aweandClaude Fable 5
e1dfbec712
- replay_raw_producer carries the RECORDED per-trace capture windows from each snapshot's meta.json (re-anchored by the same shift as the frame time) instead of one synthetic window for all traces — without this the segmented timing model degenerates in replay; - GUI/profile/orchestration swap the removed window knobs (center_depth, half_width_*, grid_n*) for the notebook parameters (ground depth, pitch override, voxel pitch, Y range, X margin, norm edge margin, smooth sigma, comp power, tx per segment). Headless replay smoke on the 20260922_mine_fast_true dataset passes: 51 sar3d result collections, transparent preprocessor. Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
260 lines
12 KiB
Python
260 lines
12 KiB
Python
"""Headless smoke: replay the recorded VNA_AlGo dataset through the full pipeline.
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Loads the replay profile, creates neutral preprocess sets, launches the whole
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pipeline (replay_raw_producer -> data_preprocessor -> data_processor) via the
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ProcessSupervisor with unique ring names, forces the sar3d processor through
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processing_live.json, and asserts that:
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- sar3d projection payloads arrive with a positive peak;
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- collection ids increase monotonically (including across a dataset loop);
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- the preprocessor is transparent: a preprocessed_tap trace equals the
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recorded snapshot's s21 within float32 rounding.
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Usage:
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python -m python_app.scripts.replay_smoke_run \
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[--config run_config_examples/run_config_replay_vna.example.json] \
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[--duration 20.0]
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"""
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from __future__ import annotations
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import argparse
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import json
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import logging
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import os
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from pathlib import Path
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import time
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import numpy as np
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from python_app.models.run_config_model import RunConfigModel
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from python_app.orchestration.config_writer import ConfigWriter
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from python_app.orchestration.live_processing_config import (
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ProcessingLiveConfig,
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ProcessingLiveConfigWriter,
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)
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from python_app.orchestration.process_supervisor import ProcessSupervisor
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from python_app.orchestration.shm import ShmRingReader
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from python_app.orchestration.shm.decoder import PREPROC_MAGIC, decode_trace_collection
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from python_app.storage.npz_store import NpzStore, radar_key_from_config
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from python_app.workflows.kamil_adc_neutral_preprocess import build_neutral_s21_sets
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logger = logging.getLogger(__name__)
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PROJECT_ROOT = Path(__file__).resolve().parents[2]
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def _make_unique_ring_name(prefix: str) -> str:
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"""Build unique POSIX SHM ring name."""
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return f"/{prefix}_{os.getpid()}_{time.monotonic_ns()}"
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def _sar3d_live_config(profile_path: Path) -> ProcessingLiveConfig:
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"""Build a sar3d live config from the profile's gui.processing.sar3d section.
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RunConfigModel does not carry the GUI section (it belongs to the GUI profile
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layer), so the sar3d defaults are read straight from the profile JSON.
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"""
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payload = json.loads(profile_path.read_text(encoding="utf-8"))
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sar3d = (
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payload.get("gui", {}).get("processing", {}).get("sar3d", {})
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if isinstance(payload, dict)
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else {}
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)
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def _positions(text: str) -> list[int]:
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return [int(value) for value in str(text).split(",") if value.strip()]
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live = ProcessingLiveConfig(processor_mode="sar3d", ignore_socket_speed=True)
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if not isinstance(sar3d, dict) or not sar3d:
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return live
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live.gpr_input_positions = _positions(sar3d.get("input_positions", ""))
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live.gpr_output_positions = _positions(sar3d.get("output_positions", ""))
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live.gpr_min_depth_m = float(sar3d.get("min_depth_m", live.gpr_min_depth_m))
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live.gpr_max_depth_m = float(sar3d.get("max_depth_m", live.gpr_max_depth_m))
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live.gpr_start_freq_mhz = float(sar3d.get("start_freq_mhz", live.gpr_start_freq_mhz))
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live.gpr_stop_freq_mhz = float(sar3d.get("stop_freq_mhz", live.gpr_stop_freq_mhz))
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live.gpr_speed_m_s = float(sar3d.get("speed_m_s", live.gpr_speed_m_s))
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live.gpr_look_angle_deg = float(sar3d.get("look_angle_deg", live.gpr_look_angle_deg))
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live.gpr_direction_sign = float(sar3d.get("direction_sign", live.gpr_direction_sign))
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live.gpr_apply_freq_phase_correction = bool(
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sar3d.get("apply_freq_phase_correction", live.gpr_apply_freq_phase_correction)
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)
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live.sar3d_frame_radius = int(sar3d.get("frame_radius", live.sar3d_frame_radius))
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live.sar3d_edge_frame_weight = float(
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sar3d.get("edge_frame_weight", live.sar3d_edge_frame_weight)
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)
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live.sar3d_pitch_override_enabled = bool(
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sar3d.get("pitch_override_enabled", live.sar3d_pitch_override_enabled)
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)
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live.sar3d_pitch_deg = float(sar3d.get("pitch_deg", live.sar3d_pitch_deg))
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live.sar3d_ground_depth_m = float(sar3d.get("ground_depth_m", live.sar3d_ground_depth_m))
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live.sar3d_x_margin_m = float(sar3d.get("x_margin_m", live.sar3d_x_margin_m))
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live.sar3d_y_min_m = float(sar3d.get("y_min_m", live.sar3d_y_min_m))
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live.sar3d_y_max_m = float(sar3d.get("y_max_m", live.sar3d_y_max_m))
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live.sar3d_voxel_x_m = float(sar3d.get("voxel_x_m", live.sar3d_voxel_x_m))
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live.sar3d_voxel_y_m = float(sar3d.get("voxel_y_m", live.sar3d_voxel_y_m))
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live.sar3d_voxel_z_m = float(sar3d.get("voxel_z_m", live.sar3d_voxel_z_m))
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live.sar3d_norm_edge_margin_m = float(
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sar3d.get("norm_edge_margin_m", live.sar3d_norm_edge_margin_m)
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)
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live.sar3d_smooth_sigma = float(sar3d.get("smooth_sigma", live.sar3d_smooth_sigma))
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live.sar3d_comp_range_power = float(
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sar3d.get("comp_range_power", live.sar3d_comp_range_power)
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)
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live.sar3d_tx_per_segment = int(sar3d.get("tx_per_segment", live.sar3d_tx_per_segment))
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live.sar3d_use_compensation = bool(sar3d.get("use_compensation", live.sar3d_use_compensation))
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live.sar3d_normalize_pairs = bool(sar3d.get("normalize_pairs", live.sar3d_normalize_pairs))
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live.sar3d_bottom_view_deg = float(sar3d.get("bottom_view_deg", live.sar3d_bottom_view_deg))
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return live
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def _check_preprocessor_transparency(
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tap_reader: ShmRingReader, dataset_dir: Path
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) -> bool:
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"""Compare one preprocessed trace against the recorded snapshot's s21."""
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payload = tap_reader.peek_latest_payload()
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if payload is None:
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logger.warning("No preprocessed_tap payload available for transparency check")
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return False
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preprocessed = decode_trace_collection(payload, PREPROC_MAGIC)
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# Any snapshot works: neutral preprocessing is time-invariant, so match the
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# trace against every recorded snapshot and accept the best one.
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trace = preprocessed.traces[0]
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combo_file = f"i{trace.combo.input}_o{trace.combo.output}_s21.npy"
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best_delta = np.inf
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for folder in sorted(p for p in dataset_dir.iterdir() if p.name[:1].isdigit()):
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recorded = np.load(folder / combo_file).astype(np.complex64)
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if recorded.size != np.asarray(trace.s21).size:
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continue
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delta = float(np.max(np.abs(np.asarray(trace.s21) - recorded)))
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best_delta = min(best_delta, delta)
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if best_delta == 0.0:
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break
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logger.info("Preprocessor transparency: max|delta| vs best snapshot = %.3e", best_delta)
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return best_delta < 1e-6
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def main() -> int:
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"""Run the replay pipeline smoke and report pass/fail."""
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parser = argparse.ArgumentParser(description="Headless replay pipeline smoke")
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parser.add_argument(
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"--config",
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type=Path,
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default=PROJECT_ROOT / "run_config_examples/run_config_replay_vna.example.json",
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)
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parser.add_argument("--duration", type=float, default=20.0)
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args = parser.parse_args()
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logging.basicConfig(level=logging.INFO, format="%(levelname)s %(name)s: %(message)s")
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config = RunConfigModel.load_from_path(args.config)
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config.ensure_combos()
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# expanduser: "~/..." dataset paths from machine-portable profiles.
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dataset_dir = Path(config.radar.replay.dataset_dir).expanduser()
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if not dataset_dir.is_dir():
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raise RuntimeError(f"Replay dataset not found: {dataset_dir}")
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config.rings.raw.name = _make_unique_ring_name("radar_raw_replay_smoke")
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config.rings.raw_tap.name = _make_unique_ring_name("radar_raw_tap_replay_smoke")
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config.rings.preprocessed.name = _make_unique_ring_name("radar_preprocessed_replay_smoke")
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config.rings.preprocessed_tap.name = _make_unique_ring_name("radar_preprocessed_tap_replay_smoke")
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config.rings.results.name = _make_unique_ring_name("radar_results_replay_smoke")
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# Private live-config path so the smoke never clobbers the GUI's file.
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live_path = PROJECT_ROOT / "python_app/runtime/processing_live_replay_smoke.json"
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config.runtime.processing_live_config_path = str(
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live_path.relative_to(PROJECT_ROOT)
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)
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radar_key = radar_key_from_config(
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model_name=config.radar.model,
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serial=config.radar.serial,
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sweep_start_hz=config.radar.sweep.start_hz,
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sweep_stop_hz=config.radar.sweep.stop_hz,
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sweep_points=config.radar.sweep.points,
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ifbw_hz=config.radar.sweep.if_bandwidth_hz,
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power_dbm=config.radar.sweep.power_dbm,
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extra_serials=config.radar_key_extra_parts() or None,
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)
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store = NpzStore(PROJECT_ROOT / "python_app/data")
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set_name = config.preprocess.s21.calibration.set_name or "neutral_replay"
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if set_name not in store.list_sets("s21_calibration", radar_key):
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calibration, reference = build_neutral_s21_sets(config)
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store.save_set("s21_calibration", radar_key, set_name, calibration)
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store.save_set("s21_reference", radar_key, set_name, reference)
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logger.info("Created neutral sets '%s' (radar_key=%s)", set_name, radar_key)
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config.preprocess.s21.calibration.set_name = set_name
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config.preprocess.s21.reference.set_name = set_name
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ProcessingLiveConfigWriter(live_path).write(_sar3d_live_config(args.config))
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config_writer = ConfigWriter(PROJECT_ROOT / "python_app/runtime")
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config_writer.prepare_preprocess_bundles(store, radar_key, config)
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config_path = config_writer.write(
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config, PROJECT_ROOT / "python_app/runtime/run_config_replay_smoke.json"
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)
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supervisor = ProcessSupervisor(PROJECT_ROOT)
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result_reader: ShmRingReader | None = None
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tap_reader: ShmRingReader | None = None
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failures: list[str] = []
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try:
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supervisor.start(config_path)
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result_reader = ShmRingReader(config.rings.results.name, open_timeout_s=15.0)
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tap_reader = ShmRingReader(config.rings.preprocessed_tap.name, open_timeout_s=15.0)
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deadline = time.monotonic() + args.duration
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received = 0
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sar3d_results = 0
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last_peak = 0.0
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last_id = 0
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ids_monotonic = True
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while time.monotonic() < deadline:
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result = result_reader.pop_result_collection()
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if result is None:
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time.sleep(0.02)
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continue
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received += 1
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if last_id and result.collection_id <= last_id:
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ids_monotonic = False
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last_id = result.collection_id
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names = {p.processing_name: p for p in result.collection_payloads}
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if "sar3d_proj_xz" in names and "sar3d_proj_bottom" in names:
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sar3d_results += 1
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peak_payload = names.get("sar3d_peak")
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if peak_payload is not None:
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last_peak = float(peak_payload.scalar_value)
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logger.info(
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"Results: total=%d, with sar3d projections=%d, last collection_id=%d, last peak=%.4e",
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received, sar3d_results, last_id, last_peak,
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)
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if received == 0:
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failures.append("no result collections received")
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if sar3d_results == 0:
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failures.append("no sar3d projection payloads received")
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if not (last_peak > 0.0):
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failures.append(f"sar3d peak is not positive: {last_peak}")
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if not ids_monotonic:
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failures.append("collection ids were not monotonically increasing")
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if not _check_preprocessor_transparency(tap_reader, dataset_dir):
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failures.append("preprocessor is not transparent vs recorded snapshots")
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finally:
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supervisor.stop_all()
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if result_reader is not None:
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result_reader.close()
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if tap_reader is not None:
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tap_reader.close()
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if failures:
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for failure in failures:
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logger.error("FAIL: %s", failure)
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return 1
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logger.info("REPLAY SMOKE OK")
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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