diff --git a/src/jimgw/single_event/runManager.py b/src/jimgw/single_event/runManager.py
index 3e5bc092..2fa00cd9 100644
--- a/src/jimgw/single_event/runManager.py
+++ b/src/jimgw/single_event/runManager.py
@@ -102,8 +102,10 @@ def __init__(self, **kwargs):
             raise ValueError("Injection mode requires injection parameters.")
 
         local_prior = self.initialize_prior()
-        local_likelihood = self.initialize_likelihood(local_prior)
         sample_transforms, likelihood_transforms = self.initialize_transforms()
+        local_likelihood = self.initialize_likelihood(
+            local_prior, sample_transforms, likelihood_transforms
+        )
         self.jim = Jim(
             local_likelihood,
             local_prior,
@@ -124,7 +126,12 @@ def load_from_path(self, path: str) -> SingleEventRun:
 
     ### Initialization functions ###
 
-    def initialize_likelihood(self, prior: prior.CombinePrior) -> SingleEventLiklihood:
+    def initialize_likelihood(
+        self,
+        prior: prior.CombinePrior,
+        sample_transforms: transforms.Transform,
+        likelihood_transforms: transforms.Transform,
+    ) -> SingleEventLiklihood:
         """
         Since prior contains information about types, naming and ranges of parameters,
         some of the likelihood class require the prior to be initialized, such as the
@@ -176,6 +183,8 @@ def initialize_likelihood(self, prior: prior.CombinePrior) -> SingleEventLikliho
             detectors,
             waveform,
             prior=prior,
+            sample_transforms=sample_transforms,
+            likelihood_transforms=likelihood_transforms,
             **self.run.likelihood_parameters,
             **self.run.data_parameters,
         )
@@ -221,6 +230,7 @@ def initialize_transforms(
                         transform_class = getattr(transforms, transform["name"])
                     except AttributeError:
                         raise ValueError(f"{transform['name']} not recognized.")
+                transform = transform.copy()
                 transform.pop("name")
                 sample_transforms.append(transform_class(**transform))
         if self.run.likelihood_transforms:
@@ -239,6 +249,7 @@ def initialize_transforms(
                         transform_class = getattr(transforms, transform["name"])
                     except AttributeError:
                         raise ValueError(f"{transform['name']} not recognized.")
+                transform = transform.copy()
                 transform.pop("name")
                 likelihood_transforms.append(transform_class(**transform))
         return sample_transforms, likelihood_transforms
@@ -460,9 +471,13 @@ def plot_diagnostic(self, path: str = "diagnostic.jpeg", **kwargs):
     def save_summary(self, path: str = "", **kwargs):
         if path == "":
             path = self.run.path + "run_manager_summary.txt"
+        orig_stdout = sys.stdout
         sys.stdout = open(path, "wt")
         self.jim.print_summary()
-        for detector, SNR in zip(self.detectors, self.SNRs):
-            print("SNR of detector " + detector + " is " + str(SNR))
-        networkSNR = jnp.sum(jnp.array(self.SNRs) ** 2) ** (0.5)
-        print("network SNR is", networkSNR)
+        if self.run.injection:
+            for detector, SNR in zip(self.detectors, self.SNRs):
+                print("SNR of detector " + detector + " is " + str(SNR))
+            networkSNR = jnp.sum(jnp.array(self.SNRs) ** 2) ** (0.5)
+            print("network SNR is", networkSNR)
+        sys.stdout.close()
+        sys.stdout = orig_stdout