fix some coding style issues

Author: pvstorageoptimization

optibess_algorithm/financial_calculator.py

@@ -530,7 +530,7 @@ def get_hourly_tariff(self, year):
             return self._hourly_tariff, self._hourly_buy_tariff
 
         relative_year = year - self.output_calculator.producer.start_year
-        self._hourly_tariff,self._hourly_buy_tariff = \
+        self._hourly_tariff, self._hourly_buy_tariff = \
             get_yearly_prices(relative_year, self._hourly_sell_prices, self._hourly_buy_prices, self._tariff_table,
                               self.output_calculator.producer.start_year, self.output_calculator.yearly_hour_num)
         self._hourly_matrix_year = year

optibess_algorithm/output_calculator.py

@@ -12,8 +12,8 @@
 
 from .producers import Producer
 from .power_storage import PowerStorage
-from .utils import year_diff, month_diff, relu, clamp, is_leap_year, hour_num_in_range, tariff_table_to_hourly, \
-    get_yearly_prices, is_real_numbers
+from .utils import (year_diff, month_diff, relu, clamp, is_leap_year, hour_num_in_range, get_yearly_prices,
+                    is_real_numbers)
 from .constants import YEAR_DAYS, YEAR_HOURS, DAY_LENGTH
 
 
@@ -1152,7 +1152,7 @@ def sell_prices(self):
         return self._sell_prices
 
     @sell_prices.setter
-    def sell_prices(self, value: np.ndarray[float]):
+    def sell_prices(self, value: np.ndarray[Any, float]):
         if isinstance(value, np.ndarray) and is_real_numbers(value):
             if value.shape != (YEAR_HOURS,) and value.shape != (self._project_hour_num,):
                 raise ValueError(f"Prices shape should be ({YEAR_HOURS},) or ({self._project_hour_num}, ), prices"
@@ -1172,7 +1172,7 @@ def buy_prices(self):
         return self._buy_prices
 
     @buy_prices.setter
-    def buy_prices(self, value: np.ndarray[float]):
+    def buy_prices(self, value: np.ndarray[Any, float]):
         if isinstance(value, np.ndarray) and is_real_numbers(value):
             if value.shape != (YEAR_HOURS,) and value.shape != (self._project_hour_num, ):
                 raise ValueError(f"Prices shape should be ({YEAR_HOURS},) or ({self._project_hour_num}, ), prices"
@@ -1200,7 +1200,7 @@ def tariff_table(self, value: np.ndarray[Any, np.dtype[np.float64]]):
                 raise ValueError("Tariff table should be of shape (7, 12, 24)")
         self._tariff_table = value
 
-    def _get_action_from_obs(self, obs: np.ndarray):
+    def _get_action_from_obs(self, obs: np.ndarray[Any, float]):
         """
         get action(s) from model given an observation
 

optibess_algorithm/utils.py

@@ -1,5 +1,5 @@
 import itertools
-from typing import Union
+from typing import Union, Any
 
 import numpy as np
 import pandas as pd
@@ -141,8 +141,8 @@ def get_seasonal_hour_division(winter_low_hours: tuple[int, ...] | None = None,
 
 def build_tariff_table(winter_low: float, winter_high_week: float, winter_high_weekend: float, transition_low: float,
                        transition_high_week: float, transition_high_weekend: float, summer_low: float,
-                       summer_high_week: float, summer_high_weekend: float, week_days: tuple = (0, 1, 2, 3, 4),
-                       winter_months: tuple[int, ...] = (0, 1, 11),
+                       summer_high_week: float, summer_high_weekend: float,
+                       week_days: tuple[int, ...] = (0, 1, 2, 3, 4), winter_months: tuple[int, ...] = (0, 1, 11),
                        transition_months: tuple[int, ...] = (2, 3, 4, 9, 10),
                        summer_months: tuple[int, ...] = (5, 6, 7, 8),
                        winter_low_hours: tuple[int, ...] | None = None,
@@ -206,7 +206,7 @@ def build_tariff_table(winter_low: float, winter_high_week: float, winter_high_w
     return tariff_table
 
 
-def tariff_table_to_hourly(tariff_table: np.ndarray, year: int):
+def tariff_table_to_hourly(tariff_table: np.ndarray[float], year: int):
     """
     Create hourly prices for tariff table in the given year
 
@@ -299,7 +299,7 @@ def get_yearly_prices(year, sell_prices, buy_prices, tariff_table, start_year, y
     return sell_output, buy_output
 
 
-def is_real_numbers(arr: np.ndarray):
+def is_real_numbers(arr: np.ndarray[Any, Any]):
     """
     check if the dtype of the given array is a type corresponding to real numbers
     :param arr: the numpy array