Clean src

src/display.py

@@ -62,9 +62,7 @@ def draw_usage_values(
                 marker=dict(symbol="circle"),
                 showlegend=True,
             )
-            for i, (area, mng) in enumerate(
-                multi_stock_management.dict_reservoirs.items()
-            )
+            for i, (_, _) in enumerate(multi_stock_management.dict_reservoirs.items())
         ]
         + [
             go.Scatter(
@@ -76,9 +74,7 @@ def draw_usage_values(
                 line=dict(dash="dash"),
                 showlegend=True,
             )
-            for i, (area, mng) in enumerate(
-                multi_stock_management.dict_reservoirs.items()
-            )
+            for i, (_, mng) in enumerate(multi_stock_management.dict_reservoirs.items())
         ]
         + [
             go.Scatter(
@@ -90,9 +86,7 @@ def draw_usage_values(
                 line=dict(dash="dash"),
                 showlegend=True,
             )
-            for i, (area, mng) in enumerate(
-                multi_stock_management.dict_reservoirs.items()
-            )
+            for i, (_, mng) in enumerate(multi_stock_management.dict_reservoirs.items())
         ],
         layout=dict(title=f"Usage Values"),
     )
@@ -166,7 +160,7 @@ def draw_uvs_sddp(
                 showlegend=True,
                 visible=(r == 0),
             )
-            for r, res in enumerate(reservoirs)
+            for r, _ in enumerate(reservoirs)
         ]
         + [
             go.Scatter(

src/estimation.py

@@ -311,7 +311,6 @@ def __init__(
         costs: np.ndarray,
         duals: np.ndarray,
         correlations: Optional[np.ndarray] = None,
-        interp_mode: bool = False,
     ) -> None:
         """
         Instanciates a LinearCostEstimator
@@ -385,7 +384,6 @@ def update(
         inputs: np.ndarray,
         costs: np.ndarray,
         duals: np.ndarray,
-        interp_mode: bool = False,
     ) -> None:
         """
         Updates the parameters of the Linear Interpolators
@@ -407,7 +405,7 @@ def update(
                     duals=duals,
                 )
 
-    def enrich_estimator(self, n_splits: int = 3) -> None:
+    def enrich_estimator(self) -> None:
         """
         Adds 'mid_cuts' to our cost estimator to smoothen the curves and (hopefully) accelerate convergence
 

src/functions_iterative.py

@@ -391,7 +391,6 @@ def init_iterative_calculation(
         stock_discretization=X,
     )
 
-    i = 0
     gap = 1e3
     fin = time()
     tot_t.append(fin - debut)

src/hyperplane_interpolation.py

@@ -122,10 +122,6 @@ def interpolate_between(
     return mlr, data
 
 
-mlrs: list = []
-datas: list = []
-
-
 def enrich_by_interpolation(
     controls_init: np.ndarray, costs: np.ndarray, slopes: np.ndarray, n_splits: int = 3
 ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:

src/launch_calculation.py

@@ -50,7 +50,7 @@ def calculate_bellman_values(
 
     elif method == "precalculated":
         # or with precalulated reward
-        vb, G = calculate_bellman_value_with_precalculated_reward(
+        vb, _ = calculate_bellman_value_with_precalculated_reward(
             len_controls=len_controls,
             param=param,
             reservoir_management=reservoir_management,
@@ -61,7 +61,7 @@ def calculate_bellman_values(
 
     elif method == "iterative":
         # or with iterative algorithm
-        vb, G, _, _, controls_upper, traj = itr_control(
+        vb, _, _, _, _, _ = itr_control(
             param=param,
             reservoir_management=reservoir_management,
             output_path=output_path,