bscan added s11
This commit is contained in:
@@ -60,6 +60,7 @@ class AppWindowSnapshotMixin:
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last_n = int(self._save_count.value())
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input_index = int(self._vna_json_input_index.value())
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output_index = int(self._vna_json_output_index.value())
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channel = self._vna_json_channel.currentText()
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output_root = Path(self._save_path_input.text().strip()).expanduser()
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output_name = self._save_name_input.text().strip()
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output_path, summary = self._store.save_runtime_vna_history_json(
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@@ -71,6 +72,7 @@ class AppWindowSnapshotMixin:
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last_n,
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input_index=input_index,
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output_index=output_index,
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channel=channel,
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primary_stage="preprocessed",
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)
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self._log(
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@@ -85,6 +87,7 @@ class AppWindowSnapshotMixin:
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f"anchor={summary.get('anchor_stage', 'unknown')}, "
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f"input={input_index}, "
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f"output={output_index}, "
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f"channel={channel}, "
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f"requested_last_n={last_n})"
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)
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except Exception as exc: # noqa: BLE001
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@@ -3,7 +3,7 @@
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from __future__ import annotations
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from PyQt6.QtCore import Qt
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from PyQt6.QtWidgets import QGroupBox, QHBoxLayout, QLabel, QLineEdit, QPushButton, QSpinBox, QVBoxLayout
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from PyQt6.QtWidgets import QComboBox, QGroupBox, QHBoxLayout, QLabel, QLineEdit, QPushButton, QSpinBox, QVBoxLayout
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def build_data_actions_group(owner) -> QGroupBox:
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@@ -32,6 +32,8 @@ def build_data_actions_group(owner) -> QGroupBox:
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owner._vna_json_output_index.setMinimum(0)
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owner._vna_json_output_index.setMaximum(65_535)
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owner._vna_json_output_index.setValue(0)
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owner._vna_json_channel = QComboBox()
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owner._vna_json_channel.addItems(["s21", "s11"])
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button_column = QVBoxLayout()
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button_column.setSpacing(8)
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@@ -54,6 +56,8 @@ def build_data_actions_group(owner) -> QGroupBox:
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json_row.addWidget(owner._vna_json_input_index)
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json_row.addWidget(QLabel("output"))
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json_row.addWidget(owner._vna_json_output_index)
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json_row.addWidget(QLabel("channel"))
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json_row.addWidget(owner._vna_json_channel)
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json_row.addStretch(1)
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layout.addLayout(json_row)
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@@ -22,7 +22,7 @@ class TraceRecord:
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monotonic_ns: int
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stage_index: int
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frequency_hz: np.ndarray
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s21: np.ndarray
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samples: np.ndarray
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@dataclass(frozen=True)
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@@ -64,12 +64,20 @@ def _pick_trace_meta(meta: dict[str, Any], input_index: int, output_index: int)
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return None
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def _normalize_channel(channel: str) -> str:
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normalized = str(channel).strip().lower()
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if normalized not in {"s21", "s11"}:
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raise ValueError("channel must be either 's21' or 's11'")
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return normalized
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def _load_stage_records(
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snapshot_dir: Path,
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stage: str,
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*,
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input_index: int,
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output_index: int,
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channel: str,
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) -> list[TraceRecord]:
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stage_dir = snapshot_dir / stage
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records: list[TraceRecord] = []
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@@ -85,20 +93,20 @@ def _load_stage_records(
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continue
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freq_file = str(trace_meta.get("freq_file", ""))
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s21_file = str(trace_meta.get("s21_file", ""))
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if not freq_file or not s21_file:
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samples_file = str(trace_meta.get(f"{channel}_file", ""))
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if not freq_file or not samples_file:
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continue
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frequency_hz = np.asarray(np.load(collection_dir / freq_file), dtype=np.float64).reshape(-1)
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s21 = np.asarray(np.load(collection_dir / s21_file), dtype=np.complex128).reshape(-1)
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if frequency_hz.shape != s21.shape:
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raise ValueError(f"Shape mismatch in {collection_dir}: freq{frequency_hz.shape} vs s21{s21.shape}")
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samples = np.asarray(np.load(collection_dir / samples_file), dtype=np.complex128).reshape(-1)
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if frequency_hz.shape != samples.shape:
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raise ValueError(f"Shape mismatch in {collection_dir}: freq{frequency_hz.shape} vs {channel}{samples.shape}")
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if frequency_hz.size == 0:
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continue
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if not (
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np.isfinite(frequency_hz).all()
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and np.isfinite(np.real(s21)).all()
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and np.isfinite(np.imag(s21)).all()
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and np.isfinite(np.real(samples)).all()
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and np.isfinite(np.imag(samples)).all()
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):
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raise ValueError(f"Non-finite values in {collection_dir}")
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@@ -109,7 +117,7 @@ def _load_stage_records(
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monotonic_ns=int(meta.get("monotonic_ns", 0)),
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stage_index=_parse_stage_index(collection_dir.name, fallback_idx),
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frequency_hz=frequency_hz,
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s21=s21,
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samples=samples,
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)
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)
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@@ -157,6 +165,7 @@ def _build_sweep_history(
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raw_records: list[TraceRecord],
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preprocessed_records: list[TraceRecord],
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*,
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channel: str,
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primary_stage: str,
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) -> list[dict[str, Any]]:
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raw_map, raw_order = _index_by_collection_occurrence(raw_records)
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@@ -188,11 +197,11 @@ def _build_sweep_history(
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history.append(
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{
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"timestamp": timestamp_sec,
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"sweep_points": _complex_to_points(sweep_source.s21),
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"calibrated_points": _complex_to_points(calibrated_source.s21),
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"sweep_points": _complex_to_points(sweep_source.samples),
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"calibrated_points": _complex_to_points(calibrated_source.samples),
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"reference_points": [],
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"vna_config": {
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"mode": "s11",
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"mode": channel,
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"start_freq": start_freq_hz,
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"stop_freq": stop_freq_hz,
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"points": int(base.frequency_hz.size),
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@@ -257,6 +266,12 @@ def _build_parser() -> argparse.ArgumentParser:
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)
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parser.add_argument("--input", dest="input_index", type=int, default=0, help="Input switch index to export.")
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parser.add_argument("--output-index", dest="output_index", type=int, default=0, help="Output switch index to export.")
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parser.add_argument(
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"--channel",
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choices=("s21", "s11"),
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default="s21",
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help="Trace channel to export into sweep/calibrated points.",
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)
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parser.add_argument(
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"--primary-stage",
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choices=("preprocessed", "raw"),
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@@ -275,6 +290,7 @@ def _build_parser() -> argparse.ArgumentParser:
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def main() -> None:
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parser = _build_parser()
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args = parser.parse_args()
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channel = _normalize_channel(args.channel)
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snapshot_dir = args.snapshot_dir.expanduser().resolve()
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if not snapshot_dir.exists():
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@@ -291,12 +307,14 @@ def main() -> None:
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"raw",
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input_index=args.input_index,
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output_index=args.output_index,
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channel=channel,
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)
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preprocessed_records = _load_stage_records(
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snapshot_dir,
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"preprocessed",
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input_index=args.input_index,
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output_index=args.output_index,
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channel=channel,
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)
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if not raw_records and not preprocessed_records:
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raise ValueError(
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@@ -304,7 +322,12 @@ def main() -> None:
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f"for input={args.input_index}, output={args.output_index}."
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)
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sweep_history = _build_sweep_history(raw_records, preprocessed_records, primary_stage=args.primary_stage)
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sweep_history = _build_sweep_history(
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raw_records,
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preprocessed_records,
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channel=channel,
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primary_stage=args.primary_stage,
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)
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if args.last_n > 0:
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sweep_history = sweep_history[-args.last_n :]
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if not sweep_history:
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@@ -324,6 +347,7 @@ def main() -> None:
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"source_snapshot_dir": str(snapshot_dir),
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"input_index": int(args.input_index),
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"output_index": int(args.output_index),
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"channel": channel,
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"primary_stage": args.primary_stage,
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"raw_record_count": len(raw_records),
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"preprocessed_record_count": len(preprocessed_records),
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@@ -341,6 +365,7 @@ def main() -> None:
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"Converted snapshot to vna_system history JSON:\n"
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f" input snapshot: {snapshot_dir}\n"
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f" output file: {output_path}\n"
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f" channel: {channel}\n"
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f" sweeps written: {len(sweep_history)}\n"
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f" raw records: {len(raw_records)}\n"
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f" pre records: {len(preprocessed_records)}"
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@@ -225,6 +225,7 @@ class NpzStore(StoreApi):
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*,
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input_index: int = 0,
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output_index: int = 0,
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channel: str = "s21",
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primary_stage: str = "preprocessed",
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) -> tuple[Path, dict[str, Any]]:
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"""Save runtime history as vna_system-compatible JSON file."""
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@@ -251,6 +252,7 @@ class NpzStore(StoreApi):
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selected_results,
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input_index=input_index,
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output_index=output_index,
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channel=channel,
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primary_stage=primary_stage,
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)
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output_path.write_text(
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@@ -267,6 +269,7 @@ class NpzStore(StoreApi):
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summary["sweep_count"] = len(payload.get("sweep_history", []))
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summary["input_index"] = int(input_index)
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summary["output_index"] = int(output_index)
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summary["channel"] = str(channel)
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summary["primary_stage"] = str(primary_stage)
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summary["output_path"] = str(output_path)
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return output_path, summary
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@@ -21,7 +21,20 @@ class TraceRecord:
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monotonic_ns: int
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stage_index: int
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frequency_hz: np.ndarray
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s21: np.ndarray
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samples: np.ndarray
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def _normalize_channel(channel: str) -> str:
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normalized = str(channel).strip().lower()
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if normalized not in {"s21", "s11"}:
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raise ValueError("channel must be either 's21' or 's11'")
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return normalized
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def _select_trace_samples(trace: TraceData, channel: str) -> np.ndarray:
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if channel == "s11":
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return np.asarray(trace.s11, dtype=np.complex128).reshape(-1)
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return np.asarray(trace.s21, dtype=np.complex128).reshape(-1)
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def _pick_trace(collection: SweepCollection, input_index: int, output_index: int) -> TraceData | None:
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@@ -37,6 +50,7 @@ def _build_stage_records(
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*,
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input_index: int,
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output_index: int,
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channel: str,
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) -> list[TraceRecord]:
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records: list[TraceRecord] = []
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for stage_index, collection in enumerate(history):
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@@ -45,18 +59,18 @@ def _build_stage_records(
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continue
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frequency_hz = np.asarray(trace.frequency_hz, dtype=np.float64).reshape(-1)
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s21 = np.asarray(trace.s21, dtype=np.complex128).reshape(-1)
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if frequency_hz.shape != s21.shape:
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samples = _select_trace_samples(trace, channel)
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if frequency_hz.shape != samples.shape:
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raise ValueError(
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f"Shape mismatch in {stage} stage for collection_id={collection.collection_id}: "
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f"freq{frequency_hz.shape} vs s21{s21.shape}"
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f"freq{frequency_hz.shape} vs {channel}{samples.shape}"
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)
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if frequency_hz.size == 0:
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continue
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if not (
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np.isfinite(frequency_hz).all()
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and np.isfinite(np.real(s21)).all()
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and np.isfinite(np.imag(s21)).all()
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and np.isfinite(np.real(samples)).all()
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and np.isfinite(np.imag(samples)).all()
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):
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raise ValueError(f"Non-finite values in {stage} stage for collection_id={collection.collection_id}")
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@@ -67,7 +81,7 @@ def _build_stage_records(
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monotonic_ns=int(collection.monotonic_ns),
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stage_index=int(stage_index),
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frequency_hz=frequency_hz,
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s21=s21,
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samples=samples,
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)
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)
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return records
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@@ -94,6 +108,7 @@ def _build_sweep_history(
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raw_records: list[TraceRecord],
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preprocessed_records: list[TraceRecord],
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*,
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channel: str,
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primary_stage: str,
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) -> list[dict[str, Any]]:
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raw_map, raw_order = _index_by_collection_occurrence(raw_records)
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@@ -124,11 +139,11 @@ def _build_sweep_history(
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history.append(
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{
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"timestamp": timestamp_sec,
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"sweep_points": _complex_to_points(sweep_source.s21),
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"calibrated_points": _complex_to_points(calibrated_source.s21),
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"sweep_points": _complex_to_points(sweep_source.samples),
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"calibrated_points": _complex_to_points(calibrated_source.samples),
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"reference_points": [],
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"vna_config": {
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"mode": "s11",
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"mode": channel,
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"start_freq": start_freq_hz,
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"stop_freq": stop_freq_hz,
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"points": int(base.frequency_hz.size),
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@@ -178,9 +193,11 @@ def build_vna_history_payload(
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*,
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input_index: int,
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output_index: int,
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channel: str = "s21",
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primary_stage: str = "preprocessed",
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) -> dict[str, Any]:
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"""Build vna_system-compatible history JSON payload from runtime histories."""
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channel = _normalize_channel(channel)
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if primary_stage not in {"preprocessed", "raw"}:
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raise ValueError("primary_stage must be either 'preprocessed' or 'raw'")
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@@ -189,12 +206,14 @@ def build_vna_history_payload(
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raw_history,
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input_index=input_index,
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output_index=output_index,
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channel=channel,
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)
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preprocessed_records = _build_stage_records(
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"preprocessed",
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preprocessed_history,
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input_index=input_index,
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output_index=output_index,
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channel=channel,
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)
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if not raw_records and not preprocessed_records:
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raise ValueError(
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@@ -205,6 +224,7 @@ def build_vna_history_payload(
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sweep_history = _build_sweep_history(
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raw_records,
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preprocessed_records,
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channel=channel,
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primary_stage=primary_stage,
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)
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if not sweep_history:
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@@ -217,6 +237,7 @@ def build_vna_history_payload(
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"source_snapshot_dir": "<runtime_history>",
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"input_index": int(input_index),
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"output_index": int(output_index),
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"channel": channel,
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"primary_stage": str(primary_stage),
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"raw_record_count": len(raw_records),
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"preprocessed_record_count": len(preprocessed_records),
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@@ -228,4 +249,3 @@ def build_vna_history_payload(
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payload["alignment_warning"] = alignment_warning
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return payload
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Reference in New Issue
Block a user