120 lines
4.7 KiB
Python
120 lines
4.7 KiB
Python
from typing import Optional, Tuple
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import numpy as np
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import pandas as pd
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#TODO: Реализовать поиск времени простоя
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class DowntimeAnalyzer:
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def __init__(self) -> None:
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...
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def generate_downtime_report(self) -> list:
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...
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def _separate_conditions(self, TWC_raw:pd.DataFrame, robot_raw:pd.DataFrame) -> Tuple[dict, dict]:
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robot_splitter = RobotConditionSplitter()
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TWC_splitter = TWC_ConditionSplitter()
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#comm_splitter = CommConditionSplitter()
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rob_conditions = robot_splitter.split(robot_raw)
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TWC_conditions = TWC_splitter.split(TWC_raw)
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#comm_df = comm_splitter.split(rob_conditions["communication"], TWC_conditions["communication"])
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return (rob_conditions, TWC_conditions)
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class ConditionSplitter:
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def __init__(self):
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self._signals = []
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def _find_indexes(self,
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signal: str,
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dataframe: pd.DataFrame) -> list[list[float], list[float]]:
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stage_diff = np.diff(dataframe[signal])
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start_idx = np.where(stage_diff == 1)
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finish_idx = np.where(stage_diff == -1)
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return start_idx[0], finish_idx[0]
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def _find_events(self,
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dataframe: pd.DataFrame,
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signals: list[str]) -> Optional[dict[dict[pd.Series]]]:
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intervals = {}
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end_time = 0
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for signal in signals:
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start_idx, finish_idx = np.array(self._find_indexes(signal, dataframe))
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start_series = dataframe.loc[start_idx, "time"].reset_index(drop=True)
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end_series = dataframe.loc[finish_idx, "time"].reset_index(drop=True)
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end_series.fillna(end_time)
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intervals[signal] = {"rise": start_series,
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"fall": end_series}
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return intervals
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def _form_intervals(self,
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start: pd.Series,
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end: pd.Series) -> dict:
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if len(start) != len(end):
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for i in range(1, len(end)):
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if end[i-1] > start[i]:
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start = start.drop(i).reset_index(drop=True)
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intervals = {'start':start.tolist, 'end':end.tolist}
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return intervals
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class RobotConditionSplitter(ConditionSplitter):
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def __init__(self):
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self._signals = [
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"$OUT3012",
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"$IN3003",
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"$OUT3003",
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"$OUT3244"
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]
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def split(self, dataframe: pd.DataFrame) -> dict:
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events = self._find_events(dataframe, self._signals)
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communication_sig = {'sent':events["$OUT3244"]["fall"], 'received':events[""][""]}
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point_interval = self._form_intervals(start=events["$OUT3012"]["rise"], end=events["$OUT3012"]["fall"])
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movement_interval = self._form_intervals(start=events["$OUT3244"]["rise"], end=events["$OUT3244"]["fall"])
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conditions = {"communication":communication_sig, "waiting": point_interval, "moving": movement_interval}
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return conditions
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class TWC_ConditionSplitter(ConditionSplitter):
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def __init__(self):
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self._signals = [
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"Closing",
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"Squeeze",
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"Welding",
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"Relief",
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"Oncoming"
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]
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def split(self, dataframe: pd.DataFrame) -> dict:
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events = self._find_events(dataframe, self._signals)
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communication_sig = {'sent':events[""][""], 'received':events[""][""]} #ситара что-то делает -конец сигнала
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closing_interval = self._form_intervals(start=events["Closing"]["rise"], end=events["Closing"]["fall"])
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squeeze_interval = self._form_intervals(start=events["Squeeze"]["rise"], end=events["Squeeze"]["fall"])
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relief_interval = self._form_intervals(start=events["Relief"]["rise"], end=events["Relief"]["fall"])
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oncoming_interval = self._form_intervals(start=events["Oncoming"]["rise"], end=events["Oncoming"]["fall"])
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conditions = {
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"communication":communication_sig,
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'closing':closing_interval,
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'squeeze':squeeze_interval,
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'relief':relief_interval,
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'oncoming':oncoming_interval
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}
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return conditions
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class CommConditionSplitter(ConditionSplitter):
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"""
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Определяет промежуток, в который происходит взаимодействие между нодами.
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"""
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def split(self, node1: dict, node2: dict) -> pd.DataFrame:
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n1_to_n2 = self._form_intervals(start=node1['sent'], end=node2['received'])
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n2_to_n1 = self._form_intervals(start=node2['sent'], end=node1['received'])
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return pd.concat([pd.DataFrame(n1_to_n2), pd.DataFrame(n2_to_n1)])
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if __name__ == "__main__":
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path = "D:\downloads\Test2\TeslaTIME29_71_KRCIO.dat"
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