Merge branch 'master' into 'calibration'

# Conflicts:
#   examples/open_data_examples/GW150914.py

.gitlab-ci.yml

@@ -13,8 +13,21 @@ stages:
   - test
   - deploy
 
-# test example on Debian 8 "jessie"
-exitcode-jessie:
+# test example on python 2
+python-2:
+  stage: test
+  image: continuumio/anaconda
+  before_script:
+    - apt install -y libgl1-mesa-glx
+    - pip install -r requirements.txt
+    - pip install lalsuite enum gwpy
+  script:
+    - python setup.py install
+    # Run tests without finding coverage
+    - for test in test/*tests.py; do python $test; done
+
+# test example on python 3
+python-3:
   stage: test
   image: continuumio/anaconda3
   before_script:
@@ -58,7 +71,8 @@ exitcode-jessie:
 pages:
   stage: deploy
   dependencies:
-    - exitcode-jessie
+    - python-3
+    - python-2
   script:
     - mkdir public/
     - mv htmlcov/ public/

examples/injection_examples/marginalized_likelihood.py

@@ -44,7 +44,8 @@ for key in ['a_1', 'a_2', 'tilt_1', 'tilt_2', 'phi_12', 'phi_jl', 'iota', 'ra',
 # This is still under development so care should be taken with the marginalised likelihood.
 likelihood = tupak.gw.GravitationalWaveTransient(
     interferometers=IFOs, waveform_generator=waveform_generator, prior=priors,
-    distance_marginalization=True, phase_marginalization=False)
+    distance_marginalization=False, phase_marginalization=True,
+    time_marginalization=False)
 
 # Run sampler
 result = tupak.run_sampler(likelihood=likelihood, priors=priors, sampler='dynesty',

test/make_standard_data.py

@@ -32,16 +32,17 @@ simulation_parameters = dict(
     psi=2.659
 )
 
-waveform_generator = WaveformGenerator(time_duration=time_duration, sampling_frequency=sampling_frequency,
-                                       frequency_domain_source_model=tupak.gw.source.lal_binary_black_hole,
-                                       parameters=simulation_parameters)
+waveform_generator = WaveformGenerator(
+    duration=time_duration, sampling_frequency=sampling_frequency,
+    frequency_domain_source_model=tupak.gw.source.lal_binary_black_hole,
+    parameters=simulation_parameters)
 
 signal = waveform_generator.frequency_domain_strain()
 
-IFO = tupak.gw.detector.get_interferometer_with_fake_noise_and_injection(name='H1', injection_polarizations=signal,
-                                                                         injection_parameters=simulation_parameters,
-                                                                         time_duration=time_duration, plot=False,
-                                                                         sampling_frequency=sampling_frequency)
+IFO = tupak.gw.detector.get_interferometer_with_fake_noise_and_injection(
+    name='H1', injection_polarizations=signal,
+    injection_parameters=simulation_parameters, duration=time_duration,
+    plot=False, sampling_frequency=sampling_frequency)
 
 hf_signal_and_noise = IFO.strain_data.frequency_domain_strain
 frequencies = tupak.core.utils.create_frequency_series(

test/other_tests.py

@@ -44,8 +44,11 @@ class Test(unittest.TestCase):
             self.dir_path + '/test/standard_data.txt').T
         hf_signal_and_noise_saved = hf_real_saved + 1j * hf_imag_saved
 
-        self.assertTrue(np.array_equal(self.msd['frequencies'], frequencies_saved))
-        self.assertAlmostEqual(all(self.msd['hf_signal_and_noise'] - hf_signal_and_noise_saved), 0.00000000, 5)
+        self.assertTrue(np.array_equal(
+            self.msd['frequencies'], frequencies_saved))
+        self.assertAlmostEqual(all(
+            self.msd['hf_signal_and_noise'] - hf_signal_and_noise_saved),
+            0.00000000, 5)
 
     def test_recover_luminosity_distance(self):
         likelihood = tupak.gw.likelihood.GravitationalWaveTransient(
@@ -61,8 +64,9 @@ class Test(unittest.TestCase):
 
         result = tupak.core.sampler.run_sampler(
             likelihood, priors, sampler='dynesty', verbose=False, npoints=100)
-        self.assertAlmostEqual(np.mean(result.samples), dL,
-                               delta=3*np.std(result.samples))
+        self.assertAlmostEqual(
+            np.mean(result.posterior.luminosity_distance), dL,
+            delta=3*np.std(result.posterior.luminosity_distance))
 
 
 if __name__ == '__main__':

tupak/core/prior.py

@@ -151,7 +151,7 @@ class PriorSet(dict):
         """
         return self.sample_subset(keys=self.keys(), size=size)
 
-    def sample_subset(self, keys=list(), size=None):
+    def sample_subset(self, keys=iter([]), size=None):
         """Draw samples from the prior set for parameters which are not a DeltaFunction
 
         Parameters
@@ -381,7 +381,7 @@ class Prior(object):
         """
         return self._subclass_repr_helper()
 
-    def _subclass_repr_helper(self, subclass_args=list()):
+    def _subclass_repr_helper(self, subclass_args=iter([])):
         """Helps out subclass _repr__ methods by creating a common template
 
         Parameters