351 lines
15 KiB
Python
351 lines
15 KiB
Python
"""Encoding and decoding logic for :mod:`python_app.models.run_config_schema`."""
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from __future__ import annotations
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from typing import Any
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from python_app.models.run_config_schema import (
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ComboModel,
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GprRxGeometryModel,
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GprTxGeometryModel,
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PreprocessAssetModel,
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PreprocessNotchModel,
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RunConfigModel,
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)
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from python_app.models.run_config_validation import load_ring_payload, load_switch_payload, validate_gpr_model
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def _as_dict(value: Any, context: str) -> dict[str, Any]:
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"""Validate payload node is object-like, treating missing values as empty object."""
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if value is None:
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return {}
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if not isinstance(value, dict):
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raise ValueError(f"{context} must be a JSON object")
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return value
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def _load_preprocess_asset(payload: dict[str, Any], target: PreprocessAssetModel) -> None:
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"""Load preprocess asset fields into target model."""
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target.set_name = str(payload.get("set_name", target.set_name))
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target.bundle_path = str(payload.get("bundle_path", target.bundle_path))
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def run_config_from_dict(payload: dict[str, Any]) -> RunConfigModel:
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"""Decode JSON-like payload into :class:`RunConfigModel`."""
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# Schema carries only minimal-safe fallbacks; operational defaults live in run_config.json.
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model = RunConfigModel()
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radar_payload = _as_dict(payload.get("radar"), "radar")
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sweep_payload = _as_dict(radar_payload.get("sweep"), "radar.sweep")
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switches_payload = _as_dict(payload.get("switches"), "switches")
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port1_payload = _as_dict(switches_payload.get("port1"), "switches.port1")
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port2_payload = _as_dict(switches_payload.get("port2"), "switches.port2")
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run_payload = _as_dict(payload.get("run"), "run")
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preprocess_payload = _as_dict(payload.get("preprocess"), "preprocess")
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gpr_payload = _as_dict(payload.get("gpr"), "gpr")
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rings_payload = _as_dict(payload.get("rings"), "rings")
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raw_ring_payload = _as_dict(rings_payload.get("raw"), "rings.raw")
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raw_tap_ring_payload = _as_dict(rings_payload.get("raw_tap"), "rings.raw_tap")
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pre_ring_payload = _as_dict(rings_payload.get("preprocessed"), "rings.preprocessed")
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pre_tap_ring_payload = _as_dict(rings_payload.get("preprocessed_tap"), "rings.preprocessed_tap")
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result_ring_payload = _as_dict(rings_payload.get("results"), "rings.results")
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locator_server_payload = _as_dict(
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run_payload.get("locator_server", run_payload.get("locator")),
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"run.locator_server",
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)
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model.radar.model = str(radar_payload.get("model", model.radar.model))
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model.radar.serial = str(radar_payload.get("serial", model.radar.serial))
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model.radar.driver_mode = str(radar_payload.get("driver_mode", model.radar.driver_mode))
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model.radar.mock_signal_hz = float(radar_payload.get("mock_signal_hz", model.radar.mock_signal_hz))
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model.radar.sweep.start_hz = float(sweep_payload.get("start_hz", model.radar.sweep.start_hz))
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model.radar.sweep.stop_hz = float(sweep_payload.get("stop_hz", model.radar.sweep.stop_hz))
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model.radar.sweep.points = int(sweep_payload.get("points", model.radar.sweep.points))
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model.radar.sweep.if_bandwidth_hz = float(
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sweep_payload.get("if_bandwidth_hz", model.radar.sweep.if_bandwidth_hz)
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)
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model.radar.sweep.power_dbm = float(sweep_payload.get("stimulus_power_dbm", model.radar.sweep.power_dbm))
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load_switch_payload(port1_payload, model.output_switch)
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load_switch_payload(port2_payload, model.input_switch)
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model.runtime.settling_ms = int(run_payload.get("settling_ms", model.runtime.settling_ms))
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model.runtime.idle_sleep_ms = int(run_payload.get("idle_sleep_ms", model.runtime.idle_sleep_ms))
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model.runtime.continuous = bool(run_payload.get("continuous", model.runtime.continuous))
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model.runtime.processing_live_config_path = str(
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run_payload.get("processing_live_config_path", model.runtime.processing_live_config_path)
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)
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model.runtime.locator_server.device_id = int(
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locator_server_payload.get("device_id", model.runtime.locator_server.device_id)
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)
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model.runtime.locator_server.protocol_version = int(
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locator_server_payload.get(
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"protocol_version",
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model.runtime.locator_server.protocol_version,
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)
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)
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model.runtime.locator_server.host = str(
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locator_server_payload.get("host", model.runtime.locator_server.host)
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)
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model.runtime.locator_server.port = int(
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locator_server_payload.get("port", model.runtime.locator_server.port)
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)
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model.runtime.locator_server.max_payload_bytes = int(
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locator_server_payload.get(
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"max_payload_bytes",
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model.runtime.locator_server.max_payload_bytes,
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)
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)
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model.runtime.locator_server.client_queue_size = int(
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locator_server_payload.get(
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"client_queue_size",
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model.runtime.locator_server.client_queue_size,
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)
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)
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model.runtime.locator_server.logger_name = str(
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locator_server_payload.get(
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"logger_name",
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model.runtime.locator_server.logger_name,
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)
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)
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s21_preprocess_payload = _as_dict(preprocess_payload.get("s21"), "preprocess.s21")
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_load_preprocess_asset(
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_as_dict(s21_preprocess_payload.get("calibration"), "preprocess.s21.calibration"),
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model.preprocess.s21.calibration,
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)
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_load_preprocess_asset(
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_as_dict(s21_preprocess_payload.get("reference"), "preprocess.s21.reference"),
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model.preprocess.s21.reference,
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)
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s11_preprocess_payload = _as_dict(preprocess_payload.get("s11"), "preprocess.s11")
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s11_calibration_payload = _as_dict(s11_preprocess_payload.get("calibration"), "preprocess.s11.calibration")
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_load_preprocess_asset(
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_as_dict(s11_calibration_payload.get("open"), "preprocess.s11.calibration.open"),
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model.preprocess.s11.calibration.open,
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)
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_load_preprocess_asset(
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_as_dict(s11_calibration_payload.get("short"), "preprocess.s11.calibration.short"),
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model.preprocess.s11.calibration.short,
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)
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_load_preprocess_asset(
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_as_dict(s11_calibration_payload.get("load"), "preprocess.s11.calibration.load"),
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model.preprocess.s11.calibration.load,
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)
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_load_preprocess_asset(
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_as_dict(s11_preprocess_payload.get("reference"), "preprocess.s11.reference"),
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model.preprocess.s11.reference,
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)
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notch_payload = _as_dict(preprocess_payload.get("notch"), "preprocess.notch")
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model.preprocess.notch = PreprocessNotchModel(
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enabled=bool(notch_payload.get("enabled", model.preprocess.notch.enabled)),
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taper_width_hz=float(notch_payload.get("taper_width_hz", model.preprocess.notch.taper_width_hz)),
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taper_type=str(notch_payload.get("taper_type", model.preprocess.notch.taper_type)),
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bands_hz=[],
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)
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bands_payload = notch_payload.get("bands_hz", [])
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if isinstance(bands_payload, list):
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for band in bands_payload:
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if isinstance(band, (list, tuple)) and len(band) == 2:
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model.preprocess.notch.bands_hz.append((float(band[0]), float(band[1])))
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model.gpr.mode = str(gpr_payload.get("mode", model.gpr.mode))
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model.gpr.relative_permittivity = float(
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gpr_payload.get("relative_permittivity", model.gpr.relative_permittivity)
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)
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model.gpr.tx_geometry = []
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tx_geometry_payload = gpr_payload.get("tx_geometry", [])
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if isinstance(tx_geometry_payload, list):
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for entry in tx_geometry_payload:
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entry_payload = _as_dict(entry, "gpr.tx_geometry[]")
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model.gpr.tx_geometry.append(
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GprTxGeometryModel(
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output_pos=int(entry_payload.get("output_pos", 0)),
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x_m=float(entry_payload.get("x_m", 0.0)),
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)
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)
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model.gpr.rx_geometry = []
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rx_geometry_payload = gpr_payload.get("rx_geometry", [])
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if isinstance(rx_geometry_payload, list):
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for entry in rx_geometry_payload:
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entry_payload = _as_dict(entry, "gpr.rx_geometry[]")
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model.gpr.rx_geometry.append(
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GprRxGeometryModel(
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input_pos=int(entry_payload.get("input_pos", 0)),
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x_m=float(entry_payload.get("x_m", 0.0)),
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)
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)
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validate_gpr_model(
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model.gpr,
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input_switch_positions=model.input_switch.positions,
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output_switch_positions=model.output_switch.positions,
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)
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load_ring_payload(raw_ring_payload, model.rings.raw)
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load_ring_payload(raw_tap_ring_payload, model.rings.raw_tap)
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load_ring_payload(pre_ring_payload, model.rings.preprocessed)
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load_ring_payload(pre_tap_ring_payload, model.rings.preprocessed_tap)
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load_ring_payload(result_ring_payload, model.rings.results)
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combos_payload = run_payload.get("combos", [])
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model.combos = []
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if isinstance(combos_payload, list):
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for combo in combos_payload:
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combo_payload = _as_dict(combo, "run.combos[]")
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model.combos.append(
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ComboModel(
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input=int(combo_payload.get("input", 0)),
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output=int(combo_payload.get("output", 0)),
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)
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)
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model.ensure_combos()
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return model
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def run_config_to_dict(model: RunConfigModel) -> dict[str, Any]:
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"""Encode :class:`RunConfigModel` to C++ pipeline-compatible JSON structure."""
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model.ensure_combos()
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return {
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"radar": {
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"model": model.radar.model,
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"serial": model.radar.serial,
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"driver_mode": model.radar.driver_mode,
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"mock_signal_hz": model.radar.mock_signal_hz,
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"sweep": {
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"start_hz": model.radar.sweep.start_hz,
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"stop_hz": model.radar.sweep.stop_hz,
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"points": model.radar.sweep.points,
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"if_bandwidth_hz": model.radar.sweep.if_bandwidth_hz,
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"stimulus_power_dbm": model.radar.sweep.power_dbm,
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},
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},
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"switches": {
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"port1": {
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"name": model.output_switch.name,
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"driver_mode": model.output_switch.driver_mode,
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"driver": model.output_switch.driver,
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"radar_port": model.output_switch.radar_port,
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"positions": model.output_switch.positions,
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"default_position": model.output_switch.default_position,
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"gpio_chip": model.output_switch.gpio_chip,
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"pin_a": model.output_switch.pin_a,
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"pin_b": model.output_switch.pin_b,
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"invert_logic": model.output_switch.invert_logic,
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},
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"port2": {
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"name": model.input_switch.name,
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"driver_mode": model.input_switch.driver_mode,
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"driver": model.input_switch.driver,
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"radar_port": model.input_switch.radar_port,
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"positions": model.input_switch.positions,
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"default_position": model.input_switch.default_position,
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"gpio_chip": model.input_switch.gpio_chip,
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"pin_a": model.input_switch.pin_a,
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"pin_b": model.input_switch.pin_b,
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"invert_logic": model.input_switch.invert_logic,
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},
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},
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"run": {
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"settling_ms": model.runtime.settling_ms,
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"idle_sleep_ms": model.runtime.idle_sleep_ms,
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"continuous": model.runtime.continuous,
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"processing_live_config_path": model.runtime.processing_live_config_path,
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"locator_server": {
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"device_id": model.runtime.locator_server.device_id,
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"protocol_version": model.runtime.locator_server.protocol_version,
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"host": model.runtime.locator_server.host,
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"port": model.runtime.locator_server.port,
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"max_payload_bytes": model.runtime.locator_server.max_payload_bytes,
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"client_queue_size": model.runtime.locator_server.client_queue_size,
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"logger_name": model.runtime.locator_server.logger_name,
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},
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"combos": [{"input": combo.input, "output": combo.output} for combo in model.combos],
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},
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"preprocess": {
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"s21": {
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"calibration": {
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"set_name": model.preprocess.s21.calibration.set_name,
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"bundle_path": model.preprocess.s21.calibration.bundle_path,
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},
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"reference": {
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"set_name": model.preprocess.s21.reference.set_name,
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"bundle_path": model.preprocess.s21.reference.bundle_path,
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},
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},
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"s11": {
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"calibration": {
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"open": {
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"set_name": model.preprocess.s11.calibration.open.set_name,
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"bundle_path": model.preprocess.s11.calibration.open.bundle_path,
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},
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"short": {
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"set_name": model.preprocess.s11.calibration.short.set_name,
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"bundle_path": model.preprocess.s11.calibration.short.bundle_path,
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},
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"load": {
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"set_name": model.preprocess.s11.calibration.load.set_name,
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"bundle_path": model.preprocess.s11.calibration.load.bundle_path,
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},
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},
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"reference": {
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"set_name": model.preprocess.s11.reference.set_name,
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"bundle_path": model.preprocess.s11.reference.bundle_path,
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},
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},
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"notch": {
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"enabled": model.preprocess.notch.enabled,
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"bands_hz": [[low_hz, high_hz] for low_hz, high_hz in model.preprocess.notch.bands_hz],
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"taper_width_hz": model.preprocess.notch.taper_width_hz,
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"taper_type": model.preprocess.notch.taper_type,
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},
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},
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"gpr": {
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"mode": model.gpr.mode,
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"relative_permittivity": model.gpr.relative_permittivity,
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"tx_geometry": [
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{
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"output_pos": entry.output_pos,
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"x_m": entry.x_m,
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}
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for entry in model.gpr.tx_geometry
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],
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"rx_geometry": [
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{
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"input_pos": entry.input_pos,
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"x_m": entry.x_m,
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}
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for entry in model.gpr.rx_geometry
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],
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},
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"rings": {
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"raw": {
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"name": model.rings.raw.name,
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"capacity": model.rings.raw.capacity,
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"slot_size_bytes": model.rings.raw.slot_size_bytes,
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},
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"raw_tap": {
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"name": model.rings.raw_tap.name,
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"capacity": model.rings.raw_tap.capacity,
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"slot_size_bytes": model.rings.raw_tap.slot_size_bytes,
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},
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"preprocessed": {
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"name": model.rings.preprocessed.name,
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"capacity": model.rings.preprocessed.capacity,
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"slot_size_bytes": model.rings.preprocessed.slot_size_bytes,
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},
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"preprocessed_tap": {
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"name": model.rings.preprocessed_tap.name,
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"capacity": model.rings.preprocessed_tap.capacity,
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"slot_size_bytes": model.rings.preprocessed_tap.slot_size_bytes,
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},
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"results": {
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"name": model.rings.results.name,
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"capacity": model.rings.results.capacity,
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"slot_size_bytes": model.rings.results.slot_size_bytes,
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},
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},
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}
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