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