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ift
NIFTy
Commits
39a06b44
Commit
39a06b44
authored
Jan 24, 2019
by
Philipp Arras
Browse files
Docs
parent
6b5818dc
Changes
2
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nifty5/library/inverse_gamma_operator.py
View file @
39a06b44
...
...
@@ -26,7 +26,7 @@ from ..sugar import makeOp
class
InverseGammaOperator
(
Operator
):
"""
Operator which t
ransforms a Gaussian into an inverse gamma distribution.
"""
T
ransforms a Gaussian into an inverse gamma distribution.
The pdf of the inverse gamma distribution is defined as follows:
...
...
nifty5/operators/energy_operators.py
View file @
39a06b44
...
...
@@ -95,7 +95,7 @@ class QuadraticFormOperator(EnergyOperator):
class
GaussianEnergy
(
EnergyOperator
):
"""C
lass for energies of fields with Gaussian probability distributio
n.
"""C
omputes a negative-log Gaussia
n.
Represents up to constants in :math:`m`:
...
...
@@ -162,8 +162,8 @@ class GaussianEnergy(EnergyOperator):
class
PoissonianEnergy
(
EnergyOperator
):
"""C
lass for
likelihood Hamiltonians of expected count field constrained
by
Poissonian count data.
"""C
omputes
likelihood Hamiltonians of expected count field constrained
by
Poissonian count data.
Represents up to an f-independent term :math:`log(d!)`:
...
...
@@ -200,8 +200,7 @@ class PoissonianEnergy(EnergyOperator):
class
InverseGammaLikelihood
(
EnergyOperator
):
"""This describes the negative log-likelihood of the inverse
gamma distribution.
"""Computes the negative log-likelihood of the inverse gamma distribution.
It negative log-pdf(x) is given by
...
...
@@ -341,7 +340,7 @@ class StandardHamiltonian(EnergyOperator):
class
AveragedEnergy
(
EnergyOperator
):
"""Averages an energy over samples
"""Averages an energy over samples
.
Parameters
----------
...
...
@@ -351,15 +350,15 @@ class AveragedEnergy(EnergyOperator):
Set of residual sample points to be added to mean field for
approximate estimation of the KL.
Note
----
Having symmetrized residual samples, with both v_i and -v_i being
present, ensures that the distribution mean is exactly represented.
Notes
-----
- Having symmetrized residual samples, with both :math:`v_i` and
:math:`-v_i` being present, ensures that the distribution mean is
exactly represented.
:class:`AveragedEnergy(h)` approximates
:math:`
\\
left< H(f)
\\
right>_{G(f-m,D)}` if the residuals
:math:`f-m` are drawn from a Gaussian distribution with covariance
:math:`D`.
- :class:`AveragedEnergy(h)` approximates
:math:`
\\
left< H(f)
\\
right>_{G(f-m,D)}` if the residuals :math:`f-m`
are drawn from a Gaussian distribution with covariance :math:`D`.
"""
def
__init__
(
self
,
h
,
res_samples
):
...
...
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