diff --git a/bilby/core/likelihood.py b/bilby/core/likelihood.py
index efc8d580cf9567d876e5f2de198e333635efc054..10feec20783621b55cd3a5928b0405a2e601dce3 100644
--- a/bilby/core/likelihood.py
+++ b/bilby/core/likelihood.py
@@ -19,6 +19,7 @@ class Likelihood(object):
"""
self.parameters = parameters
self._meta_data = None
+ self._marginalized_parameters = []
def __repr__(self):
return self.__class__.__name__ + '(parameters={})'.format(self.parameters)
@@ -61,6 +62,10 @@ class Likelihood(object):
else:
raise ValueError("The meta_data must be an instance of dict")
+ @property
+ def marginalized_parameters(self):
+ return self._marginalized_parameters
+
class ZeroLikelihood(Likelihood):
""" A special test-only class which already returns zero likelihood
diff --git a/bilby/core/sampler/__init__.py b/bilby/core/sampler/__init__.py
index 37311298ee32d65b8228938d20584f322e9f3ad9..0bc59adff77bed66f25bfd426c590e64c28a6ebb 100644
--- a/bilby/core/sampler/__init__.py
+++ b/bilby/core/sampler/__init__.py
@@ -4,9 +4,9 @@ import datetime
from collections import OrderedDict
from ..utils import command_line_args, logger
-from ..prior import PriorDict
+from ..prior import PriorDict, DeltaFunction
-from .base_sampler import Sampler
+from .base_sampler import Sampler, SamplingMarginalisedParameterError
from .cpnest import Cpnest
from .dynesty import Dynesty
from .dynamic_dynesty import DynamicDynesty
@@ -119,6 +119,8 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
if priors is None:
priors = dict()
+ _check_marginalized_parameters_not_sampled(likelihood, priors)
+
if type(priors) in [dict, OrderedDict]:
priors = PriorDict(priors)
elif isinstance(priors, PriorDict):
@@ -137,7 +139,6 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
from bilby.core.likelihood import ZeroLikelihood
likelihood = ZeroLikelihood(likelihood)
-
if isinstance(sampler, Sampler):
pass
elif isinstance(sampler, str):
@@ -210,3 +211,12 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
result.plot_corner()
logger.info("Summary of results:\n{}".format(result))
return result
+
+
+def _check_marginalized_parameters_not_sampled(likelihood, priors):
+ for key in likelihood.marginalized_parameters:
+ if key in priors:
+ if not isinstance(priors[key], (float, DeltaFunction)):
+ raise SamplingMarginalisedParameterError(
+ "Likelihood is {} marginalized but you are trying to sample in {}. "
+ .format(key, key))
diff --git a/bilby/core/sampler/base_sampler.py b/bilby/core/sampler/base_sampler.py
index fe90758ef94da23dc47baa86326a7e37112485d9..ab6d62bd4206caf12db8fbeda6b344d4ada02e0f 100644
--- a/bilby/core/sampler/base_sampler.py
+++ b/bilby/core/sampler/base_sampler.py
@@ -644,3 +644,7 @@ class SamplerNotInstalledError(SamplerError):
class IllegalSamplingSetError(Error):
""" Class for illegal sets of sampling parameters """
+
+
+class SamplingMarginalisedParameterError(IllegalSamplingSetError):
+ """ Class for errors that occur when sampling over marginalized parameters """
diff --git a/bilby/gw/likelihood.py b/bilby/gw/likelihood.py
index 3741f536cb4443533385c03be726e9bc875a31ba..9879a718729d773bbe3f1830169808da4f579cf7 100644
--- a/bilby/gw/likelihood.py
+++ b/bilby/gw/likelihood.py
@@ -118,6 +118,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
priors['time_jitter'] = Uniform(
minimum=- self._delta_tc / 2, maximum=self._delta_tc / 2,
boundary='periodic')
+ self._marginalized_parameters.append('geocent_time')
elif self.jitter_time:
logger.debug(
"Time jittering requested with non-time-marginalised "
@@ -129,6 +130,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
self._bessel_function_interped = None
self._setup_phase_marginalization()
priors['phase'] = float(0)
+ self._marginalized_parameters.append('phase')
if self.distance_marginalization:
self._lookup_table_filename = None
@@ -142,6 +144,7 @@ class GravitationalWaveTransient(likelihood.Likelihood):
self._setup_distance_marginalization(
distance_marginalization_lookup_table)
priors['luminosity_distance'] = float(self._ref_dist)
+ self._marginalized_parameters.append('luminosity_distance')
def __repr__(self):
return self.__class__.__name__ + '(interferometers={},\n\twaveform_generator={},\n\ttime_marginalization={}, ' \
diff --git a/test/gw_likelihood_test.py b/test/gw_likelihood_test.py
index 2317baaee6baf5919d5d157fb8b9c00583653c33..25171e681e324a96ce4b44da8dda9385a0c5f516 100644
--- a/test/gw_likelihood_test.py
+++ b/test/gw_likelihood_test.py
@@ -327,6 +327,36 @@ class TestMarginalizedLikelihood(unittest.TestCase):
self.assertTrue(same)
self.prior['phase'] = temp
+ def test_run_sampler_flags_if_marginalized_phase_is_sampled(self):
+ like = bilby.gw.likelihood.GravitationalWaveTransient(
+ interferometers=self.interferometers,
+ waveform_generator=self.waveform_generator, priors=self.prior,
+ phase_marginalization=True
+ )
+ new_prior = self.prior.copy()
+ new_prior['phase'] = bilby.prior.Uniform(minimum=0, maximum=2*np.pi)
+ for key, param in dict(
+ mass_1=31., mass_2=29., a_1=0.4, a_2=0.3, tilt_1=0.0, tilt_2=0.0,
+ phi_12=1.7, phi_jl=0.3, theta_jn=0.4, psi=2.659, ra=1.375, dec=-1.2108).items():
+ new_prior[key] = param
+ with self.assertRaises(bilby.core.sampler.SamplingMarginalisedParameterError):
+ bilby.run_sampler(like, new_prior)
+
+ def test_run_sampler_flags_if_marginalized_time_is_sampled(self):
+ like = bilby.gw.likelihood.GravitationalWaveTransient(
+ interferometers=self.interferometers,
+ waveform_generator=self.waveform_generator, priors=self.prior,
+ time_marginalization=True
+ )
+ new_prior = self.prior.copy()
+ new_prior['geocent_time'] = bilby.prior.Uniform(minimum=0, maximum=1)
+ for key, param in dict(
+ mass_1=31., mass_2=29., a_1=0.4, a_2=0.3, tilt_1=0.0, tilt_2=0.0,
+ phi_12=1.7, phi_jl=0.3, theta_jn=0.4, psi=2.659, ra=1.375, dec=-1.2108).items():
+ new_prior[key] = param
+ with self.assertRaises(bilby.core.sampler.SamplingMarginalisedParameterError):
+ bilby.run_sampler(like, new_prior)
+
class TestPhaseMarginalization(unittest.TestCase):