def default_pert():
return DomainRandomizer(
NormalDomainParam(name='mass', mean=1.2, std=0.1, clip_lo=10, clip_up=100),
UniformDomainParam(name='special', mean=0, halfspan=42, clip_lo=-7.4, roundint=True),
NormalDomainParam(name='length', mean=4, std=0.6, clip_up=50.1),
UniformDomainParam(name='time_delay', mean=13, halfspan=6, clip_up=17, roundint=True),
MultivariateNormalDomainParam(name='multidim', mean=10*to.ones((2,)), cov=2*to.eye(2), clip_up=11)
)
def default_randomizer():
return DomainRandomizer(
NormalDomainParam(name="mass", mean=1.2, std=0.1, clip_lo=10, clip_up=100),
UniformDomainParam(name="special", mean=0, halfspan=42, clip_lo=-7.4, roundint=True),
NormalDomainParam(name="length", mean=4, std=0.6, clip_up=50.1),
UniformDomainParam(name="time_delay", mean=13, halfspan=6, clip_up=17, roundint=True),
MultivariateNormalDomainParam(name="multidim", mean=10 * to.ones((2,)), cov=2 * to.eye(2), clip_up=11),
)
NormalDomainParam,
UniformDomainParam,
)
from pyrado.domain_randomization.domain_randomizer import DomainRandomizer
DomainParam(name="a", mean=1)
BernoulliDomainParam(name="b", val_0=2, val_1=5, prob_1=0.8)
DomainRandomizer(
NormalDomainParam(name="mass", mean=1.2, std=0.1, clip_lo=10, clip_up=100))
DomainRandomizer(
NormalDomainParam(name="mass", mean=1.2, std=0.1, clip_lo=10, clip_up=100),
UniformDomainParam(name="special",
mean=0,
halfspan=42,
clip_lo=-7.4,
roundint=True),
NormalDomainParam(name="length", mean=4, std=0.6, clip_up=50.1),
UniformDomainParam(name="time_delay",
mean=13,
halfspan=6,
clip_up=17,
roundint=True),
MultivariateNormalDomainParam(name="multidim",
mean=10 * to.ones((2, )),
cov=2 * to.eye(2),
clip_up=11),
)
NormalDomainParam,
UniformDomainParam,
)
from pyrado.domain_randomization.utils import param_grid
from pyrado.environments.sim_base import SimEnv
@pytest.mark.parametrize(
"dp",
[
UniformDomainParam(
name="", mean=3.0, halfspan=11.0, clip_lo=-5, clip_up=5),
NormalDomainParam(name="", mean=10, std=1.0, clip_lo=9, clip_up=11),
MultivariateNormalDomainParam(name="",
mean=to.ones((2, 1)),
cov=to.eye(2),
clip_lo=-1,
clip_up=1.0),
MultivariateNormalDomainParam(
name="", mean=10 * to.ones((2, )), cov=2 * to.eye(2), clip_up=11),
BernoulliDomainParam(name="", val_0=2, val_1=5, prob_1=0.8),
BernoulliDomainParam(name="", val_0=-3, val_1=5, prob_1=0.8,
clip_up=4),
],
ids=["U", "N", "MVN_v1", "MVN_v2", "B_v1", "B_v2"],
)
@pytest.mark.parametrize("num_samples", [1, 5, 100])
def test_domain_param(dp, num_samples):
# assert dp == dp
fns = dp.get_field_names()
assert fns is not None