From 2f3ca036795a0373a23a9d6a28f7c4eb632fd415 Mon Sep 17 00:00:00 2001
From: MoritzThomasHuebner <email@moritz-huebner.de>
Date: Fri, 7 Sep 2018 17:26:29 +1000
Subject: [PATCH] Added tests for the JointLikelihood
---
test/likelihood_tests.py | 77 ++++++++++++++++++++++++++++++++++++++++
1 file changed, 77 insertions(+)
diff --git a/test/likelihood_tests.py b/test/likelihood_tests.py
index a3d6da004..568832710 100644
--- a/test/likelihood_tests.py
+++ b/test/likelihood_tests.py
@@ -99,6 +99,7 @@ class TestAnalytical1DLikelihood(unittest.TestCase):
def test_set_func(self):
def new_func(x):
return x
+
with self.assertRaises(AttributeError):
# noinspection PyPropertyAccess
self.analytical_1d_likelihood.func = new_func
@@ -443,5 +444,81 @@ class TestExponentialLikelihood(unittest.TestCase):
self.assertEqual(-3, exponential_likelihood.log_likelihood())
+class TestJointLikelihood(unittest.TestCase):
+
+ def setUp(self):
+ self.x = np.array([1, 2, 3])
+ self.y = np.array([1, 2, 3])
+ self.first_likelihood = tupak.core.likelihood.GaussianLikelihood(
+ x=self.x,
+ y=self.y,
+ func=lambda x, param1, param2: (param1 + param2) * x,
+ sigma=1)
+ self.second_likelihood = tupak.core.likelihood.PoissonLikelihood(
+ x=self.x,
+ y=self.y,
+ func=lambda x, param2, param3: (param2 + param3) * x)
+ self.third_likelihood = tupak.core.likelihood.ExponentialLikelihood(
+ x=self.x,
+ y=self.y,
+ func=lambda x, param4, param5: (param4 + param5) * x
+ )
+ self.joint_likelihood = tupak.core.likelihood.JointLikelihood(self.first_likelihood,
+ self.second_likelihood,
+ self.third_likelihood)
+
+ self.first_likelihood.parameters['param1'] = 1
+ self.first_likelihood.parameters['param2'] = 2
+ self.second_likelihood.parameters['param2'] = 2
+ self.second_likelihood.parameters['param3'] = 3
+ self.third_likelihood.parameters['param4'] = 4
+ self.third_likelihood.parameters['param5'] = 5
+
+ self.joint_likelihood.parameters['param1'] = 1
+ self.joint_likelihood.parameters['param2'] = 2
+ self.joint_likelihood.parameters['param3'] = 3
+ self.joint_likelihood.parameters['param4'] = 4
+ self.joint_likelihood.parameters['param5'] = 5
+
+ def tearDown(self):
+ del self.x
+ del self.y
+ del self.first_likelihood
+ del self.second_likelihood
+ del self.third_likelihood
+ del self.joint_likelihood
+
+ def test_parameters_consistent_from_init(self):
+ expected = dict(param1=1, param2=2, param3=3, param4=4, param5=5, )
+ self.assertDictEqual(expected, self.joint_likelihood.parameters)
+
+ def test_log_likelihood_correctly_sums(self):
+ expected = self.first_likelihood.log_likelihood() + \
+ self.second_likelihood.log_likelihood() + \
+ self.third_likelihood.log_likelihood()
+ self.assertEqual(expected, self.joint_likelihood.log_likelihood())
+
+ def test_log_likelihood_checks_parameter_updates(self):
+ self.first_likelihood.parameters['param2'] = 7
+ self.second_likelihood.parameters['param2'] = 7
+ self.joint_likelihood.parameters['param2'] = 7
+ expected = self.first_likelihood.log_likelihood() + \
+ self.second_likelihood.log_likelihood() + \
+ self.third_likelihood.log_likelihood()
+ self.assertEqual(expected, self.joint_likelihood.log_likelihood())
+
+ def test_log_noise_likelihood(self):
+ self.first_likelihood.noise_log_likelihood = MagicMock(return_value=1)
+ self.second_likelihood.noise_log_likelihood = MagicMock(return_value=2)
+ self.third_likelihood.noise_log_likelihood = MagicMock(return_value=3)
+ self.joint_likelihood = tupak.core.likelihood.JointLikelihood(self.first_likelihood,
+ self.second_likelihood,
+ self.third_likelihood)
+ expected = self.first_likelihood.noise_log_likelihood() + \
+ self.second_likelihood.noise_log_likelihood() + \
+ self.third_likelihood.noise_log_likelihood()
+ self.assertEqual(expected, self.joint_likelihood.noise_log_likelihood())
+
+
if __name__ == '__main__':
unittest.main()
--
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