You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
81 lines
3.8 KiB
81 lines
3.8 KiB
import stormpy
|
|
import stormpy.logic
|
|
from helpers.helper import get_example_path
|
|
|
|
import math
|
|
|
|
|
|
class TestTransformation:
|
|
|
|
def test_transform_symbolic_dtmc_to_sparse(self):
|
|
program = stormpy.parse_prism_program(get_example_path("dtmc", "crowds5_5.pm"))
|
|
symbolic_model = stormpy.build_symbolic_model(program)
|
|
assert symbolic_model.nr_states == 8607
|
|
assert symbolic_model.nr_transitions == 15113
|
|
assert symbolic_model.model_type == stormpy.ModelType.DTMC
|
|
assert not symbolic_model.supports_parameters
|
|
assert type(symbolic_model) is stormpy.SymbolicSylvanDtmc
|
|
sparse_model = stormpy.transform_to_sparse_model(symbolic_model)
|
|
assert sparse_model.nr_states == 8607
|
|
assert sparse_model.nr_transitions == 15113
|
|
assert sparse_model.model_type == stormpy.ModelType.DTMC
|
|
assert not sparse_model.supports_parameters
|
|
assert type(sparse_model) is stormpy.SparseDtmc
|
|
|
|
def test_transform_symbolic_parametric_dtmc_to_sparse(self):
|
|
program = stormpy.parse_prism_program(get_example_path("pdtmc", "parametric_die.pm"))
|
|
model = stormpy.build_symbolic_parametric_model(program)
|
|
assert model.nr_states == 13
|
|
assert model.nr_transitions == 20
|
|
assert model.model_type == stormpy.ModelType.DTMC
|
|
assert model.supports_parameters
|
|
assert type(model) is stormpy.SymbolicSylvanParametricDtmc
|
|
symbolic_model = stormpy.transform_to_sparse_model(model)
|
|
assert symbolic_model.nr_states == 13
|
|
assert symbolic_model.nr_transitions == 20
|
|
assert symbolic_model.model_type == stormpy.ModelType.DTMC
|
|
assert symbolic_model.supports_parameters
|
|
assert type(symbolic_model) is stormpy.SparseParametricDtmc
|
|
|
|
def test_transform_continuous_to_discrete_time_model_ctmc(self):
|
|
ctmc = stormpy.build_model_from_drn(get_example_path("ctmc", "dft.drn"))
|
|
formulas = stormpy.parse_properties("T=? [ F \"failed\" ]")
|
|
assert ctmc.nr_states == 16
|
|
assert ctmc.nr_transitions == 33
|
|
assert len(ctmc.initial_states) == 1
|
|
initial_state = ctmc.initial_states[0]
|
|
assert initial_state == 1
|
|
result = stormpy.model_checking(ctmc, formulas[0])
|
|
assert math.isclose(result.at(initial_state), 4.166666667)
|
|
|
|
dtmc, dtmc_formulas = stormpy.transform_to_discrete_time_model(ctmc, formulas)
|
|
assert dtmc.nr_states == 16
|
|
assert dtmc.nr_transitions == 33
|
|
assert len(dtmc.initial_states) == 1
|
|
initial_state = dtmc.initial_states[0]
|
|
assert initial_state == 1
|
|
result = stormpy.model_checking(dtmc, dtmc_formulas[0])
|
|
assert math.isclose(result.at(initial_state), 4.166666667)
|
|
|
|
def test_transform_continuous_to_discrete_time_model_ma(self):
|
|
program = stormpy.parse_prism_program(get_example_path("ma", "simple.ma"), False, True)
|
|
formulas = stormpy.parse_properties_for_prism_program("Tmin=? [ F s=4 ]", program)
|
|
ma = stormpy.build_model(program, formulas)
|
|
assert ma.nr_states == 5
|
|
assert ma.nr_transitions == 8
|
|
assert ma.model_type == stormpy.ModelType.MA
|
|
assert len(ma.initial_states) == 1
|
|
initial_state = ma.initial_states[0]
|
|
assert initial_state == 0
|
|
result = stormpy.model_checking(ma, formulas[0])
|
|
assert math.isclose(result.at(initial_state), 0.08333333333)
|
|
|
|
mdp, mdp_formulas = stormpy.transform_to_discrete_time_model(ma, formulas)
|
|
assert mdp.nr_states == 5
|
|
assert mdp.nr_transitions == 8
|
|
assert mdp.model_type == stormpy.ModelType.MDP
|
|
assert len(mdp.initial_states) == 1
|
|
initial_state = mdp.initial_states[0]
|
|
assert initial_state == 0
|
|
result = stormpy.model_checking(mdp, mdp_formulas[0])
|
|
assert math.isclose(result.at(initial_state), 0.08333333333)
|