Commit fec4609f authored by Martin Reinecke's avatar Martin Reinecke

more doc work

parent 9ea84e2e
Pipeline #24941 passed with stages
in 6 minutes and 39 seconds
......@@ -24,14 +24,14 @@ from .. import dobj
class PowerSpace(StructuredDomain):
"""NIFTy class for spaces of power spectra.
A power space is the result of a projection of a harmonic space where
A power space is the result of a projection of a harmonic domain where
k-modes of equal length get mapped to one power index.
Parameters
----------
harmonic_partner : Space
The harmonic Space of which this is the power space.
binbounds: None, or tuple/array/list of float
harmonic_partner : StructuredDomain
The harmonic dmain of which this is the power space.
binbounds : None, or tuple of float
if None:
There will be as many bins as there are distinct k-vector lengths
in the harmonic partner space.
......@@ -54,9 +54,9 @@ class PowerSpace(StructuredDomain):
binbounds[0]=first_bound and binbounds[-1]=last_bound and the remaining
values equidistantly spaced (in linear scale) between these two.
nbin: integer
nbin : int
the number of bins
first_bound, last_bound: float
first_bound, last_bound : float
the k values for the right boundary of the first bin and the left
boundary of the last bin, respectively. They are given in length
units of the harmonic partner space.
......@@ -74,9 +74,9 @@ class PowerSpace(StructuredDomain):
values equidistantly spaced (in natural logarithmic scale)
between these two.
nbin: integer
nbin : int
the number of bins
first_bound, last_bound: float
first_bound, last_bound : float
the k values for the right boundary of the first bin and the left
boundary of the last bin, respectively. They are given in length
units of the harmonic partner space.
......
......@@ -34,33 +34,34 @@ class CriticalPowerEnergy(Energy):
Parameters
----------
position : Field,
position : Field
The current position of this energy. (Logarithm of power spectrum)
m : Field,
m : Field
The map whose power spectrum is inferred. Needs to live in harmonic
signal space.
D : EndomorphicOperator,
D : EndomorphicOperator, optional
The curvature of the Gaussian encoding the posterior covariance.
If not specified, the map is assumed to be no reconstruction.
default : None
alpha : float
alpha : float, optional
The spectral prior of the inverse gamma distribution. 1.0 corresponds
to non-informative.
default : 1.0
q : float
q : float, optional
The cutoff parameter of the inverse gamma distribution. 0.0 corresponds
to non-informative.
default : 0.0
smoothness_prior : float
smoothness_prior : float, optional
Controls the strength of the smoothness prior
default : 0.0
logarithmic : boolean
logarithmic : bool, optional
Whether smoothness acts on linear or logarithmic scale.
samples : integer
default : True
samples : int, optional
Number of samples used for the estimation of the uncertainty
corrections.
default : 3
w : Field
w : Field, optional
The contribution from the map with or without uncertainty. It is used
to pass on the result of the costly sampling during the minimization.
default : None
......
......@@ -34,18 +34,18 @@ class NonlinearPowerEnergy(Energy):
Parameters
----------
position : Field,
position : Field
The current position of this energy.
m : Field,
m : Field
The map whichs power spectrum has to be inferred
D : EndomorphicOperator,
D : EndomorphicOperator
The curvature of the Gaussian encoding the posterior covariance.
If not specified, the map is assumed to be no reconstruction.
default : None
sigma : float
The parameter of the smoothness prior.
default : ??? None? ???????
samples : integer
samples : int
Number of samples used for the estimation of the uncertainty
corrections.
default : 3
......
......@@ -56,9 +56,9 @@ class ConjugateGradient(Minimizer):
Returns
-------
energy : QuadraticEnergy
QuadraticEnergy
state at last point of the iteration
status : integer
int
Can be controller.CONVERGED or controller.ERROR
"""
controller = self._controller
......
......@@ -50,15 +50,15 @@ class DescentMinimizer(Minimizer):
Parameters
----------
energy : Energy object
nergy : Energy
Energy object which provides value, gradient and curvature at a
specific position in parameter space.
Returns
-------
energy : Energy object
Energy
Latest `energy` of the minimization.
status : integer
int
Can be controller.CONVERGED or controller.ERROR
Notes
......
......@@ -41,13 +41,13 @@ class LineSearchStrongWolfe(LineSearch):
Parameter for curvature condition rule. (Default: 0.9)
max_step_size : float
Maximum step allowed in to be made in the descent direction.
(Default: 50)
max_iterations : integer
(Default: 1000000000)
max_iterations : int, optional
Maximum number of iterations performed by the line search algorithm.
(Default: 10)
max_zoom_iterations : integer
(Default: 100)
max_zoom_iterations : int, optional
Maximum number of iterations performed by the zoom algorithm.
(Default: 10)
(Default: 100)
"""
def __init__(self, c1=1e-4, c2=0.9,
......@@ -71,18 +71,18 @@ class LineSearchStrongWolfe(LineSearch):
Parameters
----------
energy : Energy object
energy : Energy
Energy object from which we will calculate the energy and the
gradient at a specific point.
pk : Field
Vector pointing into the search direction.
f_k_minus_1 : float
f_k_minus_1 : float, optional
Value of the fuction (which is being minimized) at the k-1
iteration of the line search procedure. (Default: None)
Returns
-------
energy_star : Energy object
Energy
The new Energy object on the new position.
"""
le_0 = LineEnergy(0., energy, pk, 0.)
......@@ -188,7 +188,7 @@ class LineSearchStrongWolfe(LineSearch):
Returns
-------
energy_star : Energy object
Energy
The new Energy object on the new position.
"""
cubic_delta = 0.2 # cubic interpolant checks
......
......@@ -39,8 +39,9 @@ class Minimizer(with_metaclass(NiftyMeta, type('NewBase', (object,), {}))):
Returns
-------
energy : Energy object
Energy
Latest `energy` of the minimization.
status : integer
int
exit status of the minimization
"""
raise NotImplementedError
......@@ -51,9 +51,9 @@ class NonlinearCG(Minimizer):
Returns
-------
energy :
Energy
state at last point of the iteration
status : integer
int
Can be controller.CONVERGED or controller.ERROR
"""
controller = self._controller
......
......@@ -87,7 +87,7 @@ class InformationStore(object):
Parameters
----------
max_history_length : integer
max_history_length : int
Maximum number of stored past updates.
x0 : Field
Initial position in variable space.
......@@ -96,7 +96,7 @@ class InformationStore(object):
Attributes
----------
max_history_length : integer
max_history_length : int
Maximum number of stored past updates.
s : List
Circular buffer of past position differences, which are Fields.
......@@ -106,7 +106,7 @@ class InformationStore(object):
Latest position in variable space.
last_gradient : Field
Gradient at latest position.
k : integer
k : int
Number of updates that have taken place
ss : numpy.ndarray
2D circular buffer of scalar products between different elements of s.
......@@ -139,7 +139,7 @@ class InformationStore(object):
Returns
-------
result : List
List
List of new basis vectors.
"""
result = []
......@@ -165,7 +165,7 @@ class InformationStore(object):
Returns
-------
result : numpy.ndarray
numpy.ndarray
Scalar matrix.
"""
m = self.history_length
......@@ -207,7 +207,7 @@ class InformationStore(object):
Returns
-------
delta : List
List
List of the new scalar coefficients (deltas).
"""
m = self.history_length
......
......@@ -35,7 +35,7 @@ class LaplaceOperator(EndomorphicOperator):
Parameters
----------
logarithmic : boolean,
logarithmic : bool, optional
Whether smoothness is calculated on a logarithmic scale or linear scale
default : True
space : int
......
......@@ -57,7 +57,7 @@ class LinearOperator(with_metaclass(
@abc.abstractproperty
def domain(self):
"""
domain : DomainTuple
DomainTuple
The domain on which the Operator's input Field lives.
Every Operator which inherits from the abstract LinearOperator
base class must have this attribute.
......@@ -67,7 +67,7 @@ class LinearOperator(with_metaclass(
@abc.abstractproperty
def target(self):
"""
target : DomainTuple
DomainTuple
The domain on which the Operator's output Field lives.
Every Operator which inherits from the abstract LinearOperator
base class must have this attribute.
......@@ -77,7 +77,7 @@ class LinearOperator(with_metaclass(
@property
def inverse(self):
"""
inverse : LinearOperator
LinearOperator
Returns a LinearOperator object which behaves as if it were
the inverse of this operator.
"""
......@@ -87,7 +87,7 @@ class LinearOperator(with_metaclass(
@property
def adjoint(self):
"""
adjoint : LinearOperator
LinearOperator
Returns a LinearOperator object which behaves as if it were
the adjoint of this operator.
"""
......@@ -141,7 +141,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : integer
int
This is any subset of LinearOperator.{TIMES, ADJOINT_TIMES,
INVERSE_TIMES, ADJOINT_INVERSE_TIMES, INVERSE_ADJOINT_TIMES},
joined together by the "|" operator.
......@@ -158,7 +158,7 @@ class LinearOperator(with_metaclass(
The input Field, living on the Operator's domain or target,
depending on mode.
mode : integer
mode : int
LinearOperator.TIMES: normal application
LinearOperator.ADJOINT_TIMES: adjoint application
LinearOperator.INVERSE_TIMES: inverse application
......@@ -168,7 +168,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : Field
Field
The processed Field living on the Operator's target or domain,
depending on mode.
"""
......@@ -188,7 +188,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : Field
Field
The processed Field living on the Operator's target domain.
"""
return self.apply(x, self.TIMES)
......@@ -203,7 +203,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : Field
Field
The processed Field living on the Operator's domain.
"""
return self.apply(x, self.INVERSE_TIMES)
......@@ -218,7 +218,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : Field
Field
The processed Field living on the Operator's domain.
"""
return self.apply(x, self.ADJOINT_TIMES)
......@@ -233,7 +233,7 @@ class LinearOperator(with_metaclass(
Returns
-------
out : Field
Field
The processed Field living on the Operator's target domain.
Notes
......@@ -267,7 +267,7 @@ class LinearOperator(with_metaclass(
Returns
-------
sample : Field
Returns the a sample from the Gaussian of given covariance.
Field
A sample from the Gaussian of given covariance.
"""
raise NotImplementedError
......@@ -36,9 +36,9 @@ def SmoothnessOperator(domain, strength=1., logarithmic=True, space=None):
Parameters
----------
strength: nonnegative float
strength : nonnegative float
Specifies the strength of the SmoothnessOperator
logarithmic : boolean
logarithmic : bool, optional
Whether smoothness is calculated on a logarithmic scale or linear scale
default : True
"""
......
Markdown is supported
0% or
You are about to add 0 people to the discussion. Proceed with caution.
Finish editing this message first!
Please register or to comment