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Ayzen
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"""Concrete :class:`StoreApi` implementation backed by NPZ files."""
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from __future__ import annotations
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from datetime import datetime
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import json
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from pathlib import Path
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from typing import Any
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import numpy as np
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from python_app.models.dataset_model import ComboKey, ResultCollection, SweepCollection, TraceData
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from python_app.storage.npz.paths import radar_key_from_config, sanitize_path_component
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from python_app.storage.npz.serialize import PREPROC_MAGIC, RAW_MAGIC, serialize_trace_collection
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from python_app.storage.npz.snapshot_numpy import (
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save_result_history_binary,
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save_result_history_numpy,
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save_trace_history_binary,
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save_trace_history_numpy,
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select_aligned_histories,
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)
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from python_app.storage.store_api import StoreApi
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class NpzStore(StoreApi):
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"""Persist calibration/reference sets and runtime snapshots using NumPy files."""
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def __init__(self, root_dir: Path) -> None:
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"""Create store rooted at `root_dir`."""
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self._root_dir = root_dir
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self._root_dir.mkdir(parents=True, exist_ok=True)
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def save_set(self, kind: str, radar_key: str, set_name: str, collection: SweepCollection) -> None:
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"""Persist named calibration/reference set as NPZ and metadata JSON."""
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set_dir = self._set_dir(kind, radar_key)
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set_dir.mkdir(parents=True, exist_ok=True)
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npz_path = set_dir / f"{set_name}.npz"
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meta_path = set_dir / f"{set_name}.json"
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payload: dict[str, np.ndarray] = {}
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combo_records: list[dict[str, str | int]] = []
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for trace in collection.traces:
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suffix = f"i{trace.combo.input_pos}_o{trace.combo.output_pos}"
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freq_key = f"freq_{suffix}"
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s21_key = f"s21_{suffix}"
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payload[freq_key] = np.asarray(trace.frequency_hz, dtype=np.float32)
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payload[s21_key] = np.asarray(trace.s21, dtype=np.complex64)
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combo_records.append(
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{
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"input": trace.combo.input_pos,
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"output": trace.combo.output_pos,
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"freq_key": freq_key,
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"s21_key": s21_key,
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}
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)
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np.savez(npz_path, **payload)
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meta = {
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"collection_id": int(collection.collection_id),
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"monotonic_ns": int(collection.monotonic_ns),
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"combos": combo_records,
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}
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meta_path.write_text(json.dumps(meta, indent=2), encoding="utf-8")
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def load_set(self, kind: str, radar_key: str, set_name: str) -> SweepCollection:
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"""Load named calibration/reference set from NPZ representation."""
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set_dir = self._set_dir(kind, radar_key)
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npz_path = set_dir / f"{set_name}.npz"
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meta_path = set_dir / f"{set_name}.json"
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if not npz_path.exists() or not meta_path.exists():
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raise FileNotFoundError(f"Missing set files for {kind}/{radar_key}/{set_name}")
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meta = json.loads(meta_path.read_text(encoding="utf-8"))
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arrays = np.load(npz_path)
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traces: list[TraceData] = []
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for combo in meta["combos"]:
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freq = np.asarray(arrays[combo["freq_key"]], dtype=np.float32)
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s21 = np.asarray(arrays[combo["s21_key"]], dtype=np.complex64)
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traces.append(
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TraceData(
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combo=ComboKey(input_pos=int(combo["input"]), output_pos=int(combo["output"])),
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frequency_hz=freq,
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s21=s21,
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)
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)
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return SweepCollection(
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collection_id=int(meta["collection_id"]),
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monotonic_ns=int(meta["monotonic_ns"]),
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traces=traces,
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)
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def list_sets(self, kind: str, radar_key: str) -> list[str]:
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"""List available set names for `(kind, radar_key)`."""
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set_dir = self._set_dir(kind, radar_key)
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if not set_dir.exists():
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return []
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return sorted(path.stem for path in set_dir.glob("*.npz"))
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def has_combo_coverage(self, kind: str, radar_key: str, set_name: str, combos: list[ComboKey]) -> bool:
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"""Validate that named set covers all required switch combinations."""
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collection = self.load_set(kind, radar_key, set_name)
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existing = {(trace.combo.input_pos, trace.combo.output_pos) for trace in collection.traces}
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required = {(combo.input_pos, combo.output_pos) for combo in combos}
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return required.issubset(existing)
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def export_set_bundle(self, kind: str, radar_key: str, set_name: str, output_path: Path) -> Path:
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"""Export named set as binary collection bundle for C++ preprocessing stage."""
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collection = self.load_set(kind, radar_key, set_name)
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output_path.parent.mkdir(parents=True, exist_ok=True)
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output_path.write_bytes(serialize_trace_collection(collection, RAW_MAGIC))
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return output_path
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def save_runtime_snapshot(
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self,
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output_dir: Path,
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raw_history: list[SweepCollection],
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preprocessed_history: list[SweepCollection],
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result_history: list[ResultCollection],
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last_n: int,
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) -> Path:
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"""Save historical runtime collections using binary on-disk format."""
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if last_n <= 0:
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raise ValueError("last_n must be > 0")
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output_dir.mkdir(parents=True, exist_ok=True)
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timestamp = datetime.utcnow().strftime("%Y%m%d_%H%M%S")
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snapshot_dir = output_dir / f"snapshot_{timestamp}"
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snapshot_dir.mkdir(parents=True, exist_ok=True)
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save_trace_history_binary(snapshot_dir / "raw", raw_history[-last_n:], RAW_MAGIC)
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save_trace_history_binary(snapshot_dir / "preprocessed", preprocessed_history[-last_n:], PREPROC_MAGIC)
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save_result_history_binary(snapshot_dir / "results", result_history[-last_n:])
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return snapshot_dir
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def save_runtime_snapshot_numpy(
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self,
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output_root_dir: Path,
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snapshot_name: str,
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raw_history: list[SweepCollection],
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preprocessed_history: list[SweepCollection],
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result_history: list[ResultCollection],
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last_n: int,
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) -> tuple[Path, dict[str, Any]]:
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"""Save historical runtime collections in NumPy tree format."""
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if last_n <= 0:
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raise ValueError("last_n must be > 0")
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snapshot_stem = snapshot_name.strip() or datetime.utcnow().strftime("snapshot_%Y%m%d_%H%M%S")
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snapshot_stem = sanitize_path_component(snapshot_stem)
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output_root_dir.mkdir(parents=True, exist_ok=True)
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snapshot_dir = output_root_dir / snapshot_stem
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if snapshot_dir.exists():
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raise FileExistsError(f"Snapshot directory already exists: {snapshot_dir}")
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snapshot_dir.mkdir(parents=True, exist_ok=False)
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selected_raw, selected_preprocessed, selected_results, selection_summary = select_aligned_histories(
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raw_history,
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preprocessed_history,
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result_history,
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last_n,
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)
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save_trace_history_numpy(snapshot_dir / "raw", selected_raw)
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save_trace_history_numpy(snapshot_dir / "preprocessed", selected_preprocessed)
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save_result_history_numpy(snapshot_dir / "results", selected_results)
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(snapshot_dir / "manifest.json").write_text(
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json.dumps(
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{
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"format": "numpy-directory-v1",
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"selection_mode": selection_summary["selection_mode"],
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"selected_collection_ids": selection_summary["selected_collection_ids"],
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"raw_collections": len(selected_raw),
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"preprocessed_collections": len(selected_preprocessed),
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"result_collections": len(selected_results),
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"last_n_requested": int(last_n),
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"raw_history_size": len(raw_history),
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"preprocessed_history_size": len(preprocessed_history),
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"result_history_size": len(result_history),
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},
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indent=2,
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),
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encoding="utf-8",
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)
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selection_summary["raw_count"] = len(selected_raw)
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selection_summary["preprocessed_count"] = len(selected_preprocessed)
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selection_summary["result_count"] = len(selected_results)
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selection_summary["snapshot_dir"] = str(snapshot_dir)
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return snapshot_dir, selection_summary
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def _set_dir(self, kind: str, radar_key: str) -> Path:
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"""Return directory for set kind and radar key."""
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return self._root_dir / kind / radar_key
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__all__ = ["NpzStore", "radar_key_from_config"]
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