"""Convert ESP CAN485 logs into bounded, independently timestamped curves.""" from __future__ import annotations from collections import deque from dataclasses import dataclass from protocan.legacycan import PROJECTS, LegacyCanFormat, decode from .can485_board import BoardFrame, SdLogImport, parse_sd_log @dataclass class CanLogChannel: name: str address: int points: deque def _values(frame: BoardFrame): if frame.rtr: return prefix = f"{'EXT' if frame.extended else 'STD'} {frame.identifier:08X}" if frame.extended: for project in PROJECTS: if project.format is not LegacyCanFormat.ROTATING_THREE_WORDS: continue node = project.node_for(frame.identifier) if node is None: continue packet = decode(project.format, node, frame.identifier, frame.data) if packet is not None: for address, value in packet.present_values: # Keep both CAN directions and nodes in separate curves. yield (f"{prefix} · {node.name} · R{address:04X}", address, value) return # Unknown protocols stay explicitly raw; never guess a register layout. for offset in range(0, len(frame.data), 2): part = frame.data[offset:offset + 2] label = f"BE16 [{offset}:{offset + 1}]" if len(part) == 2 else f"байт [{offset}]" yield (f"{prefix} · {label}", offset, int.from_bytes(part, "big")) def read_can_log(lines, *, reference_timestamp: float, capacity: int, max_total_points: int = 1_000_000, frame_limit: int = 100_000) -> tuple[list[CanLogChannel], SdLogImport]: imported = parse_sd_log(lines, reference_timestamp, limit=frame_limit) channels = {} for frame in imported.frames: for name, address, _value in _values(frame): channels.setdefault(name, address) if len(channels) > 4096: raise ValueError("CAN CSV: слишком много каналов (максимум 4096)") if not channels: raise ValueError("CAN CSV: нет данных для графиков") capacity = max(1, min(capacity, max_total_points // len(channels))) result = {name: CanLogChannel(name, address, deque(maxlen=capacity)) for name, address in channels.items()} for frame in imported.frames: for name, _address, value in _values(frame): result[name].points.append((frame.timestamp * 1000, value)) return list(result.values()), imported