diff --git a/bilby/core/sampler/cpnest.py b/bilby/core/sampler/cpnest.py
index 692980876401065b16a68a1955333fbab57d14d3..2f11d94ff54c2c9c8e82bc9aca505e20b3e5b0e0 100644
--- a/bilby/core/sampler/cpnest.py
+++ b/bilby/core/sampler/cpnest.py
@@ -101,12 +101,13 @@ class Cpnest(NestedSampler):
             out.plot()
 
         self.result.posterior = DataFrame(out.posterior_samples)
-        self.result.nested_samples = DataFrame(out.get_nested_samples(filename=None))
-        self.result.nested_samples.rename(columns=dict(logL='log_likelihood'))
-        self.result.nested_samples['weights'] = np.exp(compute_weights(self.result.nested_samples['log_likelihood'],
-                                                                       out.NS.state.nlive)[1])
-        self.result.posterior.rename(columns=dict(
-            logL='log_likelihood', logPrior='log_prior'), inplace=True)
+        self.result.nested_samples = DataFrame(out.get_nested_samples(filename=''))
+        self.result.nested_samples.rename(columns=dict(logL='log_likelihood'), inplace=True)
+        self.result.posterior.rename(columns=dict(logL='log_likelihood', logPrior='log_prior'),
+                                     inplace=True)
+        _, log_weights = compute_weights(np.array(self.result.nested_samples.log_likelihood),
+                                         np.array(out.NS.state.nlive))
+        self.result.nested_samples.weights = np.exp(log_weights)
         self.result.log_evidence = out.NS.state.logZ
         self.result.log_evidence_err = np.sqrt(out.NS.state.info / out.NS.state.nlive)
         return self.result