def test_dense_prop_const_int64():
my_monitor = dense_timed_monitor(
pattern="{speed > 12.0}",
semantics="boolean",
piecewise='linear'
)
input_sequence = [
dict(time=0.0, speed=3.0),
dict(time=10.0, speed=9.0),
dict(time=12.0, speed=13.0),
dict(time=14.0, speed=11.0),
dict(time=15.0, speed=9.0),
dict(time=18.0, speed=6.0),
dict(time=19.0, speed=14.0)
]
result = []
for x in input_sequence:
chunk = my_monitor.update(x)
result.extend(chunk)
expected = [
{'time': 0, 'value': False},
{'time': 11.5, 'value': True},
{'time': 13.0, 'value': False},
{'time': 18.75, 'value': True}
]
approx_expected = [pytest.approx(x, 0.001) for x in expected]
assert result == approx_expected
def check_event(event):
global last_time, tl_oracle, property, last_res
event_dict = json.loads(event)
if not tl_oracle:
if model == 'dense' and 'time' in event_dict:
tl_oracle = reelay.dense_timed_monitor(pattern=property.PROPERTY)
else:
tl_oracle = reelay.discrete_timed_monitor(
pattern=property.PROPERTY)
if 'time' in event_dict:
if last_time is None:
last_time = event_dict['time']
event_dict['time'] = 0
else:
event_dict['time'] = event_dict['time'] - last_time
abs_msg = property.abstract_message(event_dict)
res = tl_oracle.update(abs_msg)
if model == 'discrete' and res:
last_res = res['value']
if model == 'dense' and res:
last_res = True
for d in res:
if not d['value']:
last_res = False
break
return last_res
def test_dense_robust_const_float64():
my_monitor = dense_timed_monitor(
pattern=r"{speed > 130} since[:40] {lights_on: true}",
semantics="robustness",
piecewise='constant')
input_sequence = [
dict(time=0.0, speed=33, lights_on=False),
dict(time=12.0, speed=63, lights_on=False),
dict(time=14.0, speed=93, lights_on=True),
dict(time=18.0, speed=133, lights_on=False),
dict(time=21.0, speed=134, lights_on=False),
dict(time=26.0, speed=133, lights_on=False),
dict(time=45.0, speed=132, lights_on=False),
dict(time=68.0, speed=132, lights_on=False),
]
result = []
for x in input_sequence:
chunk = my_monitor.update(x)
result.extend(chunk)
print(result)
expected = [{
'time': 0.0,
'value': -float('inf')
}, {
'time': 14.0,
'value': float('inf')
}, {
'time': 18.0,
'value': 3
}, {
'time': 45.0,
'value': 2
}, {
'time': 58.0,
'value': -float('inf')
}]
approx_expected = [pytest.approx(x, 0.001) for x in expected]
assert result == approx_expected
def test_dense_categ_const_float64():
my_monitor = dense_timed_monitor(pattern=r"""forall[sensor].
{sensor_id: *sensor, action: send_data}
implies
once[:40]{sensor_id: *sensor, action: calibrated}
""",
semantics="boolean",
piecewise='constant')
input_sequence = [
dict(time=0.0),
dict(time=6.0, sensor_id="1", action="calibrated"),
dict(time=12.0, sensor_id="2", action="calibrated"),
dict(time=15.0, sensor_id="1", action="send_data"),
dict(time=24.0, sensor_id="1", action="send_data"),
dict(time=27.0, sensor_id="1", action="send_data"),
dict(time=32.0, sensor_id="1", action="calibrated"),
dict(time=46.0, sensor_id="2", action="send_data"),
dict(time=49.0, sensor_id="1", action="send_data"),
dict(time=56.0, sensor_id="1", action="send_data"),
dict(time=62.0, sensor_id="2", action="send_data"),
dict(time=67.0, sensor_id="1", action="send_data"),
]
result = []
for x in input_sequence:
chunk = my_monitor.update(x)
print(chunk)
result.extend(chunk)
expected = [
{
'time': 0.0,
'value': True
},
{
'time': 62.0,
'value': False
},
]
approx_expected = [pytest.approx(x, 0.001) for x in expected]
assert result == approx_expected
faulty_sys_behavior = [
dict(time=0,
door_open=False,
dow_suppressed=False,
door_open_warning=False),
dict(time=1, door_open=True, dow_suppressed=False,
door_open_warning=False),
dict(time=6, door_open=True, dow_suppressed=False, door_open_warning=True),
dict(time=7, door_open=True, dow_suppressed=True, door_open_warning=False),
dict(time=8, door_open=True, dow_suppressed=True, door_open_warning=True),
dict(time=9),
]
my_monitor_1 = reelay.dense_timed_monitor(
pattern=
r"(historically[0:5]{door_open} and not {dow_suppressed}) -> {door_open_warning}"
)
my_monitor_2 = reelay.dense_timed_monitor(
pattern=r"{door_open_warning} -> historically[0:5]{door_open}")
my_monitor_3 = reelay.dense_timed_monitor(
pattern=r"{door_open_warning} -> not {dow_suppressed}")
my_monitor_4 = reelay.dense_timed_monitor(
pattern=
r"{door_open_warning} -> not(once[1:1]({door_open} since {door_open_warning}))"
)
ar1 = []
ar2 = []