diff --git a/tupak/result.py b/tupak/result.py
index 1c803bfbc4253553eeb7fbed8485dad3ac0bde43..2d01627d83a0e4fc9c5a57732ff3d88a481e36a0 100644
--- a/tupak/result.py
+++ b/tupak/result.py
@@ -205,21 +205,23 @@ class Result(dict):
             for key in self.prior:
                 prior_file.write(self.prior[key])
 
-    def samples_to_data_frame(self, waveform_generator=None, interferometers=None, priors=None):
+    def samples_to_data_frame(self, likelihood=None, priors=None, conversion_function=None):
         """
         Convert array of samples to data frame.
 
         Parameters
         ----------
-        waveform_generator: tupak.waveform_generator.WaveformGenerator, optional
-            If the waveform generator and interferometers are provided, the SNRs will be recorded.
-        interferometers: tupak.detector.Interferometer
-            If the waveform generator and interferometers are provided, the SNRs will be recorded.
+        likelihood: tupak.likelihood.Likelihood
+            Likelihood used for sampling.
         priors: dict
             Dictionary of prior object, used to fill in delta function priors.
+        conversion_function: function
+            Function which adds in extra parameters to the data frame,
+            should take the data_frame, likelihood and prior as arguments.
         """
         data_frame = pd.DataFrame(self.samples, columns=self.search_parameter_keys)
-        tupak.conversion.generate_all_bbh_parameters(data_frame, waveform_generator, interferometers, priors)
+        if conversion_function is not None:
+            conversion_function(data_frame, likelihood, priors)
         self.posterior = data_frame
 
     def construct_cbc_derived_parameters(self):