Move tests to separate folder

tests/solvers/test_internal_solver.py

@@ -0,0 +1,219 @@
+#  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.
+
+import logging
+from io import StringIO
+from warnings import warn
+
+import pyomo.environ as pe
+
+from miplearn.solvers import _RedirectOutput
+from miplearn.solvers.gurobi import GurobiSolver
+from miplearn.solvers.pyomo.base import BasePyomoSolver
+from . import (
+    _get_knapsack_instance,
+    _get_internal_solvers,
+    _get_infeasible_instance,
+)
+
+logger = logging.getLogger(__name__)
+
+
+def test_redirect_output():
+    import sys
+
+    original_stdout = sys.stdout
+    io = StringIO()
+    with _RedirectOutput([io]):
+        print("Hello world")
+    assert sys.stdout == original_stdout
+    assert io.getvalue() == "Hello world\n"
+
+
+def test_internal_solver_warm_starts():
+    for solver_class in _get_internal_solvers():
+        logger.info("Solver: %s" % solver_class)
+        instance = _get_knapsack_instance(solver_class)
+        model = instance.to_model()
+        solver = solver_class()
+        solver.set_instance(instance, model)
+        solver.set_warm_start(
+            {
+                "x": {
+                    0: 1.0,
+                    1: 0.0,
+                    2: 0.0,
+                    3: 1.0,
+                }
+            }
+        )
+        stats = solver.solve(tee=True)
+        if stats["Warm start value"] is not None:
+            assert stats["Warm start value"] == 725.0
+        else:
+            warn(f"{solver_class.__name__} should set warm start value")
+
+        solver.set_warm_start(
+            {
+                "x": {
+                    0: 1.0,
+                    1: 1.0,
+                    2: 1.0,
+                    3: 1.0,
+                }
+            }
+        )
+        stats = solver.solve(tee=True)
+        assert stats["Warm start value"] is None
+
+        solver.fix(
+            {
+                "x": {
+                    0: 1.0,
+                    1: 0.0,
+                    2: 0.0,
+                    3: 1.0,
+                }
+            }
+        )
+        stats = solver.solve(tee=True)
+        assert stats["Lower bound"] == 725.0
+        assert stats["Upper bound"] == 725.0
+
+
+def test_internal_solver():
+    for solver_class in _get_internal_solvers():
+        logger.info("Solver: %s" % solver_class)
+
+        instance = _get_knapsack_instance(solver_class)
+        model = instance.to_model()
+        solver = solver_class()
+        solver.set_instance(instance, model)
+
+        stats = solver.solve_lp()
+        assert not solver.is_infeasible()
+        assert round(stats["Optimal value"], 3) == 1287.923
+        assert len(stats["Log"]) > 100
+
+        solution = solver.get_solution()
+        assert round(solution["x"][0], 3) == 1.000
+        assert round(solution["x"][1], 3) == 0.923
+        assert round(solution["x"][2], 3) == 1.000
+        assert round(solution["x"][3], 3) == 0.000
+
+        stats = solver.solve(tee=True)
+        assert not solver.is_infeasible()
+        assert len(stats["Log"]) > 100
+        assert stats["Lower bound"] == 1183.0
+        assert stats["Upper bound"] == 1183.0
+        assert stats["Sense"] == "max"
+        assert isinstance(stats["Wallclock time"], float)
+
+        solution = solver.get_solution()
+        assert solution["x"][0] == 1.0
+        assert solution["x"][1] == 0.0
+        assert solution["x"][2] == 1.0
+        assert solution["x"][3] == 1.0
+
+        # Add a brand new constraint
+        if isinstance(solver, BasePyomoSolver):
+            model.cut = pe.Constraint(expr=model.x[0] <= 0.0, name="cut")
+            solver.add_constraint(model.cut)
+        elif isinstance(solver, GurobiSolver):
+            x = model.getVarByName("x[0]")
+            solver.add_constraint(x <= 0.0, name="cut")
+        else:
+            raise Exception("Illegal state")
+
+        # New constraint should affect solution and should be listed in
+        # constraint ids
+        assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
+        stats = solver.solve()
+        assert stats["Lower bound"] == 1030.0
+
+        assert solver.get_sense() == "max"
+        assert solver.get_constraint_sense("cut") == "<"
+        assert solver.get_constraint_sense("eq_capacity") == "<"
+
+        # Verify slacks
+        assert solver.get_inequality_slacks() == {
+            "cut": 0.0,
+            "eq_capacity": 3.0,
+        }
+
+        if isinstance(solver, GurobiSolver):
+            # Extract the new constraint
+            cobj = solver.extract_constraint("cut")
+
+            # New constraint should no longer affect solution and should no longer
+            # be listed in constraint ids
+            assert solver.get_constraint_ids() == ["eq_capacity"]
+            stats = solver.solve()
+            assert stats["Lower bound"] == 1183.0
+
+            # New constraint should not be satisfied by current solution
+            assert not solver.is_constraint_satisfied(cobj)
+
+            # Re-add constraint
+            solver.add_constraint(cobj)
+
+            # Constraint should affect solution again
+            assert solver.get_constraint_ids() == ["eq_capacity", "cut"]
+            stats = solver.solve()
+            assert stats["Lower bound"] == 1030.0
+
+            # New constraint should now be satisfied
+            assert solver.is_constraint_satisfied(cobj)
+
+            # Relax problem and make cut into an equality constraint
+            solver.relax()
+            solver.set_constraint_sense("cut", "=")
+            stats = solver.solve()
+            assert round(stats["Lower bound"]) == 1030.0
+            assert round(solver.get_dual("eq_capacity")) == 0.0
+
+
+def test_relax():
+    for solver_class in _get_internal_solvers():
+        instance = _get_knapsack_instance(solver_class)
+        solver = solver_class()
+        solver.set_instance(instance)
+        solver.relax()
+        stats = solver.solve()
+        assert round(stats["Lower bound"]) == 1288.0
+
+
+def test_infeasible_instance():
+    for solver_class in _get_internal_solvers():
+        instance = _get_infeasible_instance(solver_class)
+        solver = solver_class()
+        solver.set_instance(instance)
+        stats = solver.solve()
+
+        assert solver.is_infeasible()
+        assert solver.get_solution() is None
+        assert stats["Upper bound"] is None
+        assert stats["Lower bound"] is None
+
+        stats = solver.solve_lp()
+        assert solver.get_solution() is None
+        assert stats["Optimal value"] is None
+        assert solver.get_value("x", 0) is None
+
+
+def test_iteration_cb():
+    for solver_class in _get_internal_solvers():
+        logger.info("Solver: %s" % solver_class)
+        instance = _get_knapsack_instance(solver_class)
+        solver = solver_class()
+        solver.set_instance(instance)
+        count = 0
+
+        def custom_iteration_cb():
+            nonlocal count
+            count += 1
+            return count < 5
+
+        solver.solve(iteration_cb=custom_iteration_cb)
+        assert count == 5