UI updates

python_app/storage/npz/store.py

@@ -176,30 +176,6 @@ class NpzStore(StoreApi):
         save_trace_history_numpy(snapshot_dir / "preprocessed", selected_preprocessed)
         save_result_history_numpy(snapshot_dir / "results", selected_results)
 
-        (snapshot_dir / "manifest.json").write_text(
-            json.dumps(
-                {
-                    "format": "numpy-directory-v1",
-                    "selection_mode": selection_summary["selection_mode"],
-                    "anchor_stage": selection_summary.get("anchor_stage", "unknown"),
-                    "selected_collection_ids": selection_summary["selected_collection_ids"],
-                    "aligned_key_count": int(selection_summary.get("aligned_key_count", 0)),
-                    "raw_missing_count": int(selection_summary.get("raw_missing_count", 0)),
-                    "preprocessed_missing_count": int(selection_summary.get("preprocessed_missing_count", 0)),
-                    "result_missing_count": int(selection_summary.get("result_missing_count", 0)),
-                    "raw_collections": len(selected_raw),
-                    "preprocessed_collections": len(selected_preprocessed),
-                    "result_collections": len(selected_results),
-                    "last_n_requested": int(last_n),
-                    "raw_history_size": len(raw_history),
-                    "preprocessed_history_size": len(preprocessed_history),
-                    "result_history_size": len(result_history),
-                },
-                indent=2,
-            ),
-            encoding="utf-8",
-        )
-
         if selection_summary.get("anchor_stage") == "results":
             expected = min(int(last_n), len(result_history))
             if len(selected_results) != expected:
@@ -211,6 +187,7 @@ class NpzStore(StoreApi):
         selection_summary["raw_count"] = len(selected_raw)
         selection_summary["preprocessed_count"] = len(selected_preprocessed)
         selection_summary["result_count"] = len(selected_results)
+        selection_summary["snapshot_stem"] = snapshot_stem
         selection_summary["snapshot_dir"] = str(snapshot_dir)
         return snapshot_dir, selection_summary
 
@@ -271,9 +248,87 @@ class NpzStore(StoreApi):
         summary["output_index"] = int(output_index)
         summary["channel"] = str(channel)
         summary["primary_stage"] = str(primary_stage)
+        summary["output_stem"] = output_stem
         summary["output_path"] = str(output_path)
         return output_path, summary
 
+    def save_runtime_vna_history_json_batch(
+        self,
+        output_root_dir: Path,
+        output_name: str,
+        raw_history: list[SweepCollection],
+        preprocessed_history: list[SweepCollection],
+        result_history: list[ResultCollection],
+        last_n: int,
+        *,
+        channel: str = "s21",
+        primary_stage: str = "preprocessed",
+    ) -> tuple[list[Path], dict[str, Any]]:
+        """Save one runtime VNA-history JSON per available combo."""
+        if last_n <= 0:
+            raise ValueError("last_n must be > 0")
+
+        output_stem = output_name.strip() or datetime.utcnow().strftime("snapshot_%Y%m%d_%H%M%S")
+        output_stem = sanitize_path_component(output_stem)
+        output_root_dir.mkdir(parents=True, exist_ok=True)
+
+        selected_raw, selected_preprocessed, selected_results, selection_summary = select_aligned_histories(
+            raw_history,
+            preprocessed_history,
+            result_history,
+            last_n,
+        )
+
+        combos = sorted(
+            {
+                (int(trace.combo.input_pos), int(trace.combo.output_pos))
+                for collection in [*selected_raw, *selected_preprocessed]
+                for trace in collection.traces
+            }
+        )
+        if not combos:
+            raise ValueError("No matching raw/preprocessed traces were found in runtime history for any combo.")
+
+        output_paths: list[Path] = []
+        payloads: list[dict[str, Any]] = []
+        for input_index, output_index in combos:
+            output_path = output_root_dir / (
+                f"{output_stem}_i{input_index}_o{output_index}_{channel}_vna_bscan_history.json"
+            )
+            if output_path.exists():
+                raise FileExistsError(f"Output JSON file already exists: {output_path}")
+            payloads.append(
+                build_vna_history_payload(
+                    selected_raw,
+                    selected_preprocessed,
+                    selected_results,
+                    input_index=input_index,
+                    output_index=output_index,
+                    channel=channel,
+                    primary_stage=primary_stage,
+                )
+            )
+            output_paths.append(output_path)
+
+        for output_path, payload in zip(output_paths, payloads, strict=True):
+            output_path.write_text(
+                json.dumps(payload, ensure_ascii=False, indent=2),
+                encoding="utf-8",
+            )
+
+        summary: dict[str, Any] = dict(selection_summary)
+        summary["raw_count"] = len(selected_raw)
+        summary["preprocessed_count"] = len(selected_preprocessed)
+        summary["result_count"] = len(selected_results)
+        summary["preprocessed_record_count"] = int(sum(int(payload.get("preprocessed_record_count", 0)) for payload in payloads))
+        summary["combo_count"] = len(combos)
+        summary["combos"] = [list(combo) for combo in combos]
+        summary["channel"] = str(channel)
+        summary["primary_stage"] = str(primary_stage)
+        summary["output_stem"] = output_stem
+        summary["output_paths"] = [str(path) for path in output_paths]
+        return output_paths, summary
+
     def _set_dir(self, kind: str, radar_key: str) -> Path:
         """Return directory for set kind and radar key."""
         return self._root_dir / kind / radar_key