Commit fec4609f by 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 """ ... ...
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