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DEP: remove ability to use parameters as state #1050

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DEP: remove ability to use parameters as state #1050

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95a89fd
DEP: remove ability to use parameters as state
ColmTalbot Feb 19, 2026
02a61bc
MAINT: Clean up imports in likelihood.py
ColmTalbot Feb 19, 2026
dc31a80
MAINT: Remove unused import
ColmTalbot Feb 19, 2026
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12 changes: 5 additions & 7 deletions bilby/bilby_mcmc/sampler.py
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Original file line number Diff line number Diff line change
Expand Up @@ -10,7 +10,6 @@
from scipy.integrate import trapezoid
from scipy.optimize import differential_evolution

from ..core.likelihood import _safe_likelihood_call
from ..core.result import rejection_sample
from ..core.sampler.base_sampler import (
MCMCSampler,
Expand Down Expand Up @@ -1240,11 +1239,10 @@ def log_likelihood(self, sample):
params = deepcopy(_sampling_convenience_dump.parameters)
params.update(sample.sample_dict)

return _safe_likelihood_call(
_sampling_convenience_dump.likelihood,
parameters=params,
use_ratio=self.use_ratio,
)
if self.use_ratio:
return _sampling_convenience_dump.likelihood.log_likelihood_ratio(params)
else:
return _sampling_convenience_dump.likelihood.log_likelihood(params)

def log_prior(self, sample):
return _sampling_convenience_dump.priors.ln_prob(
Expand Down Expand Up @@ -1403,7 +1401,7 @@ def neg_log_post(x):
parameters = deepcopy(_sampling_convenience_dump.parameters)
parameters.update(sample)

return -beta * _safe_likelihood_call(likelihood, parameters) - ln_prior
return -beta * likelihood.log_likelihood(parameters) - ln_prior

res = differential_evolution(neg_log_post, bounds, popsize=100, init="sobol")
if res.success:
Expand Down
4 changes: 1 addition & 3 deletions bilby/core/fisher.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,8 +3,6 @@
import scipy.linalg
from scipy.optimize import minimize

from .likelihood import _safe_likelihood_call


class FisherMatrixPosteriorEstimator(object):
def __init__(self, likelihood, priors, parameters=None, fd_eps=1e-6, n_prior_samples=100):
Expand Down Expand Up @@ -47,7 +45,7 @@ def __init__(self, likelihood, priors, parameters=None, fd_eps=1e-6, n_prior_sam
self.prior_width_dict[key] = width

def log_likelihood(self, sample):
return _safe_likelihood_call(self.likelihood, sample)
return self.likelihood.log_likelihood(sample)

def calculate_iFIM(self, sample):
FIM = self.calculate_FIM(sample)
Expand Down
5 changes: 1 addition & 4 deletions bilby/core/grid.py
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Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,6 @@

import numpy as np

from .likelihood import _safe_likelihood_call
from .prior import Prior, PriorDict
from .utils import (
logtrapzexp, check_directory_exists_and_if_not_mkdir, logger,
Expand Down Expand Up @@ -313,9 +312,7 @@ def _evaluate_recursion(self, dimension, parameters):
current_point = tuple([[int(np.where(
parameters[name] ==
self.sample_points[name])[0])] for name in self.parameter_names])
self._ln_likelihood[current_point] = _safe_likelihood_call(
self.likelihood, parameters
)
self._ln_likelihood[current_point] = self.likelihood.log_likelihood(parameters)
else:
name = self.parameter_names[dimension]
for ii in range(self._ln_likelihood.shape[dimension]):
Expand Down
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