def test_resource_level_creation():
L = tsk.language("mylang", theories=[Theory.EQUALITY, Theory.ARITHMETIC])
platform_t = L.sort('platform')
rov1 = L.constant('rov1', platform_t)
int_t = L.Integer
direction = L.function('direction', platform_t, int_t)
req_1 = temporal.ResourceLevel(**{
"ts": 0.0, "td": 20.0, "r": direction(rov1), "n": L.constant(0, int_t)
})
def test_action_creation():
L = tsk.language("mylang", theories=[Theory.EQUALITY, Theory.ARITHMETIC])
int_t = L.Integer
platform_t = L.sort('platform')
rov1 = L.constant('rov1', platform_t)
direction = L.function('direction', platform_t, int_t)
sensor_sort = L.sort('sensor')
camera, range, bearing = [
L.constant(name, sensor_sort)
for name in ('camera', 'range', 'bearing')
]
engaged = L.function('engaged', sensor_sort, int_t)
region_t = L.sort('region')
p0 = L.constant('p0', region_t)
position = L.predicate('position', platform_t, region_t)
observed = L.predicate('observed', region_t)
req_1 = temporal.ResourceLock(**{
"ts": 0.0,
"td": 10.0,
"r": engaged(camera)
})
req_2 = temporal.ResourceLevel(**{
"ts": 0.0,
"td": 20.0,
"r": direction(rov1),
"n": L.constant(0, int_t)
})
act = temporal.Action(name='observe_poi',
precondition=position(rov1, p0),
requirements=[req_1, req_2],
effects=[(21.0, observed(p0))])
assert len(act.locks) == 1
assert len(act.levels) == 1
assert len(act.effects) == 1
def test_instance_creation():
L = tsk.language("mylang", theories=[Theory.EQUALITY, Theory.ARITHMETIC])
int_t = L.Integer
obj_t = L.Object
platform_t = L.sort('platform')
rov1 = L.constant('rov1', platform_t)
direction = L.function('direction', platform_t, int_t)
sensor_sort = L.sort('sensor')
camera, range, bearing = [L.constant(name, sensor_sort) for name in ('camera', 'range', 'bearing')]
engaged = L.function('engaged', sensor_sort, int_t)
region_t = L.sort('region')
p0 = L.constant('p0', region_t)
p1 = L.constant('p1', region_t)
p2 = L.constant('p2', region_t)
t0 = L.constant('t0', obj_t)
t1 = L.constant('t1', obj_t)
t2 = L.constant('t2', obj_t)
#t0, t1, t2 = [L.constant('t{}'.format(i), obj_t)
# for i in range(3)]
position = L.predicate('position', obj_t, region_t)
observed = L.predicate('observed', obj_t)
estimated_range = L.predicate('estimated_range', obj_t)
estimated_bearing = L.predicate('estimated_bearing', obj_t)
req_1 = temporal.ResourceLock(**{
"ts": 0.0, "td": 10.0, "r": engaged(camera)
})
req_2 = temporal.ResourceLock(**{
"ts": 0.0, "td": 10.0, "r": engaged(range)
})
req_3 = temporal.ResourceLock(**{
"ts": 0.0, "td": 10.0, "r": engaged(bearing)
})
req_4 = temporal.ResourceLevel(**{
"ts": 0.0, "td": 20.0, "r": direction(rov1), "n": L.constant(0, int_t)
})
a1 = temporal.Action(
name='localize_t0',
parameters=[],
precondition=position(rov1, p0),
requirements=[
TimedEffect(0.0, req_2),
TimedEffect(0.0, req_3)],
timed_effects=[
TimedEffect(15.0, estimated_range(t0)),
TimedEffect(20.0, estimated_bearing(t0))],
untimed_effects=[]
)
a2 = temporal.Action(
name='observed_t0',
parameters=[],
precondition=land(position(rov1, p0), estimated_range(t0), estimated_bearing(t0)),
requirements=[
TimedEffect(0.0, req_1),
TimedEffect(0.0, req_2)],
timed_effects=[
TimedEffect(21.0, observed(t0))],
untimed_effects=[]
)
initial = Model(L)
initial.add(position, rov1, p0)
initial.evaluator = evaluate
inst = temporal.Instance(
L=L,
X=[position(rov1, p0),
estimated_range(t0), estimated_bearing(t0), observed(t0),
estimated_range(t1), estimated_bearing(t1), observed(t1),
estimated_range(t2), estimated_bearing(t2), observed(t2)],
I=initial,
A=[a1, a2],
G=observed(t0)
)
assert len(inst.R) == 3