583 lines
26 KiB
Python
583 lines
26 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 _read_str(payload: dict[str, Any], key: str, default: str) -> str:
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"""Return payload string, treating an explicit JSON `null` as missing.
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`payload.get(key, default)` returns `None` when the key exists with value
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`null`, which is then coerced into the literal string `"None"` by `str()`.
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"""
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value = payload.get(key, default)
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if value is None:
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return default
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return str(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 = _read_str(payload, "set_name", target.set_name)
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target.bundle_path = _read_str(payload, "bundle_path", target.bundle_path)
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def _load_string_list(payload: dict[str, Any], key: str, context: str) -> list[str]:
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"""Load an optional list of strings with strict shape validation."""
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raw_value = payload.get(key, [])
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if raw_value is None:
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return []
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if not isinstance(raw_value, list):
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raise ValueError(f"{context}.{key} must be a JSON array")
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values: list[str] = []
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for index, item in enumerate(raw_value):
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if not isinstance(item, str):
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raise ValueError(f"{context}.{key}[{index}] must be a JSON string")
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values.append(item)
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return values
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def _load_string_dict(payload: dict[str, Any], key: str, context: str) -> dict[str, str]:
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"""Load an optional string-to-string dictionary with strict shape validation."""
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raw_value = payload.get(key, {})
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if raw_value is None:
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return {}
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if not isinstance(raw_value, dict):
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raise ValueError(f"{context}.{key} must be a JSON object")
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values: dict[str, str] = {}
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for item_key, item_value in raw_value.items():
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if not isinstance(item_key, str) or not isinstance(item_value, str):
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raise ValueError(f"{context}.{key} must contain only string keys and values")
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values[item_key] = item_value
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return values
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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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multi_device_payload = _as_dict(radar_payload.get("multi_device"), "radar.multi_device")
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kamil_adc_payload = _as_dict(radar_payload.get("kamil_adc"), "radar.kamil_adc")
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laser_control_payload = _as_dict(radar_payload.get("laser_control"), "radar.laser_control")
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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.remote_host = str(radar_payload.get("remote_host", model.radar.remote_host))
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model.radar.remote_port = int(radar_payload.get("remote_port", model.radar.remote_port))
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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.visa_library = str(radar_payload.get("visa_library", model.radar.visa_library))
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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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slave_serials_payload = multi_device_payload.get(
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"slave_serials",
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multi_device_payload.get("slave_serial_numbers", model.radar.multi_device.slave_serials),
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)
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if isinstance(slave_serials_payload, list):
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model.radar.multi_device.slave_serials = [str(value).strip() for value in slave_serials_payload if str(value).strip()]
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elif isinstance(slave_serials_payload, str):
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model.radar.multi_device.slave_serials = [
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value.strip()
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for value in slave_serials_payload.split(",")
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if value.strip()
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]
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model.radar.multi_device.force_external_reference = bool(
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multi_device_payload.get(
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"force_external_reference",
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model.radar.multi_device.force_external_reference,
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)
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)
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model.radar.multi_device.recovery_attempts = int(
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multi_device_payload.get(
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"recovery_attempts",
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model.radar.multi_device.recovery_attempts,
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)
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)
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model.radar.kamil_adc.project_dir = str(
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kamil_adc_payload.get("project_dir", model.radar.kamil_adc.project_dir)
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)
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model.radar.kamil_adc.executable_path = str(
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kamil_adc_payload.get("executable_path", model.radar.kamil_adc.executable_path)
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)
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model.radar.kamil_adc.tty_path = str(
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kamil_adc_payload.get("tty_path", model.radar.kamil_adc.tty_path)
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)
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model.radar.kamil_adc.args = _load_string_list(kamil_adc_payload, "args", "radar.kamil_adc")
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model.radar.kamil_adc.env = _load_string_dict(kamil_adc_payload, "env", "radar.kamil_adc")
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model.radar.kamil_adc.startup_timeout_s = float(
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kamil_adc_payload.get("startup_timeout_s", model.radar.kamil_adc.startup_timeout_s)
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)
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model.radar.kamil_adc.sweep_timeout_s = float(
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kamil_adc_payload.get("sweep_timeout_s", model.radar.kamil_adc.sweep_timeout_s)
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)
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model.radar.kamil_adc.stop_timeout_s = float(
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kamil_adc_payload.get("stop_timeout_s", model.radar.kamil_adc.stop_timeout_s)
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)
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model.radar.laser_control.enabled = bool(
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laser_control_payload.get("enabled", model.radar.laser_control.enabled)
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)
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model.radar.laser_control.port = str(
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laser_control_payload.get("port", model.radar.laser_control.port)
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)
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model.radar.laser_control.mode = str(
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laser_control_payload.get("mode", model.radar.laser_control.mode)
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)
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model.radar.laser_control.pi_coeff1_p = int(
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laser_control_payload.get("pi_coeff1_p", model.radar.laser_control.pi_coeff1_p)
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)
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model.radar.laser_control.pi_coeff1_i = int(
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laser_control_payload.get("pi_coeff1_i", model.radar.laser_control.pi_coeff1_i)
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)
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model.radar.laser_control.pi_coeff2_p = int(
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laser_control_payload.get("pi_coeff2_p", model.radar.laser_control.pi_coeff2_p)
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)
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model.radar.laser_control.pi_coeff2_i = int(
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laser_control_payload.get("pi_coeff2_i", model.radar.laser_control.pi_coeff2_i)
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)
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laser_manual_payload = _as_dict(laser_control_payload.get("manual"), "radar.laser_control.manual")
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model.radar.laser_control.manual.temp1 = float(
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laser_manual_payload.get("temp1", model.radar.laser_control.manual.temp1)
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)
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model.radar.laser_control.manual.temp2 = float(
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laser_manual_payload.get("temp2", model.radar.laser_control.manual.temp2)
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)
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model.radar.laser_control.manual.current1 = float(
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laser_manual_payload.get("current1", model.radar.laser_control.manual.current1)
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)
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model.radar.laser_control.manual.current2 = float(
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laser_manual_payload.get("current2", model.radar.laser_control.manual.current2)
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)
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laser_variation_payload = _as_dict(
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laser_control_payload.get("variation"),
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"radar.laser_control.variation",
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)
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model.radar.laser_control.variation.variation_type = str(
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laser_variation_payload.get(
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"variation_type",
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model.radar.laser_control.variation.variation_type,
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)
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)
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model.radar.laser_control.variation.static_temp1 = float(
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laser_variation_payload.get(
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"static_temp1",
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model.radar.laser_control.variation.static_temp1,
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)
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)
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model.radar.laser_control.variation.static_temp2 = float(
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laser_variation_payload.get(
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"static_temp2",
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model.radar.laser_control.variation.static_temp2,
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)
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)
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model.radar.laser_control.variation.static_current1 = float(
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laser_variation_payload.get(
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"static_current1",
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model.radar.laser_control.variation.static_current1,
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)
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)
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model.radar.laser_control.variation.static_current2 = float(
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laser_variation_payload.get(
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"static_current2",
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model.radar.laser_control.variation.static_current2,
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)
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)
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model.radar.laser_control.variation.min_value = float(
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laser_variation_payload.get("min_value", model.radar.laser_control.variation.min_value)
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)
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model.radar.laser_control.variation.max_value = float(
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laser_variation_payload.get("max_value", model.radar.laser_control.variation.max_value)
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)
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model.radar.laser_control.variation.step = float(
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laser_variation_payload.get("step", model.radar.laser_control.variation.step)
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)
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model.radar.laser_control.variation.time_step = int(
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laser_variation_payload.get("time_step", model.radar.laser_control.variation.time_step)
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)
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model.radar.laser_control.variation.delay_time = int(
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laser_variation_payload.get("delay_time", model.radar.laser_control.variation.delay_time)
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)
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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.apply_device_model_constraints()
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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.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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y_m=float(entry_payload.get("y_m", 0.0)),
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z_m=float(entry_payload.get("z_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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y_m=float(entry_payload.get("y_m", 0.0)),
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z_m=float(entry_payload.get("z_m", 0.0)),
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)
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)
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model.apply_device_model_constraints()
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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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sweep_payload = {
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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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"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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if not model.is_kamil_adc:
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sweep_payload["points"] = model.radar.sweep.points
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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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"remote_host": model.radar.remote_host,
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"remote_port": model.radar.remote_port,
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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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"visa_library": model.radar.visa_library,
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"multi_device": {
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"slave_serials": list(model.radar.multi_device.slave_serials),
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"force_external_reference": model.radar.multi_device.force_external_reference,
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"recovery_attempts": model.radar.multi_device.recovery_attempts,
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},
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"kamil_adc": {
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"project_dir": model.radar.kamil_adc.project_dir,
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"executable_path": model.radar.kamil_adc.executable_path,
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"tty_path": model.radar.kamil_adc.tty_path,
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"args": list(model.radar.kamil_adc.args),
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"env": dict(model.radar.kamil_adc.env),
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"startup_timeout_s": model.radar.kamil_adc.startup_timeout_s,
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"sweep_timeout_s": model.radar.kamil_adc.sweep_timeout_s,
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"stop_timeout_s": model.radar.kamil_adc.stop_timeout_s,
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},
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"laser_control": {
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"enabled": model.radar.laser_control.enabled,
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"port": model.radar.laser_control.port,
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"mode": model.radar.laser_control.mode,
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"pi_coeff1_p": model.radar.laser_control.pi_coeff1_p,
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"pi_coeff1_i": model.radar.laser_control.pi_coeff1_i,
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"pi_coeff2_p": model.radar.laser_control.pi_coeff2_p,
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"pi_coeff2_i": model.radar.laser_control.pi_coeff2_i,
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"manual": {
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"temp1": model.radar.laser_control.manual.temp1,
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"temp2": model.radar.laser_control.manual.temp2,
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"current1": model.radar.laser_control.manual.current1,
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"current2": model.radar.laser_control.manual.current2,
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},
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"variation": {
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"variation_type": model.radar.laser_control.variation.variation_type,
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"static_temp1": model.radar.laser_control.variation.static_temp1,
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"static_temp2": model.radar.laser_control.variation.static_temp2,
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"static_current1": model.radar.laser_control.variation.static_current1,
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"static_current2": model.radar.laser_control.variation.static_current2,
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"min_value": model.radar.laser_control.variation.min_value,
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"max_value": model.radar.laser_control.variation.max_value,
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"step": model.radar.laser_control.variation.step,
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"time_step": model.radar.laser_control.variation.time_step,
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"delay_time": model.radar.laser_control.variation.delay_time,
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},
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},
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"sweep": sweep_payload,
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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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|
"port2": {
|
|
"name": model.input_switch.name,
|
|
"driver_mode": model.input_switch.driver_mode,
|
|
"driver": model.input_switch.driver,
|
|
"radar_port": model.input_switch.radar_port,
|
|
"positions": model.input_switch.positions,
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|
"default_position": model.input_switch.default_position,
|
|
"gpio_chip": model.input_switch.gpio_chip,
|
|
"pin_a": model.input_switch.pin_a,
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|
"pin_b": model.input_switch.pin_b,
|
|
"invert_logic": model.input_switch.invert_logic,
|
|
},
|
|
},
|
|
"run": {
|
|
"settling_ms": model.runtime.settling_ms,
|
|
"idle_sleep_ms": model.runtime.idle_sleep_ms,
|
|
"continuous": model.runtime.continuous,
|
|
"processing_live_config_path": model.runtime.processing_live_config_path,
|
|
"locator_server": {
|
|
"device_id": model.runtime.locator_server.device_id,
|
|
"protocol_version": model.runtime.locator_server.protocol_version,
|
|
"host": model.runtime.locator_server.host,
|
|
"port": model.runtime.locator_server.port,
|
|
"max_payload_bytes": model.runtime.locator_server.max_payload_bytes,
|
|
"client_queue_size": model.runtime.locator_server.client_queue_size,
|
|
"logger_name": model.runtime.locator_server.logger_name,
|
|
},
|
|
"combos": [{"input": combo.input, "output": combo.output} for combo in model.combos],
|
|
},
|
|
"preprocess": {
|
|
"s21": {
|
|
"calibration": {
|
|
"set_name": model.preprocess.s21.calibration.set_name,
|
|
"bundle_path": model.preprocess.s21.calibration.bundle_path,
|
|
},
|
|
"reference": {
|
|
"set_name": model.preprocess.s21.reference.set_name,
|
|
"bundle_path": model.preprocess.s21.reference.bundle_path,
|
|
},
|
|
},
|
|
"s11": {
|
|
"calibration": {
|
|
"open": {
|
|
"set_name": model.preprocess.s11.calibration.open.set_name,
|
|
"bundle_path": model.preprocess.s11.calibration.open.bundle_path,
|
|
},
|
|
"short": {
|
|
"set_name": model.preprocess.s11.calibration.short.set_name,
|
|
"bundle_path": model.preprocess.s11.calibration.short.bundle_path,
|
|
},
|
|
"load": {
|
|
"set_name": model.preprocess.s11.calibration.load.set_name,
|
|
"bundle_path": model.preprocess.s11.calibration.load.bundle_path,
|
|
},
|
|
},
|
|
"reference": {
|
|
"set_name": model.preprocess.s11.reference.set_name,
|
|
"bundle_path": model.preprocess.s11.reference.bundle_path,
|
|
},
|
|
},
|
|
"notch": {
|
|
"enabled": model.preprocess.notch.enabled,
|
|
"bands_hz": [[low_hz, high_hz] for low_hz, high_hz in model.preprocess.notch.bands_hz],
|
|
"taper_width_hz": model.preprocess.notch.taper_width_hz,
|
|
"taper_type": model.preprocess.notch.taper_type,
|
|
},
|
|
},
|
|
"gpr": {
|
|
"relative_permittivity": model.gpr.relative_permittivity,
|
|
"tx_geometry": [
|
|
{
|
|
"output_pos": entry.output_pos,
|
|
"x_m": entry.x_m,
|
|
"y_m": entry.y_m,
|
|
"z_m": entry.z_m,
|
|
}
|
|
for entry in model.gpr.tx_geometry
|
|
],
|
|
"rx_geometry": [
|
|
{
|
|
"input_pos": entry.input_pos,
|
|
"x_m": entry.x_m,
|
|
"y_m": entry.y_m,
|
|
"z_m": entry.z_m,
|
|
}
|
|
for entry in model.gpr.rx_geometry
|
|
],
|
|
},
|
|
"rings": {
|
|
"raw": {
|
|
"name": model.rings.raw.name,
|
|
"capacity": model.rings.raw.capacity,
|
|
"slot_size_bytes": model.rings.raw.slot_size_bytes,
|
|
},
|
|
"raw_tap": {
|
|
"name": model.rings.raw_tap.name,
|
|
"capacity": model.rings.raw_tap.capacity,
|
|
"slot_size_bytes": model.rings.raw_tap.slot_size_bytes,
|
|
},
|
|
"preprocessed": {
|
|
"name": model.rings.preprocessed.name,
|
|
"capacity": model.rings.preprocessed.capacity,
|
|
"slot_size_bytes": model.rings.preprocessed.slot_size_bytes,
|
|
},
|
|
"preprocessed_tap": {
|
|
"name": model.rings.preprocessed_tap.name,
|
|
"capacity": model.rings.preprocessed_tap.capacity,
|
|
"slot_size_bytes": model.rings.preprocessed_tap.slot_size_bytes,
|
|
},
|
|
"results": {
|
|
"name": model.rings.results.name,
|
|
"capacity": model.rings.results.capacity,
|
|
"slot_size_bytes": model.rings.results.slot_size_bytes,
|
|
},
|
|
},
|
|
}
|