Fix sampler tests

test/core/sampler/sampler_run_test.py

-import bilby
-import unittest
-import numpy as np
-import shutil
-
-
-class TestRunningSamplers(unittest.TestCase):
-    def setUp(self):
-        np.random.seed(42)
-        bilby.core.utils.command_line_args.bilby_test_mode = False
-        self.x = np.linspace(0, 1, 11)
-        self.model = lambda x, m, c: m * x + c
-        self.injection_parameters = dict(m=0.5, c=0.2)
-        self.sigma = 0.1
-        self.y = self.model(self.x, **self.injection_parameters) + np.random.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="reflective")
-        self.priors["c"] = bilby.core.prior.Uniform(-2, 2, boundary="reflective")
-        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
-        shutil.rmtree("outdir")
-
-    def test_run_cpnest(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="cpnest",
-            nlive=100,
-            save=False,
-            resume=False,
-        )
-
-    def test_run_dnest4(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="dnest4",
-            nlive=100,
-            save=False,
-        )
-
-    def test_run_dynesty(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="dynesty",
-            nlive=100,
-            save=False,
-        )
-
-    def test_run_dynamic_dynesty(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="dynamic_dynesty",
-            nlive_init=100,
-            nlive_batch=100,
-            dlogz_init=1.0,
-            maxbatch=0,
-            maxcall=100,
-            bound="single",
-            save=False,
-        )
-
-    def test_run_emcee(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="emcee",
-            iterations=1000,
-            nwalkers=10,
-            save=False,
-        )
-
-    def test_run_kombine(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="kombine",
-            iterations=1000,
-            nwalkers=100,
-            save=False,
-            autoburnin=True,
-        )
-
-    def test_run_nestle(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="nestle",
-            nlive=100,
-            save=False,
-        )
-
-    def test_run_pypolychord(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="pypolychord",
-            nlive=100,
-            save=False,
-        )
-
-    def test_run_ptemcee(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="ptemcee",
-            nsamples=100,
-            nwalkers=50,
-            burn_in_act=1,
-            ntemps=1,
-            frac_threshold=0.5,
-            save=False,
-        )
-
-    def test_run_pymc3(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="pymc3",
-            draws=50,
-            tune=50,
-            n_init=1000,
-            save=False,
-        )
-
-    def test_run_pymultinest(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="pymultinest",
-            nlive=100,
-            save=False,
-        )
-
-    def test_run_PTMCMCSampler(self):
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood,
-            priors=self.priors,
-            sampler="PTMCMCsampler",
-            Niter=101,
-            burn=2,
-            isave=100,
-            save=False,
-        )
-
-    def test_run_ultranest(self):
-        # run using NestedSampler (with nlive specified)
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood, priors=self.priors,
-            sampler="ultranest", nlive=100, save=False,
-        )
-
-        # run using ReactiveNestedSampler (with no nlive given)
-        _ = bilby.run_sampler(
-            likelihood=self.likelihood, priors=self.priors,
-            sampler='ultranest', save=False,
-        )
-
-
-if __name__ == "__main__":
-    unittest.main()

test/integration/sampler_run_test.py

@@ -40,6 +40,15 @@ class TestRunningSamplers(unittest.TestCase):
             resume=False,
         )
 
+    def test_run_dnest4(self):
+        _ = bilby.run_sampler(
+            likelihood=self.likelihood,
+            priors=self.priors,
+            sampler="dnest4",
+            nlive=100,
+            save=False,
+        )
+
     def test_run_dynesty(self):
         _ = bilby.run_sampler(
             likelihood=self.likelihood,