Phase 1 data layer: calc/fmt/alarms + 31 CPython tests + live gateway P1 smoke

pytest 31/31. In-gateway end-to-end: 559 activations correlated (uuid mode), 3 chatterers,
34 fleeting, 1 flood, health F(22) on the deliberately-bad sim plant. Gate G1 green.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/alarms/code.py

@@ -0,0 +1,396 @@
+# PrimeControls.alarms - gateway adapter (the ONLY impure module).
+# Journal access via system.alarm.queryJournal/queryStatus exclusively - no SQL,
+# no journal name assumptions, every query bounded by the caller's date range.
+# Jython 2.7. Bare except is used on defensive paths deliberately: java exceptions
+# do not subclass Python Exception and would bypass 'except Exception'.
+from __future__ import division, print_function
+
+import sys
+
+from PrimeControls import calc, fmt
+
+
+def _err_text():
+    try:
+        return "%s" % (sys.exc_info()[1],)
+    except:
+        return "unknown error"
+
+
+def _now_ms():
+    try:
+        return system.date.toMillis(system.date.now())
+    except:
+        import time
+        return int(time.time() * 1000)
+
+
+def _ms_of(java_date):
+    try:
+        if java_date is None:
+            return None
+        return java_date.getTime()
+    except:
+        return None
+
+
+def _norm_event(evt):
+    try:
+        source = str(evt.getSource() or "")
+        state = None
+        try:
+            if evt.getAckData() is not None:
+                state = "ack"
+            elif evt.getClearedData() is not None:
+                state = "clear"
+            elif evt.getActiveData() is not None:
+                state = "active"
+        except:
+            state = None
+        if state is None:
+            s = ""
+            try:
+                s = str(evt.getState() or "")
+            except:
+                pass
+            if s.startswith("Cleared"):
+                state = "clear"
+            elif "Acknowledged" in s and not s.startswith("Active,"):
+                state = "ack"
+            else:
+                state = "active"
+        ts = None
+        try:
+            ts = _ms_of(evt.get("eventTime"))
+        except:
+            ts = None
+        if ts is None:
+            return None
+        prio_raw = None
+        try:
+            p = evt.getPriority()
+            try:
+                prio_raw = int(p.ordinal())
+            except:
+                prio_raw = str(p)
+        except:
+            prio_raw = None
+        lvl, name = calc.normalize_priority(prio_raw)
+        display_path = ""
+        try:
+            display_path = str(evt.getDisplayPath() or "")
+        except:
+            pass
+        is_system = source.startswith("evt:") or ":/alm:" not in source
+        try:
+            if evt.get("isSystemEvent"):
+                is_system = True
+        except:
+            pass
+        ack_user = None
+        try:
+            u = evt.get("ackUserName")
+            if u:
+                ack_user = str(u)
+        except:
+            pass
+        event_id = None
+        try:
+            event_id = str(evt.getId())
+        except:
+            pass
+        return {"event_id": event_id, "source": source, "display_path": display_path,
+                "priority": lvl, "priority_name": name, "state": state, "ts": ts,
+                "is_system": is_system, "ack_user": ack_user}
+    except:
+        return None
+
+
+def _fetch_journal(start_ms, end_ms, max_events, include_data=False):
+    """Returns (rows, dropped, truncated, error)."""
+    rows = []
+    dropped = 0
+    truncated = False
+    try:
+        kwargs = {"startDate": int(start_ms), "endDate": int(end_ms)}
+        result = system.alarm.queryJournal(**kwargs)
+        for evt in result:
+            r = _norm_event(evt)
+            if r is None:
+                dropped += 1
+                continue
+            rows.append(r)
+            if len(rows) >= max_events:
+                truncated = True
+                break
+        return rows, dropped, truncated, None
+    except:
+        return rows, dropped, truncated, _err_text()
+
+
+def _fetch_status():
+    out = []
+    try:
+        result = system.alarm.queryStatus(state=["ActiveUnacked", "ActiveAcked"])
+        for evt in result:
+            try:
+                source = str(evt.getSource() or "")
+                if source.startswith("evt:") or ":/alm:" not in source:
+                    continue
+                active_ms = None
+                try:
+                    data = evt.getActiveData()
+                    if data is not None:
+                        active_ms = _ms_of(data.get("eventTime"))
+                except:
+                    active_ms = None
+                if active_ms is None:
+                    try:
+                        active_ms = _ms_of(evt.get("eventTime"))
+                    except:
+                        pass
+                prio_raw = None
+                try:
+                    p = evt.getPriority()
+                    try:
+                        prio_raw = int(p.ordinal())
+                    except:
+                        prio_raw = str(p)
+                except:
+                    pass
+                lvl, name = calc.normalize_priority(prio_raw)
+                unacked = False
+                try:
+                    unacked = "Unacknowledged" in str(evt.getState() or "")
+                except:
+                    pass
+                display_path = ""
+                try:
+                    display_path = str(evt.getDisplayPath() or "")
+                except:
+                    pass
+                out.append({"source": source, "display_path": display_path,
+                            "priority": lvl, "priority_name": name,
+                            "active_ms": active_ms, "unacked": unacked})
+            except:
+                continue
+    except:
+        pass
+    return out
+
+
+def _fetch_shelved():
+    try:
+        paths = system.alarm.getShelvedPaths()
+        return len(list(paths)) if paths is not None else 0
+    except:
+        return None
+
+
+def _clean_filters(options):
+    f = {"priorities": [], "areas": [], "states": [], "search": ""}
+    if not options:
+        return f
+    try:
+        for k in ("priorities", "areas", "states"):
+            v = options.get(k)
+            if v:
+                f[k] = [x for x in list(v)]
+        f["priorities"] = [int(x) for x in f["priorities"]]
+        f["areas"] = [str(x) for x in f["areas"]]
+        f["states"] = [str(x) for x in f["states"]]
+        f["search"] = str(options.get("search") or "")
+    except:
+        pass
+    return f
+
+
+# ---------------- Perspective entry points ----------------
+
+
+def getDashboardBundle(startMs, endMs, options=None):
+    try:
+        s = int(startMs)
+        e = int(endMs)
+        opts = calc.opts_merged(None)
+        filters = _clean_filters(options)
+        span = max(e - s, 1)
+        rows, dropped, truncated, err = _fetch_journal(
+            s - span, e, int(opts["max_events"]))
+        active_now = _fetch_status()
+        shelved = _fetch_shelved()
+        bundle = calc.build_bundle(rows, active_now, shelved, s, e, _now_ms(),
+                                   {"filters": filters})
+        bundle["meta"]["dropped_rows"] = dropped
+        bundle["meta"]["truncated"] = truncated
+        if err:
+            bundle["meta"]["error"] = err
+        bundle["insights"] = fmt.insights(bundle)
+        return bundle
+    except:
+        try:
+            bundle = calc.build_bundle([], [], None, int(startMs or 0),
+                                       int(endMs or 0), _now_ms(), None)
+        except:
+            bundle = calc.build_bundle([], [], None, 0, 0, 0, None)
+        bundle["meta"]["error"] = _err_text()
+        bundle["insights"] = []
+        return bundle
+
+
+STATE_LABELS = {"active": "Active", "clear": "Cleared", "ack": "Acked"}
+
+
+def _journal_rows(start_ms, end_ms, filters, max_rows):
+    rows, dropped, truncated, err = _fetch_journal(start_ms, end_ms, max_rows)
+    out = []
+    prios = set(filters.get("priorities") or [])
+    areas = set(filters.get("areas") or [])
+    states = set(filters.get("states") or [])
+    search = (filters.get("search") or "").strip().lower()
+    for r in rows:
+        if r["is_system"]:
+            continue
+        parsed = calc.parse_source(r["source"], r["display_path"])
+        if prios and r["priority"] not in prios:
+            continue
+        if areas and parsed["area"] not in areas:
+            continue
+        if states:
+            tag = {"active": "active", "clear": "cleared", "ack": "acked"}[r["state"]]
+            if tag not in states and not ("unacked" in states and r["state"] == "active"):
+                continue
+        if search and search not in (r["source"] + " " + parsed["label"]).lower():
+            continue
+        out.append({"id": r["event_id"], "time_ms": r["ts"],
+                    "time_label": fmt.day_clock(r["ts"]),
+                    "source": r["source"], "label": parsed["label"],
+                    "area": parsed["area"], "state": r["state"],
+                    "state_label": STATE_LABELS.get(r["state"], r["state"]),
+                    "priority": r["priority"], "priority_name": r["priority_name"],
+                    "ack_user": r["ack_user"] or ""})
+    out.sort(key=lambda r: -(r["time_ms"] or 0))
+    return out, truncated, err
+
+
+def getJournalPage(startMs, endMs, filters=None, page=0, pageSize=50):
+    try:
+        f = _clean_filters(filters)
+        rows, truncated, err = _journal_rows(int(startMs), int(endMs), f,
+                                             int(calc.DEFAULTS["max_events"]))
+        page = max(0, int(page or 0))
+        page_size = max(1, int(pageSize or 50))
+        start = page * page_size
+        return {"rows": rows[start:start + page_size], "total": len(rows),
+                "page": page, "page_size": page_size, "truncated": truncated,
+                "error": err}
+    except:
+        return {"rows": [], "total": 0, "page": 0, "page_size": int(pageSize or 50),
+                "truncated": False, "error": _err_text()}
+
+
+def journalCsv(startMs, endMs, filters=None, maxRows=10000):
+    try:
+        f = _clean_filters(filters)
+        rows, truncated, err = _journal_rows(int(startMs), int(endMs), f, int(maxRows))
+        headers = ["time", "state", "priority", "label", "area", "source", "ack_user"]
+        data = [[r["time_label"], r["state_label"], r["priority_name"], r["label"],
+                 r["area"], r["source"], r["ack_user"]] for r in rows]
+        ds = system.dataset.toDataSet(headers, data)
+        return system.dataset.toCSV(ds)
+    except:
+        return "error,%s" % _err_text().replace(",", ";")
+
+
+def getSourceDetail(source, startMs, endMs):
+    try:
+        s = int(startMs)
+        e = int(endMs)
+        src = str(source or "")
+        rows, dropped, truncated, err = _fetch_journal(s, e, int(calc.DEFAULTS["max_events"]))
+        mine = [r for r in rows if r["source"] == src]
+        instances, _mode = calc.correlate_instances(mine)
+        parsed = calc.parse_source(src, mine[0]["display_path"] if mine else "")
+        day_bins = calc.rate_bins(instances, s, e, {"bin_ms": 86400000, "max_bins": 400})
+        daily = [{"t0": b["t0"], "count": b["count"]} for b in day_bins["bins"]]
+        ttas = [i["tta_ms"] for i in instances if i.get("tta_ms") is not None]
+        durs = [i["duration_ms"] for i in instances if i.get("duration_ms") is not None]
+        fleet = len([i for i in instances
+                     if i.get("duration_ms") is not None
+                     and i["duration_ms"] < calc.DEFAULTS["fleeting_s"] * 1000])
+        ack_users = {}
+        for r in mine:
+            if r["state"] == "ack" and r.get("ack_user"):
+                ack_users[r["ack_user"]] = ack_users.get(r["ack_user"], 0) + 1
+        top_ack = [{"user": u, "count": c} for u, c in
+                   sorted(ack_users.items(), key=lambda kv: -kv[1])[:5]]
+        events = []
+        for r in sorted(mine, key=lambda r: -r["ts"])[:100]:
+            events.append({"id": r["event_id"], "time_ms": r["ts"],
+                           "time_label": fmt.day_clock(r["ts"]),
+                           "state_label": STATE_LABELS.get(r["state"], r["state"]),
+                           "priority_name": r["priority_name"],
+                           "ack_user": r["ack_user"] or ""})
+        return {"label": parsed["label"], "area": parsed["area"], "events": events,
+                "daily": daily,
+                "stats": {"count": len([i for i in instances if i["active_ms"] is not None]),
+                          "avg_tta_ms": (sum(ttas) / len(ttas)) if ttas else None,
+                          "avg_active_ms": (sum(durs) / len(durs)) if durs else None,
+                          "fleeting_count": fleet, "top_ack_users": top_ack},
+                "error": err}
+    except:
+        return {"label": str(source or ""), "area": "", "events": [], "daily": [],
+                "stats": {"count": 0, "avg_tta_ms": None, "avg_active_ms": None,
+                          "fleeting_count": 0, "top_ack_users": []},
+                "error": _err_text()}
+
+
+def getEventData(eventId, aroundMs, source):
+    try:
+        eid = str(eventId or "")
+        mid = int(aroundMs)
+        props = []
+        seen = {}
+        try:
+            result = system.alarm.queryJournal(startDate=mid - 3600000,
+                                               endDate=mid + 3600000,
+                                               includeData=True)
+        except:
+            result = system.alarm.queryJournal(startDate=mid - 3600000,
+                                               endDate=mid + 3600000)
+        for evt in result:
+            try:
+                if str(evt.getId()) != eid:
+                    continue
+                try:
+                    names = evt.getProperties()
+                except:
+                    names = []
+                for p in names or []:
+                    try:
+                        n = str(p)
+                        v = evt.get(p)
+                        if n not in seen:
+                            seen[n] = True
+                            props.append({"name": n, "value": str(v)})
+                    except:
+                        continue
+            except:
+                continue
+        props.sort(key=lambda kv: kv["name"])
+        return {"props": props, "error": None}
+    except:
+        return {"props": [], "error": _err_text()}
+
+
+def getShiftReportText(shiftHours=8, anchorHour=0, options=None):
+    try:
+        bounds = fmt.shift_bounds(_now_ms(), int(shiftHours), int(anchorHour))
+        s, e = bounds["previous"]
+        bundle = getDashboardBundle(s, e, options)
+        report = fmt.shift_report(bundle, bounds["label"])
+        return {"text": report["text"], "start_ms": s, "end_ms": e,
+                "label": bounds["label"]}
+    except:
+        return {"text": "Shift report unavailable: %s" % _err_text(),
+                "start_ms": 0, "end_ms": 0, "label": ""}

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/alarms/resource.json

@@ -0,0 +1,12 @@
+{
+  "scope": "A",
+  "version": 1,
+  "restricted": false,
+  "overridable": true,
+  "files": [
+    "code.py"
+  ],
+  "attributes": {
+    "hintScope": 2
+  }
+}

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/calc/code.py

@@ -0,0 +1,737 @@
+# PrimeControls.calc - PURE alarm analytics computation (no system.*, no I/O, no clock).
+# Runs under Jython 2.7 (Ignition) AND CPython 3 (pytest). No f-strings.
+from __future__ import division, print_function
+
+DEFAULTS = {
+    "bin_ms": 600000, "flood_per_10min": 10, "flood_end_per_10min": 5,
+    "target_per_hr": 6.0,
+    "chatter_per_hr": 10.0, "chatter_gap_s": 120, "chatter_min_count": 5,
+    "fleeting_s": 10, "fleeting_min_count": 3,
+    "standing_hours": 24, "trend_buckets": 24,
+    "max_events": 50000, "max_bins": 5000,
+    "delta_flat_pct": 5.0, "insights_max": 5,
+    "priority_target": {"low": 80.0, "medium": 15.0, "high": 5.0},
+    "health_weights": {"rate": 0.30, "flood": 0.25, "chatter": 0.20,
+                       "standing": 0.15, "priority": 0.10},
+    "grade_cuts": [(90, "A"), (80, "B"), (70, "C"), (60, "D"), (0, "F")],
+    "list_cap": 50, "active_now_cap": 200,
+}
+
+PRIORITY_NAMES = {0: "Diagnostic", 1: "Low", 2: "Medium", 3: "High", 4: "Critical"}
+
+
+def opts_merged(opts):
+    out = dict(DEFAULTS)
+    if opts:
+        for k in opts:
+            out[k] = opts[k]
+    return out
+
+
+def clamp(v, lo, hi):
+    return max(lo, min(hi, v))
+
+
+def _median(values):
+    vs = sorted(v for v in values if v is not None)
+    n = len(vs)
+    if n == 0:
+        return None
+    if n % 2:
+        return float(vs[n // 2])
+    return (vs[n // 2 - 1] + vs[n // 2]) / 2.0
+
+
+def _mean(values):
+    vs = [v for v in values if v is not None]
+    if not vs:
+        return None
+    return sum(vs) / float(len(vs))
+
+
+def _safe_div(a, b):
+    try:
+        if not b:
+            return None
+        return a / float(b)
+    except Exception:
+        return None
+
+
+# ---------------- path parsing ----------------
+
+
+def parse_source(source, display_path):
+    source = source or ""
+    display_path = display_path or ""
+    tag_segments = []
+    alarm_name = ""
+    if ":/tag:" in source:
+        tag_part = source.split(":/tag:", 1)[1]
+        tag_path = tag_part.split(":", 1)[0]
+        tag_segments = [s for s in tag_path.split("/") if s]
+        if ":/alm:" in source:
+            alarm_name = source.split(":/alm:", 1)[1].split(":", 1)[0]
+    if display_path:
+        segments = [s for s in display_path.split("/") if s]
+    elif tag_segments:
+        segments = list(tag_segments)
+        if alarm_name and (not segments or alarm_name.lower() != segments[-1].lower()):
+            segments.append(alarm_name)
+    else:
+        segments = [source] if source else ["unknown"]
+    if len(segments) >= 2:
+        label = "/".join(segments[-2:])
+    else:
+        label = segments[0]
+    base = tag_segments if tag_segments else segments
+    if len(base) >= 2:
+        area = base[-2]
+    else:
+        area = base[0] if base else "unknown"
+    return {"label": label, "area": area, "segments": segments}
+
+
+def normalize_priority(value):
+    try:
+        iv = int(value)
+        if 0 <= iv <= 4:
+            return iv, PRIORITY_NAMES[iv]
+    except Exception:
+        pass
+    s = str(value).strip().lower() if value is not None else ""
+    for lvl in PRIORITY_NAMES:
+        if PRIORITY_NAMES[lvl].lower() in s and s:
+            return lvl, PRIORITY_NAMES[lvl]
+    return -1, (str(value) if value is not None else "Unknown")
+
+
+# ---------------- correlation ----------------
+
+
+def _new_instance(row):
+    lvl, name = row.get("priority", -1), row.get("priority_name", "Unknown")
+    parsed = parse_source(row.get("source"), row.get("display_path"))
+    return {"event_id": row.get("event_id"), "source": row.get("source") or "",
+            "label": parsed["label"], "area": parsed["area"],
+            "priority": lvl, "priority_name": name,
+            "active_ms": None, "clear_ms": None, "ack_ms": None,
+            "duration_ms": None, "tta_ms": None, "open": True,
+            "ack_user": None}
+
+
+def _finalize(inst):
+    a, c, k = inst["active_ms"], inst["clear_ms"], inst["ack_ms"]
+    inst["duration_ms"] = (c - a) if (a is not None and c is not None and c >= a) else None
+    inst["tta_ms"] = (k - a) if (a is not None and k is not None and k >= a) else None
+    inst["open"] = c is None
+    return inst
+
+
+def correlate_instances(rows):
+    rows = [r for r in (rows or []) if r and not r.get("is_system") and r.get("ts") is not None]
+    rows.sort(key=lambda r: r["ts"])
+    if not rows:
+        return [], "uuid"
+    with_id = [r for r in rows if r.get("event_id")]
+    mode = "uuid" if len(with_id) >= 0.9 * len(rows) else "source-sequence"
+    instances = []
+    if mode == "uuid":
+        groups, order = {}, []
+        for i, r in enumerate(rows):
+            k = r.get("event_id") or ("_noid_%d" % i)
+            if k not in groups:
+                groups[k] = []
+                order.append(k)
+            groups[k].append(r)
+        for k in order:
+            grp = groups[k]
+            ident = None
+            for r in grp:
+                if r["state"] == "active":
+                    ident = r
+                    break
+            inst = _new_instance(ident or grp[0])
+            acts = [r["ts"] for r in grp if r["state"] == "active"]
+            clears = [r["ts"] for r in grp if r["state"] == "clear"]
+            acks = [r["ts"] for r in grp if r["state"] == "ack"]
+            inst["active_ms"] = min(acts) if acts else None
+            inst["clear_ms"] = min(clears) if clears else None
+            inst["ack_ms"] = min(acks) if acks else None
+            for r in grp:
+                if r.get("ack_user"):
+                    inst["ack_user"] = r["ack_user"]
+                    break
+            instances.append(_finalize(inst))
+    else:
+        open_by_src = {}
+        for r in rows:
+            src = r.get("source") or ""
+            st = r.get("state")
+            if st == "active":
+                if src in open_by_src:
+                    instances.append(_finalize(open_by_src.pop(src)))
+                inst = _new_instance(r)
+                inst["active_ms"] = r["ts"]
+                open_by_src[src] = inst
+            else:
+                inst = open_by_src.get(src)
+                if inst is None:
+                    inst = _new_instance(r)
+                    open_by_src[src] = inst
+                if st == "clear" and inst["clear_ms"] is None:
+                    inst["clear_ms"] = r["ts"]
+                elif st == "ack" and inst["ack_ms"] is None:
+                    inst["ack_ms"] = r["ts"]
+                    if r.get("ack_user"):
+                        inst["ack_user"] = r["ack_user"]
+        for src in open_by_src:
+            instances.append(_finalize(open_by_src[src]))
+        instances.sort(key=lambda i: i["active_ms"] if i["active_ms"] is not None else 0)
+    return instances, mode
+
+
+def partition_instances(instances, start_ms, end_ms):
+    prior_start = start_ms - (end_ms - start_ms)
+    current, prior, orphans = [], [], []
+    for inst in instances or []:
+        a = inst.get("active_ms")
+        if a is None:
+            orphans.append(inst)
+        elif start_ms <= a <= end_ms:
+            current.append(inst)
+        elif prior_start <= a < start_ms:
+            prior.append(inst)
+        else:
+            orphans.append(inst)
+    return current, prior, orphans
+
+
+def apply_filters(instances, filters):
+    if not filters:
+        return instances
+    prios = set(filters.get("priorities") or [])
+    areas = set(filters.get("areas") or [])
+    states = set(filters.get("states") or [])
+    search = (filters.get("search") or "").strip().lower()
+    if not prios and not areas and not states and not search:
+        return instances
+    out = []
+    for inst in instances:
+        if prios and inst["priority"] not in prios:
+            continue
+        if areas and inst["area"] not in areas:
+            continue
+        if states:
+            tags = set()
+            if inst["open"]:
+                tags.add("active")
+            if inst["clear_ms"] is not None:
+                tags.add("cleared")
+            if inst["ack_ms"] is not None:
+                tags.add("acked")
+            else:
+                tags.add("unacked")
+            if not (states & tags):
+                continue
+        if search:
+            hay = (inst["source"] + " " + inst["label"]).lower()
+            if search not in hay:
+                continue
+        out.append(inst)
+    return out
+
+
+# ---------------- rate / floods ----------------
+
+
+def rate_bins(instances, start_ms, end_ms, opts=None):
+    o = opts_merged(opts)
+    bin_ms = int(o["bin_ms"])
+    empty = {"bins": [], "bin_ms": bin_ms,
+             "target_per_bin": o["target_per_hr"] * bin_ms / 3600000.0,
+             "flood_threshold": 1, "max_count": 0}
+    if end_ms is None or start_ms is None or end_ms <= start_ms:
+        return empty
+    while (end_ms - start_ms) // bin_ms + 1 > o["max_bins"]:
+        bin_ms *= 2
+    origin = (start_ms // bin_ms) * bin_ms
+    n = int((end_ms - origin) // bin_ms) + 1
+    counts = {}
+    for inst in instances or []:
+        a = inst.get("active_ms")
+        if a is None or a < origin or a > end_ms:
+            continue
+        idx = int((a - origin) // bin_ms)
+        counts[idx] = counts.get(idx, 0) + 1
+    flood_threshold = max(1, int(round(o["flood_per_10min"] * bin_ms / 600000.0)))
+    bins = []
+    max_count = 0
+    for i in range(n):
+        c = counts.get(i, 0)
+        max_count = max(max_count, c)
+        bins.append({"t0": origin + i * bin_ms, "t1": origin + (i + 1) * bin_ms,
+                     "count": c, "flood": c > flood_threshold})
+    return {"bins": bins, "bin_ms": bin_ms,
+            "target_per_bin": o["target_per_hr"] * bin_ms / 3600000.0,
+            "flood_threshold": flood_threshold, "max_count": max_count}
+
+
+def flood_episodes(bins_result, instances, start_ms, end_ms, opts=None):
+    o = opts_merged(opts)
+    bins = (bins_result or {}).get("bins") or []
+    bin_ms = (bins_result or {}).get("bin_ms") or o["bin_ms"]
+    thr = (bins_result or {}).get("flood_threshold") or 1
+    end_thr = max(1, int(round(o["flood_end_per_10min"] * bin_ms / 600000.0)))
+    episodes = []
+    cur = None
+    for b in bins:
+        if cur is None:
+            if b["count"] > thr:
+                cur = {"start_ms": b["t0"], "end_ms": b["t1"], "peak_bin_count": b["count"]}
+        else:
+            if b["count"] >= end_thr:
+                cur["end_ms"] = b["t1"]
+                cur["peak_bin_count"] = max(cur["peak_bin_count"], b["count"])
+            else:
+                episodes.append(cur)
+                cur = None
+    if cur is not None:
+        episodes.append(cur)
+    for ep in episodes:
+        ep["duration_ms"] = ep["end_ms"] - ep["start_ms"]
+        src_counts = {}
+        area_counts = {}
+        total = 0
+        for inst in instances or []:
+            a = inst.get("active_ms")
+            if a is not None and ep["start_ms"] <= a < ep["end_ms"]:
+                total += 1
+                key = (inst["source"], inst["label"])
+                src_counts[key] = src_counts.get(key, 0) + 1
+                area_counts[inst["area"]] = area_counts.get(inst["area"], 0) + 1
+        ep["event_count"] = total
+        if src_counts:
+            best = sorted(src_counts.items(), key=lambda kv: (-kv[1], kv[0][1]))[0]
+            ep["top_source_label"] = best[0][1]
+            ep["top_source_count"] = best[1]
+        else:
+            ep["top_source_label"] = ""
+            ep["top_source_count"] = 0
+        if area_counts:
+            ep["top_area"] = sorted(area_counts.items(), key=lambda kv: (-kv[1], kv[0]))[0][0]
+        else:
+            ep["top_area"] = ""
+    span = (end_ms - start_ms) if (end_ms and start_ms and end_ms > start_ms) else 0
+    pct = 0.0
+    if span:
+        pct = 100.0 * sum(ep["duration_ms"] for ep in episodes) / span
+    return {"episodes": episodes, "pct_time_in_flood": pct}
+
+
+# ---------------- detections ----------------
+
+
+def chattering(instances, start_ms, end_ms, opts=None):
+    o = opts_merged(opts)
+    window_h = _safe_div(end_ms - start_ms, 3600000.0) if (end_ms and start_ms) else None
+    if not window_h or window_h <= 0:
+        return []
+    groups = {}
+    for inst in instances or []:
+        a = inst.get("active_ms")
+        if a is None:
+            continue
+        groups.setdefault(inst["source"], []).append(inst)
+    out = []
+    for src in groups:
+        insts = groups[src]
+        count = len(insts)
+        if count < o["chatter_min_count"]:
+            continue
+        per_hour = count / window_h
+        times = sorted(i["active_ms"] for i in insts)
+        gaps = [times[i + 1] - times[i] for i in range(len(times) - 1)]
+        med_gap = _median(gaps)
+        if per_hour > o["chatter_per_hr"] and med_gap is not None and med_gap <= o["chatter_gap_s"] * 1000:
+            ref = insts[0]
+            out.append({"source": src, "label": ref["label"], "area": ref["area"],
+                        "priority_name": ref["priority_name"], "count": count,
+                        "per_hour": per_hour, "median_gap_s": med_gap / 1000.0})
+    out.sort(key=lambda r: (-r["per_hour"], r["label"]))
+    return out[:int(o["list_cap"])]
+
+
+def fleeting(instances, opts=None):
+    o = opts_merged(opts)
+    thresh = o["fleeting_s"] * 1000
+    groups = {}
+    total = 0
+    for inst in instances or []:
+        d = inst.get("duration_ms")
+        if d is not None and d < thresh:
+            total += 1
+            groups.setdefault(inst["source"], []).append(inst)
+    sources = []
+    for src in groups:
+        insts = groups[src]
+        if len(insts) < o["fleeting_min_count"]:
+            continue
+        ref = insts[0]
+        sources.append({"source": src, "label": ref["label"], "area": ref["area"],
+                        "priority_name": ref["priority_name"], "count": len(insts),
+                        "median_s": (_median([i["duration_ms"] for i in insts]) or 0) / 1000.0})
+    sources.sort(key=lambda r: (-r["count"], r["label"]))
+    return {"total": total, "sources": sources[:int(o["list_cap"])]}
+
+
+def standing(active_now, open_instances, now_ms, opts=None):
+    o = opts_merged(opts)
+    thresh = o["standing_hours"] * 3600000.0
+    rows = []
+    if active_now:
+        mode = "status"
+        for s in active_now:
+            a = s.get("active_ms")
+            age = (now_ms - a) if (a is not None and now_ms) else None
+            parsed = parse_source(s.get("source"), s.get("display_path"))
+            rows.append({"source": s.get("source") or "", "label": parsed["label"],
+                         "area": parsed["area"],
+                         "priority_name": s.get("priority_name", "Unknown"),
+                         "active_ms": a, "age_ms": age,
+                         "age_h": (age / 3600000.0) if age is not None else None,
+                         "unacked": bool(s.get("unacked"))})
+    else:
+        mode = "journal"
+        for inst in open_instances or []:
+            a = inst.get("active_ms")
+            age = (now_ms - a) if (a is not None and now_ms) else None
+            rows.append({"source": inst["source"], "label": inst["label"],
+                         "area": inst["area"], "priority_name": inst["priority_name"],
+                         "active_ms": a, "age_ms": age,
+                         "age_h": (age / 3600000.0) if age is not None else None,
+                         "unacked": inst.get("ack_ms") is None})
+    rows.sort(key=lambda r: -(r["age_ms"] or -1))
+    count = len([r for r in rows if r["age_ms"] is not None and r["age_ms"] > thresh])
+    return {"mode": mode, "count": count, "rows": rows[:int(o["list_cap"])]}
+
+
+# ---------------- MTTA / MTTR ----------------
+
+
+def mtta_mttr(instances, start_ms, end_ms, opts=None):
+    o = opts_merged(opts)
+    ttas = [i["tta_ms"] for i in instances or [] if i.get("tta_ms") is not None and i["tta_ms"] >= 0]
+    durs = [i["duration_ms"] for i in instances or [] if i.get("duration_ms") is not None and i["duration_ms"] >= 0]
+    result = {"mtta": {"mean_ms": _mean(ttas), "median_ms": _median(ttas), "count": len(ttas)},
+              "mttr": {"mean_ms": _mean(durs), "median_ms": _median(durs), "count": len(durs)},
+              "trend": []}
+    if not end_ms or not start_ms or end_ms <= start_ms:
+        return result
+    span = end_ms - start_ms
+    bin_ms = int(o["bin_ms"])
+    width = max(bin_ms, ((span // int(o["trend_buckets"])) // bin_ms + 1) * bin_ms)
+    origin = (start_ms // width) * width
+    n = int((end_ms - origin) // width) + 1
+    buckets = {}
+    for inst in instances or []:
+        a = inst.get("active_ms")
+        if a is None:
+            continue
+        idx = int((a - origin) // width)
+        b = buckets.setdefault(idx, {"tta": [], "dur": []})
+        if inst.get("tta_ms") is not None and inst["tta_ms"] >= 0:
+            b["tta"].append(inst["tta_ms"])
+        if inst.get("duration_ms") is not None and inst["duration_ms"] >= 0:
+            b["dur"].append(inst["duration_ms"])
+    for i in range(n):
+        b = buckets.get(i, {"tta": [], "dur": []})
+        result["trend"].append({"t0": origin + i * width,
+                                "mtta_ms": _median(b["tta"]),
+                                "mttr_ms": _median(b["dur"]),
+                                "ack_n": len(b["tta"]), "clear_n": len(b["dur"])})
+    return result
+
+
+# ---------------- pareto / heatmap / priority ----------------
+
+
+def pareto(instances, opts=None):
+    counts = {}
+    refs = {}
+    total = 0
+    for inst in instances or []:
+        if inst.get("active_ms") is None:
+            continue
+        total += 1
+        src = inst["source"]
+        counts[src] = counts.get(src, 0) + 1
+        if src not in refs:
+            refs[src] = inst
+    ordered = sorted(counts.items(), key=lambda kv: (-kv[1], refs[kv[0]]["label"]))[:10]
+    rows = []
+    cum = 0
+    for i, (src, c) in enumerate(ordered):
+        cum += c
+        ref = refs[src]
+        rows.append({"rank": i + 1, "source": src, "label": ref["label"],
+                     "area": ref["area"], "priority_name": ref["priority_name"],
+                     "count": c, "pct": 100.0 * c / total if total else 0.0,
+                     "cum_pct": 100.0 * cum / total if total else 0.0})
+    return {"total_activations": total, "rows": rows}
+
+
+def top_sources(pareto_result, n=5):
+    return list((pareto_result or {}).get("rows") or [])[:n]
+
+
+def heatmap(instances, opts=None):
+    import time as _time
+    rows = [[0] * 24 for _ in range(7)]
+    total = 0
+    mx = 0
+    for inst in instances or []:
+        a = inst.get("active_ms")
+        if a is None:
+            continue
+        lt = _time.localtime(a / 1000.0)
+        rows[lt.tm_wday][lt.tm_hour] += 1
+        total += 1
+        if rows[lt.tm_wday][lt.tm_hour] > mx:
+            mx = rows[lt.tm_wday][lt.tm_hour]
+    return {"rows": rows, "row_labels": ["Mon", "Tue", "Wed", "Thu", "Fri", "Sat", "Sun"],
+            "max_count": mx, "total": total}
+
+
+def priority_distribution(instances, opts=None):
+    o = opts_merged(opts)
+    raw_counts = {}
+    buckets = {"low": 0, "medium": 0, "high": 0, "other": 0}
+    for inst in instances or []:
+        lvl = inst.get("priority", -1)
+        name = inst.get("priority_name", "Unknown")
+        key = (lvl, name)
+        raw_counts[key] = raw_counts.get(key, 0) + 1
+        if lvl in (0, 1):
+            buckets["low"] += 1
+        elif lvl == 2:
+            buckets["medium"] += 1
+        elif lvl in (3, 4):
+            buckets["high"] += 1
+        else:
+            buckets["other"] += 1
+    raw = [{"name": k[1], "level": k[0], "count": raw_counts[k]}
+           for k in sorted(raw_counts.keys())]
+    bucketed = buckets["low"] + buckets["medium"] + buckets["high"]
+    pct = {"low": 0.0, "medium": 0.0, "high": 0.0}
+    sum_abs_dev = None
+    target = o["priority_target"]
+    if bucketed:
+        for k in pct:
+            pct[k] = 100.0 * buckets[k] / bucketed
+        sum_abs_dev = (abs(pct["low"] - target["low"]) +
+                       abs(pct["medium"] - target["medium"]) +
+                       abs(pct["high"] - target["high"]))
+    return {"raw": raw, "buckets": buckets, "pct": pct,
+            "target": dict(target), "sum_abs_dev": sum_abs_dev}
+
+
+# ---------------- health / deltas ----------------
+
+
+def _piecewise(x, points):
+    if x is None:
+        return None
+    pts = sorted(points)
+    if x <= pts[0][0]:
+        return float(pts[0][1])
+    if x >= pts[-1][0]:
+        return float(pts[-1][1])
+    for i in range(len(pts) - 1):
+        x0, y0 = pts[i]
+        x1, y1 = pts[i + 1]
+        if x0 <= x <= x1:
+            if x1 == x0:
+                return float(y1)
+            return y0 + (y1 - y0) * (x - x0) / float(x1 - x0)
+    return float(pts[-1][1])
+
+
+def health_score(rate_per_hr, pct_flood, chatter_count, standing_count,
+                 sum_abs_dev, has_activity, opts=None):
+    o = opts_merged(opts)
+    if not has_activity:
+        rate_s, flood_s, chatter_s = 100.0, 100.0, 100.0
+    else:
+        rate_s = _piecewise(rate_per_hr, [(6, 100), (12, 60), (60, 0)])
+        flood_s = _piecewise(pct_flood, [(0, 100), (1, 80), (5, 0)])
+        chatter_s = clamp(100.0 - 25.0 * chatter_count, 0, 100) if chatter_count is not None else None
+    standing_s = clamp(100.0 - 20.0 * standing_count, 0, 100) if standing_count is not None else None
+    priority_s = clamp(100.0 - sum_abs_dev, 0, 100) if sum_abs_dev is not None else None
+    weights = o["health_weights"]
+    subs = [
+        {"key": "rate", "label": "Alarm Rate", "score": rate_s, "weight": weights["rate"],
+         "detail": ("%.1f alarms/hr vs %.0f/hr ISA target" % (rate_per_hr, o["target_per_hr"]))
+         if rate_per_hr is not None else "no data"},
+        {"key": "flood", "label": "Time in Flood", "score": flood_s, "weight": weights["flood"],
+         "detail": ("%.1f%% of window in flood (target <1%%)" % pct_flood)
+         if pct_flood is not None else "no data"},
+        {"key": "chatter", "label": "Chattering Alarms", "score": chatter_s, "weight": weights["chatter"],
+         "detail": ("%d chattering alarm(s) (target 0)" % chatter_count)
+         if chatter_count is not None else "no data"},
+        {"key": "standing", "label": "Standing Alarms", "score": standing_s, "weight": weights["standing"],
+         "detail": ("%d standing alarm(s) >24h (target 0)" % standing_count)
+         if standing_count is not None else "no data"},
+        {"key": "priority", "label": "Priority Distribution", "score": priority_s, "weight": weights["priority"],
+         "detail": ("%.0f pts deviation from ISA 80/15/5" % sum_abs_dev)
+         if sum_abs_dev is not None else "no data"},
+    ]
+    num = 0.0
+    den = 0.0
+    for s in subs:
+        if s["score"] is not None:
+            num += s["score"] * s["weight"]
+            den += s["weight"]
+    score = (num / den) if den else None
+    grade = None
+    if score is not None:
+        for cut, g in o["grade_cuts"]:
+            if score >= cut:
+                grade = g
+                break
+        if grade is None:
+            grade = "F"
+    return {"grade": grade, "score": score, "subs": subs}
+
+
+def delta(current, prior, higher_is_worse=True, flat_pct=5.0):
+    d = {"value": current, "prior": prior, "delta_pct": None, "dir": "none", "good": None}
+    cur0 = current or 0
+    pri0 = prior or 0
+    if prior is None:
+        d["dir"] = "new" if cur0 > 0 else "none"
+        return d
+    if pri0 == 0:
+        d["dir"] = "new" if cur0 > 0 else "none"
+        return d
+    if current is None:
+        return d
+    dp = 100.0 * (current - prior) / float(prior)
+    d["delta_pct"] = dp
+    if abs(dp) < flat_pct:
+        d["dir"] = "flat"
+        return d
+    d["dir"] = "up" if dp > 0 else "down"
+    d["good"] = (d["dir"] == "down") == bool(higher_is_worse)
+    return d
+
+
+# ---------------- the bundle ----------------
+
+
+def build_bundle(rows, active_now, shelved_count, start_ms, end_ms, now_ms, opts=None):
+    o = opts_merged(opts)
+    try:
+        start_ms = int(start_ms or 0)
+        end_ms = int(end_ms or 0)
+        now_ms = int(now_ms or 0)
+    except Exception:
+        start_ms, end_ms, now_ms = 0, 0, 0
+    filters = (opts or {}).get("filters") if opts else None
+    instances, mode = correlate_instances(rows)
+    instances = apply_filters(instances, filters)
+    current, prior, orphans = partition_instances(instances, start_ms, end_ms)
+    window_h = _safe_div(end_ms - start_ms, 3600000.0) or 0.0
+
+    bins = rate_bins(current, start_ms, end_ms, o)
+    floods = flood_episodes(bins, current, start_ms, end_ms, o)
+    chat = chattering(current, start_ms, end_ms, o)
+    fleet = fleeting(current, o)
+    open_current = [i for i in current if i["open"]]
+    stand = standing(active_now, open_current, now_ms, o)
+    mm = mtta_mttr(current, start_ms, end_ms, o)
+    par = pareto(current, o)
+    prio = priority_distribution(current, o)
+    heat = heatmap(current, o)
+
+    # prior mirrors (cheap subset for deltas)
+    p_start = start_ms - (end_ms - start_ms)
+    p_bins = rate_bins(prior, p_start, start_ms, o)
+    p_floods = flood_episodes(p_bins, prior, p_start, start_ms, o)
+    p_chat = chattering(prior, p_start, start_ms, o)
+    p_fleet = fleeting(prior, o)
+    p_mm = mtta_mttr(prior, p_start, start_ms, o)
+
+    n_act = len(current)
+    p_act = len(prior)
+    rate = _safe_div(n_act, window_h)
+    p_rate = _safe_div(p_act, window_h)
+    unacked_now = len([s for s in active_now or [] if s.get("unacked")])
+    flat = o["delta_flat_pct"]
+
+    kpis = {
+        "activations": delta(n_act, p_act, True, flat),
+        "rate_per_hr": delta(rate, p_rate, True, flat),
+        "active_now": delta(len(active_now or []), None, True, flat),
+        "unacked_now": delta(unacked_now, None, True, flat),
+        "shelved_now": delta(shelved_count, None, True, flat),
+        "mtta_ms": delta(mm["mtta"]["median_ms"], p_mm["mtta"]["median_ms"], True, flat),
+        "mttr_ms": delta(mm["mttr"]["median_ms"], p_mm["mttr"]["median_ms"], True, flat),
+        "flood_pct": delta(floods["pct_time_in_flood"], p_floods["pct_time_in_flood"], True, flat),
+        "flood_count": delta(len(floods["episodes"]), len(p_floods["episodes"]), True, flat),
+        "chatter_count": delta(len(chat), len(p_chat), True, flat),
+        "standing_count": delta(stand["count"], None, True, flat),
+        "fleeting_count": delta(fleet["total"], p_fleet["total"], True, flat),
+    }
+
+    has_activity = n_act > 0
+    health = health_score(rate if has_activity else None,
+                          floods["pct_time_in_flood"] if has_activity else None,
+                          len(chat), stand["count"] if (active_now or open_current) or has_activity else None,
+                          prio["sum_abs_dev"], has_activity, o)
+    if not has_activity and not (active_now or []):
+        health = {"grade": None, "score": None, "subs": health["subs"]}
+
+    areas = sorted(set([i["area"] for i in current] +
+                       [r["area"] for r in stand["rows"]]))
+    prios_seen = sorted(set([(i["priority"], i["priority_name"]) for i in current]))
+    active_now_rows = []
+    for s in (active_now or [])[:int(o["active_now_cap"])]:
+        parsed = parse_source(s.get("source"), s.get("display_path"))
+        a = s.get("active_ms")
+        active_now_rows.append({"source": s.get("source") or "", "label": parsed["label"],
+                                "area": parsed["area"],
+                                "priority_name": s.get("priority_name", "Unknown"),
+                                "active_ms": a,
+                                "age_ms": (now_ms - a) if a is not None else None,
+                                "unacked": bool(s.get("unacked"))})
+
+    return {
+        "meta": {"start_ms": start_ms, "end_ms": end_ms, "prior_start_ms": p_start,
+                 "now_ms": now_ms, "window_hours": window_h,
+                 "event_count": len(rows or []), "activation_count": n_act,
+                 "dropped_rows": 0, "truncated": False,
+                 "correlation_mode": mode, "standing_mode": stand["mode"],
+                 "areas": areas,
+                 "priorities_seen": [{"value": p[0], "label": p[1]} for p in prios_seen],
+                 "source_count": len(set(i["source"] for i in current)),
+                 "error": None, "opts": {
+                     "bin_ms": bins["bin_ms"], "target_per_hr": o["target_per_hr"],
+                     "flood_per_10min": o["flood_per_10min"],
+                     "chatter_per_hr": o["chatter_per_hr"],
+                     "fleeting_s": o["fleeting_s"], "standing_hours": o["standing_hours"]}},
+        "kpis": kpis,
+        "health": health,
+        "insights": [],
+        "rate": bins,
+        "floods": floods,
+        "priority": prio,
+        "heatmap": heat,
+        "mtta_mttr": mm,
+        "pareto": par,
+        "top_sources": top_sources(par, 5),
+        "chattering": chat,
+        "fleeting": fleet,
+        "standing": stand,
+        "active_now": active_now_rows,
+    }

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/calc/resource.json

@@ -0,0 +1,12 @@
+{
+  "scope": "A",
+  "version": 1,
+  "restricted": false,
+  "overridable": true,
+  "files": [
+    "code.py"
+  ],
+  "attributes": {
+    "hintScope": 2
+  }
+}

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/fmt/code.py

@@ -0,0 +1,325 @@
+# PrimeControls.fmt - PURE formatting, insights, shift report (py2/3, no f-strings).
+from __future__ import division, print_function
+
+import time as _time
+
+from PrimeControls import calc
+
+ARROW_UP = u"▲"
+ARROW_DOWN = u"▼"
+ARROW_FLAT = u"—"
+
+
+def dur(ms):
+    if ms is None:
+        return "--"
+    try:
+        s = int(round(ms / 1000.0))
+    except Exception:
+        return "--"
+    if s < 60:
+        return "%ds" % s
+    m = s // 60
+    if m < 60:
+        return "%dm %ds" % (m, s % 60) if s % 60 else "%dm" % m
+    h = m // 60
+    if h < 24:
+        return "%dh %dm" % (h, m % 60) if m % 60 else "%dh" % h
+    d = h // 24
+    return "%dd %dh" % (d, h % 24) if h % 24 else "%dd" % d
+
+
+def num(v, dec=0):
+    if v is None:
+        return "--"
+    try:
+        if dec:
+            s = ("%%.%df" % dec) % v
+            whole, frac = s.split(".")
+            return _group(whole) + "." + frac
+        return _group("%d" % round(v))
+    except Exception:
+        return str(v)
+
+
+def _group(digits):
+    neg = digits.startswith("-")
+    if neg:
+        digits = digits[1:]
+    out = ""
+    while len(digits) > 3:
+        out = "," + digits[-3:] + out
+        digits = digits[:-3]
+    return ("-" if neg else "") + digits + out
+
+
+def pct(v, dec=0, signed=False):
+    if v is None:
+        return "--"
+    try:
+        fmtstr = "%%+.%df%%%%" % dec if signed else "%%.%df%%%%" % dec
+        return fmtstr % v
+    except Exception:
+        return str(v)
+
+
+def clock(ms):
+    if ms is None:
+        return "--"
+    try:
+        return _time.strftime("%I:%M %p", _time.localtime(ms / 1000.0)).lstrip("0")
+    except Exception:
+        return "--"
+
+
+def day_clock(ms):
+    if ms is None:
+        return "--"
+    try:
+        return _time.strftime("%a ", _time.localtime(ms / 1000.0)) + clock(ms)
+    except Exception:
+        return "--"
+
+
+def delta_chip(d):
+    if not d:
+        return {"arrow": ARROW_FLAT, "text": "--", "good": None}
+    direction = d.get("dir")
+    if direction == "up":
+        arrow = ARROW_UP
+    elif direction == "down":
+        arrow = ARROW_DOWN
+    else:
+        arrow = ARROW_FLAT
+    if direction == "new":
+        text = "new"
+    elif direction == "none":
+        text = "--"
+    elif d.get("delta_pct") is not None:
+        text = pct(d["delta_pct"], 0, True)
+    else:
+        text = "--"
+    return {"arrow": arrow, "text": text, "good": d.get("good")}
+
+
+def grade_color_key(grade):
+    return grade if grade in ("A", "B", "C", "D", "F") else "NA"
+
+
+# ---------------- insights ----------------
+
+
+def insights(bundle, opts=None):
+    o = calc.opts_merged(opts)
+    if not bundle:
+        return []
+    out = []
+    for rule in (_i_rate, _i_floods, _i_chatter, _i_standing,
+                 _i_priority, _i_pareto, _i_fleeting):
+        try:
+            r = rule(bundle)
+            if r:
+                out.append(r)
+        except Exception:
+            pass
+    out.sort(key=lambda i: (i["severity"], -i.get("magnitude", 0)))
+    out = out[:int(o["insights_max"])]
+    if not out:
+        k = bundle.get("kpis", {}).get("rate_per_hr", {})
+        rate = k.get("value")
+        if bundle.get("meta", {}).get("activation_count", 0) == 0:
+            text = "No alarm events in the selected range."
+        else:
+            text = ("No significant changes vs the prior period; rate %.1f/hr is within "
+                    "the ISA target of %.0f/hr." % (rate or 0.0,
+                                                    bundle["meta"]["opts"]["target_per_hr"]))
+        out = [{"severity": 3, "icon": "check_circle", "text": text,
+                "tab": "overview", "magnitude": 0}]
+    for i in out:
+        i.pop("magnitude", None)
+    return out
+
+
+def _i_rate(b):
+    k = b["kpis"]["activations"]
+    dp = k.get("delta_pct")
+    cur = k.get("value") or 0
+    if dp is None or cur < 10:
+        return None
+    if dp >= 25:
+        sev = 0 if dp >= 100 else 1
+        text = ("Alarm rate up %d%% vs prior period (%s -> %s activations)"
+                % (round(dp), num(k.get("prior")), num(cur)))
+        attr = _rate_attribution(b)
+        if attr:
+            text += " - largest increase from %s" % attr
+        return {"severity": sev, "icon": "trending_up", "text": text + ".",
+                "tab": "badactors", "magnitude": dp}
+    if dp <= -25:
+        return {"severity": 3, "icon": "trending_down",
+                "text": "Alarm rate down %d%% vs prior period - improving." % round(-dp),
+                "tab": "overview", "magnitude": -dp}
+    return None
+
+
+def _rate_attribution(b):
+    rows = b.get("pareto", {}).get("rows") or []
+    if rows:
+        return rows[0]["label"]
+    return None
+
+
+def _i_floods(b):
+    eps = b.get("floods", {}).get("episodes") or []
+    if not eps:
+        return None
+    worst = sorted(eps, key=lambda e: -e["event_count"])[0]
+    total_min = sum(e["duration_ms"] for e in eps) / 60000.0
+    text = ("%d flood episode(s) totaling %s; worst %s-%s (%d events, mostly %s)."
+            % (len(eps), dur(total_min * 60000), day_clock(worst["start_ms"]),
+               clock(worst["end_ms"]), worst["event_count"],
+               worst["top_source_label"] or worst["top_area"] or "n/a"))
+    return {"severity": 0, "icon": "flood", "text": text, "tab": "analysis",
+            "magnitude": len(eps)}
+
+
+def _i_chatter(b):
+    rows = b.get("chattering") or []
+    if not rows:
+        return None
+    top = rows[0]
+    if len(rows) == 1:
+        text = ("%s is chattering (%.0f re-triggers/hr, median gap %.0fs)."
+                % (top["label"], top["per_hour"], top["median_gap_s"]))
+    else:
+        text = ("%d alarms are chattering (>%.0f re-triggers/hr); worst is %s at %.0f/hr."
+                % (len(rows), b["meta"]["opts"]["chatter_per_hr"], top["label"],
+                   top["per_hour"]))
+    return {"severity": 1, "icon": "repeat", "text": text, "tab": "badactors",
+            "magnitude": len(rows)}
+
+
+def _i_standing(b):
+    st = b.get("standing") or {}
+    if not st.get("count"):
+        return None
+    rows = st.get("rows") or []
+    oldest = rows[0] if rows else None
+    text = "%d alarm(s) standing >%dh" % (st["count"], b["meta"]["opts"]["standing_hours"])
+    if oldest and oldest.get("age_h"):
+        text += "; oldest is %s at %.1f days" % (oldest["label"], oldest["age_h"] / 24.0)
+    return {"severity": 1, "icon": "schedule", "text": text + ".", "tab": "badactors",
+            "magnitude": st["count"]}
+
+
+def _i_priority(b):
+    p = b.get("priority") or {}
+    if p.get("sum_abs_dev") is None:
+        return None
+    high = p["pct"]["high"]
+    target = p["target"]["high"]
+    if high - target >= 10:
+        return {"severity": 2, "icon": "priority_high",
+                "text": ("High/Critical alarms are %d%% of events vs %d%% ISA target - "
+                         "priorities may be over-assigned." % (round(high), round(target))),
+                "tab": "analysis", "magnitude": high - target}
+    return None
+
+
+def _i_pareto(b):
+    rows = b.get("pareto", {}).get("rows") or []
+    for k, row in enumerate(rows[:3]):
+        if row["cum_pct"] >= 50:
+            n = k + 1
+            return {"severity": 2, "icon": "insights",
+                    "text": ("%d source(s) account for %d%% of all activations - start "
+                             "with %s." % (n, round(row["cum_pct"]), rows[0]["label"])),
+                    "tab": "badactors", "magnitude": row["cum_pct"]}
+    return None
+
+
+def _i_fleeting(b):
+    fl = b.get("fleeting") or {}
+    if (fl.get("total") or 0) < 10:
+        return None
+    return {"severity": 2, "icon": "bolt",
+            "text": ("%d fleeting alarms (<%ds active) in range - likely deadband or "
+                     "nuisance issues." % (fl["total"], b["meta"]["opts"]["fleeting_s"])),
+            "tab": "badactors", "magnitude": fl["total"]}
+
+
+# ---------------- shift report ----------------
+
+
+def shift_bounds(now_ms, shift_hours=8, anchor_hour=0):
+    lt = _time.localtime(now_ms / 1000.0)
+    midnight = _time.mktime((lt.tm_year, lt.tm_mon, lt.tm_mday, 0, 0, 0,
+                             lt.tm_wday, lt.tm_yday, -1))
+    anchor = midnight + anchor_hour * 3600
+    now_s = now_ms / 1000.0
+    if now_s < anchor:
+        anchor -= 86400
+    shift_s = shift_hours * 3600
+    k = int((now_s - anchor) // shift_s)
+    cur_start = anchor + k * shift_s
+    cur = (int(cur_start * 1000), int((cur_start + shift_s) * 1000))
+    prev = (int((cur_start - shift_s) * 1000), int(cur_start * 1000))
+    label = "%s - %s" % (day_clock(prev[0]), day_clock(prev[1]))
+    return {"current": cur, "previous": prev, "label": label}
+
+
+def _kpi_line(name, k, formatter):
+    chip = delta_chip(k)
+    val = formatter(k.get("value"))
+    extra = "" if chip["text"] == "--" else " (%s %s)" % (chip["arrow"], chip["text"])
+    return "%-14s %s%s" % (name + ":", val, extra)
+
+
+def shift_report(bundle, label):
+    if not bundle:
+        return {"text": "No data.", "sections": []}
+    k = bundle["kpis"]
+    h = bundle["health"]
+    subs = " | ".join("%s %s" % (s["key"], "%d" % s["score"] if s["score"] is not None else "n/a")
+                      for s in h.get("subs", []))
+    sections = []
+    head = ["Shift: %s" % label,
+            "Generated: %s" % day_clock(bundle["meta"]["now_ms"]),
+            "Health: %s (%s)   [%s]" % (h.get("grade") or "N/A",
+                                        "%d" % h["score"] if h.get("score") is not None else "-",
+                                        subs)]
+    sections.append({"heading": "PRIME CONTROLS - ALARM SHIFT REPORT", "lines": head})
+    kpis = [
+        _kpi_line("Activations", k["activations"], num),
+        _kpi_line("Rate/hr", k["rate_per_hr"], lambda v: num(v, 1)),
+        _kpi_line("MTTA", k["mtta_ms"], dur),
+        _kpi_line("MTTR", k["mttr_ms"], dur),
+        _kpi_line("Flood time", k["flood_pct"], lambda v: pct(v, 1)),
+        _kpi_line("Chattering", k["chatter_count"], num),
+        _kpi_line("Standing", k["standing_count"], num),
+        _kpi_line("Fleeting", k["fleeting_count"], num),
+    ]
+    sections.append({"heading": "KPIs (vs prior shift)", "lines": kpis})
+    actors = ["#%d %-40s %6s  %s" % (r["rank"], r["label"][:40], num(r["count"]),
+                                     pct(r["cum_pct"]))
+              for r in bundle["pareto"]["rows"][:5]] or ["none"]
+    sections.append({"heading": "Top actors (count, cumulative %)", "lines": actors})
+    floods = ["%s - %s  %s, %d events, top: %s"
+              % (day_clock(e["start_ms"]), clock(e["end_ms"]), dur(e["duration_ms"]),
+                 e["event_count"], e["top_source_label"] or e["top_area"])
+              for e in bundle["floods"]["episodes"]] or ["none"]
+    sections.append({"heading": "Flood episodes", "lines": floods})
+    standing_rows = bundle["standing"]["rows"][:8]
+    stand = ["%-40s active %s%s" % (r["label"][:40], dur(r["age_ms"]),
+                                    " (UNACKED)" if r["unacked"] else "")
+             for r in standing_rows] or ["none"]
+    sections.append({"heading": "Standing / handover attention", "lines": stand})
+    sections.append({"heading": "Insights",
+                     "lines": [i["text"] for i in bundle.get("insights") or []] or ["none"]})
+    text_parts = []
+    for s in sections:
+        text_parts.append(s["heading"])
+        text_parts.append("-" * len(s["heading"]))
+        text_parts.extend(s["lines"])
+        text_parts.append("")
+    return {"text": "\n".join(text_parts), "sections": sections}

ignition/gateway/projects/PrimeBAT/ignition/script-python/PrimeControls/fmt/resource.json

@@ -0,0 +1,12 @@
+{
+  "scope": "A",
+  "version": 1,
+  "restricted": false,
+  "overridable": true,
+  "files": [
+    "code.py"
+  ],
+  "attributes": {
+    "hintScope": 2
+  }
+}

ignition/gateway/projects/SimHarness/ignition/script-python/probe/code.py

@@ -11,7 +11,60 @@
 import json
 
 OUT_DIR = "/usr/local/bin/ignition/data/projects/.probe"
-PROBE_NAME = "P0"
+PROBE_NAME = "P1"
+
+
+def _p1():
+    """Exec PrimeBAT's real PrimeControls modules (calc/fmt/alarms) in this scope
+    and run getDashboardBundle against the live journal - end-to-end data-layer
+    smoke with zero dev footprint inside PrimeBAT."""
+    import imp
+    base = "/usr/local/bin/ignition/data/projects/PrimeBAT/ignition/script-python/PrimeControls/"
+    pkg = imp.new_module("PrimeControls")
+    pkg.__path__ = [base]
+    sys_modules = __import__("sys").modules
+    sys_modules["PrimeControls"] = pkg
+    for name in ("calc", "fmt", "alarms"):
+        m = imp.new_module("PrimeControls." + name)
+        m.__dict__["system"] = system
+        code = open(base + name + "/code.py").read()
+        compiled = compile(code, name, "exec")
+        # py2 qualified-exec statement form: required because _p1 contains
+        # closures, which forbid the unqualified exec(...) call form in Jython.
+        exec compiled in m.__dict__
+        sys_modules["PrimeControls." + name] = m
+        setattr(pkg, name, m)
+    al = pkg.alarms
+    end = system.date.toMillis(system.date.now())
+    start = end - 4 * 3600 * 1000
+    b = al.getDashboardBundle(start, end, None)
+    page = al.getJournalPage(start, end, None, 0, 5)
+    shift = al.getShiftReportText()
+    return {
+        "meta": {"event_count": b["meta"]["event_count"],
+                 "activation_count": b["meta"]["activation_count"],
+                 "areas": b["meta"]["areas"],
+                 "correlation_mode": b["meta"]["correlation_mode"],
+                 "standing_mode": b["meta"]["standing_mode"],
+                 "error": b["meta"]["error"],
+                 "dropped": b["meta"]["dropped_rows"]},
+        "health": {"grade": b["health"]["grade"], "score": b["health"]["score"],
+                   "subs": [(s["key"], s["score"]) for s in b["health"]["subs"]]},
+        "kpis": dict((k, b["kpis"][k]["value"]) for k in b["kpis"]),
+        "counts": {"chattering": len(b["chattering"]),
+                   "standing": b["standing"]["count"],
+                   "fleeting": b["fleeting"]["total"],
+                   "floods": len(b["floods"]["episodes"]),
+                   "pareto_rows": len(b["pareto"]["rows"]),
+                   "bins": len(b["rate"]["bins"]),
+                   "active_now": len(b["active_now"])},
+        "insights": [i["text"] for i in b["insights"]],
+        "journal_page": {"total": page["total"], "rows": len(page["rows"]),
+                         "error": page["error"],
+                         "first": page["rows"][0] if page["rows"] else None},
+        "shift_label": shift["label"],
+        "shift_text_head": shift["text"][:400],
+    }
 
 
 def _safe(fn):
@@ -174,6 +227,6 @@ def _p0():
 def run():
     result = {"probe": PROBE_NAME,
               "ranAt": str(system.date.now())}
-    result["payload"] = _safe(_p0)
+    result["payload"] = _safe(_p1)
     _write(result)
     system.util.getLogger("probe").info("probe %s written to %s" % (PROBE_NAME, OUT_DIR))

tests/conftest.py

@@ -0,0 +1,21 @@
+"""Register PrimeControls.{calc,fmt} from the Ignition project's code.py files so
+pytest imports them exactly as the gateway does (single source of truth)."""
+import importlib.util
+import os
+import sys
+import types
+
+ROOT = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+SP = os.path.join(ROOT, "ignition", "gateway", "projects", "PrimeBAT",
+                  "ignition", "script-python", "PrimeControls")
+
+pkg = types.ModuleType("PrimeControls")
+pkg.__path__ = [SP]
+sys.modules["PrimeControls"] = pkg
+for mod in ("calc", "fmt"):
+    spec = importlib.util.spec_from_file_location(
+        "PrimeControls." + mod, os.path.join(SP, mod, "code.py"))
+    m = importlib.util.module_from_spec(spec)
+    sys.modules["PrimeControls." + mod] = m
+    spec.loader.exec_module(m)
+    setattr(pkg, mod, m)

tests/test_calc.py

@@ -0,0 +1,306 @@
+import os
+import time
+
+import pytest
+
+from PrimeControls import calc
+
+H = 3600000
+M = 60000
+T0 = 1784200000000  # fixed epoch anchor
+
+
+def row(state, ts, src="prov:default:/tag:Sim/AreaA/T1:/alm:Alm1", eid=None,
+        prio=3, dp="", system=False, ack_user=None):
+    lvl, name = calc.normalize_priority(prio)
+    return {"event_id": eid, "source": src, "display_path": dp,
+            "priority": lvl, "priority_name": name, "state": state, "ts": ts,
+            "is_system": system, "ack_user": ack_user}
+
+
+def lifecycle(eid, src, t_active, dur_ms=None, ack_ms=None, prio=3):
+    rows = [row("active", t_active, src, eid, prio)]
+    if ack_ms is not None:
+        rows.append(row("ack", t_active + ack_ms, src, eid, prio, ack_user="op1"))
+    if dur_ms is not None:
+        rows.append(row("clear", t_active + dur_ms, src, eid, prio))
+    return rows
+
+
+# ---------------- parse_source / normalize_priority ----------------
+
+def test_parse_source_from_source_path():
+    p = calc.parse_source("prov:default:/tag:Plant/TankFarm/T101_Hi:/alm:T101_Hi", "")
+    assert p["area"] == "TankFarm"
+    assert p["label"] == "TankFarm/T101_Hi"
+
+
+def test_parse_source_display_path_wins_label_but_area_from_tag():
+    p = calc.parse_source("prov:default:/tag:Plant/Boiler/DrumLo:/alm:DrumLo", "North/Drum Level")
+    assert p["label"] == "North/Drum Level"
+    assert p["area"] == "Boiler"
+
+
+def test_parse_source_system_row():
+    p = calc.parse_source("evt:System Startup", "")
+    assert p["label"] == "evt:System Startup"
+
+
+def test_normalize_priority():
+    assert calc.normalize_priority(3) == (3, "High")
+    assert calc.normalize_priority("Critical") == (4, "Critical")
+    assert calc.normalize_priority("AlarmPriority.Low") == (1, "Low")
+    lvl, _ = calc.normalize_priority("weird")
+    assert lvl == -1
+
+
+# ---------------- correlation ----------------
+
+def test_correlate_full_lifecycle_uuid():
+    rows = lifecycle("e1", "s1", T0, dur_ms=5 * M, ack_ms=2 * M)
+    insts, mode = calc.correlate_instances(rows)
+    assert mode == "uuid"
+    assert len(insts) == 1
+    i = insts[0]
+    assert i["active_ms"] == T0 and i["duration_ms"] == 5 * M and i["tta_ms"] == 2 * M
+    assert not i["open"] and i["ack_user"] == "op1"
+
+
+def test_correlate_ack_after_clear():
+    rows = [row("active", T0, eid="e1"), row("clear", T0 + M, eid="e1"),
+            row("ack", T0 + 2 * M, eid="e1")]
+    i = calc.correlate_instances(rows)[0][0]
+    assert i["duration_ms"] == M and i["tta_ms"] == 2 * M
+
+
+def test_correlate_straddler_and_open():
+    rows = [row("clear", T0, eid="old"), row("active", T0 + M, eid="new")]
+    insts, _ = calc.correlate_instances(rows)
+    by_id = dict((i["event_id"], i) for i in insts)
+    assert by_id["old"]["active_ms"] is None and by_id["old"]["duration_ms"] is None
+    assert by_id["new"]["open"] and by_id["new"]["clear_ms"] is None
+
+
+def test_correlate_negative_skew_none():
+    rows = [row("active", T0, eid="e1"), row("ack", T0 - M, eid="e1")]
+    i = calc.correlate_instances(rows)[0][0]
+    assert i["tta_ms"] is None
+
+
+def test_correlate_system_dropped_and_empty():
+    assert calc.correlate_instances([row("active", T0, system=True)])[0] == []
+    assert calc.correlate_instances([])[0] == []
+
+
+def test_correlate_source_sequence_fallback():
+    rows = [row("active", T0, src="sA"), row("clear", T0 + M, src="sA"),
+            row("active", T0 + 2 * M, src="sA"), row("active", T0 + 3 * M, src="sB")]
+    insts, mode = calc.correlate_instances(rows)
+    assert mode == "source-sequence"
+    assert len(insts) == 3
+    closed = [i for i in insts if i["source"] == "sA" and not i["open"]]
+    assert len(closed) == 1 and closed[0]["duration_ms"] == M
+
+
+def test_partition_boundary():
+    insts = [dict(active_ms=T0, source="a"), dict(active_ms=T0 - 1, source="b"),
+             dict(active_ms=None, source="c")]
+    cur, prior, orphans = calc.partition_instances(insts, T0, T0 + H)
+    assert len(cur) == 1 and len(prior) == 1 and len(orphans) == 1
+
+
+# ---------------- bins / floods ----------------
+
+def make_insts(times, src="s1", prio=3):
+    out = []
+    for i, t in enumerate(times):
+        rows = lifecycle("e%d_%s" % (i, src), src, t, dur_ms=30000, prio=prio)
+        out.extend(rows)
+    insts, _ = calc.correlate_instances(out)
+    return insts
+
+
+def test_rate_bins_placement_and_edges():
+    start = (T0 // 600000) * 600000
+    insts = make_insts([start, start + 600000 - 1, start + 600000])
+    r = calc.rate_bins(insts, start, start + 2 * 600000)
+    assert r["bins"][0]["count"] == 2 and r["bins"][1]["count"] == 1
+
+
+def test_rate_bins_empty_and_reversed():
+    assert calc.rate_bins([], T0, T0)["bins"] == []
+    assert calc.rate_bins([], T0 + 1, T0)["bins"] == []
+
+
+def test_flood_hysteresis_merge_and_split():
+    start = (T0 // 600000) * 600000
+    times = []
+    times += [start + i for i in range(12)]                      # bin0: 12 (flood)
+    times += [start + 600000 + i for i in range(7)]              # bin1: 7 (>=5 continues)
+    times += [start + 2 * 600000 + i for i in range(12)]         # bin2: 12
+    insts = make_insts(times)
+    r = calc.rate_bins(insts, start, start + 3 * 600000)
+    f = calc.flood_episodes(r, insts, start, start + 3 * 600000)
+    assert len(f["episodes"]) == 1
+    times2 = [start + i for i in range(12)] + [start + 2 * 600000 + i for i in range(12)]
+    insts2 = make_insts(times2)
+    r2 = calc.rate_bins(insts2, start, start + 3 * 600000)
+    f2 = calc.flood_episodes(r2, insts2, start, start + 3 * 600000)
+    assert len(f2["episodes"]) == 2
+    assert f2["episodes"][0]["event_count"] == 12
+    assert f2["pct_time_in_flood"] > 0
+
+
+# ---------------- detections ----------------
+
+def test_chattering_detects_sim_shape_not_slow():
+    start = T0
+    end = T0 + 2 * H
+    chatter_times = [start + i * 45000 for i in range(160)]       # every 45s
+    slow_times = [start + i * 5 * M for i in range(24)]           # every 5min -> 12/hr slow
+    insts = make_insts(chatter_times, src="chat") + make_insts(slow_times, src="slow")
+    out = calc.chattering(insts, start, end)
+    srcs = [r["source"] for r in out]
+    assert "chat" in srcs and "slow" not in srcs
+
+
+def test_fleeting_and_standing():
+    rows = []
+    for i in range(4):
+        rows += lifecycle("f%d" % i, "fleety", T0 + i * M, dur_ms=3000)
+    rows += lifecycle("n1", "normal", T0, dur_ms=5 * M)
+    insts, _ = calc.correlate_instances(rows)
+    fl = calc.fleeting(insts)
+    assert fl["total"] == 4 and fl["sources"][0]["source"] == "fleety"
+    now = T0 + 30 * H
+    status = [{"source": "prov:default:/tag:A/B/C:/alm:C", "display_path": "",
+               "priority": 3, "priority_name": "High",
+               "active_ms": T0, "unacked": True}]
+    st = calc.standing(status, [], now)
+    assert st["mode"] == "status" and st["count"] == 1
+    st2 = calc.standing([], [i for i in insts if i["open"]], now)
+    assert st2["mode"] == "journal"
+
+
+def test_mtta_mttr_exclusions_and_median():
+    rows = (lifecycle("a", "s", T0, dur_ms=2 * M, ack_ms=M) +
+            lifecycle("b", "s", T0 + M, dur_ms=4 * M, ack_ms=3 * M) +
+            lifecycle("c", "s", T0 + 2 * M, dur_ms=100 * M) +      # no ack
+            lifecycle("d", "s", T0 + 3 * M))                        # open, no clear
+    insts, _ = calc.correlate_instances(rows)
+    mm = calc.mtta_mttr(insts, T0, T0 + H)
+    assert mm["mtta"]["count"] == 2 and mm["mtta"]["median_ms"] == 2 * M
+    assert mm["mttr"]["count"] == 3 and mm["mttr"]["median_ms"] == 4 * M
+
+
+def test_pareto_cum_pct_vs_total():
+    insts = make_insts([T0 + i * M for i in range(6)], src="hot")
+    insts += make_insts([T0 + i * M for i in range(4)], src="warm")
+    p = calc.pareto(insts)
+    assert p["total_activations"] == 10
+    assert p["rows"][0]["source"] == "hot" and abs(p["rows"][0]["cum_pct"] - 60.0) < 0.01
+    assert abs(p["rows"][1]["cum_pct"] - 100.0) < 0.01
+    assert calc.top_sources(p, 5) == p["rows"][:5]
+
+
+def test_heatmap_placement():
+    os.environ["TZ"] = "UTC"
+    time.tzset()
+    # 2026-07-16 is a Thursday; 10:00 UTC
+    ts = 1784196000000  # Thu Jul 16 2026 10:00:00 UTC
+    insts = make_insts([ts, ts, ts + H])
+    hm = calc.heatmap(insts)
+    assert hm["rows"][3][10] == 2 and hm["rows"][3][11] == 1
+    assert hm["max_count"] == 2 and hm["total"] == 3
+
+
+def test_priority_distribution_extremes():
+    insts = make_insts([T0 + i * M for i in range(8)], src="lo", prio=1)
+    insts += make_insts([T0 + i * M for i in range(2)], src="hi", prio=4)
+    d = calc.priority_distribution(insts)
+    assert d["buckets"]["low"] == 8 and d["buckets"]["high"] == 2
+    assert d["sum_abs_dev"] is not None
+    assert calc.priority_distribution([])["sum_abs_dev"] is None
+
+
+# ---------------- health / delta ----------------
+
+def test_health_anchors_and_grades():
+    h = calc.health_score(6.0, 0.0, 0, 0, 0.0, True)
+    assert h["score"] == 100 and h["grade"] == "A"
+    assert calc.health_score(60.0, None, 0, 0, None, True)["subs"][0]["score"] == 0
+    h2 = calc.health_score(None, 1.0, None, None, None, True)
+    flood_sub = [s for s in h2["subs"] if s["key"] == "flood"][0]
+    assert flood_sub["score"] == 80
+    h3 = calc.health_score(None, None, None, None, None, True)
+    assert h3["score"] is None and h3["grade"] is None
+
+
+def test_health_quiet_plant():
+    h = calc.health_score(None, None, 0, 0, None, False)
+    assert h["score"] is not None and h["grade"] in ("A", "B")
+
+
+def test_delta_semantics():
+    assert calc.delta(10, 0)["dir"] == "new"
+    assert calc.delta(0, None)["dir"] == "none"
+    assert calc.delta(102, 100)["dir"] == "flat"
+    d = calc.delta(200, 100)
+    assert d["dir"] == "up" and d["good"] is False
+    d2 = calc.delta(50, 100, higher_is_worse=True)
+    assert d2["dir"] == "down" and d2["good"] is True
+
+
+# ---------------- bundle ----------------
+
+def synth_rows():
+    rows = []
+    base = T0
+    for i in range(20):  # baseline across areas/priorities
+        src = "prov:default:/tag:Plant/Area%d/Tag%d:/alm:A%d" % (i % 4, i, i)
+        rows += lifecycle("b%d" % i, src, base + i * 8 * M, dur_ms=3 * M,
+                          ack_ms=M, prio=(i % 3) + 1)
+    chat_src = "prov:default:/tag:Plant/Area1/Chatty:/alm:Chatty"
+    for i in range(100):  # every 50s for ~83 min -> ~25/hr over the 4h window
+        rows += lifecycle("c%d" % i, chat_src, base + i * 50000, dur_ms=8000, prio=3)
+    flood_t = base + 3 * H
+    for i in range(18):
+        rows += lifecycle("fl%d" % i, "prov:default:/tag:Plant/Area2/F%d:/alm:F%d" % (i, i),
+                          flood_t + i * 20000, dur_ms=M, prio=2)
+    for i in range(5):
+        rows += lifecycle("fle%d" % i, "prov:default:/tag:Plant/Area3/Blip:/alm:Blip",
+                          base + i * 12 * M, dur_ms=4000, prio=1)
+    return rows
+
+
+def test_build_bundle_golden_and_empty():
+    start, end = T0, T0 + 4 * H
+    status = [{"source": "prov:default:/tag:Plant/Area0/Stand:/alm:Stand",
+               "display_path": "", "priority": 3, "priority_name": "High",
+               "active_ms": T0 - 30 * H, "unacked": True}]
+    b = calc.build_bundle(synth_rows(), status, 0, start, end, end + M)
+    for key in ("meta", "kpis", "health", "rate", "floods", "priority", "heatmap",
+                "mtta_mttr", "pareto", "top_sources", "chattering", "fleeting",
+                "standing", "active_now", "insights"):
+        assert key in b, key
+    assert b["meta"]["activation_count"] > 0
+    assert len(b["floods"]["episodes"]) >= 1
+    assert any(r["source"].endswith("Chatty") for r in b["chattering"])
+    assert b["standing"]["count"] == 1
+    assert b["fleeting"]["total"] >= 5
+    assert b["health"]["grade"] is not None
+    assert b["kpis"]["activations"]["value"] > 0
+    assert len(b["meta"]["areas"]) >= 4
+    empty = calc.build_bundle([], [], None, start, end, end)
+    assert empty["meta"]["activation_count"] == 0
+    assert empty["health"]["grade"] is None
+    assert empty["pareto"]["rows"] == [] and empty["rate"]["bins"] != []
+
+
+def test_build_bundle_filters():
+    start, end = T0, T0 + 4 * H
+    b = calc.build_bundle(synth_rows(), [], None, start, end, end,
+                          {"filters": {"areas": ["Area2"]}})
+    assert all(a == "Area2" for a in b["meta"]["areas"])
+    # Area2 = 5 baseline rows (i % 4 == 2) + 18 flood rows
+    assert b["meta"]["activation_count"] == 23

tests/test_fmt.py

@@ -0,0 +1,94 @@
+import os
+import time
+
+from PrimeControls import calc, fmt
+
+H = 3600000
+M = 60000
+T0 = 1784200000000
+
+
+def test_dur_num_pct():
+    assert fmt.dur(None) == "--"
+    assert fmt.dur(42000) == "42s"
+    assert fmt.dur(90 * M) == "1h 30m"
+    assert fmt.dur(26 * H) == "1d 2h"
+    assert fmt.num(None) == "--"
+    assert fmt.num(1234567) == "1,234,567"
+    assert fmt.num(12.345, 1) == "12.3"
+    assert fmt.pct(34.2) == "34%"
+    assert fmt.pct(34.2, 0, True) == "+34%"
+
+
+def test_delta_chip():
+    assert fmt.delta_chip(calc.delta(200, 100))["arrow"] == fmt.ARROW_UP
+    assert fmt.delta_chip(calc.delta(50, 100))["arrow"] == fmt.ARROW_DOWN
+    assert fmt.delta_chip(calc.delta(10, 0))["text"] == "new"
+    assert fmt.delta_chip(None)["text"] == "--"
+
+
+def bundle_with(rows=None, status=None):
+    return calc.build_bundle(rows or [], status or [], 0, T0, T0 + 4 * H, T0 + 4 * H)
+
+
+def lifecycle(eid, src, t, dur_ms=None, ack_ms=None, prio=3):
+    lvl, name = calc.normalize_priority(prio)
+    rows = [{"event_id": eid, "source": src, "display_path": "", "priority": lvl,
+             "priority_name": name, "state": "active", "ts": t, "is_system": False,
+             "ack_user": None}]
+    if dur_ms:
+        rows.append(dict(rows[0], state="clear", ts=t + dur_ms))
+    return rows
+
+
+def test_insights_fallback_and_cap():
+    b = bundle_with()
+    ins = fmt.insights(b)
+    assert len(ins) == 1 and ins[0]["severity"] == 3
+    assert "No alarm events" in ins[0]["text"]
+
+
+def test_insights_chatter_and_flood_fire():
+    rows = []
+    for i in range(100):  # ~25/hr over the 4h window, median gap 50s
+        rows += lifecycle("c%d" % i, "prov:default:/tag:P/A/Chat:/alm:Chat",
+                          T0 + i * 50000, dur_ms=8000)
+    for i in range(15):
+        rows += lifecycle("f%d" % i, "prov:default:/tag:P/B/F%d:/alm:F%d" % (i, i),
+                          T0 + 2 * H + i * 30000, dur_ms=M)
+    b = bundle_with(rows)
+    b["insights"] = fmt.insights(b)
+    texts = " | ".join(i["text"] for i in b["insights"])
+    assert "chatter" in texts.lower()
+    assert "flood" in texts.lower()
+    assert len(b["insights"]) <= 5
+
+
+def test_shift_bounds_grid():
+    os.environ["TZ"] = "UTC"
+    time.tzset()
+    # Thu Jul 16 2026 14:20 UTC
+    now = 1784211600000 + 20 * M
+    sb = fmt.shift_bounds(now, 8, 0)
+    cs, ce = sb["current"]
+    ps, pe = sb["previous"]
+    assert ce - cs == 8 * H and pe == cs
+    lt = time.localtime(cs / 1000.0)
+    assert lt.tm_hour in (0, 8, 16)
+    sb2 = fmt.shift_bounds(now, 12, 6)
+    lt2 = time.localtime(sb2["current"][0] / 1000.0)
+    assert lt2.tm_hour in (6, 18)
+
+
+def test_shift_report_sections():
+    rows = []
+    for i in range(10):
+        rows += lifecycle("b%d" % i, "prov:default:/tag:P/A/T%d:/alm:T%d" % (i, i),
+                          T0 + i * 10 * M, dur_ms=M)
+    b = bundle_with(rows)
+    b["insights"] = fmt.insights(b)
+    rep = fmt.shift_report(b, "Thu 6:00 AM - Thu 2:00 PM")
+    heads = [s["heading"] for s in rep["sections"]]
+    assert any("SHIFT REPORT" in h for h in heads)
+    assert any("KPIs" in h for h in heads)
+    assert "Activations" in rep["text"]