Remove obsolete likelihood

tupak/likelihood.py

@@ -136,39 +136,6 @@ class GravitationalWaveTransient(object):
                                                  bounds_error=False, fill_value=-np.inf)
 
 
-class BasicGravitationalWaveTransient(object):
-    def __init__(self, interferometers, waveform_generator):
-        self.interferometers = interferometers
-        self.waveform_generator = waveform_generator
-
-    def noise_log_likelihood(self):
-        log_l = 0
-        for interferometer in self.interferometers:
-            log_l -= 2. / self.waveform_generator.time_duration * np.sum(
-                abs(interferometer.data) ** 2 / interferometer.power_spectral_density_array)
-        return log_l.real
-
-    def log_likelihood(self):
-        log_l = 0
-        waveform_polarizations = self.waveform_generator.frequency_domain_strain()
-        if waveform_polarizations is None:
-            return np.nan_to_num(-np.inf)
-        for interferometer in self.interferometers:
-            log_l += self.log_likelihood_interferometer(waveform_polarizations, interferometer)
-        return log_l.real
-
-    def log_likelihood_interferometer(self, waveform_polarizations, interferometer):
-        signal_ifo = interferometer.get_detector_response(waveform_polarizations, self.waveform_generator.parameters)
-
-        log_l = - 2. / self.waveform_generator.time_duration * np.vdot(interferometer.data - signal_ifo,
-                                                                       (interferometer.data - signal_ifo)
-                                                                       / interferometer.power_spectral_density_array)
-        return log_l.real
-
-    def log_likelihood_ratio(self):
-        return self.log_likelihood() - self.noise_log_likelihood()
-
-
 def get_binary_black_hole_likelihood(interferometers):
     """ A rapper to quickly set up a likelihood for BBH parameter estimation
 
@@ -190,4 +157,3 @@ def get_binary_black_hole_likelihood(interferometers):
         parameters={'waveform_approximant': 'IMRPhenomPv2', 'reference_frequency': 50})
     likelihood = tupak.likelihood.GravitationalWaveTransient(interferometers, waveform_generator)
     return likelihood
-