isolate xpress tests

examples/python/callback_xpress.py

@@ -1,80 +0,0 @@
-#!/usr/bin/env python3
-# Copyright 2023 RTE
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-"""MIP example/test that shows how to use the callback API."""
-
-from ortools.linear_solver import pywraplp
-from ortools.linear_solver.pywraplp import MPCallbackContext, MPCallback
-import random
-import unittest
-
-
-class MyMPCallback(MPCallback):
-    def __init__(self, mp_solver: pywraplp.Solver):
-        super().__init__(False, False)
-        self._mp_solver_ = mp_solver
-        self._solutions_ = 0
-        self._last_var_values_ = [0] * len(mp_solver.variables())
-
-    def RunCallback(self, ctx: MPCallbackContext):
-        self._solutions_ += 1
-        for i in range(0, len(self._mp_solver_.variables())) :
-            self._last_var_values_[i] = ctx.VariableValue(self._mp_solver_.variable(i))
-
-
-class TestSiriusXpress(unittest.TestCase):
-    def test_callback(self):
-        """Builds a large MIP that is difficult to solve, in order for us to have time to intercept non-optimal
-         feasible solutions using callback"""
-        solver = pywraplp.Solver.CreateSolver('XPRESS_MIXED_INTEGER_PROGRAMMING')
-        n_vars = 30
-        max_time = 30
-        if not solver:
-            return
-
-        random.seed(123)
-
-        objective = solver.Objective()
-        objective.SetMaximization()
-
-        for i in range(0, n_vars):
-            x = solver.IntVar(-random.random() * 200, random.random() * 200, 'x_' + str(i))
-            objective.SetCoefficient(x, random.random() * 200 - 100)
-            if i == 0:
-                continue
-            rand1 = -random.random() * 2000
-            rand2 = random.random() * 2000
-            c = solver.Constraint(min(rand1, rand2), max(rand1, rand2))
-            c.SetCoefficient(x, random.random() * 200 - 100)
-            for j in range(0, i):
-                c.SetCoefficient(solver.variable(j), random.random() * 200 - 100)
-
-        solver.SetSolverSpecificParametersAsString("PRESOLVE 0 MAXTIME " + str(max_time))
-        solver.EnableOutput()
-
-        cb = MyMPCallback(solver)
-        solver.SetCallback(cb)
-
-        solver.Solve()
-
-        # This is a tough MIP, in 30 seconds XPRESS should have found at least 5
-        # solutions (tested with XPRESS v9.0, may change in later versions)
-        self.assertTrue(cb._solutions_ > 5)
-        # Test that the last solution intercepted by callback is the same as the optimal one retained
-        for i in range(0, len(solver.variables())):
-            self.assertAlmostEqual(cb._last_var_values_[i], solver.variable(i).SolutionValue())
-
-
-if __name__ == '__main__':
-    unittest.main()
-