Commit 5f245882 by Philipp Arras

### Add docu to KL

parent eb60c29a
 ... ... @@ -58,6 +58,9 @@ class MetricGaussianKL(Energy): as they are equally legitimate samples. If true, the number of used samples doubles. Mirroring samples stabilizes the KL estimate as extreme sample variation is counterbalanced. Default is False. napprox : int Number of samples for computing preconditioner for sampling. No preconditioning is done by default. _samples : None Only a parameter for internal uses. Typically not to be set by users. ... ... @@ -74,7 +77,7 @@ class MetricGaussianKL(Energy): def __init__(self, mean, hamiltonian, n_samples, constants=[], point_estimates=[], mirror_samples=False, _samples=None, napprox=0): napprox=0, _samples=None): super(MetricGaussianKL, self).__init__(mean) if not isinstance(hamiltonian, StandardHamiltonian): ... ... @@ -94,9 +97,7 @@ class MetricGaussianKL(Energy): met = hamiltonian(Linearization.make_partial_var( mean, point_estimates, True)).metric if napprox > 1: print('Calculate preconditioner for sampling') met._approximation = makeOp(approximation2endo(met, napprox)) print('Done') _samples = tuple(met.draw_sample(from_inverse=True) for _ in range(n_samples)) if mirror_samples: ... ... @@ -121,7 +122,7 @@ class MetricGaussianKL(Energy): def at(self, position): return MetricGaussianKL(position, self._hamiltonian, 0, self._constants, self._point_estimates, _samples=self._samples, napprox=self._napprox) napprox=self._napprox, _samples=self._samples) @property def value(self): ... ...
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