Lab046A: validate continuous soft-symbol frame scanning
This commit is contained in:
LittleSam129
@@ -32,11 +32,16 @@ from __future__ import annotations
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import argparse
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import hashlib
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import sys
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from dataclasses import dataclass, replace
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from pathlib import Path
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from typing import Callable
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import numpy as np
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if __package__ in (None, ""):
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sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
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from experiments import lab045_hackrf_bpsk_fec as lab045
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from protocol import image_fragments as fragments
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@@ -49,6 +54,10 @@ DEFAULT_OBJECT_SIZE = 16384 # 16 KiB, ровный размер, не JPEG
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DEFAULT_OBJECT_ID = 0x4C303436 # "L046"
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DEFAULT_OBJECT_SEED = 46
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CONTINUOUS_PREAMBLE_THRESHOLD = 0.80
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DEFAULT_MAX_FRAMES = 256
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DEFAULT_MAX_SEARCH_ITERATIONS = 1024
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# ============================================================ Детерминированный объект
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@@ -421,6 +430,453 @@ def run_object_transport(
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)
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# ============================================================ Lab046A: один continuous soft stream
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def _bits_to_float32_soft(bits: np.ndarray) -> np.ndarray:
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"""Преобразовать BPSK-биты в компактный нормализованный soft stream."""
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values = np.asarray(bits)
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if values.ndim != 1 or not np.all((values == 0) | (values == 1)):
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raise ValueError("bits должны быть одномерной двоичной последовательностью")
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soft = values.astype(np.float32)
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soft *= np.float32(2.0)
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soft -= np.float32(1.0)
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return soft
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def malformed_header_candidate_soft() -> np.ndarray:
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"""Преамбула PRBS7 и намеренно неверная контрольная сумма PHY header."""
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header = lab045.encode_phy_header(lab045.MIN_PACKET_BYTES).copy()
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checksum_bit = lab045.PHY_HEADER_FIELDS_BITS - 1
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first_copy = checksum_bit * lab045.HEADER_REPETITION
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header[first_copy:first_copy + 2] ^= 1
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candidate_bits = np.concatenate((lab045.lab044.preamble_bits(), header))
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return _bits_to_float32_soft(candidate_bits)
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@dataclass(frozen=True)
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class ContinuousSoftStreamPlan:
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"""TX-side описание потока; ``frame_starts`` запрещено передавать scanner-у."""
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soft_symbols: np.ndarray
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frame_plans: tuple[FramePlan, ...]
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frame_starts: tuple[int, ...]
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leading_background_symbols: int
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inter_frame_background_symbols: int
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trailing_background_symbols: int
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malformed_candidate_symbols: int
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noise_sigma: float
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@property
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def total_frame_symbols(self) -> int:
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return sum(frame.plan.frame_symbol_count for frame in self.frame_plans)
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@property
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def frame_waveform_samples(self) -> int:
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return sum(frame.plan.waveform_sample_count for frame in self.frame_plans)
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@property
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def extra_background_samples(self) -> int:
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symbols = (
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self.leading_background_symbols
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+ self.inter_frame_background_symbols
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+ self.trailing_background_symbols
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)
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return symbols * lab045.SAMPLES_PER_SYMBOL
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@property
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def equivalent_total_samples(self) -> int:
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"""Полные Lab045-формы плюс намеренно добавленные фоновые области."""
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auxiliary = self.malformed_candidate_symbols * lab045.SAMPLES_PER_SYMBOL
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return self.frame_waveform_samples + self.extra_background_samples + auxiliary
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@property
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def equivalent_duration_seconds(self) -> float:
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return self.equivalent_total_samples / lab045.SAMPLE_RATE_HZ
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def build_continuous_soft_stream(
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frame_plans: list[FramePlan] | tuple[FramePlan, ...],
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*,
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leading_background_symbols: int = 0,
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inter_frame_background: dict[int, int] | None = None,
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trailing_background_symbols: int = 0,
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background_sigma: float = 0.12,
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noise_sigma: float = 0.0,
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seed: int = 46001,
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prepend_malformed_candidate: bool = False,
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) -> ContinuousSoftStreamPlan:
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"""Собрать один float32 stream без передачи RX известных границ кадров.
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В stream представлены нормализованные soft BPSK-символы на выходе уже
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проверенного Lab045 timing/CFO/phase front-end. Полные sample-level формы
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Lab045 не материализуются: их точная длина учитывается свойствами плана.
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"""
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frames = tuple(frame_plans)
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if not frames:
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raise ValueError("нужен хотя бы один кадр")
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if leading_background_symbols < 0 or trailing_background_symbols < 0:
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raise ValueError("длина фоновой области не может быть отрицательной")
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if background_sigma < 0.0 or noise_sigma < 0.0:
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raise ValueError("sigma не может быть отрицательной")
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gaps = dict(inter_frame_background or {})
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for frame_index, symbol_count in gaps.items():
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if not 0 <= frame_index < len(frames) - 1 or symbol_count < 0:
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raise ValueError("некорректная inter-frame область")
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random_generator = np.random.default_rng(seed)
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chunks: list[np.ndarray] = []
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frame_starts: list[int] = []
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current_offset = 0
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def append_background(symbol_count: int) -> None:
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nonlocal current_offset
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if symbol_count == 0:
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return
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background = random_generator.normal(
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0.0,
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background_sigma,
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size=symbol_count,
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).astype(np.float32)
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chunks.append(background)
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current_offset += symbol_count
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append_background(leading_background_symbols)
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malformed_symbols = 0
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if prepend_malformed_candidate:
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malformed = malformed_header_candidate_soft()
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chunks.append(malformed)
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malformed_symbols = int(malformed.size)
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current_offset += malformed_symbols
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inter_frame_symbols = 0
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for frame_index, frame in enumerate(frames):
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frame_starts.append(current_offset)
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frame_soft = _bits_to_float32_soft(frame.plan.frame_bits)
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chunks.append(frame_soft)
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current_offset += int(frame_soft.size)
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if frame_index < len(frames) - 1:
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gap = int(gaps.get(frame_index, 0))
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inter_frame_symbols += gap
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append_background(gap)
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append_background(trailing_background_symbols)
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stream = np.concatenate(chunks, dtype=np.float32)
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if noise_sigma > 0.0:
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noise = random_generator.normal(0.0, noise_sigma, size=stream.size)
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stream += noise.astype(np.float32)
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return ContinuousSoftStreamPlan(
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soft_symbols=stream,
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frame_plans=frames,
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frame_starts=tuple(frame_starts),
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leading_background_symbols=leading_background_symbols,
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inter_frame_background_symbols=inter_frame_symbols,
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trailing_background_symbols=trailing_background_symbols,
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malformed_candidate_symbols=malformed_symbols,
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noise_sigma=noise_sigma,
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)
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def _normalized_soft_preamble_correlation(soft_stream: np.ndarray) -> np.ndarray:
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"""Нормированная корреляция PRBS7 через проверенный helper Lab043."""
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preamble = _bits_to_float32_soft(lab045.lab044.preamble_bits())
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if soft_stream.size < preamble.size:
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return np.empty(0, dtype=np.float32)
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scores = np.asarray(
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lab045.lab044.lab043._normalized_sliding_correlation(soft_stream, preamble),
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dtype=np.float32,
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)
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scores[~np.isfinite(scores)] = 0.0
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return np.clip(scores, 0.0, 1.0)
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def _preamble_candidate_indexes(scores: np.ndarray, threshold: float) -> np.ndarray:
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"""Вернуть все пороговые кандидаты в порядке потока, ничего не удаляя заранее."""
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return np.flatnonzero(scores >= threshold)
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@dataclass(frozen=True)
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class ContinuousFrameReception:
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candidate_start: int
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frame_end: int
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preamble_score: float
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packet_bytes: int
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fragment_index: int | None
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reception: lab045.IndependentReception
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@dataclass(frozen=True)
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class ContinuousReceiveResult:
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stream_symbol_count: int
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preamble_candidates: int
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valid_phy_headers: int
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fec_pass_count: int
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crc_pass_count: int
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crc_fail_count: int
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valid_frame_count: int
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rejected_candidates: int
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valid_fragments: int
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duplicate_fragments: int
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conflicting_fragments: int
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rejected_fragments: int
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missing_indexes: tuple[int, ...]
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object_complete: bool
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recovered_object: bytes | None
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candidate_starts: tuple[int, ...]
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cursor_history: tuple[int, ...]
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search_iterations: int
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termination_reason: str
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max_frames_reached: bool
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max_search_iterations_reached: bool
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correlation_storage_bytes: int
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frame_receptions: tuple[ContinuousFrameReception, ...]
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def scan_continuous_soft_stream(
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soft_stream: np.ndarray,
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*,
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preamble_threshold: float = CONTINUOUS_PREAMBLE_THRESHOLD,
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max_frames: int = DEFAULT_MAX_FRAMES,
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max_search_iterations: int = DEFAULT_MAX_SEARCH_ITERATIONS,
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) -> ContinuousReceiveResult:
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"""Независимо найти и декодировать все кадры в одном soft stream.
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Единственный вход с данными — сам stream. TX offsets, число кадров,
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fragment order, packets, coded bits и исходный объект функции неизвестны.
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"""
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try:
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stream = np.asarray(soft_stream, dtype=np.float32)
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except (TypeError, ValueError):
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stream = np.empty((0, 0), dtype=np.float32)
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if not 0.0 < preamble_threshold <= 1.0:
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raise ValueError("preamble_threshold должен лежать в (0, 1]")
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if max_frames < 0 or max_search_iterations < 0:
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raise ValueError("safety limits не могут быть отрицательными")
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assembler = ObjectAssembler()
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scores = np.empty(0, dtype=np.float32)
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if stream.ndim == 1 and stream.size and np.all(np.isfinite(stream)):
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scores = _normalized_soft_preamble_correlation(stream)
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candidate_indexes = _preamble_candidate_indexes(scores, preamble_threshold)
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cursor = 0
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cursor_history = [cursor]
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candidate_starts: list[int] = []
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frame_receptions: list[ContinuousFrameReception] = []
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preamble_candidates = 0
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valid_headers = 0
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fec_pass = 0
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crc_pass = 0
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crc_fail = 0
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valid_frames = 0
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rejected_candidates = 0
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search_iterations = 0
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termination_reason = "END_OF_STREAM"
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max_frames_reached = False
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max_iterations_reached = False
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while True:
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position = int(np.searchsorted(candidate_indexes, cursor, side="left"))
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if position >= candidate_indexes.size:
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break
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candidate_start = int(candidate_indexes[position])
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if search_iterations >= max_search_iterations:
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termination_reason = "MAX_SEARCH_ITERATIONS_REACHED"
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max_iterations_reached = True
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break
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if valid_frames >= max_frames:
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termination_reason = "MAX_FRAMES_REACHED"
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max_frames_reached = True
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break
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search_iterations += 1
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preamble_candidates += 1
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candidate_starts.append(candidate_start)
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preamble_end = candidate_start + lab045.PREAMBLE_BIT_COUNT
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header_end = preamble_end + lab045.PHY_HEADER_BIT_COUNT
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header = lab045.decode_phy_header_soft(stream[preamble_end:header_end])
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if not header["passed"]:
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rejected_candidates += 1
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cursor = candidate_start + 1
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cursor_history.append(cursor)
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continue
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valid_headers += 1
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packet_bytes = int(header["packet_bytes"])
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coded_length = lab045.conv.encoded_bit_count(packet_bytes * 8)
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frame_end = header_end + coded_length
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if frame_end > stream.size:
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rejected_candidates += 1
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cursor = candidate_start + 1
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cursor_history.append(cursor)
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continue
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reception = lab045.analyze_post_preamble_soft(stream[preamble_end:frame_end])
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if reception.analysis["fec_decode_pass"]:
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fec_pass += 1
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fragment = None
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fragment_index = None
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if reception.analysis["crc"] == lab045.CRC_PASS and reception.payload_bytes is not None:
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crc_pass += 1
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valid_frames += 1
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fragment = recover_fragment_from_payload(reception.payload_bytes)
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if fragment is not None:
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fragment_index = int(fragment.fragment_index)
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assembler.offer(fragment)
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else:
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if reception.analysis["crc"] == lab045.CRC_FAIL:
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crc_fail += 1
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rejected_candidates += 1
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frame_receptions.append(ContinuousFrameReception(
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candidate_start=candidate_start,
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frame_end=frame_end,
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preamble_score=float(scores[candidate_start]),
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packet_bytes=packet_bytes,
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fragment_index=fragment_index,
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reception=reception,
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))
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cursor = frame_end
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cursor_history.append(cursor)
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recovered = assembler.recovered_object()
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if stream.ndim != 1 or not stream.size or not np.all(np.isfinite(stream)):
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termination_reason = "INVALID_STREAM"
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return ContinuousReceiveResult(
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stream_symbol_count=int(stream.size),
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preamble_candidates=preamble_candidates,
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valid_phy_headers=valid_headers,
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fec_pass_count=fec_pass,
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crc_pass_count=crc_pass,
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crc_fail_count=crc_fail,
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valid_frame_count=valid_frames,
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rejected_candidates=rejected_candidates,
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valid_fragments=assembler.counters.accepted,
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duplicate_fragments=assembler.counters.duplicates,
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conflicting_fragments=assembler.counters.conflicting,
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rejected_fragments=assembler.counters.rejected,
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missing_indexes=tuple(assembler.missing_indexes()),
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object_complete=assembler.object_complete(),
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recovered_object=recovered,
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candidate_starts=tuple(candidate_starts),
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cursor_history=tuple(cursor_history),
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search_iterations=search_iterations,
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termination_reason=termination_reason,
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max_frames_reached=max_frames_reached,
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max_search_iterations_reached=max_iterations_reached,
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correlation_storage_bytes=int(scores.nbytes),
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frame_receptions=tuple(frame_receptions),
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)
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@dataclass(frozen=True)
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class ContinuousValidationResult:
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stream_plan: ContinuousSoftStreamPlan
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receive: ContinuousReceiveResult
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object_sha256: str
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recovered_object_sha256: str | None
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object_byte_errors: int | None
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sha_match: bool
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pre_fec_coded_bit_errors: int
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post_fec_protocol_bit_errors: int
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def _continuous_post_receive_diagnostics(
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receive: ContinuousReceiveResult,
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stream_plan: ContinuousSoftStreamPlan,
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) -> tuple[int, int]:
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"""Сравнить с TX только после независимых detector/header/FEC/CRC решений."""
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frame_by_index = {frame.fragment_index: frame for frame in stream_plan.frame_plans}
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pre_fec_errors = 0
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post_fec_errors = 0
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for record in receive.frame_receptions:
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if record.fragment_index is None:
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continue
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frame = frame_by_index.get(record.fragment_index)
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if frame is None:
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continue
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post_start = record.candidate_start + lab045.PREAMBLE_BIT_COUNT
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post_soft = stream_plan.soft_symbols[post_start:record.frame_end]
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diagnostic = lab045.diagnostic_pre_and_post_fec(
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record.reception,
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post_soft,
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frame.plan,
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)
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pre = diagnostic["pre_fec_coded"]["bit_errors"]
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post = diagnostic["post_fec_packet"]["bit_errors"]
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if pre is not None:
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pre_fec_errors += int(pre)
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if post is not None:
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post_fec_errors += int(post)
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return pre_fec_errors, post_fec_errors
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def run_continuous_object_transport(
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data: bytes,
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*,
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object_id: int = DEFAULT_OBJECT_ID,
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leading_background_symbols: int = 0,
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inter_frame_background: dict[int, int] | None = None,
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trailing_background_symbols: int = 0,
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noise_sigma: float = 0.0,
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seed: int = 46001,
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prepend_malformed_candidate: bool = False,
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max_frames: int = DEFAULT_MAX_FRAMES,
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max_search_iterations: int = DEFAULT_MAX_SEARCH_ITERATIONS,
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) -> ContinuousValidationResult:
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"""Построить TX stream, независимо принять его и лишь затем сравнить с TX."""
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frame_plans = build_object_frames(data, object_id)
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stream_plan = build_continuous_soft_stream(
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frame_plans,
|
||||
leading_background_symbols=leading_background_symbols,
|
||||
inter_frame_background=inter_frame_background,
|
||||
trailing_background_symbols=trailing_background_symbols,
|
||||
noise_sigma=noise_sigma,
|
||||
seed=seed,
|
||||
prepend_malformed_candidate=prepend_malformed_candidate,
|
||||
)
|
||||
receive = scan_continuous_soft_stream(
|
||||
stream_plan.soft_symbols,
|
||||
max_frames=max_frames,
|
||||
max_search_iterations=max_search_iterations,
|
||||
)
|
||||
pre_fec_errors, post_fec_errors = _continuous_post_receive_diagnostics(
|
||||
receive,
|
||||
stream_plan,
|
||||
)
|
||||
recovered = receive.recovered_object
|
||||
recovered_sha = object_sha256(recovered) if recovered is not None else None
|
||||
original_sha = object_sha256(data)
|
||||
if recovered is None:
|
||||
byte_errors = None
|
||||
elif len(recovered) != len(data):
|
||||
byte_errors = max(len(recovered), len(data))
|
||||
else:
|
||||
byte_errors = int(np.count_nonzero(
|
||||
np.frombuffer(recovered, dtype=np.uint8)
|
||||
!= np.frombuffer(data, dtype=np.uint8)
|
||||
))
|
||||
return ContinuousValidationResult(
|
||||
stream_plan=stream_plan,
|
||||
receive=receive,
|
||||
object_sha256=original_sha,
|
||||
recovered_object_sha256=recovered_sha,
|
||||
object_byte_errors=byte_errors,
|
||||
sha_match=(recovered is not None and recovered_sha == original_sha),
|
||||
pre_fec_coded_bit_errors=pre_fec_errors,
|
||||
post_fec_protocol_bit_errors=post_fec_errors,
|
||||
)
|
||||
|
||||
|
||||
# ============================================================ Airtime / goodput
|
||||
|
||||
|
||||
@@ -451,6 +907,35 @@ def goodput_report(result: ObjectTransportResult) -> dict:
|
||||
}
|
||||
|
||||
|
||||
def continuous_accounting_report(result: ContinuousValidationResult) -> dict:
|
||||
"""Длины полной Lab045-формы и фактических тестовых областей Lab046A."""
|
||||
|
||||
plan = result.stream_plan
|
||||
baseline_duration = plan.frame_waveform_samples / lab045.SAMPLE_RATE_HZ
|
||||
actual_duration = plan.equivalent_duration_seconds
|
||||
useful_bits = len(result.receive.recovered_object or b"") * 8
|
||||
return {
|
||||
"total_frame_symbols": plan.total_frame_symbols,
|
||||
"frame_waveform_samples": plan.frame_plans[0].plan.waveform_sample_count,
|
||||
"all_frame_waveform_samples": plan.frame_waveform_samples,
|
||||
"leading_samples": plan.leading_background_symbols * lab045.SAMPLES_PER_SYMBOL,
|
||||
"inter_frame_gap_samples": plan.inter_frame_background_symbols * lab045.SAMPLES_PER_SYMBOL,
|
||||
"trailing_samples": plan.trailing_background_symbols * lab045.SAMPLES_PER_SYMBOL,
|
||||
"total_stream_samples": plan.equivalent_total_samples,
|
||||
"baseline_duration_seconds": baseline_duration,
|
||||
"actual_duration_seconds": actual_duration,
|
||||
"baseline_goodput_kbit_per_second": (
|
||||
useful_bits / baseline_duration / 1000.0 if baseline_duration else 0.0
|
||||
),
|
||||
"actual_goodput_kbit_per_second": (
|
||||
useful_bits / actual_duration / 1000.0 if actual_duration else 0.0
|
||||
),
|
||||
"soft_stream_bytes": int(plan.soft_symbols.nbytes),
|
||||
"correlation_scores_bytes": result.receive.correlation_storage_bytes,
|
||||
"cumulative_energy_bytes": int((plan.soft_symbols.size + 1) * 8),
|
||||
}
|
||||
|
||||
|
||||
# ============================================================ Функциональные тесты
|
||||
|
||||
|
||||
@@ -477,6 +962,12 @@ def run_functional_tests() -> None:
|
||||
recovered = recover_fragment_from_payload(padded)
|
||||
assert recovered is not None and recovered.data == last.data
|
||||
|
||||
# Короткая Lab046A-проверка: два кадра находятся в одном stream без offsets.
|
||||
continuous = run_continuous_object_transport(obj[:300])
|
||||
assert continuous.receive.valid_frame_count == 2
|
||||
assert continuous.receive.preamble_candidates == 2
|
||||
assert continuous.sha_match
|
||||
|
||||
|
||||
# ============================================================ main
|
||||
|
||||
@@ -495,6 +986,30 @@ def main() -> int:
|
||||
channel=make_noisy_channel(arguments.sigma, base_seed=46000),
|
||||
)
|
||||
report = goodput_report(ideal)
|
||||
background_gaps = {
|
||||
frame_index: symbol_count
|
||||
for frame_index, symbol_count in ((7, 11), (23, 19), (51, 7))
|
||||
if frame_index < ideal.fragment_count - 1
|
||||
}
|
||||
continuous_ideal = run_continuous_object_transport(obj)
|
||||
continuous_background = run_continuous_object_transport(
|
||||
obj,
|
||||
leading_background_symbols=37,
|
||||
inter_frame_background=background_gaps,
|
||||
trailing_background_symbols=43,
|
||||
seed=464,
|
||||
)
|
||||
continuous_noisy = run_continuous_object_transport(
|
||||
obj,
|
||||
noise_sigma=arguments.sigma,
|
||||
seed=46001,
|
||||
)
|
||||
continuous_malformed = run_continuous_object_transport(
|
||||
obj,
|
||||
prepend_malformed_candidate=True,
|
||||
)
|
||||
continuous_accounting = continuous_accounting_report(continuous_ideal)
|
||||
background_accounting = continuous_accounting_report(continuous_background)
|
||||
|
||||
print("Lab046 software object transport")
|
||||
print(f"object size = {ideal.object_size} bytes")
|
||||
@@ -515,6 +1030,32 @@ def main() -> int:
|
||||
print(f"post-FEC protocol errors = {noisy.post_fec_protocol_bit_errors}")
|
||||
print(f"crc pass/fail = {noisy.crc_pass_count}/{noisy.crc_fail_count}")
|
||||
print(f"object complete = {noisy.object_complete}, sha match = {noisy.sha_match}, byte errors = {noisy.object_byte_errors}")
|
||||
print("--- Lab046A ideal continuous soft stream ---")
|
||||
print(f"preamble candidates = {continuous_ideal.receive.preamble_candidates}")
|
||||
print(f"valid headers/frames = {continuous_ideal.receive.valid_phy_headers}/{continuous_ideal.receive.valid_frame_count}")
|
||||
print(f"fec/crc pass = {continuous_ideal.receive.fec_pass_count}/{continuous_ideal.receive.crc_pass_count}")
|
||||
print(f"rejected candidates = {continuous_ideal.receive.rejected_candidates}")
|
||||
print(f"object complete = {continuous_ideal.receive.object_complete}, sha match = {continuous_ideal.sha_match}, byte errors = {continuous_ideal.object_byte_errors}")
|
||||
print("--- Lab046A background continuous soft stream ---")
|
||||
print(f"leading/inter-frame/trailing symbols = {continuous_background.stream_plan.leading_background_symbols}/{continuous_background.stream_plan.inter_frame_background_symbols}/{continuous_background.stream_plan.trailing_background_symbols}")
|
||||
print(f"valid frames = {continuous_background.receive.valid_frame_count}, sha match = {continuous_background.sha_match}")
|
||||
print(f"actual equivalent samples/duration = {background_accounting['total_stream_samples']}/{background_accounting['actual_duration_seconds']:.6f} s")
|
||||
print(f"--- Lab046A noisy continuous soft stream (sigma={arguments.sigma}) ---")
|
||||
print(f"valid frames = {continuous_noisy.receive.valid_frame_count}")
|
||||
print(f"pre/post-FEC errors = {continuous_noisy.pre_fec_coded_bit_errors}/{continuous_noisy.post_fec_protocol_bit_errors}")
|
||||
print(f"crc pass/fail = {continuous_noisy.receive.crc_pass_count}/{continuous_noisy.receive.crc_fail_count}")
|
||||
print(f"object complete = {continuous_noisy.receive.object_complete}, sha match = {continuous_noisy.sha_match}")
|
||||
print("--- Lab046A malformed candidate ---")
|
||||
print(f"preamble candidates = {continuous_malformed.receive.preamble_candidates}")
|
||||
print(f"rejected candidates = {continuous_malformed.receive.rejected_candidates}")
|
||||
print(f"valid frames = {continuous_malformed.receive.valid_frame_count}, sha match = {continuous_malformed.sha_match}")
|
||||
print("--- Lab046A accounting ---")
|
||||
print(f"frame waveform samples = {continuous_accounting['frame_waveform_samples']}")
|
||||
print(f"all frame waveform samples = {continuous_accounting['all_frame_waveform_samples']}")
|
||||
print(f"inter-frame gap samples = {continuous_accounting['inter_frame_gap_samples']}")
|
||||
print(f"airtime = {continuous_accounting['baseline_duration_seconds']:.6f} s")
|
||||
print(f"useful goodput = {continuous_accounting['baseline_goodput_kbit_per_second']:.6f} kbit/s")
|
||||
print(f"soft/correlation/cumulative-energy bytes = {continuous_accounting['soft_stream_bytes']}/{continuous_accounting['correlation_scores_bytes']}/{continuous_accounting['cumulative_energy_bytes']}")
|
||||
print("RF TX = 0 (software-only)")
|
||||
return 0
|
||||
|
||||
|
||||
Reference in New Issue
Block a user