def test_domain_random():
carDomain = Struct({
'position': Box([-10, 10], [-10, 10], [0, 1]),
'heading': Box([0, math.pi]),
})
domain = Array(carDomain, (2, 2))
sampler = RandomSampler(domain)
def check(samples):
for sample in samples:
assert type(sample) is tuple
assert len(sample) == 2
for row in sample:
assert type(row) is tuple
assert len(row) == 2
for car in row:
assert type(car) is carDomain.makePoint
position = car.position
assert type(position) is tuple
assert len(position) == 3
heading = car.heading
assert type(heading) is tuple
assert len(heading) == 1
assert any(sample[0][0].position[0] > sample[1][1].position[0]
for sample in samples)
assert any(sample[0][0].position[0] < sample[1][1].position[0]
for sample in samples)
check([sampler.nextSample() for i in range(100)])
check(list(itertools.islice(sampler, 100)))
def test_random_restore(tmpdir):
space = FeatureSpace({
'a':
Feature(DiscreteBox([0, 12])),
'b':
Feature(Box((0, 1)), lengthDomain=DiscreteBox((0, 2)))
})
sampler = FeatureSampler.randomSamplerFor(space)
path = os.path.join(tmpdir, 'blah.dat')
sampler.saveToFile(path)
sample1 = sampler.nextSample()
sampler = FeatureSampler.restoreFromFile(path)
sample2 = sampler.nextSample()
assert sample1 == sample2
def test_space_random():
space = FeatureSpace({
'a':
Feature(DiscreteBox([0, 12])),
'b':
Feature(Box((0, 1)), lengthDomain=DiscreteBox((0, 2)))
})
sampler = FeatureSampler.randomSamplerFor(space)
def check(samples):
for sample in samples:
assert type(sample) is space.makePoint
a = sample.a
assert type(a) is tuple
assert len(a) == 1
assert type(a[0]) is int
assert 0 <= a[0] <= 12
b = sample.b
assert type(b) is tuple
l = len(b)
assert 0 <= l <= 2
if l > 0:
assert type(b[0]) is tuple
assert len(b[0]) == 1
assert 0 <= b[0][0] <= 1
if l > 1:
assert type(b[1]) is tuple
assert len(b[1]) == 1
assert 0 <= b[1][0] <= 1
assert any(sample.a[0] > 6 for sample in samples)
assert any(sample.a[0] < 6 for sample in samples)
assert any(len(sample.b) == 0 for sample in samples)
assert any(len(sample.b) == 1 for sample in samples)
assert any(len(sample.b) == 2 for sample in samples)
check([sampler.nextSample() for i in range(100)])
check(list(itertools.islice(sampler, 100)))
from scenic.simulators.utils.colors import Color
from scenic.simulators.gta.interface import CarModel as GTACarModel
from scenic.simulators.webots.road.car_models import (CarModel as
WebotsCarModel, carModels
as webotsCarModels)
from verifai.features import (Constant, Categorical, Real, Box, Array, Struct,
Feature, FeatureSpace)
from verifai.samplers.feature_sampler import FeatureSampler
from verifai.utils.frozendict import frozendict
scalarDomain = Real()
vectorDomain = Array(scalarDomain, (2, ))
gtaModelDomain = Categorical(*GTACarModel.models.values())
webotsModelDomain = Categorical(*webotsCarModels)
colorDomain = Box((0, 1), (0, 1), (0, 1))
def convertToVerifaiType(value, strict=True):
"""Attempt to convert a Scenic value to a type known to VerifAI"""
ty = underlyingType(value)
if ty is float or ty is int:
return float(value)
elif ty is list or ty is tuple:
return tuple(convertToVerifaiType(e, strict=strict) for e in value)
elif issubclass(ty, dict) and not needsSampling(value):
return frozendict(value)
elif ty is GTACarModel:
return value
elif ty is WebotsCarModel:
return value