dev: добавлена обработка исключений в passport_former

src/controller/passport_former.py

@@ -1,26 +1,22 @@
-import traceback
-import sys
 from typing import Optional, Any
-
 import numpy as np
 import pandas as pd
 from loguru import logger
 
 from base.base import BasePointPassportFormer, BaseIdealDataBuilder, PointPassport, GraphicPassport, Settings, UsefulGraphData
-    
+
 
 class PassportFormer(BasePointPassportFormer):
-  
+
     def form_passports(self, data: list[pd.DataFrame]) -> None:
+        """
+        Формирует паспорта для каждого DataFrame из списка.
+        В случае ошибки логируется сообщение и возвращается пустой список.
+        """
         try:
             return_data = [self._build_from_df_only(dataframe) for dataframe in data]
-        except:
-            # TODO: обработка исключений!!!
-            tb = sys.exc_info()[2]
-            # TODO: Нормальные сообщения в лог!
-            tbinfo = traceback.format_tb(tb)[0]
-            pymsg = "Traceback info:\n" + tbinfo + "\nError Info:\n" + str(sys.exc_info()[1])
-            logger.error(pymsg)
+        except Exception as e:
+            logger.error(f"form_passports - Непредвиденная ошибка при формировании паспортов: {e}")
             return_data = []
         finally:
             self._mediator.notify(self, return_data)
@@ -29,26 +25,26 @@ class PassportFormer(BasePointPassportFormer):
         self._settings = settings
     
     def form_customer_passport(self, data: list[pd.DataFrame, dict]) -> None:
+        """
+        Формирует паспорт заказчика на основе DataFrame и словаря событий.
+        В случае ошибки логируется сообщение и возвращается пустой список.
+        """
         try:
             dataframe, events = data
             point_quantity = len(events["Welding"][0])
-            data = self._form_graphic_passport(dataframe, events, point_quantity)
-            return_data = [data]
-        except:
-            #TODO: Добавить обработку исключений
-            tb = sys.exc_info()[2]
-            tbinfo = traceback.format_tb(tb)[0]
-            pymsg = "Traceback info:\n" + tbinfo + "\nError Info:\n" + str(sys.exc_info()[1])
-            logger.error(pymsg)
+            data_passport = self._form_graphic_passport(dataframe, events, point_quantity)
+            return_data = [data_passport]
+        except Exception as e:
+            logger.error(f"form_customer_passport - Непредвиденная ошибка при формировании паспорта заказчика: {e}")
             return_data = []
         finally:
             self._mediator.notify(self, return_data)
 
-
-
     @staticmethod
-    def _find_indexes(signal: str,  
-                       dataframe: pd.DataFrame) -> tuple[np.ndarray, np.ndarray]:
+    def _find_indexes(signal: str, dataframe: pd.DataFrame) -> tuple[np.ndarray, np.ndarray]:
+        """
+        Находит индексы начала и конца этапа для указанного сигнала.
+        """
         stage_diff = np.diff(dataframe[signal])
         start_idx = np.where(stage_diff == 1)
         finish_idx = np.where(stage_diff == -1)
@@ -56,8 +52,11 @@ class PassportFormer(BasePointPassportFormer):
     
     @staticmethod
     def _find_events(signal: str,
-                    times:pd.Series,
-                    dataframe: pd.DataFrame) -> tuple[list[float], list[float]]: 
+                     times: pd.Series,
+                     dataframe: pd.DataFrame) -> tuple[list[float], list[float]]:
+        """
+        Формирует списки времен начала и окончания событий для указанного сигнала.
+        """
         start_idx, finish_idx = PassportFormer._find_indexes(signal, dataframe)
        
         if len(start_idx) > 0 and len(finish_idx) > 0 and start_idx[0] > finish_idx[0]:
@@ -66,203 +65,303 @@ class PassportFormer(BasePointPassportFormer):
         end_list = times.iloc[finish_idx].tolist() if len(finish_idx) > 0 else []
         if len(start_list) - len(end_list) == 1:
             end_list.append(float(times.iloc[-1]))
-
         return start_list, end_list
     
     def _generate_events(self,
-                        times: pd.Series,
-                        dataframe: pd.DataFrame) -> tuple[dict[str, list[list[float]]], int]:
+                         times: pd.Series,
+                         dataframe: pd.DataFrame) -> tuple[dict[str, list[list[float]]], int]:
+        """
+        Генерирует словарь событий для каждого этапа и определяет количество точек.
+        Если для основного этапа (_clear_stage) не найдено ни одного события,
+        логируется ошибка и возвращается пустой список.
+        """
         events = {}
         point_quantity = 0
         if self._clear_stage in self._stages:
             start_list, end_list = self._find_events(self._clear_stage, times, dataframe)
             point_quantity = len(start_list)
             if point_quantity == 0:
-                #TODO: добавить обработку исключения
-                return []
+                logger.error("_generate_events - Не найдены события для этапа '{}'.", self._clear_stage)
+                return {}, 0  # Возвращаем пустой словарь и 0 точек
             
             for stage in self._stages:
-                start_list, end_list = self._find_events(stage, times, dataframe)
-                temp = min([len(start_list), len(end_list)])
+                s_list, e_list = self._find_events(stage, times, dataframe)
+                temp = min(len(s_list), len(e_list))
                 if temp < point_quantity:
-                    print ("cant find enough", stage)
-                    start_list += [0]*(point_quantity - temp)
-                    end_list += [1]*(point_quantity - temp)
-
-                events[stage] = [start_list, end_list]
+                    logger.warning(f"_generate_events - Недостаточное количество событий для этапа '{stage}'. "
+                                   f"Ожидается {point_quantity}, получено {temp}. Заполнение нулями/единицами.")
+                    s_list += [0] * (point_quantity - temp)
+                    e_list += [1] * (point_quantity - temp)
+                events[stage] = [s_list, e_list]
         return events, point_quantity
     
-    def _build_ideal_data(self, 
-                    idealDataBuilder: Optional[BaseIdealDataBuilder] = None,
-                    point_settings: Settings = None) -> dict:  
-        self.opt_algorithm = idealDataBuilder(point_settings)
-        stage_ideals = {
-            "Closing": self._opt_algorithm.get_closingDF(),
-            "Squeeze": self._opt_algorithm.get_compressionDF(),
-            "Welding": self._opt_algorithm.get_weldingDF(),
-            "Relief": self._opt_algorithm.get_openingDF(), 
-            "Oncomming": self._opt_algorithm.get_oncomingDF(),
-            "Ideal cycle": self._opt_algorithm.get_cycle_time(),
-            "Ideal timings": self._opt_algorithm.get_ideal_timings()
-        }
-        return stage_ideals
+    def _build_ideal_data(self,
+                          idealDataBuilder: Optional[BaseIdealDataBuilder] = None,
+                          point_settings: Settings = None) -> dict:
+        """
+        Строит идеальные данные с использованием переданного билдера.
+        """
+        try:
+            self.opt_algorithm = idealDataBuilder(point_settings)
+            stage_ideals = {
+                "Closing": self._opt_algorithm.get_closingDF(),
+                "Squeeze": self._opt_algorithm.get_compressionDF(),
+                "Welding": self._opt_algorithm.get_weldingDF(),
+                "Relief": self._opt_algorithm.get_openingDF(),
+                "Oncomming": self._opt_algorithm.get_oncomingDF(),
+                "Ideal cycle": self._opt_algorithm.get_cycle_time(),
+                "Ideal timings": self._opt_algorithm.get_ideal_timings()
+            }
+            return stage_ideals
+        except Exception as e:
+            logger.error(f"_build_ideal_data - Ошибка при построении идеальных данных: {e}")
+            return {}
     
-    def _generate_cache_key(self, 
-                            point_settings:Settings) -> tuple[tuple[tuple[str, Any], ...], tuple[tuple[str, Any], ...]]:
+    def _generate_cache_key(self,
+                            point_settings: Settings) -> tuple[tuple[tuple[str, Any], ...], tuple[tuple[str, Any], ...]]:
         """
         Преобразует point_settings в хешируемый ключ для кэша.
         """
-        # Преобразуем словари в отсортированные кортежи пар ключ-значение
-        operator_tuple = frozenset((key, value) 
-                                for key, value in point_settings.operator.items()
-                                if str(key) in self._OptAlgorithm_operator_params)
-        
-        system_tuple = frozenset((key, value) 
-                                for key, value in point_settings.system.items()
-                                if str(key) in self._OptAlgorithm_system_params)
-        return (operator_tuple, system_tuple)
-
-    def _build_from_df_only(self, dataframe: pd.DataFrame) -> GraphicPassport:
-
-        if (dataframe is not None and 
-            set(self._stages).issubset(set(dataframe.columns.tolist()))):
-            events, point_quantity = self._generate_events(dataframe["time"], dataframe)
-            point_quantity = len(events["Welding"])
-            pass
-            if point_quantity == 0:
-                return []
-        else:
-            events = None
-            key = list(self._settings.operator.keys())[0]
-            point_quantity = len(self._settings.operator[key])
-
-        passport = self._form_graphic_passport(dataframe, events, point_quantity)
-        return passport
-
-    def _form_graphic_passport(self, 
-                               dataframe:pd.DataFrame, 
-                               events:dict, 
-                               point_quantity:int) -> GraphicPassport:
-
-        system_settings = {key: value[0] for key, value in self._settings.system.items()}
-        graphic_passport = GraphicPassport(dataframe, [], self._form_graphic_useful_data(system_settings))
-
-        for i in range(point_quantity):
-            point_settings = Settings(self._get_operator_settings_part(i), system_settings)      
-
-            timeframe, po_events = self._form_point_events(events, i)
-            ideal_data = self._form_point_ideal_data(point_settings)
-            useful_data = self._form_point_useful_data(point_settings.operator)
-            point_passport = PointPassport(timeframe, po_events, ideal_data, useful_data)
-
-            graphic_passport.points_pocket.append(point_passport)
-        return graphic_passport
-
-    def _form_graphic_useful_data(self, system_settings:dict) -> dict:
-        tesla_time = sum(self._settings.operator.get("Tesla summary time", []))
-        useful_data = UsefulGraphData(
-            tesla_time, 
-            system_settings["Range ME, mm"], 
-            system_settings["k_hardness_1"]
+        try:
+            operator_tuple = frozenset(
+                (key, value)
+                for key, value in point_settings.operator.items()
+                if str(key) in self._OptAlgorithm_operator_params
             )
-        return useful_data
+            system_tuple = frozenset(
+                (key, value)
+                for key, value in point_settings.system.items()
+                if str(key) in self._OptAlgorithm_system_params
+            )
+            return (operator_tuple, system_tuple)
+        except Exception as e:
+            logger.error(f"_generate_cache_key - Ошибка при генерации ключа кэша: {e}")
+            return ((), ())
     
-    def _form_point_useful_data(self, operator_settings:dict) -> dict:
-        useful_data = {"thickness": operator_settings["object_thickness"],
+    def _build_from_df_only(self, dataframe: pd.DataFrame) -> GraphicPassport:
+        """
+        Строит GraphicPassport на основе одного DataFrame.
+        Если DataFrame содержит необходимые столбцы, события генерируются; 
+        иначе используется альтернативное определение point_quantity.
+        Если количество точек равно нулю, логируется ошибка и возвращается None.
+        """
+        try:
+            if (dataframe is not None and
+                set(self._stages).issubset(set(dataframe.columns.tolist()))):
+                events, point_quantity = self._generate_events(dataframe["time"], dataframe)
+                point_quantity = len(events["Welding"][0])
+                if point_quantity == 0:
+                    logger.error("_build_from_df_only - Не найдено ни одного события в DataFrame.")
+                    return None
+            else:
+                events = None
+                key = list(self._settings.operator.keys())[0]
+                point_quantity = len(self._settings.operator[key])
+            passport = self._form_graphic_passport(dataframe, events, point_quantity)
+            return passport
+        except Exception as e:
+            logger.error(f"_build_from_df_only - Непредвиденная ошибка: {e}")
+            return None
+
+    def _form_graphic_passport(self,
+                               dataframe: pd.DataFrame,
+                               events: dict,
+                               point_quantity: int) -> GraphicPassport:
+        """
+        Формирует графический паспорт с полезными данными и списком PointPassport.
+        """
+        try:
+            system_settings = {key: value[0] for key, value in self._settings.system.items()}
+            graphic_passport = GraphicPassport(dataframe, [], self._form_graphic_useful_data(system_settings))
+
+            for i in range(point_quantity):
+                point_settings = Settings(self._get_operator_settings_part(i), system_settings)
+                timeframe, po_events = self._form_point_events(events, i)
+                ideal_data = self._form_point_ideal_data(point_settings)
+                useful_data = self._form_point_useful_data(point_settings.operator)
+                point_passport = PointPassport(timeframe, po_events, ideal_data, useful_data)
+                graphic_passport.points_pocket.append(point_passport)
+            return graphic_passport
+        except Exception as e:
+            logger.error(f"_form_graphic_passport - Ошибка при формировании графического паспорта: {e}")
+            return None
+
+    def _form_graphic_useful_data(self, system_settings: dict) -> dict:
+        """
+        Формирует словарь полезных данных для графика.
+        """
+        try:
+            tesla_time = sum(self._settings.operator.get("Tesla summary time", []))
+            useful_data = UsefulGraphData(
+                tesla_time,
+                system_settings["Range ME, mm"],
+                system_settings["k_hardness_1"]
+            )
+            return useful_data
+        except Exception as e:
+            logger.error(f"_form_graphic_useful_data - Ошибка при формировании полезных данных: {e}")
+            return {}
+
+    def _form_point_useful_data(self, operator_settings: dict) -> dict:
+        """
+        Формирует полезные данные для отдельной точки.
+        """
+        try:
+            useful_data = {
+                "thickness": operator_settings["object_thickness"],
                 "L2": operator_settings["distance_l_2"],
-                "force": operator_settings["force_target"]}
-        return useful_data
+                "force": operator_settings["force_target"]
+            }
+            return useful_data
+        except Exception as e:
+            logger.error(f"_form_point_useful_data - Ошибка при формировании полезных данных точки: {e}")
+            return {}
     
-    def _form_point_ideal_data(self, point_settings:Settings) -> dict:
-        cache_key = self._generate_cache_key(point_settings)
-        ideal_data = self._ideal_data_cashe.get(cache_key, 
-            self._build_ideal_data(idealDataBuilder=IdealDataBuilder, point_settings=point_settings))
-        self._ideal_data_cashe[cache_key] = ideal_data
-        return ideal_data
+    def _form_point_ideal_data(self, point_settings: Settings) -> dict:
+        """
+        Формирует идеальные данные для точки с использованием кэша.
+        """
+        try:
+            cache_key = self._generate_cache_key(point_settings)
+            ideal_data = self._ideal_data_cashe.get(
+                cache_key,
+                self._build_ideal_data(idealDataBuilder=IdealDataBuilder, point_settings=point_settings)
+            )
+            self._ideal_data_cashe[cache_key] = ideal_data
+            return ideal_data
+        except Exception as e:
+            logger.error(f"_form_point_ideal_data - Ошибка при формировании идеальных данных точки: {e}")
+            return {}
     
-    def _get_operator_settings_part(self, idx:int) -> dict:
-        operator_settings = {
+    def _get_operator_settings_part(self, idx: int) -> dict:
+        """
+        Извлекает часть настроек оператора для конкретного индекса.
+        """
+        try:
+            operator_settings = {
                 key: (value[idx] if idx < len(value) else value[0])
                 for key, value in self._settings.operator.items()
             }
-        return operator_settings
+            return operator_settings
+        except Exception as e:
+            logger.error(f"_get_operator_settings_part - Ошибка при получении настроек оператора для индекса {idx}: {e}")
+            return {}
     
-    def _form_point_events(self, events:dict, idx:int) -> list[list, dict]:
-        timeframe, point_events = None, None
-        if events is not None:
-            idx_shift = idx+1 if events[self._stages[-1]][0][0] == 0 else idx
-            timeframe = [events[self._stages[0]][0][idx], events[self._stages[-1]][1][idx_shift]]
-            point_events = {key: [value[0][idx], value[1][idx]] for key, value in events.items()}
-        return timeframe, point_events
+    def _form_point_events(self, events: dict, idx: int) -> list[list, dict]:
+        """
+        Формирует временной интервал и события для отдельной точки.
+        Если событий нет, возвращает (None, None).
+        """
+        try:
+            timeframe, point_events = None, None
+            if events is not None:
+                idx_shift = idx + 1 if events[self._stages[-1]][0][0] == 0 else idx
+                timeframe = [events[self._stages[0]][0][idx], events[self._stages[-1]][1][idx_shift]]
+                point_events = {key: [value[0][idx], value[1][idx]] for key, value in events.items()}
+            return timeframe, point_events
+        except Exception as e:
+            logger.error(f"_form_point_events - Ошибка при формировании событий для точки {idx}: {e}")
+            return None, None
     
 
 class IdealDataBuilder(BaseIdealDataBuilder):
 
     def get_closingDF(self) -> pd.DataFrame:
-        return self._get_data(self.Ts['tclose'], self.calcPhaseClose)
-    
+        try:
+            return self._get_data(self.Ts['tclose'], self.calcPhaseClose)
+        except Exception as e:
+            logger.error(f"get_closingDF - Ошибка при получении данных для этапа закрытия: {e}")
+            return pd.DataFrame()
+
     def get_compressionDF(self) -> pd.DataFrame:
-        return self._get_data(self.Ts['tgrow'], self.calcPhaseGrow)
-    
+        try:
+            return self._get_data(self.Ts['tgrow'], self.calcPhaseGrow)
+        except Exception as e:
+            logger.error(f"get_compressionDF - Ошибка при получении данных для этапа сжатия: {e}")
+            return pd.DataFrame()
+
     def get_openingDF(self) -> pd.DataFrame:
-        return self._get_data(self.getMarkOpen(), self.calcPhaseOpen)
-    
+        try:
+            return self._get_data(self.getMarkOpen(), self.calcPhaseOpen)
+        except Exception as e:
+            logger.error(f"get_openingDF - Ошибка при получении данных для этапа открытия: {e}")
+            return pd.DataFrame()
+
     def get_oncomingDF(self) -> pd.DataFrame:
-        return self._get_data(self.Ts['tmovement'], self.calcPhaseMovement)
+        try:
+            return self._get_data(self.Ts['tmovement'], self.calcPhaseMovement)
+        except Exception as e:
+            logger.error(f"get_oncomingDF - Ошибка при получении данных для этапа движения: {e}")
+            return pd.DataFrame()
 
     def get_weldingDF(self) -> pd.DataFrame:
-        data = []
-        X1, X2, V1, V2, F = self.calcPhaseGrow(self.Ts['tgrow']-0.0001)
-        X1, X2, V1, V2 = X1*1000, X2*1000, V1*1000, V2*1000
-        data.append({
-            "time":0,
-            "Position FE":X1,
-            "Position ME":X2,
-            "Rotor Speed FE":V1,
-            "Rotor Speed ME":V2,
-            "Force":F
-            })
-        data.append({
-            "time":self.welding_time,
-            "Position FE":X1,
-            "Position ME":X2,
-            "Rotor Speed FE":V1,
-            "Rotor Speed ME":V2, 
-            "Force":F
-            })
-        return pd.DataFrame(data)
-    
-    def get_ideal_timings(self) -> list[float]:
-        data = self.Ts
-        ideal_timings = [
-            data['tclose'],
-            data['tgrow'],
-            self.welding_time,
-            self.getMarkOpen(),
-            data['tmovement']
-            ]
-        return ideal_timings
-    
-    def _get_data(self, end_timestamp:float, func) -> pd.DataFrame:
-        data = []
-        for i in range (0, int(end_timestamp*self.mul)+1):
-            time = i/self.mul
-            X1, X2, V1, V2, F = func(time)
+        try:
+            data = []
+            X1, X2, V1, V2, F = self.calcPhaseGrow(self.Ts['tgrow'] - 0.0001)
+            X1, X2, V1, V2 = X1 * 1000, X2 * 1000, V1 * 1000, V2 * 1000
             data.append({
-                "time":time,
-                "Position FE":X1*1000,
-                "Position ME":X2*1000,
-                "Rotor Speed FE":V1*1000,
-                "Rotor Speed ME":V2*1000,
-                "Force":F
-                })
-        X1, X2, V1, V2, F = func(end_timestamp)
-        data.append({
-            "time":end_timestamp,
-            "Position FE":X1*1000,
-            "Position ME":X2*1000,
-            "Rotor Speed FE":V1*1000,
-            "Rotor Speed ME":V2*1000,
-            "Force":F
+                "time": 0,
+                "Position FE": X1,
+                "Position ME": X2,
+                "Rotor Speed FE": V1,
+                "Rotor Speed ME": V2,
+                "Force": F
             })
-        return pd.DataFrame(data)
+            data.append({
+                "time": self.welding_time,
+                "Position FE": X1,
+                "Position ME": X2,
+                "Rotor Speed FE": V1,
+                "Rotor Speed ME": V2,
+                "Force": F
+            })
+            return pd.DataFrame(data)
+        except Exception as e:
+            logger.error(f"get_weldingDF - Ошибка при получении данных для этапа сварки: {e}")
+            return pd.DataFrame()
+
+    def get_ideal_timings(self) -> list[float]:
+        try:
+            data = self.Ts
+            ideal_timings = [
+                data['tclose'],
+                data['tgrow'],
+                self.welding_time,
+                self.getMarkOpen(),
+                data['tmovement']
+            ]
+            return ideal_timings
+        except Exception as e:
+            logger.error(f"get_ideal_timings - Ошибка при получении идеальных временных интервалов: {e}")
+            return []
+
+    def _get_data(self, end_timestamp: float, func) -> pd.DataFrame:
+        """
+        Получает данные до указанного времени с шагом, определяемым mul.
+        """
+        try:
+            data = []
+            for i in range(0, int(end_timestamp * self.mul) + 1):
+                time = i / self.mul
+                X1, X2, V1, V2, F = func(time)
+                data.append({
+                    "time": time,
+                    "Position FE": X1 * 1000,
+                    "Position ME": X2 * 1000,
+                    "Rotor Speed FE": V1 * 1000,
+                    "Rotor Speed ME": V2 * 1000,
+                    "Force": F
+                })
+            X1, X2, V1, V2, F = func(end_timestamp)
+            data.append({
+                "time": end_timestamp,
+                "Position FE": X1 * 1000,
+                "Position ME": X2 * 1000,
+                "Rotor Speed FE": V1 * 1000,
+                "Rotor Speed ME": V2 * 1000,
+                "Force": F
+            })
+            return pd.DataFrame(data)
+        except Exception as e:
+            logger.error(f"_get_data - Ошибка при получении данных с end_timestamp={end_timestamp}: {e}")
+            return pd.DataFrame()