Organize test fixtures; handle infeasibility in DropRedundant

tests/fixtures/__init__.py

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+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.

tests/fixtures/infeasible.py

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+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+
+from typing import Any
+
+from pyomo import environ as pe
+
+from miplearn.instance import Instance
+from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.pyomo.base import BasePyomoSolver
+from tests.solvers import _is_subclass_or_instance
+
+
+class InfeasiblePyomoInstance(Instance):
+    def to_model(self) -> pe.ConcreteModel:
+        model = pe.ConcreteModel()
+        model.x = pe.Var([0], domain=pe.Binary)
+        model.OBJ = pe.Objective(expr=model.x[0], sense=pe.maximize)
+        model.eq = pe.Constraint(expr=model.x[0] >= 2)
+        return model
+
+
+class InfeasibleGurobiInstance(Instance):
+    def to_model(self) -> Any:
+        import gurobipy as gp
+        from gurobipy import GRB
+
+        model = gp.Model()
+        x = model.addVars(1, vtype=GRB.BINARY, name="x")
+        model.addConstr(x[0] >= 2)
+        model.setObjective(x[0])
+        return model
+
+
+def get_infeasible_instance(solver):
+    if _is_subclass_or_instance(solver, BasePyomoSolver):
+        return InfeasiblePyomoInstance()
+    if _is_subclass_or_instance(solver, GurobiSolver):
+        return InfeasibleGurobiInstance()

tests/fixtures/redundant.py

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+#  MIPLearn: Extensible Framework for Learning-Enhanced Mixed-Integer Optimization
+#  Copyright (C) 2020, UChicago Argonne, LLC. All rights reserved.
+#  Released under the modified BSD license. See COPYING.md for more details.
+from typing import Any
+
+from miplearn import Instance, BasePyomoSolver, GurobiSolver
+import pyomo.environ as pe
+
+from tests.solvers import _is_subclass_or_instance
+
+
+class PyomoInstanceWithRedundancy(Instance):
+    def to_model(self) -> pe.ConcreteModel:
+        model = pe.ConcreteModel()
+        model.x = pe.Var([0, 1], domain=pe.Binary)
+        model.OBJ = pe.Objective(expr=model.x[0] + model.x[1], sense=pe.maximize)
+        model.eq1 = pe.Constraint(expr=model.x[0] + model.x[1] <= 1)
+        model.eq2 = pe.Constraint(expr=model.x[0] + model.x[1] <= 2)
+        return model
+
+
+class GurobiInstanceWithRedundancy(Instance):
+    def to_model(self) -> Any:
+        import gurobipy as gp
+        from gurobipy import GRB
+
+        model = gp.Model()
+        x = model.addVars(2, vtype=GRB.BINARY, name="x")
+        model.addConstr(x[0] + x[1] <= 1)
+        model.addConstr(x[0] + x[1] <= 2)
+        model.setObjective(x[0] + x[1], GRB.MAXIMIZE)
+        return model
+
+
+def get_instance_with_redundancy(solver):
+    if _is_subclass_or_instance(solver, BasePyomoSolver):
+        return PyomoInstanceWithRedundancy()
+    if _is_subclass_or_instance(solver, GurobiSolver):
+        return GurobiInstanceWithRedundancy()