c34026b101
note: done using ```sh git grep -l "2010-2024 Google" | xargs sed -i 's/2010-2024 Google/2010-2025 Google/' ```
2832 lines
113 KiB
Python
2832 lines
113 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 Any, List, NamedTuple, Union
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from unittest import mock
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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.python import model
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_LINEAR_TYPES = (
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"Variable",
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"LinearTerm",
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"LinearExpression",
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"LinearSum",
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"LinearProduct",
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)
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_QUADRATIC_TYPES = (
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"QuadraticTerm",
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"QuadraticExpression",
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"QuadraticSum",
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"LinearLinearProduct",
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"QuadraticProduct",
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)
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class BoundedExprTest(absltest.TestCase):
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def test_eq_float(self) -> None:
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mod = model.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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bounded_expr = x + 2 * y + 1.0 == 2.0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.lower_bound, 2.0)
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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# Also call __eq__ directly to confirm there are no pytype issues.
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def test_eq_float_explicit(self) -> None:
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mod = model.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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bounded_expr = (x + 2 * y + 1.0).__eq__(2.0)
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.lower_bound, 2.0)
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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def test_eq_expr(self) -> None:
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mod = model.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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bounded_expr = x + 2 * y + 1.0 == 3 * y - 2.0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 3.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: -1.0})
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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self.assertEqual(bounded_expr.upper_bound, 0.0)
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# Check Variable.__eq__ calls LinearBase.__eq__ when appropriate.
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bounded_expr_var_on_lhs = x == 3 * y - 2.0
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self.assertIsInstance(bounded_expr_var_on_lhs, model.BoundedLinearExpression)
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flat_expr_var_on_lhs = model.as_flat_linear_expression(
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bounded_expr_var_on_lhs.expression
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)
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self.assertEqual(flat_expr_var_on_lhs.offset, 2.0)
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self.assertDictEqual(dict(flat_expr_var_on_lhs.terms), {x: 1.0, y: -3.0})
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self.assertEqual(bounded_expr_var_on_lhs.lower_bound, 0.0)
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self.assertEqual(bounded_expr_var_on_lhs.upper_bound, 0.0)
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bounded_expr_var_on_rhs = 3 * y - 2.0 == x
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self.assertIsInstance(bounded_expr_var_on_rhs, model.BoundedLinearExpression)
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flat_expr_var_on_rhs = model.as_flat_linear_expression(
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bounded_expr_var_on_rhs.expression
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)
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self.assertEqual(flat_expr_var_on_rhs.offset, -2.0)
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self.assertDictEqual(dict(flat_expr_var_on_rhs.terms), {x: -1.0, y: 3.0})
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self.assertEqual(bounded_expr_var_on_rhs.lower_bound, 0.0)
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self.assertEqual(bounded_expr_var_on_rhs.upper_bound, 0.0)
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# Also call __eq__ directly to confirm there are no pytype issues.
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def test_eq_expr_explicit(self) -> None:
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mod = model.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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bounded_expr = (x + 2 * y + 1.0).__eq__(3 * y - 2.0)
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 3.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: -1.0})
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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self.assertEqual(bounded_expr.upper_bound, 0.0)
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# Check Variable.__eq__ calls LinearBase.__eq__ when appropriate.
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bounded_expr_var_on_lhs = x.__eq__(3 * y - 2.0)
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self.assertIsInstance(bounded_expr_var_on_lhs, model.BoundedLinearExpression)
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flat_expr_var_on_lhs = model.as_flat_linear_expression(
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bounded_expr_var_on_lhs.expression
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)
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self.assertEqual(flat_expr_var_on_lhs.offset, 2.0)
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self.assertDictEqual(dict(flat_expr_var_on_lhs.terms), {x: 1.0, y: -3.0})
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self.assertEqual(bounded_expr_var_on_lhs.lower_bound, 0.0)
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self.assertEqual(bounded_expr_var_on_lhs.upper_bound, 0.0)
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bounded_expr_var_on_rhs = (3 * y - 2.0).__eq__(x)
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self.assertIsInstance(bounded_expr_var_on_rhs, model.BoundedLinearExpression)
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flat_expr_var_on_rhs = model.as_flat_linear_expression(
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bounded_expr_var_on_rhs.expression
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)
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self.assertEqual(flat_expr_var_on_rhs.offset, -2.0)
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self.assertDictEqual(dict(flat_expr_var_on_rhs.terms), {x: -1.0, y: 3.0})
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self.assertEqual(bounded_expr_var_on_rhs.lower_bound, 0.0)
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self.assertEqual(bounded_expr_var_on_rhs.upper_bound, 0.0)
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def test_var_eq_var(self) -> None:
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mod = model.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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also_x = x
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bounded_expr = x == y
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self.assertIsInstance(bounded_expr, model.VarEqVar)
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self.assertEqual(bounded_expr.first_variable, x)
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self.assertEqual(bounded_expr.second_variable, y)
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second_mod = model.Model()
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second_x = second_mod.add_binary_variable(name="x")
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# pylint: disable=g-generic-assert
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self.assertTrue(x == also_x)
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self.assertFalse(x == y)
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self.assertEqual(x.id, second_x.id)
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self.assertFalse(x == second_x)
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# pylint: enable=g-generic-assert
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# Also call __eq__ directly to confirm there are no pytype issues (see
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# b/227214976).
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def test_var_eq_var_explicit(self) -> None:
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mod = model.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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also_x = x
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bounded_expr = x.__eq__(y)
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self.assertIsInstance(bounded_expr, model.VarEqVar)
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self.assertEqual(bounded_expr.first_variable, x)
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self.assertEqual(bounded_expr.second_variable, y)
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second_mod = model.Model()
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second_x = second_mod.add_binary_variable(name="x")
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# pylint: disable=g-generic-assert
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self.assertTrue(x.__eq__(also_x))
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self.assertFalse(x.__eq__(y))
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self.assertEqual(x.id, second_x.id)
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self.assertFalse(x.__eq__(second_x))
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# pylint: enable=g-generic-assert
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def test_var_neq_var(self) -> None:
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mod = model.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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also_x = x
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second_mod = model.Model()
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second_x = second_mod.add_binary_variable(name="x")
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# pylint: disable=g-generic-assert
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self.assertFalse(x != also_x)
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self.assertTrue(x != y)
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self.assertEqual(x.id, second_x.id)
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self.assertTrue(x != second_x)
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# pylint: enable=g-generic-assert
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# Also call __ne__ directly to confirm there are no pytype issues (see
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# b/227214976).
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def test_var_neq_var_explicit(self) -> None:
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mod = model.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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also_x = x
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second_mod = model.Model()
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second_x = second_mod.add_binary_variable(name="x")
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# pylint: disable=g-generic-assert
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self.assertFalse(x.__ne__(also_x))
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self.assertTrue(x.__ne__(y))
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self.assertEqual(x.id, second_x.id)
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self.assertTrue(x.__ne__(second_x))
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# pylint: enable=g-generic-assert
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# Mock Variable.__hash__ to have a collision in the dictionary lookup so that
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# a correct behavior of x == y is needed to recover the values. For instance,
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# if VarEqVar.__bool__ always returned True, this test would fail.
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@mock.patch.object(model.Variable, "__hash__")
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def test_var_dict(self, fixed_hash: mock.MagicMock) -> None:
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fixed_hash.return_value = 111
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mod = model.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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var_dict = {x: 1.0, y: 2.0}
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self.assertEqual(x.__hash__(), 111)
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self.assertEqual(y.__hash__(), 111)
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self.assertEqual(var_dict[x], 1.0)
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self.assertEqual(var_dict[y], 2.0)
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def test_leq_float(self) -> None:
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mod = model.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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bounded_expr = x + 2 * y + 1.0 <= 2.0
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self.assertIsInstance(bounded_expr, model.UpperBoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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def test_leq_float_rev(self) -> None:
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mod = model.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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bounded_expr = 2.0 >= x + 2 * y + 1.0
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self.assertIsInstance(bounded_expr, model.UpperBoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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def test_geq_float(self) -> None:
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mod = model.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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bounded_expr = x + 2 * y + 1.0 >= 2.0
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self.assertIsInstance(bounded_expr, model.LowerBoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.lower_bound, 2.0)
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def test_geq_float_rev(self) -> None:
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mod = model.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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bounded_expr = 2.0 <= x + 2 * y + 1.0
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self.assertIsInstance(bounded_expr, model.LowerBoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.lower_bound, 2.0)
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def test_geq_leq_float(self) -> None:
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mod = model.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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bounded_expr = (0.0 <= x + 2 * y + 1.0) <= 2.0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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def test_geq_leq_float_rev(self) -> None:
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mod = model.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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bounded_expr = 2.0 >= (x + 2 * y + 1.0 >= 0)
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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def test_leq_geq_float(self) -> None:
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mod = model.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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bounded_expr = 0.0 <= (x + 2 * y + 1.0 <= 2.0)
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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def test_leq_geq_float_rev(self) -> None:
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mod = model.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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bounded_expr = (2.0 >= x + 2 * y + 1.0) >= 0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0})
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self.assertEqual(bounded_expr.upper_bound, 2.0)
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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def test_leq_expr(self) -> None:
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mod = model.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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bounded_expr = x + 3 * y + 2.0 <= y - 4.0 * z + 1.0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0, z: 4.0})
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self.assertEqual(bounded_expr.lower_bound, -math.inf)
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self.assertEqual(bounded_expr.upper_bound, 0.0)
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def test_geq_expr(self) -> None:
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mod = model.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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bounded_expr = x + 3 * y + 2.0 >= y - 4.0 * z + 1.0
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self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
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flat_expr = model.as_flat_linear_expression(bounded_expr.expression)
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self.assertEqual(flat_expr.offset, 1.0)
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self.assertDictEqual(dict(flat_expr.terms), {x: 1.0, y: 2.0, z: 4.0})
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self.assertEqual(bounded_expr.lower_bound, 0.0)
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self.assertEqual(bounded_expr.upper_bound, math.inf)
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class BoundedExprErrorTest(absltest.TestCase):
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def test_ne(self) -> None:
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mod = model.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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# pylint: disable=pointless-statement
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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x != y - x
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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x.__ne__(y - x)
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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y - x != x
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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(y - x).__ne__(x)
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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y - x != x + y
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with self.assertRaisesWithLiteralMatch(
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TypeError, "!= constraints are not supported"
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):
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(y - x).__ne__(x + y)
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# pylint: enable=pointless-statement
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def test_eq(self) -> None:
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mod = model.Model()
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x = mod.add_binary_variable(name="x")
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# pylint: disable=pointless-statement
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with self.assertRaisesWithLiteralMatch(
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TypeError, "unsupported operand type(s) for ==: 'Variable' and 'str'"
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):
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x == "x" # pylint: disable=pointless-statement
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# pylint: disable=pointless-statement
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# pytype: disable=unsupported-operands
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with self.assertRaisesWithLiteralMatch(
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TypeError, "unsupported operand type(s) for ==: 'Variable' and 'str'"
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):
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x.__eq__("x")
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# pylint: enable=pointless-statement
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# pylint: enable=unsupported-operands
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def test_float_le_expr_le_float(self) -> None:
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mod = model.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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self.assertIsInstance(
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0.0 <= x + 2 * y + 1.0, model.LowerBoundedLinearExpression
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)
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with self.assertRaisesRegex(
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TypeError,
|
|
"__bool__ is unsupported.*\n.*two-sided or ranged linear inequality",
|
|
):
|
|
(0.0 <= x + 2 * y + 1.0 <= 2.0) # pylint: disable=pointless-statement
|
|
|
|
def test_float_ge_expr_ge_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
self.assertIsInstance(
|
|
2.0 >= x + 2 * y + 1.0, model.UpperBoundedLinearExpression
|
|
)
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"__bool__ is unsupported.*\n.*two-sided or ranged linear inequality",
|
|
):
|
|
(2.0 >= x + 2 * y + 1.0 >= 0.0) # pylint: disable=pointless-statement
|
|
|
|
def test_expr_le_expr_le_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
self.assertIsInstance(x <= x + 2 * y + 1.0, model.BoundedLinearExpression)
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"__bool__ is unsupported.*\n.*two-sided or ranged linear inequality.*",
|
|
):
|
|
(x <= x + 2 * y + 1.0 <= 2.0) # pylint: disable=pointless-statement
|
|
|
|
def test_expr_ge_expr_ge_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
self.assertIsInstance(x >= x + 2 * y + 1.0, model.BoundedLinearExpression)
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"__bool__ is unsupported.*\n.*two-sided or ranged linear inequality",
|
|
):
|
|
(x >= x + 2 * y + 1.0 >= 0.0) # pylint: disable=pointless-statement
|
|
|
|
def test_lower_bounded_expr_leq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 2.0 + x
|
|
lower_bounded_expr = 0.0 <= x + 2 * y + 1.0
|
|
self.assertIsInstance(lower_bounded_expr, model.LowerBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"unsupported operand type(s) for <=:"
|
|
f" {type(lower_bounded_expr).__name__!r} and"
|
|
f" {type(rhs_expr).__name__!r}",
|
|
):
|
|
lower_bounded_expr <= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_lower_bounded_expr_geq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 2.0 + x
|
|
lower_bounded_expr = 0.0 <= x + 2 * y + 1.0
|
|
self.assertIsInstance(lower_bounded_expr, model.LowerBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for <=: {type(rhs_expr).__name__!r} and"
|
|
f" {type(lower_bounded_expr).__name__!r}",
|
|
):
|
|
lower_bounded_expr >= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_lower_bounded_expr_geq_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
lower_bounded_expr = 0.0 <= x + 2 * y + 1.0
|
|
self.assertIsInstance(lower_bounded_expr, model.LowerBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"'>=' not supported between instances of"
|
|
f" {type(lower_bounded_expr).__name__!r} and 'float'",
|
|
):
|
|
lower_bounded_expr >= 2.0
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_upper_bounded_expr_geq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 1.0 + x
|
|
upper_bounded_expr = 2.0 >= x + 2 * y + 1.0
|
|
self.assertIsInstance(upper_bounded_expr, model.UpperBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"unsupported operand type(s) for >=:"
|
|
f" {type(upper_bounded_expr).__name__!r} and"
|
|
f" {type(rhs_expr).__name__!r}",
|
|
):
|
|
upper_bounded_expr >= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_upper_bounded_expr_leq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 1.0 + x
|
|
upper_bounded_expr = 2.0 >= x + 2 * y + 1.0
|
|
self.assertIsInstance(upper_bounded_expr, model.UpperBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for >=: {type(rhs_expr).__name__!r} and"
|
|
f" {type(upper_bounded_expr).__name__!r}",
|
|
):
|
|
upper_bounded_expr <= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_upper_bounded_expr_leq_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
upper_bounded_expr = 2.0 >= x + 2 * y + 1.0
|
|
self.assertIsInstance(upper_bounded_expr, model.UpperBoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"'<=' not supported between instances of"
|
|
f" {type(upper_bounded_expr).__name__!r} and 'float'",
|
|
):
|
|
upper_bounded_expr <= 2.0
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_bounded_expr_leq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 1.0 + x
|
|
bounded_expr = (0.0 <= x + 2 * y + 1.0) <= 2.0
|
|
self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"unsupported operand.*\n.*two or more non-constant linear expressions",
|
|
):
|
|
bounded_expr <= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_bounded_expr_leq_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
bounded_expr = (0.0 <= x + 2 * y + 1.0) <= 2.0
|
|
self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"'<=' not supported between instances of"
|
|
f" {type(bounded_expr).__name__!r} and 'float'",
|
|
):
|
|
bounded_expr <= 2.0
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_bounded_expr_geq_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
rhs_expr = 1.0 + x
|
|
bounded_expr = (0.0 <= x + 2 * y + 1.0) <= 2.0
|
|
self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"unsupported operand.*\n.*two or more non-constant linear expressions",
|
|
):
|
|
bounded_expr >= rhs_expr
|
|
# pylint: enable=pointless-statement
|
|
|
|
def test_bounded_expr_geq_float(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
bounded_expr = (0.0 <= x + 2 * y + 1.0) <= 2.0
|
|
self.assertIsInstance(bounded_expr, model.BoundedLinearExpression)
|
|
# pylint: disable=pointless-statement
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
"'>=' not supported between instances of"
|
|
f" {type(bounded_expr).__name__!r} and 'float'",
|
|
):
|
|
bounded_expr >= 2.0
|
|
# pylint: enable=pointless-statement
|
|
|
|
|
|
class BoundedExprStrAndReprTest(absltest.TestCase):
|
|
|
|
def test_upper_bounded_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
bounded_expr = x + 2 * y + 1.0 <= 4.0
|
|
self.assertEqual(
|
|
repr(bounded_expr),
|
|
f'LinearSum((LinearSum((<Variable id: 0, name: {"x"!r}>,'
|
|
f' LinearTerm(<Variable id: 1, name: {"y"!r}>, 2))), 1.0)) <= 4.0',
|
|
)
|
|
self.assertEqual(str(bounded_expr), "1.0 + 1.0 * x + 2.0 * y <= 4.0")
|
|
|
|
def test_lower_bounded_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
bounded_expr = x + 2 * y + 1.0 >= 2.0
|
|
self.assertEqual(
|
|
repr(bounded_expr),
|
|
f'LinearSum((LinearSum((<Variable id: 0, name: {"x"!r}>,'
|
|
f' LinearTerm(<Variable id: 1, name: {"y"!r}>, 2))), 1.0)) >= 2.0',
|
|
)
|
|
self.assertEqual(str(bounded_expr), "1.0 + 1.0 * x + 2.0 * y >= 2.0")
|
|
|
|
def test_bounded_expr(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
bounded_expr = (2.0 <= x + 2 * y + 1.0) <= 4.0
|
|
self.assertEqual(
|
|
repr(bounded_expr),
|
|
f'2.0 <= LinearSum((LinearSum((<Variable id: 0, name: {"x"!r}>,'
|
|
f' LinearTerm(<Variable id: 1, name: {"y"!r}>, 2))), 1.0)) <= 4.0',
|
|
)
|
|
self.assertEqual(str(bounded_expr), "2.0 <= 1.0 + 1.0 * x + 2.0 * y <= 4.0")
|
|
|
|
|
|
# TODO(b/216492143): change __str__ to match C++ implementation in cl/421649402.
|
|
class LinearStrAndReprTest(parameterized.TestCase):
|
|
|
|
def test_sorting_ok(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
zero_plus_var_plus_pos_term = 0 + x + 2 * y
|
|
self.assertEqual(
|
|
repr(zero_plus_var_plus_pos_term),
|
|
f'LinearSum((LinearSum((0, <Variable id: 0, name: {"x"!r}>)), '
|
|
f'LinearTerm(<Variable id: 1, name: {"y"!r}>, 2)))',
|
|
)
|
|
# This fails if we don't sort by variable names in Variable.__str__().
|
|
self.assertEqual(str(zero_plus_var_plus_pos_term), "0.0 + 1.0 * x + 2.0 * y")
|
|
|
|
def test_simple_expressions(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
|
|
var_plus_pos_term = x + 2 * y
|
|
self.assertEqual(
|
|
repr(var_plus_pos_term),
|
|
f'LinearSum((<Variable id: 0, name: {"x"!r}>, '
|
|
f'LinearTerm(<Variable id: 1, name: {"y"!r}>, 2)))',
|
|
)
|
|
self.assertEqual(str(var_plus_pos_term), "0.0 + 1.0 * x + 2.0 * y")
|
|
|
|
var_plus_neg_term = x - 3 * y
|
|
self.assertEqual(
|
|
repr(var_plus_neg_term),
|
|
f'LinearSum((<Variable id: 0, name: {"x"!r}>, '
|
|
f'LinearTerm(<Variable id: 1, name: {"y"!r}>, -3)))',
|
|
)
|
|
self.assertEqual(str(var_plus_neg_term), "0.0 + 1.0 * x - 3.0 * y")
|
|
|
|
var_plus_num = x + 1.0
|
|
self.assertEqual(
|
|
repr(var_plus_num), f'LinearSum((<Variable id: 0, name: {"x"!r}>, 1.0))'
|
|
)
|
|
self.assertEqual(str(var_plus_num), "1.0 + 1.0 * x")
|
|
|
|
num_times_var_sum = 2 * (x + y + 3)
|
|
self.assertEqual(
|
|
repr(num_times_var_sum),
|
|
"LinearProduct(2.0, LinearSum((LinearSum((<Variable id: 0, name:"
|
|
f' {"x"!r}>, <Variable id: 1, name: {"y"!r}>)), 3)))',
|
|
)
|
|
self.assertEqual(str(num_times_var_sum), "6.0 + 2.0 * x + 2.0 * y")
|
|
self.assertEqual(
|
|
repr(model.as_flat_linear_expression(num_times_var_sum)),
|
|
f'LinearExpression(6.0, {"{"!s}'
|
|
f'<Variable id: 0, name: {"x"!r}>: 2.0, '
|
|
f'<Variable id: 1, name: {"y"!r}>: 2.0{"}"!s})',
|
|
)
|
|
self.assertEqual(
|
|
str(model.as_flat_linear_expression(num_times_var_sum)),
|
|
"6.0 + 2.0 * x + 2.0 * y",
|
|
)
|
|
|
|
linear_term = 2 * x
|
|
self.assertEqual(
|
|
repr(linear_term), f'LinearTerm(<Variable id: 0, name: {"x"!r}>, 2)'
|
|
)
|
|
self.assertEqual(str(linear_term), "2 * x")
|
|
|
|
def test_sum_expressions(self) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x{i}") for i in range(3)]
|
|
|
|
linear_sum = model.LinearSum(i * x[i] for i in range(3))
|
|
self.assertEqual(
|
|
repr(linear_sum),
|
|
"LinearSum(("
|
|
f'LinearTerm(<Variable id: 0, name: {"x0"!r}>, 0), '
|
|
f'LinearTerm(<Variable id: 1, name: {"x1"!r}>, 1), '
|
|
f'LinearTerm(<Variable id: 2, name: {"x2"!r}>, 2)))',
|
|
)
|
|
self.assertEqual(str(linear_sum), "0.0 + 1.0 * x1 + 2.0 * x2")
|
|
|
|
python_sum = sum(i * x[i] for i in range(3))
|
|
self.assertEqual(
|
|
repr(python_sum),
|
|
"LinearSum(("
|
|
"LinearSum(("
|
|
f'LinearSum((0, LinearTerm(<Variable id: 0, name: {"x0"!r}>, 0))), '
|
|
f'LinearTerm(<Variable id: 1, name: {"x1"!r}>, 1))), '
|
|
f'LinearTerm(<Variable id: 2, name: {"x2"!r}>, 2)))',
|
|
)
|
|
self.assertEqual(str(python_sum), "0.0 + 1.0 * x1 + 2.0 * x2")
|
|
|
|
|
|
# TODO(b/216492143): change __str__ to match C++ implementation in cl/421649402.
|
|
class QuadraticStrAndReprTest(parameterized.TestCase):
|
|
|
|
def test_sorting_ok(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
zero_plus_var_plus_pos_term = 0 + x + 2 * y + x * x
|
|
self.assertEqual(
|
|
repr(zero_plus_var_plus_pos_term),
|
|
"QuadraticSum(("
|
|
f'LinearSum((LinearSum((0, <Variable id: 0, name: {"x"!r}>)), '
|
|
f'LinearTerm(<Variable id: 1, name: {"y"!r}>, 2))), '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 0, name: {"x"!r}>, '
|
|
f'<Variable id: 0, name: {"x"!r}>), 1.0)))',
|
|
)
|
|
# This fails if we don't sort by variable names in Variable.__str__().
|
|
self.assertEqual(
|
|
str(zero_plus_var_plus_pos_term),
|
|
"0.0 + 1.0 * x + 2.0 * y + 1.0 * x * x",
|
|
)
|
|
|
|
def test_simple_expressions(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
|
|
var_plus_pos_term = x + 2 * y * y
|
|
self.assertEqual(
|
|
repr(var_plus_pos_term),
|
|
f'QuadraticSum((<Variable id: 0, name: {"x"!r}>, '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 1, name: {"y"!r}>, '
|
|
f'<Variable id: 1, name: {"y"!r}>), 2)))',
|
|
)
|
|
self.assertEqual(str(var_plus_pos_term), "0.0 + 1.0 * x + 2.0 * y * y")
|
|
|
|
var_plus_neg_term = x - 3 * y * y
|
|
self.assertEqual(
|
|
repr(var_plus_neg_term),
|
|
f'QuadraticSum((<Variable id: 0, name: {"x"!r}>, '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 1, name: {"y"!r}>, '
|
|
f'<Variable id: 1, name: {"y"!r}>), -3)))',
|
|
)
|
|
self.assertEqual(str(var_plus_neg_term), "0.0 + 1.0 * x - 3.0 * y * y")
|
|
|
|
num_times_term_sum = 2 * (x * x + y + 3)
|
|
self.assertEqual(
|
|
repr(num_times_term_sum),
|
|
"QuadraticProduct(2.0,"
|
|
" QuadraticSum((QuadraticSum((QuadraticTerm(QuadraticTermKey(<Variable"
|
|
f' id: 0, name: {"x"!r}>, <Variable id: 0, name: {"x"!r}>), 1.0),'
|
|
f' <Variable id: 1, name: {"y"!r}>)), 3)))',
|
|
)
|
|
self.assertEqual(str(num_times_term_sum), "6.0 + 2.0 * y + 2.0 * x * x")
|
|
self.assertEqual(
|
|
repr(model.as_flat_quadratic_expression(num_times_term_sum)),
|
|
f'QuadraticExpression(6.0, {"{"!s}'
|
|
f'<Variable id: 1, name: {"y"!r}>: 2.0{"}"!s}, '
|
|
f'{"{"!s}QuadraticTermKey(<Variable id: 0, name: {"x"!r}>, '
|
|
f'<Variable id: 0, name: {"x"!r}>): 2.0{"}"!s})',
|
|
)
|
|
self.assertEqual(
|
|
str(model.as_flat_quadratic_expression(num_times_term_sum)),
|
|
"6.0 + 2.0 * y + 2.0 * x * x",
|
|
)
|
|
|
|
linear_times_linear = (2 * x) * (1 + y)
|
|
self.assertEqual(
|
|
repr(linear_times_linear),
|
|
f'LinearLinearProduct(LinearTerm(<Variable id: 0, name: {"x"!r}>, 2), '
|
|
f'LinearSum((1, <Variable id: 1, name: {"y"!r}>)))',
|
|
)
|
|
self.assertEqual(str(linear_times_linear), "0.0 + 2.0 * x + 2.0 * x * y")
|
|
|
|
quadratic_term = 2 * x * x
|
|
self.assertEqual(
|
|
repr(quadratic_term),
|
|
"QuadraticTerm(QuadraticTermKey(<Variable id: 0, "
|
|
f'name: {"x"!r}>, <Variable id: 0, name: {"x"!r}>), 2)',
|
|
)
|
|
self.assertEqual(str(quadratic_term), "2 * x * x")
|
|
|
|
def test_sum_expressions(self) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x{i}") for i in range(3)]
|
|
|
|
quadratic_sum = model.QuadraticSum(i * x[i] * x[i] for i in range(3))
|
|
self.assertEqual(
|
|
repr(quadratic_sum),
|
|
"QuadraticSum(("
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 0, name: {"x0"!r}>, '
|
|
f'<Variable id: 0, name: {"x0"!r}>), 0), '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 1, name: {"x1"!r}>, '
|
|
f'<Variable id: 1, name: {"x1"!r}>), 1), '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 2, name: {"x2"!r}>, '
|
|
f'<Variable id: 2, name: {"x2"!r}>), 2)))',
|
|
)
|
|
self.assertEqual(str(quadratic_sum), "0.0 + 1.0 * x1 * x1 + 2.0 * x2 * x2")
|
|
|
|
python_sum = sum(i * x[i] * x[i] for i in range(3))
|
|
self.assertEqual(
|
|
repr(python_sum),
|
|
"QuadraticSum(("
|
|
"QuadraticSum(("
|
|
"QuadraticSum((0, QuadraticTerm(QuadraticTermKey(<Variable id: 0, "
|
|
f'name: {"x0"!r}>, <Variable id: 0, name: {"x0"!r}>), 0))), '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 1, name: {"x1"!r}>, '
|
|
f'<Variable id: 1, name: {"x1"!r}>), 1))), '
|
|
f'QuadraticTerm(QuadraticTermKey(<Variable id: 2, name: {"x2"!r}>, '
|
|
f'<Variable id: 2, name: {"x2"!r}>), 2)))',
|
|
)
|
|
self.assertEqual(str(python_sum), "0.0 + 1.0 * x1 * x1 + 2.0 * x2 * x2")
|
|
|
|
|
|
class LinearNumberOpTestsParameters(NamedTuple):
|
|
linear_type: str
|
|
constant: Union[float, int]
|
|
linear_first: bool
|
|
|
|
def test_suffix(self):
|
|
if self.linear_first:
|
|
return f"_{self.linear_type}_{type(self.constant).__name__}"
|
|
else:
|
|
return f"_{type(self.constant).__name__}_{self.linear_type}"
|
|
|
|
|
|
def all_linear_number_op_parameters() -> List[LinearNumberOpTestsParameters]:
|
|
result = []
|
|
for t in _LINEAR_TYPES:
|
|
for c in (2, 0.25):
|
|
for first in (True, False):
|
|
result.append(
|
|
LinearNumberOpTestsParameters(
|
|
linear_type=t, constant=c, linear_first=first
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
# Test all operations (including inplace) between a number and a Linear object
|
|
class LinearNumberOpTests(parameterized.TestCase):
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.linear_type, p.constant, p.linear_first)
|
|
for p in all_linear_number_op_parameters()
|
|
)
|
|
def test_mult(
|
|
self, linear_type: str, constant: Union[float, int], linear_first: bool
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
if linear_type == "Variable":
|
|
linear = x
|
|
expected_type = model.LinearTerm
|
|
expected_offset = 0
|
|
expected_terms = {x: constant}
|
|
elif linear_type == "LinearTerm":
|
|
linear = model.LinearTerm(x, 2)
|
|
expected_type = model.LinearTerm
|
|
expected_offset = 0
|
|
expected_terms = {x: 2 * constant}
|
|
elif linear_type == "LinearExpression":
|
|
linear = model.LinearExpression(x - 2 * y + 3)
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 3 * constant
|
|
expected_terms = {x: constant, y: -2 * constant}
|
|
elif linear_type == "LinearSum":
|
|
linear = model.LinearSum((x, -2 * y, 3))
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 3 * constant
|
|
expected_terms = {x: constant, y: -2 * constant}
|
|
elif linear_type == "LinearProduct":
|
|
linear = model.LinearProduct(2, x)
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 0
|
|
expected_terms = {x: 2 * constant}
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {linear_type!r}")
|
|
|
|
# Check __mul__ and __rmul__
|
|
s = linear * constant if linear_first else constant * linear
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertIsInstance(s, expected_type)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.terms), expected_terms)
|
|
|
|
# Also check __imul__
|
|
if linear_first:
|
|
expr = linear
|
|
expr *= constant
|
|
else:
|
|
expr = constant
|
|
expr *= linear
|
|
e_inplace = model.as_flat_linear_expression(expr)
|
|
self.assertIsInstance(expr, expected_type)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.terms), expected_terms)
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.linear_type, p.constant, p.linear_first)
|
|
for p in all_linear_number_op_parameters()
|
|
)
|
|
def test_div(
|
|
self, linear_type: str, constant: Union[float, int], linear_first: bool
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
if linear_type == "Variable":
|
|
linear = x
|
|
expected_type = model.LinearTerm
|
|
expected_offset = 0
|
|
expected_terms = {x: 1 / constant}
|
|
elif linear_type == "LinearTerm":
|
|
linear = model.LinearTerm(x, 2)
|
|
expected_type = model.LinearTerm
|
|
expected_offset = 0
|
|
expected_terms = {x: 2 / constant}
|
|
elif linear_type == "LinearExpression":
|
|
linear = model.LinearExpression(x - 2 * y + 3)
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 3 / constant
|
|
expected_terms = {x: 1 / constant, y: -2 / constant}
|
|
elif linear_type == "LinearSum":
|
|
linear = model.LinearSum((x, -2 * y, 3))
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 3 / constant
|
|
expected_terms = {x: 1 / constant, y: -2 / constant}
|
|
elif linear_type == "LinearProduct":
|
|
linear = model.LinearProduct(2, x)
|
|
expected_type = model.LinearProduct
|
|
expected_offset = 0
|
|
expected_terms = {x: 2 / constant}
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {linear_type!r}")
|
|
|
|
# Check __truediv__
|
|
if linear_first:
|
|
s = linear / constant
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertIsInstance(s, expected_type)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.terms), expected_terms)
|
|
else:
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for /: {type(constant).__name__!r} "
|
|
f"and {type(linear).__name__!r}",
|
|
):
|
|
s = constant / linear # pytype: disable=unsupported-operands
|
|
|
|
# Also check __itruediv__
|
|
if linear_first:
|
|
linear /= constant
|
|
e_inplace = model.as_flat_linear_expression(linear)
|
|
self.assertIsInstance(linear, expected_type)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.terms), expected_terms)
|
|
else:
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for /=: {type(constant).__name__!r} "
|
|
f"and {type(linear).__name__!r}",
|
|
):
|
|
expr = constant
|
|
expr /= linear # pytype: disable=unsupported-operands
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.linear_type, p.constant, p.linear_first)
|
|
for p in all_linear_number_op_parameters()
|
|
)
|
|
def test_add(
|
|
self, linear_type: str, constant: Union[float, int], linear_first: bool
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
if linear_type == "Variable":
|
|
linear = x
|
|
expected_offset = constant
|
|
expected_terms = {x: 1}
|
|
elif linear_type == "LinearTerm":
|
|
linear = model.LinearTerm(x, 2)
|
|
expected_offset = constant
|
|
expected_terms = {x: 2}
|
|
elif linear_type == "LinearExpression":
|
|
linear = model.LinearExpression(x - 2 * y + 1)
|
|
expected_offset = constant + 1
|
|
expected_terms = {x: 1, y: -2}
|
|
elif linear_type == "LinearSum":
|
|
linear = model.LinearSum((x, -2 * y, 1))
|
|
expected_offset = constant + 1
|
|
expected_terms = {x: 1, y: -2}
|
|
elif linear_type == "LinearProduct":
|
|
linear = model.LinearProduct(2, x)
|
|
expected_offset = constant
|
|
expected_terms = {x: 2}
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {linear_type!r}")
|
|
|
|
# Check __add__ and __radd__
|
|
s = linear + constant if linear_first else constant + linear
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertIsInstance(s, model.LinearSum)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.terms), expected_terms)
|
|
|
|
# Also check __iadd__
|
|
if linear_first:
|
|
expr = linear
|
|
expr += constant
|
|
else:
|
|
expr = constant
|
|
expr += linear
|
|
e_inplace = model.as_flat_linear_expression(expr)
|
|
self.assertIsInstance(expr, model.LinearSum)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.terms), expected_terms)
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.linear_type, p.constant, p.linear_first)
|
|
for p in all_linear_number_op_parameters()
|
|
)
|
|
def test_sub(
|
|
self, linear_type: str, constant: Union[float, int], linear_first: bool
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
sign = 1 if linear_first else -1
|
|
if linear_type == "Variable":
|
|
linear = x
|
|
expected_offset = -sign * constant
|
|
expected_terms = {x: sign}
|
|
elif linear_type == "LinearTerm":
|
|
linear = model.LinearTerm(x, 2)
|
|
expected_offset = -sign * constant
|
|
expected_terms = {x: sign * 2}
|
|
elif linear_type == "LinearExpression":
|
|
linear = model.LinearExpression(x - 2 * y + 3)
|
|
expected_offset = -sign * constant + 3 * sign
|
|
expected_terms = {x: sign, y: -sign * 2}
|
|
elif linear_type == "LinearSum":
|
|
linear = model.LinearSum((x, -2 * y, 3))
|
|
expected_offset = -sign * constant + 3 * sign
|
|
expected_terms = {x: sign, y: -sign * 2}
|
|
elif linear_type == "LinearProduct":
|
|
linear = model.LinearProduct(2, x)
|
|
expected_offset = -sign * constant
|
|
expected_terms = {x: sign * 2}
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {linear_type!r}")
|
|
|
|
# Check __sub__ and __rsub__
|
|
s = linear - constant if linear_first else constant - linear
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertIsInstance(s, model.LinearSum)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.terms), expected_terms)
|
|
|
|
# Also check __isub__
|
|
if linear_first:
|
|
linear -= constant
|
|
e_inplace = model.as_flat_linear_expression(linear)
|
|
self.assertIsInstance(linear, model.LinearSum)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.terms), expected_terms)
|
|
|
|
|
|
class QuadraticTermKey(absltest.TestCase):
|
|
|
|
# Mock QuadraticTermKey.__hash__ to have a collision in the dictionary lookup
|
|
# so that a correct behavior of term1 == term2 is needed to recover the
|
|
# values. For instance, if QuadraticTermKey.__eq__ only compared equality of
|
|
# the first variables in the keys, this test would fail.
|
|
@mock.patch.object(model.QuadraticTermKey, "__hash__")
|
|
def test_var_dict(self, fixed_hash: mock.MagicMock) -> None:
|
|
fixed_hash.return_value = 111
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
var_dict = {xx: 1, xy: 2, yy: 3}
|
|
self.assertEqual(xx.__hash__(), 111)
|
|
self.assertEqual(xy.__hash__(), 111)
|
|
self.assertEqual(yy.__hash__(), 111)
|
|
self.assertEqual(var_dict[xx], 1)
|
|
self.assertEqual(var_dict[xy], 2)
|
|
self.assertEqual(var_dict[yy], 3)
|
|
|
|
|
|
class QuadraticNumberOpTestsParameters(NamedTuple):
|
|
quadratic_type: str
|
|
constant: Union[float, int]
|
|
quadratic_first: bool
|
|
|
|
def test_suffix(self):
|
|
if self.quadratic_first:
|
|
return f"_{self.quadratic_type}_{type(self.constant).__name__}"
|
|
else:
|
|
return f"_{type(self.constant).__name__}_{self.quadratic_type}"
|
|
|
|
|
|
def all_quadratic_number_op_parameters() -> List[QuadraticNumberOpTestsParameters]:
|
|
result = []
|
|
for t in _QUADRATIC_TYPES:
|
|
for c in (2, 0.25):
|
|
for first in (True, False):
|
|
result.append(
|
|
QuadraticNumberOpTestsParameters(
|
|
quadratic_type=t, constant=c, quadratic_first=first
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
# Test all operations (including inplace) between a number and a Quadratic
|
|
# object.
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.quadratic_type, p.constant, p.quadratic_first)
|
|
for p in all_quadratic_number_op_parameters()
|
|
)
|
|
class QuadraticNumberOpTests(parameterized.TestCase):
|
|
|
|
def test_mult(
|
|
self,
|
|
quadratic_type: str,
|
|
constant: Union[float, int],
|
|
quadratic_first: bool,
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
if quadratic_type == "QuadraticTerm":
|
|
quadratic = model.QuadraticTerm(xy, 2)
|
|
expected_type = model.QuadraticTerm
|
|
expected_offset = 0
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xy: 2 * constant}
|
|
elif quadratic_type == "QuadraticExpression":
|
|
quadratic = model.QuadraticExpression(x * x - 2 * x * y - x + 3)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 3 * constant
|
|
expected_linear_terms = {x: -constant}
|
|
expected_quadratic_terms = {xx: constant, xy: -2 * constant}
|
|
elif quadratic_type == "QuadraticSum":
|
|
quadratic = model.QuadraticSum((x, -2 * y, 3, y * y))
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 3 * constant
|
|
expected_linear_terms = {x: constant, y: -2 * constant}
|
|
expected_quadratic_terms = {yy: constant}
|
|
elif quadratic_type == "LinearLinearProduct":
|
|
quadratic = model.LinearLinearProduct(x + y + 1, x + 1)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = constant
|
|
expected_linear_terms = {x: 2 * constant, y: constant}
|
|
expected_quadratic_terms = {xx: constant, xy: constant}
|
|
elif quadratic_type == "QuadraticProduct":
|
|
quadratic = model.QuadraticProduct(2, x * x)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 0.0
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xx: 2 * constant}
|
|
else:
|
|
raise AssertionError(f"unknown quaratic type: {quadratic_type!r}")
|
|
|
|
# Check __mul__ and __rmul__
|
|
s = quadratic * constant if quadratic_first else constant * quadratic
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertIsInstance(s, expected_type)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e.quadratic_terms), expected_quadratic_terms)
|
|
|
|
# Also check __imul__
|
|
if quadratic_first:
|
|
expr = quadratic
|
|
expr *= constant
|
|
else:
|
|
expr = constant
|
|
expr *= quadratic
|
|
e_inplace = model.as_flat_quadratic_expression(expr)
|
|
self.assertIsInstance(expr, expected_type)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e_inplace.quadratic_terms), expected_quadratic_terms)
|
|
|
|
def test_div(
|
|
self,
|
|
quadratic_type: str,
|
|
constant: Union[float, int],
|
|
quadratic_first: bool,
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
if quadratic_type == "QuadraticTerm":
|
|
quadratic = model.QuadraticTerm(xy, 2)
|
|
expected_type = model.QuadraticTerm
|
|
expected_offset = 0
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xy: 2 / constant}
|
|
elif quadratic_type == "QuadraticExpression":
|
|
quadratic = model.QuadraticExpression(x * x - 2 * x * y - x + 3)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 3 / constant
|
|
expected_linear_terms = {x: -1 / constant}
|
|
expected_quadratic_terms = {xx: 1 / constant, xy: -2 / constant}
|
|
elif quadratic_type == "QuadraticSum":
|
|
quadratic = model.QuadraticSum((x, -2 * y, 3, y * y))
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 3 / constant
|
|
expected_linear_terms = {x: 1 / constant, y: -2 / constant}
|
|
expected_quadratic_terms = {yy: 1 / constant}
|
|
elif quadratic_type == "LinearLinearProduct":
|
|
quadratic = model.LinearLinearProduct(x + y + 1, x + 1)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 1 / constant
|
|
expected_linear_terms = {x: 2 / constant, y: 1 / constant}
|
|
expected_quadratic_terms = {xx: 1 / constant, xy: 1 / constant}
|
|
elif quadratic_type == "QuadraticProduct":
|
|
quadratic = model.QuadraticProduct(2, x * x)
|
|
expected_type = model.QuadraticProduct
|
|
expected_offset = 0.0
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xx: 2 / constant}
|
|
else:
|
|
raise AssertionError(f"unknown quaratic type: {quadratic_type!r}")
|
|
|
|
# Check __truediv__
|
|
if quadratic_first:
|
|
s = quadratic / constant
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertIsInstance(s, expected_type)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e.quadratic_terms), expected_quadratic_terms)
|
|
else:
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for /: {type(constant).__name__!r} "
|
|
f"and {type(quadratic).__name__!r}",
|
|
):
|
|
s = constant / quadratic # pytype: disable=unsupported-operands
|
|
|
|
# Also check __itruediv__
|
|
if quadratic_first:
|
|
quadratic /= constant
|
|
e_inplace = model.as_flat_quadratic_expression(quadratic)
|
|
self.assertIsInstance(quadratic, expected_type)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(
|
|
dict(e_inplace.quadratic_terms), expected_quadratic_terms
|
|
)
|
|
else:
|
|
with self.assertRaisesWithLiteralMatch(
|
|
TypeError,
|
|
f"unsupported operand type(s) for /=: {type(constant).__name__!r} "
|
|
f"and {type(quadratic).__name__!r}",
|
|
):
|
|
expr = constant
|
|
expr /= quadratic # pytype: disable=unsupported-operands
|
|
|
|
def test_add(
|
|
self,
|
|
quadratic_type: str,
|
|
constant: Union[float, int],
|
|
quadratic_first: bool,
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
if quadratic_type == "QuadraticTerm":
|
|
quadratic = model.QuadraticTerm(xy, 2)
|
|
expected_offset = constant
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xy: 2}
|
|
elif quadratic_type == "QuadraticExpression":
|
|
quadratic = model.QuadraticExpression(x * x - 2 * x * y - x + 3)
|
|
expected_offset = 3 + constant
|
|
expected_linear_terms = {x: -1}
|
|
expected_quadratic_terms = {xx: 1, xy: -2}
|
|
elif quadratic_type == "QuadraticSum":
|
|
quadratic = model.QuadraticSum((x, -2 * y, 3, y * y))
|
|
expected_offset = 3 + constant
|
|
expected_linear_terms = {x: 1, y: -2}
|
|
expected_quadratic_terms = {yy: 1}
|
|
elif quadratic_type == "LinearLinearProduct":
|
|
quadratic = model.LinearLinearProduct(x + y + 1, x + 1)
|
|
expected_offset = 1 + constant
|
|
expected_linear_terms = {x: 2, y: 1}
|
|
expected_quadratic_terms = {xx: 1, xy: 1}
|
|
elif quadratic_type == "QuadraticProduct":
|
|
quadratic = model.QuadraticProduct(2, x * x)
|
|
expected_offset = constant
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xx: 2}
|
|
else:
|
|
raise AssertionError(f"unknown quaratic type: {quadratic_type!r}")
|
|
|
|
# Check __add__ and __radd__
|
|
s = quadratic + constant if quadratic_first else constant + quadratic
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertIsInstance(s, model.QuadraticSum)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e.quadratic_terms), expected_quadratic_terms)
|
|
|
|
# Also check __iadd__
|
|
if quadratic_first:
|
|
expr = quadratic
|
|
expr += constant
|
|
else:
|
|
expr = constant
|
|
expr += quadratic
|
|
e_inplace = model.as_flat_quadratic_expression(expr)
|
|
self.assertIsInstance(expr, model.QuadraticSum)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e_inplace.quadratic_terms), expected_quadratic_terms)
|
|
|
|
def test_sub(
|
|
self,
|
|
quadratic_type: str,
|
|
constant: Union[float, int],
|
|
quadratic_first: bool,
|
|
) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
sign = 1 if quadratic_first else -1
|
|
if quadratic_type == "QuadraticTerm":
|
|
quadratic = model.QuadraticTerm(xy, 2)
|
|
expected_offset = -sign * constant
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xy: sign * 2}
|
|
elif quadratic_type == "QuadraticExpression":
|
|
quadratic = model.QuadraticExpression(x * x - 2 * x * y - x + 3)
|
|
expected_offset = sign * 3 - sign * constant
|
|
expected_linear_terms = {x: sign * (-1)}
|
|
expected_quadratic_terms = {xx: sign * 1, xy: sign * (-2)}
|
|
elif quadratic_type == "QuadraticSum":
|
|
quadratic = model.QuadraticSum((x, -2 * y, 3, y * y))
|
|
expected_offset = sign * 3 - sign * constant
|
|
expected_linear_terms = {x: sign * 1, y: sign * (-2)}
|
|
expected_quadratic_terms = {yy: sign}
|
|
elif quadratic_type == "LinearLinearProduct":
|
|
quadratic = model.LinearLinearProduct(x + y + 1, x + 1)
|
|
expected_offset = sign * 1 - sign * constant
|
|
expected_linear_terms = {x: sign * 2, y: sign * 1}
|
|
expected_quadratic_terms = {xx: sign, xy: sign}
|
|
elif quadratic_type == "QuadraticProduct":
|
|
quadratic = model.QuadraticProduct(2, x * x)
|
|
expected_offset = -sign * constant
|
|
expected_linear_terms = {}
|
|
expected_quadratic_terms = {xx: sign * 2}
|
|
else:
|
|
raise AssertionError(f"unknown quaratic type: {quadratic_type!r}")
|
|
|
|
# Check __sub__ and __rsub__
|
|
s = quadratic - constant if quadratic_first else constant - quadratic
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertIsInstance(s, model.QuadraticSum)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(dict(e.quadratic_terms), expected_quadratic_terms)
|
|
|
|
# Also check __isub__
|
|
if quadratic_first:
|
|
quadratic -= constant
|
|
e_inplace = model.as_flat_quadratic_expression(quadratic)
|
|
self.assertIsInstance(quadratic, model.QuadraticSum)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(dict(e_inplace.linear_terms), expected_linear_terms)
|
|
self.assertDictEqual(
|
|
dict(e_inplace.quadratic_terms), expected_quadratic_terms
|
|
)
|
|
|
|
|
|
class LinearLinearAddSubTestParams(NamedTuple):
|
|
lhs_type: str
|
|
rhs_type: str
|
|
subtract: bool
|
|
|
|
def test_suffix(self):
|
|
return (
|
|
f"_{self.lhs_type}_{self.rhs_type}_"
|
|
f'{"subtract" if self.subtract else "add"}'
|
|
)
|
|
|
|
|
|
def all_linear_linear_add_sub_params() -> List[LinearLinearAddSubTestParams]:
|
|
result = []
|
|
for lhs_type in _LINEAR_TYPES:
|
|
for rhs_type in _LINEAR_TYPES:
|
|
for sub in (True, False):
|
|
result.append(
|
|
LinearLinearAddSubTestParams(
|
|
lhs_type=lhs_type, rhs_type=rhs_type, subtract=sub
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
# Test add/sub operations (including inplace) between two Linear objects.
|
|
class LinearLinearAddSubTest(parameterized.TestCase):
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.lhs_type, p.rhs_type, p.subtract)
|
|
for p in all_linear_linear_add_sub_params()
|
|
)
|
|
def test_add_and_sub(self, lhs_type: str, rhs_type: str, subtract: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
x_coefficient = 0
|
|
y_coefficient = 0
|
|
expected_offset = 0
|
|
sign = -1 if subtract else 1
|
|
# Setup first linear term.
|
|
if lhs_type == "Variable":
|
|
first_linear = x
|
|
x_coefficient += 1
|
|
elif lhs_type == "LinearTerm":
|
|
first_linear = model.LinearTerm(x, 2)
|
|
x_coefficient += 2
|
|
elif lhs_type == "LinearExpression":
|
|
first_linear = model.LinearExpression(x - 2 * y + 1)
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
elif lhs_type == "LinearSum":
|
|
first_linear = model.LinearSum((x, -2 * y, 1))
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
elif lhs_type == "LinearProduct":
|
|
first_linear = model.LinearProduct(2, x)
|
|
x_coefficient += 2
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {lhs_type!r}")
|
|
|
|
# Setup second linear term
|
|
if rhs_type == "Variable":
|
|
second_linear = y
|
|
y_coefficient += sign * 1
|
|
elif rhs_type == "LinearTerm":
|
|
second_linear = model.LinearTerm(y, 2)
|
|
y_coefficient += sign * 2
|
|
elif rhs_type == "LinearExpression":
|
|
second_linear = model.LinearExpression(y - 2 * x + 1)
|
|
x_coefficient += sign * (-2)
|
|
y_coefficient += sign * 1
|
|
expected_offset += sign * 1
|
|
elif rhs_type == "LinearSum":
|
|
second_linear = model.LinearSum((y, -2 * x, 1))
|
|
x_coefficient += sign * (-2)
|
|
y_coefficient += sign * 1
|
|
expected_offset += sign * 1
|
|
elif rhs_type == "LinearProduct":
|
|
second_linear = model.LinearProduct(2, y)
|
|
y_coefficient += sign * 2
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {rhs_type!r}")
|
|
|
|
# Check __add__ and __sub__
|
|
s = first_linear - second_linear if subtract else first_linear + second_linear
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertIsInstance(s, model.LinearSum)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqual(dict(e.terms), {x: x_coefficient, y: y_coefficient})
|
|
|
|
# Also check __iadd__ and __isub__
|
|
if subtract:
|
|
first_linear -= second_linear
|
|
else:
|
|
first_linear += second_linear
|
|
e_inplace = model.as_flat_linear_expression(first_linear)
|
|
self.assertIsInstance(first_linear, model.LinearSum)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqual(
|
|
dict(e_inplace.terms), {x: x_coefficient, y: y_coefficient}
|
|
)
|
|
|
|
|
|
class LinearQuadraticAddSubTestParams(NamedTuple):
|
|
lhs_type: str
|
|
rhs_type: str
|
|
subtract: bool
|
|
|
|
def test_suffix(self):
|
|
return (
|
|
f"_{self.lhs_type}_{self.rhs_type}_"
|
|
f'{"subtract" if self.subtract else "add"}'
|
|
)
|
|
|
|
|
|
def all_linear_quadratic_add_sub_params() -> List[LinearQuadraticAddSubTestParams]:
|
|
result = []
|
|
for lhs_type in _LINEAR_TYPES + _QUADRATIC_TYPES:
|
|
for rhs_type in _LINEAR_TYPES + _QUADRATIC_TYPES:
|
|
for sub in (True, False):
|
|
result.append(
|
|
LinearQuadraticAddSubTestParams(
|
|
lhs_type=lhs_type, rhs_type=rhs_type, subtract=sub
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
# Test add/sub operations (including inplace) between Quadratic and Linear
|
|
# objects. Also re-checks the operations for the pure Linear check when the
|
|
# result is intereted as a QuadraticExpression.
|
|
class LinearQuadraticAddSubTest(parameterized.TestCase):
|
|
|
|
def assertDictEqualWithZeroDefault(
|
|
self, dict1: dict[Any, float], dict2: dict[Any, float]
|
|
) -> None:
|
|
for key in dict1.keys():
|
|
if key not in dict2:
|
|
dict2[key] = 0.0
|
|
for key in dict2.keys():
|
|
if key not in dict1:
|
|
dict1[key] = 0.0
|
|
self.assertDictEqual(dict1, dict2)
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.lhs_type, p.rhs_type, p.subtract)
|
|
for p in all_linear_quadratic_add_sub_params()
|
|
)
|
|
def test_add_and_sub(self, lhs_type: str, rhs_type: str, subtract: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
x_coefficient = 0
|
|
y_coefficient = 0
|
|
xx_coefficient = 0
|
|
xy_coefficient = 0
|
|
yy_coefficient = 0
|
|
expected_offset = 0
|
|
sign = -1 if subtract else 1
|
|
# Setup first linear term.
|
|
if lhs_type == "Variable":
|
|
first_linear_or_quadratic = x
|
|
x_coefficient += 1
|
|
elif lhs_type == "LinearTerm":
|
|
first_linear_or_quadratic = model.LinearTerm(x, 2)
|
|
x_coefficient += 2
|
|
elif lhs_type == "LinearExpression":
|
|
first_linear_or_quadratic = model.LinearExpression(x - 2 * y + 1)
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
elif lhs_type == "LinearSum":
|
|
first_linear_or_quadratic = model.LinearSum((x, -2 * y, 1))
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
elif lhs_type == "LinearProduct":
|
|
first_linear_or_quadratic = model.LinearProduct(2, x)
|
|
x_coefficient += 2
|
|
elif lhs_type == "QuadraticTerm":
|
|
first_linear_or_quadratic = model.QuadraticTerm(xx, 2)
|
|
xx_coefficient += 2
|
|
elif lhs_type == "QuadraticExpression":
|
|
first_linear_or_quadratic = model.QuadraticExpression(
|
|
x - 2 * y + 1 + 3 * x * x - 4 * x * y
|
|
)
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
xx_coefficient += 3
|
|
xy_coefficient += -4
|
|
elif lhs_type == "QuadraticSum":
|
|
first_linear_or_quadratic = model.QuadraticSum(
|
|
(x, -2 * y, 1, y * y, -2 * x * y)
|
|
)
|
|
x_coefficient += 1
|
|
y_coefficient += -2
|
|
expected_offset += 1
|
|
yy_coefficient += 1
|
|
xy_coefficient += -2
|
|
elif lhs_type == "LinearLinearProduct":
|
|
first_linear_or_quadratic = model.LinearLinearProduct(y, x + y)
|
|
yy_coefficient += 1
|
|
xy_coefficient += 1
|
|
elif lhs_type == "QuadraticProduct":
|
|
first_linear_or_quadratic = model.QuadraticProduct(2, y * (x + y))
|
|
yy_coefficient += 2
|
|
xy_coefficient += 2
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {lhs_type!r}")
|
|
|
|
# Setup second linear term
|
|
if rhs_type == "Variable":
|
|
second_linear_or_quadratic = y
|
|
y_coefficient += 1 * sign
|
|
elif rhs_type == "LinearTerm":
|
|
second_linear_or_quadratic = model.LinearTerm(y, 2)
|
|
y_coefficient += 2 * sign
|
|
elif rhs_type == "LinearExpression":
|
|
second_linear_or_quadratic = model.LinearExpression(y - 2 * x + 1)
|
|
x_coefficient += -2 * sign
|
|
y_coefficient += 1 * sign
|
|
expected_offset += 1 * sign
|
|
elif rhs_type == "LinearSum":
|
|
second_linear_or_quadratic = model.LinearSum((y, -2 * x, 1))
|
|
x_coefficient += -2 * sign
|
|
y_coefficient += 1 * sign
|
|
expected_offset += 1 * sign
|
|
elif rhs_type == "LinearProduct":
|
|
second_linear_or_quadratic = model.LinearProduct(2, y)
|
|
y_coefficient += 2 * sign
|
|
elif rhs_type == "QuadraticTerm":
|
|
second_linear_or_quadratic = model.QuadraticTerm(xy, 5)
|
|
xy_coefficient += 5 * sign
|
|
elif rhs_type == "QuadraticExpression":
|
|
second_linear_or_quadratic = model.QuadraticExpression(
|
|
x - 2 * y + 1 + 3 * x * y - 4 * y * y
|
|
)
|
|
x_coefficient += 1 * sign
|
|
y_coefficient += -2 * sign
|
|
expected_offset += 1 * sign
|
|
xy_coefficient += 3 * sign
|
|
yy_coefficient += -4 * sign
|
|
elif rhs_type == "QuadraticSum":
|
|
second_linear_or_quadratic = model.QuadraticSum(
|
|
(x, -2 * y, 1, y * x, -2 * x * x)
|
|
)
|
|
x_coefficient += 1 * sign
|
|
y_coefficient += -2 * sign
|
|
expected_offset += 1 * sign
|
|
xy_coefficient += 1 * sign
|
|
xx_coefficient += -2 * sign
|
|
elif rhs_type == "LinearLinearProduct":
|
|
second_linear_or_quadratic = model.LinearLinearProduct(x, x + y)
|
|
xx_coefficient += sign
|
|
xy_coefficient += sign
|
|
elif rhs_type == "QuadraticProduct":
|
|
second_linear_or_quadratic = model.QuadraticProduct(2, x * (x + y))
|
|
xx_coefficient += 2 * sign
|
|
xy_coefficient += 2 * sign
|
|
else:
|
|
raise AssertionError(f"unknown linear type: {lhs_type!r}")
|
|
|
|
# Check __add__ and __sub__
|
|
s = (
|
|
first_linear_or_quadratic - second_linear_or_quadratic
|
|
if subtract
|
|
else first_linear_or_quadratic + second_linear_or_quadratic
|
|
)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(e.offset, expected_offset)
|
|
self.assertDictEqualWithZeroDefault(
|
|
dict(e.linear_terms), {x: x_coefficient, y: y_coefficient}
|
|
)
|
|
self.assertDictEqualWithZeroDefault(
|
|
dict(e.quadratic_terms),
|
|
{xx: xx_coefficient, xy: xy_coefficient, yy: yy_coefficient},
|
|
)
|
|
|
|
# Also check __iadd__ and __isub__
|
|
if subtract:
|
|
first_linear_or_quadratic -= second_linear_or_quadratic
|
|
else:
|
|
first_linear_or_quadratic += second_linear_or_quadratic
|
|
e_inplace = model.as_flat_quadratic_expression(first_linear_or_quadratic)
|
|
self.assertEqual(e_inplace.offset, expected_offset)
|
|
self.assertDictEqualWithZeroDefault(
|
|
dict(e_inplace.linear_terms), {x: x_coefficient, y: y_coefficient}
|
|
)
|
|
self.assertDictEqualWithZeroDefault(
|
|
dict(e_inplace.quadratic_terms),
|
|
{xx: xx_coefficient, xy: xy_coefficient, yy: yy_coefficient},
|
|
)
|
|
|
|
|
|
# Test multiplication of two Linear objects.
|
|
class LinearLinearMulTest(parameterized.TestCase):
|
|
|
|
def assertDictEqualWithZeroDefault(
|
|
self, dict1: dict[Any, float], dict2: dict[Any, float]
|
|
) -> None:
|
|
for key in dict1.keys():
|
|
if key not in dict2:
|
|
dict2[key] = 0.0
|
|
for key in dict2.keys():
|
|
if key not in dict1:
|
|
dict1[key] = 0.0
|
|
self.assertDictEqual(dict1, dict2)
|
|
|
|
@parameterized.named_parameters(("_x_first", True), ("_y_first", False))
|
|
def test_var_var(self, x_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
if x_first:
|
|
s = x * y
|
|
else:
|
|
s = y * x
|
|
self.assertIsInstance(s, model.QuadraticTerm)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault({xy: 1.0}, dict(e.quadratic_terms))
|
|
self.assertDictEqualWithZeroDefault({}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_var_first", True), ("_term_first", False))
|
|
def test_term_term(self, var_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
if var_first:
|
|
s = model.LinearTerm(x, 2) * model.LinearTerm(y, 3)
|
|
else:
|
|
s = model.LinearTerm(x, 3) * model.LinearTerm(y, 2)
|
|
self.assertIsInstance(s, model.QuadraticTerm)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault({xy: 6.0}, dict(e.quadratic_terms))
|
|
self.assertDictEqualWithZeroDefault({}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_expr1_first", True), ("_expr2_first", False))
|
|
def test_expr_expr(self, expr1_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
expr1 = model.LinearExpression(x - 2 * y + 3)
|
|
expr2 = model.LinearExpression(-x + y + 1)
|
|
if expr1_first:
|
|
s = expr1 * expr2
|
|
else:
|
|
s = expr2 * expr1
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{
|
|
xx: -1.0,
|
|
xy: 3.0,
|
|
yy: -2.0,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: -2.0, y: 1.0}, dict(e.linear_terms))
|
|
self.assertEqual(3.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_sum1_first", True), ("_sum2_first", False))
|
|
def test_sum_sum(self, sum1_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
sum1 = model.LinearSum((x, -2 * y, 3))
|
|
sum2 = model.LinearSum((-x, y, 1))
|
|
if sum1_first:
|
|
s = sum1 * sum2
|
|
else:
|
|
s = sum2 * sum1
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{
|
|
xx: -1.0,
|
|
xy: 3.0,
|
|
yy: -2.0,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: -2.0, y: 1.0}, dict(e.linear_terms))
|
|
self.assertEqual(3.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_prod1_first", True), ("_prod2_first", False))
|
|
def test_prod_prod(self, prod1_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
prod1 = model.LinearProduct(2.0, x)
|
|
prod2 = model.LinearProduct(3.0, x + 2 * y - 1)
|
|
if prod1_first:
|
|
s = prod1 * prod2
|
|
else:
|
|
s = prod2 * prod1
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{
|
|
xx: 6.0,
|
|
xy: 12.0,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: -6.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_var_first", True), ("_term_first", False))
|
|
def test_var_term(self, var_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
term = model.LinearTerm(y, 2)
|
|
if var_first:
|
|
s = x * term
|
|
else:
|
|
s = term * x
|
|
self.assertIsInstance(s, model.QuadraticTerm)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault({xy: 2.0}, dict(e.quadratic_terms))
|
|
self.assertDictEqualWithZeroDefault({}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_var_first", True), ("_expr_first", False))
|
|
def test_var_expr(self, var_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
expr = model.LinearExpression(x - 2 * y + 3)
|
|
if var_first:
|
|
s = x * expr
|
|
else:
|
|
s = expr * x
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xx: 1.0, xy: -2.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: 3.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_var_first", True), ("_sum_first", False))
|
|
def test_var_sum(self, var_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
linear_sum = model.LinearSum((x, -2 * y, 3))
|
|
if var_first:
|
|
s = x * linear_sum
|
|
else:
|
|
s = linear_sum * x
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xx: 1.0, xy: -2.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: 3.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_var_first", True), ("_prod_first", False))
|
|
def test_var_prod(self, var_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
expr = model.LinearProduct(2.0, y)
|
|
if var_first:
|
|
s = x * expr
|
|
else:
|
|
s = expr * x
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault({xy: 2.0}, dict(e.quadratic_terms))
|
|
self.assertDictEqualWithZeroDefault({}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_term_first", True), ("_expr_first", False))
|
|
def test_term_expr(self, term_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
term = model.LinearTerm(x, 2)
|
|
expr = model.LinearExpression(x - 2 * y + 3)
|
|
if term_first:
|
|
s = term * expr
|
|
else:
|
|
s = expr * term
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xx: 2.0, xy: -4.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: 6.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_term_first", True), ("_sum_first", False))
|
|
def test_term_sum(self, term_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
term = model.LinearTerm(x, 2)
|
|
linear_sum = model.LinearSum((x, -2 * y, 3))
|
|
if term_first:
|
|
s = term * linear_sum
|
|
else:
|
|
s = linear_sum * term
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xx: 2.0, xy: -4.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: 6.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_term_first", True), ("_prod_first", False))
|
|
def test_term_prod(self, term_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
term = model.LinearTerm(x, 2)
|
|
prod = model.LinearProduct(2.0, y)
|
|
if term_first:
|
|
s = term * prod
|
|
else:
|
|
s = prod * term
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault({xy: 4.0}, dict(e.quadratic_terms))
|
|
self.assertDictEqualWithZeroDefault({}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_expr_first", True), ("_sum_first", False))
|
|
def test_expr_sum(self, expr_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
expr = model.LinearExpression(-x + y + 1)
|
|
linear_sum = model.LinearSum((x, -2 * y, 3))
|
|
if expr_first:
|
|
s = expr * linear_sum
|
|
else:
|
|
s = linear_sum * expr
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{
|
|
xx: -1.0,
|
|
xy: 3.0,
|
|
yy: -2.0,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
self.assertDictEqualWithZeroDefault({x: -2.0, y: 1.0}, dict(e.linear_terms))
|
|
self.assertEqual(3.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_expr_first", True), ("_prod_first", False))
|
|
def test_expr_prod(self, expr_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
expr = model.LinearExpression(-x + y + 1)
|
|
prod = model.LinearProduct(2.0, y)
|
|
if expr_first:
|
|
s = expr * prod
|
|
else:
|
|
s = prod * expr
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xy: -2.0, yy: 2.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({y: 2.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
@parameterized.named_parameters(("_sum_first", True), ("_prod_first", False))
|
|
def test_sum_prod(self, sum_first: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
linear_sum = model.LinearSum((-x, y, 1))
|
|
prod = model.LinearProduct(2.0, y)
|
|
if sum_first:
|
|
s = linear_sum * prod
|
|
else:
|
|
s = prod * linear_sum
|
|
self.assertIsInstance(s, model.LinearLinearProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xy: -2.0, yy: 2.0}, dict(e.quadratic_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault({y: 2.0}, dict(e.linear_terms))
|
|
self.assertEqual(0.0, e.offset)
|
|
|
|
|
|
# Test negate on Linear and Quadratic objects.
|
|
class NegateTest(parameterized.TestCase):
|
|
|
|
def test_negate_var(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
s = -x
|
|
self.assertIsInstance(s, model.LinearTerm)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({x: -1}, dict(e.terms))
|
|
|
|
def test_negate_linear_term(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
term = model.LinearTerm(x, 0.5)
|
|
s = -term
|
|
self.assertIsInstance(s, model.LinearTerm)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({x: -0.5}, dict(e.terms))
|
|
|
|
def test_negate_linear_expression(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
expression = model.LinearExpression(y - 2 * x + 1)
|
|
s = -expression
|
|
self.assertIsInstance(s, model.LinearProduct)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(-1, e.offset)
|
|
self.assertDictEqual({x: 2, y: -1}, dict(e.terms))
|
|
|
|
def test_negate_linear_sum(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
expression = model.LinearSum((y, -2 * x, 1))
|
|
s = -expression
|
|
self.assertIsInstance(s, model.LinearProduct)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(-1, e.offset)
|
|
self.assertDictEqual({x: 2, y: -1}, dict(e.terms))
|
|
|
|
def test_negate_ast_product(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
ast_product = model.LinearProduct(0.5, x)
|
|
s = -ast_product
|
|
self.assertIsInstance(s, model.LinearProduct)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({x: -0.5}, dict(e.terms))
|
|
|
|
def test_negate_quadratic_term(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
term = model.QuadraticTerm(xx, 0.5)
|
|
s = -term
|
|
self.assertIsInstance(s, model.QuadraticTerm)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({}, dict(e.linear_terms))
|
|
self.assertDictEqual({xx: -0.5}, dict(e.quadratic_terms))
|
|
|
|
def test_negate_quadratic_expression(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
expression = model.QuadraticExpression(y - 2 * x + 1 + x * y)
|
|
s = -expression
|
|
self.assertIsInstance(s, model.QuadraticProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(-1, e.offset)
|
|
self.assertDictEqual({x: 2, y: -1}, dict(e.linear_terms))
|
|
self.assertDictEqual({xy: -1}, dict(e.quadratic_terms))
|
|
|
|
def test_negate_quadratic_sum(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
yy = model.QuadraticTermKey(y, y)
|
|
expression = model.QuadraticSum((y, -2 * x, 1, -y * y))
|
|
s = -expression
|
|
self.assertIsInstance(s, model.QuadraticProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(-1, e.offset)
|
|
self.assertDictEqual({x: 2, y: -1}, dict(e.linear_terms))
|
|
self.assertDictEqual({yy: 1}, dict(e.quadratic_terms))
|
|
|
|
def test_negate_linear_linear_product(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
ast_product = model.LinearLinearProduct(x, x + 1)
|
|
s = -ast_product
|
|
self.assertIsInstance(s, model.QuadraticProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({x: -1}, dict(e.linear_terms))
|
|
self.assertDictEqual({xx: -1}, dict(e.quadratic_terms))
|
|
|
|
def test_negate_quadratic_product(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
ast_product = model.QuadraticProduct(0.5, x + x * x)
|
|
s = -ast_product
|
|
self.assertIsInstance(s, model.QuadraticProduct)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(0, e.offset)
|
|
self.assertDictEqual({x: -0.5}, dict(e.linear_terms))
|
|
self.assertDictEqual({xx: -0.5}, dict(e.quadratic_terms))
|
|
|
|
|
|
class UnsupportedProductOperandTestParams(NamedTuple):
|
|
lhs_type: str
|
|
rhs_type: str
|
|
|
|
def test_suffix(self):
|
|
return f"_{self.lhs_type}_{self.rhs_type}"
|
|
|
|
|
|
def all_unsupported_product_operand_params() -> (
|
|
List[UnsupportedProductOperandTestParams]
|
|
):
|
|
result = []
|
|
for lhs_type in _LINEAR_TYPES:
|
|
result.append(
|
|
UnsupportedProductOperandTestParams(lhs_type=lhs_type, rhs_type="complex")
|
|
)
|
|
for lhs_type in _QUADRATIC_TYPES + ("complex",):
|
|
for rhs_type in _QUADRATIC_TYPES + ("complex",):
|
|
if lhs_type == "complex" and rhs_type == "complex":
|
|
continue
|
|
result.append(
|
|
UnsupportedProductOperandTestParams(
|
|
lhs_type=lhs_type, rhs_type=rhs_type
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
def all_unsupported_division_operand_params() -> (
|
|
List[UnsupportedProductOperandTestParams]
|
|
):
|
|
result = []
|
|
for lhs_type in _LINEAR_TYPES + _QUADRATIC_TYPES + ("complex",):
|
|
for rhs_type in _LINEAR_TYPES + _QUADRATIC_TYPES + ("complex",):
|
|
if lhs_type == "complex" and rhs_type == "complex":
|
|
continue
|
|
result.append(
|
|
UnsupportedProductOperandTestParams(
|
|
lhs_type=lhs_type, rhs_type=rhs_type
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
def get_linear_or_quadratic_for_unsupported_operand_test(
|
|
type_string: str,
|
|
) -> Union[model.LinearBase, model.QuadraticBase, complex]:
|
|
mod_ = model.Model()
|
|
x = mod_.add_binary_variable(name="x")
|
|
y = mod_.add_binary_variable(name="y")
|
|
xy = model.QuadraticTermKey(x, y)
|
|
if type_string == "Variable":
|
|
return x
|
|
elif type_string == "LinearTerm":
|
|
return model.LinearTerm(x, 2)
|
|
elif type_string == "LinearExpression":
|
|
return model.LinearExpression(x - 2 * y + 3)
|
|
elif type_string == "LinearSum":
|
|
return model.LinearSum((x, -2 * y, 3))
|
|
elif type_string == "LinearProduct":
|
|
return model.LinearProduct(2, x)
|
|
elif type_string == "QuadraticTerm":
|
|
return model.QuadraticTerm(xy, 5)
|
|
elif type_string == "QuadraticExpression":
|
|
return model.QuadraticExpression(x - 2 * y + 1 + 3 * x * y - 4 * y * y)
|
|
elif type_string == "QuadraticSum":
|
|
return model.QuadraticSum((x, -2 * y, 1, y * x, -2 * x * x))
|
|
elif type_string == "LinearLinearProduct":
|
|
return model.LinearLinearProduct(x, x + y)
|
|
elif type_string == "QuadraticProduct":
|
|
return model.QuadraticProduct(2, x * (x + y))
|
|
elif type_string == "complex":
|
|
return 6j
|
|
else:
|
|
raise AssertionError(f"unknown linear or quadratic type: {type_string!r}")
|
|
|
|
|
|
class UnsupportedProductOperandTest(parameterized.TestCase):
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.lhs_type, p.rhs_type)
|
|
for p in all_unsupported_product_operand_params()
|
|
)
|
|
def test_mult(self, lhs_type: str, rhs_type: str) -> None:
|
|
lhs = get_linear_or_quadratic_for_unsupported_operand_test(lhs_type)
|
|
rhs = get_linear_or_quadratic_for_unsupported_operand_test(rhs_type)
|
|
|
|
expected_string = f"unsupported operand.*[*].*{lhs_type}.*and.*{rhs_type}"
|
|
|
|
# pylint: disable=pointless-statement
|
|
# pytype: disable=unsupported-operands
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
lhs * rhs
|
|
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
lhs *= rhs
|
|
# pylint: enable=pointless-statement
|
|
# pytype: enable=unsupported-operands
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.lhs_type, p.rhs_type)
|
|
for p in all_unsupported_division_operand_params()
|
|
)
|
|
def test_div(self, lhs_type: str, rhs_type: str) -> None:
|
|
lhs = get_linear_or_quadratic_for_unsupported_operand_test(lhs_type)
|
|
rhs = get_linear_or_quadratic_for_unsupported_operand_test(rhs_type)
|
|
|
|
expected_string = f"unsupported operand.*[/].*{lhs_type}.*and.*{rhs_type}"
|
|
|
|
# pylint: disable=pointless-statement
|
|
# pytype: disable=unsupported-operands
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
lhs / rhs
|
|
|
|
if lhs_type == "str":
|
|
expected_string = f"unsupported operand.*[/].*{lhs_type}.*and.*{rhs_type}"
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
lhs /= rhs
|
|
# pylint: enable=pointless-statement
|
|
# pytype: enable=unsupported-operands
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
|
|
class UnsupportedAdditionOperandTestParams(NamedTuple):
|
|
linear_or_quadratic_type: str
|
|
linear_or_quadratic_first: bool
|
|
|
|
def test_suffix(self):
|
|
if self.linear_or_quadratic_first:
|
|
return f"_{self.linear_or_quadratic_type}_str"
|
|
else:
|
|
return f"_str_{self.linear_or_quadratic_type}"
|
|
|
|
|
|
def all_unsupported_addition_operand_params() -> (
|
|
List[UnsupportedAdditionOperandTestParams]
|
|
):
|
|
result = []
|
|
for linear_or_quadratic_type in _LINEAR_TYPES + _QUADRATIC_TYPES:
|
|
for linear_or_quadratic_first in (True, False):
|
|
result.append(
|
|
UnsupportedAdditionOperandTestParams(
|
|
linear_or_quadratic_type=linear_or_quadratic_type,
|
|
linear_or_quadratic_first=linear_or_quadratic_first,
|
|
)
|
|
)
|
|
return result
|
|
|
|
|
|
@parameterized.named_parameters(
|
|
(p.test_suffix(), p.linear_or_quadratic_type, p.linear_or_quadratic_first)
|
|
for p in all_unsupported_addition_operand_params()
|
|
)
|
|
class UnsupportedAdditionOperandTest(parameterized.TestCase):
|
|
|
|
def test_add(
|
|
self, linear_or_quadratic_type: str, linear_or_quadratic_first: bool
|
|
) -> None:
|
|
linear_or_quadratic = get_linear_or_quadratic_for_unsupported_operand_test(
|
|
linear_or_quadratic_type
|
|
)
|
|
other = 6j
|
|
|
|
expected_string = r"unsupported operand type\(s\) for \+.*"
|
|
if linear_or_quadratic_first:
|
|
expected_string += (
|
|
f"{linear_or_quadratic_type}.*and.*{type(other).__name__}.*"
|
|
)
|
|
else:
|
|
expected_string += (
|
|
f"{type(other).__name__}.*and.*{linear_or_quadratic_type}.*"
|
|
)
|
|
|
|
# pylint: disable=pointless-statement
|
|
# pytype: disable=unsupported-operands
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
if linear_or_quadratic_first:
|
|
linear_or_quadratic + other
|
|
else:
|
|
other + linear_or_quadratic
|
|
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
if linear_or_quadratic_first:
|
|
linear_or_quadratic += other
|
|
else:
|
|
other += linear_or_quadratic
|
|
# pylint: enable=pointless-statement
|
|
# pytype: enable=unsupported-operands
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_sub(
|
|
self, linear_or_quadratic_type: str, linear_or_quadratic_first: bool
|
|
) -> None:
|
|
linear_or_quadratic = get_linear_or_quadratic_for_unsupported_operand_test(
|
|
linear_or_quadratic_type
|
|
)
|
|
other = 6j
|
|
|
|
expected_string = "unsupported operand type[(]s[)] for [-].*"
|
|
if linear_or_quadratic_first:
|
|
expected_string += (
|
|
f"{linear_or_quadratic_type}.*and.*{type(other).__name__}.*"
|
|
)
|
|
else:
|
|
expected_string += (
|
|
f"{type(other).__name__}.*and.*{linear_or_quadratic_type}.*"
|
|
)
|
|
|
|
# pylint: disable=pointless-statement
|
|
# pytype: disable=unsupported-operands
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
if linear_or_quadratic_first:
|
|
linear_or_quadratic - other
|
|
else:
|
|
other - linear_or_quadratic
|
|
|
|
with self.assertRaisesRegex(TypeError, expected_string):
|
|
if linear_or_quadratic_first:
|
|
linear_or_quadratic -= other
|
|
else:
|
|
other -= linear_or_quadratic
|
|
# pylint: enable=pointless-statement
|
|
# pytype: enable=unsupported-operands
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
|
|
class UnsupportedInitializationTest(parameterized.TestCase):
|
|
|
|
def test_linear_sum_not_tuple(self):
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, "object is not iterable"):
|
|
model.LinearSum(2.0)
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_linear_sum_not_linear_in_tuple(self):
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, "unsupported type in iterable argument"):
|
|
model.LinearSum((2.0, x * x))
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_quadratic_sum_not_tuple(self):
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, "object is not iterable"):
|
|
model.QuadraticSum(2.0)
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_quadratic_sum_not_linear_in_tuple(self):
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(TypeError, "unsupported type in iterable argument"):
|
|
model.QuadraticSum((2.0, "string"))
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_linear_product_not_scalar(self):
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError, "unsupported type for scalar argument in LinearProduct"
|
|
):
|
|
model.LinearProduct(x, x)
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_linear_product_not_linear(self):
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError, "unsupported type for linear argument in LinearProduct"
|
|
):
|
|
model.LinearProduct(2.0, "string")
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_quadratic_product_not_scalar(self):
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError, "unsupported type for scalar argument in QuadraticProduct"
|
|
):
|
|
model.QuadraticProduct(x, x)
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_quadratic_product_not_quadratic(self):
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError, "unsupported type for linear argument in QuadraticProduct"
|
|
):
|
|
model.QuadraticProduct(2.0, "string")
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_linear_linear_product_first_not_linear(self):
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"unsupported type for first_linear argument in LinearLinearProduct",
|
|
):
|
|
model.LinearLinearProduct("string", x)
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
def test_linear_linear_product_second_not_linear(self):
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
# pytype: disable=wrong-arg-types
|
|
with self.assertRaisesRegex(
|
|
TypeError,
|
|
"unsupported type for second_linear argument in LinearLinearProduct",
|
|
):
|
|
model.LinearLinearProduct(x, "string")
|
|
# pytype: enable=wrong-arg-types
|
|
|
|
|
|
@parameterized.named_parameters(("_python_sum", True), ("LinearSum", False))
|
|
class SumTest(parameterized.TestCase):
|
|
|
|
def test_sum_vars(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
array = [x, z, x, x, y]
|
|
if python_sum:
|
|
s = sum(array) + 8.0
|
|
else:
|
|
s = model.LinearSum(array) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(8.0, e.offset)
|
|
self.assertDictEqual({x: 3, y: 1, z: 1}, dict(e.terms))
|
|
|
|
def test_sum_linear_terms(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
array = [1.25 * x, z, x, x, y, -0.5 * y, 1.0]
|
|
if python_sum:
|
|
s = sum(array) + 8.0
|
|
else:
|
|
s = model.LinearSum(array) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(9.0, e.offset)
|
|
self.assertDictEqual({x: 3.25, y: 0.5, z: 1}, dict(e.terms))
|
|
|
|
def test_sum_quadratic_terms(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
array = [1.25 * x, z, x, x, y, -0.5 * y, 1.0, 2.5 * x * x, -x * y]
|
|
if python_sum:
|
|
s = sum(array) + 8.0
|
|
else:
|
|
s = model.QuadraticSum(array) + 8.0
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(9.0, e.offset)
|
|
self.assertDictEqual({x: 3.25, y: 0.5, z: 1}, dict(e.linear_terms))
|
|
self.assertDictEqual({xx: 2.5, xy: -1}, dict(e.quadratic_terms))
|
|
|
|
def test_sum_linear_expression(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
array = [1.25 * x + z, x, x + y, -0.5 * y + 1.0]
|
|
if python_sum:
|
|
s = sum(array) + 8.0
|
|
else:
|
|
s = model.LinearSum(array) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(9.0, e.offset)
|
|
self.assertDictEqual({x: 3.25, y: 0.5, z: 1}, dict(e.terms))
|
|
|
|
def test_sum_quadratic_expression(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
array = [
|
|
1.25 * x + z,
|
|
x,
|
|
x + y,
|
|
-0.5 * y + 1.0,
|
|
2.5 * x * x - x * y,
|
|
x * z + y * z,
|
|
]
|
|
if python_sum:
|
|
s = sum(array) + 8.0
|
|
else:
|
|
s = model.QuadraticSum(array) + 8.0
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(9.0, e.offset)
|
|
self.assertDictEqual({x: 3.25, y: 0.5, z: 1}, dict(e.linear_terms))
|
|
self.assertDictEqual(
|
|
{
|
|
xx: 2.5,
|
|
xy: -1,
|
|
model.QuadraticTermKey(x, z): 1.0,
|
|
model.QuadraticTermKey(y, z): 1,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
|
|
def test_generator_sum_vars(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(3)]
|
|
if python_sum:
|
|
s = sum(x[i] for i in range(3)) + 8.0
|
|
else:
|
|
s = model.LinearSum(x[i] for i in range(3)) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(8.0, e.offset)
|
|
self.assertDictEqual({x[0]: 1, x[1]: 1, x[2]: 1}, dict(e.terms))
|
|
|
|
def test_generator_sum_terms(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(3)]
|
|
if python_sum:
|
|
s = sum(i * x[i] for i in range(3)) + 8.0
|
|
else:
|
|
s = model.LinearSum(i * x[i] for i in range(3)) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(8.0, e.offset)
|
|
self.assertDictEqual({x[0]: 0, x[1]: 1, x[2]: 2}, dict(e.terms))
|
|
|
|
def test_generator_sum_quadratic_terms(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(4)]
|
|
if python_sum:
|
|
s = sum(i * x[i] * x[i + 1] for i in range(3)) + 8.0
|
|
else:
|
|
s = model.QuadraticSum(i * x[i] * x[i + 1] for i in range(3)) + 8.0
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(8.0, e.offset)
|
|
self.assertDictEqual({}, dict(e.linear_terms))
|
|
self.assertDictEqual(
|
|
{
|
|
model.QuadraticTermKey(x[0], x[1]): 0,
|
|
model.QuadraticTermKey(x[1], x[2]): 1,
|
|
model.QuadraticTermKey(x[2], x[3]): 2,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
|
|
def test_generator_sum_expression(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(3)]
|
|
if python_sum:
|
|
s = sum(2 * x[i] - x[i + 1] + 1.5 for i in range(2)) + 8.0
|
|
else:
|
|
s = model.LinearSum(2 * x[i] - x[i + 1] + 1.5 for i in range(2)) + 8.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(11.0, e.offset)
|
|
self.assertDictEqual({x[0]: 2, x[1]: 1, x[2]: -1}, dict(e.terms))
|
|
|
|
def test_generator_quadratic_sum_expression(self, python_sum: bool) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(3)]
|
|
if python_sum:
|
|
s = sum(2 * x[i] - x[i + 1] + 1.5 + x[i] * x[i + 1] for i in range(2)) + 8.0
|
|
else:
|
|
s = (
|
|
model.QuadraticSum(
|
|
2 * x[i] - x[i + 1] + 1.5 + x[i] * x[i + 1] for i in range(2)
|
|
)
|
|
+ 8.0
|
|
)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(11.0, e.offset)
|
|
self.assertDictEqual({x[0]: 2, x[1]: 1, x[2]: -1}, dict(e.linear_terms))
|
|
self.assertDictEqual(
|
|
{
|
|
model.QuadraticTermKey(x[0], x[1]): 1,
|
|
model.QuadraticTermKey(x[1], x[2]): 1,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
|
|
|
|
class AstTest(parameterized.TestCase):
|
|
|
|
def assertDictEqualWithZeroDefault(
|
|
self, dict1: dict[Any, float], dict2: dict[Any, float]
|
|
) -> None:
|
|
for key in dict1.keys():
|
|
if key not in dict2:
|
|
dict2[key] = 0.0
|
|
for key in dict2.keys():
|
|
if key not in dict1:
|
|
dict1[key] = 0.0
|
|
self.assertDictEqual(dict1, dict2)
|
|
|
|
def test_simple_linear_ast(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
s = (6 * (3 * x + y + 3) + 6 * z + 12) / 3 + y + 7 + (x + y) * 2.0 - z * 3.0
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(6 * 3 / 3 + 12 / 3 + 7, e.offset)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{x: 8, y: 3 + 6 / 3, z: 6 / 3 - 3}, dict(e.terms)
|
|
)
|
|
|
|
def test_simple_quadratic_ast(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
xx = model.QuadraticTermKey(x, x)
|
|
xy = model.QuadraticTermKey(x, y)
|
|
yy = model.QuadraticTermKey(y, y)
|
|
s = (
|
|
(6 * (3 * x + y + 3) * x + 6 * z + 12) / 3
|
|
+ y * y
|
|
+ 7
|
|
+ (x - y) * (x + y) * 2.0
|
|
- z * 3.0
|
|
)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(12 / 3 + 7, e.offset)
|
|
self.assertDictEqualWithZeroDefault({x: 6, z: 6 / 3 - 3}, dict(e.linear_terms))
|
|
self.assertDictEqualWithZeroDefault(
|
|
{xx: 6 * 3 / 3 + 2, xy: 6 / 3, yy: 1 - 2}, dict(e.quadratic_terms)
|
|
)
|
|
|
|
def test_linear_sum_ast(self) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(5)]
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
s = (
|
|
(2 * (z + y) + 2 * y) / 2
|
|
+ sum(
|
|
x[i] + 0.5 * model.LinearSum([4 * x[1] - 2 * x[0], 2 * x[2], 2.5, -0.5])
|
|
for i in range(3)
|
|
)
|
|
- model.LinearSum([x[3], x[4]])
|
|
)
|
|
e = model.as_flat_linear_expression(s)
|
|
self.assertEqual(3.0, e.offset)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{x[0]: -2, x[1]: 7, x[2]: 4, x[3]: -1, x[4]: -1, y: 2, z: 1},
|
|
dict(e.terms),
|
|
)
|
|
|
|
def test_quadratic_sum_ast(self) -> None:
|
|
mod = model.Model()
|
|
x = [mod.add_binary_variable(name=f"x[{i}]") for i in range(3)]
|
|
y = mod.add_binary_variable(name="y")
|
|
z = mod.add_binary_variable(name="z")
|
|
yy = model.QuadraticTermKey(y, y)
|
|
zz = model.QuadraticTermKey(z, z)
|
|
s = (
|
|
1
|
|
+ y * y
|
|
+ z
|
|
+ sum(x[i] + x[i] * model.LinearSum([y, z]) for i in range(3))
|
|
- model.QuadraticSum([y, z * z])
|
|
)
|
|
e = model.as_flat_quadratic_expression(s)
|
|
self.assertEqual(1.0, e.offset)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{x[0]: 1, x[1]: 1, x[2]: 1, y: -1, z: 1}, dict(e.linear_terms)
|
|
)
|
|
self.assertDictEqualWithZeroDefault(
|
|
{
|
|
yy: 1,
|
|
zz: -1,
|
|
model.QuadraticTermKey(x[0], y): 1,
|
|
model.QuadraticTermKey(x[1], y): 1,
|
|
model.QuadraticTermKey(x[2], y): 1,
|
|
model.QuadraticTermKey(x[0], z): 1,
|
|
model.QuadraticTermKey(x[1], z): 1,
|
|
model.QuadraticTermKey(x[2], z): 1,
|
|
},
|
|
dict(e.quadratic_terms),
|
|
)
|
|
|
|
|
|
# Test behavior of LinearExpression and as_flat_linear_expression that is
|
|
# not covered by other tests.
|
|
class LinearExpressionTest(absltest.TestCase):
|
|
|
|
def test_init_to_zero(self) -> None:
|
|
expression = model.LinearExpression()
|
|
self.assertEqual(expression.offset, 0.0)
|
|
self.assertEmpty(expression.terms)
|
|
|
|
def test_terms_read_only(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
expression = model.LinearExpression(y - 2 * x + 1)
|
|
with self.assertRaisesRegex(TypeError, "does not support item assignment"):
|
|
expression.terms[x] += 1 # pytype: disable=unsupported-operands
|
|
|
|
def test_no_copy_of_linear_expression(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
expression = model.LinearExpression(y - 2 * x + 1)
|
|
self.assertIs(expression, model.as_flat_linear_expression(expression))
|
|
|
|
def test_number_as_flat_linear_expression(self) -> None:
|
|
expression = model.LinearExpression(2.0)
|
|
self.assertDictEqual(dict(expression.terms), {})
|
|
self.assertEqual(expression.offset, 2.0)
|
|
|
|
def test_evaluate(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_variable()
|
|
y = mod.add_variable()
|
|
expression = model.LinearExpression(3 * x + y + 2.0)
|
|
self.assertEqual(expression.evaluate({x: 4.0, y: 3.0}), 17.0)
|
|
|
|
|
|
# Test behavior of QuadraticExpression and as_flat_quadratic_expression that is
|
|
# not covered by other tests.
|
|
class QuadraticExpressionTest(absltest.TestCase):
|
|
|
|
def test_terms_read_only(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
yy = model.QuadraticTermKey(y, y)
|
|
expression = model.QuadraticExpression(y * y - 2 * x + 1)
|
|
with self.assertRaisesRegex(TypeError, "does not support item assignment"):
|
|
expression.linear_terms[x] += 1 # pytype: disable=unsupported-operands
|
|
with self.assertRaisesRegex(TypeError, "does not support item assignment"):
|
|
expression.quadratic_terms[yy] += 1 # pytype: disable=unsupported-operands
|
|
|
|
def test_no_copy_of_quadratic_expression(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_binary_variable(name="x")
|
|
y = mod.add_binary_variable(name="y")
|
|
expression = model.QuadraticExpression(y * y - 2 * x + 1)
|
|
self.assertIs(expression, model.as_flat_quadratic_expression(expression))
|
|
|
|
def test_number_as_flat_quadratic_expression(self) -> None:
|
|
expression = model.QuadraticExpression(2.0)
|
|
self.assertDictEqual(dict(expression.linear_terms), {})
|
|
self.assertDictEqual(dict(expression.quadratic_terms), {})
|
|
self.assertEqual(expression.offset, 2.0)
|
|
|
|
def test_evaluate(self) -> None:
|
|
mod = model.Model()
|
|
x = mod.add_variable()
|
|
y = mod.add_variable()
|
|
expression = model.QuadraticExpression(x * x + 2 * x * y + 4 * y + 2.0)
|
|
# 16 + 24 + 12 + 2 = 54
|
|
self.assertEqual(expression.evaluate({x: 4.0, y: 3.0}), 54.0)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
absltest.main()
|