Commit 6be924b0 by Philipp Arras

### Docs

parent 9a6f726b
 ... ... @@ -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 ---------- ... ...
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