See #ANT-958 Fixes after PR review

src/andromede/model/parameter.py

@@ -13,7 +13,7 @@
 from dataclasses import dataclass
 
 from andromede.expression.indexing_structure import IndexingStructure
-from andromede.model.common import ValueType, ProblemContext
+from andromede.model.common import ValueType
 
 
 @dataclass(frozen=True)
@@ -27,20 +27,17 @@ class Parameter:
     name: str
     type: ValueType
     structure: IndexingStructure
-    context: ProblemContext
 
 
 def int_parameter(
     name: str,
     structure: IndexingStructure = IndexingStructure(True, True),
-    context: ProblemContext = ProblemContext.operational,
 ) -> Parameter:
-    return Parameter(name, ValueType.INTEGER, structure, context)
+    return Parameter(name, ValueType.INTEGER, structure)
 
 
 def float_parameter(
     name: str,
     structure: IndexingStructure = IndexingStructure(True, True),
-    context: ProblemContext = ProblemContext.operational,
 ) -> Parameter:
-    return Parameter(name, ValueType.FLOAT, structure, context)
+    return Parameter(name, ValueType.FLOAT, structure)

src/andromede/simulation/optimization.py

@@ -280,13 +280,13 @@ class BlockBorderManagement(Enum):
 class SolverVariableInfo:
     """
     Helper class for constructing the structure file
-    for Bender solver. It keeps track of the corresponding
+    for Benders solver. It keeps track of the corresponding
     column of the variable in the MPS format as well as if it is
     present in the objective function or not
     """
 
     name: str
-    column: int
+    column_id: int
     is_in_objective: bool
 
 
@@ -667,16 +667,14 @@ class OptimizationProblem:
     class Type(Enum):
         """
         Class to specify the type of the created problem:
-            - simulator: Creates a Antares Simulator problem with only operational variables and constraints
-            - xpansion_master: Creates a Xpansion master problem only
-            - xpansion_subproblem: Creates Xpansion sub-problems only
-            - xpansion_merged: Creates a merged Xpansion master/subproblem
+            - master: Creates a Xpansion master problem with investment variables and constraints only
+            - subproblem: Creates Xpansion sub-problems with operational variables and constraints only
+            - merged: Creates a Antares Simulator/ Xpansion problem with both
         """
 
-        simulator = 0
-        xpansion_merged = 1
-        xpansion_master = 2
-        xpansion_subproblem = 3
+        merged = 0
+        master = 1
+        subproblem = 2
 
     name: str
     solver: lp.Solver
@@ -688,7 +686,7 @@ def __init__(
         name: str,
         solver: lp.Solver,
         opt_context: OptimizationContext,
-        opt_type: Type = Type.simulator,
+        opt_type: Type = Type.merged,
     ) -> None:
         self.name = name
         self.solver = solver
@@ -735,7 +733,7 @@ def _create_variables(self) -> None:
 
             for model_var in model.variables.values():
                 if (
-                    self.type == OptimizationProblem.Type.xpansion_master
+                    self.type == OptimizationProblem.Type.master
                     and model_var.context == ProblemContext.operational
                 ):
                     # Xpansion Master Problem only takes investment variables and parameters
@@ -784,14 +782,14 @@ def _create_constraints(self) -> None:
         for component in self.context.network.all_components:
             for constraint in component.model.get_all_constraints():
                 if (
-                    self.type == OptimizationProblem.Type.xpansion_master
+                    self.type == OptimizationProblem.Type.master
                     and constraint.context == ProblemContext.operational
                 ):
                     # Xpansion Master Problem only takes investment constraints
                     continue
 
                 elif (
-                    self.type == OptimizationProblem.Type.xpansion_subproblem
+                    self.type == OptimizationProblem.Type.subproblem
                     and constraint.context == ProblemContext.investment
                 ):
                     # Xpansion SubProblems only take operational constraints
@@ -825,7 +823,7 @@ def _create_objectives(self) -> None:
             model = component.model
 
             if (
-                self.type != OptimizationProblem.Type.xpansion_master
+                self.type != OptimizationProblem.Type.master
                 and model.objective_operational_contribution is not None
             ):
                 # Xpansion SubProblems only take the operational contribution
@@ -838,7 +836,7 @@ def _create_objectives(self) -> None:
                 )
 
             if (
-                self.type != OptimizationProblem.Type.xpansion_subproblem
+                self.type != OptimizationProblem.Type.subproblem
                 and model.objective_investment_contribution is not None
             ):
                 # Xpansion Master Problem only takes the investment contribution
@@ -866,7 +864,7 @@ def build_problem(
     problem_name: str = "optimization_problem",
     border_management: BlockBorderManagement = BlockBorderManagement.CYCLE,
     solver_id: str = "GLOP",
-    problem_type: OptimizationProblem.Type = OptimizationProblem.Type.simulator,
+    problem_type: OptimizationProblem.Type = OptimizationProblem.Type.merged,
 ) -> OptimizationProblem:
     """
     Entry point to build the optimization problem for a time period.

src/andromede/simulation/xpansion.py

@@ -12,7 +12,7 @@
 
 """
 The xpansion module extends the optimization module
-with Bender solver related functions
+with Benders solver related functions
 """
 
 import json
@@ -65,7 +65,7 @@ def export_structure(self) -> str:
             if solver_var_info.is_in_objective:
                 problem_to_candidates["master"][
                     solver_var_info.name
-                ] = solver_var_info.column
+                ] = solver_var_info.column_id
                 candidates.add(solver_var_info.name)
 
         for problem in self.subproblems:
@@ -76,7 +76,7 @@ def export_structure(self) -> str:
                     # If candidate was identified in master
                     problem_to_candidates[problem.name][
                         solver_var_info.name
-                    ] = solver_var_info.column
+                    ] = solver_var_info.column_id
 
         structure_str = ""
         for problem_name, candidate_to_index in problem_to_candidates.items():
@@ -155,6 +155,7 @@ def run(
             # TODO Maybe a more robust check and/or return value?
             # For now, it won't look anywhere else because a new
             # architecture should be discussed
+            print(root_dir + "/bin/benders executable not found. Returning True")
             return True
 
         os.chdir(path)
@@ -193,7 +194,7 @@ def build_xpansion_problem(
         problem_name="master",
         border_management=border_management,
         solver_id=solver_id,
-        problem_type=OptimizationProblem.Type.xpansion_master,
+        problem_type=OptimizationProblem.Type.master,
     )
 
     # Xpansion Sub-problems
@@ -205,7 +206,7 @@ def build_xpansion_problem(
         problem_name="subproblem",
         border_management=border_management,
         solver_id=solver_id,
-        problem_type=OptimizationProblem.Type.xpansion_subproblem,
+        problem_type=OptimizationProblem.Type.subproblem,
     )
 
     return XpansionProblem(master, [subproblem])

tests/andromede/test_xpansion.py

@@ -59,9 +59,9 @@
 INVESTMENT = ProblemContext.investment
 OPERATIONAL = ProblemContext.operational
 
-XPANSION_MASTER = OptimizationProblem.Type.xpansion_master
-XPANSION_SUBPBL = OptimizationProblem.Type.xpansion_subproblem
-XPANSION_MERGED = OptimizationProblem.Type.xpansion_merged
+MASTER = OptimizationProblem.Type.master
+SUBPBL = OptimizationProblem.Type.subproblem
+MERGED = OptimizationProblem.Type.merged
 
 
 @pytest.fixture
@@ -70,7 +70,7 @@ def thermal_candidate() -> Model:
         id="GEN",
         parameters=[
             float_parameter("op_cost", CONSTANT),
-            float_parameter("invest_cost", CONSTANT, INVESTMENT),
+            float_parameter("invest_cost", CONSTANT),
         ],
         variables=[
             float_variable("generation", lower_bound=literal(0)),
@@ -108,8 +108,8 @@ def wind_cluster_candidate() -> Model:
         id="WIND_CLUSTER",
         parameters=[
             float_parameter("op_cost", CONSTANT),
-            float_parameter("invest_cost", CONSTANT, INVESTMENT),
-            float_parameter("p_max_per_unit", CONSTANT, INVESTMENT),
+            float_parameter("invest_cost", CONSTANT),
+            float_parameter("p_max_per_unit", CONSTANT),
         ],
         variables=[
             float_variable("generation", lower_bound=literal(0)),
@@ -221,12 +221,14 @@ def test_generation_xpansion_single_time_step_single_scenario(
 
     scenarios = 1
     problem = build_problem(
-        network, database, TimeBlock(1, [0]), scenarios, problem_type=XPANSION_MERGED
+        network, database, TimeBlock(1, [0]), scenarios, problem_type=MERGED
     )
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
-    assert problem.solver.Objective().Value() == 490 * 100 + 100 * 10 + 200 * 40
+    assert problem.solver.Objective().Value() == pytest.approx(
+        490 * 100 + 100 * 10 + 200 * 40
+    )
 
     output = OutputValues(problem)
     expected_output = OutputValues()
@@ -298,8 +300,8 @@ def test_two_candidates_xpansion_single_time_step_single_scenario(
     status = problem.solver.Solve()
 
     assert status == problem.solver.OPTIMAL
-    assert problem.solver.Objective().Value() == (45 * 200) + (490 * 100 + 10 * 100) + (
-        200 * 100 + 10 * 100
+    assert problem.solver.Objective().Value() == pytest.approx(
+        (45 * 200) + (490 * 100 + 10 * 100) + (200 * 100 + 10 * 100)
     )
 
     output = OutputValues(problem)
@@ -321,7 +323,7 @@ def test_model_export_xpansion_single_time_step_single_scenario(
 ) -> None:
     """
     Same test as before but this time we separate master/subproblem and
-    export the problems in MPS format to be solved by the Bender solver in Xpansion
+    export the problems in MPS format to be solved by the Benders solver in Xpansion
     """
 
     database = DataBase()
@@ -429,9 +431,11 @@ def test_generation_xpansion_two_time_steps_two_scenarios(
     # assert (
     #     problem.solver.NumConstraints() == 3 * scenarios * horizon
     # )  # Flow balance, Max generation for each cluster
-    assert problem.solver.Objective().Value() == 490 * 300 + 0.5 * (
-        10 * 300 + 10 * 300 + 40 * 200
-    ) + 0.5 * (10 * 200 + 10 * 300 + 40 * 100)
+    assert problem.solver.Objective().Value() == pytest.approx(
+        490 * 300
+        + 0.5 * (10 * 300 + 10 * 300 + 40 * 200)
+        + 0.5 * (10 * 200 + 10 * 300 + 40 * 100)
+    )
 
     output = OutputValues(problem)
     expected_output = OutputValues()