198 lines
8.0 KiB
Python
198 lines
8.0 KiB
Python
#!/usr/bin/env python3
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# Copyright 2010-2022 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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"""Tests for statistics."""
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import math
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import unittest
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from ortools.math_opt.python import model
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from ortools.math_opt.python import statistics
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class RangeTest(unittest.TestCase):
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def test_merge_optional_ranges(self) -> None:
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self.assertIsNone(statistics.merge_optional_ranges(None, None))
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r = statistics.Range(1.0, 3.0)
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self.assertEqual(statistics.merge_optional_ranges(r, None), r)
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self.assertEqual(statistics.merge_optional_ranges(None, r), r)
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# We also test that, since Range is a frozen class, we return the non-None
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# input when only one input is not None.
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self.assertIs(statistics.merge_optional_ranges(r, None), r)
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self.assertIs(statistics.merge_optional_ranges(None, r), r)
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self.assertEqual(
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statistics.merge_optional_ranges(
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statistics.Range(1.0, 3.0), statistics.Range(-2.0, 2.0)
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),
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statistics.Range(-2.0, 3.0),
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)
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def test_absolute_finite_non_zeros_range(self) -> None:
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self.assertIsNone(statistics.absolute_finite_non_zeros_range(()))
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self.assertIsNone(
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statistics.absolute_finite_non_zeros_range((math.inf, 0.0, -0.0, -math.inf))
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)
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self.assertEqual(
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statistics.absolute_finite_non_zeros_range(
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(math.inf, -5.0e2, 0.0, 1.5e-3, -0.0, -math.inf, 1.25e-6, 3.0e2)
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),
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statistics.Range(minimum=1.25e-6, maximum=5.0e2),
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)
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class ModelRangesTest(unittest.TestCase):
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def test_printing(self) -> None:
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self.assertMultiLineEqual(
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str(
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statistics.ModelRanges(
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objective_terms=None,
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variable_bounds=None,
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linear_constraint_bounds=None,
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linear_constraint_coefficients=None,
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)
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),
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"Objective terms : no finite values\n"
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"Variable bounds : no finite values\n"
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"Linear constraints bounds : no finite values\n"
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"Linear constraints coeffs : no finite values",
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)
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self.assertMultiLineEqual(
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str(
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statistics.ModelRanges(
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objective_terms=statistics.Range(2.12345e-99, 1.12345e3),
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variable_bounds=statistics.Range(9.12345e-2, 1.12345e2),
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linear_constraint_bounds=statistics.Range(2.12345e6, 5.12345e99),
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linear_constraint_coefficients=statistics.Range(0.0, 0.0),
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)
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),
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"Objective terms : [2.12e-99 , 1.12e+03 ]\n"
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"Variable bounds : [9.12e-02 , 1.12e+02 ]\n"
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"Linear constraints bounds : [2.12e+06 , 5.12e+99 ]\n"
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"Linear constraints coeffs : [0.00e+00 , 0.00e+00 ]",
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)
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self.assertMultiLineEqual(
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str(
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statistics.ModelRanges(
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objective_terms=statistics.Range(2.12345e-1, 1.12345e3),
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variable_bounds=statistics.Range(9.12345e-2, 1.12345e2),
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linear_constraint_bounds=statistics.Range(2.12345e6, 5.12345e99),
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linear_constraint_coefficients=statistics.Range(0.0, 1.0e100),
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)
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),
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"Objective terms : [2.12e-01 , 1.12e+03 ]\n"
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"Variable bounds : [9.12e-02 , 1.12e+02 ]\n"
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"Linear constraints bounds : [2.12e+06 , 5.12e+99 ]\n"
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"Linear constraints coeffs : [0.00e+00 , 1.00e+100]",
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)
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self.assertMultiLineEqual(
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str(
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statistics.ModelRanges(
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objective_terms=statistics.Range(2.12345e-100, 1.12345e3),
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variable_bounds=statistics.Range(9.12345e-2, 1.12345e2),
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linear_constraint_bounds=statistics.Range(2.12345e6, 5.12345e99),
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linear_constraint_coefficients=statistics.Range(0.0, 0.0),
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)
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),
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"Objective terms : [2.12e-100, 1.12e+03 ]\n"
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"Variable bounds : [9.12e-02 , 1.12e+02 ]\n"
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"Linear constraints bounds : [2.12e+06 , 5.12e+99 ]\n"
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"Linear constraints coeffs : [0.00e+00 , 0.00e+00 ]",
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)
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self.assertMultiLineEqual(
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str(
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statistics.ModelRanges(
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objective_terms=statistics.Range(2.12345e-100, 1.12345e3),
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variable_bounds=statistics.Range(9.12345e-2, 1.12345e2),
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linear_constraint_bounds=statistics.Range(2.12345e6, 5.12345e99),
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linear_constraint_coefficients=statistics.Range(0.0, 1.0e100),
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)
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),
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"Objective terms : [2.12e-100, 1.12e+03 ]\n"
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"Variable bounds : [9.12e-02 , 1.12e+02 ]\n"
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"Linear constraints bounds : [2.12e+06 , 5.12e+99 ]\n"
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"Linear constraints coeffs : [0.00e+00 , 1.00e+100]",
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)
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class ComputeModelRangesTest(unittest.TestCase):
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def test_empty(self) -> None:
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mdl = model.Model(name="model")
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self.assertEqual(
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statistics.compute_model_ranges(mdl),
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statistics.ModelRanges(
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objective_terms=None,
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variable_bounds=None,
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linear_constraint_bounds=None,
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linear_constraint_coefficients=None,
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),
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)
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def test_only_zero_and_infinite_values(self) -> None:
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mdl = model.Model(name="model")
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mdl.add_variable(lb=0.0, ub=math.inf)
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mdl.add_variable(lb=-math.inf, ub=0.0)
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mdl.add_variable(lb=-math.inf, ub=math.inf)
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mdl.add_linear_constraint(lb=0.0, ub=math.inf)
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mdl.add_linear_constraint(lb=-math.inf, ub=0.0)
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mdl.add_linear_constraint(lb=-math.inf, ub=math.inf)
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self.assertEqual(
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statistics.compute_model_ranges(mdl),
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statistics.ModelRanges(
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objective_terms=None,
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variable_bounds=None,
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linear_constraint_bounds=None,
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linear_constraint_coefficients=None,
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),
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)
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def test_mixed_values(self) -> None:
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mdl = model.Model(name="model")
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x = mdl.add_variable(lb=0.0, ub=0.0, name="x")
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y = mdl.add_variable(lb=-math.inf, ub=1e-3, name="y")
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mdl.add_variable(lb=-3e2, ub=math.inf, name="z")
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mdl.objective.is_maximize = False
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mdl.objective.set_linear_coefficient(x, -5.0e4)
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# TODO(b/225219234): add the quadratic term `1.0e-6 * z * x` when the
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# support of quadratic objective is added to the Python API.
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mdl.objective.set_linear_coefficient(y, 3.0)
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c = mdl.add_linear_constraint(lb=0.0, name="c")
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c.set_coefficient(y, 1.25e-3)
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c.set_coefficient(x, -4.5e3)
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mdl.add_linear_constraint(lb=-math.inf, ub=3e4)
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d = mdl.add_linear_constraint(lb=-1e-5, ub=0.0, name="d")
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d.set_coefficient(y, 2.5e-3)
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self.assertEqual(
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statistics.compute_model_ranges(mdl),
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statistics.ModelRanges(
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# TODO(b/225219234): update this to Range(1.0e-6, 5.0e4) once the
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# quadratic term is added.
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objective_terms=statistics.Range(3.0, 5.0e4),
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variable_bounds=statistics.Range(1e-3, 3e2),
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linear_constraint_bounds=statistics.Range(1e-5, 3e4),
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linear_constraint_coefficients=statistics.Range(1.25e-3, 4.5e3),
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),
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)
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if __name__ == "__main__":
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unittest.main()
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