Add per-area alarm breakdown (Areas tab + AreaCard), disable sim tick

New area_breakdown() calc groups top-5 alarm sources by plant area for
a new Areas tab / AreaCard component. Disabled AlarmSimTick so it stops
generating data during dev.

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

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

@@ -536,6 +536,40 @@ def heatmap(instances, opts=None):
             "max_count": mx, "total": total}
 
 
+def area_breakdown(instances, opts=None, per_area=5):
+    """Top-N most active alarm sources per plant area.
+    Returns [{area, total, top: [{rank, source, label, priority_name, count,
+    pct}]}] sorted by area total desc; pct is share of the AREA's activations."""
+    groups = {}
+    for inst in instances or []:
+        if inst.get("active_ms") is None:
+            continue
+        a = inst.get("area") or "unknown"
+        if a not in groups:
+            groups[a] = {"total": 0, "counts": {}, "refs": {}}
+        g = groups[a]
+        g["total"] += 1
+        src = inst["source"]
+        g["counts"][src] = g["counts"].get(src, 0) + 1
+        if src not in g["refs"]:
+            g["refs"][src] = inst
+    out = []
+    for a in groups:
+        g = groups[a]
+        ordered = sorted(g["counts"].items(),
+                         key=lambda kv: (-kv[1], g["refs"][kv[0]]["label"]))[:per_area]
+        top = []
+        for i in range(len(ordered)):
+            src, c = ordered[i]
+            ref = g["refs"][src]
+            top.append({"rank": i + 1, "source": src, "label": ref["label"],
+                        "priority_name": ref["priority_name"], "count": c,
+                        "pct": 100.0 * c / g["total"] if g["total"] else 0.0})
+        out.append({"area": a, "total": g["total"], "top": top})
+    out.sort(key=lambda x: (-x["total"], x["area"]))
+    return out
+
+
 def priority_distribution(instances, opts=None):
     o = opts_merged(opts)
     raw_counts = {}
@@ -727,6 +761,7 @@ def _assemble(instances, active_now, shelved_count, start_ms, end_ms, now_ms,
     par = pareto(current, o)
     prio = priority_distribution(current, o)
     heat = heatmap(current, o)
+    areas_top = area_breakdown(current, o)
 
     # prior mirrors (cheap subset for deltas)
     p_start = start_ms - (end_ms - start_ms)
@@ -800,6 +835,7 @@ def _assemble(instances, active_now, shelved_count, start_ms, end_ms, now_ms,
         "heatmap": heat,
         "mtta_mttr": mm,
         "pareto": par,
+        "areas_top": areas_top,
         "top_sources": top_sources(par, 5),
         "chattering": chat,
         "fleeting": fleet,