Change scenario type in build problem

src/andromede/simulation/__init__.py

@@ -14,7 +14,12 @@
     BendersDecomposedProblem,
     build_benders_decomposed_problem,
 )
-from .optimization import BlockBorderManagement, OptimizationProblem, build_problem
+from .optimization import (
+    BlockBorderManagement,
+    OptimizationProblem,
+    build_problem,
+    scenario_playlist,
+)
 from .output_values import BendersSolution, OutputValues
 from .runner import BendersRunner, MergeMPSRunner
 from .strategy import MergedProblemStrategy, ModelSelectionStrategy

src/andromede/simulation/benders_decomposed.py

@@ -207,7 +207,7 @@ def build_benders_decomposed_problem(
     network: Network,
     database: DataBase,
     blocks: List[TimeBlock],
-    scenarios: int,
+    scenarios: List[int],
     *,
     border_management: BlockBorderManagement = BlockBorderManagement.CYCLE,
     solver_id: str = "GLOP",
@@ -217,6 +217,7 @@ def build_benders_decomposed_problem(
 
     Returns a Benders Decomposed problem
     """
+    null_scenario: List[int] = []
 
     # Benders Decomposed Master Problem
     master = build_problem(
@@ -225,7 +226,7 @@ def build_benders_decomposed_problem(
         null_time_block := TimeBlock(  # Not necessary for master, but list must be non-empty
             0, [0]
         ),
-        null_scenario := 0,  # Not necessary for master
+        null_scenario,  # Not necessary for master
         problem_name="master",
         border_management=border_management,
         solver_id=solver_id,

src/andromede/simulation/optimization.py

@@ -19,7 +19,7 @@
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from enum import Enum
-from typing import Dict, Iterable, List, Optional
+from typing import Dict, Iterable, List, Optional, Union
 
 import ortools.linear_solver.pywraplp as lp
 
@@ -69,8 +69,9 @@ def _get_parameter_value(
     name: str,
 ) -> float:
     data = context.database.get_data(component_id, name)
+    absolute_scenario = context.scenario_to_absolute_scenario(scenario)
     absolute_timestep = context.block_timestep_to_absolute_timestep(block_timestep)
-    return data.get_value(absolute_timestep, scenario)
+    return data.get_value(absolute_timestep, absolute_scenario)
 
 
 # TODO: Maybe add the notion of constant parameter in the model
@@ -304,7 +305,7 @@ def __init__(
         network: Network,
         database: DataBase,
         block: TimeBlock,
-        scenarios: int,
+        scenarios: List[int],
         border_management: BlockBorderManagement,
     ):
         self._network = network
@@ -323,9 +324,12 @@ def network(self) -> Network:
         return self._network
 
     @property
-    def scenarios(self) -> int:
+    def scenarios(self) -> List[int]:
         return self._scenarios
 
+    def scenario_length(self) -> int:
+        return len(self._scenarios)
+
     def block_length(self) -> int:
         return len(self._block.timesteps)
 
@@ -337,6 +341,12 @@ def connection_fields_expressions(self) -> Dict[PortFieldKey, List[ExpressionNod
     def block_timestep_to_absolute_timestep(self, block_timestep: int) -> int:
         return self._block.timesteps[block_timestep]
 
+    def scenario_to_absolute_scenario(self, scenario: int) -> int:
+        if len(self.scenarios) == 0:
+            return 0
+        else:
+            return self.scenarios[scenario]
+
     @property
     def database(self) -> DataBase:
         return self._database
@@ -351,7 +361,7 @@ def get_time_indices(self, index_structure: IndexingStructure) -> Iterable[int]:
         return range(self.block_length()) if index_structure.time else range(1)
 
     def get_scenario_indices(self, index_structure: IndexingStructure) -> Iterable[int]:
-        return range(self.scenarios) if index_structure.scenario else range(1)
+        return range(self.scenario_length()) if index_structure.scenario else range(1)
 
     # TODO: API to improve, variable_structure guides which of the indices block_timestep and scenario should be used
     def get_component_variable(
@@ -509,8 +519,8 @@ def _create_objective(
     for term in linear_expr.terms.values():
         # TODO : How to handle the scenario operator in a general manner ?
         if isinstance(term.scenario_operator, Expectation):
-            weight = 1 / opt_context.scenarios
-            scenario_ids = range(opt_context.scenarios)
+            weight = 1 / opt_context.scenario_length()
+            scenario_ids = range(opt_context.scenario_length())
         else:
             weight = 1
             scenario_ids = range(1)
@@ -761,7 +771,7 @@ def _create_variables(self) -> None:
                         scenario_suffix = (
                             f"_s{scenario}"
                             if var_indexing.is_scenario_varying()
-                            and (self.context.scenarios > 1)
+                            and (self.context.scenario_length() > 1)
                             else ""
                         )
 
@@ -853,7 +863,7 @@ def build_problem(
     network: Network,
     database: DataBase,
     block: TimeBlock,
-    scenarios: int,
+    scenarios: List[int],
     *,
     problem_name: str = "optimization_problem",
     border_management: BlockBorderManagement = BlockBorderManagement.CYCLE,
@@ -872,3 +882,7 @@ def build_problem(
     )
 
     return OptimizationProblem(problem_name, solver, opt_context, problem_strategy)
+
+
+def scenario_playlist(scenarios: int) -> List[int]:
+    return list(range(scenarios))

tests/functional/test_andromede.py

@@ -34,6 +34,7 @@
     OutputValues,
     TimeBlock,
     build_problem,
+    scenario_playlist,
 )
 from andromede.study import (
     ConstantData,
@@ -89,7 +90,7 @@ def test_timeseries() -> None:
     time_block = TimeBlock(1, [0, 1])
     scenarios = 1
 
-    problem = build_problem(network, database, time_block, scenarios)
+    problem = build_problem(network, database, time_block, scenario_playlist(scenarios))
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -161,15 +162,15 @@ def test_variable_bound() -> None:
 
     network = create_one_node_network(generator_model)
     database = create_simple_database(max_generation=200)
-    problem = build_problem(network, database, TimeBlock(1, [0]), 1)
+    problem = build_problem(network, database, TimeBlock(1, [0]), scenario_playlist(1))
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
     assert problem.solver.Objective().Value() == 3000
 
     network = create_one_node_network(generator_model)
     database = create_simple_database(max_generation=80)
-    problem = build_problem(network, database, TimeBlock(1, [0]), 1)
+    problem = build_problem(network, database, TimeBlock(1, [0]), scenario_playlist(1))
     status = problem.solver.Solve()
     assert status == problem.solver.INFEASIBLE  # Infeasible
 
@@ -179,15 +180,19 @@ def test_variable_bound() -> None:
         ValueError,
         match="Upper and lower bounds of variable G_generation have the same value: 0",
     ):
-        problem = build_problem(network, database, TimeBlock(1, [0]), 1)
+        problem = build_problem(
+            network, database, TimeBlock(1, [0]), scenario_playlist(1)
+        )
 
     network = create_one_node_network(generator_model)
     database = create_simple_database(max_generation=-10)
     with pytest.raises(
         ValueError,
         match=r"Upper bound \(-10\) must be strictly greater than lower bound \(0\) for variable G_generation",
     ):
-        problem = build_problem(network, database, TimeBlock(1, [0]), 1)
+        problem = build_problem(
+            network, database, TimeBlock(1, [0]), scenario_playlist(1)
+        )
 
 
 def generate_data(
@@ -251,7 +256,7 @@ def short_term_storage_base(efficiency: float, horizon: int) -> None:
         network,
         database,
         time_blocks[0],
-        scenarios,
+        scenario_playlist(scenarios),
         border_management=BlockBorderManagement.CYCLE,
     )
     status = problem.solver.Solve()

tests/functional/test_andromede_yml.py

@@ -11,6 +11,7 @@
     OutputValues,
     TimeBlock,
     build_problem,
+    scenario_playlist,
 )
 from andromede.study import (
     ConstantData,
@@ -82,7 +83,9 @@ def test_basic_balance(lib: Library) -> None:
     network.connect(PortRef(gen, "balance_port"), PortRef(node, "balance_port"))
 
     scenarios = 1
-    problem = build_problem(network, database, TimeBlock(1, [0]), scenarios)
+    problem = build_problem(
+        network, database, TimeBlock(1, [0]), scenario_playlist(scenarios)
+    )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -134,7 +137,9 @@ def test_link(lib: Library) -> None:
     network.connect(PortRef(link, "out_port"), PortRef(node2, "balance_port"))
 
     scenarios = 1
-    problem = build_problem(network, database, TimeBlock(1, [0]), scenarios)
+    problem = build_problem(
+        network, database, TimeBlock(1, [0]), scenario_playlist(scenarios)
+    )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -192,7 +197,9 @@ def test_stacking_generation(lib: Library) -> None:
     network.connect(PortRef(gen2, "balance_port"), PortRef(node1, "balance_port"))
 
     scenarios = 1
-    problem = build_problem(network, database, TimeBlock(1, [0]), scenarios)
+    problem = build_problem(
+        network, database, TimeBlock(1, [0]), scenario_playlist(scenarios)
+    )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -232,7 +239,7 @@ def test_spillage(lib: Library) -> None:
     network.connect(PortRef(gen1, "balance_port"), PortRef(node, "balance_port"))
     network.connect(PortRef(spillage, "balance_port"), PortRef(node, "balance_port"))
 
-    problem = build_problem(network, database, TimeBlock(0, [1]), 1)
+    problem = build_problem(network, database, TimeBlock(0, [1]), scenario_playlist(1))
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -322,7 +329,7 @@ def test_min_up_down_times(lib: Library) -> None:
         network,
         database,
         time_block,
-        scenarios,
+        scenario_playlist(scenarios),
         border_management=BlockBorderManagement.CYCLE,
     )
     status = problem.solver.Solve()
@@ -380,7 +387,7 @@ def test_changing_demand(lib: Library) -> None:
         network,
         database,
         time_block,
-        scenarios,
+        scenario_playlist(scenarios),
         border_management=BlockBorderManagement.CYCLE,
     )
     status = problem.solver.Solve()
@@ -472,7 +479,7 @@ def test_min_up_down_times_2(lib: Library) -> None:
         network,
         database,
         time_block,
-        scenarios,
+        scenario_playlist(scenarios),
         border_management=BlockBorderManagement.CYCLE,
     )
     status = problem.solver.Solve()

tests/functional/test_performance.py

@@ -24,7 +24,7 @@
     NODE_BALANCE_MODEL,
 )
 from andromede.model import float_parameter, float_variable, model
-from andromede.simulation import TimeBlock, build_problem
+from andromede.simulation import TimeBlock, build_problem, scenario_playlist
 from andromede.study import (
     ConstantData,
     DataBase,
@@ -70,7 +70,9 @@ def test_large_sum_inside_model_with_loop() -> None:
         cost_model = create_component(model=SIMPLE_COST_MODEL, id="simple_cost")
         network.add_component(cost_model)
 
-        problem = build_problem(network, database, time_blocks[0], scenarios)
+        problem = build_problem(
+            network, database, time_blocks[0], scenario_playlist(scenarios)
+        )
         status = problem.solver.Solve()
 
         assert status == problem.solver.OPTIMAL
@@ -106,7 +108,9 @@ def test_large_sum_outside_model_with_loop() -> None:
     )
     network.add_component(simple_model)
 
-    problem = build_problem(network, database, time_blocks[0], scenarios)
+    problem = build_problem(
+        network, database, time_blocks[0], scenario_playlist(scenarios)
+    )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -151,7 +155,9 @@ def test_large_sum_inside_model_with_sum_operator() -> None:
     cost_model = create_component(model=SIMPLE_COST_MODEL, id="simple_cost")
     network.add_component(cost_model)
 
-    problem = build_problem(network, database, time_blocks[0], scenarios)
+    problem = build_problem(
+        network, database, time_blocks[0], scenario_playlist(scenarios)
+    )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -197,7 +203,9 @@ def test_large_sum_of_port_connections() -> None:
         )
 
     with pytest.raises(RecursionError, match="maximum recursion depth exceeded"):
-        problem = build_problem(network, database, time_block, scenarios)
+        problem = build_problem(
+            network, database, time_block, scenario_playlist(scenarios)
+        )
 
         # Won't run because last statement will raise the error
         status = problem.solver.Solve()
@@ -235,7 +243,7 @@ def test_basic_balance_on_whole_year() -> None:
     network.connect(PortRef(demand, "balance_port"), PortRef(node, "balance_port"))
     network.connect(PortRef(gen, "balance_port"), PortRef(node, "balance_port"))
 
-    problem = build_problem(network, database, time_block, scenarios)
+    problem = build_problem(network, database, time_block, scenario_playlist(scenarios))
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
@@ -273,7 +281,7 @@ def test_basic_balance_on_whole_year_with_large_sum() -> None:
     network.connect(PortRef(demand, "balance_port"), PortRef(node, "balance_port"))
     network.connect(PortRef(gen, "balance_port"), PortRef(node, "balance_port"))
 
-    problem = build_problem(network, database, time_block, scenarios)
+    problem = build_problem(network, database, time_block, scenario_playlist(scenarios))
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL

tests/functional/test_stochastic.py

@@ -20,7 +20,7 @@
     THERMAL_CLUSTER_MODEL_DHD,
     THERMAL_CLUSTER_MODEL_HD,
 )
-from andromede.simulation import TimeBlock, build_problem
+from andromede.simulation import TimeBlock, build_problem, scenario_playlist
 from andromede.study import (
     ConstantData,
     DataBase,
@@ -123,7 +123,7 @@ def test_stochastic_model_with_HD_for_thermal_startup(
     network.connect(PortRef(peak, "balance_port"), PortRef(node, "balance_port"))
 
     for block in time_blocks:  # TODO : To manage blocks simply for now
-        problem = build_problem(network, database, block, scenarios)
+        problem = build_problem(network, database, block, scenario_playlist(scenarios))
         status = problem.solver.Solve()
 
         assert (
@@ -189,7 +189,7 @@ def test_stochastic_model_with_DH_for_thermal_startup(
     network.connect(PortRef(peak, "balance_port"), PortRef(node, "balance_port"))
 
     for block in time_blocks:  # TODO : To manage blocks simply for now
-        problem = build_problem(network, database, block, scenarios)
+        problem = build_problem(network, database, block, scenario_playlist(scenarios))
         status = problem.solver.Solve()
 
         assert (