diff --git a/CONTRIBUTING.md b/CONTRIBUTING.md
index f8c4bde71429cec0e6e6addcfaa65d31f3ce95f4..b5cad3bcd9f9fbe7447333a486fc059c764f34ad 100644
--- a/CONTRIBUTING.md
+++ b/CONTRIBUTING.md
@@ -33,7 +33,7 @@ when you change the code your installed version will automatically be updated.
 #### Removing previously installed versions
 
 If you have previously installed `bilby` using `pip` (or generally find buggy
-behaviour). It may be worthwhile purging your system and reinstalling. To do
+behaviour), it may be worthwhile purging your system and reinstalling. To do
 this, first find out where the module is being imported from: from any
 directory that is *not* the source directory, do the following
 
@@ -170,7 +170,7 @@ interested party) please key these three things in mind
 
 * If you open a discussion, be timely in responding to the submitter. Note, the
   reverse does not need to apply.
-* Keep your questions/comments focussed on the scope of the merge request. If
+* Keep your questions/comments focused on the scope of the merge request. If
   while reviewing the code you notice other things which could be improved, open
   a new issue.
 * Be supportive - merge requests represent a lot of hard work and effort and
diff --git a/bilby/core/sampler/__init__.py b/bilby/core/sampler/__init__.py
index b77831e64039d39ee4852365309ca13221f318f0..ade03719109e831ee517c1eb2d4be923f6e0ee67 100644
--- a/bilby/core/sampler/__init__.py
+++ b/bilby/core/sampler/__init__.py
@@ -169,10 +169,6 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
     else:
         result = sampler.run_sampler()
 
-    # Initial save of the sampler in case of failure in post-processing
-    if save:
-        result.save_to_file(extension=save, gzip=gzip)
-
     end_time = datetime.datetime.now()
     result.sampling_time = (end_time - start_time).total_seconds()
     logger.info('Sampling time: {}'.format(end_time - start_time))
@@ -187,10 +183,13 @@ def run_sampler(likelihood, priors=None, label='label', outdir='outdir',
         result.log_bayes_factor = \
             result.log_evidence - result.log_noise_evidence
 
-    if result.injection_parameters is not None:
-        if conversion_function is not None:
-            result.injection_parameters = conversion_function(
-                result.injection_parameters)
+    # Initial save of the sampler in case of failure in post-processing
+    if save:
+        result.save_to_file(extension=save, gzip=gzip)
+
+    if None not in [result.injection_parameters, conversion_function]:
+        result.injection_parameters = conversion_function(
+            result.injection_parameters)
 
     result.samples_to_posterior(likelihood=likelihood, priors=result.priors,
                                 conversion_function=conversion_function)