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145 lines
4.4 KiB
145 lines
4.4 KiB
import stormpy
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import stormpy.logic
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from stormpy.storage import BitVector
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from stormpy.utility import ShortestPathsGenerator
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from stormpy.utility import MatrixFormat
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from helpers.helper import get_example_path
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import pytest
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import math
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# this is admittedly slightly overengineered
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class ModelWithKnownShortestPaths:
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"""Knuth's die model with reference kSP methods"""
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def __init__(self):
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self.target_label = "one"
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program_path = get_example_path("dtmc", "die.pm")
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raw_formula = "P=? [ F \"" + self.target_label + "\" ]"
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program = stormpy.parse_prism_program(program_path)
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formulas = stormpy.parse_properties_for_prism_program(raw_formula, program)
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self.model = stormpy.build_model(program, formulas)
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def probability(self, k):
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return (1/2)**((2 * k) + 1)
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def state_set(self, k):
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return BitVector(self.model.nr_states, [0, 1, 3, 7])
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def path(self, k):
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path = [0] + k * [1, 3] + [7]
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return list(reversed(path)) # SPG returns traversal from back
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@pytest.fixture(scope="module", params=[1, 2, 3, 3000, 42])
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def index(request):
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return request.param
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@pytest.fixture(scope="module")
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def model_with_known_shortest_paths():
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return ModelWithKnownShortestPaths()
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@pytest.fixture(scope="module")
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def model(model_with_known_shortest_paths):
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return model_with_known_shortest_paths.model
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@pytest.fixture(scope="module")
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def expected_distance(model_with_known_shortest_paths):
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return model_with_known_shortest_paths.probability
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@pytest.fixture(scope="module")
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def expected_state_set(model_with_known_shortest_paths):
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return model_with_known_shortest_paths.state_set
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@pytest.fixture(scope="module")
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def expected_path(model_with_known_shortest_paths):
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return model_with_known_shortest_paths.path
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@pytest.fixture(scope="module")
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def target_label(model_with_known_shortest_paths):
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return model_with_known_shortest_paths.target_label
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@pytest.fixture
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def state(model):
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some_state = 7
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assert model.nr_states > some_state, "test model too small"
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return some_state
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@pytest.fixture
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def state_list(model):
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some_state_list = [4, 5, 7]
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assert model.nr_states > max(some_state_list), "test model too small"
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return some_state_list
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@pytest.fixture
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def state_bitvector(model, state_list):
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return BitVector(length=model.nr_states, set_entries=state_list)
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@pytest.fixture
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def transition_matrix(model):
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return model.transition_matrix
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@pytest.fixture
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def target_prob_map(model, state_list):
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return {i: (1.0 if i in state_list else 0.0) for i in range(model.nr_states)}
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@pytest.fixture
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def target_prob_list(target_prob_map):
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return [target_prob_map[i] for i in range(max(target_prob_map.keys()))]
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@pytest.fixture
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def initial_states(model):
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return BitVector(model.nr_states, model.initial_states)
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@pytest.fixture
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def matrix_format():
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return MatrixFormat.Straight
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class TestShortestPaths:
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def test_spg_ctor_bitvector_target(self, model, state_bitvector):
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_ = ShortestPathsGenerator(model, state_bitvector)
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def test_spg_ctor_single_state_target(self, model, state):
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_ = ShortestPathsGenerator(model, state)
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def test_spg_ctor_state_list_target(self, model, state_list):
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_ = ShortestPathsGenerator(model, state_list)
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def test_spg_ctor_label_target(self, model, target_label):
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_ = ShortestPathsGenerator(model, target_label)
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def test_spg_ctor_matrix_vector(self, transition_matrix, target_prob_list, initial_states, matrix_format):
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_ = ShortestPathsGenerator(transition_matrix, target_prob_list, initial_states, matrix_format)
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def test_spg_ctor_matrix_map(self, transition_matrix, target_prob_map, initial_states, matrix_format):
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_ = ShortestPathsGenerator(transition_matrix, target_prob_map, initial_states, matrix_format)
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def test_spg_distance(self, model, target_label, index, expected_distance):
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spg = ShortestPathsGenerator(model, target_label)
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assert math.isclose(spg.get_distance(index), expected_distance(index))
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def test_spg_state_set(self, model, target_label, index, expected_state_set):
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spg = ShortestPathsGenerator(model, target_label)
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assert spg.get_states(index) == expected_state_set(index)
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def test_spg_state_list(self, model, target_label, index, expected_path):
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spg = ShortestPathsGenerator(model, target_label)
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assert spg.get_path_as_list(index) == expected_path(index)
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