Simplified some more

tupak/gw/waveform_generator.py

@@ -122,15 +122,16 @@ class WaveformGenerator(object):
 
     def _strain_from_model(self, model_data_points, model):
         self.__full_source_model_keyword_arguments.update(self.parameters)
-        return model(model_data_points, **self.__full_source_model_keyword_arguments)
+        strain = model(model_data_points, **self.__full_source_model_keyword_arguments)
+        if isinstance(strain, np.ndarray):
+            return strain
+        else:
+            raise TypeError("The model return value should be of type numpy.ndarray, but actually was {}"
+                            .format(type(transformed_model_strain)))
 
     def _strain_from_transformed_model(self, transformed_model_data_points, transformed_model, transformation_function):
         transformed_model_strain = self._strain_from_model(transformed_model_data_points, transformed_model)
-        if isinstance(transformed_model_strain, np.ndarray):
-            model_strain = transformation_function(transformed_model_strain, self.sampling_frequency)
-        else:
-            raise TypeError("Strain should be of tupe numpy.ndarray, but actually was {}"
-                            .format(type(transformed_model_strain)))
+        model_strain = transformation_function(transformed_model_strain, self.sampling_frequency)
         for key in transformed_model_strain:
             if transformation_function == utils.nfft:
                 model_strain[key], self.frequency_array = \