diff --git a/src/jimgw/prior.py b/src/jimgw/prior.py
index 3db3f122..87406ca8 100644
--- a/src/jimgw/prior.py
+++ b/src/jimgw/prior.py
@@ -397,6 +397,7 @@ def __init__(
             ],
         )
 
+
 def trace_prior_parent(prior: Prior, output: list[Prior] = []) -> list[Prior]:
     if prior.composite:
         if isinstance(prior.base_prior, list):
@@ -410,9 +411,6 @@ def trace_prior_parent(prior: Prior, output: list[Prior] = []) -> list[Prior]:
     return output
 
 
-
-
-
 # ====================== Things below may need rework ======================
 
 # @jaxtyped(typechecker=typechecker)
diff --git a/src/jimgw/single_event/likelihood.py b/src/jimgw/single_event/likelihood.py
index 9e775b33..96e11e62 100644
--- a/src/jimgw/single_event/likelihood.py
+++ b/src/jimgw/single_event/likelihood.py
@@ -584,18 +584,35 @@ def y(x):
         )
 
         key = jax.random.PRNGKey(0)
-        initial_position = []
-        for _ in range(popsize):
-            flag = True
-            while flag:
-                key = jax.random.split(key)[1]
-                guess = prior.sample(key, 1)
-                for transform in sample_transforms:
-                    guess = transform.forward(guess)
-                guess = jnp.array([i for i in guess.values()]).T[0]
-                flag = not jnp.all(jnp.isfinite(guess))
-            initial_position.append(guess)
-        initial_position = jnp.array(initial_position)
+        initial_position = jnp.zeros((popsize, prior.n_dim)) + jnp.nan
+        while not jax.tree.reduce(
+            jnp.logical_and, jax.tree.map(lambda x: jnp.isfinite(x), initial_position)
+        ).all():
+            non_finite_index = jnp.where(
+                jnp.any(
+                    ~jax.tree.reduce(
+                        jnp.logical_and,
+                        jax.tree.map(lambda x: jnp.isfinite(x), initial_position),
+                    ),
+                    axis=1,
+                )
+            )[0]
+
+            key, subkey = jax.random.split(key)
+            guess = prior.sample(subkey, popsize)
+            for transform in sample_transforms:
+                guess = jax.vmap(transform.forward)(guess)
+            guess = jnp.array(
+                jax.tree.leaves({key: guess[key] for key in parameter_names})
+            ).T
+            finite_guess = jnp.where(
+                jnp.all(jax.tree.map(lambda x: jnp.isfinite(x), guess), axis=1)
+            )[0]
+            common_length = min(len(finite_guess), len(non_finite_index))
+            initial_position = initial_position.at[
+                non_finite_index[:common_length]
+            ].set(guess[:common_length])
+        
         rng_key, optimized_positions, summary = optimizer.optimize(
             jax.random.PRNGKey(12094), y, initial_position
         )
diff --git a/src/jimgw/single_event/prior.py b/src/jimgw/single_event/prior.py
index 76ca6376..194262f0 100644
--- a/src/jimgw/single_event/prior.py
+++ b/src/jimgw/single_event/prior.py
@@ -1,17 +1,11 @@
-import jax.numpy as jnp
 from beartype import beartype as typechecker
 from jaxtyping import jaxtyped
 
 from jimgw.prior import (
-    Prior,
-    CombinePrior,
-    UniformPrior,
     PowerLawPrior,
-    SinePrior,
 )
 
 
-
 @jaxtyped(typechecker=typechecker)
 class UniformComponentChirpMassPrior(PowerLawPrior):
     """