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)