def setUp(self):
likelihood = bilby.core.likelihood.Likelihood()
likelihood.parameters = dict(a=1, b=2, c=3)
delta_prior = prior.DeltaFunction(peak=0)
delta_prior.rescale = MagicMock(return_value=prior.DeltaFunction(
peak=1))
delta_prior.prob = MagicMock(return_value=1)
delta_prior.sample = MagicMock(return_value=0)
uniform_prior = prior.Uniform(0, 1)
uniform_prior.rescale = MagicMock(return_value=prior.Uniform(0, 2))
uniform_prior.prob = MagicMock(return_value=1)
uniform_prior.sample = MagicMock(return_value=0.5)
priors = dict(a=delta_prior, b='string', c=uniform_prior)
likelihood.log_likelihood_ratio = MagicMock(return_value=1)
likelihood.log_likelihood = MagicMock(return_value=2)
test_directory = 'test_directory'
if os.path.isdir(test_directory):
os.rmdir(test_directory)
self.sampler = bilby.core.sampler.Sampler(
likelihood=likelihood,
priors=priors,
outdir=test_directory,
use_ratio=False,
skip_import_verification=True)
def setUp(self):
self.priors = prior.PriorDict(
dict(
reflective=prior.Uniform(minimum=-0.5,
maximum=1,
boundary="reflective"),
periodic=prior.Uniform(minimum=-0.5,
maximum=1,
boundary="periodic"),
default=prior.Uniform(minimum=-0.5, maximum=1),
))
self.sample_above = dict(reflective=1.1, periodic=1.1, default=1.1)
self.sample_below = dict(reflective=-0.6, periodic=-0.6, default=-0.6)
self.sample_way_above_case1 = dict(reflective=272,
periodic=272,
default=272)
self.sample_way_above_case2 = dict(reflective=270.1,
periodic=270.1,
default=270.1)
self.sample_way_below_case1 = dict(reflective=-274,
periodic=-274.1,
default=-274)
self.sample_way_below_case2 = dict(reflective=-273.1,
periodic=-273.1,
default=-273.1)
self.jump_proposal = proposal.JumpProposal(priors=self.priors)
def setUp(self):
self.priors = prior.PriorDict(
dict(
phase=prior.Uniform(minimum=0.0, maximum=2 * np.pi),
psi=prior.Uniform(minimum=0.0, maximum=np.pi),
))
self.jump_proposal = bilby.gw.sampler.proposal.PolarisationPhaseJump(
priors=self.priors)
def setUp(self):
self.priors = prior.PriorDict(
dict(
reflective=prior.Uniform(minimum=-0.5, maximum=1, boundary="periodic"),
periodic=prior.Uniform(minimum=-0.5, maximum=1, boundary="reflective"),
default=prior.Uniform(minimum=-0.5, maximum=1),
)
)
self.jump_proposal = proposal.NormJump(step_size=3.0, priors=self.priors)
def setUp(self):
self.priors = prior.PriorDict(
dict(
ra=prior.Uniform(minimum=0.0, maximum=2 * np.pi, boundary="periodic"),
dec=prior.Uniform(minimum=0.0, maximum=np.pi, boundary="reflective"),
)
)
self.jump_proposal = bilby.gw.sampler.proposal.SkyLocationWanderJump(
priors=self.priors
)
def setUp(self):
self.priors = prior.PriorDict(
dict(
reflective=prior.Uniform(
minimum=-0.5, maximum=1, boundary="reflective"
),
periodic=prior.Uniform(minimum=-0.5, maximum=1, boundary="periodic"),
default=prior.Uniform(minimum=-0.5, maximum=1),
)
)
self.jump_proposal = proposal.EnsembleEigenVector(priors=self.priors)
def setUp(self):
self.priors = prior.PriorDict(
dict(
reflective=prior.Uniform(
minimum=-0.5, maximum=1, boundary="reflective"
),
periodic=prior.Uniform(minimum=-0.5, maximum=1, boundary="periodic"),
default=prior.Uniform(minimum=-0.5, maximum=1),
)
)
self.jump_proposal = proposal.DifferentialEvolution(
sigma=1e-3, mu=0.5, priors=self.priors
)
def setUp(self):
self.priors = prior.PriorDict(
dict(
reflective=prior.Uniform(
minimum=-0.5, maximum=1, boundary="reflective"
),
periodic=prior.Uniform(minimum=-0.5, maximum=1, boundary="periodic"),
default=prior.Uniform(minimum=-0.5, maximum=1),
)
)
self.jump_proposal = proposal.EnsembleWalk(
random_number_generator=random.random, n_points=4, priors=self.priors
)
def setUp(self):
self.priors = prior.PriorDict(
dict(
phase=prior.Uniform(minimum=0.0, maximum=2 * np.pi),
psi=prior.Cosine(minimum=0.0, maximum=np.pi),
))
self.jump_proposal = proposal.DrawFlatPrior(priors=self.priors)
def test_prior_transform_transforms_search_parameter_keys(self):
self.sampler.prior_transform([0])
expected_prior = prior.Uniform(0, 1)
self.assertListEqual([self.sampler.priors['c'].minimum,
self.sampler.priors['c'].maximum],
[expected_prior.minimum,
expected_prior.maximum])
def setUp(self):
self.priors = prior.PriorDict(dict(reflective=prior.Uniform(minimum=-0.5, maximum=1, boundary='reflective'),
periodic=prior.Uniform(minimum=-0.5, maximum=1, boundary='periodic'),
default=prior.Uniform(minimum=-0.5, maximum=1)))
self.jump_proposal = proposal.EnsembleStretch(scale=3.0, priors=self.priors)
