.gitlab-ci.yml

@@ -75,6 +75,10 @@ basic-3.10:
   <<: *test-python
   image: python:3.10
 
+basic-3.11:
+  <<: *test-python
+  image: python:3.11
+
 .test-samplers-import: &test-samplers-import
   stage: initial
   script:
@@ -82,14 +86,18 @@ basic-3.10:
     - *list-env
     - python test/test_samplers_import.py
 
-import-samplers-3.9:
-  <<: *test-samplers-import
-  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
+# import-samplers-3.9:
+#   <<: *test-samplers-import
+#   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
 
 import-samplers-3.10:
   <<: *test-samplers-import
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
 
+import-samplers-3.11:
+  <<: *test-samplers-import
+  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python311
+
 .precommits: &precommits
   stage: initial
   script:
@@ -98,16 +106,15 @@ import-samplers-3.10:
     - pip install --upgrade pip
     - pip --cache-dir=$CACHE_DIR install --upgrade bilby
     - pip --cache-dir=$CACHE_DIR install .
-    - pip --cache-dir=$CACHE_DIR install pre-commit
     # Run precommits (flake8, spellcheck, isort, no merge conflicts, etc)
     - pre-commit run --all-files --verbose --show-diff-on-failure
 
-precommits-py3.9:
-  <<: *precommits
-  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
-  variables:
-    CACHE_DIR: ".pip39"
-    PYVERSION: "python39"
+# precommits-py3.9:
+#   <<: *precommits
+#   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
+#   variables:
+#     CACHE_DIR: ".pip39"
+#     PYVERSION: "python39"
 
 precommits-py3.10:
   <<: *precommits
@@ -135,10 +142,10 @@ install:
 
     - pytest --cov=bilby --durations 10
 
-python-3.9:
-  <<: *unit-test
-  needs: ["basic-3.9", "precommits-py3.9"]
-  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
+# python-3.9:
+#   <<: *unit-test
+#   needs: ["basic-3.9", "precommits-py3.9"]
+#   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
 
 python-3.10:
   <<: *unit-test
@@ -157,6 +164,11 @@ python-3.10:
       - htmlcov/
     expire_in: 30 days
 
+python-3.11:
+  <<: *unit-test
+  needs: ["basic-3.11"]
+  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python311
+
 .test-sampler: &test-sampler
   stage: test
   script:
@@ -164,16 +176,21 @@ python-3.10:
     - *list-env
     - pytest test/integration/sampler_run_test.py --durations 10 -v
 
-python-3.9-samplers:
-  <<: *test-sampler
-  needs: ["basic-3.9", "precommits-py3.9"]
-  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
+# python-3.9-samplers:
+#   <<: *test-sampler
+#   needs: ["basic-3.9", "precommits-py3.9"]
+#   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
 
 python-3.10-samplers:
   <<: *test-sampler
   needs: ["basic-3.10", "precommits-py3.10"]
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
 
+python-3.11-samplers:
+  <<: *test-sampler
+  needs: ["basic-3.11"]
+  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python311
+
 integration-tests-python-3.10:
   stage: test
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
@@ -195,24 +212,27 @@ integration-tests-python-3.10:
     - *list-env
     - pytest test/gw/plot_test.py
 
-plotting-python-3.9:
-  <<: *plotting
-  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
-  needs: ["basic-3.9", "precommits-py3.9"]
+# plotting-python-3.9:
+#   <<: *plotting
+#   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python39
+#   needs: ["basic-3.9", "precommits-py3.9"]
 
 plotting-python-3.10:
   <<: *plotting
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
   needs: ["basic-3.10", "precommits-py3.10"]
 
+plotting-python-3.11:
+  <<: *plotting
+  image: containers.ligo.org/lscsoft/bilby/v2-bilby-python311
+  needs: ["basic-3.11"]
+
 # ------------------- Docs stage -------------------------------------------
 
 docs:
   stage: docs
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
   before_script:
-    - conda install -c conda-forge pandoc ipython jupyter nbconvert
-    - python -m pip install ipykernel
     - python -m ipykernel install
   script:
     # Make the documentation
@@ -263,16 +283,22 @@ pages:
     - docker image tag v3-bilby-$PYVERSION containers.ligo.org/lscsoft/bilby/v2-bilby-$PYVERSION:latest
     - docker image push containers.ligo.org/lscsoft/bilby/v2-bilby-$PYVERSION:latest
 
-build-python39-container:
-  <<: *build-container
-  variables:
-    PYVERSION: "python39"
+# disable building python39 container due to dependency issues
+# build-python39-container:
+#   <<: *build-container
+#   variables:
+#     PYVERSION: "python39"
 
 build-python310-container:
   <<: *build-container
   variables:
     PYVERSION: "python310"
 
+build-python311-container:
+  <<: *build-container
+  variables:
+    PYVERSION: "python311"
+
 pypi-release:
   stage: deploy
   image: containers.ligo.org/lscsoft/bilby/v2-bilby-python310
@@ -280,7 +306,6 @@ pypi-release:
     TWINE_USERNAME: $PYPI_USERNAME
     TWINE_PASSWORD: $PYPI_PASSWORD
   before_script:
-    - python -m pip install twine setuptools_scm build
     - python -m build --sdist --wheel --outdir dist/ .
   script:
     - twine upload dist/*

AUTHORS.md

@@ -57,6 +57,7 @@ Michael Puerrer
 Michael Williams
 Monica Rizzo
 Moritz Huebner
+Nico Gerardo Bers
 Nicola De Lillo
 Nikhil Sarin
 Nirban Bose
@@ -80,6 +81,7 @@ Sharan Banagiri
 Shichao Wu
 Simon Stevenson
 Soichiro Morisaki
+Soumen Roy
 Stephen R Green
 Sumeet Kulkarni
 Sylvia Biscoveanu

CHANGELOG.md

 # All notable changes will be documented in this file
 
+## [2.2.3] 2024-02-24
+Version 2.2.3 release of Bilby
+
+This is a bugfix release 
+
+There are also a number of testing/infrastructure updates.
+
+### Changes
+- Fix a bug when the specified maximum frequency is too low for the multibanding likelihood (!1279)
+- Allow the `DirichletElement` prior to be pickled (!1312)
+- Add the ability to change the pool size when resuming a `dynesty` job (!1315)
+- Fix how the random seed is passed to `dynesty` (!1319)
+
 ## [2.2.2] 2023-11-29
 Version 2.2.2 release of Bilby
 

bilby/core/prior/conditional.py

@@ -372,6 +372,7 @@ class DirichletElement(ConditionalBeta):
             label + str(ii) for ii in range(order)
         ]
         self.__class__.__name__ = 'DirichletElement'
+        self.__class__.__qualname__ = 'DirichletElement'
 
     def dirichlet_condition(self, reference_parms, **kwargs):
         remaining = 1 - sum(

bilby/core/sampler/dynesty.py

@@ -123,6 +123,9 @@ class Dynesty(NestedSampler):
         The proposal methods to use during MCMC. This can be some combination
         of :code:`"diff", "volumetric"`. See the dynesty guide in the Bilby docs
         for more details. default=:code:`["diff"]`.
+    rstate: numpy.random.Generator (None)
+        Instance of a numpy random generator for generating random numbers.
+        Also see :code:`seed` in 'Other Parameters'.
 
     Other Parameters
     ================
@@ -143,8 +146,13 @@ class Dynesty(NestedSampler):
         has no impact on the sampling.
     dlogz: float, (0.1)
         Stopping criteria
+    seed: int (None)
+        Use to seed the random number generator if :code:`rstate` is not
+        specified.
     """
 
+    sampling_seed_key = "seed"
+
     @property
     def _dynesty_init_kwargs(self):
         params = inspect.signature(self.sampler_init).parameters
@@ -176,6 +184,7 @@ class Dynesty(NestedSampler):
     def default_kwargs(self):
         kwargs = self._dynesty_init_kwargs
         kwargs.update(self._dynesty_sampler_kwargs)
+        kwargs["seed"] = None
         return kwargs
 
     def __init__(
@@ -265,6 +274,14 @@ class Dynesty(NestedSampler):
             for equiv in self.npool_equiv_kwargs:
                 if equiv in kwargs:
                     kwargs["queue_size"] = kwargs.pop(equiv)
+        if "seed" in kwargs:
+            seed = kwargs.get("seed")
+            if "rstate" not in kwargs:
+                kwargs["rstate"] = np.random.default_rng(seed)
+            else:
+                logger.warning(
+                    "Kwargs contain both 'rstate' and 'seed', ignoring 'seed'."
+                )
 
     def _verify_kwargs_against_default_kwargs(self):
         if not self.kwargs["walks"]:
@@ -604,6 +621,7 @@ class Dynesty(NestedSampler):
             sampling_time_s=self.sampling_time.seconds,
             ncores=self.kwargs.get("queue_size", 1),
         )
+        self.kwargs["rstate"] = None
 
     def _update_sampling_time(self):
         end_time = datetime.datetime.now()
@@ -717,6 +735,7 @@ class Dynesty(NestedSampler):
                 self.sampler.nqueue = -1
                 self.start_time = self.sampler.kwargs.pop("start_time")
                 self.sampling_time = self.sampler.kwargs.pop("sampling_time")
+                self.sampler.queue_size = self.kwargs["queue_size"]
                 self.sampler.pool = self.pool
                 if self.pool is not None:
                     self.sampler.M = self.pool.map

bilby/gw/detector/interferometer.py

@@ -607,7 +607,7 @@ class Interferometer(object):
 
         Returns
         =======
-        float: The matched filter signal to noise ratio squared
+        complex: The matched filter signal to noise ratio
 
         """
         return gwutils.matched_filter_snr(

bilby/gw/likelihood/multiband.py

@@ -517,7 +517,7 @@ class MBGravitationalWaveTransient(GravitationalWaveTransient):
         for ifo in self.interferometers:
             logger.info("Pre-computing linear coefficients for {}".format(ifo.name))
             fddata = np.zeros(N // 2 + 1, dtype=complex)
-            fddata[:len(ifo.frequency_domain_strain)][ifo.frequency_mask] += \
+            fddata[:len(ifo.frequency_domain_strain)][ifo.frequency_mask[:len(fddata)]] += \
                 ifo.frequency_domain_strain[ifo.frequency_mask] / ifo.power_spectral_density_array[ifo.frequency_mask]
             for b in range(self.number_of_bands):
                 Ks, Ke = self.Ks_Ke[b]
@@ -606,7 +606,7 @@ class MBGravitationalWaveTransient(GravitationalWaveTransient):
         for ifo in self.interferometers:
             logger.info("Pre-computing quadratic coefficients for {}".format(ifo.name))
             full_inv_psds = np.zeros(N // 2 + 1)
-            full_inv_psds[:len(ifo.power_spectral_density_array)][ifo.frequency_mask] = (
+            full_inv_psds[:len(ifo.power_spectral_density_array)][ifo.frequency_mask[:len(full_inv_psds)]] = (
                 1 / ifo.power_spectral_density_array[ifo.frequency_mask]
             )
             for b in range(self.number_of_bands):

bilby/gw/utils.py

@@ -398,7 +398,7 @@ def read_frame_file(file_name, start_time, end_time, resample=None, channel=None
             strain = TimeSeries.read(source=file_name, channel=channel, start=start_time, end=end_time, **kwargs)
             loaded = True
             logger.info('Successfully loaded {}.'.format(channel))
-        except RuntimeError:
+        except (RuntimeError, ValueError):
             logger.warning('Channel {} not found. Trying preset channel names'.format(channel))
 
     if loaded is False:
@@ -418,7 +418,7 @@ def read_frame_file(file_name, start_time, end_time, resample=None, channel=None
                                              **kwargs)
                     loaded = True
                     logger.info('Successfully read strain data for channel {}.'.format(channel))
-                except RuntimeError:
+                except (RuntimeError, ValueError):
                     pass
 
     if loaded:

containers/dockerfile-template

@@ -13,17 +13,6 @@ RUN /bin/bash -c "source activate ${{conda_env}}"
 RUN mamba info
 RUN python --version
 
-# Install Polychord
-RUN apt-get update --allow-releaseinfo-change
-RUN apt-get install -y build-essential
-RUN apt-get install -y libblas3 libblas-dev
-RUN apt-get install -y liblapack3 liblapack-dev
-RUN apt-get install -y libatlas3-base libatlas-base-dev
-RUN apt-get install -y gfortran
-
-RUN git clone https://github.com/PolyChord/PolyChordLite.git \
-&& (cd PolyChordLite && python setup.py --no-mpi install)
-
 # Add the ROQ data to the image
 RUN mkdir roq_basis \
     && cd roq_basis \

containers/env-template.yml

@@ -6,6 +6,7 @@ channels:
 dependencies:
   - pip
   - setuptools
+  - setuptools_scm
   - matplotlib
   - numpy
   - scipy
@@ -57,5 +58,15 @@ dependencies:
   - jaxlib>=0.4
   - jax>=0.4
   - numba>0.53.1
+  - make
+  - pre-commit
+  - pandoc
+  - ipython
+  - jupyter
+  - nbconvert
+  - twine
   - pip:
     - autodoc
+    - ipykernel
+    - build
+    - nflows

containers/v3-dockerfile-test-suite-python310

@@ -15,17 +15,6 @@ RUN /bin/bash -c "source activate ${conda_env}"
 RUN mamba info
 RUN python --version
 
-# Install Polychord
-RUN apt-get update --allow-releaseinfo-change
-RUN apt-get install -y build-essential
-RUN apt-get install -y libblas3 libblas-dev
-RUN apt-get install -y liblapack3 liblapack-dev
-RUN apt-get install -y libatlas3-base libatlas-base-dev
-RUN apt-get install -y gfortran
-
-RUN git clone https://github.com/PolyChord/PolyChordLite.git \
-&& (cd PolyChordLite && python setup.py --no-mpi install)
-
 # Add the ROQ data to the image
 RUN mkdir roq_basis \
     && cd roq_basis \

containers/v3-dockerfile-test-suite-python311

+# This dockerfile is written automatically and should not be modified by hand.
+
+FROM containers.ligo.org/docker/base:conda
+LABEL name="bilby CI testing" \
+maintainer="Gregory Ashton <gregory.ashton@ligo.org>, Colm Talbot <colm.talbot@ligo.org>"
+
+COPY env-template.yml env.yml
+RUN echo "  - python==3.11" >> env.yml
+ENV conda_env python311
+
+RUN mamba env create -f env.yml -n ${conda_env}
+RUN echo "source activate ${conda_env}" > ~/.bashrc
+ENV PATH /opt/conda/envs/${conda_env}/bin:$PATH
+RUN /bin/bash -c "source activate ${conda_env}"
+RUN mamba info
+RUN python --version
+
+# Add the ROQ data to the image
+RUN mkdir roq_basis \
+    && cd roq_basis \
+    && wget https://git.ligo.org/lscsoft/ROQ_data/raw/master/IMRPhenomPv2/4s/B_linear.npy \
+    && wget https://git.ligo.org/lscsoft/ROQ_data/raw/master/IMRPhenomPv2/4s/B_quadratic.npy \
+    && wget https://git.ligo.org/lscsoft/ROQ_data/raw/master/IMRPhenomPv2/4s/fnodes_linear.npy \
+    && wget https://git.ligo.org/lscsoft/ROQ_data/raw/master/IMRPhenomPv2/4s/fnodes_quadratic.npy \
+    && wget https://git.ligo.org/lscsoft/ROQ_data/raw/master/IMRPhenomPv2/4s/params.dat \
+    && wget https://git.ligo.org/soichiro.morisaki/roq_basis/raw/main/IMRPhenomD/16s_nospins/basis_addcal.hdf5 \
+    && wget https://git.ligo.org/soichiro.morisaki/roq_basis/raw/main/IMRPhenomD/16s_nospins/basis_multiband_addcal.hdf5

containers/v3-dockerfile-test-suite-python39

@@ -15,17 +15,6 @@ RUN /bin/bash -c "source activate ${conda_env}"
 RUN mamba info
 RUN python --version
 
-# Install Polychord
-RUN apt-get update --allow-releaseinfo-change
-RUN apt-get install -y build-essential
-RUN apt-get install -y libblas3 libblas-dev
-RUN apt-get install -y liblapack3 liblapack-dev
-RUN apt-get install -y libatlas3-base libatlas-base-dev
-RUN apt-get install -y gfortran
-
-RUN git clone https://github.com/PolyChord/PolyChordLite.git \
-&& (cd PolyChordLite && python setup.py --no-mpi install)
-
 # Add the ROQ data to the image
 RUN mkdir roq_basis \
     && cd roq_basis \

containers/write_dockerfiles.py

@@ -3,7 +3,7 @@ from datetime import date
 with open("dockerfile-template", "r") as ff:
     template = ff.read()
 
-python_versions = [(3, 9), (3, 10)]
+python_versions = [(3, 9), (3, 10), (3, 11)]
 today = date.today().strftime("%Y%m%d")
 
 for python_major_version, python_minor_version in python_versions:

docs/dynesty-guide.txt

@@ -37,8 +37,8 @@ new point from the constrained prior. These can be specified using the
    iterations of :code:`dynesty`. With this method, :code:`nact=2` often gives good
    results, however, in some cases, a larger value may be required.
 
-2. :code:`sample="acceptance-walk"`: with this method, the length of each MCMC
-   chain is predetermined. The specific length evolves during the run to yield an
+2. :code:`sample="acceptance-walk"`: with this method, at each iteration all MCMC chains
+   are set to the same length. The specific length evolves during the run to yield an
    average of :code:`naccept` accepted jumps during each chain. This method is well
    suited to parallelised applications, as each MCMC chain will run for the same
    amount of time. The value of :code:`naccept` should be tuned based on the

docs/installation.txt

@@ -10,7 +10,7 @@ Installation
 
           $ conda install -c conda-forge bilby
 
-      Supported python versions: 3.8-3.10.
+      Supported python versions: 3.9-3.11.
 
    .. tab:: Pip
 
@@ -18,7 +18,7 @@ Installation
 
           $ pip install bilby
 
-      Supported python versions: 3.8-3.10.
+      Supported python versions: 3.9-3.11.
 
 
 This will install all requirements for running :code:`bilby` for general
@@ -47,7 +47,7 @@ wave inference, please additionally run the following commands.
 Install bilby from source
 -------------------------
 
-:code:`bilby` is developed and tested with Python 3.8-3.10. In the
+:code:`bilby` is developed and tested with Python 3.9-3.11. In the
 following, we assume you have a working python installation, `python pip
 <https://packaging.python.org/tutorials/installing-packages/#use-pip-for-installing)>`_,
 and `git <https://git-scm.com/>`_. See :ref:`installing-python` for our

setup.py

@@ -66,7 +66,7 @@ setup(
         "bilby.gw.detector": ["noise_curves/*.txt", "detectors/*"],
         "bilby.gw.eos": ["eos_tables/*.dat"],
     },
-    python_requires=">=3.8",
+    python_requires=">=3.9",
     install_requires=get_requirements(),
     extras_require={
         "gw": get_requirements("gw"),
@@ -87,6 +87,7 @@ setup(
     classifiers=[
         "Programming Language :: Python :: 3.9",
         "Programming Language :: Python :: 3.10",
+        "Programming Language :: Python :: 3.11",
         "License :: OSI Approved :: MIT License",
         "Operating System :: OS Independent",
     ],

test/core/prior/conditional_test.py

@@ -5,6 +5,7 @@ from unittest import mock
 
 import numpy as np
 import pandas as pd
+import pickle
 
 import bilby
 
@@ -472,6 +473,10 @@ class TestDirichletPrior(unittest.TestCase):
         test = bilby.core.prior.PriorDict.from_json(filename="priors/test_prior.json")
         self.assertEqual(self.priors, test)
 
+    def test_pickle(self):
+        """Assert can be pickled (needed for use with bilby_pipe)"""
+        pickle.dumps(self.priors)
+
 
 if __name__ == "__main__":
     unittest.main()

test/core/result_test.py

@@ -751,5 +751,71 @@ class TestPPPlots(unittest.TestCase):
             )
 
 
+class SimpleGaussianLikelihood(bilby.core.likelihood.Likelihood):
+    def __init__(self, mean=0, sigma=1):
+        """
+        A very simple Gaussian likelihood for testing
+        """
+        from scipy.stats import norm
+        super().__init__(parameters=dict())
+        self.mean = mean
+        self.sigma = sigma
+        self.dist = norm(loc=mean, scale=sigma)
+
+    def log_likelihood(self):
+        return self.dist.logpdf(self.parameters["mu"])
+
+
+class TestReweight(unittest.TestCase):
+
+    def setUp(self):
+        self.priors = bilby.core.prior.PriorDict(dict(
+            mu=bilby.core.prior.TruncatedNormal(0, 1, minimum=-5, maximum=5),
+        ))
+        self.result = bilby.core.result.Result(
+            search_parameter_keys=list(self.priors.keys()),
+            priors=self.priors,
+            posterior=pd.DataFrame(self.priors.sample(1000)),
+            log_evidence=-np.log(10),
+        )
+
+    def _run_reweighting(self, sigma):
+        likelihood_1 = SimpleGaussianLikelihood()
+        likelihood_2 = SimpleGaussianLikelihood(sigma=sigma)
+        original_ln_likelihoods = list()
+        for ii in range(len(self.result.posterior)):
+            likelihood_1.parameters = self.result.posterior.iloc[ii]
+            original_ln_likelihoods.append(likelihood_1.log_likelihood())
+        self.result.posterior["log_prior"] = self.priors.ln_prob(self.result.posterior)
+        self.result.posterior["log_likelihood"] = original_ln_likelihoods
+        self.original_ln_likelihoods = original_ln_likelihoods
+        return bilby.core.result.reweight(
+            self.result, likelihood_1, likelihood_2, verbose_output=True
+        )
+
+    def test_reweight_same_likelihood_weights_1(self):
+        """
+        When the likelihoods are the same, the weights should be 1.
+        """
+        _, weights, _, _, _, _ = self._run_reweighting(sigma=1)
+        self.assertLess(min(abs(weights - 1)), 1e-10)
+
+    def test_reweight_different_likelihood_weights_correct(self):
+        """
+        Test the known case where the target likelihood is a Gaussian with
+        sigma=0.5. The weights can be calculated analytically and the evidence
+        should be close to the original evidence within statistical error.
+        """
+        from scipy.stats import norm
+        new, weights, _, _, _, _ = self._run_reweighting(sigma=0.5)
+        expected_weights = (
+            norm(0, 0.5).pdf(self.result.posterior["mu"])
+            / norm(0, 1).pdf(self.result.posterior["mu"])
+        )
+        self.assertLess(min(abs(weights - expected_weights)), 1e-10)
+        self.assertLess(abs(new.log_evidence - self.result.log_evidence), 0.05)
+        self.assertNotEqual(new.log_evidence, self.result.log_evidence)
+
+
 if __name__ == "__main__":
     unittest.main()

test/core/sampler/dynesty_test.py

@@ -7,6 +7,7 @@ import numpy as np
 import parameterized
 from bilby.core.sampler import dynesty_utils
 from scipy.stats import gamma, ks_1samp, uniform, powerlaw
+import shutil
 
 
 @define
@@ -271,5 +272,78 @@ class TestEstimateNMCMC(unittest.TestCase):
             self.assertAlmostEqual(estimated, expected)
 
 
+class TestReproducibility(unittest.TestCase):
+
+    @staticmethod
+    def model(x, m, c):
+        return m * x + c
+
+    def setUp(self):
+        bilby.core.utils.random.seed(42)
+        bilby.core.utils.command_line_args.bilby_test_mode = False
+        rng = bilby.core.utils.random.rng
+        self.x = np.linspace(0, 1, 11)
+        self.injection_parameters = dict(m=0.5, c=0.2)
+        self.sigma = 0.1
+        self.y = self.model(self.x, **self.injection_parameters) + rng.normal(
+            0, self.sigma, len(self.x)
+        )
+        self.likelihood = bilby.likelihood.GaussianLikelihood(
+            self.x, self.y, self.model, self.sigma
+        )
+
+        self.priors = bilby.core.prior.PriorDict()
+        self.priors["m"] = bilby.core.prior.Uniform(0, 5, boundary="periodic")
+        self.priors["c"] = bilby.core.prior.Uniform(-2, 2, boundary="reflective")
+        # Evaluate prior once to ensure normalization constant have been set
+        theta = self.priors.sample()
+        self.priors.ln_prob(theta)
+        self._remove_tree()
+        bilby.core.utils.check_directory_exists_and_if_not_mkdir("outdir")
+
+    def tearDown(self):
+        del self.likelihood
+        del self.priors
+        bilby.core.utils.command_line_args.bilby_test_mode = False
+        self._remove_tree()
+
+    def _remove_tree(self):
+        try:
+            shutil.rmtree("outdir")
+        except OSError:
+            pass
+
+    def _run_sampler(self, **kwargs):
+        bilby.core.utils.random.seed(42)
+        return bilby.run_sampler(
+            likelihood=self.likelihood,
+            priors=self.priors,
+            sampler="dynesty",
+            save=False,
+            resume=False,
+            dlogz=1.0,
+            nlive=20,
+            **kwargs,
+        )
+
+    def test_reproducibility_seed(self):
+        res0 = self._run_sampler(seed=1234)
+        res1 = self._run_sampler(seed=1234)
+        assert res0.log_evidence == res1.log_evidence
+
+    def test_reproducibility_state(self):
+        rstate = np.random.default_rng(1234)
+        res0 = self._run_sampler(rstate=rstate)
+        rstate = np.random.default_rng(1234)
+        res1 = self._run_sampler(rstate=rstate)
+        assert res0.log_evidence == res1.log_evidence
+
+    def test_reproducibility_state_and_seed(self):
+        rstate = np.random.default_rng(1234)
+        res0 = self._run_sampler(rstate=rstate)
+        res1 = self._run_sampler(seed=1234)
+        assert res0.log_evidence == res1.log_evidence
+
+
 if __name__ == "__main__":
     unittest.main()