cleanup, renaming

nifty5/__init__.py

@@ -49,7 +49,7 @@ from .operators.simple_linear_operators import (
     FieldAdapter, ducktape, GeometryRemover, NullOperator)
 from .operators.energy_operators import (
     EnergyOperator, GaussianEnergy, PoissonianEnergy, InverseGammaLikelihood,
-    BernoulliEnergy, Hamiltonian, SampledKullbachLeiblerDivergence)
+    BernoulliEnergy, Hamiltonian, AveragedEnergy)
 
 from .probing import probe_with_posterior_samples, probe_diagonal, \
     StatCalculator

nifty5/operators/energy_operators.py

@@ -300,8 +300,8 @@ class Hamiltonian(EnergyOperator):
         return 'Hamiltonian:\n' + utilities.indent(subs)
 
 
-class SampledKullbachLeiblerDivergence(EnergyOperator):
-    """Class for Kullbach Leibler (KL) Divergence or Gibbs free energies
+class AveragedEnergy(EnergyOperator):
+    """Class for Kullbach-Leibler (KL) Divergence or Gibbs free energies
 
     Precisely a sample averaged Hamiltonian (or other energy) that represents
     approximatively the relevant part of a KL to be used in Variational Bayes
@@ -320,7 +320,7 @@ class SampledKullbachLeiblerDivergence(EnergyOperator):
     in essence the information Hamiltonian averaged over a Gaussian
     distribution centered on the mean m.
 
-    SampledKullbachLeiblerDivergence(H) approximates
+    ``AveragedEnergy(H)`` approximates
     :math:`\\left< H(f) \\right>_{G(f-m,D)}` if the residuals
     :math:`f-m` are drawn from covariance :math:`D`.
 
@@ -334,7 +334,7 @@ class SampledKullbachLeiblerDivergence(EnergyOperator):
 
     Notes
     -----
-    ``KL = SampledKullbachLeiblerDivergence(H, samples)`` represents
+    ``KL = AveragedEnergy(H, samples)`` represents
 
     :math:`\\text{KL}(m) = \\sum_i H(m+v_i) / N`,
 

nifty5/operators/operator.py

@@ -107,7 +107,7 @@ class Operator(NiftyMetaBase()):
 
         Parameters
         ----------
-        x : Field/Multifield
+        x : Field or MultiField
             the operator's input
         """
         raise NotImplementedError

test/test_energy_gradients.py

@@ -73,7 +73,7 @@ def test_hamiltonian_and_KL(field):
     ift.extra.check_value_gradient_consistency(hamiltonian, field)
     S = ift.ScalingOperator(1., space)
     samps = [S.draw_sample() for i in range(3)]
-    kl = ift.SampledKullbachLeiblerDivergence(hamiltonian, samps)
+    kl = ift.AveragedEnergy(hamiltonian, samps)
     ift.extra.check_value_gradient_consistency(kl, field)