680 lines
27 KiB
Python
680 lines
27 KiB
Python
#!/usr/bin/env python3
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# Copyright 2010-2025 Google LLC
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import math
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from typing import Optional
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from absl.testing import absltest
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from absl.testing import parameterized
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from ortools.math_opt import model_pb2
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from ortools.math_opt import model_update_pb2
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from ortools.math_opt import sparse_containers_pb2
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from ortools.math_opt.python import linear_constraints
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from ortools.math_opt.python import model
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from ortools.math_opt.python import variables
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from ortools.math_opt.python.testing import compare_proto
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class ModelTest(compare_proto.MathOptProtoAssertions, parameterized.TestCase):
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def test_name(self) -> None:
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mod = model.Model(name="test_model")
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self.assertEqual("test_model", mod.name)
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def test_name_empty(self) -> None:
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mod = model.Model()
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self.assertEqual("", mod.name)
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def test_add_and_read_variables(self) -> None:
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mod = model.Model(name="test_model")
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v1 = mod.add_variable(lb=-1.0, ub=2.5, is_integer=True, name="x")
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v2 = mod.add_variable()
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self.assertEqual(-1.0, v1.lower_bound)
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self.assertEqual(2.5, v1.upper_bound)
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self.assertTrue(v1.integer)
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self.assertEqual("x", v1.name)
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self.assertEqual(0, v1.id)
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self.assertEqual("x", str(v1))
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self.assertEqual("<Variable id: 0, name: 'x'>", repr(v1))
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self.assertEqual(-math.inf, v2.lower_bound)
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self.assertEqual(math.inf, v2.upper_bound)
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self.assertFalse(v2.integer)
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self.assertEqual("", v2.name)
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self.assertEqual(1, v2.id)
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self.assertEqual("variable_1", str(v2))
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self.assertEqual("<Variable id: 1, name: ''>", repr(v2))
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self.assertListEqual([v1, v2], list(mod.variables()))
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self.assertEqual(v1, mod.get_variable(0))
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self.assertEqual(v2, mod.get_variable(1))
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def test_add_integer_variable(self) -> None:
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mod = model.Model(
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name="test_model",
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)
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v1 = mod.add_integer_variable(lb=-1.0, ub=2.5, name="x")
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self.assertEqual(-1.0, v1.lower_bound)
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self.assertEqual(2.5, v1.upper_bound)
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self.assertTrue(v1.integer)
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self.assertEqual("x", v1.name)
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self.assertEqual(0, v1.id)
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def test_add_binary_variable(self) -> None:
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mod = model.Model(name="test_model")
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v1 = mod.add_binary_variable(name="x")
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self.assertEqual(0.0, v1.lower_bound)
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self.assertEqual(1.0, v1.upper_bound)
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self.assertTrue(v1.integer)
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self.assertEqual("x", v1.name)
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self.assertEqual(0, v1.id)
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def test_update_variable(self) -> None:
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mod = model.Model(name="test_model")
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v1 = mod.add_variable(lb=-1.0, ub=2.5, is_integer=True, name="x")
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v1.lower_bound = -math.inf
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v1.upper_bound = -3.0
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v1.integer = False
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self.assertEqual(-math.inf, v1.lower_bound)
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self.assertEqual(-3.0, v1.upper_bound)
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self.assertFalse(v1.integer)
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def test_read_deleted_variable(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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mod.delete_variable(x)
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with self.assertRaises(ValueError):
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x.lower_bound # pylint: disable=pointless-statement
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def test_update_deleted_variable(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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mod.delete_variable(x)
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with self.assertRaises(ValueError):
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x.upper_bound = 2.0
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def test_add_and_read_linear_constraints(self) -> None:
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mod = model.Model(name="test_model")
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c = mod.add_linear_constraint(lb=-1.0, ub=2.5, name="c")
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d = mod.add_linear_constraint()
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self.assertEqual(-1.0, c.lower_bound)
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self.assertEqual(2.5, c.upper_bound)
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self.assertEqual("c", c.name)
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self.assertEqual(0, c.id)
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self.assertEqual("c", str(c))
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self.assertEqual("<LinearConstraint id: 0, name: 'c'>", repr(c))
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self.assertEqual(-math.inf, d.lower_bound)
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self.assertEqual(math.inf, d.upper_bound)
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self.assertEqual("", d.name)
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self.assertEqual(1, d.id)
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self.assertEqual("linear_constraint_1", str(d))
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self.assertEqual("<LinearConstraint id: 1, name: ''>", repr(d))
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self.assertListEqual([c, d], list(mod.linear_constraints()))
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self.assertEqual(c, mod.get_linear_constraint(0))
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self.assertEqual(d, mod.get_linear_constraint(1))
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def test_linear_constraint_as_bounded_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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c = mod.add_linear_constraint(lb=-1.0, ub=2.5, name="c", expr=3 * x - 2 * y)
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bounded_expr = c.as_bounded_linear_expression()
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self.assertEqual(bounded_expr.lower_bound, -1.0)
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self.assertEqual(bounded_expr.upper_bound, 2.5)
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expr = variables.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(expr.offset, 0.0)
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self.assertDictEqual(dict(expr.terms), {x: 3.0, y: -2.0})
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def test_update_linear_constraint(self) -> None:
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mod = model.Model(name="test_model")
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c = mod.add_linear_constraint(lb=-1.0, ub=2.5, name="c")
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c.lower_bound = -math.inf
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c.upper_bound = -3.0
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self.assertEqual(-math.inf, c.lower_bound)
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self.assertEqual(-3.0, c.upper_bound)
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def test_read_deleted_linear_constraint(self) -> None:
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mod = model.Model(name="test_model")
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c = mod.add_linear_constraint(lb=-1.0, ub=2.5, name="c")
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mod.delete_linear_constraint(c)
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with self.assertRaises(ValueError):
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c.name # pylint: disable=pointless-statement
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def test_update_deleted_linear_constraint(self) -> None:
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mod = model.Model(name="test_model")
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c = mod.add_linear_constraint(lb=-1.0, ub=2.5, name="c")
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mod.delete_linear_constraint(c)
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with self.assertRaises(ValueError):
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c.lower_bound = -12.0
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def test_linear_constraint_matrix(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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c = mod.add_linear_constraint(lb=0.0, ub=1.0, name="c")
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d = mod.add_linear_constraint(ub=1.0, name="d")
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c.set_coefficient(x, 1.0)
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c.set_coefficient(y, 0.0)
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d.set_coefficient(x, 2.0)
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d.set_coefficient(z, -1.0)
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self.assertEqual(1.0, c.get_coefficient(x))
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self.assertEqual(0.0, c.get_coefficient(y))
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self.assertEqual(0.0, c.get_coefficient(z))
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self.assertEqual(2.0, d.get_coefficient(x))
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self.assertEqual(0.0, d.get_coefficient(y))
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self.assertEqual(-1.0, d.get_coefficient(z))
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self.assertEqual(c.name, "c")
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self.assertEqual(d.name, "d")
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self.assertCountEqual([c, d], mod.column_nonzeros(x))
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self.assertCountEqual([], mod.column_nonzeros(y))
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self.assertCountEqual([d], mod.column_nonzeros(z))
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self.assertCountEqual([x], mod.row_nonzeros(c))
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self.assertCountEqual([x, z], mod.row_nonzeros(d))
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self.assertCountEqual(
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[repr(variables.LinearTerm(variable=x, coefficient=1.0))],
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[repr(term) for term in c.terms()],
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)
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self.assertCountEqual(
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[
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repr(variables.LinearTerm(variable=x, coefficient=2.0)),
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repr(variables.LinearTerm(variable=z, coefficient=-1.0)),
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],
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[repr(term) for term in d.terms()],
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)
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self.assertCountEqual(
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[
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linear_constraints.LinearConstraintMatrixEntry(
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linear_constraint=c, variable=x, coefficient=1.0
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),
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linear_constraints.LinearConstraintMatrixEntry(
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linear_constraint=d, variable=x, coefficient=2.0
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),
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linear_constraints.LinearConstraintMatrixEntry(
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linear_constraint=d, variable=z, coefficient=-1.0
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),
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],
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list(mod.linear_constraint_matrix_entries()),
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)
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def test_linear_constraint_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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c = mod.add_linear_constraint(lb=0.0, expr=x + 1.0, ub=1.0, name="c")
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self.assertEqual(1.0, c.get_coefficient(x))
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self.assertEqual(0.0, c.get_coefficient(y))
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self.assertEqual(0.0, c.get_coefficient(z))
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self.assertEqual(-1.0, c.lower_bound)
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self.assertEqual(0.0, c.upper_bound)
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d = mod.add_linear_constraint(ub=1.0, expr=2 * x - z, name="d")
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self.assertEqual(2.0, d.get_coefficient(x))
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self.assertEqual(0.0, d.get_coefficient(y))
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self.assertEqual(-1.0, d.get_coefficient(z))
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self.assertEqual(-math.inf, d.lower_bound)
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self.assertEqual(1.0, d.upper_bound)
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e = mod.add_linear_constraint(lb=0.0)
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self.assertEqual(0.0, e.get_coefficient(x))
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self.assertEqual(0.0, e.get_coefficient(y))
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self.assertEqual(0.0, e.get_coefficient(z))
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self.assertEqual(0.0, e.lower_bound)
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self.assertEqual(math.inf, e.upper_bound)
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f = mod.add_linear_constraint(expr=1, ub=2)
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self.assertEqual(0.0, f.get_coefficient(x))
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self.assertEqual(0.0, f.get_coefficient(y))
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self.assertEqual(0.0, f.get_coefficient(z))
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self.assertEqual(-math.inf, f.lower_bound)
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self.assertEqual(1, f.upper_bound)
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def test_linear_constraint_bounded_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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c = mod.add_linear_constraint((0.0 <= x + 1.0) <= 1.0, name="c")
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self.assertEqual(1.0, c.get_coefficient(x))
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self.assertEqual(0.0, c.get_coefficient(y))
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self.assertEqual(0.0, c.get_coefficient(z))
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self.assertEqual(-1.0, c.lower_bound)
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self.assertEqual(0.0, c.upper_bound)
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def test_linear_constraint_upper_bounded_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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d = mod.add_linear_constraint(2 * x - z + 2.0 <= 1.0, name="d")
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self.assertEqual(2.0, d.get_coefficient(x))
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self.assertEqual(0.0, d.get_coefficient(y))
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self.assertEqual(-1.0, d.get_coefficient(z))
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self.assertEqual(-math.inf, d.lower_bound)
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self.assertEqual(-1.0, d.upper_bound)
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def test_linear_constraint_lower_bounded_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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e = mod.add_linear_constraint(1.0 <= x + y + 2.0, name="e")
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self.assertEqual(1.0, e.get_coefficient(x))
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self.assertEqual(1.0, e.get_coefficient(y))
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self.assertEqual(0.0, e.get_coefficient(z))
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self.assertEqual(-1.0, e.lower_bound)
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self.assertEqual(math.inf, e.upper_bound)
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def test_linear_constraint_number_eq_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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f = mod.add_linear_constraint(1.0 == x + y + 2.0, name="e")
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self.assertEqual(1.0, f.get_coefficient(x))
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self.assertEqual(1.0, f.get_coefficient(y))
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self.assertEqual(0.0, f.get_coefficient(z))
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self.assertEqual(-1.0, f.lower_bound)
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self.assertEqual(-1.0, f.upper_bound)
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def test_linear_constraint_expression_eq_expression(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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f = mod.add_linear_constraint(1.0 - x == y + 2.0, name="e")
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self.assertEqual(-1.0, f.get_coefficient(x))
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self.assertEqual(-1.0, f.get_coefficient(y))
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self.assertEqual(0.0, f.get_coefficient(z))
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self.assertEqual(1.0, f.lower_bound)
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self.assertEqual(1.0, f.upper_bound)
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def test_linear_constraint_variable_eq_variable(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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f = mod.add_linear_constraint(x == y, name="e")
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self.assertEqual(1.0, f.get_coefficient(x))
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self.assertEqual(-1.0, f.get_coefficient(y))
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self.assertEqual(0.0, f.get_coefficient(z))
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self.assertEqual(0.0, f.lower_bound)
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self.assertEqual(0.0, f.upper_bound)
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def test_linear_constraint_errors(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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z = mod.add_binary_variable(name="z")
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with self.assertRaisesRegex(
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TypeError,
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"Unsupported type for bounded_expr.*bool.*!= constraints.*constant" " left",
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):
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mod.add_linear_constraint(x != y)
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with self.assertRaisesRegex(TypeError, "!= constraints.*"):
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mod.add_linear_constraint(x + y != y)
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with self.assertRaisesRegex(TypeError, "!= constraints.*"):
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mod.add_linear_constraint(x != x + y)
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with self.assertRaisesRegex(
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TypeError,
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"Unsupported type for bounded_expr.*bool.*!= constraints.*constant" " left",
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):
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mod.add_linear_constraint(1 <= 2) # pylint: disable=comparison-of-constants
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with self.assertRaisesRegex(
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TypeError,
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"Unsupported type for bounded_expr.*bool.*!= constraints.*constant" " left",
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):
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mod.add_linear_constraint(1 <= 0) # pylint: disable=comparison-of-constants
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with self.assertRaisesRegex(
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TypeError,
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"Unsupported type for bounded_expr.*bool.*!= constraints.*constant" " left",
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):
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mod.add_linear_constraint(True)
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with self.assertRaisesRegex(
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TypeError,
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"__bool__ is unsupported.*\n.*two-sided or ranged linear inequality",
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):
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mod.add_linear_constraint(x <= y <= z)
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with self.assertRaisesRegex(
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TypeError,
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"unsupported operand.*\n.*two or more non-constant linear expressions",
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):
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mod.add_linear_constraint((x <= y) <= z)
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with self.assertRaisesRegex(
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TypeError,
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"unsupported operand.*\n.*two or more non-constant linear expressions",
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):
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mod.add_linear_constraint(x <= (y <= z))
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with self.assertRaisesRegex(TypeError, "unsupported operand.*"):
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mod.add_linear_constraint((0 <= x) >= z)
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with self.assertRaisesRegex(AssertionError, "lb cannot be specified.*"):
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mod.add_linear_constraint(x + y == 1, lb=1)
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with self.assertRaisesRegex(AssertionError, "ub cannot be specified.*"):
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mod.add_linear_constraint(x + y == 1, ub=1)
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with self.assertRaisesRegex(AssertionError, "expr cannot be specified.*"):
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mod.add_linear_constraint(x + y == 1, expr=2 * x)
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with self.assertRaisesRegex(
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TypeError, "Unsupported type for expr argument.*str"
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):
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mod.add_linear_constraint(expr="string")
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with self.assertRaisesRegex(ValueError, ".*infinite offset."):
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mod.add_linear_constraint(expr=math.inf, lb=0.0)
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def test_linear_constraint_matrix_with_variable_deletion(self) -> None:
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mod = model.Model(name="test_model")
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x = mod.add_binary_variable(name="x")
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y = mod.add_binary_variable(name="y")
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c = mod.add_linear_constraint(lb=0.0, ub=1.0, name="c")
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d = mod.add_linear_constraint(lb=0.0, ub=1.0, name="d")
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c.set_coefficient(x, 1.0)
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c.set_coefficient(y, 2.0)
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d.set_coefficient(x, 1.0)
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mod.delete_variable(x)
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self.assertCountEqual(
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[
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linear_constraints.LinearConstraintMatrixEntry(
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linear_constraint=c, variable=y, coefficient=2.0
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)
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],
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mod.linear_constraint_matrix_entries(),
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)
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self.assertCountEqual([c], mod.column_nonzeros(y))
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self.assertCountEqual(
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[repr(variables.LinearTerm(variable=y, coefficient=2.0))],
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|
[repr(term) for term in c.terms()],
|
|
)
|
|
self.assertCountEqual([], d.terms())
|
|
with self.assertRaises(ValueError):
|
|
c.get_coefficient(x)
|
|
|
|
def test_linear_constraint_matrix_with_linear_constraint_deletion(
|
|
self,
|
|
) -> None:
|
|
mod = model.Model(name="test_model")
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
c = mod.add_linear_constraint(lb=0.0, ub=1.0, name="c")
|
|
d = mod.add_linear_constraint(lb=0.0, ub=1.0, name="d")
|
|
c.set_coefficient(x, 1.0)
|
|
c.set_coefficient(y, 2.0)
|
|
d.set_coefficient(x, 1.0)
|
|
mod.delete_linear_constraint(c)
|
|
self.assertCountEqual(
|
|
[
|
|
linear_constraints.LinearConstraintMatrixEntry(
|
|
linear_constraint=d, variable=x, coefficient=1.0
|
|
)
|
|
],
|
|
list(mod.linear_constraint_matrix_entries()),
|
|
)
|
|
self.assertCountEqual([d], mod.column_nonzeros(x))
|
|
self.assertCountEqual([], mod.column_nonzeros(y))
|
|
self.assertCountEqual(
|
|
[repr(variables.LinearTerm(variable=x, coefficient=1.0))],
|
|
[repr(term) for term in d.terms()],
|
|
)
|
|
|
|
def test_linear_constraint_matrix_wrong_model(self) -> None:
|
|
mod1 = model.Model(name="test_model1")
|
|
x1 = mod1.add_binary_variable(name="x")
|
|
mod2 = model.Model(name="test_model2")
|
|
mod2.add_binary_variable(name="x")
|
|
c2 = mod2.add_linear_constraint(lb=0.0, ub=1.0, name="c")
|
|
with self.assertRaises(ValueError):
|
|
c2.set_coefficient(x1, 1.0)
|
|
|
|
@parameterized.named_parameters(
|
|
{"testcase_name": "default", "remove_names": None},
|
|
{"testcase_name": "with_names", "remove_names": False},
|
|
{"testcase_name": "without_names", "remove_names": True},
|
|
)
|
|
def test_export(self, remove_names: Optional[bool]) -> None:
|
|
"""Test the export_model() function.
|
|
|
|
Args:
|
|
remove_names: Optional value for the remove_names parameters. When None,
|
|
calls export_model() without the parameter to test the default value.
|
|
"""
|
|
mod = model.Model(name="test_model")
|
|
mod.objective.offset = 2.0
|
|
mod.objective.is_maximize = True
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
c = mod.add_linear_constraint(lb=0.0, ub=2.0, name="c")
|
|
c.set_coefficient(x, 1.0)
|
|
c.set_coefficient(y, 2.0)
|
|
mod.objective.set_linear_coefficient(y, 3.0)
|
|
expected = model_pb2.ModelProto(
|
|
name="test_model" if not remove_names else "",
|
|
variables=model_pb2.VariablesProto(
|
|
ids=[0, 1],
|
|
lower_bounds=[0.0, 0.0],
|
|
upper_bounds=[1.0, 1.0],
|
|
integers=[True, True],
|
|
names=["x", "y"] if not remove_names else [],
|
|
),
|
|
linear_constraints=model_pb2.LinearConstraintsProto(
|
|
ids=[0],
|
|
lower_bounds=[0.0],
|
|
upper_bounds=[2.0],
|
|
names=["c"] if not remove_names else [],
|
|
),
|
|
objective=model_pb2.ObjectiveProto(
|
|
maximize=True,
|
|
offset=2.0,
|
|
linear_coefficients=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[1], values=[3.0]
|
|
),
|
|
),
|
|
linear_constraint_matrix=sparse_containers_pb2.SparseDoubleMatrixProto(
|
|
row_ids=[0, 0], column_ids=[0, 1], coefficients=[1.0, 2.0]
|
|
),
|
|
)
|
|
self.assert_protos_equiv(
|
|
expected,
|
|
(
|
|
mod.export_model()
|
|
if remove_names is None
|
|
else mod.export_model(remove_names=remove_names)
|
|
),
|
|
)
|
|
|
|
def test_from_model_proto(self) -> None:
|
|
model_proto = model_pb2.ModelProto(
|
|
name="test_model",
|
|
variables=model_pb2.VariablesProto(
|
|
ids=[0, 1],
|
|
lower_bounds=[0.0, 1.0],
|
|
upper_bounds=[2.0, 3.0],
|
|
integers=[True, False],
|
|
names=["x", "y"],
|
|
),
|
|
linear_constraints=model_pb2.LinearConstraintsProto(
|
|
ids=[0],
|
|
lower_bounds=[-1.0],
|
|
upper_bounds=[2.0],
|
|
names=["c"],
|
|
),
|
|
objective=model_pb2.ObjectiveProto(
|
|
maximize=True,
|
|
offset=2.0,
|
|
linear_coefficients=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[1], values=[3.0]
|
|
),
|
|
),
|
|
linear_constraint_matrix=sparse_containers_pb2.SparseDoubleMatrixProto(
|
|
row_ids=[0, 0], column_ids=[0, 1], coefficients=[1.0, 2.0]
|
|
),
|
|
)
|
|
mod = model.Model.from_model_proto(model_proto)
|
|
self.assertEqual(mod.name, "test_model")
|
|
self.assertEqual(mod.get_num_variables(), 2)
|
|
x = mod.get_variable(0)
|
|
y = mod.get_variable(1)
|
|
self.assertEqual(x.name, "x")
|
|
self.assertEqual(x.lower_bound, 0.0)
|
|
self.assertEqual(x.upper_bound, 2.0)
|
|
self.assertTrue(x.integer)
|
|
self.assertEqual(y.name, "y")
|
|
self.assertEqual(y.lower_bound, 1.0)
|
|
self.assertEqual(y.upper_bound, 3.0)
|
|
self.assertFalse(y.integer)
|
|
self.assertEqual(mod.get_num_linear_constraints(), 1)
|
|
c = mod.get_linear_constraint(0)
|
|
self.assertEqual(c.name, "c")
|
|
self.assertEqual(c.lower_bound, -1.0)
|
|
self.assertEqual(c.upper_bound, 2.0)
|
|
self.assertEqual(c.get_coefficient(x), 1.0)
|
|
self.assertEqual(c.get_coefficient(y), 2.0)
|
|
self.assertTrue(mod.objective.is_maximize)
|
|
self.assertEqual(mod.objective.offset, 2.0)
|
|
self.assertEqual(mod.objective.get_linear_coefficient(x), 0.0)
|
|
self.assertEqual(mod.objective.get_linear_coefficient(y), 3.0)
|
|
|
|
def test_update_tracker_simple(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
x = mod.add_binary_variable(name="x")
|
|
t = mod.add_update_tracker()
|
|
x.upper_bound = 2.0
|
|
expected = model_update_pb2.ModelUpdateProto(
|
|
variable_updates=model_update_pb2.VariableUpdatesProto(
|
|
upper_bounds=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[0], values=[2.0]
|
|
)
|
|
)
|
|
)
|
|
self.assert_protos_equiv(expected, t.export_update())
|
|
self.assert_protos_equiv(expected, t.export_update())
|
|
t.advance_checkpoint()
|
|
self.assertIsNone(t.export_update())
|
|
|
|
def test_two_update_trackers(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
t1 = mod.add_update_tracker()
|
|
x = mod.add_binary_variable(name="x")
|
|
t2 = mod.add_update_tracker()
|
|
x.upper_bound = 2.0
|
|
expected1 = model_update_pb2.ModelUpdateProto(
|
|
new_variables=model_pb2.VariablesProto(
|
|
ids=[0],
|
|
lower_bounds=[0.0],
|
|
upper_bounds=[2.0],
|
|
integers=[True],
|
|
names=["x"],
|
|
)
|
|
)
|
|
expected2 = model_update_pb2.ModelUpdateProto(
|
|
variable_updates=model_update_pb2.VariableUpdatesProto(
|
|
upper_bounds=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[0], values=[2.0]
|
|
)
|
|
)
|
|
)
|
|
self.assert_protos_equiv(expected1, t1.export_update())
|
|
self.assert_protos_equiv(expected2, t2.export_update())
|
|
|
|
def test_remove_tracker(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
x = mod.add_binary_variable(name="x")
|
|
t1 = mod.add_update_tracker()
|
|
t2 = mod.add_update_tracker()
|
|
x.upper_bound = 2.0
|
|
mod.remove_update_tracker(t1)
|
|
x.lower_bound = -1.0
|
|
expected = model_update_pb2.ModelUpdateProto(
|
|
variable_updates=model_update_pb2.VariableUpdatesProto(
|
|
upper_bounds=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[0], values=[2.0]
|
|
),
|
|
lower_bounds=sparse_containers_pb2.SparseDoubleVectorProto(
|
|
ids=[0], values=[-1.0]
|
|
),
|
|
)
|
|
)
|
|
self.assert_protos_equiv(expected, t2.export_update())
|
|
with self.assertRaises(ValueError):
|
|
t1.export_update()
|
|
with self.assertRaises(ValueError):
|
|
t1.advance_checkpoint()
|
|
with self.assertRaises(ValueError):
|
|
mod.remove_update_tracker(t1)
|
|
|
|
|
|
class WrongAttributeTest(absltest.TestCase):
|
|
"""Test case that verifies that wrong attributes are detected.
|
|
|
|
In some the tests below we have to disable pytype checks since it also detects
|
|
the issue now that the code uses __slots__.
|
|
"""
|
|
|
|
def test_variable(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
x = mod.add_variable()
|
|
with self.assertRaises(AttributeError):
|
|
x.loer_bnd = 4 # pytype: disable=not-writable
|
|
|
|
def test_linear_constraint(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
c = mod.add_linear_constraint()
|
|
with self.assertRaises(AttributeError):
|
|
c.uper_bound = 8 # pytype: disable=not-writable
|
|
|
|
def test_objective(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
with self.assertRaises(AttributeError):
|
|
mod.objective.matimuze = True # pytype: disable=not-writable
|
|
|
|
def test_aux_objective(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
aux = mod.add_auxiliary_objective(priority=1)
|
|
with self.assertRaises(AttributeError):
|
|
aux.matimuze = True # pytype: disable=not-writable
|
|
|
|
def test_model(self) -> None:
|
|
mod = model.Model(name="test_model")
|
|
with self.assertRaises(AttributeError):
|
|
mod.objectize = None # pytype: disable=not-writable
|
|
|
|
|
|
if __name__ == "__main__":
|
|
absltest.main()
|