chore: из класса plotterWidget вынесены не относящиеся к нему методы в BasePointPassportFormer
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Andrew
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@ -5,8 +5,7 @@ import numpy as np
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from numpy import floating
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from typing import Optional, Any, NamedTuple
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from src.utils.base.base import BasePlotWidget
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from src.utils.base.base import BaseIdealDataBuilder
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from src.utils.base.base import BasePlotWidget, BasePointPassportFormer, BaseIdealDataBuilder
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class idealDataBuilder(BaseIdealDataBuilder):
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@ -41,7 +40,7 @@ class ProcessStage(NamedTuple):
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finish_index: int
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class PlotWidget(BasePlotWidget):
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class PlotWidget(BasePlotWidget, BasePointPassportFormer):
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def _create_curve_ideal(self,
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stage: str,
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signal: str,
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@ -64,19 +63,6 @@ class PlotWidget(BasePlotWidget):
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region.setBrush(pg.mkBrush(self._stage_colors[stage]))
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return region
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return None
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def _get_timestamp(self,
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stage: str,
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times: pd.Series,
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dataframe: pd.DataFrame) -> Optional[list[float]]:
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stage_diff = np.diff(dataframe[stage])
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start_index = np.where(stage_diff == 1)[0]
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finish_index = np.where(stage_diff == -1)[0]
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if start_index.size:
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start_timestamp = times[start_index[0]]
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finish_timestamp = times[finish_index[0]] if finish_index.size else times[len(times) - 1]
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return start_timestamp, finish_timestamp
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return None
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@staticmethod
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def _init_plot_widget(title: str) -> tuple[pg.PlotWidget, pg.LegendItem]:
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@ -116,38 +102,32 @@ class PlotWidget(BasePlotWidget):
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plot_widget, legend = self._init_plot_widget(title=channel)
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settings = description["Settings"]
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if settings["stages"] and all([stage in dataframe_headers for stage in self._stages]):
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for stage in self._stages:
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start_timestamp, finish_timestamp = self._get_timestamp(stage, time_axis, dataframe)
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region = self._create_stage_region(stage, start_timestamp, finish_timestamp)
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if region:
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plot_widget.addItem(region)
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for signal in description["Ideal_signals"]:
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ideal_plot = self._create_curve_ideal(stage, signal, start_timestamp, finish_timestamp)
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if ideal_plot:
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plot_widget.addItem(ideal_plot)
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if (settings["stages"] or settings["performance"]) and all([stage in dataframe_headers for stage in self._stages]):
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events = self._filter_events(time_axis, dataframe)
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point_quantity = len(events[self._clear_stage][0])
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if settings["stages"]:
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for stage in self._stages:
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start_t, end_t = events[stage]
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for i in range(len(start_t)):
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region = self._create_stage_region(stage, start_t[i], end_t[i])
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if region:
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plot_widget.addItem(region)
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for signal in description["Ideal_signals"]:
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ideal_plot = self._create_curve_ideal(stage, signal, start_t[i], end_t[i])
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if ideal_plot:
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plot_widget.addItem(ideal_plot)
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end_timestamp = time_axis[len(time_axis) - 1]
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region = self._create_stage_region("Oncoming", finish_timestamp, end_timestamp)
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if region:
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plot_widget.addItem(region)
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for signal in description["Ideal_signals"]:
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ideal_plot = self._create_curve_ideal("Oncoming", signal, finish_timestamp, end_timestamp)
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if ideal_plot:
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plot_widget.addItem(ideal_plot)
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if settings["performance"] and all([stage in dataframe_headers for stage in self._stages]):
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delta_timestamp = 0
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for stage in self._stages:
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start_timestamp, finish_timestamp = self._get_timestamp(stage, time_axis, dataframe)
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delta_timestamp += finish_timestamp - start_timestamp
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ideal_delta = self._opt.get_cycle_time()
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performance = round(ideal_delta/delta_timestamp*100, 2)
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performance_label = QLabel(f"Performance = {performance} %")
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layout.addWidget(performance_label)
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if settings["performance"]:
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ideal_delta = self._opt.get_cycle_time()
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delta = np.zeros(point_quantity)
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for stage in self._stages:
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try:
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start_stage, stop_stage = events[stage]
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delta += np.array(stop_stage)-np.array(start_stage)
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except: print("Signal ", stage, " is abnormal..." )
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performance_list = ideal_delta/delta*100
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performance_label = QLabel(f"Performance: best = {performance_list.max()} %, worse = {performance_list.min()} %, average = {performance_list.mean()}")
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layout.addWidget(performance_label)
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if settings["zoom"]:
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if max(time_axis) < 5.0:
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@ -203,8 +183,8 @@ class PlotWidget(BasePlotWidget):
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widgets = [self._build_widget(data_sample) for data_sample in data]
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self._mediator.notify(self, widgets)
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def update_settings(self, data: list[dict]):
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self._initIdealBuilder(idealDataBuilder=idealDataBuilder, data=data)
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def update_settings(self, params: list[dict]):
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self._initIdealBuilder(idealDataBuilder=idealDataBuilder, params=params)
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Binary file not shown.
@ -8,6 +8,10 @@ from PyQt5.QtCore import QThread, QObject, QTimer
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from PyQt5.QtWidgets import QWidget, QTabWidget
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from src.OptAlgorithm import OptAlgorithm
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import pandas as pd
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import pandas as pd
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import numpy as np
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class BaseMediator:
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@ -102,20 +106,14 @@ class BasePlotWidget:
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mediator: Optional[BaseMediator] = None):
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super().__init__()
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self._mediator = mediator
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self._stages = [
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"Closing",
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"Squeeze",
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"Welding",
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"Relief"
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]
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self._stage_colors = {
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"Closing": [208, 28, 31, 100],
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"Squeeze": [45, 51, 89, 150],
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"Welding": [247, 183, 24, 100],
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"Relief": [0, 134, 88, 100],
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"Oncoming": [222, 184, 135, 100]
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"Oncomming": [222, 184, 135, 100]
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}
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self._plt_channels = {
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"Electrode Force, N & Welding Current, kA": {
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@ -200,18 +198,7 @@ class BasePlotWidget:
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]
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},
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}
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def _initIdealBuilder(self,
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idealDataBuilder: Optional[BaseIdealDataBuilder] = None,
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data: list[dict] = None):
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self.opt = idealDataBuilder(data)
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self._stage_ideals = {
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"Closing": self._opt.get_closingDF(),
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"Squeeze": self._opt.get_compressionDF(),
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"Welding": self._opt.get_weldingDF(),
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"Relief": self._opt.get_openingDF(),
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"Oncoming": self._opt.get_oncomingDF()
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}
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@property
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def mediator(self) -> BaseMediator:
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return self._mediator
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@ -243,10 +230,9 @@ class BaseController(QObject):
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...
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# FIXME: WeldingDF показывает только 1 секунду
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class BaseIdealDataBuilder(OptAlgorithm):
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def __init__(self, data: list[dict]):
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operator_params, system_params = data
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def __init__(self, params: list[dict]):
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operator_params, system_params = params
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self.mul = system_params['time_capture']
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self.welding_time = operator_params['time_wielding']
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super().__init__(operator_params, system_params)
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@ -337,4 +323,70 @@ class BaseMainWindow(QWidget):
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}
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""")
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class BasePointPassportFormer:
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def __init__(self):
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self._clear_stage = "Welding"
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self._stages = [
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"Closing",
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"Squeeze",
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"Welding",
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"Relief",
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]
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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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signal: str,
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times:pd.Series,
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dataframe: pd.DataFrame) -> list[list[float]]:
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start_idx, finish_idx = self._find_indexes(signal, dataframe)
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start_list = times.loc[start_idx].tolist()
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end_list = times.loc[finish_idx].tolist()
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if len(start_list) - len(end_list) == 1:
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end_list.append(float(times[len(times)-1]))
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return start_list, end_list
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def _filter_events(self,
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times: pd.Series,
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dataframe: pd.DataFrame) -> dict[list[float]]:
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events = {}
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if self._clear_stage in self._stages:
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start_list, end_list = self._find_events(self._clear_stage, times, dataframe)
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point_quantity = len(start_list)
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for stage in self._stages:
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start_list, end_list = self._find_events(stage, times, dataframe)
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events[stage] = [start_list[:point_quantity], end_list[:point_quantity]]
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return events
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def _initIdealBuilder(self,
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idealDataBuilder: Optional[BaseIdealDataBuilder] = None,
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params: list[dict] = None):
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self.opt = idealDataBuilder(params)
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self._stage_ideals = {
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"Closing": self._opt.get_closingDF(),
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"Squeeze": self._opt.get_compressionDF(),
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"Welding": self._opt.get_weldingDF(),
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"Relief": self._opt.get_openingDF(),
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"Oncomming": self._opt.get_oncomingDF()
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}
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def _create_curve_ideal(self,
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stage: str):
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data = self._stage_ideals[stage]
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...
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@property
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def opt(self) -> BaseIdealDataBuilder:
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return self._opt
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@opt.setter
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def opt(self, opt: BaseIdealDataBuilder):
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self._opt = opt
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