def test_mecs():
import numpy as np
E = [[0,1],[1,2],[2,0],[3,2],[3,1],[3,5],[4,2],[4,6],[5,4],[5,3],[6,4],[7,5],[7,6],[7,7]]
P = np.zeros(shape=(8,8))
for u,v in E:
# initialize with arbitrary probabilities
ucount = len([w for w,z in E if w == u])
P[u,v] = 1/ucount
dtmc = DTMC(P)
components,mec_count = dtmc.maximal_end_components()
assert (components == np.array([1., 1., 1., 0., 0., 0., 0., 0.])).all()
def test_read_write():
for dtmc in dtmcs:
print(dtmc)
with tempfile.NamedTemporaryFile() as namedtf:
dtmc.save(namedtf.name)
read_dtmc = DTMC.from_file(
namedtf.name + ".lab", namedtf.name + ".tra")
def example_dtmcs():
dtmcs = []
dtmcs.append(
DTMC.from_prism_model("./examples/datasets/crowds.pm",
prism_constants={("CrowdSize", 2),
("TotalRuns", 8)},
extra_labels={("target", "observe0>1")}))
dtmcs.append(toy_dtmc1())
dtmcs.append(toy_dtmc2())
dtmcs.append(
DTMC.from_prism_model("./examples/datasets/leader_sync3_2.pm",
extra_labels={("target", "s1=3 & s2=3 & s3=3")}))
dtmcs.append(
DTMC.from_prism_model("./examples/datasets/brp.pm",
prism_constants={("N", 2), ("MAX", 1)},
extra_labels={("target", "s=5 & srep=2"),
("all", "true")}))
return dtmcs
def toy_dtmc1():
P = [[0.3, 0.7, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.5, 0.0, 0.0, 0.0, 0.0, 0.5],
[0.0, 0.1, 0.0, 0.7, 0.0, 0.2, 0.0],
[0.0, 0.2, 0.0, 0.4, 0.4, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 0.0],
[0.0, 0.0, 0.1, 0.9, 0.0, 0.0, 0.0]]
labels = {"target": {3, 4, 6}, "init": {0}}
return (DTMC(P, label_to_states=labels))
def construct_conflicts(self, family, assignment, dtmc, conflict_requests, ce_generator):
conflicts = []
for request in conflict_requests:
index,prop,member_result,family_result = request
if prop.minimizing:
# safety
threshold = prop.threshold
target_label = str(prop.property.raw_formula.subformula.subformula)
else:
# liveness: flip threshold
threshold = 1 - prop.threshold
target_label = "target"
# construct a labeled SWITSS DTMC
switss_dtmc = SWITSS_DTMC.from_stormpy(dtmc.model)
for i,state in enumerate(dtmc.model.states):
# copy labels
for label in state.labels:
switss_dtmc.add_label(i, label)
# label fail states
if not prop.minimizing and not member_result.result.at(i) > 0.0:
switss_dtmc.add_label(i, "target")
# label states by relevant holes id
for dtmc_state in range(dtmc.states):
mdp_state = dtmc.quotient_state_map[dtmc_state]
for hole in dtmc.quotient_container.coloring.state_to_holes[mdp_state]:
switss_dtmc.add_label(dtmc_state, str(hole))
switss_dtmc_rf,_,_ = ReachabilityForm.reduce(switss_dtmc, "init", target_label)
results = list(ce_generator.solveiter(switss_dtmc_rf, threshold, "max"))
# get last result
witnessing_subsystem = results[-1].subsystem.subsys.system
conflict = set([int(label) for label in witnessing_subsystem.states_by_label.keys() if label.isnumeric()])
conflict = list(conflict)
scheduler_selection = None
if family_result is not None:
scheduler_selection = family_result.primary_selection
conflict = self.generalize_conflict(assignment, conflict, scheduler_selection)
conflicts.append(conflict)
return conflicts
def toy_dtmc2():
P = [[0.3, 0.7, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.1, 0.0, 0.7, 0.0, 0.1, 0.0, 0.0, 0.1, 0.0],
[0.0, 0.1, 0.0, 0.0, 0.0, 0.1, 0.0, 0.0, 0.8, 0.0],
[0.0, 0.2, 0.0, 0.4, 0.2, 0.0, 0.1, 0.1, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.7, 0.0, 0.0, 0.1, 0.2, 0.0],
[0.0, 0.0, 0.0, 0.1, 0.0, 0.8, 0.0, 0.0, 0.1, 0.0],
[0.0, 0.0, 0.7, 0.3, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0],
[0.0, 0.0, 0.0, 0.0, 0.3, 0.0, 0.0, 0.6, 0.0, 0.1],
[0.0, 0.0, 0.0, 0.0, 0.0, 0.9, 0.0, 0.0, 0.1, 0.0],
[0.0, 0.0, 0.1, 0.9, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0]]
labels = {
"target": {8},
"init": {0},
"group1": {1, 3, 6},
"group2": {7, 9, 2},
"group3": {4, 5}
}
return (DTMC(P, label_to_states=labels))