likelihood: Remove most refs. to Hamiltonian

src/re/likelihood.py

@@ -215,7 +215,7 @@ class Likelihood(AbstractModel):
         """
         # TODO: track forward model and build lsm, metric, residual only when
         # called instead of always partially
-        self._hamiltonian = energy
+        self._energy = energy
         self._transformation = transformation
         self._normalized_residual = normalized_residual
         self._left_sqrt_metric = left_sqrt_metric
@@ -260,7 +260,7 @@ class Likelihood(AbstractModel):
         energy : float
             Energy at the position `primals`.
         """
-        return self._hamiltonian(primals, **primals_kw)
+        return self._energy(primals, **primals_kw)
 
     def normalized_residual(self, primals, **primals_kw):
         """Applies the normalized_residual to `primals`.
@@ -490,7 +490,7 @@ class Likelihood(AbstractModel):
             j_trafo, j_lsm, j_rsm, j_m = None, None, None, None
 
         return self.replace(
-            jit(self._hamiltonian, **kwargs),
+            jit(self._energy, **kwargs),
             normalized_residual=j_r,
             transformation=j_trafo,
             left_sqrt_metric=j_lsm,
@@ -613,7 +613,7 @@ class Likelihood(AbstractModel):
                       Vector) or isinstance(other._lsm_tan_shp, Vector):
             joined_tangents_shape = Vector(joined_tangents_shape)
 
-        def joined_hamiltonian(p, **pkw):
+        def joined_energy(p, **pkw):
             return self.energy(p, **pkw) + other.energy(p, **pkw)
 
         def joined_normalized_residual(p, **pkw):
@@ -668,7 +668,7 @@ class Likelihood(AbstractModel):
                 raise ValueError(ve)
 
         return Likelihood(
-            joined_hamiltonian,
+            joined_energy,
             normalized_residual=joined_normalized_residual,
             transformation=joined_transformation,
             left_sqrt_metric=joined_left_sqrt_metric,
@@ -778,7 +778,7 @@ class StandardHamiltonian():
         """
         self._lh = likelihood
 
-        def joined_hamiltonian(primals, **primals_kw):
+        def joined_energy(primals, **primals_kw):
             # Assume the first primals to be the parameters
             return self._lh(primals, **
                             primals_kw) + 0.5 * vdot(primals, primals)
@@ -788,9 +788,9 @@ class StandardHamiltonian():
 
         if _compile_joined:
             from jax import jit
-            joined_hamiltonian = jit(joined_hamiltonian, **_compile_kwargs)
+            joined_energy = jit(joined_energy, **_compile_kwargs)
             joined_metric = jit(joined_metric, **_compile_kwargs)
-        self._hamiltonian = joined_hamiltonian
+        self._energy = joined_energy
         self._metric = joined_metric
 
     @doc_from(Likelihood.__call__)
@@ -799,7 +799,7 @@ class StandardHamiltonian():
 
     @doc_from(Likelihood.energy)
     def energy(self, primals, **primals_kw):
-        return self._hamiltonian(primals, **primals_kw)
+        return self._energy(primals, **primals_kw)
 
     @doc_from(Likelihood.metric)
     def metric(self, primals, tangents, **primals_kw):