From cfc6973d8929d7205025a8ac1f5a3aed10d1e501 Mon Sep 17 00:00:00 2001
From: Moritz Huebner <email@moritz-huebner.de>
Date: Tue, 22 May 2018 18:58:20 +1000
Subject: [PATCH] Moritz Huebner: Added more tests for the Sampler class
---
test/sampler_tests.py | 131 ++++++++++++++++++++++++++++++++++++------
1 file changed, 114 insertions(+), 17 deletions(-)
diff --git a/test/sampler_tests.py b/test/sampler_tests.py
index 494d4a18b..44b93ba9e 100644
--- a/test/sampler_tests.py
+++ b/test/sampler_tests.py
@@ -1,33 +1,130 @@
from context import tupak
from tupak import prior
-from tupak import likelihood
+from tupak.result import Result
import unittest
-from mock import Mock, MagicMock
+from mock import MagicMock
import numpy as np
+import inspect
+import os
+import copy
class TestSamplerInstantiation(unittest.TestCase):
def setUp(self):
- self.likelihood = likelihood.Likelihood()
- self.likelihood.parameters = MagicMock(return_value=dict(a=1, b=2, c=3))
- delta_prior = prior.DeltaFunction(0)
- delta_prior.peak = MagicMock(return_value=0)
- delta_prior.rescale = MagicMock(return_value=delta_prior)
+ likelihood = tupak.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.minimum = MagicMock(return_value=0)
- uniform_prior.maximum = MagicMock(return_value=1)
- uniform_prior.rescale = MagicMock(return_value=uniform_prior)
+ 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)
- self.priors = dict(a=delta_prior, b='string', c=uniform_prior)
- self.likelihood.log_likelihood_ratio = MagicMock(return_value=1)
- self.likelihood.log_likelihood = MagicMock(return_value=2)
+ 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 = tupak.sampler.Sampler(likelihood=likelihood,
+ priors=priors,
+ external_sampler='nestle',
+ outdir=test_directory,
+ use_ratio=False)
def tearDown(self):
- del self.likelihood
- del self.priors
+ os.rmdir(self.sampler.outdir)
+ del self.sampler
- def test_default_instantiation(self):
- sampler = tupak.sampler.Sampler(self.likelihood, self.priors)
+ def test_search_parameter_keys(self):
+ expected_search_parameter_keys = ['c']
+ self.assertListEqual(self.sampler.search_parameter_keys, expected_search_parameter_keys)
+
+ def test_fixed_parameter_keys(self):
+ expected_fixed_parameter_keys = ['a']
+ self.assertListEqual(self.sampler.fixed_parameter_keys, expected_fixed_parameter_keys)
+
+ def test_ndim(self):
+ self.assertEqual(self.sampler.ndim, 1)
+
+ def test_kwargs(self):
+ self.assertDictEqual(self.sampler.kwargs, {})
+
+ def test_label(self):
+ self.assertEqual(self.sampler.label, 'label')
+
+ def test_if_external_sampler_is_module(self):
+ self.assertTrue(inspect.ismodule(self.sampler.external_sampler))
+
+ def test_if_external_sampler_has_the_correct_module_name(self):
+ expected_name = 'nestle'
+ self.assertEqual(self.sampler.external_sampler.__name__, expected_name)
+
+ def test_external_sampler_raises_if_sampler_not_installed(self):
+ with self.assertRaises(ImportError):
+ self.sampler.external_sampler = 'unexpected_sampler'
+
+ def test_setting_custom_sampler(self):
+ other_sampler = tupak.sampler.Sampler(self.sampler.likelihood,
+ self.sampler.priors)
+ self.sampler.external_sampler = other_sampler
+ self.assertEqual(self.sampler.external_sampler, other_sampler)
+
+ def test_setting_external_sampler_to_something_else_raises_error(self):
+ with self.assertRaises(TypeError):
+ self.sampler.external_sampler = object()
+
+ def test_result(self):
+ expected_result = Result()
+ expected_result.search_parameter_keys = ['c']
+ expected_result.fixed_parameter_keys = ['a']
+ expected_result.parameter_labels = ['c']
+ expected_result.label = 'label'
+ expected_result.outdir = 'outdir'
+ expected_result.kwargs = {}
+ self.assertDictEqual(self.sampler.result.__dict__, expected_result.__dict__)
+
+ def test_make_outdir_if_no_outdir_exists(self):
+ self.assertTrue(os.path.isdir(self.sampler.outdir))
+
+ 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 test_prior_transform_does_not_transform_fixed_parameter_keys(self):
+ self.sampler.prior_transform([0])
+ self.assertEqual(self.sampler.priors['a'].peak,
+ prior.DeltaFunction(peak=0).peak)
+
+ def test_log_prior(self):
+ self.assertEqual(self.sampler.log_prior({1}), 0.0)
+
+ def test_log_likelihood_with_use_ratio(self):
+ self.sampler.use_ratio = True
+ self.assertEqual(self.sampler.log_likelihood([0]), 1)
+
+ def test_log_likelihood_without_use_ratio(self):
+ self.sampler.use_ratio = False
+ self.assertEqual(self.sampler.log_likelihood([0]), 2)
+
+ def test_log_likelihood_correctly_sets_parameters(self):
+ expected_dict = dict(a=0,
+ b=2,
+ c=0)
+ _ = self.sampler.log_likelihood([0])
+ self.assertDictEqual(self.sampler.likelihood.parameters, expected_dict)
+
+ def test_get_random_draw(self):
+ self.assertEqual(self.sampler.get_random_draw_from_prior(), np.array([0.5]))
+
+ def test_base_run_sampler(self):
+ sampler_copy = copy.copy(self.sampler)
+ self.sampler.run_sampler()
+ self.assertDictEqual(sampler_copy.__dict__, self.sampler.__dict__)
\ No newline at end of file
--
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