Rename sampling_parameter_keys -> non_standard_sampling_parameter_keys

examples/injection_examples/change_sampled_parameters.py

@@ -26,7 +26,7 @@ waveform_generator = tupak.waveform_generator.WaveformGenerator(
     sampling_frequency=sampling_frequency, time_duration=time_duration,
     frequency_domain_source_model=tupak.source.lal_binary_black_hole,
     parameter_conversion=tupak.conversion.convert_to_lal_binary_black_hole_parameters,
-    sampling_parameter_keys=['chirp_mass', 'mass_ratio', 'cos_iota'],
+    non_standard_sampling_parameter_keys=['chirp_mass', 'mass_ratio', 'cos_iota'],
     parameters=injection_parameters)
 hf_signal = waveform_generator.frequency_domain_strain()
 

tupak/conversion.py

@@ -215,7 +215,7 @@ def compute_snrs(sample, likelihood):
             for ii in range(len(temp_sample)):
                 for key in set(temp_sample.keys()).intersection(likelihood.waveform_generator.parameters.keys()):
                     likelihood.waveform_generator.parameters[key] = temp_sample[key][ii]
-                for key in likelihood.waveform_generator.sampling_parameter_keys:
+                for key in likelihood.waveform_generator.non_standard_sampling_parameter_keys:
                     likelihood.waveform_generator.parameters[key] = temp_sample[key][ii]
                 signal_polarizations = likelihood.waveform_generator.frequency_domain_strain()
                 for interferometer in all_interferometers:

tupak/likelihood.py

@@ -18,7 +18,7 @@ class Likelihood(object):
         self.interferometers = interferometers
         self.waveform_generator = waveform_generator
         self.parameters = self.waveform_generator.parameters
-        self.sampling_parameter_keys = self.waveform_generator.sampling_parameter_keys
+        self.non_standard_sampling_parameter_keys = self.waveform_generator.non_standard_sampling_parameter_keys
         self.distance_marginalization = distance_marginalization
         self.phase_marginalization = phase_marginalization
         self.prior = prior

tupak/sampler.py

@@ -444,7 +444,7 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
 
     if priors is None:
         priors = dict()
-    priors = fill_priors(priors, likelihood, parameters=likelihood.sampling_parameter_keys)
+    priors = fill_priors(priors, likelihood, parameters=likelihood.non_standard_sampling_parameter_keys)
     tupak.prior.write_priors_to_file(priors, outdir)
 
     if implemented_samplers.__contains__(sampler.title()):

tupak/waveform_generator.py

@@ -25,7 +25,7 @@ class WaveformGenerator(object):
         Initial values for the parameters
     parameter_conversion: func
         Function to convert from sampled parameters to parameters of the waveform generator
-    sampling_parameter_keys: list
+    non_standard_sampling_parameter_keys: list
         List of parameter name for *non-standard* sampling parameters.
 
     Note: the arguments of frequency_domain_source_model (except the first, which is the
@@ -35,7 +35,7 @@ class WaveformGenerator(object):
 
     def __init__(self, time_duration, sampling_frequency, frequency_domain_source_model=None,
                  time_domain_source_model=None, parameters=None, parameter_conversion=None,
-                 sampling_parameter_keys=None):
+                 non_standard_sampling_parameter_keys=None):
         self.time_duration = time_duration
         self.sampling_frequency = sampling_frequency
         self.frequency_domain_source_model = frequency_domain_source_model
@@ -43,7 +43,7 @@ class WaveformGenerator(object):
         self.time_duration = time_duration
         self.sampling_frequency = sampling_frequency
         self.parameter_conversion = parameter_conversion
-        self.sampling_parameter_keys = sampling_parameter_keys
+        self.non_standard_sampling_parameter_keys = non_standard_sampling_parameter_keys
         self.parameters = parameters
         self.__frequency_array_updated = False
         self.__time_array_updated = False
@@ -51,7 +51,7 @@ class WaveformGenerator(object):
     def frequency_domain_strain(self):
         """ Wrapper to source_model """
         if self.parameter_conversion is not None:
-            added_keys = self.parameter_conversion(self.parameters, self.sampling_parameter_keys)
+            added_keys = self.parameter_conversion(self.parameters, self.non_standard_sampling_parameter_keys)
             
         if self.frequency_domain_source_model is not None:
             model_frequency_strain = self.frequency_domain_source_model(self.frequency_array, **self.parameters)
@@ -72,7 +72,7 @@ class WaveformGenerator(object):
 
     def time_domain_strain(self):
         if self.parameter_conversion is not None:
-            added_keys = self.parameter_conversion(self.parameters, self.sampling_parameter_keys)
+            added_keys = self.parameter_conversion(self.parameters, self.non_standard_sampling_parameter_keys)
         if self.time_domain_source_model is not None:
             model_time_series = self.time_domain_source_model(self.time_array, **self.parameters)
         elif self.frequency_domain_source_model is not None: