make sure log bayes factor is stored even if nan

tupak/core/sampler/__init__.py

@@ -157,10 +157,9 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
         result.log_evidence = \
             result.log_bayes_factor + result.log_noise_evidence
     else:
-        if likelihood.noise_log_likelihood() is not np.nan:
-            result.log_noise_evidence = likelihood.noise_log_likelihood()
-            result.log_bayes_factor = \
-                result.log_evidence - result.log_noise_evidence
+        result.log_noise_evidence = likelihood.noise_log_likelihood()
+        result.log_bayes_factor = \
+            result.log_evidence - result.log_noise_evidence
     if injection_parameters is not None:
         result.injection_parameters = injection_parameters
         if conversion_function is not None: