Saving cuts in dev directory

AntaresSimulatorTeam · Dec 10, 2024 · dd4f35f · dd4f35f
1 parent 5034eaa
commit dd4f35f
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Showing 2 changed files with 14 additions and 9 deletions.
diff --git a/src/multi_stock_bellman_value_calculation.py b/src/multi_stock_bellman_value_calculation.py
@@ -513,6 +513,7 @@ def get_all_costs(
     list_models: Dict[TimeScenarioIndex, AntaresProblem],
     multi_stock_management: MultiStockManagement,
     controls_list: np.ndarray,
+    saving_dir: Optional[str] = None,
     verbose: bool = False,
     already_init: bool = False,
     keep_intermed_res: bool = False,
@@ -535,7 +536,9 @@ def get_all_costs(
     tot_iter = 0
     times = []
     n_reservoirs = len(multi_stock_management.dict_reservoirs)
-    filename = "get_all_costs_run.pkl"
+    if keep_intermed_res or already_init:
+        assert saving_dir is not None
+        filename = saving_dir + "/get_all_costs_run.pkl"
 
     # Initializing the n_weeks*n_scenarios*n_controls*n_stocks values to fill
     shape_controls = list(controls_list.shape)
@@ -594,7 +597,7 @@ def Lget_costs(
     load_from_protos: bool = False,
     prefix: str = "",
 ) -> tuple[np.ndarray, np.ndarray, np.ndarray]:
-    filename = f"{prefix}get_all_costs_run_{output_path.replace('/','_')[-27:]}.pkl"
+    filename = f"{saving_directory}/{prefix}get_all_costs_run_{output_path.replace('/','_')[-27:]}.pkl"
 
     # Initializing the n_weeks*n_scenarios*n_controls(*n_stocks) values to fill
     shape_controls = list(controls_list.shape)
@@ -1691,6 +1694,7 @@ def sddp_cutting_planes(
         param.len_scenario,
         julia_reservoirs,
         julia_capp,
+        saving_dir,
         normalization["euro"],
         normalization["energy"],
     )
@@ -1704,6 +1708,7 @@ def sddp_cutting_planes(
             param.len_scenario,
             julia_reservoirs,
             julia_capp,
+            saving_dir,
             normalization["euro"],
             normalization["energy"],
         )

diff --git a/src/sddp.jl b/src/sddp.jl
@@ -34,7 +34,7 @@ struct Normalizer
 end
 
 # Function to convert Python data to Julia structures
-function formater(n_weeks, n_scenarios, reservoirs_data, costs_approx_data, norm_euros::Float64=1e7, norm_enrgy::Float64=1e5)
+function formater(n_weeks, n_scenarios, reservoirs_data, costs_approx_data, saving_dir::String, norm_euros::Float64=1e7, norm_enrgy::Float64=1e5)
     round_energy = 4
     round_euro = 8
     round_price = 5
@@ -64,7 +64,7 @@ function formater(n_weeks, n_scenarios, reservoirs_data, costs_approx_data, norm
             round.(pyconvert(Matrix, costs_approx_data[i,j]["duals"])   /norm_price, digits=round_price), # € / MWh
             ) for j in 1:size_ca_data[2]] for i in 1:size_ca_data[1]]
 
-    return (n_weeks, n_scenarios, reservoirs, costs_approx, norms)
+    return (n_weeks, n_scenarios, reservoirs, costs_approx, norms, saving_dir)
 end
 
 
@@ -163,17 +163,17 @@ function stability_report(model)
     return SDDP.numerical_stability_report(model)
 end
 
-function reinit_cuts(n_weeks::Int, n_scenarios::Int, reservoirs::Vector{Main.Jl_SDDP.Reservoir}, costs_approx::Vector{Vector{Main.Jl_SDDP.LinInterp}}, norms::Normalizer)
+function reinit_cuts(n_weeks::Int, n_scenarios::Int, reservoirs::Vector{Main.Jl_SDDP.Reservoir}, costs_approx::Vector{Vector{Main.Jl_SDDP.LinInterp}}, norms::Normalizer, saving_dir::String)
     model = generate_model(n_weeks, n_scenarios, reservoirs, costs_approx, norms)
-    SDDP.write_cuts_to_file(model, "sddp_current_cuts")
+    SDDP.write_cuts_to_file(model, saving_dir*"/sddp_current_cuts")
 end
 
-function manage_reservoirs(n_weeks::Int, n_scenarios::Int, reservoirs::Vector{Main.Jl_SDDP.Reservoir}, costs_approx::Vector{Vector{Main.Jl_SDDP.LinInterp}}, norms::Normalizer)
+function manage_reservoirs(n_weeks::Int, n_scenarios::Int, reservoirs::Vector{Main.Jl_SDDP.Reservoir}, costs_approx::Vector{Vector{Main.Jl_SDDP.LinInterp}}, norms::Normalizer, saving_dir::String)
     model = generate_model(n_weeks, n_scenarios, reservoirs, costs_approx, norms)
-    SDDP.read_cuts_from_file(model, "sddp_current_cuts")
+    SDDP.read_cuts_from_file(model, saving_dir*"/sddp_current_cuts")
     # Training the model
     SDDP.train(model, stopping_rules = [SDDP.BoundStalling(40, 1e1)], iteration_limit = 700, cut_type = SDDP.MULTI_CUT)
-    SDDP.write_cuts_to_file(model, "sddp_current_cuts")
+    SDDP.write_cuts_to_file(model, saving_dir*"/sddp_current_cuts")
 
     #Simulating
     simulation_results = get_trajectory(n_weeks, n_scenarios, reservoirs, model, norms)