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src/library/variational_models.py

@@ -34,12 +34,29 @@ from ..utilities import myassert
 
 
 class MeanFieldVI:
-    def __init__(self, initial_position, hamiltonian, n_samples, mirror_samples,
+    """Collect the operators required for Gaussian meanfield variational
+    inference.
+
+    Parameters
+    ----------
+    position :
+        FIXME
+    hamiltonian :
+        FIXME
+    n_samples :
+        FIXME
+    mirror_samples :
+        FIXME
+    initial_sig :
+        FIXME
+    comm :
+        FIXME
+    nanisinf :
+        FIXME
+    """
+    def __init__(self, position, hamiltonian, n_samples, mirror_samples,
                  initial_sig=1, comm=None, nanisinf=False):
-        """Collect the operators required for Gaussian mean-field variational
-        inference.
-        """
-        Flat = Multifield2Vector(initial_position.domain)
+        Flat = Multifield2Vector(position.domain)
         self._std = FieldAdapter(Flat.target, 'std').absolute()
         latent = FieldAdapter(Flat.target,'latent')
         self._mean = FieldAdapter(Flat.target, 'mean')
@@ -47,7 +64,7 @@ class MeanFieldVI:
         self._entropy = GaussianEntropy(self._std.target) @ self._std
         self._mean = Flat.adjoint @ self._mean
         self._std = Flat.adjoint @ self._std
-        pos = {'mean': Flat(initial_position)}
+        pos = {'mean': Flat(position)}
         if is_fieldlike(initial_sig):
             pos['std'] = Flat(initial_sig)
         else:
@@ -78,12 +95,30 @@ class MeanFieldVI:
     def minimize(self, minimizer):
         self._KL, _ = minimizer(self._KL)
 
+
 class FullCovarianceVI:
+    """Collect the operators required for Gaussian full-covariance variational
+    inference.
+
+    Parameters
+    ----------
+    position :
+        FIXME
+    hamiltonian :
+        FIXME
+    n_samples :
+        FIXME
+    mirror_samples :
+        FIXME
+    initial_sig :
+        FIXME
+    comm :
+        FIXME
+    nanisinf :
+        FIXME
+    """
     def __init__(self, position, hamiltonian, n_samples, mirror_samples,
                 initial_sig=1, comm=None, nanisinf=False):
-        """Collect the operators required for Gaussian full-covariance variational
-        inference.
-        """
         Flat = Multifield2Vector(position.domain)
         flat_domain = Flat.target[0]
         mat_space = DomainTuple.make((flat_domain,flat_domain))
@@ -128,8 +163,8 @@ class FullCovarianceVI:
 
 
 class GaussianEntropy(EnergyOperator):
-    """Calculate the entropy of a Gaussian distribution given the diagonal of a
-    triangular decomposition of the covariance.
+    """Entropy of a Gaussian distribution given the diagonal of a triangular
+    decomposition of the covariance.
 
     Parameters
     ----------
@@ -152,7 +187,7 @@ class GaussianEntropy(EnergyOperator):
 
 
 class LowerTriangularInserter(LinearOperator):
-    """Inserts the DOFs of a lower triangular matrix into a matrix.
+    """Insert the entries of a lower triangular matrix into a matrix.
 
     Parameters
     ----------