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import stormpyimport stormpy.logicfrom helpers.helper import get_example_pathfrom configurations import numpy_avail
class TestSparseModelComponents: def test_init_default(self): components = stormpy.SparseModelComponents()
assert components.state_labeling.get_labels() == set() assert components.reward_models == {} assert components.transition_matrix.nr_rows == 0 assert components.transition_matrix.nr_columns == 0 assert components.markovian_states is None assert components.player1_matrix is None assert not components.rate_transitions
def test_build_dtmc(self): nr_states = 13 nr_choices = 13
# transition_matrix builder = stormpy.SparseMatrixBuilder(rows=0, columns=0, entries=0, force_dimensions=False, has_custom_row_grouping=False, row_groups=0)
# Add transitions builder.add_next_value(0, 1, 0.5) builder.add_next_value(0, 2, 0.5) builder.add_next_value(1, 3, 0.5) builder.add_next_value(1, 4, 0.5) builder.add_next_value(2, 5, 0.5) builder.add_next_value(2, 6, 0.5) builder.add_next_value(3, 7, 0.5) builder.add_next_value(3, 1, 0.5) builder.add_next_value(4, 8, 0.5) builder.add_next_value(4, 9, 0.5) builder.add_next_value(5, 10, 0.5) builder.add_next_value(5, 11, 0.5) builder.add_next_value(6, 2, 0.5) builder.add_next_value(6, 12, 0.5) for s in range(7, 13): builder.add_next_value(s, s, 1) # Build transition matrix, update number of rows and columns transition_matrix = builder.build(nr_states, nr_states)
# state labeling state_labeling = stormpy.storage.StateLabeling(nr_states) state_labels = {'init', 'one', 'two', 'three', 'four', 'five', 'six', 'done', 'deadlock'} for label in state_labels: state_labeling.add_label(label) # Add label to one state state_labeling.add_label_to_state('init', 0) state_labeling.add_label_to_state('one', 7) state_labeling.add_label_to_state('two', 8) state_labeling.add_label_to_state('three', 9) state_labeling.add_label_to_state('four', 10) state_labeling.add_label_to_state('five', 11) state_labeling.add_label_to_state('six', 12)
state_labeling.set_states('done', stormpy.BitVector(nr_states, [7, 8, 9, 10, 11, 12]))
# reward_models reward_models = {} # Create a vector representing the state-action rewards action_reward = [1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] reward_models['coin_flips'] = stormpy.SparseRewardModel(optional_state_action_reward_vector=action_reward)
# state valuations manager = stormpy.ExpressionManager() var_s = manager.create_integer_variable(name='s') var_d = manager.create_integer_variable(name='d') v_builder = stormpy.StateValuationsBuilder()
v_builder.add_variable(var_s) v_builder.add_variable(var_d)
for s in range(7): v_builder.add_state(state=s, integer_values=[s, 0]) for s in range(7, 13): v_builder.add_state(state=s, integer_values=[7, s - 6])
state_valuations = v_builder.build(13)
# choice origins prism_program = stormpy.parse_prism_program(get_example_path("dtmc", "die.pm")) index_to_identifier_mapping = [1, 2, 3, 4, 5, 6, 7, 8, 8, 8, 8, 8, 8] id_to_command_set_mapping = [stormpy.FlatSet() for _ in range(9)] for i in range(1, 8): # 0: no origin id_to_command_set_mapping[i].insert(i - 1) id_to_command_set_mapping[8].insert(7) choice_origins = stormpy.PrismChoiceOrigins(prism_program, index_to_identifier_mapping, id_to_command_set_mapping)
# Construct components components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, reward_models=reward_models) components.choice_origins = choice_origins components.state_valuations = state_valuations
# Build DTMC dtmc = stormpy.storage.SparseDtmc(components)
assert type(dtmc) is stormpy.SparseDtmc assert not dtmc.supports_parameters
# Test transition matrix assert dtmc.nr_choices == nr_choices assert dtmc.nr_states == nr_states assert dtmc.nr_transitions == 20 assert dtmc.transition_matrix.nr_entries == dtmc.nr_transitions for e in dtmc.transition_matrix: assert e.value() == 0.5 or e.value() == 0 or (e.value() == 1 and e.column > 6) for state in dtmc.states: assert len(state.actions) <= 1
# Test state labeling assert dtmc.labeling.get_labels() == {'init', 'deadlock', 'done', 'one', 'two', 'three', 'four', 'five', 'six'}
# Test reward_models assert len(dtmc.reward_models) == 1 assert not dtmc.reward_models["coin_flips"].has_state_rewards assert dtmc.reward_models["coin_flips"].has_state_action_rewards for reward in dtmc.reward_models["coin_flips"].state_action_rewards: assert reward == 1.0 or reward == 0.0 assert not dtmc.reward_models["coin_flips"].has_transition_rewards
# Test choice labeling assert not dtmc.has_choice_labeling()
# Test state_valuations assert dtmc.has_state_valuations() assert dtmc.state_valuations value_s = [None] * nr_states value_d = [None] * nr_states for s in range(0, dtmc.nr_states): value_s[s] = dtmc.state_valuations.get_integer_value(s, var_s) value_d[s] = dtmc.state_valuations.get_integer_value(s, var_d) assert value_s == [0, 1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7] assert value_d == [0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6]
# Test choice origins assert dtmc.has_choice_origins() assert dtmc.choice_origins is components.choice_origins assert dtmc.choice_origins.get_number_of_identifiers() == 9
def test_build_mdp(self): nr_states = 13 nr_choices = 14
# Build transition matrix builder = stormpy.SparseMatrixBuilder(rows=0, columns=0, entries=0, force_dimensions=False, has_custom_row_grouping=True, row_groups=0)
# Row group, state 0 builder.new_row_group(0) builder.add_next_value(0, 1, 0.5) builder.add_next_value(0, 2, 0.5) builder.add_next_value(1, 1, 0.2) builder.add_next_value(1, 2, 0.8) # Row group, state 1 builder.new_row_group(2) builder.add_next_value(2, 3, 0.5) builder.add_next_value(2, 4, 0.5) # Row group, state 2 builder.new_row_group(3) builder.add_next_value(3, 5, 0.5) builder.add_next_value(3, 6, 0.5) # Row group, state 3 builder.new_row_group(4) builder.add_next_value(4, 7, 0.5) builder.add_next_value(4, 1, 0.5) # Row group, state 4 builder.new_row_group(5) builder.add_next_value(5, 8, 0.5) builder.add_next_value(5, 9, 0.5) # Row group, state 5 builder.new_row_group(6) builder.add_next_value(6, 10, 0.5) builder.add_next_value(6, 11, 0.5) # Row group, state 6 builder.new_row_group(7) builder.add_next_value(7, 2, 0.5) builder.add_next_value(7, 12, 0.5) # final states for s in range(8, 14): builder.new_row_group(s) builder.add_next_value(s, s - 1, 1)
transition_matrix = builder.build(nr_choices, nr_states)
# state labeling state_labeling = stormpy.storage.StateLabeling(nr_states) labels = {'init', 'one', 'two', 'three', 'four', 'five', 'six', 'done', 'deadlock'} for label in labels: state_labeling.add_label(label) state_labeling.add_label_to_state('init', 0) state_labeling.add_label_to_state('one', 7) state_labeling.add_label_to_state('two', 8) state_labeling.add_label_to_state('three', 9) state_labeling.add_label_to_state('four', 10) state_labeling.add_label_to_state('five', 11) state_labeling.add_label_to_state('six', 12)
state_labeling.set_states('done', stormpy.BitVector(nr_states, [7, 8, 9, 10, 11, 12]))
# reward models reward_models = {} # Vector representing the state-action rewards action_reward = [0.0, 0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0] reward_models['coin_flips'] = stormpy.SparseRewardModel(optional_state_action_reward_vector=action_reward)
# choice labeling choice_labeling = stormpy.storage.ChoiceLabeling(nr_choices) choice_labels = {'a', 'b'} for label in choice_labels: choice_labeling.add_label(label) choice_labeling.add_label_to_choice('a', 0) choice_labeling.add_label_to_choice('b', 1)
# state valuations manager = stormpy.ExpressionManager() var_s = manager.create_integer_variable(name='s') var_d = manager.create_integer_variable(name='d') v_builder = stormpy.StateValuationsBuilder() v_builder.add_variable(var_s) v_builder.add_variable(var_d) for s in range(7): # values: vector [value for s, value for d] v_builder.add_state(state=s, boolean_values=[], integer_values=[s, 0], rational_values=[]) for s in range(7, 13): v_builder.add_state(state=s, boolean_values=[], integer_values=[7, s - 6], rational_values=[]) state_valuations = v_builder.build(13)
# choice origins prism_program = stormpy.parse_prism_program(get_example_path("mdp", "die_c1.nm")) index_to_identifier_mapping = [1, 2, 3, 4, 5, 6, 7, 8, 9, 9, 9, 9, 9, 9]
id_to_command_set_mapping = [stormpy.FlatSet() for _ in range(10)] for i in range(1, 9): # 0: no origin id_to_command_set_mapping[i].insert(i - 1) id_to_command_set_mapping[9].insert(8) choice_origins = stormpy.PrismChoiceOrigins(prism_program, index_to_identifier_mapping, id_to_command_set_mapping)
# Construct Components components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, reward_models=reward_models, rate_transitions=False) components.state_valuations = state_valuations components.choice_labeling = choice_labeling components.choice_origins = choice_origins
# Build MDP mdp = stormpy.storage.SparseMdp(components)
assert type(mdp) is stormpy.SparseMdp assert not mdp.supports_parameters
# Test transition matrix assert mdp.nr_choices == nr_choices assert mdp.nr_states == nr_states assert mdp.nr_transitions == 22 assert mdp.transition_matrix.nr_entries == mdp.nr_transitions for e in mdp.transition_matrix: assert e.value() == 0.5 or e.value() == 0 or e.value() == 0.2 or e.value() == 0.8 or ( e.value() == 1 and e.column > 6) for state in mdp.states: assert len(state.actions) <= 2
# Test state labeling assert mdp.labeling.get_labels() == {'init', 'deadlock', 'done', 'one', 'two', 'three', 'four', 'five', 'six'}
# Test reward models assert len(mdp.reward_models) == 1 assert not mdp.reward_models["coin_flips"].has_state_rewards assert mdp.reward_models["coin_flips"].has_state_action_rewards for reward in mdp.reward_models["coin_flips"].state_action_rewards: assert reward == 1.0 or reward == 0.0 assert not mdp.reward_models["coin_flips"].has_transition_rewards
# Test choice labeling assert mdp.has_choice_labeling() assert mdp.choice_labeling.get_labels() == {'a', 'b'}
# Test state valuations assert mdp.has_state_valuations() assert mdp.state_valuations value_s = [None] * nr_states value_d = [None] * nr_states for s in range(0, mdp.nr_states): value_s[s] = mdp.state_valuations.get_integer_value(s, var_s) value_d[s] = mdp.state_valuations.get_integer_value(s, var_d) assert value_s == [0, 1, 2, 3, 4, 5, 6, 7, 7, 7, 7, 7, 7] assert value_d == [0, 0, 0, 0, 0, 0, 0, 1, 2, 3, 4, 5, 6]
# Test choice origins assert mdp.has_choice_origins() assert mdp.choice_origins is components.choice_origins assert mdp.choice_origins.get_number_of_identifiers() == 10
@numpy_avail def test_build_ctmc(self): import numpy as np
nr_states = 12 nr_choices = 12
# Build transition_matrix transitions = np.array([ [0, 0.5, 0.5, 200, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0.5, 200, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0.5, 0, 200, 0, 0, 0, 0, 0], [200, 0, 0, 0, 0, 0, 0.5, 0.5, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 200, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0.5, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5, 200, 0], [0, 200, 0, 0, 0, 0, 0, 0, 0, 0.5, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 200], [1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.5], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype='float64')
transition_matrix = stormpy.build_sparse_matrix(transitions)
# state labeling state_labeling = stormpy.storage.StateLabeling(nr_states) # Add labels state_labels = {'init', 'deadlock', 'target'} for label in state_labels: state_labeling.add_label(label)
# Add labels to states state_labeling.add_label_to_state('init', 0) state_labeling.set_states('target', stormpy.BitVector(nr_states, [5, 8]))
# reward models reward_models = {} # vector representing state-action rewards action_reward = [0.0, 0.0, 0.0, 0.0, 0.0, 2 / 3, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0] reward_models['served'] = stormpy.SparseRewardModel(optional_state_action_reward_vector=action_reward)
# vector representing state rewards state_reward = [0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0] reward_models['waiting'] = stormpy.SparseRewardModel(optional_state_reward_vector=state_reward)
# choice labeling choice_labeling = stormpy.storage.ChoiceLabeling(nr_choices) choice_labels = {'loop1a', 'loop1b', 'serve1', 'loop2a', 'loop2b', 'serve2'} # Add labels for label in choice_labels: choice_labeling.add_label(label)
choice_labeling.set_choices('loop1a', stormpy.BitVector(nr_choices, [0, 2])) choice_labeling.set_choices('loop1b', stormpy.BitVector(nr_choices, [1, 4])) choice_labeling.set_choices('serve1', stormpy.BitVector(nr_choices, [5, 8])) choice_labeling.set_choices('loop2a', stormpy.BitVector(nr_choices, [3, 7])) choice_labeling.set_choices('loop2b', stormpy.BitVector(nr_choices, [6, 9])) choice_labeling.set_choices('serve2', stormpy.BitVector(nr_choices, [10, 11]))
# state exit rates exit_rates = [201.0, 200.5, 200.5, 201.0, 200.0, 1.5, 200.5, 200.5, 1.0, 200.0, 1.5, 1.0]
# state valuations manager = stormpy.ExpressionManager() var_s = manager.create_integer_variable(name='s') var_a = manager.create_integer_variable(name='a') var_s1 = manager.create_integer_variable(name='s1') var_s2 = manager.create_integer_variable(name='s2') v_builder = stormpy.StateValuationsBuilder() v_builder.add_variable(var_s) v_builder.add_variable(var_a) v_builder.add_variable(var_s1) v_builder.add_variable(var_s2)
v_builder.add_state(state=0, boolean_values=[], integer_values=[1, 0, 0, 0], rational_values=[]) v_builder.add_state(state=1, boolean_values=[], integer_values=[1, 0, 1, 0], rational_values=[]) v_builder.add_state(state=2, boolean_values=[], integer_values=[1, 0, 0, 1], rational_values=[]) v_builder.add_state(state=3, boolean_values=[], integer_values=[2, 0, 0, 0], rational_values=[]) v_builder.add_state(state=4, boolean_values=[], integer_values=[1, 0, 1, 1], rational_values=[]) v_builder.add_state(state=5, boolean_values=[], integer_values=[1, 1, 1, 0], rational_values=[]) v_builder.add_state(state=6, boolean_values=[], integer_values=[2, 0, 0, 1], rational_values=[]) v_builder.add_state(state=7, boolean_values=[], integer_values=[2, 0, 1, 0], rational_values=[]) v_builder.add_state(state=8, boolean_values=[], integer_values=[1, 1, 1, 1], rational_values=[]) v_builder.add_state(state=9, boolean_values=[], integer_values=[2, 0, 1, 1], rational_values=[]) v_builder.add_state(state=10, boolean_values=[], integer_values=[2, 1, 0, 1], rational_values=[]) v_builder.add_state(state=11, boolean_values=[], integer_values=[2, 1, 1, 1], rational_values=[])
state_valuations = v_builder.build(nr_states)
# set rate_transitions to True: the transition values are interpreted as rates components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, reward_models=reward_models, rate_transitions=True) components.choice_labeling = choice_labeling components.exit_rates = exit_rates components.state_valuations = state_valuations
# Build CTMC ctmc = stormpy.storage.SparseCtmc(components) assert type(ctmc) is stormpy.SparseCtmc assert not ctmc.supports_parameters
# Test transition matrix assert ctmc.nr_choices == nr_choices assert ctmc.nr_states == nr_states assert ctmc.nr_transitions == 22 assert ctmc.transition_matrix.nr_columns == nr_states assert ctmc.transition_matrix.nr_rows == nr_choices for e in ctmc.transition_matrix: assert e.value() == 0.5 or e.value() == 0 or e.value() == 200 or e.value() == 1.0 for state in ctmc.states: assert len(state.actions) <= 1
# Test state labeling assert ctmc.labeling.get_labels() == {'target', 'init', 'deadlock'}
# Test reward models assert len(ctmc.reward_models) == 2 assert not ctmc.reward_models["served"].has_state_rewards assert ctmc.reward_models["served"].has_state_action_rewards assert ctmc.reward_models["served"].state_action_rewards == [0.0, 0.0, 0.0, 0.0, 0.0, 0.6666666666666666, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0] assert not ctmc.reward_models["served"].has_transition_rewards
assert ctmc.reward_models["waiting"].has_state_rewards assert not ctmc.reward_models["waiting"].has_state_action_rewards assert ctmc.reward_models["waiting"].state_rewards == [0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 0.0, 1.0, 0.0, 1.0, 0.0, 1.0] assert not ctmc.reward_models["waiting"].has_transition_rewards
# Test choice labeling assert ctmc.has_choice_labeling() assert ctmc.choice_labeling.get_labels() == {'loop1a', 'loop1b', 'serve1', 'loop2a', 'loop2b', 'serve2'}
# Test state valuations assert ctmc.has_state_valuations() assert ctmc.state_valuations value_s = [None] * nr_states value_a = [None] * nr_states value_s1 = [None] * nr_states value_s2 = [None] * nr_states for s in range(0, ctmc.nr_states): value_s[s] = ctmc.state_valuations.get_integer_value(s, var_s) value_a[s] = ctmc.state_valuations.get_integer_value(s, var_a) value_s1[s] = ctmc.state_valuations.get_integer_value(s, var_s1) value_s2[s] = ctmc.state_valuations.get_integer_value(s, var_s2) assert value_s == [1, 1, 1, 2, 1, 1, 2, 2, 1, 2, 2, 2] assert value_a == [0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 1, 1] assert value_s1 == [0, 1, 0, 0, 1, 1, 0, 1, 1, 1, 0, 1] assert value_s2 == [0, 0, 1, 0, 1, 0, 1, 0, 1, 1, 1, 1]
# Test choice origins assert not ctmc.has_choice_origins()
# Test exit_rates assert ctmc.exit_rates == [201.0, 200.5, 200.5, 201.0, 200.0, 1.5, 200.5, 200.5, 1.0, 200.0, 1.5, 1.0]
def test_build_ma(self): nr_states = 5 nr_choices = 10
# Build transition matrix builder = stormpy.SparseMatrixBuilder(rows=0, columns=0, entries=0, force_dimensions=False, has_custom_row_grouping=True, row_groups=0)
# Row group, state 0 builder.new_row_group(0) # Add Transition for (state) 0 to target states builder.add_next_value(0, 2, 1) builder.add_next_value(1, 2, 1) builder.add_next_value(2, 0, 0.8) builder.add_next_value(2, 1, 0.2)
# Row group, state 1 builder.new_row_group(3) # New Transition (state) 1 to target state builder.add_next_value(3, 3, 1)
# Row group, state 2 builder.new_row_group(4) # New Transition (state) 1 to target state builder.add_next_value(4, 0, 0.9) builder.add_next_value(4, 4, 0.1)
# Row group, state 3 builder.new_row_group(5) # New Transition (state) 1 to target state builder.add_next_value(5, 4, 1) builder.add_next_value(6, 3, 1)
# Row group, state 4 builder.new_row_group(7) # New Transition (state) 1 to target state builder.add_next_value(7, 3, 0.5) builder.add_next_value(7, 4, 0.5) builder.add_next_value(8, 3, 1) builder.add_next_value(9, 4, 1)
transition_matrix = builder.build(nr_choices, nr_states)
# state labeling state_labeling = stormpy.storage.StateLabeling(nr_states) # Add labels state_labels = {'init', 'deadlock'} for label in state_labels: state_labeling.add_label(label)
# Add label to states state_labeling.add_label_to_state('init', 0)
# state valuations manager = stormpy.ExpressionManager() var_s = manager.create_integer_variable(name='s') v_builder = stormpy.StateValuationsBuilder() v_builder.add_variable(var_s)
v_builder.add_state(state=0, boolean_values=[], integer_values=[0], rational_values=[]) v_builder.add_state(state=1, boolean_values=[], integer_values=[2], rational_values=[]) v_builder.add_state(state=2, boolean_values=[], integer_values=[1], rational_values=[]) v_builder.add_state(state=3, boolean_values=[], integer_values=[4], rational_values=[]) v_builder.add_state(state=4, boolean_values=[], integer_values=[3], rational_values=[])
state_valuations = v_builder.build(nr_states)
# choice origins: prism_program = stormpy.parse_prism_program(get_example_path("ma", "hybrid_states.ma")) index_to_identifier_mapping = [1, 2, 3, 4, 5, 6, 7, 8, 9, 10] id_to_command_set_mapping = [stormpy.FlatSet() for _ in range(11)]
id_to_command_set_mapping[1].insert(2) id_to_command_set_mapping[2].insert(1) id_to_command_set_mapping[3].insert(0) id_to_command_set_mapping[4].insert(4) id_to_command_set_mapping[5].insert(3) id_to_command_set_mapping[6].insert(9) id_to_command_set_mapping[7].insert(8) id_to_command_set_mapping[8].insert(7) id_to_command_set_mapping[9].insert(6) id_to_command_set_mapping[10].insert(5)
choice_origins = stormpy.PrismChoiceOrigins(prism_program, index_to_identifier_mapping, id_to_command_set_mapping)
exit_rates = [3.0, 12.0, 10.0, 3.0, 4.0]
markovian_states = stormpy.BitVector(5, [0, 1, 2, 3, 4])
# Build components, set rate_transitions to False components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, rate_transitions=False, markovian_states=markovian_states) components.state_valuations = state_valuations components.choice_origins = choice_origins components.exit_rates = exit_rates
# Build MA ma = stormpy.storage.SparseMA(components) assert type(ma) is stormpy.SparseMA assert not ma.supports_parameters
# Test transition matrix assert ma.nr_choices == nr_choices assert ma.nr_states == nr_states assert ma.nr_transitions == 13 assert ma.transition_matrix.nr_columns == nr_states assert ma.transition_matrix.nr_rows == nr_choices # Check row groups assert ma.transition_matrix.get_row_group_start(0) == 0 assert ma.transition_matrix.get_row_group_end(0) == 3 assert ma.transition_matrix.get_row_group_start(1) == 3 assert ma.transition_matrix.get_row_group_end(1) == 4 assert ma.transition_matrix.get_row_group_start(2) == 4 assert ma.transition_matrix.get_row_group_end(2) == 5 assert ma.transition_matrix.get_row_group_start(3) == 5 assert ma.transition_matrix.get_row_group_end(3) == 7 assert ma.transition_matrix.get_row_group_start(4) == 7 assert ma.transition_matrix.get_row_group_end(4) == 10
for e in ma.transition_matrix: assert e.value() == 1.0 or e.value() == 0 or e.value() == 0.8 or e.value() == 0.2 or e.value() == 0.1 or e.value() == 0.5 or e.value() == 0.9 for state in ma.states: assert len(state.actions) <= 3
# Test state labeling assert ma.labeling.get_labels() == {'deadlock', 'init'}
# Test reward models assert len(ma.reward_models) == 0
# Test choice labeling assert not ma.has_choice_labeling()
# Test state valuations assert ma.has_state_valuations()
value_s = [None] * nr_states for s in range(0, ma.nr_states): value_s[s] = ma.state_valuations.get_integer_value(s, var_s) assert value_s == [0, 2, 1, 4, 3]
# Test choice origins assert ma.has_choice_origins() assert ma.choice_origins.get_number_of_identifiers() == 11
# Test exit rates assert ma.exit_rates == [3.0, 12.0, 10.0, 3.0, 4.0]
# Test Markovian states assert ma.markovian_states == stormpy.BitVector(5, [0, 1, 2, 3, 4])
@numpy_avail def test_build_pomdp(self): import numpy as np nr_states = 10 nr_choices = 34
# Build transition matrix builder = stormpy.SparseMatrixBuilder(rows=0, columns=0, entries=0, force_dimensions=False, has_custom_row_grouping=True, row_groups=0)
transitions = np.array([ [0, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0.125, 0],
[0, 0, 0, 0, 1, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 1], [0, 1, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 1, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 1, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 1, 0, 0], [0, 0, 0, 0, 0, 1, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 1],
[0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 1, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 1, 0], [0, 0, 0, 0, 0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 1]])
transition_matrix = stormpy.build_sparse_matrix(transitions, row_group_indices=[0, 1, 5, 9, 13, 17, 21, 25, 29, 33])
# state labeling state_labeling = stormpy.storage.StateLabeling(nr_states) labels = {'deadlock', 'goal', 'init'} for label in labels: state_labeling.add_label(label) state_labeling.add_label_to_state('init', 0) state_labeling.add_label_to_state('goal', 9)
# reward models reward_models = {} # Vector representing state-action rewards action_reward = [0.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 0.0] reward_models[''] = stormpy.SparseRewardModel(optional_state_action_reward_vector=action_reward)
# choice labeling choice_labeling = stormpy.storage.ChoiceLabeling(nr_choices) choice_labels = {'south', 'north', 'west', 'east', 'done'} for label in choice_labels: choice_labeling.add_label(label) choice_labeling.set_choices('south', stormpy.BitVector(nr_choices, [4, 8, 12, 16, 20, 24, 28, 32])) choice_labeling.set_choices('north', stormpy.BitVector(nr_choices, [3, 7, 11, 15, 19, 23, 27, 31])) choice_labeling.set_choices('west', stormpy.BitVector(nr_choices, [2, 6, 10, 14, 18, 22, 26, 30])) choice_labeling.set_choices('east', stormpy.BitVector(nr_choices, [1, 5, 9, 13, 17, 21, 25, 29])) choice_labeling.set_choices('done', stormpy.BitVector(nr_choices, [33]))
# state valuations manager = stormpy.ExpressionManager() var_x = manager.create_integer_variable(name='x') var_y = manager.create_integer_variable(name='y') var_o = manager.create_integer_variable(name='o') v_builder = stormpy.StateValuationsBuilder()
v_builder.add_variable(var_x) v_builder.add_variable(var_y) v_builder.add_variable(var_o)
v_builder.add_state(state=0, boolean_values=[], integer_values=[0, 0, 0], rational_values=[]) v_builder.add_state(state=1, boolean_values=[], integer_values=[0, 0, 1], rational_values=[]) v_builder.add_state(state=2, boolean_values=[], integer_values=[0, 1, 1], rational_values=[]) v_builder.add_state(state=3, boolean_values=[], integer_values=[0, 2, 1], rational_values=[]) v_builder.add_state(state=4, boolean_values=[], integer_values=[1, 0, 1], rational_values=[]) v_builder.add_state(state=5, boolean_values=[], integer_values=[1, 1, 1], rational_values=[]) v_builder.add_state(state=6, boolean_values=[], integer_values=[1, 2, 1], rational_values=[]) v_builder.add_state(state=7, boolean_values=[], integer_values=[2, 1, 1], rational_values=[]) v_builder.add_state(state=8, boolean_values=[], integer_values=[2, 2, 1], rational_values=[]) v_builder.add_state(state=9, boolean_values=[], integer_values=[2, 0, 2], rational_values=[])
state_valuations = v_builder.build(nr_states)
observations = [1, 0, 0, 0, 0, 0, 0, 0, 0, 2]
# Build components, set rate_transitions to False components = stormpy.SparseModelComponents(transition_matrix=transition_matrix, state_labeling=state_labeling, reward_models=reward_models, rate_transitions=False) components.state_valuations = state_valuations components.choice_labeling = choice_labeling # components.choice_origins=choice_origins components.observability_classes = observations
# Build POMDP pomdp = stormpy.storage.SparsePomdp(components) assert type(pomdp) is stormpy.SparsePomdp assert not pomdp.supports_parameters
# Test transition matrix assert pomdp.nr_choices == nr_choices assert pomdp.nr_states == nr_states assert pomdp.nr_transitions == 41 for e in pomdp.transition_matrix: assert e.value() == 1 or e.value() == 0 or e.value() == 0.125 for state in pomdp.states: assert len(state.actions) <= 4
# Test state labeling assert pomdp.labeling.get_labels() == {'init', 'goal', 'deadlock'}
# Test reward models assert len(pomdp.reward_models) == 1 assert not pomdp.reward_models[''].has_state_rewards assert pomdp.reward_models[''].has_state_action_rewards for reward in pomdp.reward_models[''].state_action_rewards: assert reward == 1.0 or reward == 0.0 assert not pomdp.reward_models[''].has_transition_rewards
# Test choice labeling assert pomdp.has_choice_labeling() assert pomdp.choice_labeling.get_labels() == {'east', 'west', 'north', 'south', 'done'}
# Test state valuations assert pomdp.has_state_valuations() assert pomdp.state_valuations value_x = [None] * nr_states value_y = [None] * nr_states value_o = [None] * nr_states for s in range(0, pomdp.nr_states): value_x[s] = pomdp.state_valuations.get_integer_value(s, var_x) value_y[s] = pomdp.state_valuations.get_integer_value(s, var_y) value_o[s] = pomdp.state_valuations.get_integer_value(s, var_o) assert value_x == [0, 0, 0, 0, 1, 1, 1, 2, 2, 2] assert value_y == [0, 0, 1, 2, 0, 1, 2, 1, 2, 0] assert value_o == [0, 1, 1, 1, 1, 1, 1, 1, 1, 2]
# Test choice origins assert not pomdp.has_choice_origins()
assert pomdp.observations == [1, 0, 0, 0, 0, 0, 0, 0, 0, 2]
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