Merge branch 'Add_some_tests' into 'master'

Add some tests

See merge request Monash/tupak!193

test/likelihood_test.py

@@ -189,6 +189,12 @@ class TestGaussianLikelihood(unittest.TestCase):
         likelihood.log_likelihood()
         self.assertTrue(likelihood.sigma == 1)
 
+    def test_sigma_other(self):
+        likelihood = GaussianLikelihood(
+            self.x, self.y, self.function, sigma=None)
+        with self.assertRaises(ValueError):
+            likelihood.sigma = 'test'
+
     def test_repr(self):
         likelihood = GaussianLikelihood(
             self.x, self.y, self.function, sigma=self.sigma)
@@ -467,6 +473,10 @@ class TestExponentialLikelihood(unittest.TestCase):
             m.return_value = 3
             self.assertEqual(-3, exponential_likelihood.log_likelihood())
 
+    def test_repr(self):
+        expected = 'ExponentialLikelihood(x={}, y={}, func={})'.format(self.x, self.y, self.function.__name__)
+        self.assertEqual(expected, repr(self.exponential_likelihood))
+
 
 class TestJointLikelihood(unittest.TestCase):
 
@@ -554,6 +564,10 @@ class TestJointLikelihood(unittest.TestCase):
         self.joint_likelihood.likelihoods = self.first_likelihood
         self.assertEqual(self.first_likelihood.log_likelihood(), self.joint_likelihood.log_likelihood())
 
+    def test_setting_likelihood_other(self):
+        with self.assertRaises(ValueError):
+            self.joint_likelihood.likelihoods = 'test'
+
     # Appending is not supported
     # def test_appending(self):
     #     joint_likelihood = tupak.core.likelihood.JointLikelihood(self.first_likelihood, self.second_likelihood)

test/waveform_generator_test.py

@@ -47,6 +47,43 @@ class TestWaveformGeneratorInstantiationWithoutOptionalParameters(unittest.TestC
                     self.waveform_generator.waveform_arguments)
         self.assertEqual(expected, repr(self.waveform_generator))
 
+    def test_repr_with_time_domain_source_model(self):
+        self.waveform_generator = \
+            tupak.gw.waveform_generator.WaveformGenerator(1, 4096,
+                                                          time_domain_source_model=dummy_func_dict_return_value)
+        expected = 'WaveformGenerator(duration={}, sampling_frequency={}, start_time={}, ' \
+                   'frequency_domain_source_model={}, time_domain_source_model={}, parameters={}, ' \
+                   'parameter_conversion={}, non_standard_sampling_parameter_keys={}, waveform_arguments={})'\
+            .format(self.waveform_generator.duration,
+                    self.waveform_generator.sampling_frequency,
+                    self.waveform_generator.start_time,
+                    self.waveform_generator.frequency_domain_source_model,
+                    self.waveform_generator.time_domain_source_model.__name__,
+                    self.waveform_generator.parameters,
+                    None,
+                    self.waveform_generator.non_standard_sampling_parameter_keys,
+                    self.waveform_generator.waveform_arguments)
+        self.assertEqual(expected, repr(self.waveform_generator))
+
+    def test_repr_with_param_conversion(self):
+        def conversion_func():
+            pass
+
+        self.waveform_generator.parameter_conversion = conversion_func
+        expected = 'WaveformGenerator(duration={}, sampling_frequency={}, start_time={}, ' \
+                   'frequency_domain_source_model={}, time_domain_source_model={}, parameters={}, ' \
+                   'parameter_conversion={}, non_standard_sampling_parameter_keys={}, waveform_arguments={})'\
+            .format(self.waveform_generator.duration,
+                    self.waveform_generator.sampling_frequency,
+                    self.waveform_generator.start_time,
+                    self.waveform_generator.frequency_domain_source_model.__name__,
+                    self.waveform_generator.time_domain_source_model,
+                    self.waveform_generator.parameters,
+                    conversion_func.__name__,
+                    self.waveform_generator.non_standard_sampling_parameter_keys,
+                    self.waveform_generator.waveform_arguments)
+        self.assertEqual(expected, repr(self.waveform_generator))
+
     def test_duration(self):
         self.assertEqual(self.waveform_generator.duration, 1)
 
@@ -128,6 +165,16 @@ class TestSetters(unittest.TestCase):
         self.assertListEqual(sorted(list(self.waveform_generator.parameters.keys())),
                              sorted(list(self.simulation_parameters.keys())))
 
+    def test_set_parameter_conversion_at_init(self):
+        def conversion_func():
+            pass
+
+        self.waveform_generator = \
+            tupak.gw.waveform_generator.WaveformGenerator(1, 4096,
+                                                          frequency_domain_source_model=dummy_func_dict_return_value,
+                                                          parameter_conversion=conversion_func)
+        self.assertEqual(conversion_func, self.waveform_generator.parameter_conversion)
+
 
 class TestFrequencyDomainStrainMethod(unittest.TestCase):
 

tupak/gw/waveform_generator.py

@@ -75,7 +75,7 @@ class WaveformGenerator(object):
         else:
             fdsm_name = None
         if self.time_domain_source_model is not None:
-            tdsm_name = self.frequency_domain_source_model.__name__
+            tdsm_name = self.time_domain_source_model.__name__
         else:
             tdsm_name = None
         if self.parameter_conversion.__name__ == '<lambda>':