Continued refactoring

tupak/gw/waveform_generator.py

@@ -78,29 +78,30 @@ class WaveformGenerator(object):
         RuntimeError: If no source model is given
 
         """
-        model_strain = None
-        added_keys = self._setup_conversion()
 
-        preferred_model = self.frequency_domain_source_model
-        preferred_model_data_points = self.frequency_array
-        alternative_model = self.time_domain_source_model
-        alternative_model_data_points = self.time_array
+        model = self.frequency_domain_source_model
+        model_data_points = self.frequency_array
+        transformed_model = self.time_domain_source_model
+        transformed_model_data_points = self.time_array
+        transformation_function = utils.nfft
+        added_keys = self._setup_conversion()
 
-        if preferred_model is not None:
+        model_strain = None
+        if model is not None:
             self.__full_source_model_keyword_arguments.update(self.parameters)
-            model_strain = preferred_model(
-                preferred_model_data_points,
+            model_strain = model(
+                model_data_points,
                 **self.__full_source_model_keyword_arguments)
-        elif alternative_model is not None:
+        elif transformed_model is not None:
             model_strain = dict()
             self.__full_source_model_keyword_arguments.update(self.parameters)
-            time_domain_strain = alternative_model(
-                alternative_model_data_points, **self.__full_source_model_keyword_arguments)
-            if isinstance(time_domain_strain, np.ndarray):
-                return utils.nfft(time_domain_strain, self.sampling_frequency)
-            for key in time_domain_strain:
-                model_strain[key], self.frequency_array = utils.nfft(time_domain_strain[key],
-                                                                               self.sampling_frequency)
+            transformed_model_strain = transformed_model(
+                transformed_model_data_points, **self.__full_source_model_keyword_arguments)
+            if isinstance(transformed_model_strain, np.ndarray):
+                return transformation_function(transformed_model_strain, self.sampling_frequency)
+            for key in transformed_model_strain:
+                model_strain[key], self.frequency_array = transformation_function(transformed_model_strain[key],
+                                                                                  self.sampling_frequency)
         else:
             raise RuntimeError("No source model given")
 
@@ -131,27 +132,28 @@ class WaveformGenerator(object):
         RuntimeError: If no source model is given
 
         """
-        model_strain = None
-        added_keys = self._setup_conversion()
 
-        preferred_model = self.time_domain_source_model
-        preferred_model_data_points = self.time_array
-        alternative_model = self.frequency_domain_source_model
-        alternative_model_data_points = self.frequency_array
+        model = self.time_domain_source_model
+        model_data_points = self.time_array
+        transformed_model = self.frequency_domain_source_model
+        transformed_model_data_points = self.frequency_array
+        transformation_function = utils.infft
+        added_keys = self._setup_conversion()
 
-        if preferred_model is not None:
+        model_strain = None
+        if model is not None:
             self.__full_source_model_keyword_arguments.update(self.parameters)
-            model_strain = preferred_model(
-                preferred_model_data_points, **self.__full_source_model_keyword_arguments)
-        elif alternative_model is not None:
+            model_strain = model(
+                model_data_points, **self.__full_source_model_keyword_arguments)
+        elif transformed_model is not None:
             model_strain = dict()
             self.__full_source_model_keyword_arguments.update(self.parameters)
-            frequency_domain_strain = alternative_model(
-                alternative_model_data_points, **self.__full_source_model_keyword_arguments)
-            if isinstance(frequency_domain_strain, np.ndarray):
-                return utils.infft(frequency_domain_strain, self.sampling_frequency)
-            for key in frequency_domain_strain:
-                model_strain[key] = utils.infft(frequency_domain_strain[key], self.sampling_frequency)
+            transformed_model_strain = transformed_model(
+                transformed_model_data_points, **self.__full_source_model_keyword_arguments)
+            if isinstance(transformed_model_strain, np.ndarray):
+                return transformation_function(transformed_model_strain, self.sampling_frequency)
+            for key in transformed_model_strain:
+                model_strain[key] = transformation_function(transformed_model_strain[key], self.sampling_frequency)
         else:
             raise RuntimeError("No source model given")
 
@@ -169,8 +171,8 @@ class WaveformGenerator(object):
         """
         if self.__frequency_array_updated is False:
             self.frequency_array = utils.create_frequency_series(
-                                        self.sampling_frequency,
-                                        self.duration)
+                self.sampling_frequency,
+                self.duration)
         return self.__frequency_array
 
     @frequency_array.setter
@@ -189,9 +191,9 @@ class WaveformGenerator(object):
 
         if self.__time_array_updated is False:
             self.__time_array = utils.create_time_series(
-                                        self.sampling_frequency,
-                                        self.duration,
-                                        self.start_time)
+                self.sampling_frequency,
+                self.duration,
+                self.start_time)
 
             self.__time_array_updated = True
         return self.__time_array