def test_decode_10teams_mps(self): test1_filename = os.path.join(TEST_DATA_DIR, '10teams.mps') decoder = mps.decode(test1_filename) self.assert_equal('10teams', decoder.get_name()) self.assert_equal(2025, len(decoder.get_objective_coefficients())) self.assert_equal(230, decoder.get_rows_coefficients().shape[0]) self.assert_equal(230, len(decoder.get_rows_rhs()))
def test_decode_test1_mps(self): test1_filename = os.path.join(TEST_DATA_DIR, 'test1.mps') decoder = mps.decode(test1_filename) self.assert_equal('TESTPROB', decoder.get_name()) self.assert_equal(['L', 'G', 'E'], decoder.get_rows_senses()) self.assert_equal(['X', 'Y', 'Z'], decoder.get_columns_names()) self.assert_equal(['LIM1', 'LIM2', 'LIM3'], decoder.get_rows_names()) self.assert_equal([5.0, 10.0, 7.0], decoder.get_rows_rhs()) self.assert_equal([1.0, 4.0, 9.0], decoder.get_objective_coefficients()) rows_coefs = sparse.lil_matrix([[1.0, 1.0, 0.0], [1.0, 0.0, 1.0], [0.0, -1.0, 1.0]])
def test_encode(self): model1 = mp_model_builder.MPModelBuilder.build_from( [8, 2, 5, 5, 8, 3, 9, 7, 6], [[2, 3, 4, 1, 0, 0, 0, 0, 0], [1, 2, 3, 2, 0, 0, 0, 0, 0], [0, 0, 1, 4, 3, 4, 2, 0, 0], [0, 0, 2, 1, 1, 2, 5, 0, 0], [0, 0, 0, 0, 0, 0, 2, 1, 2], [0, 0, 0, 0, 0, 0, 3, 4, 1]], ['L'] * 6, [7, 6, 9, 7, 3, 5]) model1.set_name('DEMO1') model1.set_objective_name('PRODUCT') stream = StringIO.StringIO() mps.encode(stream, model1) model2 = mp_model_builder.MPModelBuilder.build_from(mps.decode(stream)) self.assert_equal(model1.get_name(), model2.get_name()) self.assert_equal(model1.get_num_columns(), model2.get_num_columns()) self.assert_equal(model1.get_num_rows(), model2.get_num_rows())