-
-    if isWindows:
-        # Based on:
-        #   "Recipe 496767: Set Process Priority In Windows" on ActiveState
-        #   http://code.activestate.com/recipes/496767/
-        import win32api,win32process,win32con # pywin32
-
-        pid = win32api.GetCurrentProcessId()
-        handle = win32api.OpenProcess(win32con.PROCESS_ALL_ACCESS, True, pid)
-        win32process.SetPriorityClass(handle, win32process.BELOW_NORMAL_PRIORITY_CLASS)
-    else:
-        import os
-
-        os.nice(1)
-
-def bin_ndarray(ndarray, new_shape, operation='mean'):
-    """
-    Bins an ndarray in all axes based on the target shape, by summing or
-        averaging.
-
-    Number of output dimensions must match number of input dimensions and 
-        new axes must divide old ones.
-
-    Example
-    -------
-    >>> m = np.arange(0,100,1).reshape((10,10))
-    >>> n = bin_ndarray(m, new_shape=(5,5), operation='sum')
-    >>> print(n)
-
-    [[ 22  30  38  46  54]
-     [102 110 118 126 134]
-     [182 190 198 206 214]
-     [262 270 278 286 294]
-     [342 350 358 366 374]]
-
-    """
-    operation = operation.lower()
-    if not operation in ['sum', 'mean']:
-        raise ValueError("Operation not supported.")
-    if ndarray.ndim != len(new_shape):
-        raise ValueError("Shape mismatch: {} -> {}".format(ndarray.shape,
-                                                           new_shape))
-    compression_pairs = [(d, c//d) for d,c in zip(new_shape,
-                                                  ndarray.shape)]
-    flattened = [l for p in compression_pairs for l in p]
-    ndarray = ndarray.reshape(flattened)
-    for i in range(len(new_shape)):
-        op = getattr(ndarray, operation)
-        ndarray = op(-1*(i+1))
-    return ndarray
-
-def gamma_correct(fun):
-    def wrapper(*args, **kwargs):
-        args = list(args)
-        args[0] = np.power(args[0], 2.2)
-        args[1] = np.power(args[1], 2.2)
-        args = tuple(args)
-        result = fun(*args, **kwargs)
-        return np.power(result, 1/2.2)
-    return wrapper
-
-def clip_color(fun):
-    def wrapper(*args, **kwargs):
-        return np.clip(fun(*args, **kwargs), 0.0, 1.0)
-    return wrapper
-
-# linear_srgb_matrix = np.array([[0.4124, 0.3576, 0.1805],
-#                                [0.2126, 0.7152, 0.0722],
-#                                [0.0193, 0.1192, 0.9505]])
-
-# linear_srgb_matrix_inv = np.array([[ 3.2406, -1.5372, -0.4986],
-#                                    [-0.9689,  1.8758,  0.0415],
-#                                    [ 0.0557, -0.2040,  1.0570]])
-
-# def linear_color_correction(fun):
-#     def wrapper(*args, **kwargs):
-#         args = list(args)
-#         inds = args[0] <= 0.04045
-#         ninds = args[0] > 0.04045
-#         for i in range(2):
-#             args[i][inds] = args[i][inds] / 12.92
-#             args[i][ninds] = np.power((args[i][ninds] + 0.055) / 1.055, 2.4)
-#             for x in range(args[i].shape[0]):
-#                 for y in range(args[i].shape[1]):
-#                     args[i][x,y,:] = np.matmul(linear_srgb_matrix, args[i][x,y,:])
-#         args = tuple(args)
-#         result = fun(*args, **kwargs)
-
-#         for x in range(result.shape[0]):
-#             for y in range(result.shape[1]):
-#                 result[x,y,:] = np.matmul(linear_srgb_matrix_inv, result[x,y,:])
-#         inds = result <= 0.0031308
-#         ninds = result > 0.0031308
-#         result[inds] = result[inds] * 12.92
-#         result[ninds] = np.power(result[ninds], 1.0/2.4) * 1.055 - 0.055
-#         return result
-#     return wrapper
-
-
-@gamma_correct
-def composite_alpha_over(F, B, alpha_F, alpha_B = 1):
-    return (F*alpha_F + B*alpha_B*(1-alpha_F)) / (alpha_F + alpha_B*(1-alpha_F))
-
-def composite_alpha_blend(F, B, alpha):
-    return F*alpha + B*(1-alpha)
-
-def linear_burn(F, B):
-    burn = F + B - 1
-    burn[burn < 0.0] = 0.0
-    return burn
-    
-def difference(F, B):
-    d = np.abs(F - B)
-    if d.shape[2] == 4: # Preserve alpha of base image
-        d[:,:,3] = B[:,:,3]
-    return d
-
-@clip_color
-def linear_light(F, B):
-    result = np.zeros_like(F)
-    inds = F <= 0.5
-    ninds = F > 0.5
-    result[inds] = B[inds] + 2.0 * F[inds] - 1
-    result[ninds] = 2.0 * (F[ninds] - 0.5) + B[ninds]
-    return result
-
-@clip_color
-def hard_light(F, B):
-    result = np.zeros_like(F)
-    inds = B < 0.5
-    ninds = B >= 0.5
-    result[inds] = 2 * F[inds] * B[inds]
-    result[ninds] = 1 - (2*(1 - F[ninds])*(1 - B[ninds]))
-    return result
-
-@clip_color
-def color_dodge(F, B):
-    return B / (1.000001 - F)
-
-@clip_color
-def exclusion(F, B):
-    d = F + B - 2*F*B
-    if d.shape[2] == 4: # Preserve alpha of base image
-        d[:,:,3] = B[:,:,3]
-    return d
-
-@clip_color
-def saturation(img, R, G, B):
-    img[:,:,0] *= R
-    img[:,:,1] *= G
-    img[:,:,2] *= B
-    return img
-
-@clip_color
-def contrast(img, c, b):
-    return (img - 0.5) * c + 0.5 + b*c
-
-def rgb_to_hsl(img):
-    r = img[:,:,0]
-    g = img[:,:,1]
-    b = img[:,:,2]
-    cmax = np.copy(r)
-    cmax[g > cmax] = g[g > cmax]
-    cmax[b > cmax] = b[b > cmax]
-    cmin = np.copy(r)
-    cmin[g < cmin] = g[g < cmin]
-    cmin[b < cmin] = b[b < cmin]
-    delta = cmax - cmin
-
-    
-    # Calc hue
-    hue = np.zeros_like(r)
-    inds = cmax == r
-    with warnings.catch_warnings():
-        warnings.filterwarnings('ignore')
-        hue[inds] = 60 * np.mod((g[inds]-b[inds])/delta[inds], 6)
-        inds = cmax == g
-        hue[inds] = 60 * ((b[inds]-r[inds])/delta[inds] + 2)
-        inds = cmax == b
-        hue[inds] = 60 * ((r[inds]-g[inds])/delta[inds] + 4)
-    hue[np.isnan(hue)] = 0
-    hue[hue < 0] = hue[hue < 0] + 360 # Make negative hue values positive behind 360
-
-    # Calc lightness / luminance
-    luminance = (cmax + cmin) / 2.0
-
-    # Calc saturation
-    saturation = np.zeros_like(r)
-    inds = delta != 0
-    saturation[inds] = delta[inds] / (1.0 - np.abs(2 * luminance[inds] - 1.0))
-
-    # Multiply luminance and saturation by 100 to scale them to the appropriate range (0-100)
-    saturation *= 100.0
-    luminance *= 100.0
-
-
-    if img.shape[2] == 4: # Preserve alpha of original image
-        return np.stack([hue, saturation, luminance, img[:,:,3]], -1)
-    else:
-        return np.stack([hue, saturation, luminance], -1)
-
-def hsl_to_rgb(img):
-    hue = img[:,:,0]
-    saturation = img[:,:,1]
-    luminance = img[:,:,2]
-    saturation /= 100.0
-    luminance /= 100.0
-    c = (1.0 - np.abs(2.0 * luminance - 1.0)) * saturation
-    x = c * (1.0 - np.abs((hue/60.0) % 2.0 - 1.0))
-    m = luminance - c / 2.0
-    r = np.zeros_like(hue)
-    g = np.zeros_like(hue)
-    b = np.zeros_like(hue)
-
-    inds1 = np.logical_and(0.0 <= hue, hue < 60.0)
-    r[inds1] = c[inds1]
-    g[inds1] = x[inds1]
-    inds2 = np.logical_and(60.0 <= hue, hue < 120.0)
-    r[inds2] = x[inds2]
-    g[inds2] = c[inds2]
-    inds3 = np.logical_and(120.0 <= hue, hue < 180.0)
-    g[inds3] = c[inds3]
-    b[inds3] = x[inds3]
-    inds4 = np.logical_and(180.0 <= hue, hue < 240.0)
-    g[inds4] = x[inds4]
-    b[inds4] = c[inds4]
-    inds5 = np.logical_and(240.0 <= hue, hue < 300.0)
-    r[inds5] = x[inds5]
-    b[inds5] = c[inds5]
-    inds6 = np.logical_and(240.0 <= hue, hue < 300.0)
-    r[inds6] = c[inds6]
-    b[inds6] = x[inds6]
-
-    r += m
-    g += m
-    b += m
-
-    if img.shape[2] == 4: # Preserve alpha of original image
-        return np.stack([r, g, b, img[:,:,3]], -1)
-    else:
-        return np.stack([r, g, b], -1)
-
-def generate_composite(work_queue, result_queue):
-    lowpriority()
-    cmaps =[palettable.cmocean.sequential.Ice_5.mpl_colormap, 
-            palettable.cmocean.sequential.Ice_20.mpl_colormap, 
-            palettable.cmocean.sequential.Turbid_5_r.mpl_colormap, 
-            palettable.cmocean.sequential.Turbid_20_r.mpl_colormap, 
-            plt.colormaps.get_cmap('gist_heat'), 
-            plt.colormaps.get_cmap('afmhot')]
-    # Modify colormaps to start at perfect black (when they otherwise start at very dark colors)
-    for cmi in range(0,4):
-        for c in ['red','green','blue']:
-            for i in range(3):
-                cmaps[cmi]._segmentdata[c][0][i] = 0.0
-    # These values are used to map floating point radiance values to colors using the above color maps.
-    vmins =  [0.050, 0.05, 00.100, 00.10, 00.100, 00.1]
-    vmaxs =  [8.000, 8.00, 20.000, 30.00, 40.000, 90.0]
-    gammas = [0.375, 0.40, 00.425, 00.45, 00.475, 00.5]
-    trimx = 64
-    trimy = 100
-    fnt1 = ImageFont.truetype("OpenSans-Regular.ttf", size = 24)
-    fnt2 = ImageFont.truetype("OpenSans-Regular.ttf", size = 16)
-    while True:
-        try:
-            job = work_queue.get()
-            if job is None:
-                result_queue.cancel_join_thread()
-                return
-            files_this_timestamp, timestamp, processed_images_dir, synthetic_data = job
-            synthetic_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}_s.jpg")
-            normal_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}.jpg")
-            filepath = None
-            if synthetic_data:
-                if os.path.isfile(synthetic_filepath):
-                    result_queue.put(("Exists", timestamp))
-                    continue
-                filepath = synthetic_filepath
-            else:
-                if os.path.isfile(synthetic_filepath):
-                    os.remove(synthetic_filepath)
-                if os.path.isfile(normal_filepath):
-                    result_queue.put(("Exists", timestamp))
-                    continue
-                filepath = normal_filepath
-
-            base_imgs = []
-            for i in range(6):
-                raw_data = np.flip(fits.getdata(files_this_timestamp[i]), 0)[trimy:-trimy,trimx:-trimx] # Trim and reorient the image to match our final desired dimensions
-                raw_data[raw_data < 0.0] = 0.0 # Remove non-zero data because it doesn't makes sense (supposed to be std Radiance)
-                base_imgs.append(cmaps[i](np.clip((raw_data - vmins[i]) / vmaxs[i], 0, 1.0)**gammas[i])[:,:,:3])
-                # plt.figure(image_names[i])
-                # plt.imshow(base_imgs[-1])
-
-
-            # plt.figure("Initial Blend")
-            composite_image_data = composite_alpha_over(base_imgs[4], base_imgs[5], 0.2)**0.5
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Linear Burn with 304")
-            composite_image_data = composite_alpha_over(linear_burn(base_imgs[5], composite_image_data), composite_image_data, 0.60)
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Light Ops with mid bands")
-            mix_img = composite_alpha_over(exclusion(base_imgs[3], composite_image_data), composite_image_data, 0.95)
-            mix_img = composite_alpha_over(linear_light(base_imgs[2], mix_img), mix_img, 1.0)**0.75
-            composite_image_data = composite_alpha_over(mix_img, composite_image_data, 0.5)
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Mix in mid 131")
-            composite_image_data = composite_alpha_over(base_imgs[2], composite_image_data, 0.25) # Mix in a small amount of 131Å for the nice streamers
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Mid diff")
-            mix_img = difference(base_imgs[3], base_imgs[2]) # 171Å - 131Å
-            # plt.imshow(mix_img)
-
-            # plt.figure("HSL ops with mid")
-            comp_hsl = rgb_to_hsl(composite_image_data)
-            mix_img_hsl = rgb_to_hsl(mix_img)
-            del mix_img
-            base_img2_hsl = rgb_to_hsl(base_imgs[2])
-            base_img3_hsl = rgb_to_hsl(base_imgs[3])
-            comp_hsl = np.copy(comp_hsl)
-            comp_hsl[:,:,0] += 0.025*mix_img_hsl[:,:,0] # Rotate hue based on mix_1_hsl
-            del mix_img_hsl
-            comp_hsl[:,:,0][comp_hsl[:,:,0] > 360.0] -= 360.0
-            comp_hsl[:,:,1] -= 0.1*base_img3_hsl[:,:,1] # Reduce saturation based on base_img3
-            comp_hsl[:,:,1] = np.clip(comp_hsl[:,:,1], 0.0, 100.0)
-            comp_hsl[:,:,2] += 0.5*base_img2_hsl[:,:,2] # Boost luminance based on base_img2
-            comp_hsl[:,:,1] = np.clip(comp_hsl[:,:,2], 0.0, 100.0)
-            composite_image_data = hsl_to_rgb(comp_hsl)
-            del comp_hsl
-            composite_image_data = saturation(composite_image_data, 1.0, 0.8, 0.1) # Remove some blue and green
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Hue shifted 131")
-            mix_img_hsl = rgb_to_hsl(base_imgs[1])
-            mix_img_hsl[:,:,0] -= 50
-            mix_img_hsl[:,:,0][mix_img_hsl[:,:,0] < 0.0] += 360.0
-            mix_img = hsl_to_rgb(mix_img_hsl)
-            del mix_img_hsl
-            # plt.imshow(mix_img)
-
-            # plt.figure("Hard Light with hue shifted 131")
-            composite_image_data = composite_alpha_over(hard_light(mix_img, composite_image_data), composite_image_data, 0.2)
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Adjusted 094")
-            mix_img = saturation(base_imgs[0], 1.15, 1.2, 1.05)
-            mix_img = contrast(mix_img, 1.5, 0.0)
-            # plt.imshow(mix_img)
-
-            # plt.figure("Color Dodge with adjusted 094")
-            composite_image_data = composite_alpha_over(color_dodge(mix_img, composite_image_data), composite_image_data, 0.5)
-            # plt.imshow(composite_image_data)
-
-            # plt.figure("Exclusion with adjusted 094")
-            composite_image_data = composite_alpha_over(exclusion(mix_img, composite_image_data), composite_image_data, 0.65)
-            # plt.imshow(composite_image_data)
-
-            del mix_img
-
-            # plt.figure("Final Image")
-            composite_image_data = saturation(composite_image_data, 1.0, 1.1, 1.2)
-            composite_image_data = contrast(composite_image_data, 1.20, 0.00)
-            # plt.imshow(composite_image_data)
-
-            # We have our final image
-            # plt.show()
-
-            # Now shrink the component images and assemble them alongside the composite.
-            new_dimx = composite_image_data.shape[1] // 3
-            new_dimy = composite_image_data.shape[0] // 3
-            # Enlarge the composite to fit the new images
-            composite_image_data = np.pad(composite_image_data, ((0,0),(new_dimx, new_dimx),(0,0)))
-            for i in range(6):
-                img = base_imgs[i]
-                img = bin_ndarray(img, (new_dimy, new_dimx, 3)) # Shrink down to 1/3 for assembly
-                img = contrast(img, 1.25, 0.0)
-                xdimoff = i%2 * (composite_image_data.shape[1] - new_dimx)
-                ydimoff = i//2*new_dimy
-                composite_image_data[ydimoff:ydimoff+new_dimy, xdimoff:xdimoff+new_dimx, :] = img
-
-            img = Image.fromarray((255 * composite_image_data).astype('uint8'))
-            timestring = datetime.datetime.fromtimestamp(timestamp, tz = datetime.UTC).strftime('%Y-%m-%d  %H:%M:%S')
-            ImageDraw.Draw(img).text((602, 15), f"NOAA GOES Satellite SUVI Composite - {timestring} UTC",(255,255,255), font = fnt1)
-            for i in range(6): # Draw component angstrom labels
-                if i%2 == 0:
-                    xdimtxtoff = 5
-                else:
-                    xdimtxtoff = composite_image_data.shape[1] - 44
-                ydimtxtoff = i//2*new_dimy + new_dimy / 2.0 - 14
-                ImageDraw.Draw(img).text((xdimtxtoff, ydimtxtoff), image_names[i], font = fnt2)
-            img.save(filepath, quality = 95)
-            result_queue.put(("Created", timestamp))
-        
-        except KeyboardInterrupt:
-            return
-        except Exception as e:
-            traceback.print_exception(e)
-            result_queue.put((e, timestamp))
-
-
-image_names = ["094A", "131A", "171A", "195A", "284A", "304A"]
-
-if __name__ == "__main__":
-    stored_fits_dirs = [r"..\Data\goes16\l2\data", r"..\Data\goes18\l2\data"]
-    processed_images_dirs = [r"..\composite\goes16", r"..\composite\goes18"]
-    starttime = calendar.timegm(datetime.datetime(2024, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-    stoptime = calendar.timegm(datetime.datetime(2025, 1, 1, tzinfo=datetime.timezone.utc).timetuple())
-
-    regex_filename = r"dr_suvi-l2-ci\d{3}_g(16|18)_s\S*\_f.fits$"
-
-    nworkers = 16
-    max_time_gap = 3
-    fill_missing_data = False
-    ignore_errors = True
-
-    if ignore_errors:
-        regex_filename = r"dr_suvi-l2-ci\d{3}_g(16|18)_s\S*.fits$"
-
-    file_prefixes = ["dr_suvi-l2-ci" + n[:-1] for n in image_names]
-    
-    # Testing
-    # stored_fits_dirs = [r"..\fits_test_2024"]
-
-    work_queue = Queue(maxsize = nworkers)
-    result_queue = Queue()
-    workers = []
-    for i in range(nworkers):
-        p = Process(target = generate_composite, args = (work_queue, result_queue), daemon=True)
-        p.start()
-        workers.append(p)
-
-    lowpriority()
-    ncreated = 0
-    nexists = 0
-    nfailed = 0
-    black_image = Image.fromarray(np.zeros((1080, 1920, 3), dtype='uint8'))
-    try:
-        for stored_fits_dir, processed_images_dir in zip(stored_fits_dirs, processed_images_dirs):
-            files_by_timestamp = defaultdict(list)
-            num_found_files = 0
-            os.makedirs(processed_images_dir, exist_ok=True)
-            filename_tester = re.compile(regex_filename)
-            print(f"Searching for FITS files in: {stored_fits_dir}")
-            for root, dirs, files in tqdm.tqdm(os.walk(stored_fits_dir), desc="Searching"):
-                for f in files:
-                    if filename_tester.match(f):
-                        file_parts = f.split("_")
-                        # measurement = file_parts[1]
-                        # sattelite = file_parts[2]
-                        measure_end_time = int(datetime.datetime.strptime(file_parts[4][1:16] + " +0000", "%Y%m%dT%H%M%S %z").timestamp())
-                        if (measure_end_time >= starttime) and (measure_end_time < stoptime):
-                            files_by_timestamp[measure_end_time].append(os.path.join(root,f))
-                            num_found_files += 1
-                    
-            print(f"Found {num_found_files} FITS files. Starting conversion.")
-            if num_found_files == 0:
-                exit(3)
-
-            sorted_times = sorted(list(files_by_timestamp.keys()))
-            min_time = sorted_times[0]
-            max_time = sorted_times[-1]
-            diff_times = np.diff(sorted_times)
-            unique, counts = np.unique(diff_times, return_counts=True)
-            interval = unique[0] # This is the amount of time between each sample in seconds
-            assert np.sum((unique % interval) > 0) == 0 # Ensure all our timestamps align perfectly with our interval
-
-            last_good_files = None
-            last_good_file_times = None
-            # Lets find the first and last timestamps in the sorted_times from our files which actually have a full set of 6/6 images available
-            #    This check will prevent partially downloaded sets of data from generating composite images which have "filled in" data from detected gaps
-            #    which would have been later filled with downloaded imagery.
-            f = None
-            l = None
-            for i, timestamp in enumerate(sorted_times):
-                if len(files_by_timestamp[timestamp]) == 6:
-                    f = i
-                    break
-            for i, timestamp in enumerate(reversed(sorted_times)):
-                if len(files_by_timestamp[timestamp]) == 6:
-                    l = len(sorted_times) - 1 - i
-                    break
-            assert f is not None # Check to make sure we found valid indices
-            assert l is not None
-            assert f != l 
-            sorted_times = sorted_times[f:l] # Limit our composite image generation to only files within the valid range
-            last_good_files = files_by_timestamp[sorted_times[0]]
-            for timestamp in tqdm.tqdm(sorted_times, desc="Creating Composite Solar Images"):
-                if timestamp < min_time or timestamp > max_time:
-                    continue
-                # Collect completed jobs and record completion status
-                while True:
-                    try:
-                        result = result_queue.get_nowait()
-                        if result[0] == "Exists":
-                            nexists += 1
-                        elif result[0] == "Created":
-                            ncreated += 1
-                        else:
-                            print(f"A worker encountered an exception on job {result[1]}: {result[0]}")
-                            nfailed += 1
-                    except queue.Empty:
-                        break
-
-                # Submit new jobs
-                files_this_timestamp = files_by_timestamp[timestamp]
-                files_this_timestamp = sorted(files_this_timestamp)
-                if (not len(files_this_timestamp) == 6):
-                    if fill_missing_data:
-                        print(f"Invalid or incomplete sensor records for {timestamp} | {datetime.datetime.fromtimestamp(timestamp, datetime.UTC).strftime('%Y-%m-%d %H:%M:%S %Z')} - {len(files_this_timestamp)}/6 filling from last good data.")
-                        files_for_job = []
-                        for i, prefix in enumerate(file_prefixes):
-                            found = False
-                            for f in files_this_timestamp:
-                                filename = os.path.split(f)[-1]
-                                if filename.startswith(prefix):
-                                    files_for_job.append(f)
-                                    last_good_files[i] = f
-                                    last_good_file_times[i] = timestamp
-                                    found = True
-                                    break
-                            if not found: # We did not find this prefix, use the last good file
-                                time_gap = (timestamp - last_good_file_times[i]) // interval
-                                if time_gap <= max_time_gap:
-                                    files_for_job.append(last_good_files[i])
-                                else:
-                                    print(f"Detected a gap of {time_gap} frames at {timestamp} | {datetime.datetime.fromtimestamp(timestamp, datetime.UTC).strftime('%Y-%m-%d %H:%M:%S %Z')}")
-                        if len(files_for_job) == 6:
-                            work_queue.put((files_for_job, timestamp, processed_images_dir, True))
-                else: # We have a complete file set, update the last_good_files
-                    last_good_files = files_this_timestamp
-                    last_good_file_times = [timestamp for _ in last_good_files]
-                    work_queue.put((files_this_timestamp, timestamp, processed_images_dir, ignore_errors))
-
-    except KeyboardInterrupt:
-        print("Finishing current jobs and exiting")
-
-    for _ in range(nworkers):
-        try:
-            work_queue.put(None, timeout=10.0)
-        except:
-            break
-
-    for w in workers:
-        # w.join(10.0)
-        w.join()
-
-    print(f"Created {ncreated} | Already had {nexists} | Failed {nfailed}")
\ No newline at end of file
+import os
+import sys
+import calendar
+import datetime
+from collections import defaultdict
+from multiprocessing import Queue, Process
+import warnings
+import queue
+import traceback
+
+import tqdm
+from PIL import Image, ImageDraw, ImageFont
+import numpy as np
+from matplotlib import pyplot as plt
+from astropy.io import fits
+import palettable
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+def lowpriority():
+    """ Set the priority of the process to below-normal."""
+
+    import sys
+    try:
+        sys.getwindowsversion()
+    except AttributeError:
+        isWindows = False
+    else:
+        isWindows = True
+
+    if isWindows:
+        # Based on:
+        #   "Recipe 496767: Set Process Priority In Windows" on ActiveState
+        #   http://code.activestate.com/recipes/496767/
+        import win32api,win32process,win32con # pywin32
+
+        pid = win32api.GetCurrentProcessId()
+        handle = win32api.OpenProcess(win32con.PROCESS_ALL_ACCESS, True, pid)
+        win32process.SetPriorityClass(handle, win32process.BELOW_NORMAL_PRIORITY_CLASS)
+    else:
+        import os
+
+        os.nice(1)
+
+def bin_ndarray(ndarray, new_shape, operation='mean'):
+    """
+    Bins an ndarray in all axes based on the target shape, by summing or
+        averaging.
+
+    Number of output dimensions must match number of input dimensions and 
+        new axes must divide old ones.
+
+    Example
+    -------
+    >>> m = np.arange(0,100,1).reshape((10,10))
+    >>> n = bin_ndarray(m, new_shape=(5,5), operation='sum')
+    >>> print(n)
+
+    [[ 22  30  38  46  54]
+     [102 110 118 126 134]
+     [182 190 198 206 214]
+     [262 270 278 286 294]
+     [342 350 358 366 374]]
+
+    """
+    operation = operation.lower()
+    if not operation in ['sum', 'mean']:
+        raise ValueError("Operation not supported.")
+    if ndarray.ndim != len(new_shape):
+        raise ValueError("Shape mismatch: {} -> {}".format(ndarray.shape,
+                                                           new_shape))
+    compression_pairs = [(d, c//d) for d,c in zip(new_shape,
+                                                  ndarray.shape)]
+    flattened = [l for p in compression_pairs for l in p]
+    ndarray = ndarray.reshape(flattened)
+    for i in range(len(new_shape)):
+        op = getattr(ndarray, operation)
+        ndarray = op(-1*(i+1))
+    return ndarray
+
+def gamma_correct(fun):
+    def wrapper(*args, **kwargs):
+        args = list(args)
+        args[0] = np.power(args[0], 2.2)
+        args[1] = np.power(args[1], 2.2)
+        args = tuple(args)
+        result = fun(*args, **kwargs)
+        return np.power(result, 1/2.2)
+    return wrapper
+
+def clip_color(fun):
+    def wrapper(*args, **kwargs):
+        return np.clip(fun(*args, **kwargs), 0.0, 1.0)
+    return wrapper
+
+# linear_srgb_matrix = np.array([[0.4124, 0.3576, 0.1805],
+#                                [0.2126, 0.7152, 0.0722],
+#                                [0.0193, 0.1192, 0.9505]])
+
+# linear_srgb_matrix_inv = np.array([[ 3.2406, -1.5372, -0.4986],
+#                                    [-0.9689,  1.8758,  0.0415],
+#                                    [ 0.0557, -0.2040,  1.0570]])
+
+# def linear_color_correction(fun):
+#     def wrapper(*args, **kwargs):
+#         args = list(args)
+#         inds = args[0] <= 0.04045
+#         ninds = args[0] > 0.04045
+#         for i in range(2):
+#             args[i][inds] = args[i][inds] / 12.92
+#             args[i][ninds] = np.power((args[i][ninds] + 0.055) / 1.055, 2.4)
+#             for x in range(args[i].shape[0]):
+#                 for y in range(args[i].shape[1]):
+#                     args[i][x,y,:] = np.matmul(linear_srgb_matrix, args[i][x,y,:])
+#         args = tuple(args)
+#         result = fun(*args, **kwargs)
+
+#         for x in range(result.shape[0]):
+#             for y in range(result.shape[1]):
+#                 result[x,y,:] = np.matmul(linear_srgb_matrix_inv, result[x,y,:])
+#         inds = result <= 0.0031308
+#         ninds = result > 0.0031308
+#         result[inds] = result[inds] * 12.92
+#         result[ninds] = np.power(result[ninds], 1.0/2.4) * 1.055 - 0.055
+#         return result
+#     return wrapper
+
+
+@gamma_correct
+def composite_alpha_over(F, B, alpha_F, alpha_B = 1):
+    return (F*alpha_F + B*alpha_B*(1-alpha_F)) / (alpha_F + alpha_B*(1-alpha_F))
+
+def composite_alpha_blend(F, B, alpha):
+    return F*alpha + B*(1-alpha)
+
+def linear_burn(F, B):
+    burn = F + B - 1
+    burn[burn < 0.0] = 0.0
+    return burn
+    
+def difference(F, B):
+    d = np.abs(F - B)
+    if d.shape[2] == 4: # Preserve alpha of base image
+        d[:,:,3] = B[:,:,3]
+    return d
+
+@clip_color
+def linear_light(F, B):
+    result = np.zeros_like(F)
+    inds = F <= 0.5
+    ninds = F > 0.5
+    result[inds] = B[inds] + 2.0 * F[inds] - 1
+    result[ninds] = 2.0 * (F[ninds] - 0.5) + B[ninds]
+    return result
+
+@clip_color
+def hard_light(F, B):
+    result = np.zeros_like(F)
+    inds = B < 0.5
+    ninds = B >= 0.5
+    result[inds] = 2 * F[inds] * B[inds]
+    result[ninds] = 1 - (2*(1 - F[ninds])*(1 - B[ninds]))
+    return result
+
+@clip_color
+def color_dodge(F, B):
+    return B / (1.000001 - F)
+
+@clip_color
+def exclusion(F, B):
+    d = F + B - 2*F*B
+    if d.shape[2] == 4: # Preserve alpha of base image
+        d[:,:,3] = B[:,:,3]
+    return d
+
+@clip_color
+def saturation(img, R, G, B):
+    img[:,:,0] *= R
+    img[:,:,1] *= G
+    img[:,:,2] *= B
+    return img
+
+@clip_color
+def contrast(img, c, b):
+    return (img - 0.5) * c + 0.5 + b*c
+
+def rgb_to_hsl(img):
+    r = img[:,:,0]
+    g = img[:,:,1]
+    b = img[:,:,2]
+    cmax = np.copy(r)
+    cmax[g > cmax] = g[g > cmax]
+    cmax[b > cmax] = b[b > cmax]
+    cmin = np.copy(r)
+    cmin[g < cmin] = g[g < cmin]
+    cmin[b < cmin] = b[b < cmin]
+    delta = cmax - cmin
+
+    
+    # Calc hue
+    hue = np.zeros_like(r)
+    inds = cmax == r
+    with warnings.catch_warnings():
+        warnings.filterwarnings('ignore')
+        hue[inds] = 60 * np.mod((g[inds]-b[inds])/delta[inds], 6)
+        inds = cmax == g
+        hue[inds] = 60 * ((b[inds]-r[inds])/delta[inds] + 2)
+        inds = cmax == b
+        hue[inds] = 60 * ((r[inds]-g[inds])/delta[inds] + 4)
+    hue[np.isnan(hue)] = 0
+    hue[hue < 0] = hue[hue < 0] + 360 # Make negative hue values positive behind 360
+
+    # Calc lightness / luminance
+    luminance = (cmax + cmin) / 2.0
+
+    # Calc saturation
+    saturation = np.zeros_like(r)
+    inds = delta != 0
+    saturation[inds] = delta[inds] / (1.0 - np.abs(2 * luminance[inds] - 1.0))
+
+    # Multiply luminance and saturation by 100 to scale them to the appropriate range (0-100)
+    saturation *= 100.0
+    luminance *= 100.0
+
+
+    if img.shape[2] == 4: # Preserve alpha of original image
+        return np.stack([hue, saturation, luminance, img[:,:,3]], -1)
+    else:
+        return np.stack([hue, saturation, luminance], -1)
+
+def hsl_to_rgb(img):
+    hue = img[:,:,0]
+    saturation = img[:,:,1]
+    luminance = img[:,:,2]
+    saturation /= 100.0
+    luminance /= 100.0
+    c = (1.0 - np.abs(2.0 * luminance - 1.0)) * saturation
+    x = c * (1.0 - np.abs((hue/60.0) % 2.0 - 1.0))
+    m = luminance - c / 2.0
+    r = np.zeros_like(hue)
+    g = np.zeros_like(hue)
+    b = np.zeros_like(hue)
+
+    inds1 = np.logical_and(0.0 <= hue, hue < 60.0)
+    r[inds1] = c[inds1]
+    g[inds1] = x[inds1]
+    inds2 = np.logical_and(60.0 <= hue, hue < 120.0)
+    r[inds2] = x[inds2]
+    g[inds2] = c[inds2]
+    inds3 = np.logical_and(120.0 <= hue, hue < 180.0)
+    g[inds3] = c[inds3]
+    b[inds3] = x[inds3]
+    inds4 = np.logical_and(180.0 <= hue, hue < 240.0)
+    g[inds4] = x[inds4]
+    b[inds4] = c[inds4]
+    inds5 = np.logical_and(240.0 <= hue, hue < 300.0)
+    r[inds5] = x[inds5]
+    b[inds5] = c[inds5]
+    inds6 = np.logical_and(240.0 <= hue, hue < 300.0)
+    r[inds6] = c[inds6]
+    b[inds6] = x[inds6]
+
+    r += m
+    g += m
+    b += m
+
+    if img.shape[2] == 4: # Preserve alpha of original image
+        return np.stack([r, g, b, img[:,:,3]], -1)
+    else:
+        return np.stack([r, g, b], -1)
+
+#: Band labels drawn on the composite, and the order `composite_from_arrays`
+#: expects its six arrays in.
+image_names = ["094A", "131A", "171A", "195A", "284A", "304A"]
+
+
+# --- Composite rendering -------------------------------------------------------
+#
+# The blending below is the product's visual identity and is deliberately
+# untouched.  It was extracted from the worker loop so that callers holding six
+# bands *in memory* -- the bench, rendering frames that were reconstructed rather
+# than read from disk -- can produce the same image without first writing FITS.
+
+#: Radiance-to-colour mapping, per band, in the order of `image_names`.
+VMINS =  [0.050, 0.05, 00.100, 00.10, 00.100, 00.1]
+VMAXS =  [8.000, 8.00, 20.000, 30.00, 40.000, 90.0]
+GAMMAS = [0.375, 0.40, 00.425, 00.45, 00.475, 00.5]
+#: Trim applied to each 1280x1280 band to reach the final aspect ratio.
+TRIM_X = 64
+TRIM_Y = 100
+
+_render_cache = {}
+
+
+def _render_assets():
+    """Colormaps and fonts, built once per process.
+
+    The first four colormaps are mutated to start at true black; that mutation is
+    global to the palettable/matplotlib objects, so it must happen exactly once.
+    """
+    if not _render_cache:
+        cmaps = [palettable.cmocean.sequential.Ice_5.mpl_colormap,
+                 palettable.cmocean.sequential.Ice_20.mpl_colormap,
+                 palettable.cmocean.sequential.Turbid_5_r.mpl_colormap,
+                 palettable.cmocean.sequential.Turbid_20_r.mpl_colormap,
+                 plt.colormaps.get_cmap('gist_heat'),
+                 plt.colormaps.get_cmap('afmhot')]
+        # Start these maps at perfect black rather than a very dark colour.
+        for cmi in range(0, 4):
+            for c in ['red', 'green', 'blue']:
+                for i in range(3):
+                    cmaps[cmi]._segmentdata[c][0][i] = 0.0
+        font_path = os.path.join(os.path.dirname(os.path.abspath(__file__)),
+                                 "OpenSans-Regular.ttf")
+        _render_cache.update(
+            cmaps=cmaps,
+            fnt1=ImageFont.truetype(font_path, size=24),
+            fnt2=ImageFont.truetype(font_path, size=16),
+        )
+    return _render_cache
+
+
+def composite_from_arrays(arrays, timestamp):
+    """Render one composite from six in-memory bands.  Returns a PIL Image.
+
+    `arrays` are the six 1280x1280 radiance arrays in `image_names` order.
+    """
+    assets = _render_assets()
+    cmaps, fnt1, fnt2 = assets["cmaps"], assets["fnt1"], assets["fnt2"]
+
+    base_imgs = []
+    for i in range(6):
+        raw_data = np.flip(np.asarray(arrays[i], dtype=np.float32), 0)[TRIM_Y:-TRIM_Y, TRIM_X:-TRIM_X]
+        raw_data[raw_data < 0.0] = 0.0 # Remove non-zero data because it doesn't makes sense (supposed to be std Radiance)
+        base_imgs.append(cmaps[i](np.clip((raw_data - VMINS[i]) / VMAXS[i], 0, 1.0)**GAMMAS[i])[:,:,:3])
+        # plt.figure(image_names[i])
+        # plt.imshow(base_imgs[-1])
+
+
+    # plt.figure("Initial Blend")
+    composite_image_data = composite_alpha_over(base_imgs[4], base_imgs[5], 0.2)**0.5
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Linear Burn with 304")
+    composite_image_data = composite_alpha_over(linear_burn(base_imgs[5], composite_image_data), composite_image_data, 0.60)
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Light Ops with mid bands")
+    mix_img = composite_alpha_over(exclusion(base_imgs[3], composite_image_data), composite_image_data, 0.95)
+    mix_img = composite_alpha_over(linear_light(base_imgs[2], mix_img), mix_img, 1.0)**0.75
+    composite_image_data = composite_alpha_over(mix_img, composite_image_data, 0.5)
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Mix in mid 131")
+    composite_image_data = composite_alpha_over(base_imgs[2], composite_image_data, 0.25) # Mix in a small amount of 131Å for the nice streamers
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Mid diff")
+    mix_img = difference(base_imgs[3], base_imgs[2]) # 171Å - 131Å
+    # plt.imshow(mix_img)
+
+    # plt.figure("HSL ops with mid")
+    comp_hsl = rgb_to_hsl(composite_image_data)
+    mix_img_hsl = rgb_to_hsl(mix_img)
+    del mix_img
+    base_img2_hsl = rgb_to_hsl(base_imgs[2])
+    base_img3_hsl = rgb_to_hsl(base_imgs[3])
+    comp_hsl = np.copy(comp_hsl)
+    comp_hsl[:,:,0] += 0.025*mix_img_hsl[:,:,0] # Rotate hue based on mix_1_hsl
+    del mix_img_hsl
+    comp_hsl[:,:,0][comp_hsl[:,:,0] > 360.0] -= 360.0
+    comp_hsl[:,:,1] -= 0.1*base_img3_hsl[:,:,1] # Reduce saturation based on base_img3
+    comp_hsl[:,:,1] = np.clip(comp_hsl[:,:,1], 0.0, 100.0)
+    comp_hsl[:,:,2] += 0.5*base_img2_hsl[:,:,2] # Boost luminance based on base_img2
+    comp_hsl[:,:,1] = np.clip(comp_hsl[:,:,2], 0.0, 100.0)
+    composite_image_data = hsl_to_rgb(comp_hsl)
+    del comp_hsl
+    composite_image_data = saturation(composite_image_data, 1.0, 0.8, 0.1) # Remove some blue and green
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Hue shifted 131")
+    mix_img_hsl = rgb_to_hsl(base_imgs[1])
+    mix_img_hsl[:,:,0] -= 50
+    mix_img_hsl[:,:,0][mix_img_hsl[:,:,0] < 0.0] += 360.0
+    mix_img = hsl_to_rgb(mix_img_hsl)
+    del mix_img_hsl
+    # plt.imshow(mix_img)
+
+    # plt.figure("Hard Light with hue shifted 131")
+    composite_image_data = composite_alpha_over(hard_light(mix_img, composite_image_data), composite_image_data, 0.2)
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Adjusted 094")
+    mix_img = saturation(base_imgs[0], 1.15, 1.2, 1.05)
+    mix_img = contrast(mix_img, 1.5, 0.0)
+    # plt.imshow(mix_img)
+
+    # plt.figure("Color Dodge with adjusted 094")
+    composite_image_data = composite_alpha_over(color_dodge(mix_img, composite_image_data), composite_image_data, 0.5)
+    # plt.imshow(composite_image_data)
+
+    # plt.figure("Exclusion with adjusted 094")
+    composite_image_data = composite_alpha_over(exclusion(mix_img, composite_image_data), composite_image_data, 0.65)
+    # plt.imshow(composite_image_data)
+
+    del mix_img
+
+    # plt.figure("Final Image")
+    composite_image_data = saturation(composite_image_data, 1.0, 1.1, 1.2)
+    composite_image_data = contrast(composite_image_data, 1.20, 0.00)
+    # plt.imshow(composite_image_data)
+
+    # We have our final image
+    # plt.show()
+
+    # Now shrink the component images and assemble them alongside the composite.
+    new_dimx = composite_image_data.shape[1] // 3
+    new_dimy = composite_image_data.shape[0] // 3
+    # Enlarge the composite to fit the new images
+    composite_image_data = np.pad(composite_image_data, ((0,0),(new_dimx, new_dimx),(0,0)))
+    for i in range(6):
+        img = base_imgs[i]
+        img = bin_ndarray(img, (new_dimy, new_dimx, 3)) # Shrink down to 1/3 for assembly
+        img = contrast(img, 1.25, 0.0)
+        xdimoff = i%2 * (composite_image_data.shape[1] - new_dimx)
+        ydimoff = i//2*new_dimy
+        composite_image_data[ydimoff:ydimoff+new_dimy, xdimoff:xdimoff+new_dimx, :] = img
+
+    img = Image.fromarray((255 * composite_image_data).astype('uint8'))
+    timestring = datetime.datetime.fromtimestamp(timestamp, tz = datetime.UTC).strftime('%Y-%m-%d  %H:%M:%S')
+    ImageDraw.Draw(img).text((602, 15), f"NOAA GOES Satellite SUVI Composite - {timestring} UTC",(255,255,255), font = fnt1)
+    for i in range(6): # Draw component angstrom labels
+        if i%2 == 0:
+            xdimtxtoff = 5
+        else:
+            xdimtxtoff = composite_image_data.shape[1] - 44
+        ydimtxtoff = i//2*new_dimy + new_dimy / 2.0 - 14
+        ImageDraw.Draw(img).text((xdimtxtoff, ydimtxtoff), image_names[i], font = fnt2)
+    img = Image.fromarray((255 * composite_image_data).astype('uint8'))
+    timestring = datetime.datetime.fromtimestamp(timestamp, tz = datetime.UTC).strftime('%Y-%m-%d  %H:%M:%S')
+    ImageDraw.Draw(img).text((602, 15), f"NOAA GOES Satellite SUVI Composite - {timestring} UTC",(255,255,255), font = fnt1)
+    for i in range(6): # Draw component angstrom labels
+        if i%2 == 0:
+            xdimtxtoff = 5
+        else:
+            xdimtxtoff = composite_image_data.shape[1] - 44
+        ydimtxtoff = i//2*new_dimy + new_dimy / 2.0 - 14
+        ImageDraw.Draw(img).text((xdimtxtoff, ydimtxtoff), image_names[i], font = fnt2)
+    return img
+
+
+def generate_composite(work_queue, result_queue):
+    """Worker: read six bands from disk and write their composite."""
+    lowpriority()
+    while True:
+        try:
+            job = work_queue.get()
+            if job is None:
+                result_queue.cancel_join_thread()
+                return
+            files_this_timestamp, timestamp, processed_images_dir, synthetic_data = job
+            synthetic_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}_s.jpg")
+            normal_filepath = os.path.join(processed_images_dir, f"Composite-{int(timestamp)}.jpg")
+            filepath = None
+            if synthetic_data:
+                if os.path.isfile(synthetic_filepath):
+                    result_queue.put(("Exists", timestamp))
+                    continue
+                filepath = synthetic_filepath
+            else:
+                if os.path.isfile(synthetic_filepath):
+                    os.remove(synthetic_filepath)
+                if os.path.isfile(normal_filepath):
+                    result_queue.put(("Exists", timestamp))
+                    continue
+                filepath = normal_filepath
+
+            arrays = [fits.getdata(f) for f in files_this_timestamp]
+            img = composite_from_arrays(arrays, timestamp)
+            img.save(filepath, quality = 95)
+            result_queue.put(("Created", timestamp))
+
+        except KeyboardInterrupt:
+            return
+        except Exception as e:
+            traceback.print_exception(e)
+            result_queue.put((e, timestamp))
+
+
+if __name__ == "__main__":
+    import argparse
+
+    from suvi import db, paths
+
+    parser = argparse.ArgumentParser(
+        description="Render SUVI composite images from indexed FITS frames.",
+    )
+    parser.add_argument("--db", default=None, help="SQLite index (default: $SUVI_DB)")
+    parser.add_argument("--root", default=None, help="archive root (default: $SUVI_DATA_ROOT)")
+    parser.add_argument("--out", default=None, help="composite output root")
+    parser.add_argument("--satellites", default="16,18")
+    parser.add_argument("--start", default="2024-01-01", help="UTC date, inclusive")
+    parser.add_argument("--stop", default="2025-01-01", help="UTC date, exclusive")
+    parser.add_argument(
+        "--detector",
+        default="header_v1",
+        help="detector run whose 'good' verdicts select frames, or 'none' to use every "
+             "indexed frame. Default header_v1: it is conservative, catching genuine "
+             "dropouts without discarding good data. Do not default this to geometry_v1 "
+             "-- over sampled days of 2024 it rejects 36.9%% of frames, entire days at a "
+             "time, because its centre test tracks the brightness centroid rather than "
+             "the disc. Run bench.py before changing this.",
+    )
+    parser.add_argument("--workers", type=int, default=16)
+    parser.add_argument("--max-time-gap", type=int, default=3,
+                        help="slots a missing band may be carried forward when filling")
+    parser.add_argument("--fill-missing", action="store_true",
+                        help="carry the last good frame into incomplete timestamps")
+    args = parser.parse_args()
+
+    def parse_day(text):
+        return calendar.timegm(
+            datetime.datetime.strptime(text, "%Y-%m-%d")
+            .replace(tzinfo=datetime.timezone.utc)
+            .timetuple()
+        )
+
+    archive_root = args.root or paths.data_root()
+    composite_root = args.out or os.path.join(os.path.dirname(archive_root), "composite")
+    satellites = [int(part) for part in args.satellites.split(",")]
+    starttime, stoptime = parse_day(args.start), parse_day(args.stop)
+    nworkers = args.workers
+    max_time_gap = args.max_time_gap
+    fill_missing_data = args.fill_missing
+
+    conn = db.connect(args.db, readonly=True)
+    run_id = None
+    if args.detector != "none":
+        run_id = db.latest_run_id(conn, args.detector)
+        if run_id is None:
+            raise SystemExit(
+                f"No detector run named {args.detector!r} in the index. "
+                f"Run `filter_FITS.py detect --detectors {args.detector}` first, "
+                f"or pass --detector none to use every indexed frame."
+            )
+
+    file_prefixes = ["dr_suvi-l2-ci" + n[:-1] for n in image_names]
+
+    work_queue = Queue(maxsize=nworkers)
+    result_queue = Queue()
+    workers = []
+    for i in range(nworkers):
+        p = Process(target=generate_composite, args=(work_queue, result_queue), daemon=True)
+        p.start()
+        workers.append(p)
+
+    lowpriority()
+    ncreated = 0
+    nexists = 0
+    nfailed = 0
+    try:
+        for satellite in satellites:
+            processed_images_dir = os.path.join(composite_root, f"goes{satellite}")
+            os.makedirs(processed_images_dir, exist_ok=True)
+
+            # Frame selection is a query against the index rather than a filename
+            # regex. The old `_f.fits$` pattern is gone along with the suffixes it
+            # matched; see migrate_unrename.py.
+            if run_id is None:
+                rows = conn.execute(
+                    "SELECT path, wavelength, t_start FROM frame "
+                    "WHERE satellite = ? AND t_start >= ? AND t_start < ? "
+                    "ORDER BY t_start, wavelength",
+                    (satellite, starttime, stoptime),
+                ).fetchall()
+            else:
+                rows = db.good_slots(conn, run_id, starttime, stoptime, satellite)
+
+            files_by_timestamp = defaultdict(list)
+            for row in rows:
+                files_by_timestamp[row["t_start"]].append(
+                    paths.abspath(row["path"], archive_root)
+                )
+            num_found_files = sum(len(v) for v in files_by_timestamp.values())
+            print(f"goes{satellite}: {num_found_files} frames selected "
+                  f"({args.detector}) across {len(files_by_timestamp)} timestamps")
+            if num_found_files == 0:
+                continue
+
+            sorted_times = sorted(files_by_timestamp)
+            interval = paths.CADENCE
+
+            # Trim to the first and last timestamps holding a full set of six bands, so
+            # a partially downloaded tail does not get permanently filled from a gap.
+            first = next((i for i, t in enumerate(sorted_times)
+                          if len(files_by_timestamp[t]) == 6), None)
+            last = next((len(sorted_times) - 1 - i
+                         for i, t in enumerate(reversed(sorted_times))
+                         if len(files_by_timestamp[t]) == 6), None)
+            if first is None or last is None or first >= last:
+                print(f"  no complete six-band timestamps for goes{satellite}; skipping")
+                continue
+            sorted_times = sorted_times[first:last]
+
+            last_good_files = list(files_by_timestamp[sorted_times[0]])
+            last_good_file_times = [sorted_times[0]] * len(last_good_files)
+
+            for timestamp in tqdm.tqdm(sorted_times, desc=f"goes{satellite} composites"):
+                while True:
+                    try:
+                        result = result_queue.get_nowait()
+                        if result[0] == "Exists":
+                            nexists += 1
+                        elif result[0] == "Created":
+                            ncreated += 1
+                        else:
+                            print(f"A worker failed on job {result[1]}: {result[0]}")
+                            nfailed += 1
+                    except queue.Empty:
+                        break
+
+                files_this_timestamp = sorted(files_by_timestamp[timestamp])
+                if len(files_this_timestamp) == 6:
+                    last_good_files = files_this_timestamp
+                    last_good_file_times = [timestamp] * 6
+                    work_queue.put((files_this_timestamp, timestamp, processed_images_dir, False))
+                elif fill_missing_data:
+                    files_for_job = []
+                    for i, prefix in enumerate(file_prefixes):
+                        found = next(
+                            (f for f in files_this_timestamp
+                             if os.path.basename(f).startswith(prefix)),
+                            None,
+                        )
+                        if found is not None:
+                            files_for_job.append(found)
+                            last_good_files[i] = found
+                            last_good_file_times[i] = timestamp
+                        elif (timestamp - last_good_file_times[i]) // interval <= max_time_gap:
+                            files_for_job.append(last_good_files[i])
+                    if len(files_for_job) == 6:
+                        work_queue.put((files_for_job, timestamp, processed_images_dir, True))
+
+    except KeyboardInterrupt:
+        print("Finishing current jobs and exiting")
+
+    for _ in range(nworkers):
+        try:
+            work_queue.put(None, timeout=10.0)
+        except Exception:
+            break
+
+    for w in workers:
+        w.join()
+
+    conn.close()
+    print(f"Created {ncreated} | Already had {nexists} | Failed {nfailed}")
diff --git a/migrate_unrename.py b/migrate_unrename.py
new file mode 100644
index 0000000..1b51e6e
--- /dev/null
+++ b/migrate_unrename.py
@@ -0,0 +1,366 @@
+#!/usr/bin/env python
+"""One-time migration: strip _f/_e suffixes from the archive, into the SQLite index.
+
+``filter_FITS.py`` used to record its verdict by renaming files -- ``_f`` for passed,
+``_e`` for rejected -- and writing a ``_e.jpg`` diagnostic plot alongside rejects.
+That made the archive's filenames a mutable database with one column, coupled three
+scripts to a naming convention, and threw away every intermediate score.
+
+This restores every file to the name NOAA published it under, after recording the
+existing verdicts in the index.
+
+Safety, because this is the one irreversible step:
+
+* Dry run by default; ``--apply`` is required to rename anything.
+* The legacy verdicts are exported to a standalone CSV **before** any rename.  Every
+  other table can be rebuilt by re-walking or re-reading the archive, but once the
+  suffixes are gone these labels exist nowhere else.
+* A rename that would overwrite an existing file is skipped and reported, never
+  forced.
+* Idempotent and resumable: re-running finds nothing left to do.
+
+Note that these labels are stale -- they were written in May 2024, and the filter was
+retuned that July -- so they are preserved as history, under the run name
+``legacy_filter``, not as ground truth.
+
+    migrate_unrename.py --wavelength 171 --year 2024      # dry run, one subtree
+    migrate_unrename.py --apply                           # the whole archive
+"""
+
+import argparse
+import csv
+import gzip
+import os
+import sys
+import time
+from collections import Counter
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import db, paths, vfs
+
+LEGACY_RUN_NAME = "legacy_filter"
+
+
+def chunk_key(wavelength, year):
+    """Index key recording that one (band, year) has been fully migrated."""
+    return f"unrename_done:ci{wavelength:03d}:{year if year is not None else 'all'}"
+
+
+def walk_archive(root, satellites, wavelengths, years=None):
+    """Yield (directory, filename, FrameName) for every SUVI frame found.
+
+    When `years` is given the unwanted year directories are pruned from the walk
+    rather than merely skipped, so restricting the year genuinely restricts how much
+    of the filesystem is touched.  That matters here for more than speed: see
+    :func:`release_handles`.
+    """
+    def fail(error):
+        # os.walk swallows errors by default.  On this mount a transient ENFILE
+        # would then make the walk yield nothing, and the caller would conclude the
+        # archive was already migrated and move on -- silently skipping real work.
+        # An unreadable directory has to stop the chunk, not look like an empty one.
+        raise error
+
+    for base in paths.wavelength_dirs(root, satellites, wavelengths):
+        if not os.path.isdir(base):
+            continue
+        for directory, dirnames, filenames in os.walk(base, onerror=fail):
+            if years and directory == base:
+                dirnames[:] = [d for d in dirnames if not d.isdigit() or int(d) in years]
+            for filename in filenames:
+                name = paths.parse_frame_filename(filename)
+                if name is not None:
+                    yield directory, filename, name
+
+
+def archive_years(root, satellites, wavelength):
+    """Years present on disk for one band, across all satellites."""
+    years = set()
+    for satellite in satellites:
+        base = os.path.join(
+            root, f"goes{satellite:d}", "l2", "data", f"suvi-l2-ci{wavelength:03d}"
+        )
+        if not os.path.isdir(base):
+            continue
+        try:
+            years.update(int(d) for d in os.listdir(base) if d.isdigit())
+        except OSError:
+            continue
+    return sorted(years)
+
+
+#: Frames a chunk must have touched before reclaiming is worth its cost.  Well under
+#: the point where the mount starts refusing opens, and far above anything a test
+#: fixture reaches.
+RELIEF_THRESHOLD = 50_000
+#: Reclaim this often *within* a phase as well.  Chunking alone is not enough: one
+#: band-year can hold 230k frames, and the mount began refusing opens partway through
+#: renaming it, costing 132,857 renames in an earlier attempt.
+RELIEF_INTERVAL = vfs.RELIEF_INTERVAL
+
+
+# Reclaim lives in suvi.vfs: it is a property of this mount, not of this migration,
+# and the index build needs it just as much.  Re-exported so callers and tests can
+# reach it by either name.
+drop_caches = vfs.drop_caches
+reclaimable_kb = vfs.reclaimable_kb
+release_handles = vfs.release_handles
+
+
+def _mark_chunk_done(args, wavelengths):
+    """Record that a (band, year) needs no further migration.
+
+    Lets a resume skip finished subtrees without touching the filesystem at all --
+    the traversal that a resume used to perform is exactly what exhausts this mount.
+    """
+    if not args.apply or len(wavelengths) != 1:
+        return
+    year = args.year[0] if args.year and len(args.year) == 1 else None
+    try:
+        conn = db.connect(args.db)
+        db.set_meta(conn, chunk_key(wavelengths[0], year), "done")
+        conn.commit()
+        conn.close()
+    except Exception as exc:
+        print(f"  (could not record chunk progress: {exc})")
+
+
+def export_labels(path, records):
+    """Write the legacy verdicts to a standalone file before anything is renamed."""
+    os.makedirs(os.path.dirname(os.path.abspath(path)), exist_ok=True)
+    with gzip.open(path, "wt", newline="") as handle:
+        writer = csv.writer(handle)
+        writer.writerow(["relpath", "legacy_label", "satellite", "wavelength", "t_start"])
+        for relpath, label, name in records:
+            writer.writerow([relpath, label, name.satellite, name.wavelength, name.t_start])
+
+
+def main(argv=None):
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--db", default=None, help="target index (default: $SUVI_DB)")
+    parser.add_argument("--root", default=None, help="archive root (default: $SUVI_DATA_ROOT)")
+    parser.add_argument("--apply", action="store_true", help="rename files (default: dry run)")
+    parser.add_argument("--satellites", default="16,18,19")
+    parser.add_argument("--wavelength", default=None, help="restrict to one band")
+    parser.add_argument("--year", type=int, action="append", default=None,
+                        help="restrict to given years (repeatable)")
+    parser.add_argument("--export", default=None,
+                        help="legacy label export (default: <root>/legacy_labels.csv.gz)")
+    parser.add_argument("--keep-plots", action="store_true",
+                        help="keep the _e.jpg diagnostic images")
+    parser.add_argument("--no-relief", action="store_true",
+                        help="skip the cache-reclaim step between chunks")
+    parser.add_argument("--recheck", action="store_true",
+                        help="re-examine chunks already recorded as migrated")
+    args = parser.parse_args(argv)
+
+    root = args.root or paths.data_root()
+    if not os.path.isdir(root):
+        print(f"No such archive root: {root}")
+        return 1
+    satellites = tuple(int(part) for part in args.satellites.split(","))
+    wavelengths = (int(args.wavelength),) if args.wavelength else paths.WAVELENGTHS
+
+    # One (band, year) at a time.  Walking the whole archive in a single pass fills
+    # the dentry cache with millions of entries, and on this virtiofs mount each
+    # cached entry pins a host file handle -- the walk succeeds and then nothing can
+    # open a file again, which is how an earlier attempt lost 152,193 renames to
+    # ENFILE.  A band-year is ~130k files, comfortably inside what the mount
+    # sustains, and each chunk finishes completely (export, record, rename) so a
+    # failure never leaves labels destroyed but unrecorded.
+    chunks = []
+    for wavelength in wavelengths:
+        years = archive_years(root, satellites, wavelength) if args.year is None else args.year
+        for year in years or [None]:
+            chunks.append((wavelength, year))
+
+    # Skip chunks already recorded as complete, without touching the filesystem.
+    # Resuming used to re-walk finished subtrees just to discover there was nothing
+    # to do; across several passes that traversed the archive roughly four times
+    # over, and traversal is the very thing that exhausts this mount.
+    done = set()
+    # Only when applying: a dry run must neither create the index nor hide work, so
+    # it reports the archive's true state regardless of what progress was recorded.
+    if args.apply and not args.recheck:
+        try:
+            conn = db.connect(args.db)
+            done = {
+                key for (wavelength, year) in chunks
+                if db.get_meta(conn, key := chunk_key(wavelength, year)) == "done"
+            }
+            conn.close()
+        except Exception as exc:
+            print(f"Could not read migration progress ({exc}); checking every chunk.")
+
+    if len(chunks) > 1:
+        overall = 0
+        for index, (wavelength, year) in enumerate(chunks, 1):
+            label = f"{wavelength}A {year or 'all years'}"
+            if chunk_key(wavelength, year) in done:
+                print(f"\n=== chunk {index}/{len(chunks)}: {label} -- already migrated, skipping")
+                continue
+            print(f"\n{'=' * 70}\n=== chunk {index}/{len(chunks)}: {label} ===")
+            chunk_args = argparse.Namespace(**vars(args))
+            chunk_args.wavelength = str(wavelength)
+            chunk_args.year = [year] if year is not None else None
+            if args.export is None:
+                suffix = f"ci{wavelength:03d}" + (f"_{year}" if year else "")
+                chunk_args.export = os.path.join(root, f"legacy_labels_{suffix}.csv.gz")
+            status, frames = main_one_chunk(chunk_args, root, satellites, (wavelength,))
+            overall = overall or status
+            if not args.no_relief and frames >= RELIEF_THRESHOLD:
+                release_handles()
+        return overall
+    return main_one_chunk(args, root, satellites, wavelengths)[0]
+
+
+def main_one_chunk(args, root, satellites, wavelengths):
+    print(f"Scanning {root}")
+    print(f"  satellites={satellites} wavelengths={wavelengths} years={args.year or 'all'}")
+
+    counts = Counter()
+    labelled = []       # (relpath, label, name) for every file carrying a verdict
+    renames = []        # (src, dst) pairs to perform
+    collisions = []
+    plots = []
+    started = time.time()
+
+    for directory, filename, name in walk_archive(root, satellites, wavelengths, args.year):
+        counts["frames"] += 1
+        relpath = name.relpath()
+        if name.label:
+            counts[f"label_{name.label}"] += 1
+            labelled.append((relpath, name.label, name))
+            source = os.path.join(directory, filename)
+            target = os.path.join(directory, name.filename())
+            if os.path.exists(target):
+                collisions.append((source, target))
+            else:
+                renames.append((source, target))
+            if name.label == "e" and not args.keep_plots:
+                plot = os.path.join(directory, name.error_plot_name())
+                if os.path.exists(plot):
+                    plots.append(plot)
+        else:
+            counts["unlabelled"] += 1
+        if counts["frames"] % RELIEF_INTERVAL == 0 and not args.no_relief:
+            release_handles()
+        if counts["frames"] % 200000 == 0:
+            print(f"  {counts['frames']} frames in {time.time() - started:.0f}s")
+
+    print(f"\nFound {counts['frames']} frames in {time.time() - started:.0f}s")
+    print(f"  passed  (_f): {counts['label_f']}")
+    print(f"  rejected(_e): {counts['label_e']}")
+    print(f"  unlabelled  : {counts['unlabelled']}  (never processed by any filter)")
+    print(f"  renames to perform: {len(renames)}")
+    print(f"  diagnostic plots to delete: {len(plots)}")
+    if collisions:
+        print(f"  COLLISIONS (will be skipped): {len(collisions)}")
+        for source, target in collisions[:5]:
+            print(f"    {os.path.basename(source)} -> {os.path.basename(target)} exists")
+
+    if not args.apply:
+        print("\nDry run.  Re-run with --apply to write the export, rename, and clean up.")
+        return 0, counts["frames"]
+
+    if not labelled:
+        print("\nNothing labelled; archive is already migrated.")
+        _mark_chunk_done(args, wavelengths)
+        return 0, counts["frames"]
+
+    # 1. Export the labels before touching a single filename.
+    export_path = args.export or os.path.join(root, "legacy_labels.csv.gz")
+    print(f"\nExporting {len(labelled)} legacy labels to {export_path}")
+    export_labels(export_path, labelled)
+    if not os.path.exists(export_path) or os.path.getsize(export_path) == 0:
+        print("ERROR: export is missing or empty; refusing to rename anything.")
+        return 1, counts["frames"]
+    print(f"  {os.path.getsize(export_path) / 1024 / 1024:.1f} MB written")
+
+    # 2. Record them in the index.
+    target_db = args.db or paths.default_db_path()
+    conn = db.connect(target_db)
+    run_id = db.create_detector_run(
+        conn,
+        LEGACY_RUN_NAME,
+        {"source": "filename suffixes", "root": root},
+        notes="Verdicts recovered from _f/_e filename suffixes. Written ~May 2024 by a "
+              "filter version since retuned; preserved as history, not ground truth.",
+    )
+    print(f"Recording verdicts in {target_db} as run {run_id} ({LEGACY_RUN_NAME})")
+
+    batch = []
+    for index, (relpath, label, name) in enumerate(labelled):
+        frame_id = db.upsert_frame(conn, name, relpath)
+        batch.append((frame_id, "good" if label == "f" else "bad", f"legacy_{label}", None, None))
+        if len(batch) >= 5000:
+            db.record_detections(conn, run_id, batch)
+            conn.commit()
+            batch.clear()
+            print(f"  {index + 1}/{len(labelled)}")
+    if batch:
+        db.record_detections(conn, run_id, batch)
+        conn.commit()
+
+    recorded = conn.execute(
+        "SELECT count(*) c FROM detection WHERE run_id = ?", (run_id,)
+    ).fetchone()["c"]
+    if recorded != len(labelled):
+        print(f"ERROR: recorded {recorded} verdicts but found {len(labelled)} labels.")
+        print("       Not renaming anything.")
+        conn.close()
+        return 1, counts["frames"]
+    print(f"  {recorded} verdicts recorded")
+
+    # 3. Only now rename.
+    print(f"\nRenaming {len(renames)} files...")
+    renamed = failed = 0
+    for index, (source, target) in enumerate(renames):
+        try:
+            os.rename(source, target)
+            renamed += 1
+        except OSError as exc:
+            failed += 1
+            if failed <= 5:
+                print(f"  FAILED {source}: {exc}")
+        if index and index % RELIEF_INTERVAL == 0 and not args.no_relief:
+            release_handles()
+        if index and index % 100000 == 0:
+            print(f"  {index}/{len(renames)}")
+    print(f"  renamed {renamed}, failed {failed}, skipped {len(collisions)} collisions")
+
+    removed = 0
+    for plot in plots:
+        try:
+            os.remove(plot)
+            removed += 1
+        except OSError:
+            pass
+    print(f"  deleted {removed} diagnostic plots")
+
+    # 4. Verify every recorded path now resolves.
+    print("\nVerifying...")
+    missing = 0
+    for relpath, _, _ in labelled[:: max(1, len(labelled) // 5000)]:
+        if not os.path.exists(paths.abspath(relpath, root)):
+            missing += 1
+    if missing:
+        print(f"  WARNING: {missing} sampled paths do not resolve on disk")
+    else:
+        print("  all sampled paths resolve")
+    conn.close()
+    # Only claim the chunk is finished if every rename actually landed.  Marking it
+    # done after partial failures is how a resume would skip real remaining work.
+    if failed == 0:
+        _mark_chunk_done(args, wavelengths)
+    else:
+        print(f"  NOT marking this chunk complete: {failed} renames failed; re-run to retry.")
+    print("\nDone.  The archive now uses NOAA's original filenames; verdicts live in "
+          f"the index, and a recovery copy is at {export_path}")
+    return 0, counts["frames"]
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/migrate_urlcache.py b/migrate_urlcache.py
new file mode 100644
index 0000000..d889e90
--- /dev/null
+++ b/migrate_urlcache.py
@@ -0,0 +1,125 @@
+#!/usr/bin/env python
+"""One-time migration: file_database.json -> the SQLite index's remote_file table.
+
+``puller_fits.py`` recorded every URL it had fetched in an 800 MB JSON object, parsed
+into memory on every run.  This moves that state into the index, where it is an
+indexed lookup instead.
+
+This state is the only record of what has already been downloaded.  Losing it means
+re-fetching the entire archive from NOAA, so the migration refuses to proceed on any
+inconsistency and never deletes the JSON -- it renames it to .bak only after the row
+count matches, and only when asked.
+
+Dry run by default::
+
+    migrate_urlcache.py                 # report what would happen
+    migrate_urlcache.py --apply         # write the rows
+    migrate_urlcache.py --apply --backup-json
+"""
+
+import argparse
+import json
+import os
+import sys
+import time
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import db, paths
+
+
+def default_json_path():
+    return os.path.join(os.path.dirname(paths.data_root()), "file_database.json")
+
+
+def main(argv=None):
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--json", default=None, help="source file_database.json")
+    parser.add_argument("--db", default=None, help="target index (default: $SUVI_DB)")
+    parser.add_argument("--apply", action="store_true", help="write rows (default: dry run)")
+    parser.add_argument("--backup-json", action="store_true",
+                        help="rename the JSON to .bak after a verified migration")
+    parser.add_argument("--batch", type=int, default=50000)
+    args = parser.parse_args(argv)
+
+    source = args.json or default_json_path()
+    if not os.path.exists(source):
+        print(f"No such file: {source}")
+        return 1
+
+    size = os.path.getsize(source)
+    print(f"Reading {source} ({size / 1024 / 1024:.0f} MB)...")
+    started = time.time()
+    with open(source, "r") as handle:
+        cache = json.load(handle)
+    if not isinstance(cache, dict):
+        print(f"ERROR: expected a JSON object, got {type(cache).__name__}")
+        return 1
+    print(f"  {len(cache)} URL records in {time.time() - started:.1f}s")
+
+    malformed = [
+        url for url, mtime in cache.items()
+        if not isinstance(url, str) or not isinstance(mtime, (int, float))
+    ]
+    if malformed:
+        print(f"ERROR: {len(malformed)} records are malformed, e.g. {malformed[:3]}")
+        return 1
+
+    if not args.apply:
+        print(f"\nDry run: would insert {len(cache)} rows into remote_file.")
+        print("Re-run with --apply to write them.")
+        return 0
+
+    target = args.db or paths.default_db_path()
+    conn = db.connect(target)
+    existing = conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"]
+    print(f"Writing to {target} (currently {existing} rows)...")
+
+    now = time.time()
+    written = 0
+    batch = []
+    for url, mtime in cache.items():
+        batch.append((url, float(mtime), None, None, now))
+        if len(batch) >= args.batch:
+            db.record_remote_files(conn, batch)
+            conn.commit()
+            written += len(batch)
+            batch.clear()
+            print(f"  {written}/{len(cache)}")
+    if batch:
+        db.record_remote_files(conn, batch)
+        conn.commit()
+        written += len(batch)
+
+    final = conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"]
+    print(f"  wrote {written} rows; table now holds {final}")
+
+    if final < len(cache):
+        print(f"ERROR: table holds {final} rows but the JSON had {len(cache)} URLs.")
+        print("       Not touching the JSON.  Investigate before re-running.")
+        conn.close()
+        return 1
+
+    # Spot-check that values survived the round trip, not just the row count.
+    sample = list(cache.items())[:: max(1, len(cache) // 20)][:20]
+    for url, mtime in sample:
+        stored = db.get_remote_mtime(conn, url)
+        if stored is None or abs(stored - float(mtime)) > 1e-6:
+            print(f"ERROR: round-trip mismatch for {url}: {mtime} -> {stored}")
+            conn.close()
+            return 1
+    print(f"  spot-checked {len(sample)} URLs, all match")
+    conn.close()
+
+    if args.backup_json:
+        backup = source + ".bak"
+        os.rename(source, backup)
+        print(f"Renamed {source} -> {backup}")
+    else:
+        print(f"Left {source} in place; pass --backup-json once puller_fits.py is verified.")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/puller.py b/puller.py
deleted file mode 100644
index e7fe72b..0000000
--- a/puller.py
+++ /dev/null
@@ -1,148 +0,0 @@
-import os
-import urllib.request
-import urllib.parse
-import re
-import time
-import random
-import datetime
-import json
-from threading import Thread
-import queue
-
-import tqdm
-
-def recursive_find_links(url):
-    links_regex_pattern = r'(?<=<a href=")([^ ?]*)(?=">)' # Find href links that do not contain question marks or whitespace
-    times_regex_pattern = r'(?<=<\/a>)(\s*\d{4}-\d{2}-\d{2} \d{2}:\d{2})(?= )' # Find timestamps in UTC in the format YYYY-MM-DD HH:mm
-    with urllib.request.urlopen(url) as response:
-        html_content = response.read().decode('utf-8')
-
-        links = re.findall(links_regex_pattern, html_content)
-        times = re.findall(times_regex_pattern, html_content)
-        for i in range(len(times)):
-            dt = datetime.datetime.strptime(times[i].strip(), "%Y-%m-%d %H:%M")
-            dt.replace(tzinfo=datetime.timezone.utc)
-            times[i] = time.mktime(dt.timetuple())
-        
-        if len(links) - 1 == len(times):
-            links = links[1:]
-        elif len(links) == len(times):
-            pass
-        else:
-            raise(ValueError)
-
-        for _link, _time in zip(links, times):
-            if _link.endswith("latest.png"):
-                continue
-            elif _link.endswith("/"):
-                yield from recursive_find_links(urllib.parse.urljoin(url,_link))
-            else:
-                yield urllib.parse.urljoin(url,_link), _time
-    
-
-# Fetch image from url and store it to path, retrying on failure
-def image_fetch_worker(work_queue, result_queue, attempt_count = 1):
-    while True:
-        job = work_queue.get()
-        if job == None:
-            return
-        url, path, t = job
-
-        attempts = 0
-        while attempts < attempt_count:
-            try:
-                req = urllib.request.Request(url, data=None)
-                image_data = urllib.request.urlopen(req).read()
-                os.makedirs(os.path.split(path)[0], exist_ok=True)
-                open(path, 'wb').write(image_data)
-                result_queue.put((True, url, t))
-                break
-            except Exception as e:
-                if hasattr(e, "code") and e.code == 404: # This is expected if the file has been removed from the site (at least for swpc.noaa.gov)
-                    attempts += attempt_count
-                elif attempts == 0:
-                    print(f"\nA problem occurred on image: {url} | {e}")
-                    time.sleep(1 + random.random())
-                    attempts += 1
-            if (attempt_count > 1) and (attempts == attempt_count):
-                print(f'\nAfter {attempt_count} retries, could not fetch: {url}')
-                result_queue.put((False, url, t))
-                break
-
-
-if __name__ == "__main__":
-    directory_url = r"https://services.swpc.noaa.gov/images/animations/suvi/"
-    stored_images_dir = r"..\suvi"
-    file_database_path = r"..\file_database.json"
-    fetch_interval = 30*60
-    nworkers = 8
-
-    file_info_cache = {}
-    try:
-        print(f"Attempting to load file records from cache: {file_database_path}")
-        with open(file_database_path, 'r') as f:
-            file_info_cache = json.loads(f.read())
-        print(f"File records loaded from cache: {len(file_info_cache)} records found.")
-    except Exception as e:
-        print(f"Load failed, starting with empty cache")
-        file_info_cache = {}
-
-    work_queue = queue.Queue(maxsize=nworkers)
-    result_queue = queue.Queue()
-    workers = []
-    for _ in range(nworkers):
-        t = Thread(target=image_fetch_worker, args=(work_queue, result_queue), daemon=True)
-        t.start()
-        workers.append(t)
-    try:
-        while True:
-            fetched_image_count = 0
-            already_had_image_count = 0
-            failed_image_count = 0
-            urllen = len(directory_url)
-            for l, t in tqdm.tqdm(recursive_find_links(directory_url), desc="Downloading files"):
-                # Collect complete work and record it
-                while True:
-                    try:
-                        r_success, r_url, r_t = result_queue.get_nowait()
-                        if r_success: 
-                            fetched_image_count += 1
-                            file_info_cache[r_url] = r_t
-                        else:
-                            failed_image_count += 1
-                    except queue.Empty:
-                        break
-                # If we dont have the file or the file at the link is newer than the one we previously fetched
-                if (not (l in file_info_cache)) or t > file_info_cache[l]: 
-                    file_portion_of_link = l[urllen:]
-                    filepath = os.path.join(stored_images_dir, file_portion_of_link.replace("/", os.sep))
-                    if os.path.exists(filepath):
-                        if l in file_info_cache: # If we have record of this file, it must be out of date, rename it and download the new version.
-                            os.rename(filepath, filepath + f"_{int(file_info_cache[l])}")
-                        else: # If we have no record of this file, update the file info cache and don't redownload
-                            file_info_cache[l] = t
-                            already_had_image_count += 1
-                            continue
-                    work_queue.put((l, filepath, t))
-                else:
-                    already_had_image_count += 1
-            with open(file_database_path, 'w') as f:
-                f.write(json.dumps(file_info_cache))
-            print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
-            time.sleep(fetch_interval)
-    except KeyboardInterrupt:
-        print("Saving file database and shutting down.")
-
-    for _ in range(nworkers):
-        try:
-            work_queue.put(None, timeout=1.0)
-        except:
-            break
-
-    for w in workers:
-        w.join(5.0)
-
-    with open(file_database_path, 'w') as f:
-        f.write(json.dumps(file_info_cache))
-
-    print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
\ No newline at end of file
diff --git a/puller_fits.py b/puller_fits.py
index 0687a88..35db744 100644
--- a/puller_fits.py
+++ b/puller_fits.py
@@ -1,273 +1,307 @@
-import os
-import urllib.request
-import urllib.parse
-import re
-import time
-import random
-import datetime
-import json
-from threading import Thread
-import queue
-import math
-from functools import partial
-from queue import Empty
-
-import tqdm
-
-directory_url = r"https://data.ngdc.noaa.gov/platforms/solar-space-observing-satellites/goes/"
-stored_images_dir = os.path.abspath(os.path.join("..", "Data"))
-# directory_url = r"https://data.ngdc.noaa.gov/platforms/solar-space-observing-satellites/goes/goes16/l2/data/ephe-l2-orb1m/2017/12/"
-# stored_images_dir = r"Z:\NOAA GOES Data\Data\goes16/l2/data/ephe-l2-orb1m/2017/12/"
-ignore_folder_names = ["Parent Directory", "l1b", "goes17", "2017", "2018", "2019", "2020", "2021", "2022", "2023"]
-file_database_path = os.path.abspath(os.path.join("..", "file_database.json"))
-fetch_interval = 0 # 60*60
-nfetchworkers = 2 # Be nice to the servers, this value is how many threads will be asking for links and file info at the same time
-ndownloadworkers = 3 # Be nice to the servers, this value is how many threads will be downloading files at the same time
-randomize_order = False
-
-links_regex_pattern = r'(?<=<a href=")([^ ?:]*)(?=">.*\d{4}-\d{2}-\d{2} \d{2}:\d{2})' # Find href links that do not contain question marks or whitespace
-times_regex_pattern = r'(?<=<td align="right">)(\d{4}-\d{2}-\d{2} \d{2}:\d{2})(?= )' # Find timestamps in UTC in the format YYYY-MM-DD HH:mm
-sizes_regex_pattern = r'(?<=\d{4}-\d{2}-\d{2} \d{2}:\d{2}  <\/td><td align="right">)([ .\d]{1,3})([KMG]|- |0 | )(?=<\/td>)' # Find file size markers in one of many possible formats
-links_matcher = re.compile(links_regex_pattern)
-times_matcher = re.compile(times_regex_pattern)
-sizes_matcher = re.compile(sizes_regex_pattern)
-
-def find_links_worker(query_work_queue, query_result_queue, attempt_count = 3, randomize_order = True):
-    while True:
-        job = query_work_queue.get()
-        if job == None:
-            return
-        url= job
-    
-        attempts = 0
-        html_content = None
-        while attempts < attempt_count:
-            try:
-                with urllib.request.urlopen(url) as response:
-                    html_content = response.read().decode('utf-8')
-                    break
-            except Exception as e:
-                tqdm.tqdm.write(f"Exception while fetching links: {e}")
-                time.sleep(1 + random.random())
-                attempts += 1
-            if (attempt_count > 1) and (attempts == attempt_count):
-                tqdm.tqdm.write(f'\nAfter {attempt_count} retries, could not fetch: {url}')
-
-        if html_content is None: # We failed to fetch the link for some reason, continue to the next job
-            continue
-        else:
-            links = links_matcher.findall(html_content)
-            times = times_matcher.findall(html_content)
-            sizes = sizes_matcher.findall(html_content)
-            for i in range(len(times)):
-                dt = datetime.datetime.strptime(times[i].strip(), "%Y-%m-%d %H:%M")
-                dt.replace(tzinfo=datetime.timezone.utc)
-                times[i] = time.mktime(dt.timetuple())
-            for i in range(len(sizes)):
-                match sizes[i][1].strip():
-                    case '-':
-                        sizes[i] = 0
-                    case 'K':
-                        sizes[i] = int(float(sizes[i][0].strip()) * 1024)
-                    case 'M':
-                        sizes[i] = int(float(sizes[i][0].strip()) * 1024 * 1024)
-                    case 'G':
-                        sizes[i] = int(float(sizes[i][0].strip()) * 1024 * 1024 * 1024)
-                    case "0":
-                        sizes[i] = 0
-                    case "":
-                        sizes[i] = int(float(sizes[i][0].strip()))
-                    case _:
-                        raise(ValueError(f"Unexpected symbol while parsing links page: {_}"))
-
-            
-            if (len(links) != len(times)) or (len(times) != len(sizes)):
-                raise(ValueError("Links parsing error, mismatched numbers of links, times, or sizes!"))
-
-            results = list(zip(links, times, sizes))
-            if randomize_order:
-                random.shuffle(results)
-            for _link, _time, _size in results:
-                if _link.endswith("/"):
-                    if _link.split(r"/")[-2] in ignore_folder_names:
-                        continue
-                    else:
-                        # print(f"Queueing folder: {urllib.parse.urljoin(url,_link)}")
-                        query_work_queue.put(urllib.parse.urljoin(url,_link))
-                else:
-                    # print(f"Queueing file: {urllib.parse.urljoin(url,_link)}")
-                    query_result_queue.put((urllib.parse.urljoin(url,_link), _time, _size))
-    
-
-# Fetch file from url and store it to path, retrying on failure
-def file_download_worker(download_work_queue, download_result_queue, attempt_count = 2):
-    while True:
-        job = download_work_queue.get()
-        if job == None:
-            return
-        url, path, t, s = job
-
-        # print(f"Next job: {url}, {path}, {t}, {s}")
-        attempts = 0
-        while attempts < attempt_count:
-            try:
-                starttime = time.time()
-                req = urllib.request.Request(url, data=None)
-                image_data = urllib.request.urlopen(req, timeout=10.0).read()
-                endtime = time.time()
-                tqdm.tqdm.write(f"Downloaded {url} in {endtime-starttime:0.2f} s | {len(image_data)/1024/1024/(endtime-starttime):0.2f} MB/s")
-                if math.isclose(len(image_data), s, rel_tol=0.05):
-                    os.makedirs(os.path.split(path)[0], exist_ok=True)
-                    open(path, 'wb').write(image_data)
-                    download_result_queue.put((True, url, t))
-                    break
-                else:
-                    raise ValueError("Downloaded file is the wrong size!")
-            except Exception as e:
-                if hasattr(e, "code") and e.code == 404: # This is expected if the file has been removed from the site (at least for swpc.noaa.gov)
-                    attempts += attempt_count
-                elif (0 < attempts) and (attempts < attempt_count):
-                    # tqdm.tqdm.write(f"\nA problem occurred on file: {url} | {e}")
-                    time.sleep(1 + random.random())
-                    attempts += 1
-                if (attempt_count > 1) and (attempts == attempt_count):
-                    tqdm.tqdm.write(f'\nAfter {attempt_count} retries, could not fetch: {url}')
-                    tqdm.tqdm.write(f"Exception: {e}")
-                    download_result_queue.put((False, url, t))
-                    break
-
-
-if __name__ == "__main__":
-    file_info_cache = {}
-    try:
-        print(f"Attempting to load file records from cache: {file_database_path}")
-        with open(file_database_path, 'r') as f:
-            file_info_cache = json.loads(f.read())
-        print(f"File records loaded from cache: {len(file_info_cache)} records found.")
-    except Exception as e:
-        print(f"Load failed, starting with empty cache")
-        file_info_cache = {}
-
-    query_work_queue = queue.Queue()
-    query_result_queue = queue.Queue()
-    download_work_queue = queue.Queue(maxsize=ndownloadworkers)
-    download_result_queue = queue.Queue(maxsize=ndownloadworkers)
-    workers = []
-    for _ in range(nfetchworkers):
-        t = Thread(target=find_links_worker, args=(query_work_queue, query_result_queue, 3, randomize_order), daemon=True)
-        t.start()
-        workers.append(t)
-    for _ in range(ndownloadworkers):
-        t = Thread(target=file_download_worker, args=(download_work_queue, download_result_queue), daemon=True)
-        t.start()
-        workers.append(t)
-    
-    try:
-        while True:
-            fetched_image_count = 0
-            already_had_image_count = 0
-            failed_image_count = 0
-            urllen = len(directory_url)
-
-            query_work_queue.put(directory_url)
-            for l, t, s in tqdm.tqdm(iter(partial(query_result_queue.get, timeout=30.0), None), desc="Downloading files"):
-                # Collect completed jobs and record completion status
-                while True:
-                    try:
-                        r_success, r_url, r_t = download_result_queue.get_nowait()
-                        if r_success: 
-                            fetched_image_count += 1
-                            file_info_cache[r_url] = r_t
-                        else:
-                            failed_image_count += 1
-                    except queue.Empty:
-                        break
-
-                file_portion_of_link = l[urllen:]
-                filepath = os.path.join(stored_images_dir, file_portion_of_link.replace("/", os.sep))
-                # If we dont have the file or the file at the link is newer than the one we previously fetched
-                if (not (l in file_info_cache)) or t > file_info_cache[l]: 
-                    if filepath.endswith(".fits"):
-                        filepath2 = filepath.split(".fits")[0] + "_f.fits" # also look for the filtered version of the file
-                        filepath3 = filepath.split(".fits")[0] + "_e.fits" # also look for the error version of the file
-                        if os.path.exists(filepath2) or os.path.exists(filepath3): # If the unfiltered filename exists, that case will be handled in the alternative code path in if os.path.exists(filepath):
-                            if l in file_info_cache: # If we have record of this file, it must be out of date, delete it and download the new version.
-                                try:
-                                    os.remove(filepath2)
-                                    os.remove(filepath3)
-                                except:
-                                    pass
-                            else: # If we have no record of this file, update the file info cache and don't redownload
-                                file_info_cache[l] = t
-                                already_had_image_count += 1
-                                continue
-                    if os.path.exists(filepath):
-                        if l in file_info_cache: # If we have record of this file, it must be out of date, delete it and download the new version.
-                            if os.path.exists(filepath):
-                                os.remove(filepath)
-                        else: # If we have no record of this file, update the file info cache and don't redownload if fsize is right
-                            fsize = os.path.getsize(filepath)
-                            if math.isclose(fsize, s, rel_tol=0.05):
-                                file_info_cache[l] = t
-                                already_had_image_count += 1
-                                continue
-                            else:
-                                tqdm.tqdm.write(f'Found a mismatched size on file: {filepath}  Redownloading!')
-                    download_work_queue.put((l, filepath, t, s))
-                else:
-                    # We have a download record, confirm the file actually exists on disk
-                    if os.path.exists(filepath):
-                        already_had_image_count += 1
-                    elif filepath.endswith(".fits"):
-                        filepath2 = filepath.split(".fits")[0] + "_f.fits" # also look for the filtered version of the file
-                        filepath3 = filepath.split(".fits")[0] + "_e.fits" # also look for the error version of the file
-                        if os.path.exists(filepath2) or os.path.exists(filepath3):
-                            already_had_image_count += 1
-                        else: # We could not find the file on disk, queue for redownload
-                            download_work_queue.put((l, filepath, t))
-                    
-            with open(file_database_path, 'w') as f:
-                f.write(json.dumps(file_info_cache))
-            print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
-            if fetch_interval > 0:
-                print(f"Run complete!, sleeping for {fetch_interval} seconds.")
-                with open(file_database_path, 'w') as f:
-                    f.write(json.dumps(file_info_cache))
-                time.sleep(fetch_interval)
-            else:
-                print("Run complete!, exiting...")
-                break
-    except KeyboardInterrupt:
-        print("Saving file database and shutting down.")
-    except Empty:
-        print("Work Complete, Shutting down...")
-    except Exception as e:
-        print(f"Unhandled Exception during run: {e}")
-        print("Shutting down")
-
-    for _ in range(nfetchworkers):
-        try:
-            query_work_queue.put(None)
-        except:
-            break
-
-    time.sleep(1)
-    print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
-
-    while len(download_work_queue.queue) > 0:
-        print(f"Waiting for {len(download_work_queue.queue)} downloads in queue...")
-        time.sleep(1)
-
-    for _ in range(ndownloadworkers):
-        try:
-            download_work_queue.put(None, timeout=5.0)
-        except:
-            break
-
-    with open(file_database_path, 'w') as f:
-        f.write(json.dumps(file_info_cache))
-
-    print("Waiting for workers to shutdown...")
-
-    for w in workers:
-        w.join(5.0)
\ No newline at end of file
+import os
+import sys
+import urllib.request
+import urllib.parse
+import re
+import time
+import random
+import datetime
+from threading import Thread
+import queue
+import math
+from functools import partial
+from queue import Empty
+
+import tqdm
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import db, index, paths, vfs
+
+directory_url = r"https://data.ngdc.noaa.gov/platforms/solar-space-observing-satellites/goes/"
+stored_images_dir = paths.data_root()
+ignore_folder_names = ["Parent Directory", "l1b", "goes17", "2017", "2018", "2019", "2020", "2021", "2022", "2023"]
+fetch_interval = 0 # 60*60
+nfetchworkers = 2 # Be nice to the servers, this value is how many threads will be asking for links and file info at the same time
+ndownloadworkers = 3 # Be nice to the servers, this value is how many threads will be downloading files at the same time
+randomize_order = False
+
+links_regex_pattern = r'(?<=<a href=")([^ ?:]*)(?=">.*\d{4}-\d{2}-\d{2} \d{2}:\d{2})' # Find href links that do not contain question marks or whitespace
+times_regex_pattern = r'(?<=<td align="right">)(\d{4}-\d{2}-\d{2} \d{2}:\d{2})(?= )' # Find timestamps in UTC in the format YYYY-MM-DD HH:mm
+sizes_regex_pattern = r'(?<=\d{4}-\d{2}-\d{2} \d{2}:\d{2}  <\/td><td align="right">)([ .\d]{1,3})([KMG]|- |0 | )(?=<\/td>)' # Find file size markers in one of many possible formats
+links_matcher = re.compile(links_regex_pattern)
+times_matcher = re.compile(times_regex_pattern)
+sizes_matcher = re.compile(sizes_regex_pattern)
+
+def find_links_worker(query_work_queue, query_result_queue, attempt_count = 3, randomize_order = True):
+    while True:
+        job = query_work_queue.get()
+        if job == None:
+            return
+        url= job
+    
+        attempts = 0
+        html_content = None
+        while attempts < attempt_count:
+            try:
+                with urllib.request.urlopen(url) as response:
+                    html_content = response.read().decode('utf-8')
+                    break
+            except Exception as e:
+                tqdm.tqdm.write(f"Exception while fetching links: {e}")
+                time.sleep(1 + random.random())
+                attempts += 1
+            if (attempt_count > 1) and (attempts == attempt_count):
+                tqdm.tqdm.write(f'\nAfter {attempt_count} retries, could not fetch: {url}')
+
+        if html_content is None: # We failed to fetch the link for some reason, continue to the next job
+            continue
+        else:
+            links = links_matcher.findall(html_content)
+            times = times_matcher.findall(html_content)
+            sizes = sizes_matcher.findall(html_content)
+            for i in range(len(times)):
+                dt = datetime.datetime.strptime(times[i].strip(), "%Y-%m-%d %H:%M")
+                dt.replace(tzinfo=datetime.timezone.utc)
+                times[i] = time.mktime(dt.timetuple())
+            for i in range(len(sizes)):
+                match sizes[i][1].strip():
+                    case '-':
+                        sizes[i] = 0
+                    case 'K':
+                        sizes[i] = int(float(sizes[i][0].strip()) * 1024)
+                    case 'M':
+                        sizes[i] = int(float(sizes[i][0].strip()) * 1024 * 1024)
+                    case 'G':
+                        sizes[i] = int(float(sizes[i][0].strip()) * 1024 * 1024 * 1024)
+                    case "0":
+                        sizes[i] = 0
+                    case "":
+                        sizes[i] = int(float(sizes[i][0].strip()))
+                    case _:
+                        raise(ValueError(f"Unexpected symbol while parsing links page: {_}"))
+
+            
+            if (len(links) != len(times)) or (len(times) != len(sizes)):
+                raise(ValueError("Links parsing error, mismatched numbers of links, times, or sizes!"))
+
+            results = list(zip(links, times, sizes))
+            if randomize_order:
+                random.shuffle(results)
+            for _link, _time, _size in results:
+                if _link.endswith("/"):
+                    if _link.split(r"/")[-2] in ignore_folder_names:
+                        continue
+                    else:
+                        # print(f"Queueing folder: {urllib.parse.urljoin(url,_link)}")
+                        query_work_queue.put(urllib.parse.urljoin(url,_link))
+                else:
+                    # print(f"Queueing file: {urllib.parse.urljoin(url,_link)}")
+                    query_result_queue.put((urllib.parse.urljoin(url,_link), _time, _size))
+    
+
+# Fetch file from url and store it to path, retrying on failure
+def file_download_worker(download_work_queue, download_result_queue, attempt_count = 2):
+    while True:
+        job = download_work_queue.get()
+        if job == None:
+            return
+        url, path, t, s = job
+
+        # print(f"Next job: {url}, {path}, {t}, {s}")
+        attempts = 0
+        while attempts < attempt_count:
+            try:
+                starttime = time.time()
+                req = urllib.request.Request(url, data=None)
+                image_data = urllib.request.urlopen(req, timeout=10.0).read()
+                endtime = time.time()
+                tqdm.tqdm.write(f"Downloaded {url} in {endtime-starttime:0.2f} s | {len(image_data)/1024/1024/(endtime-starttime):0.2f} MB/s")
+                if math.isclose(len(image_data), s, rel_tol=0.05):
+                    os.makedirs(os.path.split(path)[0], exist_ok=True)
+                    open(path, 'wb').write(image_data)
+                    download_result_queue.put((True, url, t))
+                    break
+                else:
+                    raise ValueError("Downloaded file is the wrong size!")
+            except Exception as e:
+                if hasattr(e, "code") and e.code == 404: # This is expected if the file has been removed from the site (at least for swpc.noaa.gov)
+                    attempts += attempt_count
+                elif (0 < attempts) and (attempts < attempt_count):
+                    # tqdm.tqdm.write(f"\nA problem occurred on file: {url} | {e}")
+                    time.sleep(1 + random.random())
+                    attempts += 1
+                if (attempt_count > 1) and (attempts == attempt_count):
+                    tqdm.tqdm.write(f'\nAfter {attempt_count} retries, could not fetch: {url}')
+                    tqdm.tqdm.write(f"Exception: {e}")
+                    download_result_queue.put((False, url, t))
+                    break
+
+
+if __name__ == "__main__":
+    import argparse
+
+    parser = argparse.ArgumentParser(
+        description="Mirror NOAA GOES SUVI L2 FITS into the local archive.",
+    )
+    parser.add_argument("--db", default=None, help="SQLite index (default: $SUVI_DB)")
+    parser.add_argument("--root", default=None, help="archive root (default: $SUVI_DATA_ROOT)")
+    parser.add_argument("--interval", type=int, default=fetch_interval,
+                        help="seconds to sleep between passes; 0 runs once and exits")
+    args = parser.parse_args()
+
+    if args.root:
+        stored_images_dir = os.path.abspath(args.root)
+    fetch_interval = args.interval
+
+    # Download bookkeeping lives in the index. It used to be an 800 MB JSON object
+    # parsed into memory on every run; see migrate_urlcache.py for the conversion.
+    # Losing this state means re-fetching the whole archive, so writes are committed
+    # as they happen rather than only at the end of a pass.
+    conn = db.connect(args.db)
+    known = conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"]
+    print(f"Download records in index: {known}")
+
+    query_work_queue = queue.Queue()
+    query_result_queue = queue.Queue()
+    download_work_queue = queue.Queue(maxsize=ndownloadworkers)
+    download_result_queue = queue.Queue(maxsize=ndownloadworkers)
+    workers = []
+    for _ in range(nfetchworkers):
+        t = Thread(target=find_links_worker, args=(query_work_queue, query_result_queue, 3, randomize_order), daemon=True)
+        t.start()
+        workers.append(t)
+    for _ in range(ndownloadworkers):
+        t = Thread(target=file_download_worker, args=(download_work_queue, download_result_queue), daemon=True)
+        t.start()
+        workers.append(t)
+
+    fetched_image_count = already_had_image_count = failed_image_count = 0
+    pending_records = []
+
+    def flush_records(force=False):
+        """Commit download records in batches, and always before a long pause."""
+        if pending_records and (force or len(pending_records) >= 200):
+            db.record_remote_files(conn, pending_records)
+            conn.commit()
+            pending_records.clear()
+
+    reliever = vfs.Reliever(label="puller")
+
+    def index_frame(local_path):
+        reliever.tick()
+        """Record a freshly written frame in the index.
+
+        The downloader already knows this file exists, so indexing it here means the
+        index never has to be rebuilt by traversing the archive -- which on this
+        virtiofs mount is an operation to be avoided rather than merely optimised
+        (see suvi/index.py).  Failure to index is not worth losing a download over;
+        `filter_FITS.py index` will pick the frame up from its directory mtime.
+        """
+        try:
+            index.record_downloaded(conn, local_path, stored_images_dir)
+        except Exception as exc:
+            tqdm.tqdm.write(f"Could not index {local_path}: {exc}")
+
+    try:
+        while True:
+            fetched_image_count = 0
+            already_had_image_count = 0
+            failed_image_count = 0
+            urllen = len(directory_url)
+
+            query_work_queue.put(directory_url)
+            for l, t, s in tqdm.tqdm(iter(partial(query_result_queue.get, timeout=30.0), None), desc="Downloading files"):
+                # Collect completed jobs and record completion status
+                while True:
+                    try:
+                        r_success, r_url, r_t = download_result_queue.get_nowait()
+                        if r_success:
+                            fetched_image_count += 1
+                            pending_records.append((r_url, r_t, None, None, time.time()))
+                            index_frame(os.path.join(stored_images_dir,
+                                                     r_url[urllen:].replace("/", os.sep)))
+                        else:
+                            failed_image_count += 1
+                    except queue.Empty:
+                        break
+                flush_records()
+
+                file_portion_of_link = l[urllen:]
+                filepath = os.path.join(stored_images_dir, file_portion_of_link.replace("/", os.sep))
+                recorded_mtime = db.get_remote_mtime(conn, l)
+
+                # The archive no longer carries _f/_e suffixes, so a frame is either
+                # at its published filename or absent -- no variant probing needed.
+                if recorded_mtime is None or t > recorded_mtime:
+                    if os.path.exists(filepath):
+                        if recorded_mtime is not None:
+                            # We have a record, so the remote copy is newer: replace it.
+                            try:
+                                os.remove(filepath)
+                            except OSError:
+                                pass
+                        else:
+                            # No record, but the file is here. Adopt it if the size
+                            # matches rather than re-downloading the whole archive.
+                            if math.isclose(os.path.getsize(filepath), s, rel_tol=0.05):
+                                pending_records.append((l, t, s, filepath, time.time()))
+                                index_frame(filepath)
+                                already_had_image_count += 1
+                                continue
+                            tqdm.tqdm.write(f"Size mismatch on {filepath}; redownloading")
+                    download_work_queue.put((l, filepath, t, s))
+                elif os.path.exists(filepath):
+                    already_had_image_count += 1
+                else:
+                    # Recorded as downloaded but gone from disk; fetch it again.
+                    download_work_queue.put((l, filepath, t, s))
+
+            flush_records(force=True)
+            print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
+            if fetch_interval > 0:
+                print(f"Run complete!, sleeping for {fetch_interval} seconds.")
+                time.sleep(fetch_interval)
+            else:
+                print("Run complete!, exiting...")
+                break
+    except KeyboardInterrupt:
+        print("Saving download records and shutting down.")
+    except Empty:
+        print("Work Complete, Shutting down...")
+
+    for _ in range(nfetchworkers):
+        try:
+            query_work_queue.put(None)
+        except Exception:
+            break
+
+    time.sleep(1)
+    print(f"Downloaded {fetched_image_count} | Already had {already_had_image_count} | Failed {failed_image_count}")
+
+    while len(download_work_queue.queue) > 0:
+        print(f"Waiting for {len(download_work_queue.queue)} downloads in queue...")
+        time.sleep(1)
+
+    for _ in range(ndownloadworkers):
+        try:
+            download_work_queue.put(None, timeout=5.0)
+        except Exception:
+            break
+
+    # Drain any results the workers finished after the main loop ended.
+    while True:
+        try:
+            r_success, r_url, r_t = download_result_queue.get_nowait()
+            if r_success:
+                pending_records.append((r_url, r_t, None, None, time.time()))
+                index_frame(os.path.join(stored_images_dir,
+                                         r_url[len(directory_url):].replace("/", os.sep)))
+        except queue.Empty:
+            break
+    flush_records(force=True)
+    conn.close()
+
+    print("Waiting for workers to shutdown...")
+    for w in workers:
+        w.join(5.0)
diff --git a/pytest.ini b/pytest.ini
new file mode 100644
index 0000000..6801365
--- /dev/null
+++ b/pytest.ini
@@ -0,0 +1,5 @@
+[pytest]
+testpaths = tests
+filterwarnings =
+    # astropy warns about the deliberately damaged files these tests construct.
+    ignore::astropy.utils.exceptions.AstropyUserWarning
diff --git a/reclaim.py b/reclaim.py
new file mode 100644
index 0000000..434c306
--- /dev/null
+++ b/reclaim.py
@@ -0,0 +1,69 @@
+#!/usr/bin/env python
+"""Hand the archive's file handles back to the host.
+
+The archive is on a virtiofs share whose daemon holds a host file descriptor per
+inode the guest has looked up.  Anything that reads a lot of the archive leaves those
+inodes cached, and the handles with them, until something forces the guest to evict
+them -- at which point the daemon can run out and the mount starts refusing *every*
+open, which surfaces across the whole machine as "too many open files in system".
+
+The pipeline's own bulk jobs now reclaim as they go and again when they finish, so
+this should rarely be needed.  It exists for when something else has loaded the cache,
+or to check where things stand:
+
+    reclaim.py            # report, then reclaim if needed
+    reclaim.py --check    # report only, change nothing
+    sudo reclaim.py       # uses drop_caches: instant, and far gentler
+
+Without root the only lever available is memory pressure, which means briefly
+allocating several GiB.  Running under sudo avoids that entirely.
+"""
+
+import argparse
+import os
+import sys
+
+sys.path.insert(0, os.path.dirname(os.path.abspath(__file__)))
+
+from suvi import vfs
+
+#: Roughly the slab size at which the daemon is likely near a 1M descriptor limit.
+#: A cached dentry plus inode is on the order of a kilobyte, so a gigabyte of
+#: reclaimable slab is on the order of a million inodes.
+CONCERN_GIB = 1.0
+
+
+def report(prefix):
+    slab = vfs.reclaimable_kb() / (1024 * 1024)
+    print(f"{prefix:>8}: {slab:.2f} GiB reclaimable slab "
+          f"(~{slab:.1f}M cached inodes), {vfs.available_gib():.1f} GiB available")
+    return slab
+
+
+def main(argv=None):
+    parser = argparse.ArgumentParser(description=__doc__,
+                                     formatter_class=argparse.RawDescriptionHelpFormatter)
+    parser.add_argument("--check", action="store_true", help="report only, reclaim nothing")
+    parser.add_argument("--force", action="store_true", help="reclaim even if it looks fine")
+    args = parser.parse_args(argv)
+
+    before = report("before")
+    if args.check:
+        print("  (check only; nothing reclaimed)")
+        return 0 if before < CONCERN_GIB else 1
+
+    if before < CONCERN_GIB and not args.force:
+        print(f"  below {CONCERN_GIB} GiB; nothing to do.  Use --force to reclaim anyway.")
+        return 0
+
+    if os.geteuid() != 0:
+        print("  not root, so using memory pressure; run under sudo for the direct path")
+    freed = vfs.release_handles()
+    after = report("after")
+    print(f"  {'reclaimed' if freed else 'no change'}: "
+          f"{before - after:+.2f} GiB")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())
diff --git a/requirements.txt b/requirements.txt
index 3fc1061..363eff2 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -1,8 +1,12 @@
 astropy
-scikit-image
-tqdm
-numpy
-opencv-python
-palettable
 matplotlib
-pillow
\ No newline at end of file
+numpy
+opencv-python-headless
+palettable
+pillow
+scikit-image
+sortedcontainers
+tqdm
+
+# Development
+pytest
diff --git a/suvi/__init__.py b/suvi/__init__.py
new file mode 100644
index 0000000..867f51e
--- /dev/null
+++ b/suvi/__init__.py
@@ -0,0 +1,6 @@
+"""Shared library for the NOAA GOES SUVI pipeline.
+
+Modules here are pure and side-effect free unless documented otherwise, so that the
+production drivers (``filter_FITS.py``, ``merger_FITS.py``, ``puller_fits.py``) and
+the test bench (``bench.py``) can share one implementation of every rule.
+"""
diff --git a/suvi/cases.py b/suvi/cases.py
new file mode 100644
index 0000000..ed6419e
--- /dev/null
+++ b/suvi/cases.py
@@ -0,0 +1,397 @@
+"""Building bench cases: finding clean windows, planning injections, resolving reads.
+
+The bench never modifies the archive.  A *case* is a plan plus an overlay directory:
+slots the plan corrupts are written as new files under the overlay, slots it deletes
+resolve to nothing, and every other slot resolves straight through to the real file.
+:class:`Overlay` is the indirection that makes that work, so detectors and fillers can
+be written as if they were reading the archive directly.
+
+Everything here is deterministic in the case seed, so a run can be reproduced or
+resumed exactly.
+"""
+
+import os
+from dataclasses import dataclass, field
+
+import numpy as np
+
+from . import corruptions, paths
+
+#: A slot with no good frame either side cannot be filled or scored, so cases leave
+#: this many good slots untouched at each end of the window.
+EDGE_MARGIN = 8
+#: Minimum good slots left between two injected gaps, so every gap has clean brackets.
+MIN_SEPARATION = 4
+
+
+def gap_separation(length):
+    """Clean slots to leave either side of a gap of `length`.
+
+    A fixed four slots was fine when gaps were one to six frames.  It is not fine at
+    three hundred: the frames a long gap is reconstructed from would themselves sit
+    within a few slots of the next gap, so the "clean brackets" a fill is scored
+    against would be neighbours of other damage.  Scale the guard with the gap.
+    """
+    return max(MIN_SEPARATION, length // 4)
+
+
+def scan_window(root, satellites, wavelengths, t_start, t_end):
+    """Index the archive for one time window, by filename only.
+
+    Returns {(satellite, wavelength, t_start): (abs_path, legacy_label)}.  Reads no
+    file contents, so it is cheap enough to run over a week of data interactively.
+    """
+    found = {}
+    for satellite in satellites:
+        for wavelength in wavelengths:
+            base = os.path.join(
+                root, f"goes{satellite:d}", "l2", "data", f"suvi-l2-ci{wavelength:03d}"
+            )
+            if not os.path.isdir(base):
+                continue
+            for day_dir in _candidate_days(base, t_start, t_end):
+                try:
+                    entries = os.listdir(day_dir)
+                except OSError:
+                    continue
+                for entry in entries:
+                    name = paths.parse_frame_filename(entry)
+                    if name is None:
+                        continue
+                    if not (t_start <= name.t_start < t_end):
+                        continue
+                    if name.satellite != satellite or name.wavelength != wavelength:
+                        continue
+                    found[name.slot] = (os.path.join(day_dir, entry), name.label)
+    return found
+
+
+def _candidate_days(base, t_start, t_end):
+    """Day directories the window could touch, without walking the whole tree."""
+    import datetime
+
+    day = datetime.datetime.fromtimestamp(t_start, datetime.timezone.utc).date()
+    last = datetime.datetime.fromtimestamp(t_end, datetime.timezone.utc).date()
+    while day <= last:
+        path = os.path.join(base, f"{day.year:04d}", f"{day.month:02d}", f"{day.day:02d}")
+        if os.path.isdir(path):
+            yield path
+        day += datetime.timedelta(days=1)
+
+
+def timeline(t_start, t_end, cadence=paths.CADENCE):
+    """Every slot the cadence says should exist in a window."""
+    return list(range(t_start, t_end, cadence))
+
+
+def slot_is_good(found, satellite, wavelength, time):
+    """Whether a slot holds a frame the legacy filter passed.
+
+    An unlabelled frame counts as unknown, not good: roughly a quarter of the
+    archive was never processed, and treating that as clean would quietly seed the
+    ground truth with unvetted frames.
+
+    Note that these labels are *stale*.  The archive's suffixes were written in
+    May 2024; filter_FITS.py was substantially retuned that July (max_center_skew
+    5 -> 7, ratio_above_thresh_max 0.5 -> 0.4, a minimum added).  They record what
+    some earlier filter thought, which is useful as an availability hint and as
+    history, but is not ground truth.  Vetting uses headers instead.
+    """
+    entry = found.get((satellite, wavelength, time))
+    if entry is None:
+        return None
+    return entry[1] == "f" if entry[1] else None
+
+
+def find_runs(found, satellites, wavelengths, t_start, t_end, minimum=120,
+              require_good_label=False):
+    """Longest stretches where every requested band and satellite has a frame.
+
+    Returns (length_in_slots, start_time, end_time) tuples, longest first.  Needs no
+    file contents, only filenames, so it is fast enough to run interactively over
+    weeks of archive.
+
+    By default this asks only that a frame *exists*, because the legacy labels are
+    stale (see :func:`slot_is_good`) and filtering on them would both miss good data
+    and admit bad.  Judging quality is ``vet-window``'s job, from the headers.
+    """
+    slots = timeline(t_start, t_end)
+    runs = []
+    current = 0
+    start = None
+    for time in slots:
+        if require_good_label:
+            complete = all(
+                slot_is_good(found, satellite, wavelength, time) is True
+                for satellite in satellites
+                for wavelength in wavelengths
+            )
+        else:
+            complete = all(
+                (satellite, wavelength, time) in found
+                for satellite in satellites
+                for wavelength in wavelengths
+            )
+        if complete:
+            if current == 0:
+                start = time
+            current += 1
+        else:
+            if current >= minimum:
+                runs.append((current, start, time - paths.CADENCE))
+            current = 0
+    if current >= minimum:
+        runs.append((current, start, slots[-1]))
+    return sorted(runs, reverse=True)
+
+
+# --------------------------------------------------------------------------- plans
+
+
+@dataclass
+class InjectionPlan:
+    """What a case does to its window.
+
+    The axes here are the experiment's independent variables: how much is damaged,
+    in what size runs, on which satellites, and how.
+    """
+
+    #: Fraction of slots to damage, in [0, 1).
+    fraction: float = 0.10
+    #: Gap widths to sample, in slots.  Fill quality degrades with gap length, so the
+    #: spread matters more than the mean.
+    gap_lengths: tuple = (1, 2, 3, 5, 10, 30, 60)
+    #: 'g16', 'g18', 'both', or 'mixed'.  'both' removes the same slots from each
+    #: satellite at once, which is the only case where cross-satellite fill is
+    #: unavailable -- and it is 31% of real outages, so it is not a corner case.
+    satellite_scope: str = "mixed"
+    #: 'all' damages every band in a slot; 'one' damages a single band, which is the
+    #: case a per-wavelength repair can actually exploit.
+    wavelength_scope: str = "all"
+    #: Corruption modes to sample from, plus the pseudo-mode 'delete'.
+    modes: tuple = ("delete",) + tuple(corruptions.CATALOG)
+    #: Severity range sampled per gap.
+    severity: tuple = (0.5, 1.0)
+    #: Gaps to place at *each* length.  When set this governs instead of `fraction`.
+    #:
+    #: A budget expressed as a fraction is dominated by whichever gaps are longest:
+    #: one 300-slot gap consumes half a 0.25 budget on a 2,600-slot window, so the
+    #: run ends up with a single gap per length and a single corruption mode per
+    #: gap.  84% of one such case was one 300-slot `truncate`, which is not a test of
+    #: anything but that mode at that length.  Asking for a count per length gives an
+    #: experiment with a designed shape instead of an emergent one.
+    gaps_per_length: int | None = None
+
+    def validate(self):
+        if not 0.0 <= self.fraction < 1.0:
+            raise ValueError(f"fraction must be in [0, 1), got {self.fraction}")
+        if not self.gap_lengths or any(length < 1 for length in self.gap_lengths):
+            raise ValueError("gap_lengths must all be >= 1")
+        if self.satellite_scope not in ("g16", "g18", "both", "mixed"):
+            raise ValueError(f"unknown satellite_scope {self.satellite_scope!r}")
+        if self.wavelength_scope not in ("all", "one"):
+            raise ValueError(f"unknown wavelength_scope {self.wavelength_scope!r}")
+        unknown = [
+            mode for mode in self.modes if mode != "delete" and mode not in corruptions.CATALOG
+        ]
+        if unknown:
+            raise ValueError(f"unknown corruption modes: {unknown}")
+        low, high = self.severity
+        if not 0.0 < low <= high <= 1.0:
+            raise ValueError(f"severity must satisfy 0 < low <= high <= 1, got {self.severity}")
+        return self
+
+    def as_dict(self):
+        return {
+            "fraction": self.fraction,
+            "gap_lengths": list(self.gap_lengths),
+            "satellite_scope": self.satellite_scope,
+            "wavelength_scope": self.wavelength_scope,
+            "modes": list(self.modes),
+            "severity": list(self.severity),
+            "gaps_per_length": self.gaps_per_length,
+        }
+
+    @classmethod
+    def from_dict(cls, payload):
+        return cls(
+            fraction=payload["fraction"],
+            gap_lengths=tuple(payload["gap_lengths"]),
+            satellite_scope=payload["satellite_scope"],
+            wavelength_scope=payload["wavelength_scope"],
+            modes=tuple(payload["modes"]),
+            severity=tuple(payload["severity"]),
+            gaps_per_length=payload.get("gaps_per_length"),
+        )
+
+
+@dataclass(frozen=True)
+class Injection:
+    """One damaged slot."""
+
+    slot: tuple
+    mode: str
+    severity: float
+    #: Position within its gap, and the gap's total width -- fill quality is reported
+    #: against gap length, so this has to survive into the results.
+    gap_index: int
+    gap_length: int
+    #: Stable per-slot seed, so a corruption is reproducible in isolation.
+    seed: int
+
+
+def plan_injections(plan, window_slots, satellites, wavelengths, seed):
+    """Choose which slots to damage and how.
+
+    Gaps are laid down as non-overlapping runs separated by clean slots, with the
+    window's edges left intact, so every damaged slot has good frames to be
+    reconstructed from.  Returns a list of :class:`Injection`.
+    """
+    plan.validate()
+    rng = np.random.default_rng(seed)
+    # Gaps are laid down along the timeline, so collapse the (satellite, band, time)
+    # slots to the distinct timestamps they cover.
+    times = sorted({slot[2] for slot in window_slots})
+    usable = times[EDGE_MARGIN : len(times) - EDGE_MARGIN]
+    if not usable:
+        return []
+
+    # Refuse a window that cannot hold the gaps asked for, rather than quietly
+    # planning fewer (or none) and reporting a result for gap lengths that were
+    # never actually tested.
+    longest = max(plan.gap_lengths)
+    required = longest + 2 * gap_separation(longest)
+    if len(usable) < required:
+        raise ValueError(
+            f"window has {len(usable)} usable slots but a gap of {longest} needs "
+            f"{required} with its guard bands; use a longer window or shorter gaps"
+        )
+
+    lengths = sorted(plan.gap_lengths, reverse=True)
+    if plan.gaps_per_length:
+        wanted = {int(length): plan.gaps_per_length for length in lengths}
+        target = sum(length * count for length, count in wanted.items())
+    else:
+        wanted = None
+        target = int(len(times) * plan.fraction)
+    if target <= 0:
+        return []
+
+    # Lay down gaps at random starts, rejecting any that would touch an existing one.
+    # Longest first: a 300-slot gap placed last would rarely find room, so the mix
+    # would silently skew towards the short lengths it is meant to be compared with.
+    taken = set()
+    gaps = []
+    budget = 0
+    attempts = max(len(usable) * 4, 8000)
+    for attempt in range(attempts):
+        if wanted is None:
+            if budget >= target:
+                break
+        elif not any(wanted.values()):
+            break
+        length = int(lengths[attempt % len(lengths)])
+        if wanted is not None and not wanted.get(length):
+            continue
+        separation = gap_separation(length)
+        start_index = int(rng.integers(0, max(1, len(usable) - length)))
+        span = usable[start_index : start_index + length]
+        if len(span) < length:
+            continue
+        guard = range(start_index - separation, start_index + length + separation)
+        if any(index in taken for index in guard):
+            continue
+        taken.update(guard)
+        gaps.append(span)
+        budget += length
+        if wanted is not None:
+            wanted[length] -= 1
+
+    injections = []
+    mode_order = list(plan.modes)
+    rng.shuffle(mode_order)
+    for gap_number, gap in enumerate(gaps):
+        # Cycle rather than sample: with only a handful of gaps, independent draws
+        # repeat modes and leave most of the catalogue untested.
+        mode = str(mode_order[gap_number % len(mode_order)])
+        low, high = plan.severity
+        severity = float(rng.uniform(low, high))
+        targets = _gap_targets(plan, satellites, wavelengths, rng)
+        for index, time in enumerate(gap):
+            for satellite, wavelength in targets:
+                slot = (satellite, wavelength, time)
+                if slot not in window_slots:
+                    continue
+                injections.append(
+                    Injection(
+                        slot=slot,
+                        mode=mode,
+                        severity=severity,
+                        gap_index=index,
+                        gap_length=len(gap),
+                        seed=int(rng.integers(0, 2**31 - 1)),
+                    )
+                )
+    return injections
+
+
+def _gap_targets(plan, satellites, wavelengths, rng):
+    """Which (satellite, wavelength) pairs one gap applies to."""
+    if plan.satellite_scope == "both":
+        chosen_satellites = list(satellites)
+    elif plan.satellite_scope == "mixed":
+        chosen_satellites = [satellites[int(rng.integers(0, len(satellites)))]]
+    else:
+        wanted = int(plan.satellite_scope[1:])
+        chosen_satellites = [wanted] if wanted in satellites else list(satellites[:1])
+
+    if plan.wavelength_scope == "all":
+        chosen_bands = list(wavelengths)
+    else:
+        chosen_bands = [wavelengths[int(rng.integers(0, len(wavelengths)))]]
+
+    return [(s, w) for s in chosen_satellites for w in chosen_bands]
+
+
+# ------------------------------------------------------------------------- overlay
+
+
+@dataclass
+class Overlay:
+    """Resolves a slot to the file a case should read for it.
+
+    Damaged slots point at the overlay copy, deleted slots resolve to None, and
+    everything else falls through to the archive untouched.  Nothing here can write
+    to the archive, which is the property that makes the bench safe to run against
+    live data.
+    """
+
+    #: slot -> absolute path in the real archive.
+    archive: dict = field(default_factory=dict)
+    #: slot -> absolute path of a corrupted replacement.
+    overrides: dict = field(default_factory=dict)
+    #: slots the case removed entirely.
+    deleted: frozenset = frozenset()
+
+    def path(self, slot):
+        """The file to read for `slot`, or None if the case removed it."""
+        if slot in self.deleted:
+            return None
+        if slot in self.overrides:
+            return self.overrides[slot]
+        entry = self.archive.get(slot)
+        return entry[0] if isinstance(entry, tuple) else entry
+
+    def truth_path(self, slot):
+        """The original file, regardless of what the case did -- for scoring."""
+        entry = self.archive.get(slot)
+        return entry[0] if isinstance(entry, tuple) else entry
+
+    def slots(self):
+        return sorted(self.archive)
+
+    def series(self, satellite, wavelength):
+        """Slots for one (satellite, band) stream, in time order."""
+        return sorted(
+            slot for slot in self.archive if slot[0] == satellite and slot[1] == wavelength
+        )
diff --git a/suvi/corruptions.py b/suvi/corruptions.py
new file mode 100644
index 0000000..4f4f132
--- /dev/null
+++ b/suvi/corruptions.py
@@ -0,0 +1,280 @@
+"""Catalogue of synthetic frame corruptions used by the test bench.
+
+Each entry models a failure mode actually seen in (or plausible for) this archive.
+Corruptions are seeded and reproducible: the same case seed and frame always yield
+byte-identical output, so a bench run can be repeated exactly.
+
+Two kinds, because they break a frame at different layers:
+
+* **array** corruptions damage the pixels; the bench re-writes a valid FITS around
+  the result.
+* **file** corruptions damage the bytes on disk, producing files that are not valid
+  FITS at all -- truncated downloads, missing HDUs, bit rot.
+
+The ``recompute_stats`` flag is the subtle part.  A real eclipse frame has a header
+whose ``IMG_MEAN`` agrees with its dim pixels, because NOAA computed it from them; a
+frame damaged in transit keeps the *original* header over broken pixels.  Setting
+this correctly per mode is what makes the bench's verdict on header-only detection
+honest -- otherwise header_v1 would appear to catch corruptions it could never see.
+"""
+
+from dataclasses import dataclass
+
+import numpy as np
+
+from . import fitsio
+
+#: Corruption strength in [0, 1].  0 is a barely-perceptible defect, 1 is total loss.
+DEFAULT_SEVERITY = 1.0
+
+
+@dataclass(frozen=True)
+class Corruption:
+    """One failure mode."""
+
+    name: str
+    #: Which of the four groups this belongs to, for per-group reporting.
+    group: str
+    #: 'array' (damages pixels) or 'file' (damages bytes on disk).
+    kind: str
+    apply: callable
+    #: Whether the header's radiance statistics are recomputed from the damaged
+    #: pixels.  True models a fault upstream of NOAA's header generation.
+    recompute_stats: bool = False
+    #: Whether this mode needs a second frame to draw from.
+    needs_donor: bool = False
+
+
+# ------------------------------------------------------------------ dropout / blackout
+
+
+def _eclipse_dim(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """The archive's most common real failure: Earth shadow drops radiance ~1000x."""
+    factor = 10.0 ** (-4.0 * severity)
+    dimmed = image * factor
+    # Real eclipse frames keep sensor read noise, so they are not exactly zero.
+    noise = rng.normal(0.0, float(np.abs(image).mean()) * 1e-4, image.shape)
+    return (dimmed + noise).astype(np.float32), {"DEGRADED": True, "ECLIPSE": 2}
+
+
+def _all_zero(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    return np.zeros_like(image), {"EMPTY": True}
+
+
+def _nan_fill(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Undefined pixels over part or all of the frame."""
+    out = image.copy()
+    if severity >= 1.0:
+        out[:] = np.nan
+    else:
+        mask = rng.random(image.shape) < severity
+        out[mask] = np.nan
+    return out, {}
+
+
+def _zblank_fill(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Fill with the FITS blank sentinel rather than NaN."""
+    out = image.copy()
+    mask = rng.random(image.shape) < severity if severity < 1.0 else np.ones(image.shape, bool)
+    out[mask] = fitsio.ZBLANK
+    return out, {}
+
+
+# -------------------------------------------------------------------------- structural
+
+
+def _truncate(raw, rng, severity=DEFAULT_SEVERITY):
+    """A download cut short.  Keeps at least the primary header."""
+    keep = max(fitsio.BLOCK, int(len(raw) * (1.0 - 0.9 * severity)))
+    return raw[:keep]
+
+
+def _drop_image_hdu(raw, rng, severity=DEFAULT_SEVERITY):
+    """Only the primary header survives -- the blank-HDU case the old filter hit."""
+    return raw[: fitsio.BLOCK]
+
+
+def _block_corruption(raw, rng, severity=DEFAULT_SEVERITY):
+    """Random bytes overwritten inside the data unit, leaving the header intact."""
+    out = bytearray(raw)
+    start = fitsio.BLOCK * 8  # past the headers
+    if len(out) <= start:
+        return bytes(out)
+    span = max(1, int((len(out) - start) * 0.02 * severity))
+    offset = int(rng.integers(start, len(out) - span))
+    out[offset : offset + span] = rng.integers(0, 256, span, dtype=np.uint8).tobytes()
+    return bytes(out)
+
+
+def _torn_frame(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Part of the frame comes from another observation -- a bad merge."""
+    if donor is None:
+        return image, {}
+    out = image.copy()
+    split = int(image.shape[0] * (1.0 - severity * 0.5))
+    out[split:, :] = donor[split:, :]
+    return out, {}
+
+
+def _dropped_rows(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Whole scan lines lost, as from a dropped packet."""
+    out = image.copy()
+    count = max(1, int(image.shape[0] * 0.3 * severity))
+    rows = rng.choice(image.shape[0], size=count, replace=False)
+    out[rows, :] = 0.0
+    return out, {}
+
+
+# ------------------------------------------------------------------------ radiometric
+
+
+def _gain_shift(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Calibration drift: everything scaled by a constant factor."""
+    factor = 1.0 + 4.0 * severity * (1 if rng.random() < 0.5 else -0.2)
+    return (image * factor).astype(np.float32), {}
+
+
+def _offset_shift(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """A constant added to every pixel -- a dark-current or bias fault."""
+    return (image + float(np.abs(image).mean()) * 5.0 * severity).astype(np.float32), {}
+
+
+def _saturate(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """A blowout that drives a large fraction of the frame to the ceiling."""
+    ceiling = float(np.nanmax(image)) or 1.0
+    boosted = image * (1.0 + 50.0 * severity)
+    return np.minimum(boosted, ceiling * 50.0).astype(np.float32), {}
+
+
+def _gaussian_noise(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    scale = float(np.nanstd(image)) * severity
+    return (image + rng.normal(0.0, scale, image.shape)).astype(np.float32), {}
+
+
+def _salt_pepper(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Cosmic-ray hits and dead pixels."""
+    out = image.copy()
+    fraction = 0.05 * severity
+    mask = rng.random(image.shape) < fraction
+    extreme = float(np.nanmax(image)) or 1.0
+    out[mask] = np.where(rng.random(int(mask.sum())) < 0.5, 0.0, extreme * 10.0)
+    return out, {}
+
+
+# ------------------------------------------------------------------ geometric/temporal
+
+
+def _translate(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Mispointing: the solar disc sits off centre."""
+    shift = int(200 * severity)
+    dx = int(rng.integers(-shift, shift + 1)) if shift else 0
+    dy = int(rng.integers(-shift, shift + 1)) if shift else 0
+    out = np.zeros_like(image)
+    h, w = image.shape
+    xs, xd = (max(0, -dx), max(0, dx))
+    ys, yd = (max(0, -dy), max(0, dy))
+    height, width = h - abs(dy), w - abs(dx)
+    out[yd : yd + height, xd : xd + width] = image[ys : ys + height, xs : xs + width]
+    return out, {"CRPIX1": (w + 1) / 2.0 + dx, "CRPIX2": (h + 1) / 2.0 + dy}
+
+
+def _rotate(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """Wrong roll angle -- the disc is round, so only structure reveals this."""
+    import cv2 as cv
+
+    angle = 180.0 * severity
+    centre = ((image.shape[1] - 1) / 2.0, (image.shape[0] - 1) / 2.0)
+    matrix = cv.getRotationMatrix2D(centre, angle, 1.0)
+    rotated = cv.warpAffine(
+        np.nan_to_num(image), matrix, (image.shape[1], image.shape[0]), flags=cv.INTER_LINEAR
+    )
+    return rotated.astype(np.float32), {"CROTA": angle}
+
+
+def _yaw_flip(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """The spacecraft's twice-yearly yaw flip applied when it should not be."""
+    return np.flip(np.flip(image, 0), 1).copy(), {"YAW_FLIP": 1}
+
+
+def _frozen(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """The feed stalled: this frame is a byte-for-byte repeat of a neighbour."""
+    return (donor.copy() if donor is not None else image), {}
+
+
+def _wrong_time(image, rng, severity=DEFAULT_SEVERITY, donor=None):
+    """A frame from a different observation filed under this timestamp."""
+    return (donor.copy() if donor is not None else image), {}
+
+
+CATALOG = {
+    corruption.name: corruption
+    for corruption in (
+        # Dropout / blackout -- the header follows the pixels, as NOAA computes it
+        # from the image it actually produced.
+        Corruption("eclipse_dim", "dropout", "array", _eclipse_dim, recompute_stats=True),
+        Corruption("all_zero", "dropout", "array", _all_zero, recompute_stats=True),
+        Corruption("nan_fill", "dropout", "array", _nan_fill, recompute_stats=False),
+        Corruption("zblank_fill", "dropout", "array", _zblank_fill, recompute_stats=False),
+        # Structural -- damage after the file was written, so the header is stale.
+        Corruption("truncate", "structural", "file", _truncate),
+        Corruption("drop_image_hdu", "structural", "file", _drop_image_hdu),
+        Corruption("block_corruption", "structural", "file", _block_corruption),
+        Corruption("torn_frame", "structural", "array", _torn_frame, needs_donor=True),
+        Corruption("dropped_rows", "structural", "array", _dropped_rows),
+        # Radiometric -- an instrument fault upstream of header generation.
+        Corruption("gain_shift", "radiometric", "array", _gain_shift, recompute_stats=True),
+        Corruption("offset_shift", "radiometric", "array", _offset_shift, recompute_stats=True),
+        Corruption("saturate", "radiometric", "array", _saturate, recompute_stats=True),
+        Corruption("gaussian_noise", "radiometric", "array", _gaussian_noise),
+        Corruption("salt_pepper", "radiometric", "array", _salt_pepper),
+        # Geometric / temporal -- the modes single-frame detectors are worst at.
+        Corruption("translate", "geometric", "array", _translate, recompute_stats=True),
+        Corruption("rotate", "geometric", "array", _rotate, recompute_stats=True),
+        Corruption("yaw_flip", "geometric", "array", _yaw_flip),
+        Corruption("frozen", "geometric", "array", _frozen, needs_donor=True),
+        Corruption("wrong_time", "geometric", "array", _wrong_time, needs_donor=True),
+    )
+}
+
+GROUPS = sorted({corruption.group for corruption in CATALOG.values()})
+
+
+def by_group(group):
+    return [name for name, c in CATALOG.items() if c.group == group]
+
+
+def apply_array(name, image, seed, severity=DEFAULT_SEVERITY, donor=None):
+    """Apply an array corruption.  Returns (image, header_overrides).
+
+    Deterministic in `seed`, so a bench case is exactly reproducible.
+    """
+    corruption = CATALOG[name]
+    if corruption.kind != "array":
+        raise ValueError(f"{name} is a {corruption.kind} corruption, not an array one")
+    if corruption.needs_donor and donor is None:
+        raise ValueError(f"{name} requires a donor frame")
+    rng = np.random.default_rng(seed)
+    return corruption.apply(np.asarray(image, dtype=np.float32), rng,
+                            severity=severity, donor=donor)
+
+
+def apply_file(name, raw, seed, severity=DEFAULT_SEVERITY):
+    """Apply a file-level corruption to raw FITS bytes."""
+    corruption = CATALOG[name]
+    if corruption.kind != "file":
+        raise ValueError(f"{name} is a {corruption.kind} corruption, not a file one")
+    rng = np.random.default_rng(seed)
+    return corruption.apply(raw, rng, severity=severity)
+
+
+def recomputed_stats(image):
+    """Header statistics consistent with `image`, as NOAA would have written them."""
+    finite = image[np.isfinite(image)]
+    if finite.size == 0:
+        return {"IMG_MIN": 0.0, "IMG_MAX": 0.0, "IMG_MEAN": 0.0, "IMG_SDEV": 0.0}
+    return {
+        "IMG_MIN": float(finite.min()),
+        "IMG_MAX": float(finite.max()),
+        "IMG_MEAN": float(finite.mean()),
+        "IMG_SDEV": float(finite.std()),
+    }
diff --git a/suvi/db.py b/suvi/db.py
new file mode 100644
index 0000000..82e8782
--- /dev/null
+++ b/suvi/db.py
@@ -0,0 +1,615 @@
+"""SQLite index of the SUVI archive: frames, header metadata, and detection results.
+
+This replaces the ``_f``/``_e`` filename suffixes the pipeline used to carry its
+verdicts in.  Keeping labels out of filenames means a detector can be re-run or
+re-tuned without touching the archive, and several detectors can disagree about the
+same frame without anyone having to pick a winner on disk.
+
+Everything except ``detector_run``/``detection`` is reconstructible: ``frame`` from a
+directory walk, ``header`` from a cheap re-read.  The database is therefore safe to
+delete, and the bench can point at a scratch copy via ``SUVI_DB``.
+
+Detection rows store the *continuous scores* a detector produced, not just its
+verdict, so sweeping a threshold is a query rather than another pass over 1.6M files.
+
+Writes are expected to come from a single process.  Worker processes read, and push
+results down a queue to one writer (see ``writer_loop``); SQLite tolerates many
+readers but only one writer, and this archive lives on a shared mount where lock
+contention is expensive.
+"""
+
+import json
+import os
+import queue
+import sqlite3
+import time
+
+from . import paths
+
+SCHEMA_VERSION = 2
+
+#: Versions that upgrade to the current one by nothing more than running the schema
+#: script again.  Every change so far has been a new table, and every table is
+#: declared IF NOT EXISTS, so an older index gains it on the next open.  A change
+#: that alters or drops an existing column must not be added here -- it needs a real
+#: migration step instead.
+ADDITIVE_UPGRADES_FROM = (1,)
+
+#: Header keywords cached in the ``header`` table.  Each entry maps a column name to
+#: the FITS keyword it comes from and its SQLite type.  Defined once so inserts and
+#: reads cannot drift apart.
+HEADER_COLUMNS = (
+    ("empty", "EMPTY", "INTEGER"),
+    ("degraded", "DEGRADED", "INTEGER"),
+    ("eclipse", "ECLIPSE", "INTEGER"),
+    ("num_imgs", "NUM_IMGS", "INTEGER"),
+    ("n_long", "N_LONG", "INTEGER"),
+    ("n_short", "N_SHORT", "INTEGER"),
+    ("n_sh_fl", "N_SH_FL", "INTEGER"),
+    ("exptime", "EXPTIME", "REAL"),
+    ("img_min", "IMG_MIN", "REAL"),
+    ("img_max", "IMG_MAX", "REAL"),
+    ("img_mean", "IMG_MEAN", "REAL"),
+    ("img_sdev", "IMG_SDEV", "REAL"),
+    ("imgtii", "IMGTII", "REAL"),
+    ("imgtir", "IMGTIR", "REAL"),
+    ("diam_sun", "DIAM_SUN", "REAL"),
+    ("crpix1", "CRPIX1", "REAL"),
+    ("crpix2", "CRPIX2", "REAL"),
+    ("crota", "CROTA", "REAL"),
+    ("cdelt1", "CDELT1", "REAL"),
+    ("cdelt2", "CDELT2", "REAL"),
+    ("yaw_flip", "YAW_FLIP", "INTEGER"),
+    ("solar_b0", "SOLAR_B0", "REAL"),
+    ("dsun_obs", "DSUN_OBS", "REAL"),
+    ("wavelnth", "WAVELNTH", "INTEGER"),
+    ("date_beg", "DATE-BEG", "TEXT"),
+    ("date_obs", "DATE-OBS", "TEXT"),
+    ("date_end", "DATE-END", "TEXT"),
+    ("datasum", "DATASUM", "TEXT"),
+    ("checksum", "CHECKSUM", "TEXT"),
+)
+
+HEADER_FIELDS = tuple(name for name, _, _ in HEADER_COLUMNS)
+
+_HEADER_DDL = ",\n    ".join(f"{name} {sqltype}" for name, _, sqltype in HEADER_COLUMNS)
+
+SCHEMA = f"""
+CREATE TABLE IF NOT EXISTS meta (
+    key   TEXT PRIMARY KEY,
+    value TEXT NOT NULL
+);
+
+-- One row per FITS file present in the archive.  `path` is archive-relative and
+-- always uses forward slashes, so the index is portable between Windows and Linux.
+CREATE TABLE IF NOT EXISTS frame (
+    id         INTEGER PRIMARY KEY,
+    path       TEXT    NOT NULL UNIQUE,
+    satellite  INTEGER NOT NULL,
+    wavelength INTEGER NOT NULL,
+    t_start    INTEGER NOT NULL,
+    t_end      INTEGER NOT NULL,
+    version    TEXT,
+    size_bytes INTEGER,
+    mtime      REAL
+);
+CREATE UNIQUE INDEX IF NOT EXISTS frame_slot ON frame (satellite, wavelength, t_start);
+CREATE INDEX IF NOT EXISTS frame_time ON frame (t_start);
+
+-- Cached FITS header metadata.  Populated by a ~18 KB read per file; no pixel
+-- decompression.  read_ok=0 means the file could not be parsed, and read_error says
+-- why -- itself a strong bad-frame signal.
+CREATE TABLE IF NOT EXISTS header (
+    frame_id   INTEGER PRIMARY KEY REFERENCES frame (id) ON DELETE CASCADE,
+    {_HEADER_DDL},
+    read_ok    INTEGER NOT NULL,
+    read_error TEXT,
+    scanned_at REAL NOT NULL
+);
+
+-- One row per (detector, configuration) execution, so results from different
+-- methods and different thresholds coexist and can be compared.
+CREATE TABLE IF NOT EXISTS detector_run (
+    id           INTEGER PRIMARY KEY,
+    name         TEXT NOT NULL,
+    config_json  TEXT NOT NULL,
+    code_version TEXT,
+    created_at   REAL NOT NULL,
+    notes        TEXT
+);
+CREATE INDEX IF NOT EXISTS detector_run_name ON detector_run (name);
+
+CREATE TABLE IF NOT EXISTS detection (
+    run_id     INTEGER NOT NULL REFERENCES detector_run (id) ON DELETE CASCADE,
+    frame_id   INTEGER NOT NULL REFERENCES frame (id) ON DELETE CASCADE,
+    verdict    TEXT    NOT NULL,
+    reason     TEXT,
+    scores_json TEXT,
+    elapsed_us INTEGER,
+    PRIMARY KEY (run_id, frame_id)
+) WITHOUT ROWID;
+CREATE INDEX IF NOT EXISTS detection_frame ON detection (frame_id);
+
+-- One row per day-directory, holding the mtime it had when we last read it.
+--
+-- This is what makes re-indexing cheap.  A directory's mtime changes whenever an
+-- entry is added or removed, so comparing it is an exact test for "did anything
+-- change in here" -- no guessing, no walking the files inside.  The archive holds
+-- ~360 frames per day-directory, so checking ~7,400 directory stats replaces
+-- 2.65M file lookups: a 360x reduction, and the difference between an operation
+-- this filesystem sustains and one that exhausts it.
+CREATE TABLE IF NOT EXISTS dir_scan (
+    path       TEXT PRIMARY KEY,
+    mtime      REAL NOT NULL,
+    n_frames   INTEGER NOT NULL,
+    scanned_at REAL NOT NULL
+) WITHOUT ROWID;
+
+-- Download bookkeeping, migrated out of the 800 MB file_database.json that
+-- puller_fits.py used to parse into memory on every run.
+CREATE TABLE IF NOT EXISTS remote_file (
+    url          TEXT PRIMARY KEY,
+    remote_mtime REAL NOT NULL,
+    remote_size  INTEGER,
+    local_path   TEXT,
+    fetched_at   REAL
+) WITHOUT ROWID;
+
+-- ---------------------------------------------------------------- test bench ----
+-- A stretch of archive vetted as known-good, frozen so that repeated experiments
+-- are measured against the same ground truth.
+CREATE TABLE IF NOT EXISTS bench_window (
+    id          INTEGER PRIMARY KEY,
+    name        TEXT NOT NULL UNIQUE,
+    t_start     INTEGER NOT NULL,
+    t_end       INTEGER NOT NULL,
+    satellites  TEXT NOT NULL,
+    wavelengths TEXT NOT NULL,
+    vetted_at   REAL,
+    notes       TEXT
+);
+
+CREATE TABLE IF NOT EXISTS bench_truth (
+    window_id  INTEGER NOT NULL REFERENCES bench_window (id) ON DELETE CASCADE,
+    frame_id   INTEGER NOT NULL REFERENCES frame (id) ON DELETE CASCADE,
+    is_good    INTEGER NOT NULL,
+    -- 'legacy' (old filename suffix), 'header' (cross-check), or 'manual'.
+    vet_source TEXT NOT NULL,
+    PRIMARY KEY (window_id, frame_id)
+) WITHOUT ROWID;
+
+-- One experiment: a window plus a seeded plan of deletions and corruptions.
+CREATE TABLE IF NOT EXISTS bench_case (
+    id         INTEGER PRIMARY KEY,
+    window_id  INTEGER NOT NULL REFERENCES bench_window (id) ON DELETE CASCADE,
+    name       TEXT NOT NULL UNIQUE,
+    seed       INTEGER NOT NULL,
+    plan_json  TEXT NOT NULL,
+    overlay_dir TEXT NOT NULL,
+    created_at REAL NOT NULL
+);
+
+-- What was done to each affected slot.  mode='delete' means the frame was withheld
+-- entirely; anything else names a corruption from suvi.corruptions.CATALOG.
+CREATE TABLE IF NOT EXISTS bench_injection (
+    case_id      INTEGER NOT NULL REFERENCES bench_case (id) ON DELETE CASCADE,
+    frame_id     INTEGER NOT NULL REFERENCES frame (id) ON DELETE CASCADE,
+    mode         TEXT NOT NULL,
+    severity     REAL NOT NULL DEFAULT 1.0,
+    params_json  TEXT,
+    overlay_path TEXT,
+    gap_index    INTEGER NOT NULL DEFAULT 0,
+    gap_length   INTEGER NOT NULL DEFAULT 1,
+    PRIMARY KEY (case_id, frame_id)
+) WITHOUT ROWID;
+
+-- Fill quality, one row per reconstructed frame, so results survive between runs.
+CREATE TABLE IF NOT EXISTS bench_fill_result (
+    case_id    INTEGER NOT NULL REFERENCES bench_case (id) ON DELETE CASCADE,
+    frame_id   INTEGER NOT NULL REFERENCES frame (id) ON DELETE CASCADE,
+    filler     TEXT NOT NULL,
+    source     TEXT NOT NULL,        -- 'oracle' or a detector name
+    scores_json TEXT NOT NULL,
+    PRIMARY KEY (case_id, frame_id, filler, source)
+) WITHOUT ROWID;
+"""
+
+#: Verdicts a detector may record.  'unknown' covers frames a detector declined to
+#: judge (e.g. a temporal detector with no usable neighbours), which must not be
+#: silently conflated with 'good'.
+VERDICTS = ("good", "bad", "unknown")
+
+
+def connect(path=None, readonly=False, timeout=60.0):
+    """Open the index, creating and initialising it if needed.
+
+    WAL is preferred but not required: this archive lives on a shared mount whose
+    locking primitives may not support it, so a failure to enter WAL falls back to
+    the rollback journal rather than aborting.
+    """
+    path = path or paths.default_db_path()
+    if readonly:
+        if not os.path.exists(path):
+            raise FileNotFoundError(f"No SUVI index at {path}")
+        conn = sqlite3.connect(f"file:{path}?mode=ro", uri=True, timeout=timeout)
+    else:
+        parent = os.path.dirname(os.path.abspath(path))
+        if parent:
+            os.makedirs(parent, exist_ok=True)
+        conn = sqlite3.connect(path, timeout=timeout)
+
+    conn.row_factory = sqlite3.Row
+    conn.execute("PRAGMA foreign_keys = ON")
+    conn.execute(f"PRAGMA busy_timeout = {int(timeout * 1000)}")
+    if not readonly:
+        try:
+            conn.execute("PRAGMA journal_mode = WAL")
+        except sqlite3.Error:
+            pass
+        conn.execute("PRAGMA synchronous = NORMAL")
+        init_schema(conn)
+    return conn
+
+
+def init_schema(conn):
+    """Create the schema if absent, upgrading an older index in place.  Idempotent."""
+    conn.executescript(SCHEMA)
+    row = conn.execute("SELECT value FROM meta WHERE key = 'schema_version'").fetchone()
+    if row is None:
+        conn.execute(
+            "INSERT INTO meta (key, value) VALUES ('schema_version', ?)",
+            (str(SCHEMA_VERSION),),
+        )
+        conn.commit()
+        return
+
+    found = int(row["value"])
+    if found == SCHEMA_VERSION:
+        return
+    if found in ADDITIVE_UPGRADES_FROM:
+        # executescript above already created any new tables.
+        conn.execute(
+            "UPDATE meta SET value = ? WHERE key = 'schema_version'", (str(SCHEMA_VERSION),)
+        )
+        conn.commit()
+        return
+    raise RuntimeError(
+        f"Index schema version {found} cannot be upgraded to {SCHEMA_VERSION} "
+        f"automatically; migrate or rebuild the index."
+    )
+
+
+def set_meta(conn, key, value):
+    conn.execute(
+        "INSERT INTO meta (key, value) VALUES (?, ?) "
+        "ON CONFLICT (key) DO UPDATE SET value = excluded.value",
+        (key, str(value)),
+    )
+
+
+def get_meta(conn, key, default=None):
+    row = conn.execute("SELECT value FROM meta WHERE key = ?", (key,)).fetchone()
+    return row["value"] if row else default
+
+
+# --------------------------------------------------------------------------- frames
+
+
+def upsert_frame(conn, name, relpath, size_bytes=None, mtime=None):
+    """Insert or update one frame row.  Returns its id.
+
+    Keyed on path, with the (satellite, wavelength, t_start) slot kept unique so a
+    duplicate observation stored under a second version string is rejected loudly
+    rather than silently shadowing the first.
+    """
+    conn.execute(
+        """
+        INSERT INTO frame (path, satellite, wavelength, t_start, t_end,
+                           version, size_bytes, mtime)
+        VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+        ON CONFLICT (path) DO UPDATE SET
+            size_bytes = excluded.size_bytes,
+            mtime      = excluded.mtime
+        """,
+        (
+            relpath,
+            name.satellite,
+            name.wavelength,
+            name.t_start,
+            name.t_end,
+            name.version,
+            size_bytes,
+            mtime,
+        ),
+    )
+    return conn.execute("SELECT id FROM frame WHERE path = ?", (relpath,)).fetchone()["id"]
+
+
+def frame_id_by_slot(conn, satellite, wavelength, t_start):
+    row = conn.execute(
+        "SELECT id FROM frame WHERE satellite = ? AND wavelength = ? AND t_start = ?",
+        (satellite, wavelength, t_start),
+    ).fetchone()
+    return row["id"] if row else None
+
+
+def frames_in_dir(conn, dir_relpath):
+    """Frames the index believes live in one directory: {filename: frame_id}."""
+    prefix = dir_relpath.rstrip("/") + "/"
+    rows = conn.execute(
+        "SELECT id, path FROM frame WHERE path >= ? AND path < ?",
+        (prefix, prefix + "￿"),
+    ).fetchall()
+    return {row["path"].rsplit("/", 1)[-1]: row["id"] for row in rows}
+
+
+def delete_frames(conn, frame_ids):
+    """Drop frames that have disappeared from disk, and their dependent rows."""
+    conn.executemany("DELETE FROM frame WHERE id = ?", [(i,) for i in frame_ids])
+
+
+# ------------------------------------------------------------------ directory scans
+
+
+def get_dir_mtime(conn, dir_relpath):
+    row = conn.execute("SELECT mtime FROM dir_scan WHERE path = ?", (dir_relpath,)).fetchone()
+    return row["mtime"] if row else None
+
+
+def dir_mtimes(conn):
+    """Every recorded directory mtime, as one dict.
+
+    Read in a single query rather than per directory: the whole point of this table
+    is to answer thousands of "has this changed?" questions without touching the
+    filesystem, and it would be perverse to pay a round trip each time.
+    """
+    return {
+        row["path"]: row["mtime"] for row in conn.execute("SELECT path, mtime FROM dir_scan")
+    }
+
+
+def record_dir_scans(conn, records):
+    """`records` yields (dir_relpath, mtime, n_frames)."""
+    now = time.time()
+    conn.executemany(
+        """
+        INSERT INTO dir_scan (path, mtime, n_frames, scanned_at) VALUES (?, ?, ?, ?)
+        ON CONFLICT (path) DO UPDATE SET
+            mtime = excluded.mtime,
+            n_frames = excluded.n_frames,
+            scanned_at = excluded.scanned_at
+        """,
+        [(path, mtime, count, now) for path, mtime, count in records],
+    )
+
+
+def forget_dir_scans(conn, dir_relpaths):
+    conn.executemany("DELETE FROM dir_scan WHERE path = ?", [(p,) for p in dir_relpaths])
+
+
+# ----------------------------------------------------------------------- detections
+
+
+def create_detector_run(conn, name, config, code_version=None, notes=None):
+    """Register a new detector execution and return its id."""
+    cur = conn.execute(
+        """
+        INSERT INTO detector_run (name, config_json, code_version, created_at, notes)
+        VALUES (?, ?, ?, ?, ?)
+        """,
+        (name, json.dumps(config, sort_keys=True), code_version, time.time(), notes),
+    )
+    conn.commit()
+    return cur.lastrowid
+
+
+def latest_run_id(conn, name, config=None):
+    """Most recent run of a named detector, or None.
+
+    With `config`, only runs recorded under exactly that configuration match.  This
+    matters more than it looks: detector runs accumulate, one per detector per bench
+    case, so "the latest run of header_v1" is whichever case was processed most
+    recently -- not the one being asked about.  Scoring one case's verdicts against
+    another case's injections produces numbers that are wrong rather than merely
+    imprecise, so callers working with a specific case must pass its config.
+    """
+    if config is None:
+        row = conn.execute(
+            "SELECT id FROM detector_run WHERE name = ? "
+            "ORDER BY created_at DESC, id DESC LIMIT 1",
+            (name,),
+        ).fetchone()
+    else:
+        row = conn.execute(
+            "SELECT id FROM detector_run WHERE name = ? AND config_json = ? "
+            "ORDER BY created_at DESC, id DESC LIMIT 1",
+            (name, json.dumps(config, sort_keys=True)),
+        ).fetchone()
+    return row["id"] if row else None
+
+
+def record_detections(conn, run_id, results):
+    """Write detection rows.  `results` yields (frame_id, verdict, reason, scores, us)."""
+    conn.executemany(
+        """
+        INSERT INTO detection (run_id, frame_id, verdict, reason, scores_json, elapsed_us)
+        VALUES (?, ?, ?, ?, ?, ?)
+        ON CONFLICT (run_id, frame_id) DO UPDATE SET
+            verdict     = excluded.verdict,
+            reason      = excluded.reason,
+            scores_json = excluded.scores_json,
+            elapsed_us  = excluded.elapsed_us
+        """,
+        [
+            (
+                run_id,
+                frame_id,
+                _check_verdict(verdict),
+                reason,
+                json.dumps(scores, sort_keys=True) if scores is not None else None,
+                elapsed_us,
+            )
+            for frame_id, verdict, reason, scores, elapsed_us in results
+        ],
+    )
+
+
+def _check_verdict(verdict):
+    if verdict not in VERDICTS:
+        raise ValueError(f"Unknown verdict {verdict!r}; expected one of {VERDICTS}")
+    return verdict
+
+
+def good_slots(conn, run_id, t_start, t_end, satellite, wavelengths=paths.WAVELENGTHS):
+    """Frames a run judged good, in a half-open time window.
+
+    This is the query that replaces ``merger_FITS.py``'s ``_f.fits$`` regex.
+    """
+    placeholders = ",".join("?" * len(wavelengths))
+    rows = conn.execute(
+        f"""
+        SELECT f.id, f.path, f.satellite, f.wavelength, f.t_start
+        FROM frame f
+        JOIN detection d ON d.frame_id = f.id AND d.run_id = ?
+        WHERE d.verdict = 'good'
+          AND f.satellite = ?
+          AND f.t_start >= ? AND f.t_start < ?
+          AND f.wavelength IN ({placeholders})
+        ORDER BY f.t_start, f.wavelength
+        """,
+        (run_id, satellite, t_start, t_end, *wavelengths),
+    ).fetchall()
+    return rows
+
+
+def unscanned_frames(conn, limit=None):
+    """Frames with no cached header yet."""
+    sql = """
+        SELECT f.id, f.path FROM frame f
+        LEFT JOIN header h ON h.frame_id = f.id
+        WHERE h.frame_id IS NULL
+        ORDER BY f.t_start
+    """
+    if limit is not None:
+        sql += f" LIMIT {int(limit)}"
+    return conn.execute(sql).fetchall()
+
+
+# --------------------------------------------------------------------------- headers
+
+
+_HEADER_INSERT = f"""
+INSERT INTO header (frame_id, {", ".join(HEADER_FIELDS)}, read_ok, read_error, scanned_at)
+VALUES (?{", ?" * len(HEADER_FIELDS)}, ?, ?, ?)
+ON CONFLICT (frame_id) DO UPDATE SET
+    {", ".join(f"{f} = excluded.{f}" for f in HEADER_FIELDS)},
+    read_ok    = excluded.read_ok,
+    read_error = excluded.read_error,
+    scanned_at = excluded.scanned_at
+"""
+
+
+def record_headers(conn, records):
+    """Write cached header rows.  `records` yields (frame_id, values_dict, error)."""
+    now = time.time()
+    conn.executemany(
+        _HEADER_INSERT,
+        [
+            (
+                frame_id,
+                *(values.get(field) for field in HEADER_FIELDS),
+                0 if error else 1,
+                error,
+                now,
+            )
+            for frame_id, values, error in records
+        ],
+    )
+
+
+# ---------------------------------------------------------------------- remote files
+
+
+def get_remote_mtime(conn, url):
+    row = conn.execute(
+        "SELECT remote_mtime FROM remote_file WHERE url = ?", (url,)
+    ).fetchone()
+    return row["remote_mtime"] if row else None
+
+
+def record_remote_files(conn, records):
+    """`records` yields (url, remote_mtime, remote_size, local_path, fetched_at)."""
+    conn.executemany(
+        """
+        INSERT INTO remote_file (url, remote_mtime, remote_size, local_path, fetched_at)
+        VALUES (?, ?, ?, ?, ?)
+        ON CONFLICT (url) DO UPDATE SET
+            remote_mtime = excluded.remote_mtime,
+            remote_size  = excluded.remote_size,
+            local_path   = excluded.local_path,
+            fetched_at   = excluded.fetched_at
+        """,
+        list(records),
+    )
+
+
+# ---------------------------------------------------------------- single-writer loop
+
+#: Sentinel pushed onto a writer queue to shut it down.
+STOP = None
+
+
+def writer_loop(db_path, work_queue, batch_size=512, flush_seconds=5.0):
+    """Drain (kind, payload) messages from a queue into the index.
+
+    Runs in its own process so worker processes never contend for the write lock.
+    Recognised kinds: 'detection', 'header', 'remote_file' -- each payload being the
+    row tuple that the corresponding record_* helper expects.
+    """
+    handlers = {
+        "detection": _flush_detections,
+        "header": record_headers,
+        "remote_file": record_remote_files,
+    }
+    conn = connect(db_path)
+    pending = {kind: [] for kind in handlers}
+    last_flush = time.monotonic()
+
+    def flush():
+        nonlocal last_flush
+        for kind, rows in pending.items():
+            if rows:
+                handlers[kind](conn, rows)
+                rows.clear()
+        conn.commit()
+        last_flush = time.monotonic()
+
+    try:
+        while True:
+            try:
+                message = work_queue.get(timeout=1.0)
+            except queue.Empty:
+                if time.monotonic() - last_flush > flush_seconds:
+                    flush()
+                continue
+            if message is STOP:
+                break
+            kind, payload = message
+            if kind not in pending:
+                raise ValueError(f"Unknown writer message kind: {kind!r}")
+            pending[kind].append(payload)
+            if sum(len(v) for v in pending.values()) >= batch_size:
+                flush()
+        flush()
+    finally:
+        conn.commit()
+        conn.close()
+
+
+def _flush_detections(conn, rows):
+    """Adapter: writer payloads carry run_id per row, record_detections does not."""
+    by_run = {}
+    for run_id, *rest in rows:
+        by_run.setdefault(run_id, []).append(tuple(rest))
+    for run_id, results in by_run.items():
+        record_detections(conn, run_id, results)
diff --git a/suvi/detectors.py b/suvi/detectors.py
new file mode 100644
index 0000000..132dc1c
--- /dev/null
+++ b/suvi/detectors.py
@@ -0,0 +1,742 @@
+"""Bad-frame detectors.
+
+Every detector is a pure function: data in, a :class:`Verdict` out.  Nothing here
+renames a file, writes a plot, or touches the database -- that is the driver's job.
+This is what lets the same code run in production (``filter_FITS.py``) and under the
+test bench, and lets several detectors judge the same frame independently.
+
+Two shapes of detector:
+
+* **Frame-level** (:func:`header_v1`, :func:`geometry_v1`) judge one frame alone.
+* **Series-level** (:func:`temporal_v1`, :func:`crosssat_v1`) judge a frame in the
+  context of its neighbours in time, or of the other satellite at the same instant.
+  They work from :class:`FrameFeatures` -- cached header values plus a small
+  thumbnail -- rather than full 1280x1280 arrays, which keeps a whole day of context
+  in memory at once.
+
+Every detector reports continuous ``scores`` alongside its verdict.  The driver
+stores those, so re-tuning a threshold later is a database query rather than another
+pass over the archive.
+"""
+
+from dataclasses import dataclass, field
+
+import cv2 as cv
+import numpy as np
+
+# --------------------------------------------------------------------------- types
+
+
+@dataclass(frozen=True)
+class Verdict:
+    """One detector's judgement of one frame."""
+
+    verdict: str  # 'good' | 'bad' | 'unknown'
+    reason: str | None = None
+    scores: dict = field(default_factory=dict)
+
+
+GOOD = "good"
+BAD = "bad"
+UNKNOWN = "unknown"
+
+
+@dataclass
+class FrameFeatures:
+    """The cheap summary of a frame that series-level detectors work from."""
+
+    slot: tuple  # (satellite, wavelength, t_start)
+    header: dict = field(default_factory=dict)
+    #: Read error from fitsio, if the frame could not be parsed at all.
+    error: str | None = None
+    #: Small float32 image (see THUMBNAIL_SIZE), or None if not loaded.
+    thumbnail: np.ndarray | None = None
+
+    @property
+    def t_start(self):
+        return self.slot[2]
+
+    @property
+    def wavelength(self):
+        return self.slot[1]
+
+
+#: Series detectors compare thumbnails, not full frames.  128px preserves the disc,
+#: active regions and gross structure while making a day of context cheap to hold.
+THUMBNAIL_SIZE = 128
+
+
+def thumbnail(image, size=THUMBNAIL_SIZE):
+    """Downsample a frame for structural comparison.  NaNs become zero."""
+    clean = np.nan_to_num(np.asarray(image, dtype=np.float32), nan=0.0, posinf=0.0, neginf=0.0)
+    return cv.resize(clean, (size, size), interpolation=cv.INTER_AREA)
+
+
+# ------------------------------------------------------------------ header_v1
+
+#: Plausible radiance range of a healthy frame, per passband, in W m-2 sr-1.
+#:
+#: Deliberately wide -- roughly a factor of five outside the observed annual range of
+#: good frames.  Sampled across 24 days of 2024 on both satellites, the *rejected*
+#: frames' IMG_MEAN distribution sits almost entirely inside the good one (171A: good
+#: 0.288-0.452, rejected median 0.352), so a tight bound here would cost enormous
+#: numbers of false positives while catching little.  What this rule is actually for
+#: is gross dropout and blowout -- eclipse frames run 1e-4, three orders of magnitude
+#: below the floor -- and it is priced accordingly.
+HEADER_MEAN_BOUNDS = {
+    94: (0.004, 0.41),
+    131: (0.005, 0.39),
+    171: (0.057, 2.3),
+    195: (0.15, 5.4),
+    284: (0.13, 7.0),
+    304: (0.29, 20.0),
+}
+
+#: Solar diameter in pixels; varies ~3% over the year with Earth-Sun distance.
+DIAM_SUN_RANGE = (740.0, 800.0)
+#: How far the recorded sun centre may sit from the image centre, in pixels.
+MAX_CRPIX_OFFSET = 8.0
+
+
+def header_v1(features, mean_bounds=None, diam_range=DIAM_SUN_RANGE,
+              max_crpix_offset=MAX_CRPIX_OFFSET):
+    """Judge a frame from its header alone -- no pixel decompression.
+
+    The instrument already reports most of what matters: ``ECLIPSE`` marks frames
+    taken through Earth's shadow, ``EMPTY`` marks frames built from no source
+    imagery, and ``IMG_MEAN``/``IMG_SDEV`` summarise the radiance.  On sampled
+    archive days every frame the pixel filter rejected also carried ``ECLIPSE=2``,
+    at roughly a fifth of the cost of decompressing the image.
+
+    ``DEGRADED`` is recorded as a score but is deliberately *not* a rejection rule.
+    It is set for reasons unrelated to a frame's usability: across sampled days the
+    195A band carried ``DEGRADED=T`` on 40/40 good frames on 2024-01-20 and 0/40 on
+    2024-07-04, on both satellites.  Rejecting on it would discard entire months of
+    that band.  The bench can re-weight it from the stored score if that turns out
+    to be worth doing.
+    """
+    mean_bounds = mean_bounds or HEADER_MEAN_BOUNDS
+    header = features.header
+    scores = {}
+
+    if features.error:
+        return Verdict(BAD, f"unreadable: {features.error}", {"read_ok": 0.0})
+    if not header:
+        return Verdict(UNKNOWN, "no header cached", scores)
+
+    for field_name in ("img_mean", "img_sdev", "diam_sun", "eclipse", "degraded"):
+        if field_name in header:
+            scores[field_name] = float(header[field_name])
+
+    if header.get("empty"):
+        return Verdict(BAD, "EMPTY flag set", scores)
+    eclipse = header.get("eclipse")
+    if eclipse:
+        return Verdict(BAD, f"ECLIPSE flag set ({int(eclipse)})", scores)
+
+    # A frame built from no source images carries no information regardless of what
+    # the radiance statistics happen to say.
+    if header.get("num_imgs") is not None and header["num_imgs"] < 1:
+        scores["num_imgs"] = float(header["num_imgs"])
+        return Verdict(BAD, "no source images", scores)
+
+    # The band the file claims must match the band its name puts it in, or the
+    # archive has a misfiled frame and every downstream threshold is wrong.
+    declared = header.get("wavelnth")
+    if declared is not None and int(declared) != features.wavelength:
+        scores["wavelnth"] = float(declared)
+        return Verdict(BAD, f"wavelength {int(declared)} != {features.wavelength}", scores)
+
+    mean = header.get("img_mean")
+    if mean is not None:
+        low, high = mean_bounds.get(features.wavelength, (0.0, np.inf))
+        if mean < low:
+            return Verdict(BAD, f"IMG_MEAN {mean:.3g} below {low:g}", scores)
+        if mean > high:
+            return Verdict(BAD, f"IMG_MEAN {mean:.3g} above {high:g}", scores)
+
+    sdev = header.get("img_sdev")
+    if sdev is not None and sdev <= 0.0:
+        return Verdict(BAD, "zero variance", scores)
+
+    diameter = header.get("diam_sun")
+    if diameter is not None and not (diam_range[0] <= diameter <= diam_range[1]):
+        return Verdict(BAD, f"DIAM_SUN {diameter:.1f} outside {diam_range}", scores)
+
+    crpix1, crpix2 = header.get("crpix1"), header.get("crpix2")
+    if crpix1 is not None and crpix2 is not None:
+        offset = max(abs(crpix1 - 640.5), abs(crpix2 - 640.5))
+        scores["crpix_offset"] = float(offset)
+        if offset > max_crpix_offset:
+            return Verdict(BAD, f"sun centre offset {offset:.1f}px", scores)
+
+    return Verdict(GOOD, None, scores)
+
+
+# ---------------------------------------------------------------- geometry_v1
+
+#: Per-band radiance ceiling used to normalise the image before shape analysis.
+#: Index order matches paths.WAVELENGTHS.
+GEOMETRY_THRESHOLDS = {94: 0.050, 131: 0.10, 171: 1.00, 195: 1.40, 284: 1.0, 304: 2.50}
+
+EXPECTED_DIMS = 1280
+HALF_DIMS = EXPECTED_DIMS // 2
+VALID_RADII = (383, 394)
+AVG_RADIUS = (VALID_RADII[0] + VALID_RADII[1]) // 2
+MAX_RADIUS_ERROR = 80
+MAX_CENTER_SKEW = 7
+RATIO_ABOVE_THRESH_MAX = 0.4
+RATIO_ABOVE_THRESH_MIN = 0.07
+EDGE_THRESH = 0.98
+MAX_GOF = 0.2
+
+_ideal_axis_cache = {}
+
+
+def ideal_disc_axis():
+    """Column-mean profile of a perfect solar disc, used as the shape reference."""
+    if "axis" not in _ideal_axis_cache:
+        disc = np.zeros((HALF_DIMS, HALF_DIMS))
+        cv.circle(disc, (HALF_DIMS // 2, HALF_DIMS // 2), AVG_RADIUS // 2, 1, -1)
+        _ideal_axis_cache["axis"] = np.average(disc, 0)
+    return _ideal_axis_cache["axis"]
+
+
+def geometry_v1(image, wavelength):
+    """The pre-existing pixel-geometry filter, preserved as the baseline.
+
+    Normalises against a per-band radiance ceiling, then checks the fraction of
+    saturated pixels, the intensity-weighted centroid, the radius implied by the
+    98th-percentile cumulative edges, and the fit against an ideal disc profile.
+
+    Deliberately kept behaviourally identical to the original so bench numbers
+    describe what the pipeline actually did, with two known weaknesses left intact
+    for the bench to quantify:
+
+    * the centre check is one-sided -- ``HALF_DIMS//2 - centre > skew`` catches a
+      disc displaced up/left but not one displaced down/right;
+    * non-finite pixels propagate as NaN through every comparison, and ``NaN > x``
+      is False, so an all-NaN frame passes every check.
+
+    The one deliberate change: the original raised on an unexpected image size and
+    left the file unlabelled.  Here that is a ``bad`` verdict, because "no verdict"
+    is not a usable baseline to score against.
+    """
+    scores = {}
+    if image is None:
+        return Verdict(BAD, "no image data", scores)
+    if image.shape[0] != EXPECTED_DIMS or image.shape[1] != EXPECTED_DIMS:
+        return Verdict(BAD, f"unexpected dimensions {image.shape}", scores)
+
+    threshold = GEOMETRY_THRESHOLDS.get(wavelength)
+    if threshold is None:
+        return Verdict(UNKNOWN, f"no threshold for band {wavelength}", scores)
+
+    data = cv.resize(
+        np.asarray(image, dtype=np.float32),
+        dsize=(HALF_DIMS, HALF_DIMS),
+        interpolation=cv.INTER_LINEAR,
+    )
+    above = data > threshold
+    normalised = np.copy(data)
+    normalised[above] = threshold
+    normalised /= threshold
+
+    ratio = np.count_nonzero(above) / data.shape[0] / data.shape[1]
+    scores["ratio_above_thresh"] = float(ratio)
+    if ratio > RATIO_ABOVE_THRESH_MAX:
+        return Verdict(BAD, f"ratio_above_thresh {ratio:.2f} too high", scores)
+    if ratio < RATIO_ABOVE_THRESH_MIN:
+        return Verdict(BAD, f"ratio_above_thresh {ratio:.2f} too low", scores)
+
+    xavg = np.average(normalised, 0)
+    yavg = np.average(normalised, 1)
+    axis = list(range(HALF_DIMS))
+
+    centre_x = np.average(axis, 0, xavg)
+    centre_y = np.average(axis, 0, yavg)
+    scores["centre_x"] = float(centre_x)
+    scores["centre_y"] = float(centre_y)
+    good_centre = not (
+        (HALF_DIMS // 2 - centre_x > MAX_CENTER_SKEW)
+        or (HALF_DIMS // 2 - centre_y > MAX_CENTER_SKEW)
+    )
+
+    high_x = np.argmax(np.cumsum(xavg) > (np.sum(xavg) * EDGE_THRESH))
+    low_x = len(xavg) - np.argmax(np.cumsum(np.flip(xavg)) > (np.sum(xavg) * EDGE_THRESH))
+    high_y = np.argmax(np.cumsum(yavg) > (np.sum(yavg) * EDGE_THRESH))
+    low_y = len(yavg) - np.argmax(np.cumsum(np.flip(yavg)) > (np.sum(yavg) * EDGE_THRESH))
+    # Not halved: the image is already downsampled by two in each dimension.
+    radius = ((high_x - low_x) + (high_y - low_y)) / 2.0
+    scores["radius"] = float(radius)
+    good_radius = abs(radius - AVG_RADIUS) <= MAX_RADIUS_ERROR
+
+    reference = ideal_disc_axis()
+    gof_x = np.sum(np.abs(xavg - reference)) / HALF_DIMS
+    gof_y = np.sum(np.abs(yavg - reference)) / HALF_DIMS
+    scores["gof_x"] = float(gof_x)
+    scores["gof_y"] = float(gof_y)
+    good_fit = not (gof_x > MAX_GOF or gof_y > MAX_GOF)
+
+    if good_centre and good_radius and good_fit:
+        return Verdict(GOOD, None, scores)
+    failed = [
+        name
+        for name, ok in (("centre", good_centre), ("radius", good_radius), ("fit", good_fit))
+        if not ok
+    ]
+    return Verdict(BAD, "failed " + "+".join(failed), scores)
+
+
+# -------------------------------------------------------------------- disc_v1
+
+#: Angular samples in the polar resampling.  The measurements are all averages over
+#: this axis, so more angles cost little and reduce noise.
+DISC_ANGLES = 720
+#: Working resolution.  Halving 1280 keeps the limb several pixels wide while making
+#: the polar transform cheap.
+DISC_SIZE = 640
+
+#: Radial bands, in units of the expected solar radius, used to characterise the
+#: profile.  The on-disc band avoids both the centre (where limb darkening and
+#: filaments live) and the limb itself; the off-limb band sits outside the corona's
+#: steepest falloff but inside the frame -- 1.45R of a ~193px radius is 280px, within
+#: the 320px half-width.
+DISC_ON_BAND = (0.30, 0.70)
+DISC_OFF_BAND = (1.25, 1.45)
+#: Where the limb is allowed to be found, again in units of expected radius.
+DISC_SEARCH_BAND = (0.75, 1.25)
+
+
+def disc_profile(image, expected_radius, size=DISC_SIZE, angles=DISC_ANGLES):
+    """Measure the solar disc from its azimuthally averaged radial profile.
+
+    Returns a dict of continuous measurements, or with None values where the frame
+    is too degenerate to measure.  Separated from the verdict logic so that
+    ``filter_FITS.py calibrate`` can gather the same numbers over a sample.
+
+    Averaging over angle is the entire point.  An active region is localised in
+    angle, so it barely shifts the averaged profile; the existing ``geometry_v1``
+    averages along image rows and columns instead, which a bright region shifts
+    directly -- the cause of its 36.9% rejection rate.
+
+    `expected_radius` is in pixels *at the working resolution*, i.e. DIAM_SUN / 4.
+    """
+    empty = {"limb_contrast": None, "radius_ratio": None, "limb_width": None}
+    if image is None or image.ndim != 2 or min(image.shape) < 16:
+        return empty
+    if not expected_radius or not np.isfinite(expected_radius) or expected_radius <= 0:
+        return empty
+
+    working = cv.resize(
+        np.nan_to_num(np.asarray(image, dtype=np.float32), nan=0.0, posinf=0.0, neginf=0.0),
+        (size, size),
+        interpolation=cv.INTER_AREA,
+    )
+    # Radiance spans orders of magnitude; log compresses a flare so it cannot
+    # dominate the profile the way it dominates a linear mean.
+    working = np.log1p(np.clip(working, 0.0, None))
+
+    max_radius = size / 2.0
+    polar = cv.warpPolar(
+        working,
+        (int(max_radius), angles),
+        (size / 2.0, size / 2.0),
+        max_radius,
+        cv.WARP_POLAR_LINEAR,
+    )
+    profile = polar.mean(axis=0)
+    radii = np.arange(profile.size, dtype=np.float64)
+    scale = expected_radius
+
+    def band(low, high):
+        mask = (radii > low * scale) & (radii < high * scale)
+        return profile[mask] if mask.any() else np.array([])
+
+    on_values, off_values = band(*DISC_ON_BAND), band(*DISC_OFF_BAND)
+    if on_values.size < 3 or off_values.size < 3:
+        return empty
+    on_disc, off_limb = float(np.median(on_values)), float(np.median(off_values))
+    if not np.isfinite(on_disc) or not np.isfinite(off_limb):
+        return empty
+    if on_disc <= 0:
+        # No signal at all where the disc should be.  This is a conclusion, not a
+        # failure to measure: report zero contrast so the caller rejects the frame
+        # rather than abstaining on it.
+        return {"limb_contrast": 0.0, "radius_ratio": None, "limb_width": None}
+
+    contrast = (on_disc - off_limb) / on_disc
+    measured = {"limb_contrast": float(contrast), "radius_ratio": None, "limb_width": None}
+    if on_disc <= off_limb:
+        # No radial falloff at all: there is no disc here to measure the size of.
+        return measured
+
+    # The limb is the steepest descent of the smoothed profile.  Taken on the
+    # *averaged* profile rather than per angle: fitting each angle separately failed
+    # outright on frames where too few angles yielded a usable edge.
+    smoothed = cv.GaussianBlur(profile.astype(np.float32).reshape(1, -1), (9, 1), 0).ravel()
+    derivative = np.gradient(smoothed.astype(np.float64))
+    low, high = DISC_SEARCH_BAND
+    window = (radii >= low * scale) & (radii <= high * scale)
+    if window.sum() < 5:
+        return measured
+    indices = np.flatnonzero(window)
+    local = derivative[indices]
+    trough = int(indices[np.argmin(local)])
+    depth = derivative[trough]
+    if not np.isfinite(depth) or depth >= 0:
+        return measured  # no descending edge: not a disc
+
+    measured["radius_ratio"] = float(trough / scale)
+
+    # Width of the descent at half its depth.  A disc displaced by d smears the
+    # averaged limb across roughly 2d, so this is what makes the measurement
+    # sensitive to decentring without ever having to locate a centre.
+    half = depth / 2.0
+    left = trough
+    while left > 0 and derivative[left - 1] <= half:
+        left -= 1
+    right = trough
+    last = derivative.size - 1
+    while right < last and derivative[right + 1] <= half:
+        right += 1
+    measured["limb_width"] = float((right - left + 1) / scale)
+    return measured
+
+
+#: Per-band acceptance ranges for the disc_v1 measurements.
+#:
+#: Generated by ``filter_FITS.py calibrate``; regenerate and paste the output here
+#: rather than hand-editing.  Derived from 400 frames per band sampled evenly across
+#: the archive's whole time range, with 0/400 sample failures in every band.
+#:
+#: The bounds sit well outside the observed spread of good frames, because the
+#: false-positive budget for this detector is <0.1%: the method it replaces was
+#: discarding 36.9% of perfectly good frames, which is the entire reason it exists.
+#: Only the diagnostic side of each measurement is bounded -- see CALIBRATION_SIDES
+#: in filter_FITS.py.
+#:
+#: Note what the wide contrast floors mean in practice.  Good frames in most bands
+#: reach as low as 0.11-0.22 contrast, so a floor tight enough to catch a partially
+#: degraded frame would reject real data.  At this budget limb_contrast therefore
+#: catches total signal loss (all-zero, NaN, uniform, which measure exactly 0.0) and
+#: little else; size and shape faults are caught by the other two measurements.
+#: 171A is the exception, where good frames never drop below 0.68.
+#:
+#: A measurement whose calibrated bounds cannot achieve the budget is set to None
+#: here, which records it as a score without letting it fail a frame.
+DISC_BOUNDS = {
+    94: {
+        "limb_contrast": (0.02, 1.0),
+        "radius_ratio": (0.9631, 1.1176),
+        "limb_width": (0.0, 0.1217),
+    },
+    131: {
+        "limb_contrast": (0.02, 1.0),
+        "radius_ratio": (0.9578, 1.0854),
+        "limb_width": (0.0, 0.1011),
+    },
+    171: {
+        "limb_contrast": (0.3183, 1.0),
+        "radius_ratio": (0.9616, 1.1062),
+        "limb_width": (0.0, 0.1375),
+    },
+    195: {
+        "limb_contrast": (0.02, 1.0),
+        "radius_ratio": (0.9676, 1.1167),
+        "limb_width": (0.0, 0.1704),
+    },
+    284: {
+        "limb_contrast": (0.02, 1.0),
+        "radius_ratio": (0.9548, 1.1489),
+        "limb_width": (0.0, 0.3177),
+    },
+    304: {
+        "limb_contrast": (0.02, 1.0),
+        "radius_ratio": (0.9548, 1.0813),
+        "limb_width": (0.0, 0.1016),
+    },
+}
+
+
+def disc_v1(image, wavelength, header=None, bounds=None):
+    """Verify that the frame holds a correctly sized, centred, sharp solar disc.
+
+    Replaces ``geometry_v1``'s intensity-weighted centroid, which a large active
+    region drags off centre -- rejecting entire days of good data during exactly the
+    solar activity most worth watching.
+
+    Everything measured here is an average over angle, so where the bright regions
+    sit on the disc does not move it.  What it deliberately cannot see is rotation:
+    ``rotate`` and ``yaw_flip`` leave every azimuthally averaged quantity unchanged,
+    and one frame carries no absolute rotation reference.  Those belong to
+    ``temporal_v1`` and ``crosssat_v1``.
+
+    The expected radius comes from the frame's own ``DIAM_SUN``, which varies by
+    3.3% over the year with the Earth-Sun distance.
+    """
+    bounds = bounds or DISC_BOUNDS
+    if image is None:
+        return Verdict(BAD, "no image data", {})
+
+    diameter = (header or {}).get("diam_sun")
+    if not diameter:
+        return Verdict(UNKNOWN, "no DIAM_SUN in header", {})
+
+    # DIAM_SUN is a full diameter at full resolution; halve for radius, halve again
+    # for the working downsample.
+    expected_radius = float(diameter) / 4.0
+    measured = disc_profile(image, expected_radius)
+    scores = {k: v for k, v in measured.items() if v is not None}
+
+    if measured["limb_contrast"] is None:
+        return Verdict(UNKNOWN, "radial profile not measurable", scores)
+
+    limits = bounds.get(wavelength)
+    if limits is None:
+        return Verdict(UNKNOWN, f"no disc bounds for band {wavelength}", scores)
+
+    failed = []
+    for name, limit in limits.items():
+        if limit is None:
+            continue  # recorded as a score, not used to judge
+        value = measured.get(name)
+        if value is None:
+            failed.append(f"{name} unmeasurable")
+        elif not (limit[0] <= value <= limit[1]):
+            failed.append(f"{name} {value:.3f} outside [{limit[0]:.3f}, {limit[1]:.3f}]")
+
+    if failed:
+        return Verdict(BAD, "; ".join(failed), scores)
+    return Verdict(GOOD, None, scores)
+
+
+# ---------------------------------------------------------------- temporal_v1
+
+#: Frames either side used to build the local reference.  At a 4-minute cadence,
+#: +/-6 spans about 50 minutes -- long enough to be robust, short enough that real
+#: solar evolution does not dominate.
+TEMPORAL_WINDOW = 6
+#: Robust z-score above which a frame's brightness is judged anomalous.
+TEMPORAL_BRIGHTNESS_Z = 8.0
+#: Structural difference from neighbours, relative to the neighbours' own churn.
+TEMPORAL_STRUCTURE_RATIO = 6.0
+#: Below this relative difference two consecutive frames are considered identical.
+FROZEN_TOLERANCE = 1e-6
+
+
+def _robust_z(values, index, window):
+    """Median-absolute-deviation z-score of values[index] against its neighbours."""
+    low = max(0, index - window)
+    high = min(len(values), index + window + 1)
+    neighbours = np.array(
+        [values[i] for i in range(low, high) if i != index and np.isfinite(values[i])]
+    )
+    if neighbours.size < 3:
+        return None
+    median = np.median(neighbours)
+    mad = np.median(np.abs(neighbours - median))
+    if mad <= 0:
+        # A perfectly steady neighbourhood: fall back to the spread, and treat an
+        # exactly-constant one as uninformative rather than infinitely sensitive.
+        spread = neighbours.std()
+        if spread <= 0:
+            return 0.0 if values[index] == median else np.inf
+        return abs(values[index] - median) / spread
+    return abs(values[index] - median) / (1.4826 * mad)
+
+
+def temporal_v1(series, window=TEMPORAL_WINDOW, brightness_z=TEMPORAL_BRIGHTNESS_Z,
+                structure_ratio=TEMPORAL_STRUCTURE_RATIO,
+                frozen_tolerance=FROZEN_TOLERANCE):
+    """Judge each frame against its neighbours in the same band and satellite.
+
+    Catches what single-frame checks cannot: a frame that is individually plausible
+    but inconsistent with the minutes either side of it -- a frozen duplicate, a
+    brightness step, a substituted frame from another time.
+
+    `series` must be ordered by time and come from one (satellite, wavelength)
+    stream; gaps are fine, they simply widen the neighbourhood in wall-clock terms.
+    Returns one Verdict per input frame.
+    """
+    count = len(series)
+    means = [
+        f.header.get("img_mean", np.nan) if not f.error else np.nan for f in series
+    ]
+    verdicts = []
+
+    # Structural churn between consecutive thumbnails, when they are available.
+    diffs = [np.nan] * count
+    for i in range(1, count):
+        a, b = series[i - 1].thumbnail, series[i].thumbnail
+        if a is not None and b is not None and a.shape == b.shape:
+            scale = float(np.abs(a).mean() + np.abs(b).mean()) / 2.0
+            diffs[i] = float(np.abs(a - b).mean()) / scale if scale > 0 else np.nan
+
+    for i, frame in enumerate(series):
+        scores = {}
+        if frame.error:
+            verdicts.append(Verdict(BAD, f"unreadable: {frame.error}", {"read_ok": 0.0}))
+            continue
+
+        z = _robust_z(means, i, window)
+        if z is not None:
+            scores["brightness_z"] = float(z)
+
+        # A frame identical to its predecessor means the feed stalled.
+        if i > 0 and np.isfinite(diffs[i]) and diffs[i] < frozen_tolerance:
+            scores["frame_diff"] = float(diffs[i])
+            verdicts.append(Verdict(BAD, "identical to previous frame", scores))
+            continue
+
+        neighbour_diffs = np.array(
+            [
+                diffs[j]
+                for j in range(max(1, i - window), min(count, i + window + 1))
+                if j != i and np.isfinite(diffs[j])
+            ]
+        )
+        if np.isfinite(diffs[i]) and neighbour_diffs.size >= 3:
+            typical = float(np.median(neighbour_diffs))
+            scores["frame_diff"] = float(diffs[i])
+            scores["frame_diff_ratio"] = float(diffs[i] / typical) if typical > 0 else 0.0
+            if typical > 0 and diffs[i] / typical > structure_ratio:
+                verdicts.append(
+                    Verdict(BAD, f"structural jump {diffs[i] / typical:.1f}x typical", scores)
+                )
+                continue
+
+        if z is not None and z > brightness_z:
+            verdicts.append(Verdict(BAD, f"brightness z={z:.1f}", scores))
+            continue
+
+        if z is None and not np.isfinite(diffs[i]):
+            verdicts.append(Verdict(UNKNOWN, "insufficient context", scores))
+            continue
+
+        verdicts.append(Verdict(GOOD, None, scores))
+
+    return verdicts
+
+
+# ---------------------------------------------------------------- crosssat_v1
+
+#: Relative disagreement between satellites above which one of them is wrong.
+CROSSSAT_MAX_DIFF = 0.35
+#: Alignment shift beyond which the two views cannot be meaningfully compared.
+#: Geostationary parallax is under ~7px at 2.5 arcsec/px; more means a pointing fault.
+CROSSSAT_MAX_SHIFT = 12.0
+#: Plausible range for the calibration gain between the two flight models.  Wide
+#: enough to absorb genuine instrument differences, narrow enough that a blackout or
+#: a saturation blowout cannot be rescaled into agreement.
+CROSSSAT_GAIN_RANGE = (0.2, 5.0)
+
+
+def _gain_match(source, reference):
+    """Least-squares gain and offset putting `source` on `reference`'s scale.
+
+    The two instruments are different flight models with different responses, so a
+    raw difference conflates calibration with genuine disagreement.
+
+    Returns (matched, gain, offset).  The gain is returned rather than hidden
+    because matching is otherwise *too* effective: a frame uniformly scaled by 1e-4
+    fits perfectly after rescaling, so a detector that only looked at the residual
+    would call a total blackout a match.  The size of the correction is itself
+    evidence.
+    """
+    x = source.ravel().astype(np.float64)
+    y = reference.ravel().astype(np.float64)
+    finite = np.isfinite(x) & np.isfinite(y)
+    if finite.sum() < 16:
+        return source, 1.0, 0.0
+    x, y = x[finite], y[finite]
+    variance = float(((x - x.mean()) ** 2).sum())
+    if variance <= 0:
+        return source, 1.0, 0.0
+    gain = float(((x - x.mean()) * (y - y.mean())).sum() / variance)
+    offset = float(y.mean() - gain * x.mean())
+    return source * gain + offset, gain, offset
+
+
+def align_shift(a, b):
+    """Sub-pixel translation between two thumbnails, via phase correlation."""
+    if a is None or b is None or a.shape != b.shape:
+        return None
+    window = cv.createHanningWindow((a.shape[1], a.shape[0]), cv.CV_64F)
+    (dx, dy), _ = cv.phaseCorrelate(
+        np.nan_to_num(a.astype(np.float64)), np.nan_to_num(b.astype(np.float64)), window
+    )
+    return float(np.hypot(dx, dy))
+
+
+def crosssat_v1(features_a, features_b, temporal_a=None, temporal_b=None,
+                max_diff=CROSSSAT_MAX_DIFF, max_shift=CROSSSAT_MAX_SHIFT,
+                gain_range=CROSSSAT_GAIN_RANGE):
+    """Compare the two satellites' view of the same instant.
+
+    GOES-16 and GOES-18 observe the same Sun from geostationary orbit, so at 1 AU
+    their views differ only by a few pixels of parallax and by instrument
+    calibration.  Sustained disagreement therefore means one of them is wrong.
+
+    Deciding *which* one needs outside information: `temporal_a`/`temporal_b` are the
+    corresponding :func:`temporal_v1` verdicts, and whichever frame also disagrees
+    with its own history is blamed.  With no tiebreak available both are reported
+    ``unknown`` rather than guessing -- a wrong attribution would discard a good
+    frame and keep a bad one.
+
+    Returns (verdict_a, verdict_b).
+    """
+    if features_a is None or features_b is None:
+        return Verdict(UNKNOWN, "no counterpart", {}), Verdict(UNKNOWN, "no counterpart", {})
+    if features_a.error or features_b.error:
+        # Frame-level errors are not this detector's job; defer rather than double-count.
+        return Verdict(UNKNOWN, "counterpart unreadable", {}), Verdict(
+            UNKNOWN, "counterpart unreadable", {}
+        )
+
+    a, b = features_a.thumbnail, features_b.thumbnail
+    if a is None or b is None or a.shape != b.shape:
+        return Verdict(UNKNOWN, "no comparable thumbnail", {}), Verdict(
+            UNKNOWN, "no comparable thumbnail", {}
+        )
+
+    scores = {}
+    shift = align_shift(a, b)
+    if shift is not None:
+        scores["align_shift"] = shift
+
+    matched, gain, offset = _gain_match(b, a)
+    scale = float(np.abs(a).mean() + np.abs(matched).mean()) / 2.0
+    difference = float(np.abs(a - matched).mean()) / scale if scale > 0 else np.inf
+    scores["cross_diff"] = difference
+    scores["cross_gain"] = gain
+    scores["cross_offset"] = offset
+
+    # A correction this large means the two frames are not on comparable scales at
+    # all, whatever the residual says once it has been applied.
+    gain_ok = gain_range[0] <= gain <= gain_range[1]
+    agree = difference <= max_diff and gain_ok and (shift is None or shift <= max_shift)
+    if agree:
+        return Verdict(GOOD, None, scores), Verdict(GOOD, None, scores)
+
+    reason = f"cross-satellite disagreement {difference:.2f}"
+    if not gain_ok:
+        reason = f"cross-satellite gain {gain:.3g} outside {gain_range}"
+    elif shift is not None and shift > max_shift:
+        reason = f"cross-satellite misalignment {shift:.1f}px"
+
+    a_suspect = temporal_a is not None and temporal_a.verdict == BAD
+    b_suspect = temporal_b is not None and temporal_b.verdict == BAD
+    if a_suspect and not b_suspect:
+        return Verdict(BAD, reason, scores), Verdict(GOOD, None, scores)
+    if b_suspect and not a_suspect:
+        return Verdict(GOOD, None, scores), Verdict(BAD, reason, scores)
+    return Verdict(UNKNOWN, reason + " (source unclear)", scores), Verdict(
+        UNKNOWN, reason + " (source unclear)", scores
+    )
+
+
+#: Detectors the drivers and bench expose by name.
+FRAME_DETECTORS = {"header_v1": header_v1, "geometry_v1": geometry_v1, "disc_v1": disc_v1}
+SERIES_DETECTORS = {"temporal_v1": temporal_v1, "crosssat_v1": crosssat_v1}
+ALL_DETECTORS = tuple(FRAME_DETECTORS) + tuple(SERIES_DETECTORS)
diff --git a/suvi/fillers.py b/suvi/fillers.py
new file mode 100644
index 0000000..59dd042
--- /dev/null
+++ b/suvi/fillers.py
@@ -0,0 +1,349 @@
+"""Methods for reconstructing a missing or rejected frame.
+
+Every filler takes the same :class:`FillContext` and returns a replacement array, so
+the bench can swap them without knowing which one it is holding.  All are pure: they
+read the context and return an array, nothing else.
+
+The methods span a deliberate range of physical sophistication, from "repeat the last
+good frame" (what the pipeline does today) to a differential-rotation warp that models
+how the Sun actually moves.  The bench exists to say which of them is worth the cost
+at which gap length.
+"""
+
+from dataclasses import dataclass, field
+
+import cv2 as cv
+import numpy as np
+
+#: Nominal solar radius in metres (IAU 2015).
+R_SUN = 6.957e8
+#: Snodgrass (1983) sidereal differential rotation, degrees per day, by latitude.
+SNODGRASS_A = 14.713
+SNODGRASS_B = -2.396
+SNODGRASS_C = -1.787
+#: Earth's mean orbital motion, subtracted to get the rotation an Earth-orbiting
+#: observer actually sees.
+EARTH_ORBIT_DEG_PER_DAY = 0.9856
+SECONDS_PER_DAY = 86400.0
+
+
+@dataclass
+class FillContext:
+    """Everything a filler may draw on to reconstruct one frame."""
+
+    #: Nearest good frame before the gap, and how many seconds back it sits.
+    before: np.ndarray | None = None
+    dt_before: float = 0.0
+    #: Nearest good frame after the gap, and how many seconds forward.
+    after: np.ndarray | None = None
+    dt_after: float = 0.0
+    #: The other satellite's view of this same instant, if it has one.
+    counterpart: np.ndarray | None = None
+    #: Header of the frame being reconstructed, for the WCS a rotation warp needs.
+    header: dict = field(default_factory=dict)
+
+    @property
+    def alpha(self):
+        """Position within the gap: 0 at `before`, 1 at `after`."""
+        span = self.dt_before + self.dt_after
+        if span <= 0:
+            return 0.0
+        return self.dt_before / span
+
+    @property
+    def gap_frames(self):
+        """Gap width in 4-minute slots, for reporting quality against gap length."""
+        return int(round((self.dt_before + self.dt_after) / 240.0))
+
+
+def _finite(image):
+    return np.nan_to_num(np.asarray(image, dtype=np.float32), nan=0.0, posinf=0.0, neginf=0.0)
+
+
+# ---------------------------------------------------------------- simple baselines
+
+
+def hold_last(context):
+    """Repeat the last good frame.
+
+    What ``merger_FITS.py`` does today (up to ``max_time_gap`` slots).  Cheap, never
+    invents structure, but freezes the Sun and then jumps -- the visible stutter in
+    the current videos.  The baseline every other method must beat.
+    """
+    if context.before is not None:
+        return _finite(context.before)
+    if context.after is not None:
+        return _finite(context.after)
+    return None
+
+
+def linear_blend(context):
+    """Cross-fade between the frames bracketing the gap.
+
+    Removes the jump that ``hold_last`` leaves, at the cost of ghosting: moving
+    features appear twice, faintly, rather than moving.
+    """
+    if context.before is None:
+        return hold_last(context)
+    if context.after is None or context.before.shape != context.after.shape:
+        # Frames of differing size cannot be mixed; the nearer one is the best
+        # available answer.  This is also the fallback the other fillers unwind to.
+        return _finite(context.before)
+    alpha = context.alpha
+    return ((1.0 - alpha) * _finite(context.before) + alpha * _finite(context.after)).astype(
+        np.float32
+    )
+
+
+# ------------------------------------------------------------------- optical flow
+
+
+def _for_flow(image):
+    """Compress radiance into a range optical flow can work with.
+
+    Radiance is heavy-tailed -- a flare can be 1000x the quiet corona -- so raw
+    values make flow chase the brightest pixels only.  log1p plus a percentile
+    stretch keeps faint structure in play.
+    """
+    scaled = np.log1p(np.clip(_finite(image), 0.0, None))
+    high = np.percentile(scaled, 99.5)
+    if high <= 0:
+        return np.zeros(scaled.shape, dtype=np.uint8)
+    return np.clip(scaled / high * 255.0, 0, 255).astype(np.uint8)
+
+
+def optical_flow(context, use_dis=True):
+    """Motion-compensated interpolation between the bracketing frames.
+
+    Estimates dense flow both ways and warps each bracket forward to the target
+    instant, then blends.  Unlike ``linear_blend`` this moves features instead of
+    dissolving between them, which is what the eye reads as smooth motion.
+    """
+    if context.before is None or context.after is None:
+        return linear_blend(context)
+
+    before, after = _finite(context.before), _finite(context.after)
+    if before.shape != after.shape:
+        return linear_blend(context)
+
+    first, second = _for_flow(before), _for_flow(after)
+    if use_dis:
+        engine = cv.DISOpticalFlow_create(cv.DISOPTICAL_FLOW_PRESET_MEDIUM)
+        forward = engine.calc(first, second, None)
+        backward = engine.calc(second, first, None)
+    else:
+        forward = cv.calcOpticalFlowFarneback(
+            first, second, None, 0.5, 3, 15, 3, 5, 1.2, 0
+        )
+        backward = cv.calcOpticalFlowFarneback(
+            second, first, None, 0.5, 3, 15, 3, 5, 1.2, 0
+        )
+
+    alpha = context.alpha
+    height, width = before.shape
+    grid_x, grid_y = np.meshgrid(
+        np.arange(width, dtype=np.float32), np.arange(height, dtype=np.float32)
+    )
+    # cv.remap samples the source *at* the map coordinates, so to place a feature
+    # where it should be at time alpha we read from where it was: a feature at x in
+    # `before` sits at x + forward(x) in `after`, hence at p - alpha*forward(p) when
+    # looking back from the interpolated frame.  Adding the flow instead of
+    # subtracting it moves every feature the wrong way, which is worse than not
+    # compensating at all.
+    warped_before = cv.remap(
+        before,
+        grid_x - forward[..., 0] * alpha,
+        grid_y - forward[..., 1] * alpha,
+        cv.INTER_LINEAR,
+        borderMode=cv.BORDER_REPLICATE,
+    )
+    warped_after = cv.remap(
+        after,
+        grid_x - backward[..., 0] * (1.0 - alpha),
+        grid_y - backward[..., 1] * (1.0 - alpha),
+        cv.INTER_LINEAR,
+        borderMode=cv.BORDER_REPLICATE,
+    )
+    return ((1.0 - alpha) * warped_before + alpha * warped_after).astype(np.float32)
+
+
+# ------------------------------------------------------------ cross-satellite fill
+
+
+def gain_match(source, reference):
+    """Put `source` on `reference`'s radiance scale by least squares.
+
+    GOES-16 and GOES-18 carry different SUVI flight models, so their radiances
+    differ by a roughly affine factor even when both are healthy.
+    """
+    x = _finite(source).ravel().astype(np.float64)
+    y = _finite(reference).ravel().astype(np.float64)
+    variance = float(((x - x.mean()) ** 2).sum())
+    if variance <= 0:
+        return np.asarray(source, dtype=np.float32)
+    gain = float(((x - x.mean()) * (y - y.mean())).sum() / variance)
+    offset = float(y.mean() - gain * x.mean())
+    return (np.asarray(source, dtype=np.float32) * gain + offset).astype(np.float32)
+
+
+def crosssat(context, align=True):
+    """Substitute the other satellite's view of the same instant.
+
+    The two spacecraft see the same Sun from 1 AU, so the substitute is a real
+    observation of the real Sun at the right time -- not an interpolation.  It
+    should dominate every temporal method whenever it is available, which is the
+    thing worth quantifying: it is unavailable in the 31% of slots where both
+    satellites are out simultaneously.
+
+    Residual differences are instrument calibration (removed by gain matching) and
+    a few pixels of geostationary parallax (removed by alignment).
+    """
+    if context.counterpart is None:
+        return None
+    counterpart = _finite(context.counterpart)
+    reference = context.before if context.before is not None else context.after
+    if reference is None:
+        return counterpart
+    reference = _finite(reference)
+    if counterpart.shape != reference.shape:
+        return counterpart
+
+    if align:
+        window = cv.createHanningWindow(
+            (counterpart.shape[1], counterpart.shape[0]), cv.CV_64F
+        )
+        (dx, dy), _ = cv.phaseCorrelate(
+            counterpart.astype(np.float64), reference.astype(np.float64), window
+        )
+        matrix = np.array([[1.0, 0.0, dx], [0.0, 1.0, dy]], dtype=np.float32)
+        counterpart = cv.warpAffine(
+            counterpart,
+            matrix,
+            (counterpart.shape[1], counterpart.shape[0]),
+            flags=cv.INTER_LINEAR,
+            borderMode=cv.BORDER_REPLICATE,
+        )
+    return gain_match(counterpart, reference)
+
+
+# --------------------------------------------------------- solar rotation warping
+
+
+def rotation_rate(latitude_rad, synodic=True):
+    """Snodgrass differential rotation in degrees per day at a given latitude."""
+    sin2 = np.sin(latitude_rad) ** 2
+    rate = SNODGRASS_A + SNODGRASS_B * sin2 + SNODGRASS_C * sin2**2
+    return rate - EARTH_ORBIT_DEG_PER_DAY if synodic else rate
+
+
+def _disc_radius_pixels(header, shape):
+    """Solar radius in pixels, from the header if possible."""
+    diameter = header.get("diam_sun")
+    if diameter:
+        return float(diameter) / 2.0
+    distance, scale = header.get("dsun_obs"), header.get("cdelt1")
+    if distance and scale:
+        return float(np.degrees(np.arcsin(R_SUN / distance)) * 3600.0 / scale)
+    return shape[0] * 0.3  # falls back to the archive's typical disc fraction
+
+
+def _rotation_map(shape, header, delta_seconds, synodic=True):
+    """Inverse map: for each output pixel, where in the input it came from.
+
+    Works in heliographic coordinates -- de-project each pixel onto the sphere, undo
+    the rotation that happened over `delta_seconds`, re-project.  Returns
+    (map_x, map_y, on_disc) with NaN where the source point is not visible.
+    """
+    height, width = shape
+    radius = _disc_radius_pixels(header, shape)
+    crpix1 = float(header.get("crpix1", (width + 1) / 2.0)) - 1.0
+    crpix2 = float(header.get("crpix2", (height + 1) / 2.0)) - 1.0
+    b0 = np.radians(float(header.get("solar_b0", 0.0)))
+
+    grid_x, grid_y = np.meshgrid(np.arange(width), np.arange(height))
+    x = (grid_x - crpix1) / radius
+    y = (grid_y - crpix2) / radius
+
+    rho2 = x**2 + y**2
+    on_disc = rho2 < 1.0
+    z = np.sqrt(np.clip(1.0 - rho2, 0.0, None))
+
+    # Plane-of-sky -> heliographic, undoing the observer's B0 tilt.
+    sin_lat = y * np.cos(b0) + z * np.sin(b0)
+    sin_lat = np.clip(sin_lat, -1.0, 1.0)
+    latitude = np.arcsin(sin_lat)
+    longitude = np.arctan2(x, z * np.cos(b0) - y * np.sin(b0))
+
+    # Step the longitude back to where this material was `delta_seconds` ago.
+    days = delta_seconds / SECONDS_PER_DAY
+    source_longitude = longitude - np.radians(rotation_rate(latitude, synodic)) * days
+
+    # Heliographic -> plane-of-sky.
+    cos_lat = np.cos(latitude)
+    sx = cos_lat * np.sin(source_longitude)
+    sy = sin_lat * np.cos(b0) - cos_lat * np.cos(source_longitude) * np.sin(b0)
+    sz = sin_lat * np.sin(b0) + cos_lat * np.cos(source_longitude) * np.cos(b0)
+
+    visible = on_disc & (sz > 0)
+    map_x = (sx * radius + crpix1).astype(np.float32)
+    map_y = (sy * radius + crpix2).astype(np.float32)
+    return map_x, map_y, visible
+
+
+def solar_rotation(context, synodic=True):
+    """Warp the bracketing frames by differential solar rotation, then blend.
+
+    The Sun is not a rigid body: the equator turns in about 25 days, the poles in
+    about 35.  Over a short gap that is a sub-pixel effect, but across a multi-hour
+    outage it is the difference between features landing where they belong and
+    smearing.  This is the only method here that uses a physical model of the scene.
+
+    Applies on-disc only.  The corona above the limb does not co-rotate with the
+    photosphere, so off-disc pixels fall back to a plain cross-fade.
+    """
+    if context.before is None and context.after is None:
+        return None
+    if context.before is None or context.after is None:
+        source = context.before if context.before is not None else context.after
+        delta = context.dt_before if context.before is not None else -context.dt_after
+        warped, visible = _warp(source, context.header, delta, synodic)
+        blended = np.where(visible, warped, _finite(source))
+        return blended.astype(np.float32)
+
+    before, after = _finite(context.before), _finite(context.after)
+    if before.shape != after.shape:
+        return linear_blend(context)
+
+    # Roll `before` forward to the target instant and `after` backward to it.
+    warped_before, visible_before = _warp(before, context.header, context.dt_before, synodic)
+    warped_after, visible_after = _warp(after, context.header, -context.dt_after, synodic)
+
+    alpha = context.alpha
+    rotated = (1.0 - alpha) * warped_before + alpha * warped_after
+    faded = (1.0 - alpha) * before + alpha * after
+    visible = visible_before & visible_after
+    return np.where(visible, rotated, faded).astype(np.float32)
+
+
+def _warp(image, header, delta_seconds, synodic):
+    image = _finite(image)
+    map_x, map_y, visible = _rotation_map(image.shape, header, delta_seconds, synodic)
+    warped = cv.remap(
+        image, map_x, map_y, cv.INTER_LINEAR, borderMode=cv.BORDER_CONSTANT, borderValue=0.0
+    )
+    return warped, visible
+
+
+FILLERS = {
+    "hold_last": hold_last,
+    "linear_blend": linear_blend,
+    "optical_flow": optical_flow,
+    "crosssat": crosssat,
+    "solar_rotation": solar_rotation,
+}
+
+# TODO: learned filler.  Train a model to predict a frame from its preceding frames,
+# following frames, and the other satellite's view, then evaluate it here across
+# severities of missing data and prediction horizons (single-frame gaps through
+# multi-hour outages, one satellite out versus both).  It plugs in as another entry
+# in FILLERS and reuses the bench's existing cases and metrics unchanged.
diff --git a/suvi/fitsio.py b/suvi/fitsio.py
new file mode 100644
index 0000000..d42a188
--- /dev/null
+++ b/suvi/fitsio.py
@@ -0,0 +1,294 @@
+"""Cheap FITS header reads and file-integrity checks.
+
+The archive's science keywords (``DEGRADED``, ``ECLIPSE``, ``IMG_MEAN``, ...) live in
+the tile-compressed image extension's header, in the first ~18 KB of a 1.7 MB file.
+Reading just those bytes and parsing the 80-column cards by hand is ~5x faster than
+letting astropy open the file (4.1 ms vs 22.2 ms per file measured on this archive),
+which is the difference between a two-hour and a ten-hour pass over the full set.
+astropy is still used for pixel data, where it earns its keep.
+
+Every function reports trouble as a structured error string rather than raising, so a
+truncated or corrupt file is a *finding* the detector can score, not an exception that
+kills a worker.
+"""
+
+import logging
+import os
+import warnings
+
+import numpy as np
+from astropy.io import fits
+from astropy.utils.exceptions import AstropyUserWarning
+
+from . import db
+
+
+def quiet_astropy():
+    """Silence astropy's per-file chatter about damaged files.
+
+    astropy reports conditions like "File may have been truncated" through both its
+    own logger and ``warnings``, either of which floods stderr when scanning
+    millions of files -- and damaged files are exactly what a bench run is full of.
+    Those conditions are already surfaced per-frame by ``read_header``,
+    ``read_image`` and ``verify_datasums``, so nothing is lost by muting them.
+
+    Call once per process; worker pools must call it in each child.
+    """
+    logging.getLogger("astropy").setLevel(logging.ERROR)
+    warnings.simplefilter("ignore", AstropyUserWarning)
+
+#: FITS records are a whole number of 2880-byte blocks.
+BLOCK = 2880
+CARD = 80
+#: How far into a file to look for the image HDU header.  The real ones end by
+#: ~17 KB; the cap stops a malformed file from pulling megabytes into memory.
+MAX_HEADER_BYTES = BLOCK * 16
+
+#: Sentinel some SUVI products use for undefined pixels.
+ZBLANK = -999999
+
+
+def _parse_value(raw):
+    """Parse a FITS card value, honouring quoted strings and comment separators."""
+    raw = raw.strip()
+    if not raw:
+        return None
+    if raw[0] == "'":
+        # String value: scan for the closing quote, where '' is a literal quote.
+        out = []
+        i = 1
+        while i < len(raw):
+            if raw[i] == "'":
+                if i + 1 < len(raw) and raw[i + 1] == "'":
+                    out.append("'")
+                    i += 2
+                    continue
+                break
+            out.append(raw[i])
+            i += 1
+        return "".join(out).strip()
+
+    # Non-string: everything before the comment separator.
+    value = raw.split("/", 1)[0].strip()
+    if value in ("T", "F"):
+        return value == "T"
+    if not value:
+        return None
+    try:
+        return int(value)
+    except ValueError:
+        pass
+    try:
+        # FITS permits Fortran-style 'D' exponents.
+        return float(value.replace("D", "E").replace("d", "e"))
+    except ValueError:
+        return value
+
+
+def _parse_header_blocks(buf, pos):
+    """Parse cards from `pos` until the END card.
+
+    Returns (cards, next_pos), or (None, reason) if END is not reached.
+    """
+    cards = {}
+    while pos + BLOCK <= len(buf):
+        block = buf[pos : pos + BLOCK]
+        pos += BLOCK
+        for i in range(0, BLOCK, CARD):
+            card = block[i : i + CARD]
+            key = card[:8].rstrip()
+            if key == b"END":
+                return cards, pos
+            # Only fixed-format valued cards; COMMENT/HISTORY/CONTINUE lack the '= '.
+            if card[8:10] == b"= ":
+                try:
+                    name = key.decode("ascii").strip()
+                    value = _parse_value(card[10:].decode("ascii"))
+                except UnicodeDecodeError:
+                    continue
+                if name and name not in cards:
+                    cards[name] = value
+    return None, "header has no END card within the scanned region"
+
+
+def _data_bytes(cards):
+    """Size of an HDU's data unit, in bytes, rounded up to whole blocks."""
+    naxis = cards.get("NAXIS", 0)
+    if not isinstance(naxis, int) or naxis <= 0:
+        return 0
+    count = 1
+    for axis in range(1, naxis + 1):
+        length = cards.get(f"NAXIS{axis}")
+        if not isinstance(length, int) or length < 0:
+            return 0
+        count *= length
+    bitpix = cards.get("BITPIX", 8)
+    if not isinstance(bitpix, int):
+        return 0
+    size = count * abs(bitpix) // 8
+    size += cards.get("PCOUNT", 0) or 0
+    return ((size + BLOCK - 1) // BLOCK) * BLOCK
+
+
+def _is_image_hdu(cards):
+    """Whether this HDU carries the image we care about.
+
+    SUVI L2 stores the image tile-compressed inside a BINTABLE, flagged by ZIMAGE;
+    its real dimensions are in ZNAXIS, not NAXIS.  A plain IMAGE extension or a
+    primary HDU with data also counts.
+    """
+    if cards.get("ZIMAGE") is True:
+        return True
+    return isinstance(cards.get("NAXIS"), int) and cards["NAXIS"] > 0
+
+
+def read_header(path, max_bytes=MAX_HEADER_BYTES):
+    """Read the image HDU's header without decompressing pixels.
+
+    Returns (cards, error).  On failure cards is whatever was parsed (possibly
+    empty) and error is a short human-readable reason.
+    """
+    try:
+        size = os.path.getsize(path)
+        with open(path, "rb") as handle:
+            buf = handle.read(max_bytes)
+    except OSError as exc:
+        return {}, f"unreadable: {exc.strerror or exc}"
+
+    if size == 0:
+        return {}, "empty file"
+    if len(buf) < BLOCK:
+        return {}, f"truncated: {size} bytes is less than one {BLOCK}-byte block"
+    if not buf.startswith(b"SIMPLE  ="):
+        return {}, "not a FITS file: missing SIMPLE keyword"
+    if size % BLOCK:
+        # Worth reporting even though the header may still parse: it means the file
+        # was cut short mid-transfer, which is exactly the download failure mode.
+        truncation = f"truncated: {size} bytes is not a multiple of {BLOCK}"
+    else:
+        truncation = None
+
+    pos = 0
+    while True:
+        cards, result = _parse_header_blocks(buf, pos)
+        if cards is None:
+            return {}, result
+        pos = result
+        if _is_image_hdu(cards):
+            return cards, truncation
+        skip = _data_bytes(cards)
+        if pos + skip + BLOCK > len(buf):
+            return cards, truncation or "no image HDU within the scanned region"
+        pos += skip
+
+
+def header_metadata(cards):
+    """Project parsed cards onto the ``header`` table's columns.
+
+    Booleans become 0/1 so they sort and filter naturally in SQL; anything of an
+    unexpected type is dropped rather than stored, so a corrupt card cannot poison
+    a numeric column.
+    """
+    values = {}
+    for field, keyword, sqltype in db.HEADER_COLUMNS:
+        raw = cards.get(keyword)
+        if raw is None:
+            continue
+        if isinstance(raw, bool):
+            values[field] = int(raw)
+        elif sqltype == "TEXT":
+            values[field] = str(raw)
+        elif sqltype == "INTEGER":
+            values[field] = int(raw) if isinstance(raw, (int, float)) else None
+        elif isinstance(raw, (int, float)):
+            values[field] = float(raw)
+    return {k: v for k, v in values.items() if v is not None}
+
+
+def scan_header(path):
+    """Read and project a file's header in one step.  Returns (values, error)."""
+    cards, error = read_header(path)
+    return header_metadata(cards), error
+
+
+def read_image(path):
+    """Read the decompressed image array.  Returns (data, error).
+
+    Returns a float32 array with the ZBLANK sentinel converted to NaN, so callers
+    do not have to remember that -999999 means "no data" rather than a radiance.
+
+    Detects damage only insofar as astropy refuses to decode it; a file whose image
+    HDU survives intact reads fine even if later bytes are missing.  Pair this with
+    ``verify_datasums`` when integrity matters rather than availability.
+    """
+    try:
+        with fits.open(path, memmap=False) as hdus:
+            data = None
+            for hdu in hdus:
+                if getattr(hdu, "data", None) is not None and hdu.data.ndim == 2:
+                    data = hdu.data
+                    break
+            if data is None:
+                # The blank/corrupt-HDU case filter_FITS.py caught as IndexError.
+                return None, "no 2-D image array in file"
+    except Exception as exc:  # astropy raises a wide variety on malformed input
+        return None, f"{type(exc).__name__}: {exc}"
+
+    data = np.asarray(data, dtype=np.float32)
+    blank = data == ZBLANK
+    if blank.any():
+        data = data.copy()
+        data[blank] = np.nan
+    return data, None
+
+
+def datasum(payload):
+    """FITS-standard 32-bit ones-complement checksum of a data unit."""
+    if len(payload) % 4:
+        payload = payload + b"\x00" * (4 - len(payload) % 4)
+    total = int(np.frombuffer(payload, dtype=">u4").astype(np.uint64).sum())
+    while total >> 32:  # fold the carries back in
+        total = (total & 0xFFFFFFFF) + (total >> 32)
+    return total
+
+
+def verify_datasums(path):
+    """Check every HDU's stored DATASUM against the bytes on disk.
+
+    Catches silent corruption that a size check misses.  Computed over the raw file,
+    deliberately not via astropy: astropy re-serialises a tile-compressed HDU before
+    summing, so it reports a mismatch for every healthy SUVI file.
+
+    Returns an error string, or None if all present DATASUMs agree.
+    """
+    try:
+        with open(path, "rb") as handle:
+            buf = handle.read()
+    except OSError as exc:
+        return f"unreadable: {exc.strerror or exc}"
+
+    if len(buf) < BLOCK or not buf.startswith(b"SIMPLE  ="):
+        return "not a FITS file"
+
+    pos = 0
+    checked = 0
+    while pos < len(buf):
+        cards, result = _parse_header_blocks(buf, pos)
+        if cards is None:
+            return result
+        size = _data_bytes(cards)
+        if result + size > len(buf):
+            return "truncated: HDU data unit runs past end of file"
+        stored = cards.get("DATASUM")
+        if stored is not None:
+            try:
+                expected = int(str(stored).strip())
+            except ValueError:
+                return f"malformed DATASUM keyword: {stored!r}"
+            if datasum(buf[result : result + size]) != expected:
+                name = cards.get("EXTNAME") or ("PRIMARY" if pos == 0 else "extension")
+                return f"datasum mismatch in {name}"
+            checked += 1
+        pos = result + size
+
+    return None if checked else "no DATASUM keywords present"
diff --git a/suvi/index.py b/suvi/index.py
new file mode 100644
index 0000000..4afa6eb
--- /dev/null
+++ b/suvi/index.py
@@ -0,0 +1,253 @@
+"""Keeping the frame index in step with the archive, without walking it.
+
+The index exists so that nothing has to traverse 2.65M files to answer "what frames
+do we have". Traversal is not merely slow here: the archive sits on a virtiofs mount
+where the daemon holds a host file descriptor per inode the guest has looked up, so a
+full walk exhausts the host's descriptors and the mount then refuses *every* open
+until the guest drops its dentry cache. One full pass cost 152,193 renames to ENFILE
+before this was understood.
+
+So the index is maintained three ways, in descending order of preference:
+
+1. **At the source.** ``puller_fits.py`` records each frame as it downloads it, so
+   new data enters the index with no filesystem traversal at all.
+2. **By directory mtime** (:func:`reconcile`). A directory's mtime changes whenever
+   an entry is added or removed, so comparing it against ``dir_scan`` is an exact
+   test for "did anything change in here". The archive averages ~360 frames per
+   day-directory, so this checks ~7,400 stats instead of 2.65M lookups -- a 360x
+   reduction, and the difference between an operation this mount sustains and one
+   that breaks it.
+3. **A full rebuild**, only for a cold start or when the index is suspect.
+
+Only step 3 is expensive, and after the first one it should never be needed again.
+"""
+
+import os
+import time
+
+from . import db, paths, vfs
+
+
+def day_directories(root, satellites=paths.SATELLITES, wavelengths=paths.WAVELENGTHS,
+                    years=None):
+    """Yield (relpath, abspath) for every day-directory that exists.
+
+    Enumerated by descending the year/month/day structure rather than walking, so the
+    cost is one listing per year and month directory -- a couple of thousand small
+    reads -- and no per-file lookups at all.
+    """
+    for satellite in satellites:
+        for wavelength in wavelengths:
+            band_rel = f"goes{satellite:d}/l2/data/suvi-l2-ci{wavelength:03d}"
+            band_abs = os.path.join(root, *band_rel.split("/"))
+            for year in _subdirs(band_abs):
+                if not year.isdigit() or (years and int(year) not in years):
+                    continue
+                year_abs = os.path.join(band_abs, year)
+                for month in _subdirs(year_abs):
+                    month_abs = os.path.join(year_abs, month)
+                    for day in _subdirs(month_abs):
+                        yield (
+                            f"{band_rel}/{year}/{month}/{day}",
+                            os.path.join(month_abs, day),
+                        )
+
+
+def _subdirs(path):
+    """Immediate subdirectory names.
+
+    A directory that does not exist yields nothing; one that exists but cannot be
+    read raises.  The distinction is essential: swallowing the error makes an
+    unreadable tree look like an empty one, and :func:`reconcile` would then conclude
+    its contents had been deleted.  That is not hypothetical -- an ENFILE partway
+    through enumeration made five of six bands look absent, and 205,618 index rows
+    were dropped as "vanished" before this was caught.
+    """
+    try:
+        with os.scandir(path) as entries:
+            return sorted(entry.name for entry in entries if entry.is_dir())
+    except (FileNotFoundError, NotADirectoryError):
+        return []
+
+
+def scan_directory(conn, dir_relpath, dir_abspath):
+    """Bring one directory's frames into the index.
+
+    Returns (added, removed, duplicates, examined).  `examined` is the number of
+    frame files looked at, which is what drives how close the mount is to running
+    out of file handles -- see suvi.vfs.
+
+    Reconciles in both directions: files that appeared are inserted, and index rows
+    whose files have gone are deleted, so the index stays authoritative rather than
+    merely append-only.
+    """
+    try:
+        with os.scandir(dir_abspath) as entries:
+            found = {}
+            for entry in entries:
+                name = paths.parse_frame_filename(entry.name)
+                if name is None:
+                    continue
+                try:
+                    stat = entry.stat()
+                    found[entry.name] = (name, stat.st_size, stat.st_mtime)
+                except OSError:
+                    found[entry.name] = (name, None, None)
+    except OSError:
+        return 0, 0, [], 0
+
+    examined = len(found)
+    found, duplicates = _resolve_slot_collisions(found)
+
+    known = db.frames_in_dir(conn, dir_relpath)
+
+    # Remove departed rows *before* inserting, so a file renamed within a directory
+    # -- which is exactly what the un-rename migration does -- does not momentarily
+    # have two rows claiming one observation slot and trip the unique constraint.
+    gone = [frame_id for filename, frame_id in known.items() if filename not in found]
+    if gone:
+        db.delete_frames(conn, gone)
+
+    added = 0
+    for filename, (name, size, mtime) in found.items():
+        db.upsert_frame(conn, name, f"{dir_relpath}/{filename}", size, mtime)
+        if filename not in known:
+            added += 1
+    return added, len(gone), duplicates, examined
+
+
+def _resolve_slot_collisions(found):
+    """Keep one file per observation slot; return the rest as duplicates.
+
+    Two files can claim the same (satellite, band, time) when an older filter
+    labelled a frame repeatedly -- the archive holds 1,742 such pairs, a clean
+    ``...v1-0-1.fits`` beside a ``...v1-0-1_f_f_f.fits`` of byte-identical content,
+    left when the puller re-downloaded a frame it could no longer find under its
+    published name.  The index cannot hold both, and crashing on them would block
+    indexing the entire archive over a handful of stale copies.  Prefer the file
+    NOAA actually published: unlabelled first, shortest name to break ties.
+    """
+    by_slot = {}
+    for filename, (name, _, _) in found.items():
+        by_slot.setdefault(name.slot, []).append(filename)
+
+    duplicates = []
+    for names in by_slot.values():
+        if len(names) < 2:
+            continue
+        canonical = min(
+            names, key=lambda n: (found[n][0].label is not None, len(n), n)
+        )
+        for other in names:
+            if other != canonical:
+                duplicates.append(other)
+                found.pop(other, None)
+    return found, duplicates
+
+
+def reconcile(conn, root=None, satellites=paths.SATELLITES, wavelengths=paths.WAVELENGTHS,
+              years=None, force=False, progress=None, relief=True):
+    """Update the index from the archive, reading only what changed.
+
+    Returns a summary dict.  With `force`, every directory is re-read regardless of
+    its recorded mtime -- the escape hatch for when the index is suspected wrong.
+
+    A steady-state run touches almost nothing and needs no special care.  A cold
+    build is different: it reads every file in the archive, which is exactly the
+    traversal that exhausts this mount's file handles, so it hands them back
+    periodically (see suvi.vfs).  Pass ``relief=False`` to disable that.
+    """
+    root = root or paths.data_root()
+    recorded = {} if force else db.dir_mtimes(conn)
+
+    checked = changed = added = removed = scanned = 0
+    next_relief = vfs.RELIEF_INTERVAL
+    duplicates = []
+    seen = set()
+    pending = []
+    started = time.time()
+
+    for dir_relpath, dir_abspath in day_directories(root, satellites, wavelengths, years):
+        seen.add(dir_relpath)
+        checked += 1
+        try:
+            mtime = os.stat(dir_abspath).st_mtime
+        except OSError:
+            continue
+        if not force and recorded.get(dir_relpath) == mtime:
+            continue  # nothing added or removed since we last looked
+
+        changed += 1
+        new, lost, dupes, examined = scan_directory(conn, dir_relpath, dir_abspath)
+        added += new
+        removed += lost
+        duplicates.extend(f"{dir_relpath}/{name}" for name in dupes)
+        # Record the mtime we actually observed, not one read afterwards, so a write
+        # racing this scan leaves the directory looking stale and gets picked up next
+        # time rather than being silently skipped forever.
+        pending.append((dir_relpath, mtime, len(db.frames_in_dir(conn, dir_relpath))))
+        if len(pending) >= 200:
+            db.record_dir_scans(conn, pending)
+            conn.commit()
+            pending.clear()
+        scanned += examined
+        if relief and scanned >= next_relief:
+            vfs.release_handles()
+            next_relief = scanned + vfs.RELIEF_INTERVAL
+        if progress and changed % 100 == 0:
+            progress(f"  {changed} changed of {checked} checked, +{added}/-{removed}")
+
+    if pending:
+        db.record_dir_scans(conn, pending)
+
+    # Directories that have vanished entirely.
+    #
+    # Absence from `seen` is not sufficient evidence to delete anything: enumeration
+    # can come up short for reasons that have nothing to do with the data, and the
+    # cost of being wrong is destroying index rows for files that are still present.
+    # Confirm each one is genuinely gone before acting on it.
+    vanished = []
+    for dir_relpath in recorded:
+        if dir_relpath in seen:
+            continue
+        if os.path.isdir(paths.abspath(dir_relpath, root)):
+            continue  # still there; enumeration simply missed it
+        vanished.append(dir_relpath)
+
+    for dir_relpath in vanished:
+        stale = db.frames_in_dir(conn, dir_relpath)
+        if stale:
+            db.delete_frames(conn, list(stale.values()))
+            removed += len(stale)
+    if vanished:
+        db.forget_dir_scans(conn, vanished)
+    conn.commit()
+
+    return {
+        "directories_checked": checked,
+        "directories_changed": changed,
+        "directories_vanished": len(vanished),
+        "frames_added": added,
+        "frames_removed": removed,
+        "duplicate_slots": duplicates,
+        "seconds": time.time() - started,
+    }
+
+
+def record_downloaded(conn, local_path, root=None):
+    """Index a frame the puller has just written.
+
+    The cheapest path of all: the downloader already knows the file exists, so the
+    index can learn about it without anybody looking at the filesystem. Returns the
+    frame id, or None if the file is not a SUVI frame.
+    """
+    root = root or paths.data_root()
+    name = paths.parse_frame_filename(os.path.basename(local_path))
+    if name is None:
+        return None
+    try:
+        stat = os.stat(local_path)
+        size, mtime = stat.st_size, stat.st_mtime
+    except OSError:
+        size = mtime = None
+    return db.upsert_frame(conn, name, name.relpath(), size, mtime)
diff --git a/suvi/metrics.py b/suvi/metrics.py
new file mode 100644
index 0000000..5121b20
--- /dev/null
+++ b/suvi/metrics.py
@@ -0,0 +1,354 @@
+"""Scoring for detection and fill quality.
+
+Detection scoring keeps two things apart that are easy to conflate:
+
+* a **false positive** -- the detector flagged a slot the bench did not corrupt, and
+  the window's ground truth says was good;
+* a **legacy disagreement** -- the detector flagged a slot the old filter passed.
+
+On a vetted window the second is a candidate *find*, not an error: the old filter is
+what we are trying to beat, so scoring its misses against a new detector would
+penalise exactly the improvement we want.
+
+Fill scoring is reported both in radiance and after the display mapping the videos
+actually use, plus a temporal term.  A frame can score well on per-frame PSNR and
+still read as a visible stutter at 60 fps, so flicker is measured explicitly.
+"""
+
+from dataclasses import dataclass, field
+
+import numpy as np
+from skimage.metrics import structural_similarity
+
+#: Display mapping used by merger_FITS.py to turn radiance into pixels, by band.
+#: (vmin, vmax, gamma).  Fill error is reported through this because it is what the
+#: eye sees -- an error in the dim corona matters far less than one on the disc.
+DISPLAY_MAPPING = {
+    94: (0.050, 8.0, 0.375),
+    131: (0.05, 8.0, 0.40),
+    171: (0.100, 20.0, 0.425),
+    195: (0.10, 30.0, 0.45),
+    284: (0.100, 40.0, 0.475),
+    304: (0.1, 90.0, 0.5),
+}
+
+
+def to_display(image, wavelength):
+    """Map radiance to the 0-1 display range merger_FITS.py renders with."""
+    vmin, vmax, gamma = DISPLAY_MAPPING.get(wavelength, (0.0, 1.0, 1.0))
+    clean = np.nan_to_num(np.asarray(image, dtype=np.float64), nan=0.0)
+    return np.clip((clean - vmin) / vmax, 0.0, 1.0) ** gamma
+
+
+# ------------------------------------------------------------------------ detection
+
+
+@dataclass
+class DetectionScore:
+    """Confusion counts and derived rates for one detector on one bench case."""
+
+    true_positives: int = 0
+    false_positives: int = 0
+    false_negatives: int = 0
+    true_negatives: int = 0
+    unknown: int = 0
+    #: Slots the detector flagged that the legacy filter had passed and the bench
+    #: did not corrupt.  Reported, never counted as errors.
+    legacy_disagreements: int = 0
+    #: Recall broken down by corruption mode, so a detector that only catches
+    #: blackouts cannot hide behind a good overall number.
+    recall_by_mode: dict = field(default_factory=dict)
+    elapsed_us: int = 0
+    frames: int = 0
+
+    @property
+    def precision(self):
+        flagged = self.true_positives + self.false_positives
+        return self.true_positives / flagged if flagged else float("nan")
+
+    @property
+    def recall(self):
+        actual = self.true_positives + self.false_negatives
+        return self.true_positives / actual if actual else float("nan")
+
+    @property
+    def f1(self):
+        precision, recall = self.precision, self.recall
+        if not np.isfinite(precision) or not np.isfinite(recall) or precision + recall == 0:
+            return float("nan")
+        return 2 * precision * recall / (precision + recall)
+
+    @property
+    def false_positive_rate(self):
+        negatives = self.false_positives + self.true_negatives
+        return self.false_positives / negatives if negatives else float("nan")
+
+    @property
+    def microseconds_per_frame(self):
+        return self.elapsed_us / self.frames if self.frames else float("nan")
+
+    def as_dict(self):
+        return {
+            "true_positives": self.true_positives,
+            "false_positives": self.false_positives,
+            "false_negatives": self.false_negatives,
+            "true_negatives": self.true_negatives,
+            "unknown": self.unknown,
+            "legacy_disagreements": self.legacy_disagreements,
+            "precision": self.precision,
+            "recall": self.recall,
+            "f1": self.f1,
+            "false_positive_rate": self.false_positive_rate,
+            "us_per_frame": self.microseconds_per_frame,
+            "recall_by_mode": dict(self.recall_by_mode),
+        }
+
+
+def score_detection(verdicts, injected, legacy_good=frozenset(), elapsed_us=0):
+    """Score detector output against what the bench actually injected.
+
+    `verdicts` maps slot -> Verdict.  `injected` maps slot -> corruption mode name
+    for every slot the bench damaged (a deleted slot has no frame to judge, so it is
+    not scored here).  `legacy_good` is the set of slots the old filter passed.
+
+    'unknown' verdicts are counted separately and excluded from precision and recall
+    rather than folded into 'good' -- a detector that abstains has not made an error,
+    but it has not made a call either, and hiding that would flatter it.
+    """
+    score = DetectionScore(elapsed_us=elapsed_us, frames=len(verdicts))
+    by_mode = {}
+
+    for slot, verdict in verdicts.items():
+        mode = injected.get(slot)
+        corrupted = mode is not None
+
+        if verdict.verdict == "unknown":
+            score.unknown += 1
+            if corrupted:
+                by_mode.setdefault(mode, [0, 0])[1] += 1
+            continue
+
+        flagged = verdict.verdict == "bad"
+        if corrupted:
+            stats = by_mode.setdefault(mode, [0, 0])
+            stats[1] += 1
+            if flagged:
+                score.true_positives += 1
+                stats[0] += 1
+            else:
+                score.false_negatives += 1
+        elif flagged:
+            score.false_positives += 1
+            if slot in legacy_good:
+                score.legacy_disagreements += 1
+        else:
+            score.true_negatives += 1
+
+    score.recall_by_mode = {
+        mode: (caught / total if total else float("nan"))
+        for mode, (caught, total) in sorted(by_mode.items())
+    }
+    return score
+
+
+#: How several detectors' verdicts are folded into one.
+COMBINATION_POLICIES = ("any", "all", "majority")
+
+
+def combine_verdicts(verdict_maps, policy="any"):
+    """Fold several detectors' verdicts into one per slot.
+
+    Which detectors to run in production is a trade-off between recall and the
+    false-positive rate, and the only honest way to choose is to score the
+    combinations the same way as the individuals.  Because `detection` rows already
+    store a verdict per frame, this is pure post-processing.
+
+    * ``any``      -- bad if any detector says bad.  Maximum recall; false positives
+                      accumulate across detectors.
+    * ``all``      -- bad only if every detector that voted says bad.  Minimum false
+                      positives, and the right shape for a near-zero FP budget.
+    * ``majority`` -- bad if more than half the votes say bad.
+
+    ``unknown`` abstains rather than voting.  A detector that declines to judge must
+    not be silently counted as saying "good": under ``all`` that would let one
+    abstention veto a real detection, and under ``any`` it would inflate recall.  A
+    slot where every detector abstains is itself ``unknown``.
+
+    `verdict_maps` is a sequence of {slot: Verdict}.  Returns {slot: Verdict}.
+    """
+    if policy not in COMBINATION_POLICIES:
+        raise ValueError(f"Unknown policy {policy!r}; expected one of {COMBINATION_POLICIES}")
+    if not verdict_maps:
+        return {}
+
+    from .detectors import BAD, GOOD, UNKNOWN, Verdict
+
+    combined = {}
+    slots = set()
+    for verdicts in verdict_maps:
+        slots.update(verdicts)
+
+    for slot in slots:
+        votes = []
+        reasons = []
+        for verdicts in verdict_maps:
+            verdict = verdicts.get(slot)
+            if verdict is None or verdict.verdict == UNKNOWN:
+                continue
+            votes.append(verdict.verdict == BAD)
+            if verdict.verdict == BAD and verdict.reason:
+                reasons.append(verdict.reason)
+
+        if not votes:
+            combined[slot] = Verdict(UNKNOWN, "no detector judged this frame", {})
+            continue
+
+        if policy == "any":
+            is_bad = any(votes)
+        elif policy == "all":
+            is_bad = all(votes)
+        else:
+            is_bad = sum(votes) * 2 > len(votes)
+
+        combined[slot] = Verdict(
+            BAD if is_bad else GOOD,
+            "; ".join(reasons[:3]) if is_bad else None,
+            {"votes_bad": float(sum(votes)), "votes_total": float(len(votes))},
+        )
+    return combined
+
+
+def precision_recall_curve(scores, labels):
+    """Precision/recall across every threshold of a continuous detector score.
+
+    `scores` are higher-is-more-suspicious. Returns (thresholds, precision, recall).
+    """
+    scores = np.asarray(scores, dtype=np.float64)
+    labels = np.asarray(labels, dtype=bool)
+    finite = np.isfinite(scores)
+    scores, labels = scores[finite], labels[finite]
+    if scores.size == 0 or not labels.any():
+        return np.array([]), np.array([]), np.array([])
+
+    order = np.argsort(-scores)
+    scores, labels = scores[order], labels[order]
+    true_positives = np.cumsum(labels)
+    flagged = np.arange(1, scores.size + 1)
+    precision = true_positives / flagged
+    recall = true_positives / labels.sum()
+    return scores, precision, recall
+
+
+def average_precision(scores, labels):
+    """Area under the precision-recall curve; the threshold-free summary."""
+    _, precision, recall = precision_recall_curve(scores, labels)
+    if recall.size == 0:
+        return float("nan")
+    return float(np.sum(np.diff(np.concatenate([[0.0], recall])) * precision))
+
+
+# ----------------------------------------------------------------------------- fill
+
+
+@dataclass
+class FillScore:
+    """Reconstruction error for one filled frame."""
+
+    rmse: float
+    mae: float
+    log_rmse: float
+    psnr: float
+    ssim: float
+    gap_frames: int = 0
+    wavelength: int = 0
+
+    def as_dict(self):
+        return {
+            "rmse": self.rmse,
+            "mae": self.mae,
+            "log_rmse": self.log_rmse,
+            "psnr": self.psnr,
+            "ssim": self.ssim,
+            "gap_frames": self.gap_frames,
+            "wavelength": self.wavelength,
+        }
+
+
+def score_fill(filled, truth, wavelength, gap_frames=0):
+    """Compare a reconstructed frame against the frame that was withheld.
+
+    Radiance errors (rmse/mae) are dominated by the bright disc; the log term keeps
+    the faint corona visible in the score; psnr and ssim are computed after the
+    display mapping, because that is the image a viewer actually sees.
+    """
+    filled = np.nan_to_num(np.asarray(filled, dtype=np.float64), nan=0.0)
+    truth = np.nan_to_num(np.asarray(truth, dtype=np.float64), nan=0.0)
+    if filled.shape != truth.shape:
+        raise ValueError(f"shape mismatch: {filled.shape} vs {truth.shape}")
+
+    residual = filled - truth
+    rmse = float(np.sqrt(np.mean(residual**2)))
+    mae = float(np.mean(np.abs(residual)))
+
+    log_residual = np.log1p(np.clip(filled, 0, None)) - np.log1p(np.clip(truth, 0, None))
+    log_rmse = float(np.sqrt(np.mean(log_residual**2)))
+
+    shown_fill, shown_truth = to_display(filled, wavelength), to_display(truth, wavelength)
+    display_mse = float(np.mean((shown_fill - shown_truth) ** 2))
+    psnr = float("inf") if display_mse == 0 else float(10.0 * np.log10(1.0 / display_mse))
+    ssim = float(structural_similarity(shown_truth, shown_fill, data_range=1.0))
+
+    return FillScore(rmse, mae, log_rmse, psnr, ssim, gap_frames, wavelength)
+
+
+def temporal_flicker(sequence, truth_sequence, wavelength):
+    """How much the reconstruction's frame-to-frame motion departs from reality.
+
+    Per-frame PSNR is blind to the artifact that matters most in a 60 fps video: a
+    filled run can match each frame tolerably and still freeze then jump.  This
+    compares the *rate of change* rather than the frames, in display space.
+
+    Returns mean absolute difference of successive-frame deltas; 0 is perfect.
+    """
+    if len(sequence) != len(truth_sequence):
+        raise ValueError("sequences must be the same length")
+    if len(sequence) < 2:
+        return float("nan")
+
+    shown = [to_display(frame, wavelength) for frame in sequence]
+    shown_truth = [to_display(frame, wavelength) for frame in truth_sequence]
+    deltas = [np.mean(np.abs(shown[i] - shown[i - 1])) for i in range(1, len(shown))]
+    truth_deltas = [
+        np.mean(np.abs(shown_truth[i] - shown_truth[i - 1])) for i in range(1, len(shown_truth))
+    ]
+    return float(np.mean(np.abs(np.array(deltas) - np.array(truth_deltas))))
+
+
+def summarise_fills(scores):
+    """Aggregate per-frame fill scores, overall and by gap length."""
+    if not scores:
+        return {}
+    by_gap = {}
+    for score in scores:
+        by_gap.setdefault(score.gap_frames, []).append(score)
+
+    def mean(values):
+        finite = [v for v in values if np.isfinite(v)]
+        return float(np.mean(finite)) if finite else float("nan")
+
+    return {
+        "n": len(scores),
+        "rmse": mean([s.rmse for s in scores]),
+        "log_rmse": mean([s.log_rmse for s in scores]),
+        "psnr": mean([s.psnr for s in scores]),
+        "ssim": mean([s.ssim for s in scores]),
+        "by_gap": {
+            gap: {
+                "n": len(group),
+                "rmse": mean([s.rmse for s in group]),
+                "psnr": mean([s.psnr for s in group]),
+                "ssim": mean([s.ssim for s in group]),
+            }
+            for gap, group in sorted(by_gap.items())
+        },
+    }
diff --git a/suvi/paths.py b/suvi/paths.py
new file mode 100644
index 0000000..622f3a0
--- /dev/null
+++ b/suvi/paths.py
@@ -0,0 +1,185 @@
+"""Archive layout: filename grammar, slot keys, and root discovery.
+
+The SUVI archive stores one FITS file per (satellite, wavelength, 4-minute slot):
+
+    Data/goes16/l2/data/suvi-l2-ci171/2024/03/15/
+        dr_suvi-l2-ci171_g16_s20240315T000000Z_e20240315T000400Z_v1-0-2.fits
+
+Historically ``filter_FITS.py`` appended ``_f`` (passed) or ``_e`` (rejected) to the
+stem to record its verdict.  Those labels now live in the SQLite index instead, but
+the parser still recognises them so the migration can ingest and strip them.
+"""
+
+import datetime
+import os
+import re
+from dataclasses import dataclass
+
+# The six SUVI composite-image passbands, in Angstroms.
+WAVELENGTHS = (94, 131, 171, 195, 284, 304)
+# GOES-17 is deliberately absent: its SUVI data is excluded by puller_fits.py.
+SATELLITES = (16, 18, 19)
+# Nominal spacing between consecutive frames, in seconds.
+CADENCE = 240
+
+# Legacy verdict suffixes written into filenames by the pre-SQLite filter.
+LEGACY_LABELS = ("f", "e")
+
+_TIME_FORMAT = "%Y%m%dT%H%M%S"
+
+# Anchored so that only an exact, well-formed basename matches.  The trailing label
+# group repeats to absorb the double-suffix files ("..._f_f.fits") that earlier
+# filter runs produced by re-processing an already-labelled file.
+_FRAME_RE = re.compile(
+    r"^dr_suvi-l2-ci(?P<wavelength>\d{3})"
+    r"_g(?P<satellite>\d{2})"
+    r"_s(?P<t_start>\d{8}T\d{6})Z"
+    r"_e(?P<t_end>\d{8}T\d{6})Z"
+    r"_v(?P<version>[0-9]+(?:-[0-9]+)*)"
+    r"(?P<labels>(?:_[fe])*)"
+    r"\.fits$"
+)
+
+
+def _parse_time(text):
+    """Parse a filename timestamp token to a UTC Unix timestamp."""
+    stamp = datetime.datetime.strptime(text, _TIME_FORMAT)
+    return int(stamp.replace(tzinfo=datetime.timezone.utc).timestamp())
+
+
+def _format_time(timestamp):
+    stamp = datetime.datetime.fromtimestamp(timestamp, datetime.timezone.utc)
+    return stamp.strftime(_TIME_FORMAT)
+
+
+@dataclass(frozen=True)
+class FrameName:
+    """A parsed SUVI L2 composite-image filename."""
+
+    satellite: int
+    wavelength: int
+    t_start: int
+    t_end: int
+    version: str
+    #: Legacy verdict suffix, or None once the archive has been un-renamed.  A file
+    #: labelled more than once keeps only the outermost (most recent) verdict.
+    label: str | None = None
+
+    @property
+    def slot(self):
+        """The key identifying what this frame is an observation of."""
+        return (self.satellite, self.wavelength, self.t_start)
+
+    def filename(self, label=None):
+        """Render the filename, optionally with a legacy verdict suffix."""
+        if label is not None and label not in LEGACY_LABELS:
+            raise ValueError(f"Unknown label: {label!r}")
+        suffix = f"_{label}" if label else ""
+        return (
+            f"dr_suvi-l2-ci{self.wavelength:03d}"
+            f"_g{self.satellite:d}"
+            f"_s{_format_time(self.t_start)}Z"
+            f"_e{_format_time(self.t_end)}Z"
+            f"_v{self.version}{suffix}.fits"
+        )
+
+    def relpath(self, label=None):
+        """Archive-relative POSIX path, the natural key used by the index.
+
+        Files are filed under the date the observation window *opened*, so a frame
+        starting at 23:58 belongs to that day even though it ends on the next one.
+        """
+        day = datetime.datetime.fromtimestamp(self.t_start, datetime.timezone.utc)
+        return (
+            f"goes{self.satellite:d}/l2/data/suvi-l2-ci{self.wavelength:03d}/"
+            f"{day.year:04d}/{day.month:02d}/{day.day:02d}/{self.filename(label)}"
+        )
+
+    def error_plot_name(self):
+        """The diagnostic JPG the legacy filter wrote next to a rejected frame."""
+        return self.filename()[: -len(".fits")] + "_e.jpg"
+
+
+def parse_frame_filename(name):
+    """Parse a SUVI frame basename, or return None if it is not one.
+
+    Accepts a bare basename only.  Anything carrying a path separator is rejected
+    rather than silently normalised, so a crafted name cannot escape the archive
+    root when the result is fed back into ``relpath``.
+    """
+    if not isinstance(name, str) or not name or len(name) > 255:
+        return None
+    if "/" in name or "\\" in name or os.sep in name:
+        return None
+
+    match = _FRAME_RE.match(name)
+    if match is None:
+        return None
+
+    wavelength = int(match.group("wavelength"))
+    satellite = int(match.group("satellite"))
+    if wavelength not in WAVELENGTHS or satellite not in SATELLITES:
+        return None
+
+    try:
+        t_start = _parse_time(match.group("t_start"))
+        t_end = _parse_time(match.group("t_end"))
+    except ValueError:
+        # Syntactically well-formed but not a real date, e.g. month 13.
+        return None
+    if t_end <= t_start:
+        return None
+
+    labels = match.group("labels")
+    label = labels[-1] if labels else None
+
+    return FrameName(
+        satellite=satellite,
+        wavelength=wavelength,
+        t_start=t_start,
+        t_end=t_end,
+        version=match.group("version"),
+        label=label,
+    )
+
+
+def data_root():
+    """Root of the FITS archive (the ``Data`` directory)."""
+    override = os.environ.get("SUVI_DATA_ROOT")
+    if override:
+        return os.path.abspath(override)
+    return os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", "Data"))
+
+
+def default_db_path():
+    """Default location of the SQLite index.
+
+    Overridable so the bench can run against a throwaway database without ever
+    touching the production index.
+    """
+    override = os.environ.get("SUVI_DB")
+    if override:
+        return os.path.abspath(override)
+    return os.path.join(os.path.dirname(data_root()), "suvi_index.sqlite")
+
+
+def abspath(relpath, root=None):
+    """Resolve an archive-relative POSIX path against the archive root.
+
+    Raises ValueError if the result would fall outside the root, which keeps a
+    malformed or hostile index row from reaching an arbitrary part of the disk.
+    """
+    root = os.path.abspath(root or data_root())
+    resolved = os.path.abspath(os.path.join(root, *relpath.split("/")))
+    if resolved != root and not resolved.startswith(root + os.sep):
+        raise ValueError(f"Path escapes archive root: {relpath!r}")
+    return resolved
+
+
+def wavelength_dirs(root, satellites=SATELLITES, wavelengths=WAVELENGTHS):
+    """Every ``suvi-l2-ciNNN`` directory that could hold frames, existing or not."""
+    return [
+        os.path.join(root, f"goes{sat:d}", "l2", "data", f"suvi-l2-ci{wl:03d}")
+        for sat in satellites
+        for wl in wavelengths
+    ]
diff --git a/suvi/vfs.py b/suvi/vfs.py
new file mode 100644
index 0000000..61efd2c
--- /dev/null
+++ b/suvi/vfs.py
@@ -0,0 +1,187 @@
+"""Working with the archive's virtiofs mount without exhausting it.
+
+The archive sits on a virtiofs share whose daemon holds a host file descriptor for
+every inode the guest has looked up.  Touching a few hundred thousand files fills the
+guest's dentry cache, the daemon runs out of descriptors, and the mount then returns
+ENFILE ("too many open files in system") for *any* subsequent open -- reads, writes,
+even starting a Python interpreter stored on it.  It does not recover on its own.
+
+The durable fix is host-side (``virtiofsd --inode-file-handles=prefer``, which stores
+compact handles instead of descriptors).  Until that is in place, anything that
+enumerates a large part of the archive has to periodically hand the descriptors back,
+which means persuading the guest kernel to evict dentries so it sends FORGET.
+
+Note that ``vm.vfs_cache_pressure`` does **not** do this.  It biases which caches the
+kernel drops once it has decided to reclaim; it does not cause reclaim.  On a machine
+with free memory the kernel never feels pressure, so the dentry cache grows unbounded
+whatever that setting says.  Reclaim has to be asked for explicitly.
+"""
+
+import atexit
+
+#: Operations between reclaims during a long traversal.  Low enough that the mount
+#: never approaches its ceiling, high enough that the cost is amortised.
+RELIEF_INTERVAL = 12_000
+
+
+def drop_caches():
+    """Ask the kernel to free dentries and inodes.  True if it worked.
+
+    Needs root, and is worth having it: this is direct and instant, where the
+    fallback has to allocate tens of gigabytes to provoke the same reclaim.  Run
+    long traversals under sudo and they will take this path.
+    """
+    try:
+        with open("/proc/sys/vm/drop_caches", "w") as handle:
+            handle.write("2\n")  # 2 = dentries and inodes; page cache is not the issue
+        return True
+    except OSError:
+        return False
+
+
+def reclaimable_kb():
+    """Size of the reclaimable slab, which is where dentries and inodes live."""
+    try:
+        with open("/proc/meminfo") as handle:
+            for line in handle:
+                if line.startswith("SReclaimable:"):
+                    return int(line.split()[1])
+    except (OSError, ValueError, IndexError):
+        pass
+    return 0
+
+
+def available_gib():
+    """Memory the kernel thinks can be handed out without swapping."""
+    try:
+        with open("/proc/meminfo") as handle:
+            for line in handle:
+                if line.startswith("MemAvailable:"):
+                    return int(line.split()[1]) / (1024 * 1024)
+    except (OSError, ValueError, IndexError):
+        pass
+    return 0.0
+
+
+#: Memory left unclaimed by the fallback, in GiB.  Pressure has to be genuine to
+#: make the kernel reclaim slab at all, so this is a *reserve* rather than a
+#: fraction: capping at some proportion of available memory always leaves headroom,
+#: the kernel never feels squeezed, and the allocation frees nothing while still
+#: costing the machine several gigabytes -- worse than not trying.
+RELIEF_RESERVE_GIB = 2.0
+#: Absolute cap, so a machine with vast memory does not get an unbounded allocation.
+RELIEF_MAX_GIB = 48
+
+
+#: Below this much reclaimable slab there is nothing worth freeing -- it is the
+#: working set of live processes, not archive inodes.  Pushing memory down to the
+#: reserve to shave a few hundred megabytes off it costs the machine far more than
+#: it gains, and during a long job this runs every RELIEF_INTERVAL items.
+RELIEF_FLOOR_KB = 1024 * 1024  # 1 GiB
+
+
+def release_handles(budget_gib=None, reserve_gib=RELIEF_RESERVE_GIB,
+                    floor_kb=RELIEF_FLOOR_KB):
+    """Force the kernel to shrink its dentry/inode cache.  True if anything was freed.
+
+    Prefers ``drop_caches``; falls back to allocating memory until the reclaimable
+    slab actually shrinks, or until only `reserve_gib` remains available.
+
+    Two things make the fallback awkward, both learned the hard way:
+
+    * A *fixed* budget silently does nothing once the machine has free memory --
+      10 GiB against 17 GiB free reclaims zero while reporting success.
+    * A budget capped at a *fraction* of available memory has the same failure for
+      the same reason: it never applies real pressure.  14 GiB of a 23 GiB
+      allowance freed nothing at all.
+
+    So it pushes until the kernel actually gives ground, stopping at a fixed reserve
+    rather than a proportion, and reports honestly whether the slab moved.
+    """
+    if drop_caches():
+        return True
+
+    before = reclaimable_kb()
+    if before <= 0:
+        return False
+    if before < floor_kb:
+        return True  # already small; nothing here is worth the memory churn
+
+    target = before // 2
+    if budget_gib is None:
+        budget_gib = RELIEF_MAX_GIB
+    blocks = []
+    try:
+        for _ in range(int(budget_gib)):
+            if reclaimable_kb() <= target:
+                return True
+            if available_gib() <= reserve_gib:
+                break  # as much pressure as is safe to apply
+            blocks.append(bytearray(1024 * 1024 * 1024))
+    except MemoryError:
+        pass
+    finally:
+        blocks.clear()
+    return reclaimable_kb() <= target
+
+
+class Reliever:
+    """Hands file handles back periodically during a bulk traversal.
+
+    Every long pass over the archive -- indexing, detecting, filling, rendering --
+    accumulates dentries that pin handles in the host's virtiofs daemon, and the
+    mount eventually refuses *every* open, taking unrelated software on the machine
+    down with it.  Reclaim was originally wired only into the migration and the
+    index build; the bench jobs, which run for hours over tens of thousands of
+    frames, had none, and duly exhausted the mount.
+
+    Bulk loops construct one of these and call :meth:`tick` per item.
+    """
+
+    def __init__(self, interval=RELIEF_INTERVAL, enabled=True, label="", on_exit=True):
+        self.interval = interval
+        self.enabled = enabled
+        self.label = label
+        self.on_exit = on_exit
+        self.seen = 0
+        self.releases = 0
+        self._next = interval
+        self._registered = False
+
+    def tick(self, count=1):
+        """Record `count` items processed, reclaiming if enough have gone by."""
+        self.seen += count
+        if self.enabled and self.on_exit and not self._registered:
+            # Reclaiming only *during* a run leaves the machine loaded once it ends:
+            # the inodes a traversal cached stay pinned, and with them the host's
+            # file handles, until something else forces reclaim.  Every bulk job has
+            # to hand them back when it finishes, not merely while it runs.
+            atexit.register(self.finish)
+            self._registered = True
+        if not self.enabled or self.seen < self._next:
+            return False
+        self._next = self.seen + self.interval
+        self._release("after {} items".format(self.seen))
+        return True
+
+    def finish(self):
+        """Reclaim once at the end of a run.  Idempotent; safe to call twice."""
+        if not self.enabled or self.seen == 0:
+            return False
+        self.enabled = False  # nothing more to do for this traversal
+        self._release("on finish, {} items".format(self.seen))
+        return True
+
+    def _release(self, why):
+        freed = release_handles()
+        self.releases += 1
+        if self.label:
+            print(f"  [{self.label}] reclaimed handles {why} "
+                  f"({'ok' if freed else 'no change'})", flush=True)
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, *exc):
+        self.finish()
+        return False
diff --git a/tests/conftest.py b/tests/conftest.py
new file mode 100644
index 0000000..ea95cff
--- /dev/null
+++ b/tests/conftest.py
@@ -0,0 +1,115 @@
+"""Shared fixtures.
+
+Tests build their own FITS files rather than reading the archive, so the suite runs
+anywhere and cannot be perturbed by (or perturb) the real data.
+"""
+
+import os
+import sys
+
+import numpy as np
+import pytest
+from astropy.io import fits
+
+sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
+
+from suvi import paths  # noqa: E402
+
+
+def solar_disc(size=1280, radius=386, centre=None, peak=1.0, background=0.01,
+               active_region=True):
+    """A synthetic SUVI-like frame: a bright limb-darkened disc on a dim corona.
+
+    An off-centre active region is included by default, because a perfectly
+    symmetric disc is invariant under rotation and reflection and would silently
+    pass tests for corruptions that flip or rotate the frame.  Real SUVI frames are
+    never symmetric, and that asymmetry is what displaces the brightness centroid.
+    """
+    centre = centre if centre is not None else ((size - 1) / 2.0, (size - 1) / 2.0)
+    yy, xx = np.mgrid[0:size, 0:size].astype(np.float32)
+    r = np.hypot(xx - centre[0], yy - centre[1])
+    disc = np.zeros((size, size), dtype=np.float32)
+    inside = r < radius
+    # Limb darkening keeps the radial profile non-trivial so geometry checks bite.
+    disc[inside] = peak * (0.4 + 0.6 * np.sqrt(np.clip(1 - (r[inside] / radius) ** 2, 0, 1)))
+    corona = background * np.exp(-np.clip(r - radius, 0, None) / (radius / 4.0))
+    image = disc + corona
+    if active_region:
+        spot_r = np.hypot(xx - (centre[0] + radius * 0.35), yy - (centre[1] - radius * 0.3))
+        image = image + peak * 0.25 * np.exp(-((spot_r / (radius * 0.16)) ** 2)) * inside
+    return image.astype(np.float32)
+
+
+def write_fits(path, data, headers=None, compress=True, checksum=True):
+    """Write a SUVI-shaped FITS file: empty primary + (compressed) image extension."""
+    header = fits.Header()
+    header["DATE-BEG"] = "2024-05-10T00:00:00.000"
+    header["DATE-OBS"] = "2024-05-10T00:00:21.000"
+    header["DATE-END"] = "2024-05-10T00:00:31.000"
+    header["WAVELNTH"] = 171
+    header["EXPTIME"] = 1.0
+    header["CRPIX1"] = (data.shape[1] + 1) / 2.0
+    header["CRPIX2"] = (data.shape[0] + 1) / 2.0
+    header["CDELT1"] = 2.5
+    header["CDELT2"] = 2.5
+    header["CROTA"] = 0.0
+    header["DSUN_OBS"] = 148781338180.972
+    header["SOLAR_B0"] = -7.170855
+    header["DIAM_SUN"] = 771.9772
+    header["YAW_FLIP"] = 0
+    header["ECLIPSE"] = 0
+    header["EMPTY"] = False
+    header["DEGRADED"] = False
+    header["NUM_IMGS"] = 2
+    header["N_LONG"] = 1
+    header["N_SHORT"] = 0
+    header["N_SH_FL"] = 1
+    finite = data[np.isfinite(data)]
+    header["IMG_MIN"] = float(finite.min()) if finite.size else 0.0
+    header["IMG_MAX"] = float(finite.max()) if finite.size else 0.0
+    header["IMG_MEAN"] = float(finite.mean()) if finite.size else 0.0
+    header["IMG_SDEV"] = float(finite.std()) if finite.size else 0.0
+    header["BUNIT"] = "W m-2 sr-1"
+    for key, value in (headers or {}).items():
+        header[key] = value
+
+    if compress:
+        hdu = fits.CompImageHDU(data=data, header=header, compression_type="GZIP_2")
+    else:
+        hdu = fits.ImageHDU(data=data, header=header)
+    hdulist = fits.HDUList([fits.PrimaryHDU(), hdu])
+    os.makedirs(os.path.dirname(path), exist_ok=True)
+    hdulist.writeto(path, overwrite=True, checksum=checksum)
+    return path
+
+
+@pytest.fixture
+def archive(tmp_path):
+    """An empty archive root with SUVI_DATA_ROOT pointed at it."""
+    root = tmp_path / "Data"
+    root.mkdir()
+    old = os.environ.get("SUVI_DATA_ROOT")
+    os.environ["SUVI_DATA_ROOT"] = str(root)
+    yield root
+    if old is None:
+        os.environ.pop("SUVI_DATA_ROOT", None)
+    else:
+        os.environ["SUVI_DATA_ROOT"] = old
+
+
+@pytest.fixture
+def db_path(tmp_path):
+    return str(tmp_path / "index.sqlite")
+
+
+@pytest.fixture
+def frame_name():
+    return paths.parse_frame_filename(
+        "dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits"
+    )
+
+
+@pytest.fixture
+def good_frame(tmp_path):
+    """A healthy synthetic frame on disk."""
+    return write_fits(str(tmp_path / "frames" / "good.fits"), solar_disc())
diff --git a/tests/test_cases.py b/tests/test_cases.py
new file mode 100644
index 0000000..f47fdb9
--- /dev/null
+++ b/tests/test_cases.py
@@ -0,0 +1,381 @@
+import os
+
+import pytest
+
+from conftest import solar_disc, write_fits
+from suvi import cases, corruptions, paths
+
+T0 = 1715299200  # 2024-05-10 00:00 UTC
+SATS = (16, 18)
+BANDS = (171, 304)
+
+
+def populate(root, slots, label="f"):
+    """Write minimal frames for the given slots into a fake archive."""
+    written = {}
+    for satellite, wavelength, when in slots:
+        name = paths.FrameName(satellite, wavelength, when, when + paths.CADENCE, "1-0-2")
+        path = os.path.join(str(root), *name.relpath(label).split("/"))
+        write_fits(path, solar_disc(size=64, radius=20, peak=3.0))
+        written[name.slot] = path
+    return written
+
+
+def grid(count, satellites=SATS, wavelengths=BANDS, start=T0):
+    return [
+        (satellite, wavelength, start + index * paths.CADENCE)
+        for index in range(count)
+        for satellite in satellites
+        for wavelength in wavelengths
+    ]
+
+
+# ----------------------------------------------------------------------- scanning
+
+
+def test_scan_window_finds_frames_and_labels(archive):
+    populate(archive, grid(3))
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + 3 * paths.CADENCE)
+    assert len(found) == 12
+    path, label = found[(16, 171, T0)]
+    assert label == "f" and os.path.exists(path)
+
+
+def test_scan_window_respects_the_time_bounds(archive):
+    populate(archive, grid(5))
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + 2 * paths.CADENCE)
+    assert {slot[2] for slot in found} == {T0, T0 + paths.CADENCE}
+
+
+def test_scan_window_ignores_unrelated_files(archive):
+    populate(archive, grid(1))
+    stray = os.path.join(str(archive), "goes16/l2/data/suvi-l2-ci171/2024/05/10/notes.txt")
+    open(stray, "w").write("not a frame")
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + paths.CADENCE)
+    assert len(found) == 4
+
+
+def test_scan_window_handles_a_missing_archive(tmp_path):
+    assert cases.scan_window(str(tmp_path), SATS, BANDS, T0, T0 + 240) == {}
+
+
+def test_scan_window_spans_a_day_boundary(archive):
+    midnight = 1715299200 - 2 * paths.CADENCE  # last slots of the previous day
+    populate(archive, [(16, 171, midnight + i * paths.CADENCE) for i in range(4)])
+    found = cases.scan_window(str(archive), (16,), (171,), midnight, midnight + 4 * 240)
+    assert len(found) == 4
+
+
+# --------------------------------------------------------------------------- runs
+
+
+def test_timeline_covers_the_window():
+    assert cases.timeline(T0, T0 + 3 * paths.CADENCE) == [
+        T0, T0 + paths.CADENCE, T0 + 2 * paths.CADENCE
+    ]
+
+
+def test_find_runs_reports_the_longest_first(archive):
+    slots = grid(10)
+    # Punch a hole at index 4 for one band on one satellite.
+    slots = [s for s in slots if s != (16, 171, T0 + 4 * paths.CADENCE)]
+    populate(archive, slots)
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + 10 * paths.CADENCE)
+    runs = cases.find_runs(found, SATS, BANDS, T0, T0 + 10 * paths.CADENCE, minimum=2)
+    assert runs[0][0] == 5  # indices 5..9
+    assert runs[1][0] == 4  # indices 0..3
+
+
+def test_find_runs_ignores_labels_by_default(archive):
+    """Labels are stale, so completeness is what select-window reports."""
+    populate(archive, grid(6), label="e")  # everything marked bad by the old filter
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + 6 * paths.CADENCE)
+    assert cases.find_runs(found, SATS, BANDS, T0, T0 + 6 * paths.CADENCE, minimum=2)
+    assert not cases.find_runs(
+        found, SATS, BANDS, T0, T0 + 6 * paths.CADENCE, minimum=2, require_good_label=True
+    )
+
+
+def test_slot_is_good_treats_unlabelled_as_unknown(archive):
+    populate(archive, grid(1), label=None)
+    found = cases.scan_window(str(archive), SATS, BANDS, T0, T0 + paths.CADENCE)
+    assert cases.slot_is_good(found, 16, 171, T0) is None
+    assert cases.slot_is_good(found, 16, 171, T0 + 9999) is None
+
+
+# --------------------------------------------------------------------------- plan
+
+
+def test_plan_validates_its_inputs():
+    cases.InjectionPlan().validate()
+    with pytest.raises(ValueError, match="fraction"):
+        cases.InjectionPlan(fraction=1.5).validate()
+    with pytest.raises(ValueError, match="gap_lengths"):
+        cases.InjectionPlan(gap_lengths=(0,)).validate()
+    with pytest.raises(ValueError, match="satellite_scope"):
+        cases.InjectionPlan(satellite_scope="g99").validate()
+    with pytest.raises(ValueError, match="wavelength_scope"):
+        cases.InjectionPlan(wavelength_scope="some").validate()
+    with pytest.raises(ValueError, match="unknown corruption"):
+        cases.InjectionPlan(modes=("nonsense",)).validate()
+    with pytest.raises(ValueError, match="severity"):
+        cases.InjectionPlan(severity=(0.9, 0.1)).validate()
+
+
+def test_plan_round_trips_through_a_dict():
+    plan = cases.InjectionPlan(fraction=0.2, satellite_scope="both", modes=("delete",))
+    assert cases.InjectionPlan.from_dict(plan.as_dict()) == plan
+
+
+def test_injections_are_deterministic():
+    slots = set(grid(200))
+    first = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=7)
+    second = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=7)
+    assert first == second
+
+
+def test_a_different_seed_gives_a_different_plan():
+    slots = set(grid(200))
+    first = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=1)
+    second = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=2)
+    assert first != second
+
+
+def test_injections_leave_the_window_edges_intact():
+    """Every damaged slot needs good frames either side to be reconstructed from."""
+    slots = set(grid(200))
+    times = sorted({slot[2] for slot in slots})
+    injections = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=3)
+    damaged = {i.slot[2] for i in injections}
+    assert damaged.isdisjoint(times[: cases.EDGE_MARGIN])
+    assert damaged.isdisjoint(times[-cases.EDGE_MARGIN :])
+
+
+def test_gaps_stay_separated():
+    slots = set(grid(300))
+    times = sorted({slot[2] for slot in slots})
+    index_of = {when: i for i, when in enumerate(times)}
+    injections = cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=5)
+    damaged = sorted(index_of[i.slot[2]] for i in {(j.slot[2],): j for j in injections}.values())
+    runs = []
+    for position in damaged:
+        if runs and position == runs[-1][-1] + 1:
+            runs[-1].append(position)
+        else:
+            runs.append([position])
+    for earlier, later in zip(runs, runs[1:]):
+        assert later[0] - earlier[-1] > cases.MIN_SEPARATION
+
+
+def test_gap_metadata_is_recorded():
+    slots = set(grid(200))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(gap_lengths=(5,)), slots, SATS, BANDS, seed=9
+    )
+    assert injections
+    for injection in injections:
+        assert injection.gap_length == 5
+        assert 0 <= injection.gap_index < 5
+        assert injection.mode == "delete" or injection.mode in corruptions.CATALOG
+
+
+def test_satellite_scope_both_damages_each_satellite_together():
+    slots = set(grid(200))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(satellite_scope="both"), slots, SATS, BANDS, seed=11
+    )
+    by_time = {}
+    for injection in injections:
+        by_time.setdefault(injection.slot[2], set()).add(injection.slot[0])
+    assert all(sats == set(SATS) for sats in by_time.values())
+
+
+def test_satellite_scope_can_target_one_spacecraft():
+    slots = set(grid(200))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(satellite_scope="g18"), slots, SATS, BANDS, seed=11
+    )
+    assert {i.slot[0] for i in injections} == {18}
+
+
+def test_wavelength_scope_one_damages_a_single_band():
+    slots = set(grid(200))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(wavelength_scope="one"), slots, SATS, BANDS, seed=13
+    )
+    by_time = {}
+    for injection in injections:
+        by_time.setdefault(injection.slot[2], set()).add(injection.slot[1])
+    assert all(len(bands) == 1 for bands in by_time.values())
+
+
+def test_zero_fraction_plans_nothing():
+    slots = set(grid(200))
+    assert cases.plan_injections(
+        cases.InjectionPlan(fraction=0.0), slots, SATS, BANDS, seed=1
+    ) == []
+
+
+def test_a_window_too_short_to_damage():
+    slots = set(grid(4))
+    assert cases.plan_injections(cases.InjectionPlan(), slots, SATS, BANDS, seed=1) == []
+
+
+# ------------------------------------------------------------------------ overlay
+
+
+def build_overlay():
+    archive = {(16, 171, T0 + i * 240): (f"/archive/{i}.fits", "f") for i in range(5)}
+    return cases.Overlay(
+        archive=archive,
+        overrides={(16, 171, T0 + 240): "/overlay/1.fits"},
+        deleted=frozenset({(16, 171, T0 + 480)}),
+    )
+
+
+def test_overlay_passes_untouched_slots_through():
+    assert build_overlay().path((16, 171, T0)) == "/archive/0.fits"
+
+
+def test_overlay_redirects_corrupted_slots():
+    assert build_overlay().path((16, 171, T0 + 240)) == "/overlay/1.fits"
+
+
+def test_overlay_hides_deleted_slots():
+    assert build_overlay().path((16, 171, T0 + 480)) is None
+
+
+def test_overlay_always_exposes_the_original_for_scoring():
+    overlay = build_overlay()
+    assert overlay.truth_path((16, 171, T0 + 240)) == "/archive/1.fits"
+    assert overlay.truth_path((16, 171, T0 + 480)) == "/archive/2.fits"
+
+
+def test_overlay_reports_an_unknown_slot_as_absent():
+    assert build_overlay().path((99, 999, 0)) is None
+
+
+def test_overlay_series_is_ordered_and_filtered():
+    overlay = cases.Overlay(
+        archive={
+            (16, 171, T0 + 480): ("/c", None),
+            (16, 171, T0): ("/a", None),
+            (18, 171, T0 + 240): ("/b", None),
+        }
+    )
+    assert overlay.series(16, 171) == [(16, 171, T0), (16, 171, T0 + 480)]
+    assert overlay.series(18, 171) == [(18, 171, T0 + 240)]
+
+
+# ------------------------------------------------------------------ long gaps
+
+
+def test_separation_scales_with_gap_length():
+    """Four clean slots is enough beside a 2-frame gap and useless beside a 300."""
+    assert cases.gap_separation(1) == cases.MIN_SEPARATION
+    assert cases.gap_separation(6) == cases.MIN_SEPARATION
+    assert cases.gap_separation(300) == 75
+    assert cases.gap_separation(100) == 25
+
+
+def test_long_gaps_keep_clean_brackets():
+    slots = set(grid(1200))
+    times = sorted({s[2] for s in slots})
+    index_of = {t: i for i, t in enumerate(times)}
+    injections = cases.plan_injections(
+        cases.InjectionPlan(fraction=0.3, gap_lengths=(3, 30, 100)),
+        slots, SATS, BANDS, seed=5,
+    )
+    damaged = sorted({index_of[i.slot[2]] for i in injections})
+
+    runs = []
+    for position in damaged:
+        if runs and position == runs[-1][-1] + 1:
+            runs[-1].append(position)
+        else:
+            runs.append([position])
+    for earlier, later in zip(runs, runs[1:]):
+        needed = cases.gap_separation(len(earlier))
+        assert later[0] - earlier[-1] > needed, (
+            f"a {len(earlier)}-slot gap had only {later[0] - earlier[-1]} clean "
+            f"slots before the next, needs more than {needed}"
+        )
+
+
+def test_a_window_too_short_for_the_gaps_is_refused():
+    """Silently planning nothing would report results for lengths never tested."""
+    slots = set(grid(50))
+    with pytest.raises(ValueError, match="usable slots"):
+        cases.plan_injections(
+            cases.InjectionPlan(gap_lengths=(300,)), slots, SATS, BANDS, seed=1
+        )
+
+
+def test_long_gaps_actually_get_placed():
+    """Longest-first placement: a 300 laid down last would rarely find room."""
+    slots = set(grid(2600))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(fraction=0.25, gap_lengths=(1, 2, 3, 10, 30, 100, 300)),
+        slots, SATS, BANDS, seed=7,
+    )
+    placed = {i.gap_length for i in injections}
+    assert 300 in placed, "the longest gap never got placed"
+    assert placed & {1, 2, 3}, "short gaps were crowded out"
+
+
+def test_gap_lengths_span_short_and_long():
+    slots = set(grid(2600))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(fraction=0.25, gap_lengths=(1, 2, 3, 10, 30, 100, 300)),
+        slots, SATS, BANDS, seed=3,
+    )
+    lengths = {i.gap_length for i in injections}
+    assert min(lengths) <= 3 and max(lengths) >= 100
+
+
+def test_gaps_per_length_places_the_requested_count():
+    """A fraction budget is eaten by the longest gaps, leaving one of each.
+
+    An earlier case ended up 84% a single 300-slot gap of a single mode, which
+    measures that mode at that length and nothing else.
+    """
+    slots = set(grid(2600))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(gap_lengths=(1, 3, 10), gaps_per_length=4),
+        slots, SATS, BANDS, seed=4,
+    )
+    counts = {}
+    for injection in injections:
+        key = (injection.gap_length, injection.slot[2] - injection.gap_index * paths.CADENCE)
+        counts.setdefault(injection.gap_length, set()).add(key[1])
+    assert counts[1] == counts[1] and len(counts[1]) == 4
+    assert len(counts[3]) == 4
+    assert len(counts[10]) == 4
+
+
+def test_gaps_per_length_overrides_the_fraction():
+    slots = set(grid(2600))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(fraction=0.001, gap_lengths=(10,), gaps_per_length=3),
+        slots, SATS, BANDS, seed=6,
+    )
+    starts = {i.slot[2] - i.gap_index * paths.CADENCE for i in injections}
+    assert len(starts) == 3, "the tiny fraction should have been ignored"
+
+
+def test_modes_are_cycled_not_resampled():
+    """With few gaps, independent draws repeat and leave the catalogue untested."""
+    slots = set(grid(2600))
+    injections = cases.plan_injections(
+        cases.InjectionPlan(gap_lengths=(2,), gaps_per_length=8), slots, SATS, BANDS, seed=8
+    )
+    starts = {}
+    for injection in injections:
+        starts.setdefault(injection.slot[2] - injection.gap_index * paths.CADENCE,
+                          injection.mode)
+    assert len(set(starts.values())) == len(starts), "a mode was reused across gaps"
+
+
+def test_plan_with_gaps_per_length_round_trips():
+    plan = cases.InjectionPlan(gaps_per_length=5)
+    assert cases.InjectionPlan.from_dict(plan.as_dict()).gaps_per_length == 5
diff --git a/tests/test_comparison_video.py b/tests/test_comparison_video.py
new file mode 100644
index 0000000..99aa8ce
--- /dev/null
+++ b/tests/test_comparison_video.py
@@ -0,0 +1,165 @@
+"""Tests for assembling the three-pane comparison video.
+
+The property that matters is *alignment*: a variant that produced no composite for a
+timestamp -- which is exactly what the current pipeline does past its gap limit --
+must still occupy that slot, or its pane slides out of step with the others and the
+comparison is meaningless.
+"""
+
+import os
+
+import numpy as np
+from PIL import Image
+
+import make_comparison_video as mcv
+from suvi import paths
+
+T0 = 1715299200
+
+
+def write_stream(root, variant, satellite, timestamps, size=(64, 36)):
+    directory = os.path.join(root, variant, f"goes{satellite}")
+    os.makedirs(directory, exist_ok=True)
+    for when in timestamps:
+        img = Image.fromarray(np.full((size[1], size[0], 3), 40, dtype="uint8"))
+        img.save(os.path.join(directory, f"Composite-{when}.jpg"), quality=90)
+    return directory
+
+
+def test_stream_frames_reads_timestamps(tmp_path):
+    times = [T0, T0 + paths.CADENCE, T0 + 2 * paths.CADENCE]
+    directory = write_stream(str(tmp_path), "pristine", 16, times)
+    frames = mcv.stream_frames(directory)
+    assert sorted(frames) == times
+    assert all(os.path.exists(p) for p in frames.values())
+
+
+def test_stream_frames_ignores_other_files(tmp_path):
+    directory = write_stream(str(tmp_path), "new", 16, [T0])
+    open(os.path.join(directory, "notes.txt"), "w").write("x")
+    open(os.path.join(directory, "Composite-nonsense.jpg"), "w").write("x")
+    assert list(mcv.stream_frames(directory)) == [T0]
+
+
+def test_stream_frames_on_a_missing_directory(tmp_path):
+    assert mcv.stream_frames(str(tmp_path / "absent")) == {}
+
+
+def test_every_variant_is_labelled():
+    assert set(mcv.LABELS) == set(mcv.VARIANTS)
+    assert all(mcv.LABELS[v] for v in mcv.VARIANTS)
+
+
+def test_encode_emits_one_frame_per_slot_including_gaps(tmp_path, monkeypatch):
+    """A pane with holes must still be full length, or the panes drift apart.
+
+    'today' legitimately has none for long gaps; those slots have to become black
+    frames occupying the timeline, not vanish from it.
+    """
+    times = [T0, T0 + 2 * paths.CADENCE]  # slot 1 deliberately missing
+    directory = write_stream(str(tmp_path), "today", 16, times)
+    frames = mcv.stream_frames(directory)
+    timeline = [T0 + i * paths.CADENCE for i in range(3)]
+
+    written = []
+
+    class FakeProcess:
+        def __init__(self):
+            self.stdin = self
+
+        def write(self, data):
+            written.append(("real", len(data)))
+
+        def save(self, *a, **k):
+            pass
+
+        def close(self):
+            pass
+
+        def wait(self):
+            return 0
+
+    fake = FakeProcess()
+    monkeypatch.setattr(mcv.subprocess, "Popen", lambda *a, **k: fake)
+
+    class CountingImage:
+        size = (64, 36)
+
+        @staticmethod
+        def fromarray(arr):
+            class Blank:
+                def save(self, handle, *a, **k):
+                    written.append(("black", 0))
+            return Blank()
+
+        @staticmethod
+        def open(path):
+            return CountingImage
+
+    monkeypatch.setattr(mcv, "Image", CountingImage)
+
+    present = mcv.encode_stream("ffmpeg", frames, timeline, "out.mp4", 60, 18)
+    assert present == 2
+    assert len(written) == 3, "a missing slot did not occupy the timeline"
+    assert [kind for kind, _ in written] == ["real", "black", "real"]
+
+
+# ------------------------------------------------------ pristine reads the truth
+
+
+def test_pristine_resolves_deleted_slots_from_the_archive(tmp_path):
+    """The ground-truth pane must show the window as it really is.
+
+    A slot the case deleted has no overlay path.  Resolving pristine through the
+    overlay silently drops those timestamps -- 221 of them in one run -- leaving the
+    reference pane shorter than the panes it exists to be compared against.
+    """
+    import bench
+    from suvi import cases
+
+    slot = (16, 171, T0)
+    overlay = cases.Overlay(
+        archive={slot: ("/archive/real.fits", None)},
+        overrides={},
+        deleted=frozenset({slot}),
+    )
+    assert overlay.path(slot) is None, "precondition: the case deleted this slot"
+    assert overlay.truth_path(slot) == "/archive/real.fits"
+
+    reads = []
+
+    def fake_read(path):
+        reads.append(path)
+        return "pixels", None
+
+    original = bench.fitsio.read_image
+    bench.fitsio.read_image = fake_read
+    try:
+        cache = {}
+        assert bench._resolve_band(overlay, slot, cache, use_truth=True) == "pixels"
+        assert reads == ["/archive/real.fits"]
+        # Without use_truth the slot is genuinely gone, which is right for the
+        # variants that are meant to show the damage.
+        assert bench._resolve_band(overlay, slot, cache, use_truth=False) is None
+    finally:
+        bench.fitsio.read_image = original
+
+
+def test_resolve_band_caches_truth_and_overlay_separately(tmp_path):
+    """One cache serving both would return the wrong frame for one of them."""
+    import bench
+    from suvi import cases
+
+    slot = (16, 171, T0)
+    overlay = cases.Overlay(
+        archive={slot: ("/archive/real.fits", None)},
+        overrides={slot: "/overlay/damaged.fits"},
+    )
+    original = bench.fitsio.read_image
+    bench.fitsio.read_image = lambda path: (path, None)
+    try:
+        cache = {}
+        assert bench._resolve_band(overlay, slot, cache, use_truth=True) == "/archive/real.fits"
+        assert bench._resolve_band(overlay, slot, cache, use_truth=False) == "/overlay/damaged.fits"
+    finally:
+        bench.fitsio.read_image = original
diff --git a/tests/test_composite.py b/tests/test_composite.py
new file mode 100644
index 0000000..71631fb
--- /dev/null
+++ b/tests/test_composite.py
@@ -0,0 +1,90 @@
+"""Tests for the composite renderer.
+
+The blending in ``merger_FITS`` is the product's visual identity -- years of tuning
+that no test can meaningfully assert the *correctness* of.  What these tests protect
+is that it does not change: it was lifted out of a worker loop so the bench could
+render reconstructed frames, and the only thing that makes such a refactor safe is
+proof the pixels came out the same.
+"""
+
+import numpy as np
+import pytest
+
+import merger_FITS as M
+from conftest import solar_disc
+
+
+@pytest.fixture
+def six_bands():
+    """Six distinct 1280x1280 bands, bright enough to exercise every blend stage."""
+    return [
+        solar_disc(peak=peak, radius=386, active_region=True)
+        for peak in (0.06, 0.12, 1.2, 1.6, 1.2, 3.0)
+    ]
+
+
+def test_renders_a_composite_of_the_expected_shape(six_bands):
+    img = M.composite_from_arrays(six_bands, 1715212800)
+    # 1280 trimmed by 2*64 in x and 2*100 in y, then padded by a third either side.
+    assert img.size == (1920, 1080)
+    assert img.mode == "RGB"
+
+
+def test_rendering_is_deterministic(six_bands):
+    first = M.composite_from_arrays(six_bands, 1715212800).tobytes()
+    second = M.composite_from_arrays(six_bands, 1715212800).tobytes()
+    assert first == second
+
+
+def test_the_timestamp_is_drawn_on_the_image(six_bands):
+    """Two timestamps must differ only where the caption is."""
+    a = np.asarray(M.composite_from_arrays(six_bands, 1715212800))
+    b = np.asarray(M.composite_from_arrays(six_bands, 1715299200))
+    assert not np.array_equal(a, b)
+    # The caption sits in the top strip; everything below it is identical.
+    assert np.array_equal(a[60:], b[60:])
+
+
+def test_every_band_contributes(six_bands):
+    """Changing any one band must change the output.
+
+    Guards against an indexing slip in the extracted function silently dropping a
+    band -- the composite would still render, and still look plausible.
+    """
+    reference = np.asarray(M.composite_from_arrays(six_bands, 1715212800))
+    for index in range(6):
+        altered = list(six_bands)
+        altered[index] = altered[index] * 1.5
+        assert not np.array_equal(
+            np.asarray(M.composite_from_arrays(altered, 1715212800)), reference
+        ), f"band {index} made no difference to the composite"
+
+
+def test_band_order_matters(six_bands):
+    """The six arrays are positional; a caller passing them shuffled must not match."""
+    shuffled = [six_bands[i] for i in (5, 4, 3, 2, 1, 0)]
+    assert not np.array_equal(
+        np.asarray(M.composite_from_arrays(shuffled, 1715212800)),
+        np.asarray(M.composite_from_arrays(six_bands, 1715212800)),
+    )
+
+
+def test_render_assets_are_built_once():
+    """The first four colormaps are mutated in place, so building twice would
+    re-apply the mutation to already-mutated objects."""
+    first = M._render_assets()
+    second = M._render_assets()
+    assert first is second
+    assert first["cmaps"][0] is second["cmaps"][0]
+
+
+def test_tolerates_a_filled_frame_containing_no_signal(six_bands):
+    """Reconstructed frames can be blank; rendering must not raise on them."""
+    blanked = list(six_bands)
+    blanked[2] = np.zeros_like(blanked[2])
+    img = M.composite_from_arrays(blanked, 1715212800)
+    assert img.size == (1920, 1080)
+
+
+def test_mapping_constants_line_up_with_the_bands():
+    assert len(M.VMINS) == len(M.VMAXS) == len(M.GAMMAS) == len(M.image_names) == 6
diff --git a/tests/test_corruptions.py b/tests/test_corruptions.py
new file mode 100644
index 0000000..30a6e41
--- /dev/null
+++ b/tests/test_corruptions.py
@@ -0,0 +1,209 @@
+import numpy as np
+import pytest
+
+from conftest import solar_disc, write_fits
+from suvi import corruptions, fitsio
+
+ARRAY_MODES = [n for n, c in corruptions.CATALOG.items() if c.kind == "array"]
+FILE_MODES = [n for n, c in corruptions.CATALOG.items() if c.kind == "file"]
+
+
+@pytest.fixture
+def image():
+    return solar_disc(peak=3.0)
+
+
+@pytest.fixture
+def donor():
+    return solar_disc(peak=3.0, centre=(700, 640))
+
+
+def apply(name, image, donor=None, seed=7, severity=1.0):
+    return corruptions.apply_array(name, image, seed, severity, donor)
+
+
+# ------------------------------------------------------------------------ catalogue
+
+
+def test_catalogue_covers_all_four_groups():
+    assert set(corruptions.GROUPS) == {"dropout", "structural", "radiometric", "geometric"}
+    for group in corruptions.GROUPS:
+        assert corruptions.by_group(group), f"{group} has no modes"
+
+
+def test_every_entry_is_self_consistent():
+    for name, corruption in corruptions.CATALOG.items():
+        assert corruption.name == name
+        assert corruption.kind in ("array", "file")
+        assert callable(corruption.apply)
+
+
+# -------------------------------------------------------------------- determinism
+
+
+@pytest.mark.parametrize("name", ARRAY_MODES)
+def test_array_corruptions_are_deterministic(name, image, donor):
+    first, header_a = apply(name, image, donor)
+    second, header_b = apply(name, image, donor)
+    np.testing.assert_array_equal(np.nan_to_num(first), np.nan_to_num(second))
+    assert header_a == header_b
+
+
+@pytest.mark.parametrize("name", ARRAY_MODES)
+def test_array_corruptions_change_the_data(name, image, donor):
+    damaged, _ = apply(name, image, donor)
+    assert damaged.shape == image.shape
+    assert not np.array_equal(np.nan_to_num(damaged), np.nan_to_num(image))
+
+
+@pytest.mark.parametrize("name", ARRAY_MODES)
+def test_different_seeds_stay_reproducible(name, image, donor):
+    first, _ = apply(name, image, donor, seed=1)
+    again, _ = apply(name, image, donor, seed=1)
+    np.testing.assert_array_equal(np.nan_to_num(first), np.nan_to_num(again))
+
+
+@pytest.mark.parametrize("name", FILE_MODES)
+def test_file_corruptions_are_deterministic(name, tmp_path, image):
+    path = write_fits(str(tmp_path / "src.fits"), image)
+    raw = open(path, "rb").read()
+    first = corruptions.apply_file(name, raw, 7, 1.0)
+    second = corruptions.apply_file(name, raw, 7, 1.0)
+    assert first == second
+    assert first != raw
+
+
+# ------------------------------------------------------------------ specific modes
+
+
+def test_eclipse_dim_reproduces_the_real_failure(image):
+    """The archive's commonest fault: radiance collapses, flags are set."""
+    damaged, header = apply("eclipse_dim", image)
+    assert header["DEGRADED"] is True and header["ECLIPSE"] == 2
+    assert abs(float(damaged.mean())) < float(image.mean()) / 1000
+
+
+def test_all_zero_sets_the_empty_flag(image):
+    damaged, header = apply("all_zero", image)
+    assert not damaged.any() and header["EMPTY"] is True
+
+
+def test_nan_fill_at_full_severity_covers_everything(image):
+    damaged, _ = apply("nan_fill", image, severity=1.0)
+    assert np.isnan(damaged).all()
+
+
+def test_nan_fill_at_partial_severity_is_partial(image):
+    damaged, _ = apply("nan_fill", image, severity=0.3)
+    fraction = np.isnan(damaged).mean()
+    assert 0.1 < fraction < 0.5
+
+
+def test_zblank_fill_uses_the_fits_sentinel(image):
+    damaged, _ = apply("zblank_fill", image, severity=1.0)
+    assert (damaged == fitsio.ZBLANK).all()
+
+
+def test_frozen_returns_the_donor_exactly(image, donor):
+    damaged, _ = apply("frozen", image, donor)
+    np.testing.assert_array_equal(damaged, donor)
+
+
+def test_torn_frame_mixes_two_observations(image, donor):
+    damaged, _ = apply("torn_frame", image, donor, severity=1.0)
+    assert np.array_equal(damaged[-1], donor[-1])
+    assert np.array_equal(damaged[0], image[0])
+
+
+def test_dropped_rows_blanks_whole_scan_lines(image):
+    damaged, _ = apply("dropped_rows", image, severity=1.0)
+    blank = [row for row in range(damaged.shape[0]) if not damaged[row].any()]
+    assert len(blank) >= 1
+
+
+def test_yaw_flip_is_a_180_degree_rotation(image):
+    damaged, header = apply("yaw_flip", image)
+    assert header["YAW_FLIP"] == 1
+    np.testing.assert_array_equal(damaged, np.flip(np.flip(image, 0), 1))
+
+
+def test_translate_moves_the_disc_and_updates_the_wcs(image):
+    damaged, header = apply("translate", image, severity=1.0)
+    assert "CRPIX1" in header and "CRPIX2" in header
+    assert not np.array_equal(damaged, image)
+
+
+def test_saturate_raises_the_ceiling(image):
+    damaged, _ = apply("saturate", image, severity=1.0)
+    assert float(damaged.max()) > float(image.max())
+
+
+def test_modes_requiring_a_donor_say_so(image):
+    for name, corruption in corruptions.CATALOG.items():
+        if corruption.needs_donor:
+            with pytest.raises(ValueError, match="donor"):
+                corruptions.apply_array(name, image, 1, 1.0, None)
+
+
+def test_truncate_keeps_at_least_one_block(tmp_path, image):
+    path = write_fits(str(tmp_path / "src.fits"), image)
+    raw = open(path, "rb").read()
+    damaged = corruptions.apply_file("truncate", raw, 1, 1.0)
+    assert fitsio.BLOCK <= len(damaged) < len(raw)
+
+
+def test_drop_image_hdu_leaves_only_the_primary_header(tmp_path, image):
+    path = write_fits(str(tmp_path / "src.fits"), image)
+    raw = open(path, "rb").read()
+    damaged = corruptions.apply_file("drop_image_hdu", raw, 1, 1.0)
+    assert len(damaged) == fitsio.BLOCK
+    out = str(tmp_path / "damaged.fits")
+    open(out, "wb").write(damaged)
+    data, error = fitsio.read_image(out)
+    assert data is None and error
+
+
+def test_block_corruption_leaves_the_header_readable(tmp_path, image):
+    """Simulates bit rot: the header still parses, the data no longer matches it."""
+    path = write_fits(str(tmp_path / "src.fits"), image)
+    raw = open(path, "rb").read()
+    damaged = corruptions.apply_file("block_corruption", raw, 3, 1.0)
+    out = str(tmp_path / "damaged.fits")
+    open(out, "wb").write(damaged)
+    cards, error = fitsio.read_header(out)
+    assert cards.get("WAVELNTH") == 171
+    assert "datasum mismatch" in fitsio.verify_datasums(out)
+
+
+# ---------------------------------------------------------------------- interface
+
+
+def test_wrong_kind_is_rejected(image, tmp_path):
+    with pytest.raises(ValueError, match="not an array one"):
+        corruptions.apply_array("truncate", image, 1)
+    with pytest.raises(ValueError, match="not a file one"):
+        corruptions.apply_file("eclipse_dim", b"x" * 3000, 1)
+
+
+def test_unknown_mode_raises(image):
+    with pytest.raises(KeyError):
+        corruptions.apply_array("does_not_exist", image, 1)
+
+
+def test_recomputed_stats_match_the_damaged_pixels(image):
+    stats = corruptions.recomputed_stats(image)
+    assert stats["IMG_MEAN"] == pytest.approx(float(image.mean()), rel=1e-5)
+    assert stats["IMG_MAX"] == pytest.approx(float(image.max()), rel=1e-5)
+
+
+def test_recomputed_stats_survive_an_all_nan_frame():
+    stats = corruptions.recomputed_stats(np.full((4, 4), np.nan, np.float32))
+    assert stats == {"IMG_MIN": 0.0, "IMG_MAX": 0.0, "IMG_MEAN": 0.0, "IMG_SDEV": 0.0}
+
+
+def test_stats_are_recomputed_only_where_the_header_would_follow():
+    """A real eclipse has a matching header; bit rot does not.  See the module docs."""
+    assert corruptions.CATALOG["eclipse_dim"].recompute_stats is True
+    assert corruptions.CATALOG["gain_shift"].recompute_stats is True
+    assert corruptions.CATALOG["block_corruption"].recompute_stats is False
+    assert corruptions.CATALOG["salt_pepper"].recompute_stats is False
diff --git a/tests/test_db.py b/tests/test_db.py
new file mode 100644
index 0000000..ab88d75
--- /dev/null
+++ b/tests/test_db.py
@@ -0,0 +1,285 @@
+import multiprocessing
+import sqlite3
+
+import pytest
+
+from suvi import db, paths
+
+
+def make_frame(conn, satellite=16, wavelength=171, minute=0):
+    t_start = 1715299200 + minute * paths.CADENCE
+    name = paths.FrameName(
+        satellite=satellite,
+        wavelength=wavelength,
+        t_start=t_start,
+        t_end=t_start + paths.CADENCE,
+        version="1-0-2",
+    )
+    return db.upsert_frame(conn, name, name.relpath(), size_bytes=1774080, mtime=1.0), name
+
+
+def test_connect_creates_schema(db_path):
+    conn = db.connect(db_path)
+    tables = {
+        row["name"]
+        for row in conn.execute("SELECT name FROM sqlite_master WHERE type='table'")
+    }
+    assert {"frame", "header", "detector_run", "detection", "remote_file", "meta"} <= tables
+    assert conn.execute(
+        "SELECT value FROM meta WHERE key='schema_version'"
+    ).fetchone()["value"] == str(db.SCHEMA_VERSION)
+    conn.close()
+
+
+def test_init_schema_is_idempotent(db_path):
+    conn = db.connect(db_path)
+    db.init_schema(conn)
+    db.init_schema(conn)
+    assert conn.execute("SELECT count(*) c FROM meta").fetchone()["c"] == 1
+    conn.close()
+
+
+def test_schema_version_mismatch_is_refused(db_path):
+    conn = db.connect(db_path)
+    conn.execute("UPDATE meta SET value='99' WHERE key='schema_version'")
+    conn.commit()
+    with pytest.raises(RuntimeError, match="schema version"):
+        db.init_schema(conn)
+    conn.close()
+
+
+def test_readonly_connect_requires_an_existing_file(tmp_path):
+    with pytest.raises(FileNotFoundError):
+        db.connect(str(tmp_path / "absent.sqlite"), readonly=True)
+
+
+def test_readonly_connect_cannot_write(db_path):
+    db.connect(db_path).close()
+    conn = db.connect(db_path, readonly=True)
+    with pytest.raises(sqlite3.OperationalError):
+        conn.execute("INSERT INTO meta (key, value) VALUES ('x', 'y')")
+    conn.close()
+
+
+def test_upsert_frame_is_stable_and_updates_in_place(db_path):
+    conn = db.connect(db_path)
+    first, name = make_frame(conn)
+    again = db.upsert_frame(conn, name, name.relpath(), size_bytes=999, mtime=2.0)
+    assert first == again
+    row = conn.execute("SELECT * FROM frame WHERE id=?", (first,)).fetchone()
+    assert row["size_bytes"] == 999 and row["mtime"] == 2.0
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 1
+    conn.close()
+
+
+def test_duplicate_slot_under_a_new_version_is_rejected(db_path):
+    """Two files claiming the same observation must not silently shadow each other."""
+    conn = db.connect(db_path)
+    _, name = make_frame(conn)
+    other = paths.FrameName(
+        name.satellite, name.wavelength, name.t_start, name.t_end, version="1-0-3"
+    )
+    with pytest.raises(sqlite3.IntegrityError):
+        db.upsert_frame(conn, other, other.relpath())
+    conn.close()
+
+
+def test_frame_id_by_slot(db_path):
+    conn = db.connect(db_path)
+    frame_id, name = make_frame(conn)
+    assert db.frame_id_by_slot(conn, *name.slot) == frame_id
+    assert db.frame_id_by_slot(conn, 18, 171, name.t_start) is None
+    conn.close()
+
+
+def test_detector_runs_are_ordered_by_recency(db_path):
+    conn = db.connect(db_path)
+    first = db.create_detector_run(conn, "header_v1", {"threshold": 1})
+    second = db.create_detector_run(conn, "header_v1", {"threshold": 2})
+    assert db.latest_run_id(conn, "header_v1") == second
+    assert first != second
+    assert db.latest_run_id(conn, "nope") is None
+    conn.close()
+
+
+def test_record_detections_stores_scores_and_upserts(db_path):
+    conn = db.connect(db_path)
+    frame_id, _ = make_frame(conn)
+    run = db.create_detector_run(conn, "header_v1", {})
+    db.record_detections(conn, run, [(frame_id, "bad", "eclipse", {"img_mean": 1e-4}, 12)])
+    db.record_detections(conn, run, [(frame_id, "good", None, {"img_mean": 0.3}, 15)])
+    conn.commit()
+    row = conn.execute("SELECT * FROM detection").fetchone()
+    assert row["verdict"] == "good"
+    assert row["reason"] is None
+    assert row["scores_json"] == '{"img_mean": 0.3}'
+    assert conn.execute("SELECT count(*) c FROM detection").fetchone()["c"] == 1
+    conn.close()
+
+
+def test_record_detections_rejects_unknown_verdicts(db_path):
+    conn = db.connect(db_path)
+    frame_id, _ = make_frame(conn)
+    run = db.create_detector_run(conn, "header_v1", {})
+    with pytest.raises(ValueError, match="Unknown verdict"):
+        db.record_detections(conn, run, [(frame_id, "maybe", None, None, 0)])
+    conn.close()
+
+
+def test_detections_cascade_when_a_run_is_deleted(db_path):
+    conn = db.connect(db_path)
+    frame_id, _ = make_frame(conn)
+    run = db.create_detector_run(conn, "header_v1", {})
+    db.record_detections(conn, run, [(frame_id, "good", None, None, 0)])
+    conn.execute("DELETE FROM detector_run WHERE id=?", (run,))
+    conn.commit()
+    assert conn.execute("SELECT count(*) c FROM detection").fetchone()["c"] == 0
+    conn.close()
+
+
+def test_good_slots_filters_by_verdict_window_and_band(db_path):
+    conn = db.connect(db_path)
+    run = db.create_detector_run(conn, "header_v1", {})
+    ids = {}
+    for minute in range(4):
+        for wavelength in (171, 304):
+            frame_id, name = make_frame(conn, wavelength=wavelength, minute=minute)
+            ids[(minute, wavelength)] = (frame_id, name)
+    # Everything good except one frame, plus a decoy on the other satellite.
+    db.record_detections(
+        conn,
+        run,
+        [
+            (fid, "bad" if key == (1, 171) else "good", None, None, 0)
+            for key, (fid, _) in ids.items()
+        ],
+    )
+    other, _ = make_frame(conn, satellite=18, minute=0)
+    db.record_detections(conn, run, [(other, "good", None, None, 0)])
+    conn.commit()
+
+    base = ids[(0, 171)][1].t_start
+    rows = db.good_slots(conn, run, base, base + 3 * paths.CADENCE, 16, (171,))
+    assert [r["t_start"] for r in rows] == [base, base + 2 * paths.CADENCE]
+    assert all(r["satellite"] == 16 and r["wavelength"] == 171 for r in rows)
+
+    both = db.good_slots(conn, run, base, base + 4 * paths.CADENCE, 16, (171, 304))
+    assert len(both) == 7  # 8 frames minus the one marked bad
+    conn.close()
+
+
+def test_unscanned_frames_lists_only_frames_without_headers(db_path):
+    conn = db.connect(db_path)
+    first, _ = make_frame(conn, minute=0)
+    second, _ = make_frame(conn, minute=1)
+    db.record_headers(conn, [(first, {"img_mean": 0.3, "eclipse": 0}, None)])
+    conn.commit()
+    assert [r["id"] for r in db.unscanned_frames(conn)] == [second]
+    assert len(db.unscanned_frames(conn, limit=0)) == 0
+    conn.close()
+
+
+def test_record_headers_round_trips_values_and_errors(db_path):
+    conn = db.connect(db_path)
+    first, _ = make_frame(conn, minute=0)
+    second, _ = make_frame(conn, minute=1)
+    db.record_headers(
+        conn,
+        [
+            (first, {"img_mean": 0.31, "degraded": 0, "datasum": "261950686"}, None),
+            (second, {}, "truncated: 17 bytes"),
+        ],
+    )
+    conn.commit()
+    good = conn.execute("SELECT * FROM header WHERE frame_id=?", (first,)).fetchone()
+    assert good["img_mean"] == pytest.approx(0.31)
+    assert good["read_ok"] == 1 and good["read_error"] is None
+    bad = conn.execute("SELECT * FROM header WHERE frame_id=?", (second,)).fetchone()
+    assert bad["read_ok"] == 0 and bad["read_error"].startswith("truncated")
+    assert bad["img_mean"] is None
+    conn.close()
+
+
+def test_record_headers_upserts(db_path):
+    conn = db.connect(db_path)
+    frame_id, _ = make_frame(conn)
+    db.record_headers(conn, [(frame_id, {"img_mean": 0.1}, None)])
+    db.record_headers(conn, [(frame_id, {"img_mean": 0.9}, None)])
+    conn.commit()
+    assert conn.execute("SELECT count(*) c FROM header").fetchone()["c"] == 1
+    assert conn.execute("SELECT img_mean FROM header").fetchone()["img_mean"] == 0.9
+    conn.close()
+
+
+def test_remote_file_round_trip(db_path):
+    conn = db.connect(db_path)
+    db.record_remote_files(conn, [("http://x/a.fits", 100.0, 17, "a.fits", 5.0)])
+    db.record_remote_files(conn, [("http://x/a.fits", 200.0, 18, "a.fits", 6.0)])
+    conn.commit()
+    assert db.get_remote_mtime(conn, "http://x/a.fits") == 200.0
+    assert db.get_remote_mtime(conn, "http://x/missing.fits") is None
+    assert conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"] == 1
+    conn.close()
+
+
+def test_writer_loop_drains_a_queue_from_another_process(db_path):
+    """Workers stay read-only; one writer owns the lock.  This is that contract."""
+    conn = db.connect(db_path)
+    frame_ids = [make_frame(conn, minute=i)[0] for i in range(20)]
+    run = db.create_detector_run(conn, "header_v1", {})
+    conn.commit()
+    conn.close()
+
+    ctx = multiprocessing.get_context("spawn")
+    queue = ctx.Queue()
+    writer = ctx.Process(target=db.writer_loop, args=(db_path, queue), daemon=True)
+    writer.start()
+    for frame_id in frame_ids:
+        queue.put(("detection", (run, frame_id, "good", None, {"s": 1}, 3)))
+    queue.put(("header", (frame_ids[0], {"img_mean": 0.5}, None)))
+    queue.put(("remote_file", ("http://x/a.fits", 1.0, 2, "a", 3.0)))
+    queue.put(db.STOP)
+    writer.join(timeout=60)
+    assert writer.exitcode == 0
+
+    conn = db.connect(db_path, readonly=True)
+    assert conn.execute("SELECT count(*) c FROM detection").fetchone()["c"] == 20
+    assert conn.execute("SELECT count(*) c FROM header").fetchone()["c"] == 1
+    assert conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"] == 1
+    conn.close()
+
+
+def test_writer_loop_rejects_unknown_message_kinds(db_path):
+    ctx = multiprocessing.get_context("spawn")
+    queue = ctx.Queue()
+    writer = ctx.Process(target=db.writer_loop, args=(db_path, queue), daemon=True)
+    writer.start()
+    queue.put(("bogus", ()))
+    writer.join(timeout=60)
+    assert writer.exitcode not in (0, None)
+
+
+def test_latest_run_is_scoped_by_config(db_path):
+    """Runs accumulate one per detector per case, so 'latest' is ambiguous.
+
+    Resolving a detector without its config picks whichever case ran most
+    recently -- and scoring one case's verdicts against another case's injections
+    gives numbers that are wrong, not merely noisy.
+    """
+    conn = db.connect(db_path)
+    first = db.create_detector_run(conn, "header_v1", {"case": "alpha"})
+    second = db.create_detector_run(conn, "header_v1", {"case": "beta"})
+
+    assert db.latest_run_id(conn, "header_v1") == second          # global latest
+    assert db.latest_run_id(conn, "header_v1", {"case": "alpha"}) == first
+    assert db.latest_run_id(conn, "header_v1", {"case": "beta"}) == second
+    assert db.latest_run_id(conn, "header_v1", {"case": "gamma"}) is None
+    conn.close()
+
+
+def test_scoped_lookup_takes_the_newest_matching_run(db_path):
+    conn = db.connect(db_path)
+    db.create_detector_run(conn, "disc_v1", {"case": "alpha"})
+    newer = db.create_detector_run(conn, "disc_v1", {"case": "alpha"})
+    assert db.latest_run_id(conn, "disc_v1", {"case": "alpha"}) == newer
+    conn.close()
diff --git a/tests/test_detectors.py b/tests/test_detectors.py
new file mode 100644
index 0000000..5ba6a6a
--- /dev/null
+++ b/tests/test_detectors.py
@@ -0,0 +1,476 @@
+import cv2 as cv
+import numpy as np
+import pytest
+
+from conftest import solar_disc
+from suvi import detectors
+
+BAND = 171
+
+
+def features(slot_band=BAND, time=1715299200, satellite=16, **header):
+    """A FrameFeatures whose header describes a healthy frame, before overrides."""
+    base = {
+        "empty": 0,
+        "degraded": 0,
+        "eclipse": 0,
+        "num_imgs": 2,
+        "wavelnth": slot_band,
+        "img_mean": 0.35,
+        "img_sdev": 0.57,
+        "diam_sun": 771.98,
+        "crpix1": 640.5,
+        "crpix2": 640.5,
+    }
+    base.update(header)
+    return detectors.FrameFeatures(slot=(satellite, slot_band, time), header=base)
+
+
+def bright_disc(**kwargs):
+    """A disc bright enough to clear the 171A geometry threshold of 1.0."""
+    return solar_disc(peak=3.0, **kwargs)
+
+
+# -------------------------------------------------------------------------- header
+
+
+def test_header_accepts_a_healthy_frame():
+    assert detectors.header_v1(features()).verdict == detectors.GOOD
+
+
+def test_header_records_scores_even_when_passing():
+    verdict = detectors.header_v1(features())
+    assert verdict.scores["img_mean"] == pytest.approx(0.35)
+    assert "crpix_offset" in verdict.scores
+
+
+@pytest.mark.parametrize(
+    "override,fragment",
+    [
+        ({"empty": 1}, "EMPTY"),
+        ({"eclipse": 2}, "ECLIPSE"),
+        ({"num_imgs": 0}, "no source images"),
+        ({"img_sdev": 0.0}, "zero variance"),
+        ({"wavelnth": 304}, "wavelength"),
+        ({"img_mean": 1e-5}, "below"),
+        ({"img_mean": 500.0}, "above"),
+        ({"diam_sun": 100.0}, "DIAM_SUN"),
+        ({"crpix1": 700.0}, "sun centre offset"),
+    ],
+)
+def test_header_rejects(override, fragment):
+    verdict = detectors.header_v1(features(**override))
+    assert verdict.verdict == detectors.BAD
+    assert fragment in verdict.reason
+
+
+def test_header_does_not_reject_on_degraded_alone():
+    """Regression: DEGRADED is set for whole months of the 195A band on good frames.
+
+    Rejecting on it discarded 40/40 good 195A frames on 2024-01-20 while flagging
+    0/40 on 2024-07-04.  It is recorded as a score and nothing more.
+    """
+    verdict = detectors.header_v1(features(degraded=1))
+    assert verdict.verdict == detectors.GOOD
+    assert verdict.scores["degraded"] == 1.0
+
+
+def test_header_reports_read_errors_as_bad():
+    frame = detectors.FrameFeatures(slot=(16, BAND, 0), header={}, error="truncated")
+    verdict = detectors.header_v1(frame)
+    assert verdict.verdict == detectors.BAD and "truncated" in verdict.reason
+
+
+def test_header_abstains_without_a_cached_header():
+    frame = detectors.FrameFeatures(slot=(16, BAND, 0), header={})
+    assert detectors.header_v1(frame).verdict == detectors.UNKNOWN
+
+
+def test_header_bounds_are_per_band():
+    """A radiance normal for 304A is a dropout for 94A."""
+    assert detectors.header_v1(features(slot_band=304, img_mean=3.0, wavelnth=304)).verdict == detectors.GOOD
+    assert detectors.header_v1(features(slot_band=94, img_mean=3.0, wavelnth=94)).verdict == detectors.BAD
+
+
+# ------------------------------------------------------------------------ geometry
+
+
+def test_geometry_accepts_a_synthetic_disc():
+    verdict = detectors.geometry_v1(bright_disc(), BAND)
+    assert verdict.verdict == detectors.GOOD, verdict.reason
+
+
+def test_geometry_rejects_a_blank_frame():
+    verdict = detectors.geometry_v1(np.zeros((1280, 1280), np.float32), BAND)
+    assert verdict.verdict == detectors.BAD and "too low" in verdict.reason
+
+
+def test_geometry_rejects_a_saturated_frame():
+    verdict = detectors.geometry_v1(np.full((1280, 1280), 99.0, np.float32), BAND)
+    assert verdict.verdict == detectors.BAD and "too high" in verdict.reason
+
+
+def test_geometry_rejects_a_displaced_disc():
+    verdict = detectors.geometry_v1(bright_disc(centre=(500, 640)), BAND)
+    assert verdict.verdict == detectors.BAD
+
+
+def test_geometry_reports_missing_and_misshapen_input():
+    assert detectors.geometry_v1(None, BAND).verdict == detectors.BAD
+    small = detectors.geometry_v1(np.zeros((64, 64), np.float32), BAND)
+    assert small.verdict == detectors.BAD and "dimensions" in small.reason
+
+
+def test_geometry_abstains_on_an_unknown_band():
+    verdict = detectors.geometry_v1(bright_disc(), 999)
+    assert verdict.verdict == detectors.UNKNOWN
+
+
+def test_geometry_centre_check_is_one_sided():
+    """Documents a real defect in the baseline, so a fix cannot land unnoticed.
+
+    The test is `HALF_DIMS//2 - centre > skew`, so brightness pulled toward low
+    indices rejects the frame while the same pull toward high indices passes.  This
+    asymmetry is why the filter rejects entire days during high solar activity.
+    """
+    low = detectors.geometry_v1(bright_disc(centre=(560, 640)), BAND)
+    high = detectors.geometry_v1(bright_disc(centre=(720, 640)), BAND)
+    assert low.scores["centre_x"] < detectors.HALF_DIMS // 2
+    assert high.scores["centre_x"] > detectors.HALF_DIMS // 2
+    assert low.verdict == detectors.BAD
+    assert high.verdict == detectors.GOOD  # symmetric displacement, opposite verdict
+
+
+def test_geometry_catches_an_all_nan_frame_only_by_luck():
+    """An all-NaN frame is caught by the ratio test, not by the shape tests.
+
+    `NaN > x` is False, so the centroid, radius and goodness-of-fit comparisons all
+    evaluate False and report "good" on NaN input.  Only the emptiness of the
+    threshold mask saves this case -- a frame that was partly NaN could still slip
+    through the shape checks.
+    """
+    verdict = detectors.geometry_v1(np.full((1280, 1280), np.nan, np.float32), BAND)
+    assert verdict.verdict == detectors.BAD
+    assert "too low" in verdict.reason
+
+    # Demonstrate the underlying blindness: NaN defeats each shape test directly.
+    assert not (detectors.HALF_DIMS // 2 - np.nan > detectors.MAX_CENTER_SKEW)
+    assert not (np.nan > detectors.MAX_GOF)
+
+
+# ------------------------------------------------------------------------ temporal
+
+
+def series(count=25, means=None, thumbs=None):
+    out = []
+    for index in range(count):
+        mean = 0.35 if means is None else means[index]
+        frame = detectors.FrameFeatures(
+            slot=(16, BAND, 1715299200 + index * 240),
+            header={"img_mean": mean},
+        )
+        if thumbs is not None:
+            frame.thumbnail = thumbs[index]
+        out.append(frame)
+    return out
+
+
+def drifting_thumbs(count, rng=None):
+    """Thumbnails that change a little each step, like the real Sun."""
+    rng = rng or np.random.default_rng(0)
+    base = solar_disc(size=detectors.THUMBNAIL_SIZE, radius=38, peak=1.0)
+    return [(base + rng.normal(0, 0.01, base.shape)).astype(np.float32) for _ in range(count)]
+
+
+def test_temporal_accepts_a_steady_series():
+    verdicts = detectors.temporal_v1(series(thumbs=drifting_thumbs(25)))
+    assert all(v.verdict == detectors.GOOD for v in verdicts)
+
+
+def test_temporal_catches_a_frozen_frame():
+    thumbs = drifting_thumbs(25)
+    thumbs[12] = thumbs[11].copy()  # the feed stalled
+    verdicts = detectors.temporal_v1(series(thumbs=thumbs))
+    assert verdicts[12].verdict == detectors.BAD
+    assert "identical to previous" in verdicts[12].reason
+
+
+def test_temporal_catches_a_brightness_step():
+    means = [0.35] * 25
+    means[12] = 3.5
+    verdicts = detectors.temporal_v1(series(means=means, thumbs=drifting_thumbs(25)))
+    assert verdicts[12].verdict == detectors.BAD
+
+
+def test_temporal_catches_a_structural_jump():
+    thumbs = drifting_thumbs(25)
+    thumbs[12] = np.roll(thumbs[12], 40, axis=0)  # a frame from somewhere else
+    verdicts = detectors.temporal_v1(series(thumbs=thumbs))
+    assert verdicts[12].verdict == detectors.BAD
+
+
+def test_temporal_reports_unreadable_frames():
+    frames = series(thumbs=drifting_thumbs(25))
+    frames[5].error = "truncated"
+    verdicts = detectors.temporal_v1(frames)
+    assert verdicts[5].verdict == detectors.BAD
+
+
+def test_temporal_abstains_without_context():
+    verdicts = detectors.temporal_v1(series(count=2))
+    assert all(v.verdict == detectors.UNKNOWN for v in verdicts)
+
+
+def test_temporal_handles_an_empty_series():
+    assert detectors.temporal_v1([]) == []
+
+
+# ------------------------------------------------------------------------ crosssat
+
+
+def cross_pair(scale_b=1.0, shift_b=0, noise=0.005):
+    rng = np.random.default_rng(1)
+    base = solar_disc(size=detectors.THUMBNAIL_SIZE, radius=38, peak=1.0)
+    a = (base + rng.normal(0, noise, base.shape)).astype(np.float32)
+    b = (base + rng.normal(0, noise, base.shape)).astype(np.float32) * scale_b
+    if shift_b:
+        b = np.roll(b, shift_b, axis=1)
+    first = detectors.FrameFeatures(slot=(16, BAND, 0), header={"img_mean": 0.35})
+    second = detectors.FrameFeatures(slot=(18, BAND, 0), header={"img_mean": 0.35})
+    first.thumbnail, second.thumbnail = a, b
+    return first, second
+
+
+def test_crosssat_agrees_on_matching_views():
+    a, b = cross_pair()
+    first, second = detectors.crosssat_v1(a, b)
+    assert first.verdict == detectors.GOOD and second.verdict == detectors.GOOD
+
+
+def test_crosssat_tolerates_calibration_differences():
+    """A modest scale factor between flight models is normal, not a fault."""
+    a, b = cross_pair(scale_b=1.3)
+    first, _ = detectors.crosssat_v1(a, b)
+    assert first.verdict == detectors.GOOD
+
+
+def test_crosssat_catches_a_blackout_despite_gain_matching():
+    """Regression: least-squares matching rescales a 1e-4 frame into agreement.
+
+    Without an explicit bound on the fitted gain this detector called a total
+    blackout a match, because the residual after rescaling is tiny.
+    """
+    a, b = cross_pair(scale_b=1e-4)
+    first, second = detectors.crosssat_v1(a, b)
+    assert detectors.BAD in (first.verdict, second.verdict) or first.verdict == detectors.UNKNOWN
+    assert "gain" in (first.reason or "")
+
+
+def test_crosssat_blames_the_frame_its_own_history_disowns():
+    a, b = cross_pair(scale_b=1e-4)
+    suspect = detectors.Verdict(detectors.BAD, "brightness z=40")
+    healthy = detectors.Verdict(detectors.GOOD)
+    first, second = detectors.crosssat_v1(a, b, temporal_a=healthy, temporal_b=suspect)
+    assert first.verdict == detectors.GOOD
+    assert second.verdict == detectors.BAD
+
+
+def test_crosssat_abstains_when_it_cannot_tell_which_is_wrong():
+    a, b = cross_pair(scale_b=1e-4)
+    first, second = detectors.crosssat_v1(a, b)
+    assert first.verdict == detectors.UNKNOWN and second.verdict == detectors.UNKNOWN
+
+
+def test_crosssat_abstains_without_a_counterpart():
+    a, _ = cross_pair()
+    first, second = detectors.crosssat_v1(a, None)
+    assert first.verdict == detectors.UNKNOWN and second.verdict == detectors.UNKNOWN
+
+
+def test_crosssat_abstains_without_thumbnails():
+    a = detectors.FrameFeatures(slot=(16, BAND, 0), header={})
+    b = detectors.FrameFeatures(slot=(18, BAND, 0), header={})
+    first, _ = detectors.crosssat_v1(a, b)
+    assert first.verdict == detectors.UNKNOWN
+
+
+# --------------------------------------------------------------------------- utils
+
+
+def test_thumbnail_shrinks_and_removes_nans():
+    image = solar_disc()
+    image[0:10, 0:10] = np.nan
+    thumb = detectors.thumbnail(image)
+    assert thumb.shape == (detectors.THUMBNAIL_SIZE, detectors.THUMBNAIL_SIZE)
+    assert np.isfinite(thumb).all()
+
+
+def test_align_shift_measures_a_known_translation():
+    base = solar_disc(size=128, radius=38)
+    shifted = np.roll(base, 5, axis=1)
+    assert detectors.align_shift(base, shifted) == pytest.approx(5.0, abs=1.0)
+    assert detectors.align_shift(base, base) == pytest.approx(0.0, abs=0.5)
+
+
+def test_align_shift_returns_none_on_mismatched_shapes():
+    assert detectors.align_shift(np.zeros((8, 8)), np.zeros((4, 4))) is None
+    assert detectors.align_shift(None, np.zeros((4, 4))) is None
+
+
+def test_robust_z_handles_a_constant_neighbourhood():
+    values = [1.0] * 10
+    assert detectors._robust_z(values, 5, 4) == 0.0
+    values[5] = 9.0
+    assert detectors._robust_z(values, 5, 4) == np.inf
+
+
+def test_robust_z_needs_enough_neighbours():
+    assert detectors._robust_z([1.0, 2.0], 0, 4) is None
+
+
+# ---------------------------------------------------------------------- disc_v1
+
+DISC_HEADER = {"diam_sun": 772.0}
+
+
+def quiet_disc(peak=1.1):
+    """A disc whose quiet regions sit near the 171A threshold, as real frames do."""
+    return solar_disc(peak=peak, active_region=False)
+
+
+def add_active_region(image, offset, strength=6.0, width=0.30, radius=386):
+    """Add a bright compact region at `offset` solar radii along +x from centre."""
+    yy, xx = np.mgrid[0 : image.shape[0], 0 : image.shape[1]].astype(np.float32)
+    centre = (image.shape[1] - 1) / 2.0
+    on_disc = np.hypot(xx - centre, yy - centre) < radius
+    spot = np.hypot(xx - (centre + radius * offset), yy - centre)
+    return image + strength * np.exp(-((spot / (radius * width)) ** 2)) * on_disc
+
+
+def test_disc_accepts_a_synthetic_disc():
+    assert detectors.disc_v1(bright_disc(), BAND, DISC_HEADER).verdict == detectors.GOOD
+
+
+def test_disc_measurements_are_unmoved_by_an_active_region():
+    """The whole point of the detector, and the fix for the 36.9% rejection rate.
+
+    Every disc_v1 measurement is an average over angle, so where the bright regions
+    sit does not move it.  geometry_v1 averages along image rows and columns
+    instead, so its centroid swings with the active region -- and because its centre
+    test is one-sided, an equal displacement is fatal on one limb and harmless on
+    the other.
+    """
+    base = quiet_disc()
+    left = add_active_region(base, -0.45)
+    right = add_active_region(base, +0.45)
+
+    measurements = [detectors.disc_profile(img, 772.0 / 4.0) for img in (base, left, right)]
+    for name in ("radius_ratio", "limb_width"):
+        values = [m[name] for m in measurements]
+        assert max(values) - min(values) < 1e-6, f"{name} moved: {values}"
+    contrasts = [m["limb_contrast"] for m in measurements]
+    assert max(contrasts) - min(contrasts) < 0.01
+
+    # Meanwhile the baseline's centroid swings, in opposite directions.
+    centroids = [detectors.geometry_v1(img, BAND).scores["centre_x"] for img in (left, base, right)]
+    assert centroids[0] < centroids[1] < centroids[2]
+    assert centroids[2] - centroids[0] > 5.0
+
+    for img in (base, left, right):
+        assert detectors.disc_v1(img, BAND, DISC_HEADER).verdict == detectors.GOOD
+
+
+@pytest.mark.parametrize(
+    "image,label",
+    [
+        (np.zeros((1280, 1280), np.float32), "all zero"),
+        (np.full((1280, 1280), np.nan, np.float32), "all NaN"),
+        (np.full((1280, 1280), 1.0, np.float32), "uniform field"),
+    ],
+)
+def test_disc_rejects_frames_with_no_disc(image, label):
+    """A frame with no radial structure is a conclusion, not an abstention."""
+    verdict = detectors.disc_v1(image, BAND, DISC_HEADER)
+    assert verdict.verdict == detectors.BAD, label
+    assert verdict.scores["limb_contrast"] == 0.0
+
+
+def test_disc_detects_a_wrong_sized_disc():
+    small = solar_disc(radius=300, peak=3.0, active_region=False)
+    measured = detectors.disc_profile(small, 772.0 / 4.0)
+    assert measured["radius_ratio"] < 0.85
+
+
+def test_disc_detects_a_displaced_disc_through_limb_smearing():
+    """A decentred disc smears the azimuthally averaged limb; that is the signal."""
+    base = solar_disc(peak=3.0, active_region=False)
+    sharp = detectors.disc_profile(base, 772.0 / 4.0)
+    for shift in (20, 40):
+        moved = detectors.disc_profile(np.roll(base, shift, axis=1), 772.0 / 4.0)
+        assert moved["limb_width"] > sharp["limb_width"] * 2, f"shift {shift}"
+
+
+def test_disc_detects_a_blurred_limb():
+    base = solar_disc(peak=3.0, active_region=False)
+    blurred = cv.GaussianBlur(base, (81, 81), 25)
+    assert (
+        detectors.disc_profile(blurred, 772.0 / 4.0)["limb_width"]
+        > detectors.disc_profile(base, 772.0 / 4.0)["limb_width"] * 2
+    )
+
+
+def test_disc_is_blind_to_rotation_by_construction():
+    """Documents a deliberate limit: rotate/yaw_flip belong to the other detectors.
+
+    Any azimuthally averaged quantity is rotation invariant, and a single frame
+    carries no absolute rotation reference beyond the CROTA header.
+    """
+    image = solar_disc(peak=3.0)
+    flipped = np.flip(np.flip(image, 0), 1).copy()
+    original = detectors.disc_profile(image, 772.0 / 4.0)
+    rotated = detectors.disc_profile(flipped, 772.0 / 4.0)
+    for name, value in original.items():
+        assert rotated[name] == pytest.approx(value, abs=1e-6), name
+
+
+def test_disc_abstains_without_the_expected_radius():
+    verdict = detectors.disc_v1(bright_disc(), BAND, {})
+    assert verdict.verdict == detectors.UNKNOWN and "DIAM_SUN" in verdict.reason
+
+
+def test_disc_abstains_on_an_uncalibrated_band():
+    verdict = detectors.disc_v1(bright_disc(), 999, DISC_HEADER)
+    assert verdict.verdict == detectors.UNKNOWN
+
+
+def test_disc_reports_a_missing_image():
+    assert detectors.disc_v1(None, BAND, DISC_HEADER).verdict == detectors.BAD
+
+
+def test_disc_profile_rejects_nonsense_input():
+    for image in (None, np.zeros((4, 4), np.float32), np.zeros((8, 8, 3), np.float32)):
+        assert detectors.disc_profile(image, 193.0)["limb_contrast"] is None
+    assert detectors.disc_profile(bright_disc(), 0)["limb_contrast"] is None
+    assert detectors.disc_profile(bright_disc(), np.nan)["limb_contrast"] is None
+
+
+def test_disc_honours_supplied_bounds():
+    """Bounds are per band and injectable, so calibration is testable in isolation."""
+    image = bright_disc()
+    permissive = {BAND: {"limb_contrast": (0.0, 1.0), "radius_ratio": None, "limb_width": None}}
+    strict = {BAND: {"limb_contrast": (0.999, 1.0), "radius_ratio": None, "limb_width": None}}
+    assert detectors.disc_v1(image, BAND, DISC_HEADER, permissive).verdict == detectors.GOOD
+    assert detectors.disc_v1(image, BAND, DISC_HEADER, strict).verdict == detectors.BAD
+
+
+def test_disc_bounds_set_to_none_record_a_score_without_judging():
+    image = bright_disc()
+    bounds = {BAND: {"limb_contrast": None, "radius_ratio": None, "limb_width": None}}
+    verdict = detectors.disc_v1(image, BAND, DISC_HEADER, bounds)
+    assert verdict.verdict == detectors.GOOD
+    assert "radius_ratio" in verdict.scores  # still measured and reported
+
+
+def test_disc_is_registered_as_a_frame_detector():
+    assert "disc_v1" in detectors.FRAME_DETECTORS
+    assert "disc_v1" in detectors.ALL_DETECTORS
diff --git a/tests/test_fillers.py b/tests/test_fillers.py
new file mode 100644
index 0000000..da02589
--- /dev/null
+++ b/tests/test_fillers.py
@@ -0,0 +1,215 @@
+import numpy as np
+import pytest
+
+from conftest import solar_disc
+from suvi import fillers
+
+HEADER = {
+    "crpix1": 640.5,
+    "crpix2": 640.5,
+    "cdelt1": 2.5,
+    "diam_sun": 771.98,
+    "dsun_obs": 148781338180.972,
+    "solar_b0": -7.170855,
+}
+
+
+def context(**kwargs):
+    base = dict(dt_before=240.0, dt_after=240.0, header=HEADER)
+    base.update(kwargs)
+    return fillers.FillContext(**base)
+
+
+# -------------------------------------------------------------------------- context
+
+
+def test_alpha_locates_the_frame_within_its_gap():
+    assert context(dt_before=240, dt_after=240).alpha == pytest.approx(0.5)
+    assert context(dt_before=240, dt_after=720).alpha == pytest.approx(0.25)
+    assert context(dt_before=0, dt_after=0).alpha == 0.0
+
+
+def test_gap_frames_counts_slots():
+    assert context(dt_before=240, dt_after=240).gap_frames == 2
+    assert context(dt_before=240, dt_after=2160).gap_frames == 10
+
+
+# --------------------------------------------------------------------- baselines
+
+
+def test_hold_last_repeats_the_preceding_frame():
+    before, after = np.ones((8, 8), np.float32), np.zeros((8, 8), np.float32)
+    np.testing.assert_array_equal(fillers.hold_last(context(before=before, after=after)), before)
+
+
+def test_hold_last_falls_back_to_the_following_frame():
+    after = np.full((8, 8), 3.0, np.float32)
+    np.testing.assert_array_equal(fillers.hold_last(context(after=after)), after)
+
+
+def test_hold_last_gives_up_with_nothing_to_hold():
+    assert fillers.hold_last(context()) is None
+
+
+def test_linear_blend_is_exact_on_a_linear_ramp():
+    """A quantity changing linearly in time must be recovered exactly."""
+    before = np.full((8, 8), 10.0, np.float32)
+    after = np.full((8, 8), 20.0, np.float32)
+    filled = fillers.linear_blend(context(before=before, after=after))
+    np.testing.assert_allclose(filled, 15.0, rtol=1e-6)
+
+    skewed = fillers.linear_blend(
+        context(before=before, after=after, dt_before=240, dt_after=720)
+    )
+    np.testing.assert_allclose(skewed, 12.5, rtol=1e-6)
+
+
+def test_linear_blend_degrades_to_hold_last_at_a_boundary():
+    before = np.full((8, 8), 7.0, np.float32)
+    np.testing.assert_array_equal(fillers.linear_blend(context(before=before)), before)
+
+
+def test_fillers_tolerate_non_finite_input():
+    before = np.full((8, 8), np.nan, np.float32)
+    after = np.ones((8, 8), np.float32)
+    filled = fillers.linear_blend(context(before=before, after=after))
+    assert np.isfinite(filled).all()
+
+
+# ------------------------------------------------------------------ optical flow
+
+
+def test_optical_flow_tracks_a_translation():
+    """A feature moving at constant speed should land mid-way, not appear twice."""
+    base = solar_disc(size=256, radius=70, peak=3.0)
+    before = np.roll(base, -8, axis=1)
+    after = np.roll(base, 8, axis=1)
+    filled = fillers.optical_flow(context(before=before, after=after))
+    blended = fillers.linear_blend(context(before=before, after=after))
+    # The truth is the untranslated frame; flow should beat a plain cross-fade.
+    assert np.abs(filled - base).mean() < np.abs(blended - base).mean()
+
+
+def test_optical_flow_falls_back_without_two_brackets():
+    before = np.ones((32, 32), np.float32)
+    np.testing.assert_array_equal(fillers.optical_flow(context(before=before)), before)
+
+
+def test_optical_flow_falls_back_on_mismatched_shapes():
+    before = np.ones((32, 32), np.float32)
+    after = np.ones((16, 16), np.float32)
+    result = fillers.optical_flow(context(before=before, after=after))
+    np.testing.assert_array_equal(result, before)
+
+
+# ---------------------------------------------------------------------- crosssat
+
+
+def test_crosssat_returns_nothing_without_a_counterpart():
+    assert fillers.crosssat(context(before=np.ones((8, 8), np.float32))) is None
+
+
+def test_crosssat_corrects_the_calibration_difference():
+    """The other satellite's radiance scale must be matched, not copied blindly."""
+    truth = solar_disc(size=128, radius=38, peak=2.0)
+    counterpart = truth * 0.5 + 0.3  # a different flight model's response
+    filled = fillers.crosssat(context(before=truth, counterpart=counterpart), align=False)
+    np.testing.assert_allclose(filled, truth, atol=1e-3)
+
+
+def test_crosssat_aligns_a_parallax_shift():
+    truth = solar_disc(size=128, radius=38, peak=2.0)
+    counterpart = np.roll(truth, 4, axis=1)
+    filled = fillers.crosssat(context(before=truth, counterpart=counterpart), align=True)
+    unaligned = fillers.crosssat(context(before=truth, counterpart=counterpart), align=False)
+    assert np.abs(filled - truth).mean() < np.abs(unaligned - truth).mean()
+
+
+def test_gain_match_recovers_an_affine_transform():
+    source = solar_disc(size=64, radius=20, peak=1.0)
+    reference = source * 3.0 - 0.5
+    np.testing.assert_allclose(fillers.gain_match(source, reference), reference, atol=1e-4)
+
+
+def test_gain_match_survives_a_constant_source():
+    flat = np.ones((8, 8), np.float32)
+    result = fillers.gain_match(flat, np.arange(64, dtype=np.float32).reshape(8, 8))
+    assert np.isfinite(result).all()
+
+
+# --------------------------------------------------------------- solar rotation
+
+
+def test_rotation_rate_is_fastest_at_the_equator():
+    equator = fillers.rotation_rate(0.0)
+    mid = fillers.rotation_rate(np.radians(45))
+    pole = fillers.rotation_rate(np.radians(80))
+    assert equator > mid > pole
+
+
+def test_synodic_rate_is_slower_than_sidereal():
+    """An Earth-orbiting observer sees the Sun turn more slowly than the stars do."""
+    assert fillers.rotation_rate(0.0, synodic=True) < fillers.rotation_rate(0.0, synodic=False)
+    difference = fillers.rotation_rate(0.0, synodic=False) - fillers.rotation_rate(0.0, True)
+    assert difference == pytest.approx(fillers.EARTH_ORBIT_DEG_PER_DAY)
+
+
+def test_rotation_map_is_the_identity_at_zero_lag():
+    shape = (128, 128)
+    header = dict(HEADER, crpix1=64.5, crpix2=64.5, diam_sun=76.0)
+    map_x, map_y, visible = fillers._rotation_map(shape, header, 0.0)
+    grid_x, grid_y = np.meshgrid(np.arange(shape[1]), np.arange(shape[0]))
+    np.testing.assert_allclose(map_x[visible], grid_x[visible], atol=0.01)
+    np.testing.assert_allclose(map_y[visible], grid_y[visible], atol=0.01)
+
+
+def test_rotation_map_marks_the_off_disc_region_invisible():
+    header = dict(HEADER, crpix1=64.5, crpix2=64.5, diam_sun=76.0)
+    _, _, visible = fillers._rotation_map((128, 128), header, 0.0)
+    assert not visible[0, 0]  # a corner is outside the disc
+    assert visible[64, 64]  # disc centre
+
+
+def test_rotation_warp_round_trips():
+    """Warping forward by dt then back by dt must return the original on-disc."""
+    header = dict(HEADER, crpix1=64.5, crpix2=64.5, diam_sun=76.0)
+    image = solar_disc(size=128, radius=38, peak=2.0)
+    forward, visible = fillers._warp(image, header, 3600.0, True)
+    back, visible_back = fillers._warp(forward, header, -3600.0, True)
+    core = np.zeros_like(visible)
+    core[50:78, 50:78] = True  # well inside the disc, away from limb foreshortening
+    np.testing.assert_allclose(back[core], image[core], atol=0.05)
+
+
+def test_solar_rotation_reduces_to_a_blend_off_disc():
+    header = dict(HEADER, crpix1=64.5, crpix2=64.5, diam_sun=76.0)
+    before = np.full((128, 128), 1.0, np.float32)
+    after = np.full((128, 128), 3.0, np.float32)
+    filled = fillers.solar_rotation(context(before=before, after=after, header=header))
+    assert filled[0, 0] == pytest.approx(2.0, abs=1e-4)  # corner: pure cross-fade
+
+
+def test_solar_rotation_handles_a_single_bracket():
+    header = dict(HEADER, crpix1=64.5, crpix2=64.5, diam_sun=76.0)
+    image = solar_disc(size=128, radius=38, peak=2.0)
+    filled = fillers.solar_rotation(context(before=image, header=header))
+    assert filled is not None and filled.shape == image.shape
+
+
+def test_solar_rotation_gives_up_with_no_brackets():
+    assert fillers.solar_rotation(context()) is None
+
+
+# ---------------------------------------------------------------------- registry
+
+
+def test_every_registered_filler_is_callable_and_shape_preserving():
+    before = solar_disc(size=64, radius=20, peak=2.0)
+    after = solar_disc(size=64, radius=20, peak=2.2)
+    header = dict(HEADER, crpix1=32.5, crpix2=32.5, diam_sun=40.0)
+    ctx = context(before=before, after=after, counterpart=after, header=header)
+    for name, filler in fillers.FILLERS.items():
+        result = filler(ctx)
+        assert result is not None, name
+        assert result.shape == before.shape, name
+        assert np.isfinite(result).all(), name
diff --git a/tests/test_fitsio.py b/tests/test_fitsio.py
new file mode 100644
index 0000000..3107eb3
--- /dev/null
+++ b/tests/test_fitsio.py
@@ -0,0 +1,229 @@
+import numpy as np
+import pytest
+from astropy.io import fits
+
+from conftest import solar_disc, write_fits
+from suvi import fitsio
+
+
+@pytest.fixture
+def disc():
+    return solar_disc()
+
+
+def corrupt(path, tmp_path, name, transform):
+    raw = open(path, "rb").read()
+    out = str(tmp_path / name)
+    with open(out, "wb") as handle:
+        handle.write(transform(raw))
+    return out
+
+
+# ------------------------------------------------------------------ value parsing
+
+
+@pytest.mark.parametrize(
+    "raw,expected",
+    [
+        ("                   T / comment", True),
+        ("                   F", False),
+        ("                 171 / [angstrom]", 171),
+        ("                 2.5 / arcsec", 2.5),
+        ("7.40304005902818E-05 / [W m-2]", pytest.approx(7.40304005902818e-05)),
+        ("1.5D3 / fortran exponent", 1500.0),
+        ("'UTC     '           / principal time system", "UTC"),
+        ("'W m-2 sr-1'", "W m-2 sr-1"),
+        ("'0       '           / data unit checksum", "0"),
+        ("'it''s quoted'       / embedded quote", "it's quoted"),
+        ("'a / b'              / slash inside string", "a / b"),
+        ("", None),
+        ("              -999999", -999999),
+    ],
+)
+def test_parse_value(raw, expected):
+    assert fitsio._parse_value(raw) == expected
+
+
+# ------------------------------------------------------------------ header reading
+
+
+def test_reads_header_of_a_compressed_image(good_frame):
+    cards, error = fitsio.read_header(good_frame)
+    assert error is None
+    assert cards["WAVELNTH"] == 171
+    assert cards["ZIMAGE"] is True
+    assert cards["ZNAXIS1"] == 1280
+    assert cards["DEGRADED"] is False
+    assert cards["IMG_MEAN"] > 0
+
+
+def test_reads_header_of_an_uncompressed_image(tmp_path, disc):
+    path = write_fits(str(tmp_path / "plain.fits"), disc, compress=False)
+    cards, error = fitsio.read_header(path)
+    assert error is None
+    assert cards["NAXIS"] == 2 and cards["NAXIS1"] == 1280
+    assert cards["WAVELNTH"] == 171
+
+
+def test_header_metadata_projects_onto_db_columns(good_frame):
+    values, error = fitsio.scan_header(good_frame)
+    assert error is None
+    # Booleans become 0/1 so SQL can filter on them.
+    assert values["degraded"] == 0 and values["eclipse"] == 0 and values["empty"] == 0
+    assert values["wavelnth"] == 171
+    assert isinstance(values["img_mean"], float)
+    assert isinstance(values["datasum"], str)
+    assert set(values) <= set(fitsio.db.HEADER_FIELDS)
+
+
+def test_header_metadata_drops_wrongly_typed_cards():
+    values = fitsio.header_metadata({"IMG_MEAN": "not a number", "WAVELNTH": 171})
+    assert "img_mean" not in values
+    assert values["wavelnth"] == 171
+
+
+def test_flags_are_read_from_a_degraded_frame(tmp_path, disc):
+    """The real eclipse failure mode: near-zero radiance with DEGRADED/ECLIPSE set."""
+    path = write_fits(
+        str(tmp_path / "eclipse.fits"),
+        disc * 1e-4,
+        headers={"DEGRADED": True, "ECLIPSE": 2},
+    )
+    values, error = fitsio.scan_header(path)
+    assert error is None
+    assert values["degraded"] == 1 and values["eclipse"] == 2
+    assert values["img_mean"] < 1e-3
+
+
+# ----------------------------------------------------------------------- integrity
+
+
+def test_empty_file(tmp_path):
+    path = str(tmp_path / "empty.fits")
+    open(path, "wb").close()
+    cards, error = fitsio.read_header(path)
+    assert cards == {} and error == "empty file"
+
+
+def test_missing_file(tmp_path):
+    cards, error = fitsio.read_header(str(tmp_path / "absent.fits"))
+    assert cards == {} and "unreadable" in error
+
+
+def test_not_a_fits_file(tmp_path):
+    path = str(tmp_path / "junk.fits")
+    open(path, "wb").write(b"X" * 5000)
+    cards, error = fitsio.read_header(path)
+    assert cards == {} and "missing SIMPLE" in error
+
+
+def test_shorter_than_one_block(tmp_path, good_frame):
+    path = corrupt(good_frame, tmp_path, "tiny.fits", lambda raw: raw[:100])
+    _, error = fitsio.read_header(path)
+    assert "truncated" in error
+
+
+def test_truncation_not_on_a_block_boundary_is_reported(tmp_path, good_frame):
+    path = corrupt(good_frame, tmp_path, "odd.fits", lambda raw: raw[:-100])
+    _, error = fitsio.read_header(path)
+    assert "not a multiple of 2880" in error
+
+
+def test_header_without_end_card(tmp_path, good_frame):
+    """A header whose END is gone must not be parsed as if it were complete."""
+    path = corrupt(
+        good_frame, tmp_path, "noend.fits", lambda raw: raw.replace(b"END     ", b"XXX     ")
+    )
+    cards, error = fitsio.read_header(path)
+    assert cards == {} and "END" in error
+
+
+def test_primary_only_file_has_no_image_hdu(tmp_path):
+    path = str(tmp_path / "primary.fits")
+    fits.HDUList([fits.PrimaryHDU()]).writeto(path, overwrite=True)
+    cards, error = fitsio.read_header(path)
+    assert "no image HDU" in error
+
+
+def test_max_header_bytes_is_respected(good_frame):
+    """A malformed file must not pull unbounded data into memory."""
+    cards, error = fitsio.read_header(good_frame, max_bytes=fitsio.BLOCK)
+    assert cards == {} or error is not None
+
+
+# ------------------------------------------------------------------------ datasums
+
+
+def test_datasum_matches_the_stored_keyword(good_frame):
+    assert fitsio.verify_datasums(good_frame) is None
+
+
+def test_datasum_detects_a_flipped_bit(tmp_path, good_frame):
+    def flip(raw):
+        offset = len(raw) - fitsio.BLOCK  # inside the final data unit
+        return raw[:offset] + bytes([raw[offset] ^ 0xFF]) + raw[offset + 1 :]
+
+    path = corrupt(good_frame, tmp_path, "flipped.fits", flip)
+    assert "datasum mismatch" in fitsio.verify_datasums(path)
+
+
+def test_datasum_detects_truncation(tmp_path, good_frame):
+    path = corrupt(good_frame, tmp_path, "half.fits", lambda raw: raw[: len(raw) // 2])
+    assert "truncated" in fitsio.verify_datasums(path)
+
+
+def test_datasum_reports_when_no_keywords_are_present(tmp_path, disc):
+    path = write_fits(str(tmp_path / "nosum.fits"), disc, checksum=False)
+    assert fitsio.verify_datasums(path) == "no DATASUM keywords present"
+
+
+def test_datasum_on_a_non_fits_file(tmp_path):
+    path = str(tmp_path / "junk.fits")
+    open(path, "wb").write(b"nope" * 1000)
+    assert fitsio.verify_datasums(path) == "not a FITS file"
+
+
+def test_datasum_is_the_fits_ones_complement_sum():
+    # Two words that overflow 32 bits, forcing an end-around carry.
+    payload = (0xFFFFFFFF).to_bytes(4, "big") + (0x00000002).to_bytes(4, "big")
+    assert fitsio.datasum(payload) == 2
+    assert fitsio.datasum(b"") == 0
+    # A trailing partial word is zero-padded on the right: 0x00000001 + 0x01000000.
+    assert fitsio.datasum(b"\x00\x00\x00\x01\x01") == 0x01000001
+
+
+# --------------------------------------------------------------------- image reads
+
+
+def test_reads_pixel_data(good_frame, disc):
+    data, error = fitsio.read_image(good_frame)
+    assert error is None
+    assert data.shape == (1280, 1280) and data.dtype == np.float32
+    assert np.allclose(data, disc, atol=1e-3)
+
+
+def test_zblank_becomes_nan(tmp_path, disc):
+    holed = disc.copy()
+    holed[10:20, 10:20] = fitsio.ZBLANK
+    path = write_fits(str(tmp_path / "blank.fits"), holed)
+    data, error = fitsio.read_image(path)
+    assert error is None
+    assert np.isnan(data[10:20, 10:20]).all()
+    assert np.isfinite(data[500:600, 500:600]).all()
+
+
+def test_image_read_reports_a_missing_array(tmp_path):
+    path = str(tmp_path / "primary.fits")
+    fits.HDUList([fits.PrimaryHDU()]).writeto(path, overwrite=True)
+    data, error = fitsio.read_image(path)
+    assert data is None and "no 2-D image array" in error
+
+
+def test_image_read_reports_corruption_instead_of_raising(tmp_path, good_frame):
+    path = corrupt(good_frame, tmp_path, "broken.fits", lambda raw: raw[: len(raw) // 2])
+    data, error = fitsio.read_image(path)
+    assert data is None and error
+
+
+def test_quiet_astropy_is_callable():
+    fitsio.quiet_astropy()
diff --git a/tests/test_index.py b/tests/test_index.py
new file mode 100644
index 0000000..6e26104
--- /dev/null
+++ b/tests/test_index.py
@@ -0,0 +1,401 @@
+"""Tests for keeping the index in step with the archive without traversing it.
+
+The property under test throughout is that a *re-run reads nothing it does not have
+to*.  That is not an optimisation here: a full traversal of this archive exhausts the
+file handles of the virtiofs mount it lives on, and the mount then refuses every open
+until the guest drops its dentry cache.  So "how many directories did we open" is a
+correctness-adjacent measurement, and several tests assert on it directly.
+"""
+
+import os
+import re
+
+import pytest
+
+from conftest import solar_disc, write_fits
+from suvi import db, index, paths
+
+T0 = 1715299200
+
+
+def add_frame(root, satellite=16, wavelength=171, index_=0, day=None, label=None):
+    when = T0 + index_ * paths.CADENCE
+    name = paths.FrameName(satellite, wavelength, when, when + paths.CADENCE, "1-0-2")
+    relpath = name.relpath(label)
+    if day:
+        relpath = relpath.replace("/2024/05/10/", f"/{day}/")
+    path = os.path.join(str(root), *relpath.split("/"))
+    write_fits(path, solar_disc(size=32, radius=10, peak=3.0))
+    return name, path, relpath
+
+
+@pytest.fixture
+def small_archive(archive):
+    for i in range(5):
+        add_frame(archive, index_=i)
+    for i in range(3):
+        add_frame(archive, wavelength=304, index_=i)
+    return archive
+
+
+class CountingScandir:
+    """Wraps os.scandir so a test can assert how much of the tree was opened."""
+
+    def __init__(self, monkeypatch, only_under=None):
+        self.paths = []
+        self._real = os.scandir
+        self._only = str(only_under) if only_under else None
+        monkeypatch.setattr(os, "scandir", self)
+
+    def __call__(self, path=".", *args, **kwargs):
+        text = str(path)
+        if self._only is None or text.startswith(self._only):
+            self.paths.append(text)
+        return self._real(path, *args, **kwargs)
+
+    #: .../YYYY/MM/DD -- the directories holding ~360 frames each.  Month
+    #: directories must still be listed to discover day directories at all; it is
+    #: only the day directories, and the per-file lookups inside them, that a
+    #: no-change reconcile has to avoid.
+    _DAY_DIR = re.compile(r"/\d{4}/\d{2}/\d{2}/?$")
+
+    def opened_day_dirs(self):
+        return [p for p in self.paths if self._DAY_DIR.search(p)]
+
+
+# ------------------------------------------------------------- day_directories
+
+
+def test_day_directories_finds_every_day(small_archive):
+    found = list(index.day_directories(str(small_archive), (16,), (171, 304)))
+    assert len(found) == 2
+    for relpath, abspath in found:
+        assert relpath.endswith("2024/05/10")
+        assert os.path.isdir(abspath)
+
+
+def test_day_directories_filters_by_year(small_archive):
+    add_frame(small_archive, day="2023/07/04")
+    assert len(list(index.day_directories(str(small_archive), (16,), (171,)))) == 2
+    only = list(index.day_directories(str(small_archive), (16,), (171,), years=[2023]))
+    assert len(only) == 1 and only[0][0].endswith("2023/07/04")
+
+
+def test_day_directories_tolerates_a_missing_archive(tmp_path):
+    assert list(index.day_directories(str(tmp_path), (16,), (171,))) == []
+
+
+# ------------------------------------------------------------------- reconcile
+
+
+def test_first_reconcile_indexes_everything(small_archive, db_path):
+    conn = db.connect(db_path)
+    summary = index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    assert summary["frames_added"] == 8
+    assert summary["directories_changed"] == 2
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 8
+    conn.close()
+
+
+def test_second_reconcile_opens_no_day_directories(small_archive, db_path, monkeypatch):
+    """The heart of it: an unchanged archive must cost directory stats, nothing more.
+
+    Re-reading directories that have not changed is what made a resume traverse the
+    whole archive, and traversal is what breaks the mount.
+    """
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171, 304))
+
+    spy = CountingScandir(monkeypatch, only_under=small_archive)
+    summary = index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    assert summary["directories_changed"] == 0
+    assert summary["frames_added"] == 0
+    assert spy.opened_day_dirs() == [], "re-read a directory that had not changed"
+    conn.close()
+
+
+def test_reconcile_picks_up_a_new_frame(small_archive, db_path):
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    add_frame(small_archive, index_=99)
+    summary = index.reconcile(conn, str(small_archive), (16,), (171,))
+    assert summary["frames_added"] == 1
+    assert summary["directories_changed"] == 1
+    conn.close()
+
+
+def test_reconcile_notices_a_deleted_frame(small_archive, db_path):
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    before = conn.execute("SELECT count(*) c FROM frame").fetchone()["c"]
+
+    _, path, _ = add_frame(small_archive, index_=0)  # existing file
+    os.remove(path)
+    summary = index.reconcile(conn, str(small_archive), (16,), (171,))
+    assert summary["frames_removed"] == 1
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == before - 1
+    conn.close()
+
+
+def test_reconcile_handles_a_vanished_directory(small_archive, db_path):
+    import shutil
+
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    shutil.rmtree(os.path.join(str(small_archive), "goes16/l2/data/suvi-l2-ci304"))
+    summary = index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    assert summary["directories_vanished"] == 1
+    assert summary["frames_removed"] == 3
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 5
+    conn.close()
+
+
+def test_force_rereads_everything(small_archive, db_path, monkeypatch):
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    spy = CountingScandir(monkeypatch, only_under=small_archive)
+    summary = index.reconcile(conn, str(small_archive), (16,), (171,), force=True)
+    assert summary["directories_changed"] == 1
+    assert spy.opened_day_dirs(), "--full should re-read directories"
+    conn.close()
+
+
+def test_reconcile_is_idempotent(small_archive, db_path):
+    conn = db.connect(db_path)
+    first = index.reconcile(conn, str(small_archive), (16,), (171,))
+    second = index.reconcile(conn, str(small_archive), (16,), (171,))
+    third = index.reconcile(conn, str(small_archive), (16,), (171,))
+    assert first["frames_added"] == 5
+    assert second["frames_added"] == third["frames_added"] == 0
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 5
+    conn.close()
+
+
+def test_reconcile_ignores_non_frame_files(small_archive, db_path):
+    conn = db.connect(db_path)
+    day = os.path.join(str(small_archive), "goes16/l2/data/suvi-l2-ci171/2024/05/10")
+    open(os.path.join(day, "notes.txt"), "w").write("not a frame")
+    summary = index.reconcile(conn, str(small_archive), (16,), (171,))
+    assert summary["frames_added"] == 5
+    conn.close()
+
+
+def test_reconcile_records_the_observed_mtime(small_archive, db_path):
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    relpath = "goes16/l2/data/suvi-l2-ci171/2024/05/10"
+    abspath = os.path.join(str(small_archive), *relpath.split("/"))
+    assert db.get_dir_mtime(conn, relpath) == pytest.approx(os.stat(abspath).st_mtime)
+    conn.close()
+
+
+# ------------------------------------------------------------ record_downloaded
+
+
+def test_record_downloaded_indexes_without_any_traversal(archive, db_path, monkeypatch):
+    """The cheapest path: the downloader already knows the file is there."""
+    conn = db.connect(db_path)
+    _, path, relpath = add_frame(archive)
+
+    spy = CountingScandir(monkeypatch, only_under=archive)
+    frame_id = index.record_downloaded(conn, path, str(archive))
+    assert frame_id is not None
+    assert spy.paths == [], "indexing a download must not scan the archive"
+    row = conn.execute("SELECT path FROM frame WHERE id = ?", (frame_id,)).fetchone()
+    assert row["path"] == relpath
+    conn.close()
+
+
+def test_record_downloaded_ignores_other_files(archive, db_path):
+    conn = db.connect(db_path)
+    other = os.path.join(str(archive), "readme.txt")
+    open(other, "w").write("x")
+    assert index.record_downloaded(conn, other, str(archive)) is None
+    conn.close()
+
+
+def test_record_downloaded_survives_a_missing_file(archive, db_path):
+    conn = db.connect(db_path)
+    _, path, _ = add_frame(archive)
+    os.remove(path)
+    assert index.record_downloaded(conn, path, str(archive)) is not None
+    conn.close()
+
+
+# ------------------------------------------------------------------ db helpers
+
+
+def test_frames_in_dir_scopes_to_one_directory(small_archive, db_path):
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    in_171 = db.frames_in_dir(conn, "goes16/l2/data/suvi-l2-ci171/2024/05/10")
+    in_304 = db.frames_in_dir(conn, "goes16/l2/data/suvi-l2-ci304/2024/05/10")
+    assert len(in_171) == 5 and len(in_304) == 3
+    assert all("ci171" in name for name in in_171)
+    conn.close()
+
+
+def test_schema_upgrades_from_version_one(tmp_path):
+    """An index created before dir_scan existed must gain it, not be rejected."""
+    path = str(tmp_path / "old.sqlite")
+    conn = db.connect(path)
+    conn.execute("DROP TABLE dir_scan")
+    conn.execute("UPDATE meta SET value = '1' WHERE key = 'schema_version'")
+    conn.commit()
+    conn.close()
+
+    conn = db.connect(path)  # re-open triggers the upgrade
+    assert db.get_meta(conn, "schema_version") == str(db.SCHEMA_VERSION)
+    conn.execute("SELECT count(*) FROM dir_scan")  # table now exists
+    conn.close()
+
+
+def test_meta_round_trip(db_path):
+    conn = db.connect(db_path)
+    assert db.get_meta(conn, "absent") is None
+    assert db.get_meta(conn, "absent", "fallback") == "fallback"
+    db.set_meta(conn, "unrename_done:ci171:2024", "done")
+    db.set_meta(conn, "unrename_done:ci171:2024", "done")  # upsert, not duplicate
+    assert db.get_meta(conn, "unrename_done:ci171:2024") == "done"
+    conn.close()
+
+
+# ------------------------------------------------------------ slot collisions
+
+
+def test_two_files_claiming_one_slot_do_not_break_indexing(archive, db_path):
+    """The archive holds 1,742 such pairs; they must not block the whole index.
+
+    An older filter labelled some frames repeatedly, and the puller later
+    re-downloaded a clean copy it could no longer find under the published name --
+    leaving `X_v1-0-1.fits` beside a byte-identical `X_v1-0-1_f_f_f.fits`.
+    """
+    _, path, _ = add_frame(archive)                       # canonical
+    add_frame(archive, label="f")                          # same slot, labelled
+    conn = db.connect(db_path)
+    summary = index.reconcile(conn, str(archive), (16,), (171,))
+    assert summary["frames_added"] == 1
+    assert len(summary["duplicate_slots"]) == 1
+    assert summary["duplicate_slots"][0].endswith("_f.fits")
+    row = conn.execute("SELECT path FROM frame").fetchone()
+    assert row["path"].endswith("v1-0-2.fits"), "kept the labelled copy over the published one"
+    conn.close()
+
+
+def test_the_published_name_wins_over_a_multiply_labelled_one(archive, db_path):
+    _, path, _ = add_frame(archive)
+    name = paths.parse_frame_filename(os.path.basename(path))
+    triple = os.path.join(os.path.dirname(path), name.filename().replace(".fits", "_f_f_f.fits"))
+    write_fits(triple, solar_disc(size=32, radius=10, peak=3.0))
+
+    conn = db.connect(db_path)
+    summary = index.reconcile(conn, str(archive), (16,), (171,))
+    assert summary["frames_added"] == 1
+    assert conn.execute("SELECT path FROM frame").fetchone()["path"].endswith("v1-0-2.fits")
+    assert summary["duplicate_slots"][0].endswith("_f_f_f.fits")
+    conn.close()
+
+
+def test_a_renamed_file_does_not_collide_with_its_old_row(archive, db_path):
+    """Un-renaming moves a file within its directory; reconcile must cope.
+
+    The removal has to be applied before the insertion, or both names briefly claim
+    the same observation slot and the unique constraint fires.
+    """
+    _, old_path, _ = add_frame(archive, label="f")
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(archive), (16,), (171,))
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 1
+
+    name = paths.parse_frame_filename(os.path.basename(old_path))
+    os.rename(old_path, os.path.join(os.path.dirname(old_path), name.filename()))
+
+    summary = index.reconcile(conn, str(archive), (16,), (171,))
+    assert summary["frames_added"] == 1 and summary["frames_removed"] == 1
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == 1
+    assert conn.execute("SELECT path FROM frame").fetchone()["path"].endswith("v1-0-2.fits")
+    conn.close()
+
+
+# ------------------------------------------------- unreadable != empty
+
+
+def test_unreadable_directory_raises_rather_than_looking_empty(small_archive, monkeypatch):
+    """Regression: swallowing OSError made five of six bands look absent.
+
+    reconcile then treated their contents as deleted and dropped 205,618 index rows
+    for files that were still on disk.  An unreadable directory has to stop the run.
+    """
+    real = os.scandir
+
+    def refuse(path=".", *args, **kwargs):
+        if "suvi-l2-ci304" in str(path):
+            raise OSError(23, "Too many open files in system")
+        return real(path, *args, **kwargs)
+
+    monkeypatch.setattr(os, "scandir", refuse)
+    with pytest.raises(OSError):
+        list(index.day_directories(str(small_archive), (16,), (171, 304)))
+
+
+def test_a_missing_directory_is_still_treated_as_empty(tmp_path):
+    """Only genuine absence may be silent."""
+    assert index._subdirs(str(tmp_path / "does-not-exist")) == []
+
+
+def test_frames_are_not_purged_when_enumeration_comes_up_short(small_archive, db_path, monkeypatch):
+    """Defence in depth: absence from the scan is not proof a directory is gone.
+
+    Even if enumeration misses a directory, its rows must survive as long as the
+    directory is still on disk.
+    """
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    before = conn.execute("SELECT count(*) c FROM frame").fetchone()["c"]
+    assert before == 8
+
+    # Enumerate only one band, as though the other had been missed entirely.
+    real = index.day_directories
+    partial = list(real(str(small_archive), (16,), (171,)))
+    monkeypatch.setattr(index, "day_directories", lambda *a, **k: iter(partial))
+    summary = index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    assert summary["directories_vanished"] == 0
+    assert conn.execute("SELECT count(*) c FROM frame").fetchone()["c"] == before
+    conn.close()
+
+
+def test_a_cold_build_reclaims_periodically(small_archive, db_path, monkeypatch):
+    """A cold build reads every file, which is what exhausts the mount's handles.
+
+    It must hand them back as it goes, or the build cannot finish.
+    """
+    calls = []
+    monkeypatch.setattr(index.vfs, "release_handles", lambda *a, **k: calls.append(1))
+    monkeypatch.setattr(index.vfs, "RELIEF_INTERVAL", 3)
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171, 304))
+    assert calls, "cold build never reclaimed"
+    conn.close()
+
+
+def test_reclaim_can_be_disabled(small_archive, db_path, monkeypatch):
+    def explode(*a, **k):
+        raise AssertionError("reclaimed despite relief=False")
+
+    monkeypatch.setattr(index.vfs, "release_handles", explode)
+    monkeypatch.setattr(index.vfs, "RELIEF_INTERVAL", 1)
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,), relief=False)
+    conn.close()
+
+
+def test_a_steady_state_run_does_not_reclaim(small_archive, db_path, monkeypatch):
+    """Nothing changed means nothing was read, so there is nothing to hand back."""
+    conn = db.connect(db_path)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    calls = []
+    monkeypatch.setattr(index.vfs, "release_handles", lambda *a, **k: calls.append(1))
+    monkeypatch.setattr(index.vfs, "RELIEF_INTERVAL", 1)
+    index.reconcile(conn, str(small_archive), (16,), (171,))
+    assert calls == []
+    conn.close()
diff --git a/tests/test_metrics.py b/tests/test_metrics.py
new file mode 100644
index 0000000..1a477bd
--- /dev/null
+++ b/tests/test_metrics.py
@@ -0,0 +1,350 @@
+import numpy as np
+import pytest
+
+from conftest import solar_disc
+from suvi import detectors, metrics
+
+BAND = 171
+
+
+def verdict(kind, reason=None):
+    return detectors.Verdict(kind, reason, {})
+
+
+# ------------------------------------------------------------------------ display
+
+
+def test_display_mapping_is_bounded():
+    image = solar_disc(size=64, radius=20, peak=50.0)
+    shown = metrics.to_display(image, BAND)
+    assert shown.min() >= 0.0 and shown.max() <= 1.0
+
+
+def test_display_mapping_is_monotonic():
+    ramp = np.linspace(0, 20, 100).reshape(10, 10)
+    shown = metrics.to_display(ramp, BAND)
+    assert np.all(np.diff(shown.ravel()) >= -1e-12)
+
+
+def test_display_mapping_differs_per_band():
+    ramp = np.full((4, 4), 5.0)
+    assert not np.allclose(metrics.to_display(ramp, 94), metrics.to_display(ramp, 304))
+
+
+def test_display_mapping_handles_nan():
+    assert np.isfinite(metrics.to_display(np.full((4, 4), np.nan), BAND)).all()
+
+
+# ---------------------------------------------------------------------- detection
+
+
+def test_scores_a_perfect_detector():
+    injected = {(16, BAND, 0): "eclipse_dim", (16, BAND, 240): "truncate"}
+    verdicts = {
+        (16, BAND, 0): verdict("bad"),
+        (16, BAND, 240): verdict("bad"),
+        (16, BAND, 480): verdict("good"),
+        (16, BAND, 720): verdict("good"),
+    }
+    score = metrics.score_detection(verdicts, injected)
+    assert (score.true_positives, score.false_negatives) == (2, 0)
+    assert (score.false_positives, score.true_negatives) == (0, 2)
+    assert score.precision == 1.0 and score.recall == 1.0 and score.f1 == 1.0
+    assert score.false_positive_rate == 0.0
+
+
+def test_scores_a_detector_that_flags_everything():
+    injected = {(16, BAND, 0): "eclipse_dim"}
+    verdicts = {(16, BAND, t): verdict("bad") for t in (0, 240, 480, 720)}
+    score = metrics.score_detection(verdicts, injected)
+    assert score.recall == 1.0
+    assert score.precision == pytest.approx(0.25)
+    assert score.false_positive_rate == 1.0
+
+
+def test_unknown_verdicts_are_excluded_not_counted_as_good():
+    """Abstaining is neither a hit nor a miss, and must not flatter the score."""
+    injected = {(16, BAND, 0): "eclipse_dim"}
+    verdicts = {(16, BAND, 0): verdict("unknown"), (16, BAND, 240): verdict("unknown")}
+    score = metrics.score_detection(verdicts, injected)
+    assert score.unknown == 2
+    assert score.true_positives == score.false_positives == 0
+    assert score.false_negatives == score.true_negatives == 0
+    assert np.isnan(score.precision) and np.isnan(score.recall)
+
+
+def test_legacy_disagreements_are_reported_separately():
+    """Flagging a frame the old filter passed may be a find, not an error."""
+    injected = {}
+    verdicts = {(16, BAND, 0): verdict("bad"), (16, BAND, 240): verdict("bad")}
+    score = metrics.score_detection(verdicts, injected, legacy_good={(16, BAND, 0)})
+    assert score.false_positives == 2
+    assert score.legacy_disagreements == 1
+
+
+def test_recall_is_broken_down_by_mode():
+    injected = {
+        (16, BAND, 0): "eclipse_dim",
+        (16, BAND, 240): "eclipse_dim",
+        (16, BAND, 480): "gain_shift",
+        (16, BAND, 720): "gain_shift",
+    }
+    verdicts = {
+        (16, BAND, 0): verdict("bad"),
+        (16, BAND, 240): verdict("bad"),
+        (16, BAND, 480): verdict("bad"),
+        (16, BAND, 720): verdict("good"),
+    }
+    score = metrics.score_detection(verdicts, injected)
+    assert score.recall_by_mode == {"eclipse_dim": 1.0, "gain_shift": 0.5}
+
+
+def test_unknown_counts_against_a_modes_recall():
+    injected = {(16, BAND, 0): "rotate", (16, BAND, 240): "rotate"}
+    verdicts = {(16, BAND, 0): verdict("bad"), (16, BAND, 240): verdict("unknown")}
+    score = metrics.score_detection(verdicts, injected)
+    assert score.recall_by_mode["rotate"] == 0.5
+
+
+def test_scoring_an_empty_case():
+    score = metrics.score_detection({}, {})
+    assert np.isnan(score.precision) and np.isnan(score.recall) and np.isnan(score.f1)
+    assert np.isnan(score.microseconds_per_frame)
+
+
+def test_throughput_is_per_frame():
+    verdicts = {(16, BAND, t): verdict("good") for t in range(0, 1000, 240)}
+    score = metrics.score_detection(verdicts, {}, elapsed_us=1000)
+    assert score.microseconds_per_frame == pytest.approx(1000 / len(verdicts))
+
+
+def test_as_dict_is_serialisable():
+    score = metrics.score_detection({(16, BAND, 0): verdict("bad")}, {(16, BAND, 0): "x"})
+    import json
+
+    assert json.loads(json.dumps(score.as_dict()))["recall"] == 1.0
+
+
+# ---------------------------------------------------------------------- pr curves
+
+
+def test_precision_recall_curve_on_a_separable_score():
+    scores = [0.9, 0.8, 0.2, 0.1]
+    labels = [True, True, False, False]
+    thresholds, precision, recall = metrics.precision_recall_curve(scores, labels)
+    assert list(thresholds) == [0.9, 0.8, 0.2, 0.1]
+    assert precision[1] == 1.0 and recall[1] == 1.0
+    assert metrics.average_precision(scores, labels) == pytest.approx(1.0)
+
+
+def test_average_precision_of_an_uninformative_score():
+    scores = [0.5, 0.5, 0.5, 0.5]
+    labels = [True, False, True, False]
+    assert 0.0 < metrics.average_precision(scores, labels) < 1.0
+
+
+def test_curves_handle_degenerate_input():
+    assert metrics.average_precision([], []) != metrics.average_precision([], []) or True
+    assert np.isnan(metrics.average_precision([1.0], [False]))
+    thresholds, _, _ = metrics.precision_recall_curve([np.nan, np.inf], [True, False])
+    assert len(thresholds) <= 1
+
+
+# --------------------------------------------------------------------------- fill
+
+
+def test_identical_frames_score_perfectly():
+    image = solar_disc(size=64, radius=20, peak=3.0)
+    score = metrics.score_fill(image, image, BAND)
+    assert score.rmse == 0.0 and score.mae == 0.0 and score.log_rmse == 0.0
+    assert score.psnr == float("inf")
+    assert score.ssim == pytest.approx(1.0)
+
+
+def test_worse_reconstructions_score_worse():
+    truth = solar_disc(size=64, radius=20, peak=3.0)
+    close = truth + 0.01
+    far = truth + 0.5
+    assert metrics.score_fill(close, truth, BAND).rmse < metrics.score_fill(far, truth, BAND).rmse
+    assert metrics.score_fill(close, truth, BAND).psnr > metrics.score_fill(far, truth, BAND).psnr
+    assert metrics.score_fill(close, truth, BAND).ssim > metrics.score_fill(far, truth, BAND).ssim
+
+
+def test_log_error_keeps_the_faint_corona_visible():
+    """The log term makes an equal *relative* error count comparably everywhere.
+
+    Radiance spans orders of magnitude, so a plain rmse is dominated by the bright
+    disc: tripling the faint corona and tripling the disc are the same mistake, but
+    rmse rates one ~1000x worse than the other.  log_rmse compresses that gap so a
+    filler cannot look good by getting only the bright pixels right.
+    """
+    faint = np.full((32, 32), 0.01)
+    bright = np.full((32, 32), 10.0)
+    faint_score = metrics.score_fill(faint * 3.0, faint, BAND)
+    bright_score = metrics.score_fill(bright * 3.0, bright, BAND)
+
+    assert bright_score.rmse / faint_score.rmse == pytest.approx(1000, rel=0.01)
+    assert bright_score.log_rmse / faint_score.log_rmse < 100
+
+
+def test_fill_scoring_rejects_mismatched_shapes():
+    with pytest.raises(ValueError, match="shape mismatch"):
+        metrics.score_fill(np.zeros((4, 4)), np.zeros((8, 8)), BAND)
+
+
+def test_fill_scoring_tolerates_nan():
+    truth = solar_disc(size=32, radius=10, peak=2.0)
+    filled = truth.copy()
+    filled[0:4, 0:4] = np.nan
+    score = metrics.score_fill(filled, truth, BAND)
+    assert np.isfinite(score.rmse) and np.isfinite(score.ssim)
+
+
+# ------------------------------------------------------------------------ flicker
+
+
+def test_flicker_is_zero_for_a_perfect_reconstruction():
+    frames = [solar_disc(size=32, radius=10, peak=1.0 + i * 0.1) for i in range(5)]
+    assert metrics.temporal_flicker(frames, frames, BAND) == pytest.approx(0.0)
+
+
+def test_flicker_penalises_a_freeze_that_psnr_forgives():
+    """The artifact per-frame metrics miss: hold-then-jump instead of smooth motion."""
+    truth = [solar_disc(size=32, radius=10, peak=1.0 + i * 0.4) for i in range(4)]
+    frozen = [truth[0], truth[0], truth[0], truth[3]]  # hold, hold, then snap
+    smooth = truth
+    assert metrics.temporal_flicker(frozen, truth, BAND) > metrics.temporal_flicker(
+        smooth, truth, BAND
+    )
+
+
+def test_flicker_requires_matching_lengths():
+    frames = [np.zeros((8, 8))] * 3
+    with pytest.raises(ValueError, match="same length"):
+        metrics.temporal_flicker(frames, frames[:2], BAND)
+
+
+def test_flicker_of_a_single_frame_is_undefined():
+    assert np.isnan(metrics.temporal_flicker([np.zeros((8, 8))], [np.zeros((8, 8))], BAND))
+
+
+# ------------------------------------------------------------------------ summary
+
+
+def test_summary_groups_by_gap_length():
+    scores = [
+        metrics.FillScore(1.0, 1.0, 0.1, 30.0, 0.9, gap_frames=1, wavelength=BAND),
+        metrics.FillScore(3.0, 3.0, 0.3, 20.0, 0.7, gap_frames=1, wavelength=BAND),
+        metrics.FillScore(5.0, 5.0, 0.5, 10.0, 0.5, gap_frames=10, wavelength=BAND),
+    ]
+    summary = metrics.summarise_fills(scores)
+    assert summary["n"] == 3
+    assert summary["rmse"] == pytest.approx(3.0)
+    assert summary["by_gap"][1]["n"] == 2
+    assert summary["by_gap"][1]["psnr"] == pytest.approx(25.0)
+    assert summary["by_gap"][10]["ssim"] == pytest.approx(0.5)
+
+
+def test_summary_ignores_infinite_psnr_from_perfect_frames():
+    scores = [
+        metrics.FillScore(0.0, 0.0, 0.0, float("inf"), 1.0, 1, BAND),
+        metrics.FillScore(1.0, 1.0, 0.1, 20.0, 0.8, 1, BAND),
+    ]
+    assert metrics.summarise_fills(scores)["psnr"] == pytest.approx(20.0)
+
+
+def test_summary_of_nothing():
+    assert metrics.summarise_fills([]) == {}
+
+
+# -------------------------------------------------------------------- combinations
+
+
+def vmap(**pairs):
+    """Build a {slot: Verdict} from slot-suffix -> verdict-string pairs."""
+    return {(16, BAND, int(k[1:])): verdict(v) for k, v in pairs.items()}
+
+
+def test_any_policy_flags_if_one_detector_does():
+    combined = metrics.combine_verdicts(
+        [vmap(t0="bad", t1="good"), vmap(t0="good", t1="good")], "any"
+    )
+    assert combined[(16, BAND, 0)].verdict == "bad"
+    assert combined[(16, BAND, 1)].verdict == "good"
+
+
+def test_all_policy_requires_unanimity():
+    combined = metrics.combine_verdicts(
+        [vmap(t0="bad", t1="bad"), vmap(t0="good", t1="bad")], "all"
+    )
+    assert combined[(16, BAND, 0)].verdict == "good"
+    assert combined[(16, BAND, 1)].verdict == "bad"
+
+
+def test_majority_policy():
+    maps = [vmap(t0="bad"), vmap(t0="bad"), vmap(t0="good")]
+    assert metrics.combine_verdicts(maps, "majority")[(16, BAND, 0)].verdict == "bad"
+    maps = [vmap(t0="bad"), vmap(t0="good"), vmap(t0="good")]
+    assert metrics.combine_verdicts(maps, "majority")[(16, BAND, 0)].verdict == "good"
+
+
+def test_unknown_abstains_rather_than_voting():
+    """An abstention must not act as a 'good' vote.
+
+    Under 'all' that would let one abstaining detector veto a real detection; under
+    'any' it would quietly inflate recall.
+    """
+    combined = metrics.combine_verdicts(
+        [vmap(t0="bad"), vmap(t0="unknown")], "all"
+    )
+    assert combined[(16, BAND, 0)].verdict == "bad"  # the abstention is ignored
+    assert combined[(16, BAND, 0)].scores["votes_total"] == 1.0
+
+
+def test_all_detectors_abstaining_yields_unknown():
+    combined = metrics.combine_verdicts([vmap(t0="unknown"), vmap(t0="unknown")], "any")
+    assert combined[(16, BAND, 0)].verdict == "unknown"
+
+
+def test_slots_missing_from_one_map_are_still_judged():
+    combined = metrics.combine_verdicts([vmap(t0="bad"), vmap(t1="good")], "any")
+    assert set(combined) == {(16, BAND, 0), (16, BAND, 1)}
+    assert combined[(16, BAND, 0)].verdict == "bad"
+
+
+def test_single_detector_reduces_to_itself():
+    single = vmap(t0="bad", t1="good", t2="unknown")
+    for policy in metrics.COMBINATION_POLICIES:
+        combined = metrics.combine_verdicts([single], policy)
+        for slot, original in single.items():
+            assert combined[slot].verdict == original.verdict, policy
+
+
+def test_combining_nothing():
+    assert metrics.combine_verdicts([], "any") == {}
+
+
+def test_unknown_policy_is_rejected():
+    with pytest.raises(ValueError, match="Unknown policy"):
+        metrics.combine_verdicts([vmap(t0="bad")], "consensus")
+
+
+def test_combined_verdicts_carry_the_reasons():
+    maps = [vmap(t0="bad"), vmap(t0="bad")]
+    maps[0][(16, BAND, 0)] = detectors.Verdict("bad", "eclipse", {})
+    maps[1][(16, BAND, 0)] = detectors.Verdict("bad", "limb_contrast 0.0", {})
+    combined = metrics.combine_verdicts(maps, "any")
+    assert "eclipse" in combined[(16, BAND, 0)].reason
+    assert "limb_contrast" in combined[(16, BAND, 0)].reason
+
+
+def test_a_combination_can_be_scored_like_any_detector():
+    """Combinations feed straight into score_detection -- that is the point."""
+    injected = {(16, BAND, 0): "eclipse_dim"}
+    narrow = vmap(t0="bad", t1="good")       # perfect
+    noisy = vmap(t0="bad", t1="bad")         # one false positive
+    strict = metrics.combine_verdicts([narrow, noisy], "all")
+    loose = metrics.combine_verdicts([narrow, noisy], "any")
+    assert metrics.score_detection(strict, injected).false_positive_rate == 0.0
+    assert metrics.score_detection(loose, injected).false_positive_rate == 1.0
+    assert metrics.score_detection(strict, injected).recall == 1.0
diff --git a/tests/test_migrations.py b/tests/test_migrations.py
new file mode 100644
index 0000000..5da1672
--- /dev/null
+++ b/tests/test_migrations.py
@@ -0,0 +1,355 @@
+"""Tests for the two one-time migrations.
+
+These are the only steps in the project that mutate the archive or destroy state, so
+the properties tested here are the ones that make them safe to run: dry runs change
+nothing, re-runs are no-ops, collisions are skipped rather than forced, and nothing
+is renamed until the labels it would destroy have been exported and recorded.
+"""
+
+import csv
+import gzip
+import json
+import os
+
+import pytest
+
+import migrate_unrename
+import migrate_urlcache
+from conftest import solar_disc, write_fits
+from suvi import db, paths
+
+T0 = 1715299200
+
+
+def make_frame_file(root, satellite=16, wavelength=171, index=0, label=None):
+    when = T0 + index * paths.CADENCE
+    name = paths.FrameName(satellite, wavelength, when, when + paths.CADENCE, "1-0-2")
+    path = os.path.join(str(root), *name.relpath(label).split("/"))
+    write_fits(path, solar_disc(size=32, radius=10, peak=3.0))
+    return name, path
+
+
+# ------------------------------------------------------------------- url cache
+
+
+@pytest.fixture
+def url_json(tmp_path):
+    payload = {f"https://example.test/file{i}.fits": 1700000000.0 + i for i in range(50)}
+    path = tmp_path / "file_database.json"
+    path.write_text(json.dumps(payload))
+    return path, payload
+
+
+def test_urlcache_dry_run_writes_nothing(url_json, db_path):
+    path, payload = url_json
+    assert migrate_urlcache.main(["--json", str(path), "--db", db_path]) == 0
+    assert not os.path.exists(db_path)
+    assert path.exists()
+
+
+def test_urlcache_migrates_every_record(url_json, db_path):
+    path, payload = url_json
+    assert migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"]) == 0
+    conn = db.connect(db_path, readonly=True)
+    assert conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"] == len(payload)
+    for url, mtime in list(payload.items())[:5]:
+        assert db.get_remote_mtime(conn, url) == mtime
+    conn.close()
+
+
+def test_urlcache_leaves_the_json_alone_unless_asked(url_json, db_path):
+    path, _ = url_json
+    migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"])
+    assert path.exists()
+    assert not os.path.exists(str(path) + ".bak")
+
+
+def test_urlcache_backs_up_only_after_verifying(url_json, db_path):
+    path, _ = url_json
+    migrate_urlcache.main(
+        ["--json", str(path), "--db", db_path, "--apply", "--backup-json"]
+    )
+    assert not path.exists()
+    assert os.path.exists(str(path) + ".bak")
+
+
+def test_urlcache_is_idempotent(url_json, db_path):
+    path, payload = url_json
+    migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"])
+    migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"])
+    conn = db.connect(db_path, readonly=True)
+    assert conn.execute("SELECT count(*) c FROM remote_file").fetchone()["c"] == len(payload)
+    conn.close()
+
+
+def test_urlcache_refuses_malformed_records(tmp_path, db_path):
+    path = tmp_path / "bad.json"
+    path.write_text(json.dumps({"https://example.test/a": "not a timestamp"}))
+    assert migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"]) == 1
+    assert not os.path.exists(db_path)
+
+
+def test_urlcache_refuses_a_non_object(tmp_path, db_path):
+    path = tmp_path / "list.json"
+    path.write_text(json.dumps(["a", "b"]))
+    assert migrate_urlcache.main(["--json", str(path), "--db", db_path, "--apply"]) == 1
+
+
+def test_urlcache_reports_a_missing_source(tmp_path, db_path):
+    assert migrate_urlcache.main(["--json", str(tmp_path / "nope.json"), "--db", db_path]) == 1
+
+
+# -------------------------------------------------------------------- un-rename
+
+
+@pytest.fixture
+def labelled_archive(archive):
+    """An archive in the pre-migration state: suffixed files plus error plots."""
+    made = []
+    for index in range(4):
+        made.append(make_frame_file(archive, index=index, label="f"))
+    for index in range(4, 6):
+        name, path = make_frame_file(archive, index=index, label="e")
+        made.append((name, path))
+        plot = os.path.join(os.path.dirname(path), name.error_plot_name())
+        open(plot, "w").write("diagnostic")
+    make_frame_file(archive, index=6, label=None)  # never processed
+    return archive, made
+
+
+def test_unrename_dry_run_changes_nothing(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    before = sorted(os.listdir(_day_dir(archive)))
+    assert migrate_unrename.main(["--root", str(archive), "--db", db_path]) == 0
+    assert sorted(os.listdir(_day_dir(archive))) == before
+    assert not os.path.exists(db_path)
+
+
+def _day_dir(archive):
+    return os.path.join(str(archive), "goes16/l2/data/suvi-l2-ci171/2024/05/10")
+
+
+def test_unrename_strips_both_suffixes(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    assert migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"]) == 0
+    names = os.listdir(_day_dir(archive))
+    assert not [n for n in names if n.endswith("_f.fits") or n.endswith("_e.fits")]
+    assert len([n for n in names if n.endswith(".fits")]) == 7
+
+
+def test_unrename_deletes_diagnostic_plots(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+    assert not [n for n in os.listdir(_day_dir(archive)) if n.endswith(".jpg")]
+
+
+def test_unrename_keeps_plots_when_asked(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    migrate_unrename.main(
+        ["--root", str(archive), "--db", db_path, "--apply", "--keep-plots"]
+    )
+    assert len([n for n in os.listdir(_day_dir(archive)) if n.endswith(".jpg")]) == 2
+
+
+def test_unrename_exports_labels_before_renaming(labelled_archive, db_path, tmp_path):
+    archive, _ = labelled_archive
+    export = tmp_path / "labels.csv.gz"
+    migrate_unrename.main(
+        ["--root", str(archive), "--db", db_path, "--apply", "--export", str(export)]
+    )
+    assert export.exists()
+    with gzip.open(export, "rt") as handle:
+        rows = list(csv.DictReader(handle))
+    assert len(rows) == 6
+    assert sum(1 for r in rows if r["legacy_label"] == "f") == 4
+    assert sum(1 for r in rows if r["legacy_label"] == "e") == 2
+    # The export must name the *restored* path, so it can be rejoined after renaming.
+    for row in rows:
+        assert not row["relpath"].endswith("_f.fits")
+        assert os.path.exists(paths.abspath(row["relpath"], str(archive)))
+
+
+def test_unrename_records_verdicts_in_the_index(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+    conn = db.connect(db_path, readonly=True)
+    run_id = db.latest_run_id(conn, migrate_unrename.LEGACY_RUN_NAME)
+    assert run_id is not None
+    rows = conn.execute(
+        "SELECT verdict, count(*) c FROM detection WHERE run_id = ? GROUP BY verdict",
+        (run_id,),
+    ).fetchall()
+    counts = {row["verdict"]: row["c"] for row in rows}
+    assert counts == {"good": 4, "bad": 2}
+    conn.close()
+
+
+def test_unrename_is_idempotent(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+    names_after_first = sorted(os.listdir(_day_dir(archive)))
+    assert migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"]) == 0
+    assert sorted(os.listdir(_day_dir(archive))) == names_after_first
+
+
+def test_unrename_skips_collisions_rather_than_overwriting(archive, db_path):
+    """If both the suffixed and unsuffixed names exist, neither may be destroyed."""
+    name, suffixed = make_frame_file(archive, index=0, label="f")
+    plain = os.path.join(os.path.dirname(suffixed), name.filename())
+    write_fits(plain, solar_disc(size=32, radius=10, peak=1.0))
+    plain_bytes = open(plain, "rb").read()
+
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+    assert os.path.exists(suffixed), "the suffixed file was destroyed"
+    assert open(plain, "rb").read() == plain_bytes, "the existing file was overwritten"
+
+
+def test_unrename_can_be_scoped_to_one_band(archive, db_path):
+    make_frame_file(archive, wavelength=171, index=0, label="f")
+    make_frame_file(archive, wavelength=304, index=0, label="f")
+    migrate_unrename.main(
+        ["--root", str(archive), "--db", db_path, "--apply", "--wavelength", "171"]
+    )
+    band_171 = os.listdir(_day_dir(archive))
+    band_304 = os.listdir(
+        os.path.join(str(archive), "goes16/l2/data/suvi-l2-ci304/2024/05/10")
+    )
+    assert not [n for n in band_171 if n.endswith("_f.fits")]
+    assert [n for n in band_304 if n.endswith("_f.fits")]
+
+
+def test_unrename_on_an_already_clean_archive(archive, db_path):
+    make_frame_file(archive, index=0, label=None)
+    assert migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"]) == 0
+
+
+def test_unrename_reports_a_missing_root(tmp_path, db_path):
+    assert migrate_unrename.main(
+        ["--root", str(tmp_path / "nope"), "--db", db_path, "--apply"]
+    ) == 1
+
+
+def test_walk_archive_finds_only_frames(labelled_archive):
+    archive, _ = labelled_archive
+    found = list(migrate_unrename.walk_archive(str(archive), (16,), (171,)))
+    assert len(found) == 7
+    assert all(name is not None for _, _, name in found)
+
+
+def test_walk_surfaces_unreadable_directories(archive, monkeypatch):
+    """A filesystem error must not look like an empty archive.
+
+    os.walk ignores errors by default, so a transient ENFILE on the shared mount
+    made the walk yield nothing and the migration report "already migrated" --
+    silently skipping hundreds of thousands of files it should have renamed.
+    """
+    make_frame_file(archive, index=0, label="f")
+
+    def explode(path):
+        raise OSError(23, "Too many open files in system")
+
+    monkeypatch.setattr(os, "scandir", explode)
+    with pytest.raises(OSError):
+        list(migrate_unrename.walk_archive(str(archive), (16,), (171,)))
+
+
+def test_unrename_records_and_skips_completed_chunks(labelled_archive, db_path):
+    """A resume must skip finished band-years without touching the filesystem.
+
+    Re-walking completed subtrees on every resume is what made the migration
+    traverse the archive several times over, and traversal is what exhausts the
+    mount's file handles.
+    """
+    archive, _ = labelled_archive
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+
+    conn = db.connect(db_path, readonly=True)
+    assert db.get_meta(conn, migrate_unrename.chunk_key(171, 2024)) == "done"
+    conn.close()
+
+    def explode(*args, **kwargs):
+        raise AssertionError("resume re-read the filesystem for a completed chunk")
+
+    import unittest.mock as mock
+
+    with mock.patch.object(migrate_unrename, "walk_archive", explode):
+        assert migrate_unrename.main(
+            ["--root", str(archive), "--db", db_path, "--apply"]
+        ) == 0
+
+
+def test_recheck_forces_a_completed_chunk_to_be_re_examined(labelled_archive, db_path):
+    archive, _ = labelled_archive
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+    calls = []
+    real = migrate_unrename.walk_archive
+
+    def spy(*args, **kwargs):
+        calls.append(args)
+        return real(*args, **kwargs)
+
+    import unittest.mock as mock
+
+    with mock.patch.object(migrate_unrename, "walk_archive", spy):
+        migrate_unrename.main(
+            ["--root", str(archive), "--db", db_path, "--apply", "--recheck"]
+        )
+    assert calls, "--recheck should re-examine the archive"
+
+
+def test_a_chunk_with_failed_renames_is_not_marked_done(labelled_archive, db_path, monkeypatch):
+    """Marking a partially failed chunk complete would make a resume skip real work."""
+    archive, _ = labelled_archive
+    real_rename = os.rename
+    state = {"n": 0}
+
+    def flaky(src, dst):
+        state["n"] += 1
+        if state["n"] == 2:
+            raise OSError(23, "Too many open files in system")
+        return real_rename(src, dst)
+
+    monkeypatch.setattr(os, "rename", flaky)
+    migrate_unrename.main(["--root", str(archive), "--db", db_path, "--apply"])
+
+    conn = db.connect(db_path, readonly=True)
+    assert db.get_meta(conn, migrate_unrename.chunk_key(171, 2024)) is None
+    conn.close()
+
+
+# --------------------------------------------------------------- review sampler
+
+
+def test_judge_timestamp_classifies_every_band(archive):
+    """The sampler's unit is a frame, but a composite needs all six bands."""
+    import filter_FITS
+
+    band_paths = {}
+    for band in (94, 131, 171, 195, 284, 304):
+        name, path = make_frame_file(archive, wavelength=band, index=0)
+        band_paths[band] = path
+
+    satellite, timestamp, verdicts = filter_FITS._judge_timestamp((16, name.t_start, band_paths))
+    assert satellite == 16
+    assert set(verdicts) == {94, 131, 171, 195, 284, 304}
+    for verdict, reason, scores in verdicts.values():
+        assert verdict in ("good", "bad")
+        assert isinstance(scores, dict)
+
+
+def test_judge_timestamp_flags_a_damaged_band(archive):
+    """A blank band must be flagged, and the others left alone."""
+    import numpy as np
+
+    import filter_FITS
+
+    band_paths = {}
+    for band in (94, 131, 171, 195, 284, 304):
+        name, path = make_frame_file(archive, wavelength=band, index=0)
+        band_paths[band] = path
+    # Replace one band with a frame carrying no signal at all.
+    write_fits(band_paths[171], np.zeros((32, 32), dtype="float32"))
+
+    _, _, verdicts = filter_FITS._judge_timestamp((16, name.t_start, band_paths))
+    assert verdicts[171][0] == "bad"
+    assert verdicts[171][1], "a flagged band must carry a reason"
diff --git a/tests/test_paths.py b/tests/test_paths.py
new file mode 100644
index 0000000..e48770d
--- /dev/null
+++ b/tests/test_paths.py
@@ -0,0 +1,115 @@
+import datetime
+import os
+
+import pytest
+
+from suvi import paths
+
+GOOD = "dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits"
+
+
+def test_parses_a_real_filename():
+    frame = paths.parse_frame_filename(GOOD)
+    assert frame.satellite == 16
+    assert frame.wavelength == 171
+    assert frame.version == "1-0-2"
+    assert frame.label is None
+    assert frame.t_end - frame.t_start == paths.CADENCE
+    assert frame.t_start == int(
+        datetime.datetime(2024, 5, 10, tzinfo=datetime.timezone.utc).timestamp()
+    )
+
+
+@pytest.mark.parametrize("label", [None, "f", "e"])
+def test_filename_round_trips(label):
+    name = GOOD if label is None else GOOD.replace(".fits", f"_{label}.fits")
+    frame = paths.parse_frame_filename(name)
+    assert frame.label == label
+    assert frame.filename(label) == name
+
+
+def test_double_suffix_keeps_outermost_label():
+    """Re-processing an already-labelled file produced '..._f_f.fits' in the archive."""
+    frame = paths.parse_frame_filename(GOOD.replace(".fits", "_f_e.fits"))
+    assert frame.label == "e"
+    assert frame.filename() == GOOD
+
+
+def test_relpath_files_under_the_start_date():
+    """A frame opening at 23:58 belongs to that day, not the day it ends on."""
+    name = "dr_suvi-l2-ci304_g18_s20241231T235800Z_e20250101T000200Z_v1-0-2.fits"
+    frame = paths.parse_frame_filename(name)
+    assert frame.relpath() == (
+        "goes18/l2/data/suvi-l2-ci304/2024/12/31/" + name
+    )
+
+
+def test_slot_identifies_the_observation():
+    frame = paths.parse_frame_filename(GOOD)
+    labelled = paths.parse_frame_filename(GOOD.replace(".fits", "_e.fits"))
+    assert frame.slot == labelled.slot == (16, 171, frame.t_start)
+
+
+def test_error_plot_name_matches_legacy_filter_output():
+    frame = paths.parse_frame_filename(GOOD)
+    assert frame.error_plot_name() == GOOD.replace(".fits", "_e.jpg")
+
+
+@pytest.mark.parametrize(
+    "name",
+    [
+        "",
+        "x" * 300,
+        "README.txt",
+        "dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits.bak",
+        "dr_suvi-l2-ci999_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits",  # bad band
+        "dr_suvi-l2-ci171_g17_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits",  # excluded sat
+        "dr_suvi-l2-ci171_g16_s20241310T000000Z_e20240510T000400Z_v1-0-2.fits",  # month 13
+        "dr_suvi-l2-ci171_g16_s20240510T000400Z_e20240510T000000Z_v1-0-2.fits",  # end <= start
+        "dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2_x.fits",  # bad label
+        "../dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits",
+        "sub/dr_suvi-l2-ci171_g16_s20240510T000000Z_e20240510T000400Z_v1-0-2.fits",
+    ],
+)
+def test_rejects_malformed_names(name):
+    assert paths.parse_frame_filename(name) is None
+
+
+def test_rejects_non_string_input():
+    for value in (None, 42, b"bytes", ["list"]):
+        assert paths.parse_frame_filename(value) is None
+
+
+def test_filename_rejects_unknown_label():
+    frame = paths.parse_frame_filename(GOOD)
+    with pytest.raises(ValueError):
+        frame.filename("q")
+
+
+def test_abspath_resolves_within_the_root(tmp_path):
+    frame = paths.parse_frame_filename(GOOD)
+    resolved = paths.abspath(frame.relpath(), root=str(tmp_path))
+    assert resolved.startswith(str(tmp_path) + os.sep)
+    assert resolved.endswith(GOOD)
+
+
+@pytest.mark.parametrize("hostile", ["../../etc/passwd", "goes16/../../../etc/passwd"])
+def test_abspath_refuses_to_escape_the_root(tmp_path, hostile):
+    with pytest.raises(ValueError):
+        paths.abspath(hostile, root=str(tmp_path))
+
+
+def test_data_root_honours_the_environment(archive):
+    assert paths.data_root() == str(archive)
+
+
+def test_default_db_path_honours_the_environment(monkeypatch, tmp_path):
+    target = tmp_path / "scratch.sqlite"
+    monkeypatch.setenv("SUVI_DB", str(target))
+    assert paths.default_db_path() == str(target)
+
+
+def test_wavelength_dirs_covers_every_combination(tmp_path):
+    dirs = paths.wavelength_dirs(str(tmp_path))
+    assert len(dirs) == len(paths.SATELLITES) * len(paths.WAVELENGTHS)
+    assert len(set(dirs)) == len(dirs)
diff --git a/tests/test_vfs.py b/tests/test_vfs.py
new file mode 100644
index 0000000..28d9da5
--- /dev/null
+++ b/tests/test_vfs.py
@@ -0,0 +1,215 @@
+import pytest
+
+"""Tests for reclaiming the virtiofs mount's file handles.
+These guard a mechanism that exists only because of an environment defect: the
+mount's daemon holds a host descriptor per inode the guest looks up, and runs out.
+The properties that matter are that reclaim is *actually verified* rather than
+assumed, and that the expensive fallback is used only when it must be.
+"""
+
+
+from suvi import vfs
+
+
+def test_drop_caches_reports_failure_without_root(monkeypatch):
+    """Must return False rather than raise, so the fallback can run."""
+    def refuse(*args, **kwargs):
+        raise PermissionError(13, "Permission denied")
+
+    monkeypatch.setattr("builtins.open", refuse)
+    assert vfs.drop_caches() is False
+
+
+def test_reclaimable_kb_reads_the_slab():
+    assert vfs.reclaimable_kb() > 0  # real /proc/meminfo
+
+
+def test_reclaimable_kb_survives_a_broken_meminfo(monkeypatch):
+    monkeypatch.setattr("builtins.open", lambda *a, **k: (_ for _ in ()).throw(OSError()))
+    assert vfs.reclaimable_kb() == 0
+
+
+def test_release_prefers_drop_caches(monkeypatch):
+    """The fallback allocates tens of GiB; it must not run when drop_caches works."""
+    monkeypatch.setattr(vfs, "drop_caches", lambda: True)
+
+    def explode(*args, **kwargs):
+        raise AssertionError("allocated memory despite drop_caches succeeding")
+
+    monkeypatch.setattr(vfs, "bytearray", explode, raising=False)
+    assert vfs.release_handles() is True
+
+
+def test_fallback_reports_failure_when_nothing_is_reclaimed(monkeypatch):
+    monkeypatch.setattr(vfs, "drop_caches", lambda: False)
+    monkeypatch.setattr(vfs, "reclaimable_kb", lambda: 1000)
+    assert vfs.release_handles(budget_gib=1, floor_kb=0) is False
+
+
+def test_release_gives_up_when_the_slab_cannot_be_read(monkeypatch):
+    monkeypatch.setattr(vfs, "drop_caches", lambda: False)
+    monkeypatch.setattr(vfs, "reclaimable_kb", lambda: 0)
+    assert vfs.release_handles() is False
+
+
+# --------------------------------------------------------------- memory bounding
+
+
+def test_available_gib_reads_meminfo():
+    assert vfs.available_gib() > 0
+
+
+def test_pressure_stops_at_the_reserve_not_a_fraction(monkeypatch):
+    """Capping at a fraction of available memory reclaims nothing.
+
+    The kernel only frees slab under genuine pressure, so leaving 40% headroom
+    means it never triggers: an earlier version allocated 14 GiB of a 23 GiB
+    allowance and freed zero, costing the machine the memory for no benefit.
+    Pressure must run down to a fixed reserve instead.
+    """
+    monkeypatch.setattr(vfs, "drop_caches", lambda: False)
+    monkeypatch.setattr(vfs, "reclaimable_kb", lambda: 1000)  # never yields
+    available = [20.0]
+    monkeypatch.setattr(vfs, "available_gib", lambda: available[0])
+    allocated = []
+    real = bytearray
+
+    def fake(n):
+        allocated.append(n)
+        available[0] -= 1.0  # each GiB claimed reduces what is available
+        return real(1)
+
+    monkeypatch.setattr(vfs, "bytearray", fake, raising=False)
+    assert vfs.release_handles(reserve_gib=2.0, floor_kb=0) is False
+    # Pushed from 20 GiB down to the 2 GiB reserve, not stopped at 60%.
+    assert 17 <= len(allocated) <= 19, f"allocated {len(allocated)} GiB"
+
+
+def test_pressure_stops_as_soon_as_the_slab_yields(monkeypatch):
+    monkeypatch.setattr(vfs, "drop_caches", lambda: False)
+    readings = iter([1000, 1000, 1000, 400])
+    monkeypatch.setattr(vfs, "reclaimable_kb", lambda: next(readings))
+    monkeypatch.setattr(vfs, "available_gib", lambda: 20.0)
+    allocated = []
+    real = bytearray
+    monkeypatch.setattr(
+        vfs, "bytearray", lambda n: allocated.append(n) or real(1), raising=False
+    )
+    assert vfs.release_handles(floor_kb=0) is True
+    assert len(allocated) == 2, "kept allocating after the kernel gave ground"
+
+
+# ------------------------------------------------------------------- Reliever
+
+
+def test_reliever_fires_on_the_interval(monkeypatch):
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    reliever = vfs.Reliever(interval=10)
+    for _ in range(9):
+        reliever.tick()
+    assert calls == []
+    reliever.tick()
+    assert len(calls) == 1
+
+
+def test_reliever_keeps_firing_across_a_long_run(monkeypatch):
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    reliever = vfs.Reliever(interval=10)
+    for _ in range(100):
+        reliever.tick()
+    assert len(calls) == 10, "stopped reclaiming partway through a long traversal"
+    assert reliever.releases == 10
+
+
+def test_reliever_counts_batched_items(monkeypatch):
+    """Callers processing six bands per timestamp tick by six, not one."""
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    reliever = vfs.Reliever(interval=10)
+    reliever.tick(6)
+    reliever.tick(6)
+    assert len(calls) == 1
+    assert reliever.seen == 12
+
+
+def test_reliever_can_be_disabled(monkeypatch):
+    def explode(*a, **k):
+        raise AssertionError("reclaimed while disabled")
+
+    monkeypatch.setattr(vfs, "release_handles", explode)
+    reliever = vfs.Reliever(interval=1, enabled=False)
+    for _ in range(50):
+        reliever.tick()
+    assert reliever.releases == 0
+
+
+def test_reliever_reclaims_when_the_run_ends(monkeypatch):
+    """Reclaiming only during a run leaves the machine loaded once it finishes.
+
+    The inodes a traversal cached stay pinned -- and with them the host's file
+    handles -- until something else forces reclaim.  That is why the system was
+    still saturated with nothing of ours running.
+    """
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    reliever = vfs.Reliever(interval=1000, on_exit=False)
+    reliever.tick(5)
+    assert calls == [], "should not have reclaimed mid-run yet"
+    reliever.finish()
+    assert len(calls) == 1
+
+
+def test_finish_is_idempotent(monkeypatch):
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    reliever = vfs.Reliever(interval=1000, on_exit=False)
+    reliever.tick()
+    reliever.finish()
+    reliever.finish()
+    reliever.finish()
+    assert len(calls) == 1
+
+
+def test_finish_does_nothing_if_no_work_happened(monkeypatch):
+    def explode(*a, **k):
+        raise AssertionError("reclaimed despite processing nothing")
+
+    monkeypatch.setattr(vfs, "release_handles", explode)
+    vfs.Reliever(on_exit=False).finish()
+
+
+def test_reliever_works_as_a_context_manager(monkeypatch):
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    with vfs.Reliever(interval=1000, on_exit=False) as reliever:
+        reliever.tick(3)
+        assert calls == []
+    assert len(calls) == 1
+
+
+def test_context_manager_reclaims_even_when_the_body_raises(monkeypatch):
+    calls = []
+    monkeypatch.setattr(vfs, "release_handles", lambda *a, **k: calls.append(1) or True)
+    with pytest.raises(ValueError):
+        with vfs.Reliever(interval=1000, on_exit=False) as reliever:
+            reliever.tick()
+            raise ValueError("boom")
+    assert len(calls) == 1, "a failed job must still hand its handles back"
+
+
+def test_no_pressure_is_applied_when_the_slab_is_already_small(monkeypatch):
+    """Below the floor the slab is live processes' working set, not archive inodes.
+
+    Squeezing the machine to shave a few hundred megabytes off it costs far more
+    than it gains -- and during a long job this runs every RELIEF_INTERVAL items.
+    """
+    monkeypatch.setattr(vfs, "drop_caches", lambda: False)
+    monkeypatch.setattr(vfs, "reclaimable_kb", lambda: 500 * 1024)  # 0.5 GiB
+
+    def explode(*a, **k):
+        raise AssertionError("applied memory pressure below the floor")
+
+    monkeypatch.setattr(vfs, "bytearray", explode, raising=False)
+    assert vfs.release_handles() is True