fix minor typehint error

Author: kazewong

example/GW170817_heterodyne.py

@@ -93,7 +93,7 @@
 )
 
 # The following only works if every prior has xmin and xmax property, which is OK for Uniform and Powerlaw
-bounds = jnp.array([[p.xmin, p.xmax] for p in prior.priors]).T
+bounds = jnp.array([[p.xmin, p.xmax] for p in prior.priors])
 
 ### Create likelihood object
 likelihood = HeterodynedTransientLikelihoodFD([H1, L1, V1], prior=prior, bounds=bounds, waveform=RippleIMRPhenomD(), trigger_time=gps, duration=T, n_bins=500)
@@ -116,7 +116,6 @@
 jim = Jim(
     likelihood,
     prior,
-    n_loop_pretraining=0,
     n_loop_training=200,
     n_loop_production=20,
     n_local_steps=200,

src/jimgw/prior.py

@@ -167,21 +167,21 @@ def new_transform(param):
             self.naming[0]: (local_transform[self.naming[0]][0], new_transform)
         }
 
-    def to_range(self, x: dict[str, Float]) -> Float:
+    def to_range(self, x: Float) -> Float:
         """
         Transform the parameters to the range of the prior.
 
         Parameters
         ----------
-        x : dict
-            A dictionary of parameters. Names should match the ones in the prior.
+        x : Float
+            The parameters to transform.
 
         Returns
         -------
         x : dict
             A dictionary of parameters with the transforms applied.
         """
-        return (self.xmax - self.xmin) / (1 + jnp.exp(-x[self.naming[0]])) + self.xmin
+        return (self.xmax - self.xmin) / (1 + jnp.exp(-x)) + self.xmin
 
     def sample(
         self, rng_key: PRNGKeyArray, n_samples: int