Lab043: add hardware diagnostics and HackRF comparison tools
This commit is contained in:
LittleSam129
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experiments/lab043_hackrf_continuity.py
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618
experiments/lab043_hackrf_continuity.py
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"""Однотонная проверка непрерывности HackRF RX для Lab043.
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Разрешён ровно один непрерывный комплексный тон Pluto+ +50 кГц. Здесь нет
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BPSK, PRBS, пакетов, JPEG и HackRF TX.
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"""
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from __future__ import annotations
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import argparse
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import hashlib
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import json
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import math
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import threading
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import time
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from dataclasses import asdict, dataclass
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from datetime import datetime, timezone
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from pathlib import Path
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import numpy as np
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from experiments import lab043_hackrf_hardware as hackrf
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from experiments import lab043_pluto_to_rtlsdr as lab043
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from experiments import lab043_prbs11_hardware as rtl_hardware
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TONE_OFFSET_HZ = 50_000.0
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TONE_AMPLITUDE = 0.35
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TONE_SECONDS = 5.0
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RX_LEADING_SECONDS = 0.75
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RX_TRAILING_SECONDS = 0.75
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STABLE_EDGE_SECONDS = 0.25
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CYCLIC_PERIOD_COUNT = 4096
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COARSE_FFT_SAMPLES = 262_144
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TONE_MARGIN_THRESHOLD_DB = 10.0
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BOUNDARY_PHASE_THRESHOLD_RAD = 0.25
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LOCAL_PHASE_RMS_LIMIT_RAD = 0.35
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BOUNDARY_SIDE_SAMPLES = 65_536
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LOCAL_PHASE_BLOCK_SAMPLES = 32_768
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LOCAL_PHASE_HOP_SAMPLES = 8_192
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GLOBAL_PHASE_BLOCK_SAMPLES = 262_144
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GLOBAL_PHASE_HOP_SAMPLES = 65_536
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TRANSITION_BLOCK_SAMPLES = 16_384
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TRANSITION_HOP_SAMPLES = 512
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RAW_DIRECTORY = Path("data/raw/lab043_hackrf")
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@dataclass(frozen=True)
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class TonePhaseFit:
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frequency_hz: float
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phase_at_reference_rad: float
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phase_fit_rms_rad: float
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maximum_phase_error_rad: float
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projection_count: int
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def build_periodic_tone(actual_sample_rate_hz: float) -> tuple[np.ndarray, float]:
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"""Построить циклически непрерывный тон около +50 кГц."""
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samples_per_cycle = int(round(actual_sample_rate_hz / TONE_OFFSET_HZ))
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sample_count = samples_per_cycle * CYCLIC_PERIOD_COUNT
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indexes = np.arange(sample_count, dtype=np.float64)
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tone = TONE_AMPLITUDE * np.exp(
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1j * 2.0 * np.pi * CYCLIC_PERIOD_COUNT * indexes / sample_count
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)
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actual_tone_hz = CYCLIC_PERIOD_COUNT * actual_sample_rate_hz / sample_count
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return tone.astype(np.complex64), float(actual_tone_hz)
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def _phase_projections(
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samples: np.ndarray,
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sample_rate_hz: float,
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coarse_frequency_hz: float,
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global_start_sample: int,
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reference_sample: int,
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block_samples: int,
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hop_samples: int,
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) -> tuple[np.ndarray, np.ndarray]:
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received = np.asarray(samples, dtype=np.complex64)
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if len(received) < block_samples + 2 * hop_samples:
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raise ValueError("Участок слишком короток для фазовой модели")
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window = np.hanning(block_samples).astype(np.float64)
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starts = np.arange(0, len(received) - block_samples + 1, hop_samples)
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projections = np.empty(len(starts), dtype=np.complex128)
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centers = np.empty(len(starts), dtype=np.float64)
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local_indexes = np.arange(block_samples, dtype=np.float64)
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for row, start in enumerate(starts):
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absolute_start = global_start_sample + int(start)
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relative_indexes = absolute_start - reference_sample + local_indexes
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oscillator = np.exp(
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-1j * 2.0 * np.pi * coarse_frequency_hz * relative_indexes / sample_rate_hz
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)
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projections[row] = np.sum(received[start : start + block_samples] * oscillator * window)
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centers[row] = (
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absolute_start + (block_samples - 1) / 2.0 - reference_sample
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) / sample_rate_hz
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return centers, projections
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def fit_tone_phase(
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samples: np.ndarray,
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sample_rate_hz: float,
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coarse_frequency_hz: float,
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global_start_sample: int,
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reference_sample: int,
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block_samples: int,
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hop_samples: int,
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) -> TonePhaseFit:
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"""Оценить частоту и фазу тона, не пересекая неизвестную границу."""
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times, projections = _phase_projections(
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samples,
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sample_rate_hz,
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coarse_frequency_hz,
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global_start_sample,
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reference_sample,
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block_samples,
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hop_samples,
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)
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phases = np.unwrap(np.angle(projections))
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weights = np.abs(projections) ** 2
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design = np.column_stack((np.ones(len(times)), times))
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root_weights = np.sqrt(weights / max(float(np.max(weights)), 1e-30))
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coefficients, *_ = np.linalg.lstsq(
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design * root_weights[:, None], phases * root_weights, rcond=None
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)
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fitted = design @ coefficients
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residuals = phases - fitted
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weight_sum = max(float(np.sum(weights)), 1e-30)
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rms = math.sqrt(float(np.sum(weights * residuals**2)) / weight_sum)
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return TonePhaseFit(
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frequency_hz=float(coarse_frequency_hz + coefficients[1] / (2.0 * np.pi)),
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phase_at_reference_rad=float(np.angle(np.exp(1j * coefficients[0]))),
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phase_fit_rms_rad=float(rms),
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maximum_phase_error_rad=float(np.max(np.abs(residuals))),
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projection_count=int(len(projections)),
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)
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def estimate_coarse_tone(
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samples: np.ndarray,
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sample_rate_hz: float,
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fft_samples: int = COARSE_FFT_SAMPLES,
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) -> dict:
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"""Найти единственный тон около |50 кГц| по усреднённому спектру."""
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received = np.asarray(samples, dtype=np.complex64)
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if len(received) < fft_samples:
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raise ValueError("Недостаточно отсчётов для фиксированного спектрального окна")
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window = np.hanning(fft_samples).astype(np.float64)
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accumulated = np.zeros(fft_samples, dtype=np.float64)
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segment_count = len(received) // fft_samples
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for index in range(segment_count):
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segment = received[index * fft_samples : (index + 1) * fft_samples]
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spectrum = np.fft.fft(segment * window)
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accumulated += np.abs(spectrum) ** 2
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powers = accumulated / segment_count
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frequencies = np.fft.fftfreq(fft_samples, d=1.0 / sample_rate_hz)
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search = (np.abs(frequencies) >= 35_000.0) & (np.abs(frequencies) <= 65_000.0)
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candidate_indexes = np.flatnonzero(search)
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peak_index = int(candidate_indexes[np.argmax(powers[candidate_indexes])])
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peak_frequency = float(frequencies[peak_index])
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local_noise = search & (np.abs(frequencies - peak_frequency) >= 2_000.0)
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noise_floor = float(np.median(powers[local_noise]))
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margin_db = 10.0 * math.log10(float(powers[peak_index]) / max(noise_floor, 1e-30))
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resolution_hz = sample_rate_hz / fft_samples
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left = (peak_index - 1) % fft_samples
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right = (peak_index + 1) % fft_samples
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y0, y1, y2 = np.log(np.maximum(powers[[left, peak_index, right]], 1e-300))
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denominator = y0 - 2.0 * y1 + y2
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offset_bins = 0.0 if abs(denominator) < 1e-18 else 0.5 * (y0 - y2) / denominator
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refined = peak_frequency + float(offset_bins) * resolution_hz
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return {
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"frequency_hz": float(refined),
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"peak_bin_frequency_hz": peak_frequency,
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"tone_above_noise_db": float(margin_db),
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"noise_floor_power": noise_floor,
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"fft_resolution_hz": float(resolution_hz),
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"fft_segment_count": int(segment_count),
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"credible": bool(margin_db >= TONE_MARGIN_THRESHOLD_DB),
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}
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def _wrap_phase(value: float) -> float:
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return float(np.angle(np.exp(1j * value)))
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def _transition_offset(
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samples: np.ndarray,
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sample_rate_hz: float,
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coarse_frequency_hz: float,
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global_start_sample: int,
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boundary_sample: int,
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before_fit: TonePhaseFit,
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jump_rad: float,
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) -> dict:
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times, projections = _phase_projections(
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samples,
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sample_rate_hz,
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coarse_frequency_hz,
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global_start_sample,
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boundary_sample,
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TRANSITION_BLOCK_SAMPLES,
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TRANSITION_HOP_SAMPLES,
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)
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before_model = before_fit.phase_at_reference_rad + 2.0 * np.pi * (
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before_fit.frequency_hz - coarse_frequency_hz
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) * times
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residual = np.unwrap(np.angle(projections * np.exp(-1j * before_model)))
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kernel = np.ones(9, dtype=np.float64) / 9.0
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smoothed = np.convolve(residual, kernel, mode="same")
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guard = 4
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usable = slice(guard, len(times) - guard)
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target = jump_rad / 2.0
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local_index = int(np.argmin(np.abs(smoothed[usable] - target))) + guard
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return {
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"transition_offset_samples": float(times[local_index] * sample_rate_hz),
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"transition_resolution_samples": TRANSITION_HOP_SAMPLES,
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"transition_window_half_width_samples": TRANSITION_BLOCK_SAMPLES // 2,
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}
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def analyze_callback_boundaries(
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samples: np.ndarray,
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boundaries: tuple[hackrf.HackrfBoundary, ...],
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sample_rate_hz: float,
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coarse_frequency_hz: float,
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stable_start_sample: int,
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stable_end_sample: int,
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side_samples: int = BOUNDARY_SIDE_SAMPLES,
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block_samples: int = LOCAL_PHASE_BLOCK_SAMPLES,
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hop_samples: int = LOCAL_PHASE_HOP_SAMPLES,
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) -> tuple[list[dict], dict]:
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rows: list[dict] = []
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for boundary in boundaries:
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sample = int(boundary.accepted_end_sample)
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if sample - side_samples < stable_start_sample or sample + side_samples > stable_end_sample:
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continue
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before = fit_tone_phase(
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samples[sample - side_samples : sample],
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sample_rate_hz,
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coarse_frequency_hz,
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sample - side_samples,
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sample,
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block_samples,
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hop_samples,
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)
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after = fit_tone_phase(
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samples[sample : sample + side_samples],
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sample_rate_hz,
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coarse_frequency_hz,
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sample,
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sample,
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block_samples,
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hop_samples,
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)
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jump = _wrap_phase(after.phase_at_reference_rad - before.phase_at_reference_rad)
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credible = bool(
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before.phase_fit_rms_rad <= LOCAL_PHASE_RMS_LIMIT_RAD
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and after.phase_fit_rms_rad <= LOCAL_PHASE_RMS_LIMIT_RAD
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)
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confirmed = bool(credible and abs(jump) > BOUNDARY_PHASE_THRESHOLD_RAD)
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mean_frequency = 0.5 * (before.frequency_hz + after.frequency_hz)
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phase_per_sample = 2.0 * np.pi * mean_frequency / sample_rate_hz
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period_samples = sample_rate_hz / abs(mean_frequency)
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equivalent_shift = jump / phase_per_sample
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row = {
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"callback_index": boundary.callback_index,
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"boundary_sample": sample,
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"buffer_length_bytes": boundary.buffer_length,
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"valid_length_bytes": boundary.valid_bytes,
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"complex_samples_in_callback": boundary.valid_bytes // 2,
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"callback_duration_seconds": boundary.valid_bytes / (2.0 * sample_rate_hz),
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"frequency_before_hz": before.frequency_hz,
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"frequency_after_hz": after.frequency_hz,
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"phase_before_at_boundary_rad": before.phase_at_reference_rad,
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"phase_after_at_boundary_rad": after.phase_at_reference_rad,
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"expected_phase_per_sample_rad": float(phase_per_sample),
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"additional_phase_jump_rad": jump,
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"before_phase_fit_rms_rad": before.phase_fit_rms_rad,
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"after_phase_fit_rms_rad": after.phase_fit_rms_rad,
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"credible": credible,
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"confirmed_jump": confirmed,
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"equivalent_sample_shift_principal": float(equivalent_shift),
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"tone_period_samples": float(period_samples),
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"equivalent_sample_shift_ambiguity": "principal + k * tone_period_samples",
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}
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if confirmed:
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transition_radius = 2 * TRANSITION_BLOCK_SAMPLES
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local_start = sample - transition_radius
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local_end = sample + transition_radius
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transition = _transition_offset(
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samples[local_start:local_end],
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sample_rate_hz,
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coarse_frequency_hz,
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local_start,
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sample,
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before,
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jump,
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)
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row.update(transition)
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uncertainty = transition["transition_window_half_width_samples"]
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offset = transition["transition_offset_samples"]
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row["relation_to_callback_boundary"] = (
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"consistent_with_exact_boundary"
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if abs(offset) <= uncertainty
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else "delayed_after_boundary"
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if offset > uncertainty
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else "before_boundary"
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)
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else:
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row.update(
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{
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"transition_offset_samples": None,
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"transition_resolution_samples": None,
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"transition_window_half_width_samples": None,
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"relation_to_callback_boundary": "no_confirmed_jump",
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}
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)
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rows.append(row)
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credible_count = sum(bool(row["credible"]) for row in rows)
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confirmed_count = sum(bool(row["confirmed_jump"]) for row in rows)
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return rows, {
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"checked_boundary_count": len(rows),
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"credible_boundary_count": credible_count,
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"confirmed_jump_count": confirmed_count,
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"maximum_absolute_jump_rad": float(
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max((abs(row["additional_phase_jump_rad"]) for row in rows), default=float("nan"))
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),
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}
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def analyze_continuity_tone(
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samples: np.ndarray,
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boundaries: tuple[hackrf.HackrfBoundary, ...],
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sample_rate_hz: float,
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stable_start_sample: int,
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stable_end_sample: int,
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) -> dict:
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stable = np.asarray(samples[stable_start_sample:stable_end_sample], dtype=np.complex64)
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coarse = estimate_coarse_tone(stable, sample_rate_hz)
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if not coarse["credible"]:
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return {
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"classification": "D",
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"reason": "Тон не прошёл заранее заданный спектральный порог 10 дБ",
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"coarse_tone": coarse,
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"boundaries": [],
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}
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whole = fit_tone_phase(
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stable,
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sample_rate_hz,
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coarse["frequency_hz"],
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stable_start_sample,
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stable_start_sample,
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GLOBAL_PHASE_BLOCK_SAMPLES,
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GLOBAL_PHASE_HOP_SAMPLES,
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)
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rows, boundary_summary = analyze_callback_boundaries(
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samples,
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boundaries,
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sample_rate_hz,
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coarse["frequency_hz"],
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stable_start_sample,
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stable_end_sample,
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)
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thirds = []
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edges = np.linspace(stable_start_sample, stable_end_sample, 4, dtype=int)
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for index in range(3):
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start, end = int(edges[index]), int(edges[index + 1])
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fit = fit_tone_phase(
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samples[start:end],
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sample_rate_hz,
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coarse["frequency_hz"],
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start,
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start,
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GLOBAL_PHASE_BLOCK_SAMPLES,
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GLOBAL_PHASE_HOP_SAMPLES,
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)
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thirds.append(
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{
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"section": index + 1,
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"start_sample": start,
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"end_sample": end,
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**asdict(fit),
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}
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)
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centers = np.asarray(
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[0.5 * (row["start_sample"] + row["end_sample"]) / sample_rate_hz for row in thirds]
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)
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frequencies = np.asarray([row["frequency_hz"] for row in thirds])
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drift_hz_per_second = float(np.polyfit(centers, frequencies, 1)[0])
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required_credible = max(10, math.ceil(0.8 * len(rows)))
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if len(rows) == 0 or boundary_summary["credible_boundary_count"] < required_credible:
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classification = "D"
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reason = "Локальная фазовая точность недостаточна для решения о непрерывности"
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elif boundary_summary["confirmed_jump_count"]:
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classification = "B"
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reason = "Подтверждены реальные фазовые скачки в непрерывном HackRF RX"
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else:
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classification = "A"
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reason = "Однотонный контроль непрерывен; прежняя двухтональная проверка была недостоверна"
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return {
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"classification": classification,
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"reason": reason,
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"coarse_tone": coarse,
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"stable_start_sample": int(stable_start_sample),
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"stable_end_sample": int(stable_end_sample),
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"stable_sample_count": int(len(stable)),
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"stable_duration_seconds": float(len(stable) / sample_rate_hz),
|
||||
"whole_tone_phase_fit": asdict(whole),
|
||||
"frequency_by_thirds": thirds,
|
||||
"frequency_drift_hz_per_second": drift_hz_per_second,
|
||||
"frequency_span_hz": float(np.ptp(frequencies)),
|
||||
"boundary_summary": boundary_summary,
|
||||
"boundaries": rows,
|
||||
"phase_jump_threshold_rad": BOUNDARY_PHASE_THRESHOLD_RAD,
|
||||
"local_phase_rms_limit_rad": LOCAL_PHASE_RMS_LIMIT_RAD,
|
||||
"software_callback_bug_found": False,
|
||||
}
|
||||
|
||||
|
||||
def _monotonic_to_sample(
|
||||
monotonic_value: float,
|
||||
capture: hackrf.HackrfCapture,
|
||||
sample_rate_hz: float,
|
||||
) -> int:
|
||||
relative = monotonic_value - capture.diagnostics["stream_started_monotonic"]
|
||||
boundary = min(
|
||||
capture.boundaries,
|
||||
key=lambda row: abs(row.monotonic_seconds - relative),
|
||||
)
|
||||
estimate = boundary.accepted_end_sample + round(
|
||||
(relative - boundary.monotonic_seconds) * sample_rate_hz
|
||||
)
|
||||
return int(np.clip(estimate, 0, len(capture.samples)))
|
||||
|
||||
|
||||
def run_one_continuity_tone(raw_directory: Path = RAW_DIRECTORY) -> dict:
|
||||
"""Выполнить ровно один однотоновый опыт и остановиться."""
|
||||
|
||||
pluto_preflight = rtl_hardware.preflight_pluto()
|
||||
hackrf_preflight = hackrf.preflight_hackrf()
|
||||
pluto, tx_parameters = rtl_hardware.configure_pluto()
|
||||
actual_tx_rate = float(tx_parameters["actual_sample_rate_hz"])
|
||||
waveform, actual_tx_tone_hz = build_periodic_tone(actual_tx_rate)
|
||||
device_waveform = lab043.to_pluto_tx_samples(waveform)
|
||||
waveform_sha256 = hashlib.sha256(waveform.tobytes()).hexdigest()
|
||||
target_samples = math.ceil(
|
||||
(RX_LEADING_SECONDS + TONE_SECONDS + RX_TRAILING_SECONDS)
|
||||
* hackrf.HACKRF_SAMPLE_RATE_HZ
|
||||
) + hackrf.HACKRF_EXPECTED_CALLBACK_BYTES // 2
|
||||
capture_started = datetime.now(timezone.utc)
|
||||
capture_holder: list[hackrf.HackrfCapture] = []
|
||||
errors: list[str] = []
|
||||
tx_times: dict[str, float] = {}
|
||||
|
||||
with hackrf.HackrfRxDevice() as receiver:
|
||||
rx_parameters = receiver.configure_rx()
|
||||
|
||||
def receive() -> None:
|
||||
try:
|
||||
capture_holder.append(receiver.capture(target_samples))
|
||||
except Exception as error: # pragma: no cover - аппаратный путь
|
||||
errors.append(f"RX {type(error).__name__}: {error}")
|
||||
|
||||
rx_thread = threading.Thread(target=receive, daemon=True)
|
||||
rx_thread.start()
|
||||
deadline = time.perf_counter() + 5.0
|
||||
while time.perf_counter() < deadline:
|
||||
if receiver.library.hackrf_is_streaming(receiver.device) == 1:
|
||||
break
|
||||
if errors:
|
||||
break
|
||||
time.sleep(0.01)
|
||||
else:
|
||||
raise RuntimeError("HackRF RX не подтвердил непрерывный поток; TX не включён")
|
||||
time.sleep(RX_LEADING_SECONDS)
|
||||
pluto.tx_cyclic_buffer = True
|
||||
pluto.tx_destroy_buffer()
|
||||
try:
|
||||
tx_times["tx_call_started_monotonic"] = time.perf_counter()
|
||||
pluto.tx(device_waveform)
|
||||
tx_times["tx_confirmed_monotonic"] = time.perf_counter()
|
||||
time.sleep(TONE_SECONDS)
|
||||
tx_times["tx_stop_started_monotonic"] = time.perf_counter()
|
||||
finally:
|
||||
pluto.tx_destroy_buffer()
|
||||
tx_times["tx_destroyed_monotonic"] = time.perf_counter()
|
||||
rx_thread.join(timeout=hackrf.HACKRF_STREAM_TIMEOUT_SECONDS + 5.0)
|
||||
if rx_thread.is_alive():
|
||||
raise RuntimeError("Непрерывный поток HackRF не завершился")
|
||||
if errors:
|
||||
raise RuntimeError("; ".join(errors))
|
||||
if len(capture_holder) != 1:
|
||||
raise RuntimeError("HackRF не вернул единственный непрерывный массив")
|
||||
capture = capture_holder[0]
|
||||
stable_start = _monotonic_to_sample(
|
||||
tx_times["tx_confirmed_monotonic"] + STABLE_EDGE_SECONDS,
|
||||
capture,
|
||||
hackrf.HACKRF_SAMPLE_RATE_HZ,
|
||||
)
|
||||
stable_end = _monotonic_to_sample(
|
||||
tx_times["tx_stop_started_monotonic"] - STABLE_EDGE_SECONDS,
|
||||
capture,
|
||||
hackrf.HACKRF_SAMPLE_RATE_HZ,
|
||||
)
|
||||
overload = {
|
||||
"peak_magnitude": float(np.max(np.abs(capture.samples))),
|
||||
"clipped_component_fraction": float(
|
||||
np.mean(
|
||||
(np.abs(capture.samples.real * 128.0) >= 127)
|
||||
| (np.abs(capture.samples.imag * 128.0) >= 127)
|
||||
)
|
||||
),
|
||||
}
|
||||
boundary_rows = [asdict(row) for row in capture.boundaries]
|
||||
metadata = {
|
||||
"experiment": "Lab043 HackRF single-tone continuity",
|
||||
"capture_status": "captured",
|
||||
"processing_status": "pending",
|
||||
"processing_error": None,
|
||||
"capture_started_utc": capture_started.isoformat().replace("+00:00", "Z"),
|
||||
"tx_parameters": tx_parameters,
|
||||
"rx_parameters": rx_parameters | {
|
||||
"serial_number": hackrf_preflight["serial_number"],
|
||||
"firmware_version": hackrf_preflight["firmware_version"],
|
||||
"libhackrf_version": hackrf_preflight["libhackrf_version"],
|
||||
},
|
||||
"pluto_preflight": pluto_preflight,
|
||||
"hackrf_preflight": hackrf_preflight,
|
||||
"physical_scheme": "Pluto+ TX -> SMA -> AT30S 30 dB -> HackRF ANTENNA; antennas removed",
|
||||
"waveform_sha256": waveform_sha256,
|
||||
"waveform": {
|
||||
"kind": "single_complex_tone",
|
||||
"requested_offset_hz": TONE_OFFSET_HZ,
|
||||
"actual_periodic_offset_hz": actual_tx_tone_hz,
|
||||
"amplitude": TONE_AMPLITUDE,
|
||||
"cyclic_buffer_sample_count": len(waveform),
|
||||
"cyclic_period_count": CYCLIC_PERIOD_COUNT,
|
||||
},
|
||||
"tx_waveform_duration_seconds": TONE_SECONDS,
|
||||
"tx_timing": tx_times,
|
||||
"callback_count": capture.diagnostics["callback_count_total"],
|
||||
"callback_boundaries": boundary_rows,
|
||||
"continuous_rx": capture.diagnostics | {"boundaries": boundary_rows},
|
||||
"expected_intervals": {
|
||||
"rx_leading_seconds": RX_LEADING_SECONDS,
|
||||
"tone_seconds": TONE_SECONDS,
|
||||
"rx_trailing_seconds": RX_TRAILING_SECONDS,
|
||||
"stable_edge_seconds": STABLE_EDGE_SECONDS,
|
||||
"stable_start_sample": stable_start,
|
||||
"stable_end_sample": stable_end,
|
||||
},
|
||||
"overload": overload,
|
||||
}
|
||||
stamp = capture_started.strftime("%Y%m%d_%H%M%S")
|
||||
base = raw_directory / f"lab043_hackrf_continuity_tone_{stamp}"
|
||||
iq_path, metadata_path, document = lab043.save_raw_iq_before_processing(
|
||||
base,
|
||||
capture.samples,
|
||||
metadata,
|
||||
)
|
||||
restored = np.load(iq_path, allow_pickle=False)
|
||||
if hashlib.sha256(iq_path.read_bytes()).hexdigest() != document["iq_sha256"]:
|
||||
raise RuntimeError("SHA-256 raw изменился перед анализом")
|
||||
try:
|
||||
analysis = analyze_continuity_tone(
|
||||
restored,
|
||||
capture.boundaries,
|
||||
hackrf.HACKRF_SAMPLE_RATE_HZ,
|
||||
stable_start,
|
||||
stable_end,
|
||||
)
|
||||
except Exception as error:
|
||||
message = f"{type(error).__name__}: {error}"
|
||||
lab043.update_processing_metadata(
|
||||
metadata_path,
|
||||
processing_status="processing_failed",
|
||||
processing_error=message,
|
||||
)
|
||||
return {
|
||||
"iq_path": str(iq_path),
|
||||
"metadata_path": str(metadata_path),
|
||||
"iq_sha256": document["iq_sha256"],
|
||||
"processing_status": "processing_failed",
|
||||
"processing_error": message,
|
||||
}
|
||||
lab043.update_processing_metadata(
|
||||
metadata_path,
|
||||
processing_status="success",
|
||||
processing_error=None,
|
||||
analysis=analysis,
|
||||
)
|
||||
return {
|
||||
"iq_path": str(iq_path),
|
||||
"metadata_path": str(metadata_path),
|
||||
"iq_sha256": document["iq_sha256"],
|
||||
"processing_status": "success",
|
||||
"tx_parameters": tx_parameters,
|
||||
"rx_parameters": metadata["rx_parameters"],
|
||||
"overload": overload,
|
||||
"continuous_rx": capture.diagnostics,
|
||||
"analysis": analysis,
|
||||
}
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--run-one-continuity-tone", action="store_true", required=True)
|
||||
arguments = parser.parse_args()
|
||||
if not arguments.run_one_continuity_tone: # pragma: no cover
|
||||
return 2
|
||||
result = run_one_continuity_tone()
|
||||
print(json.dumps(result, ensure_ascii=False, indent=2))
|
||||
return 0 if result["processing_status"] == "success" else 2
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
raise SystemExit(main())
|
||||
Reference in New Issue
Block a user