def test_decoder_basic_1(self):
     sat_problem = SATProblem()
     Encoder.encode_basic_clause(self.tbn_problem, sat_problem)
     Encoder.increment_min_representatives(self.tbn_problem, sat_problem)
     sat_problem.solve()
     polymers = Decoder.decode_boolean_values(self.tbn_problem, sat_problem)
     self.assertEqual(len(polymers), 1)
示例#2
0
    def test_solve_empty_clause(self):
        sat_problem = SATProblem()
        sat_problem.constraint_clauses.append([])
        sat_problem.solve(True)
        success = sat_problem.success
        result = sat_problem.result

        self.assertFalse(success)
        self.assertEqual(0, len(result))
        self.assertEqual([], result)
示例#3
0
    def test_solve_single_clause(self):
        sat_problem = SATProblem()
        sat_problem.constraint_clauses.append([1])
        sat_problem.solve(True)
        success = sat_problem.success
        result = sat_problem.result

        self.assertTrue(success)
        self.assertEqual(1, len(result))
        self.assertEqual([1], result)
    def test_basic(self):
        tbn_file = open("../input/classic.txt", 'rt')
        tbn_problem = parse_input_lines(tbn_file.readlines(), [])
        tbn_file.close()
        sat_problem = SATProblem()

        Encoder.encode_basic_clause(tbn_problem, sat_problem)

        while sat_problem.success:
            Encoder.increment_min_representatives(tbn_problem, sat_problem)
            sat_problem.solve()
        self.assertEqual(sat_problem.min_reps, 4)
示例#5
0
    def test_solve_basic_clauses(self):
        sat_problem = SATProblem()
        sat_problem.constraint_clauses.append([1, 2, 3])
        sat_problem.constraint_clauses.append([-2])
        sat_problem.constraint_clauses.append([-3])
        sat_problem.solve(True)
        success = sat_problem.success
        result = sat_problem.result

        self.assertTrue(success)
        self.assertEqual(3, len(result))
        self.assertEqual([1, -2, -3], result)
def get_stable_config(tbn_lines,
                      constr_lines,
                      gen_count,
                      init_k,
                      celery_task=None):
    # parse the input to encode it into BindingSite/Monomer classes

    t0 = time.time()
    # Celery Task is flag to indicate if a call is made from library or from a celery broker worker API
    if celery_task is not None:

        if celery_task.is_aborted():
            raise EarlyTerminationException(0, 0)

        celery_task.update_state(state="PROGRESS",
                                 meta={
                                     'status': "Progress",
                                     'count': 0,
                                     'k': 0
                                 })

    tbn_problem = parse_input_lines(tbn_lines, constr_lines)

    tbn_problem.gen_count = gen_count
    tbn_problem.init_k = init_k
    configs = []

    # encode problem to SAT solver compatible problem
    sat_problem = SATProblem()
    Encoder.encode_basic_clause(tbn_problem, sat_problem)
    print()
    print("[1] COMPUTING ORIGINAL STABLE CONFIGURATION:")

    # Increment solver to minimum polymers before computing
    while sat_problem.min_reps < tbn_problem.init_k:
        Encoder.increment_min_representatives(tbn_problem, sat_problem)

    original_num_reps = 0

    # solve the problem (SAT solver)
    while sat_problem.success:

        if celery_task is not None:
            if celery_task.is_aborted():
                raise EarlyTerminationException(1, sat_problem.min_reps)
            celery_task.update_state(state="PROGRESS",
                                     meta={
                                         'status': "Progress",
                                         'count': 1,
                                         'k': sat_problem.min_reps
                                     })

        else:
            print("... Checking for k =", sat_problem.min_reps, "polymers")

        sat_problem.solve(False)
        if (sat_problem.success):
            original_num_reps = sat_problem.min_reps
            Encoder.increment_min_representatives(tbn_problem, sat_problem)

    if original_num_reps > 0:
        if celery_task is None:
            print("Found an original stable configuration with [",
                  original_num_reps, "] polymers.\n")
    else:
        if celery_task is None:
            print("Could not find original stable configuration with [",
                  tbn_problem.init_k, "] polymers.\n")
            # Printing execution time
            print("\nCompleted in", time.time() - t0, "seconds.\n")
        raise MinPolymersExceedEntropyException(tbn_problem.init_k)

    # Decode the problem into polymers and print results
    polymers = Decoder.decode_boolean_values(tbn_problem, sat_problem)
    if celery_task is None:
        for index, polymer in enumerate(polymers):
            print("\t" + "Polymer number", index + 1)
            for monomer in polymer.monomer_list:
                print("\t\t" + str(monomer))
            print()

    # SOLVING WITH CONSTRAINTS
    if len(tbn_problem.constraints) != 0:
        configs = get_stable_configs_using_constraints(tbn_problem,
                                                       sat_problem,
                                                       original_num_reps,
                                                       celery_task)

    # SOLVING WITHOUT CONSTRAINTS
    else:
        # Add original configuration solution to result list
        configs.append(polymers)

        # Generate additional unique solutions
        if tbn_problem.gen_count > 1:
            additional_configs = get_stable_configs_using_constraints(
                tbn_problem, sat_problem, original_num_reps, celery_task)
            # Add results to existing solution list
            configs.extend(additional_configs)

    # Printing execution time
    if celery_task is None:
        print("\nCompleted in", time.time() - t0, "seconds.\n")

    return configs, original_num_reps