285 lines
12 KiB
Python
285 lines
12 KiB
Python
"""Raw producer that replays a recorded snapshot dataset (no hardware).
|
|
|
|
Selected by the supervisor instead of the model's normal acquisition producer
|
|
when ``radar.replay.dataset_dir`` is non-empty. The dataset is a directory of
|
|
snapshot folders named ``NNNN_idK_ns<timestamp>`` (the VNA_AlGo
|
|
preprocessed-capture layout), each holding ``i{input}_o{output}_s21.npy`` and
|
|
``i{input}_o{output}_freq.npy`` files for every run combo.
|
|
|
|
The recorded data is already background-subtracted, so the profile must pair
|
|
this producer with NEUTRAL preprocess sets (calibration = 1, reference = 0,
|
|
no notch) — then the C++ preprocessor passes the traces through bit-exactly
|
|
and the processors (e.g. sar3d) see the recorded scene.
|
|
|
|
Timeline: snapshot timestamps are re-anchored to this process's monotonic
|
|
clock, preserving the recorded inter-frame gaps. On loop, the seam advances by
|
|
the median inter-frame gap, so motion-model consumers (sar3d aperture offsets)
|
|
never see time jump backwards. ``collection_id`` increases forever.
|
|
"""
|
|
|
|
from __future__ import annotations
|
|
|
|
import argparse
|
|
from contextlib import ExitStack
|
|
import json
|
|
import logging
|
|
from pathlib import Path
|
|
import re
|
|
import signal
|
|
import statistics
|
|
import threading
|
|
import time
|
|
|
|
import numpy as np
|
|
|
|
from python_app.logging_setup import coerce_level
|
|
from python_app.models.dataset_model import ComboKey, SweepCollection, TraceData
|
|
from python_app.models.run_config_model import RunConfigModel
|
|
from python_app.orchestration.shm import ShmRingWriter
|
|
from python_app.storage.npz.serialize import RAW_MAGIC, serialize_trace_collection
|
|
|
|
logger = logging.getLogger(__name__)
|
|
|
|
_SNAPSHOT_NAME = re.compile(r"^(\d+)_id\d+_ns(\d+)$")
|
|
|
|
|
|
class ReplayDataset:
|
|
"""Recorded snapshots preloaded into memory, with their recorded timeline."""
|
|
|
|
def __init__(self, snapshots: list[list[TraceData]], timestamps_ns: list[int]) -> None:
|
|
self.snapshots = snapshots
|
|
self.timestamps_ns = timestamps_ns
|
|
gaps = [b - a for a, b in zip(timestamps_ns, timestamps_ns[1:])]
|
|
# Median gap doubles as the loop-seam step and the capture-window span;
|
|
# a single-snapshot dataset falls back to an arbitrary sane cadence.
|
|
self.median_gap_ns = int(statistics.median(gaps)) if gaps else 160_000_000
|
|
|
|
def __len__(self) -> int:
|
|
return len(self.snapshots)
|
|
|
|
|
|
def _load_dataset(dataset_dir: Path, combos: list[ComboKey], expected_points: int) -> ReplayDataset:
|
|
"""Preload every snapshot's traces; fail loudly on a malformed dataset."""
|
|
if not dataset_dir.is_dir():
|
|
raise RuntimeError(f"radar.replay.dataset_dir is not a directory: {dataset_dir}")
|
|
|
|
named: list[tuple[int, str, int]] = []
|
|
for entry in dataset_dir.iterdir():
|
|
match = _SNAPSHOT_NAME.match(entry.name)
|
|
if entry.is_dir() and match:
|
|
named.append((int(match.group(1)), entry.name, int(match.group(2))))
|
|
if not named:
|
|
raise RuntimeError(
|
|
f"No snapshot folders (NNNN_idK_ns<ts>) found in {dataset_dir}"
|
|
)
|
|
|
|
snapshots: list[list[TraceData]] = []
|
|
timestamps_ns: list[int] = []
|
|
for _, name, timestamp_ns in sorted(named):
|
|
folder = dataset_dir / name
|
|
# Recorded per-trace capture windows from the snapshot's meta.json: the
|
|
# sar3d segmented timing model reconstructs the acquisition segments
|
|
# from them. Missing/partial meta leaves the zero "unmeasured" sentinel
|
|
# and the consumer falls back to its uniform-segment model.
|
|
windows: dict[tuple[int, int], tuple[int, int]] = {}
|
|
meta_path = folder / "meta.json"
|
|
if meta_path.is_file():
|
|
try:
|
|
meta = json.loads(meta_path.read_text())
|
|
for entry in meta.get("traces", []):
|
|
windows[(int(entry["input"]), int(entry["output"]))] = (
|
|
int(entry["capture_start_ns"]),
|
|
int(entry["capture_end_ns"]),
|
|
)
|
|
except (OSError, ValueError, KeyError, TypeError):
|
|
windows = {}
|
|
traces: list[TraceData] = []
|
|
for combo in combos:
|
|
s21_path = folder / f"i{combo.input}_o{combo.output}_s21.npy"
|
|
freq_path = folder / f"i{combo.input}_o{combo.output}_freq.npy"
|
|
if not s21_path.is_file() or not freq_path.is_file():
|
|
raise RuntimeError(
|
|
f"Snapshot {name} is missing files for combo "
|
|
f"input={combo.input} output={combo.output}: expected "
|
|
f"{s21_path.name} and {freq_path.name}. Check run.combos vs the dataset."
|
|
)
|
|
s21 = np.load(s21_path, allow_pickle=False).astype(np.complex64, copy=False)
|
|
freq = np.load(freq_path, allow_pickle=False).astype(np.float32, copy=False)
|
|
s11_path = folder / f"i{combo.input}_o{combo.output}_s11.npy"
|
|
s11 = np.load(s11_path, allow_pickle=False).astype(np.complex64, copy=False) if s11_path.is_file() else np.zeros_like(s21)
|
|
if freq.ndim != 1 or s21.shape != freq.shape or s11.shape != freq.shape:
|
|
raise RuntimeError(f"Snapshot {name}: frequency, S11 and S21 must be equally sized 1D arrays")
|
|
if expected_points and s21.size != expected_points:
|
|
raise RuntimeError(
|
|
f"{s21_path}: {s21.size} points, but radar.sweep.points = "
|
|
f"{expected_points}. Align the profile's sweep with the dataset."
|
|
)
|
|
window = windows.get((combo.input, combo.output), (0, 0))
|
|
traces.append(
|
|
TraceData(
|
|
combo=combo,
|
|
frequency_hz=freq,
|
|
s11=s11,
|
|
s21=s21,
|
|
capture_start_ns=window[0],
|
|
capture_end_ns=window[1],
|
|
)
|
|
)
|
|
snapshots.append(traces)
|
|
timestamps_ns.append(timestamp_ns)
|
|
|
|
return ReplayDataset(snapshots, timestamps_ns)
|
|
|
|
|
|
def _build_collection(
|
|
dataset: ReplayDataset,
|
|
index: int,
|
|
collection_id: int,
|
|
frame_ns: int,
|
|
) -> SweepCollection:
|
|
"""Wrap one preloaded snapshot in a SweepCollection at the given frame time.
|
|
|
|
Recorded per-trace capture windows are re-anchored by the same shift as the
|
|
frame time, preserving the real intra-frame segment layout. Traces without
|
|
recorded windows get a synthetic window spanning the median frame gap.
|
|
"""
|
|
span_ns = dataset.median_gap_ns
|
|
start_ns = frame_ns - span_ns // 2
|
|
end_ns = frame_ns + span_ns // 2
|
|
shift_ns = frame_ns - dataset.timestamps_ns[index]
|
|
traces = []
|
|
for source in dataset.snapshots[index]:
|
|
if source.capture_end_ns > source.capture_start_ns:
|
|
capture = (source.capture_start_ns + shift_ns, source.capture_end_ns + shift_ns)
|
|
else:
|
|
capture = (start_ns, end_ns)
|
|
traces.append(
|
|
TraceData(
|
|
combo=source.combo,
|
|
frequency_hz=source.frequency_hz,
|
|
s11=source.s11,
|
|
s21=source.s21,
|
|
capture_start_ns=capture[0],
|
|
capture_end_ns=capture[1],
|
|
)
|
|
)
|
|
return SweepCollection(
|
|
collection_id=collection_id,
|
|
monotonic_ns=frame_ns,
|
|
traces=traces,
|
|
capture_start_ns=min(t.capture_start_ns for t in traces),
|
|
capture_end_ns=max(t.capture_end_ns for t in traces),
|
|
)
|
|
|
|
|
|
def main() -> int:
|
|
"""Replay the configured dataset into the raw SHM rings until stopped."""
|
|
parser = argparse.ArgumentParser(description="Replay a recorded dataset to raw SHM rings")
|
|
parser.add_argument("--config", required=True, type=Path, help="Path to run_config.json")
|
|
args = parser.parse_args()
|
|
|
|
logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
|
|
stop_requested = threading.Event()
|
|
|
|
def request_stop(_signum: int, _frame: object) -> None:
|
|
stop_requested.set()
|
|
|
|
signal.signal(signal.SIGINT, request_stop)
|
|
signal.signal(signal.SIGTERM, request_stop)
|
|
|
|
config = RunConfigModel.load_from_path(args.config)
|
|
config.apply_device_model_constraints()
|
|
logging.getLogger("python_app").setLevel(coerce_level(config.logging.level))
|
|
|
|
replay = config.radar.replay
|
|
if not replay.dataset_dir:
|
|
raise RuntimeError("replay_raw_producer requires a non-empty radar.replay.dataset_dir")
|
|
rate_scale = float(replay.rate_scale) if replay.rate_scale > 0 else 1.0
|
|
combos = [ComboKey(input=combo.input, output=combo.output) for combo in config.combos]
|
|
|
|
# expanduser: profiles are copied between machines, so "~/..." dataset paths
|
|
# must resolve against the local home instead of failing as a literal "~".
|
|
dataset = _load_dataset(
|
|
Path(replay.dataset_dir).expanduser(), combos, int(config.radar.sweep.points)
|
|
)
|
|
logger.info(
|
|
"Replay producer starting: dataset=%s, snapshots=%d, combos=%d, "
|
|
"median_gap=%.3f s, loop=%s, rate_scale=%.2f",
|
|
replay.dataset_dir, len(dataset), len(combos),
|
|
dataset.median_gap_ns / 1e9, replay.loop, rate_scale,
|
|
)
|
|
|
|
cleanup = ExitStack()
|
|
try:
|
|
raw_writer = ShmRingWriter(
|
|
config.rings.raw.name,
|
|
config.rings.raw.capacity,
|
|
config.rings.raw.slot_size_bytes,
|
|
)
|
|
cleanup.callback(raw_writer.close)
|
|
raw_tap_writer = ShmRingWriter(
|
|
config.rings.raw_tap.name,
|
|
config.rings.raw_tap.capacity,
|
|
config.rings.raw_tap.slot_size_bytes,
|
|
)
|
|
cleanup.callback(raw_tap_writer.close)
|
|
|
|
payload_size = len(serialize_trace_collection(
|
|
_build_collection(dataset, 0, 1, time.monotonic_ns()), RAW_MAGIC
|
|
))
|
|
for ring in (config.rings.raw, config.rings.raw_tap):
|
|
if ring.slot_size_bytes < payload_size:
|
|
raise ValueError(f"Replay requires {payload_size} bytes per slot; ring {ring.name} has {ring.slot_size_bytes}")
|
|
|
|
base_ns = time.monotonic_ns()
|
|
wall_start_s = time.monotonic()
|
|
first_ts = dataset.timestamps_ns[0]
|
|
cycle_span_ns = dataset.timestamps_ns[-1] - first_ts + dataset.median_gap_ns
|
|
|
|
collection_id = 1
|
|
cycle = 0
|
|
while not stop_requested.is_set():
|
|
for index in range(len(dataset)):
|
|
if stop_requested.is_set():
|
|
break
|
|
# Monotonic replay timeline: recorded offsets re-anchored at
|
|
# base_ns, each loop shifted by one full cycle span.
|
|
frame_ns = (
|
|
base_ns
|
|
+ (dataset.timestamps_ns[index] - first_ts)
|
|
+ cycle * cycle_span_ns
|
|
)
|
|
# Publish on the recorded cadence (scaled); waiting via the stop
|
|
# event keeps shutdown prompt.
|
|
deadline_s = wall_start_s + (frame_ns - base_ns) / 1e9 / rate_scale
|
|
delay_s = deadline_s - time.monotonic()
|
|
if delay_s > 0 and stop_requested.wait(delay_s):
|
|
break
|
|
|
|
collection = _build_collection(dataset, index, collection_id, frame_ns)
|
|
payload = serialize_trace_collection(collection, RAW_MAGIC)
|
|
if not raw_writer.push(payload):
|
|
raise RuntimeError(f"Replay raw ring rejected collection {collection_id}")
|
|
raw_tap_writer.push(payload)
|
|
if collection_id == 1 or collection_id % 50 == 0:
|
|
logger.info(
|
|
"replay collection %d published (snapshot %d/%d, cycle %d)",
|
|
collection_id, index + 1, len(dataset), cycle,
|
|
)
|
|
collection_id += 1
|
|
if not config.runtime.continuous:
|
|
stop_requested.set()
|
|
break
|
|
if not replay.loop:
|
|
break
|
|
cycle += 1
|
|
finally:
|
|
cleanup.close()
|
|
|
|
logger.info("replay raw producer stopped")
|
|
return 0
|
|
|
|
|
|
if __name__ == "__main__":
|
|
raise SystemExit(main())
|