fix type hints in Forecaster

assume/common/forecasts.py

@@ -30,32 +30,32 @@ class Forecaster:
 
     """
 
-    def __init__(self, index: pd.Series):
+    def __init__(self, index: FastIndex):
         self.index = index
 
-    def __getitem__(self, column: str) -> pd.Series:
+    def __getitem__(self, column: str) -> FastSeries:
         """
         Returns the forecast for a given column.
 
         Args:
             column (str): The column of the forecast.
 
         Returns:
-            pd.Series: The forecast.
+            FastSeries: The forecast.
 
         This method returns the forecast for a given column as a pandas Series based on the provided index.
         """
         return FastSeries(value=0.0, index=self.index)
 
-    def get_availability(self, unit: str) -> pd.Series:
+    def get_availability(self, unit: str) -> FastSeries:
         """
         Returns the availability of a given unit as a pandas Series based on the provided index.
 
         Args:
             unit (str): The unit.
 
         Returns:
-            pd.Series: The availability of the unit.
+            FastSeries: The availability of the unit.
 
         Example:
         >>> forecaster = Forecaster(index=pd.Series([1, 2, 3]))
@@ -65,7 +65,7 @@ def get_availability(self, unit: str) -> pd.Series:
 
         return self[f"availability_{unit}"]
 
-    def get_price(self, fuel_type: str) -> pd.Series:
+    def get_price(self, fuel_type: str) -> FastSeries:
         """
         Returns the price for a given fuel type as a pandas Series or zeros if the type does
         not exist.
@@ -74,7 +74,7 @@ def get_price(self, fuel_type: str) -> pd.Series:
             fuel_type (str): The fuel type.
 
         Returns:
-            pd.Series: The price of the fuel.
+            FastSeries: The price of the fuel.
 
         Example:
             >>> forecaster = Forecaster(index=pd.Series([1, 2, 3]))
@@ -125,9 +125,9 @@ class CsvForecaster(Forecaster):
     def __init__(
         self,
         index: pd.Series,
-        powerplants_units: dict[str, pd.Series] = {},
-        demand_units: dict[str, pd.Series] = {},
-        market_configs: dict[str, pd.Series] = {},
+        powerplants_units: pd.DataFrame,
+        demand_units: pd.DataFrame,
+        market_configs: dict = {},
         *args,
         **kwargs,
     ):
@@ -138,7 +138,7 @@ def __init__(
         self.market_configs = market_configs
         self.forecasts = pd.DataFrame(index=index)
 
-    def __getitem__(self, column: str) -> pd.Series:
+    def __getitem__(self, column: str) -> FastSeries:
         """
         Returns the forecast for a given column.
 
@@ -148,7 +148,7 @@ def __getitem__(self, column: str) -> pd.Series:
             column (str): The column of the forecast.
 
         Returns:
-            pd.Series: The forecast for the given column.
+            FastSeries: The forecast for the given column.
 
         """
 
@@ -441,12 +441,12 @@ class RandomForecaster(CsvForecaster):
 
     Attributes:
         index (pandas.Series): The index of the forecasts.
-        powerplants_units (dict[str, pandas.Series]): The power plants.
+        powerplants_units (pandas.DataFrame): The power plants.
         sigma (float): The standard deviation of the noise.
 
     Args:
         index (pandas.Series): The index of the forecasts.
-        powerplants_units (dict[str, pandas.Series]): The power plants.
+        powerplants_units (pandas.DataFrame): The power plants.
         sigma (float): The standard deviation of the noise.
 
     Example:
@@ -459,17 +459,19 @@ class RandomForecaster(CsvForecaster):
     def __init__(
         self,
         index: pd.Series,
-        powerplants_units: dict[str, pd.Series] = {},
+        powerplants_units: pd.DataFrame,
+        demand_units: pd.DataFrame,
+        market_configs: dict = {},
         sigma: float = 0.02,
         *args,
         **kwargs,
     ):
-        super().__init__(index, powerplants_units, *args, **kwargs)
+        super().__init__(index, powerplants_units, demand_units, market_configs, *args, **kwargs)
 
         self.index = FastIndex(start=index[0], end=index[-1], freq=pd.infer_freq(index))
         self.sigma = sigma
 
-    def __getitem__(self, column: str) -> pd.Series:
+    def __getitem__(self, column: str) -> FastSeries:
         """
         Retrieves forecasted values modified by random noise.
 
@@ -481,7 +483,7 @@ def __getitem__(self, column: str) -> pd.Series:
             column (str): The column of the forecast.
 
         Returns:
-            pd.Series: The forecast modified by random noise.
+            FastSeries: The forecast modified by random noise.
 
         """
 
@@ -549,7 +551,7 @@ def __init__(
         self.demand = self._to_fast_series(demand, "demand")
         self.price_forecast = self._to_fast_series(price_forecast, "price_forecast")
 
-    def __getitem__(self, column: str) -> pd.Series:
+    def __getitem__(self, column: str) -> FastSeries:
         """
         Retrieves forecasted values.
 
@@ -562,7 +564,7 @@ def __getitem__(self, column: str) -> pd.Series:
             column (str): The column for which forecasted values are requested.
 
         Returns:
-            pd.Series: The forecasted values for the specified column.
+            FastSeries: The forecasted values for the specified column.
 
         """