Commit e73ed95e authored by Pumpe, Daniel (dpumpe)'s avatar Pumpe, Daniel (dpumpe)

Merge branch 'master' of gitlab.mpcdf.mpg.de:ift/NIFTy

parents 778cca38 a220fe56
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.. currentmodule:: nifty
The ``ComposedOperator`` class -- A possibility to combine several operators
............................................................................
.. autoclass:: ComposedOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``ConjugateGradient`` class -- Minimization routine
.......................................................
.. autoclass:: ConjugateGradient
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``DescentMinimizer`` class -- The Base class for minimizers
...............................................................
.. autoclass:: DescentMinimizer
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``DiagonalOperator`` class -- ...
.....................................
.. autoclass:: DiagonalOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``EndomorphicOperator`` class -- ...
........................................
.. autoclass:: EndomorphicOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``FFTOperator`` class -- Fourier Transformations
....................................................
.. autoclass:: FFTOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``GLSpace`` class -- Gauss-Legendre pixelization of the sphere
..................................................................
.. autoclass:: GLSpace
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``GLLMTransformation`` class -- A transformation routine
............................................................
.. autoclass:: GLLMTransformation
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``HPSpace`` class -- HEALPix discretization of the sphere
.............................................................
.. autoclass:: HPSpace
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``HPLMTransformation`` class -- A transformation routine
............................................................
.. autoclass:: HPLMTransformation
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``InvertibleOperatorMixin`` class -- ...
............................................
.. autoclass:: InvertibleOperatorMixin
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``LMSpace`` class -- Spherical Harmonics components
.......................................................
.. autoclass:: LMSpace
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``LMGLTransformation`` class -- A transformation routine
............................................................
.. autoclass:: LMGLTransformation
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``LMHPTransformation`` class -- A transformation routine
............................................................
.. autoclass:: LMHPTransformation
:show-inheritance:
:members:
Minimization
------------
NIFTY provides several minimization routines.
.. toctree::
:maxdepth: 1
conjugate_gradient
descent_minimizer
Operators
=========
Operators perform some operation on a given field. In practice an operator can
take the form of an explicit matrix (e.g. stored in a Numpy array) or it may be
implicitly defined as a function (e.g. an FFT operation would not be encoded in
a matrix, but performed using an FFT routine). NIFTY includes a framework for
handling arbitrary operators, and basic methods for manipulating these
operators. Common functions like taking traces and extracting diagonals are
provided.
In order to have a blueprint for operators capable of handling fields, any
application of operators is split into a general and a concrete part. The
general part comprises the correct involvement of normalizations and
transformations, necessary for any operator type, while the concrete part is
unique for each operator subclass. In analogy to the field class, any operator
instance has a set of properties that specify its domain and target as well as
some additional flags.
Operator classes
----------------
NIFTY provides a base class for defining operators, as well as several pre-implemented operator types that are very often needed for signal inference
algorithms.
.. toctree::
:maxdepth: 1
diagonal_operator
fft_operator
composed_operator
response_operator
smoothing_operator
projection_operator
propagator_operator
endomorphic_operator
invertible_operator_mixin
transformations
.. currentmodule:: nifty
The ``LinearOperator`` class -- The base Operator Object
--------------------------------------------------------
.. autoclass:: LinearOperator
:show-inheritance:
:members:
...@@ -33,7 +33,6 @@ algorithms. ...@@ -33,7 +33,6 @@ algorithms.
propagator_operator propagator_operator
endomorphic_operator endomorphic_operator
invertible_operator_mixin invertible_operator_mixin
transformations
.. currentmodule:: nifty .. currentmodule:: nifty
......
.. currentmodule:: nifty
The ``PowerSpace`` class -- The natural space underlying power-spectra
.......................................................................
.. autoclass:: PowerSpace
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``ProjectionOperator`` class -- ...
.......................................
.. autoclass:: ProjectionOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``PropagatorOperator`` class -- ...
.......................................
.. autoclass:: PropagatorOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``ResponseOperator`` class -- A possible response implementation
....................................................................
.. autoclass:: ResponseOperator
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``RGSpace`` class -- Regular Cartesian grids
................................................
.. autoclass:: RGSpace
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``RGRGTransformation`` class -- A transformation routine
............................................................
.. autoclass:: RGRGTransformation
:show-inheritance:
:members:
.. currentmodule:: nifty
The ``SmoothingOperator`` class -- Smoothing fields
...................................................
.. autoclass:: SmoothingOperator
:show-inheritance:
:members:
Spaces
======
The :py:class:`Space` classes of NIFTY represent geometrical spaces approximated by grids in the computer environment. Each subclass of the base class corresponds to a specific grid type and replaces some of the inherited methods with its own methods that are unique to the respective grid. This framework ensures an abstract handling of spaces independent of the underlying geometrical grid and the grid's resolution.
Each instance of a :py:class:`Space` needs to capture all structural and dimensional specifics of the grid and all computationally relevant quantities such as the data type of associated field values. These parameters are stored as properties of an instance of the class at its initialization, and they do not need to be accessed explicitly by the user thereafter. This prevents the writing of grid or resolution dependent code.
Spatial symmetries of a system can be exploited by corresponding coordinate transformations. Often, transformations from one basis to its harmonic counterpart can greatly reduce the computational complexity of algorithms. The harmonic basis is defined by the eigenbasis of the Laplace operator; e.g., for a flat position space it is the Fourier basis. This conjugation of bases is implemented in NIFTY by distinguishing conjugate space classes, which can be obtained by the instance method *get_codomain* (and checked for by *check_codomain*). Moreover, transformations between conjugate spaces are performed automatically if required.
Space classes
-------------
Next to the generic :py:class:`Space` class, NIFTY has implementations of five subclasses, representing specific geometrical spaces and their discretizations.
.. toctree::
:maxdepth: 1
rg_space
hp_space
gl_space
lm_space
power_space
.. currentmodule:: nifty
The ``Space`` class -- The base Space object
--------------------------------------------
.. autoclass:: Space
:show-inheritance:
:members:
Transformations
---------------
NIFTY provides transformations
.. toctree::
:maxdepth: 1
rgrg_transformation
gllm_transformation
hplm_transformation
lmgl_transformation
lmhp_transformation
...@@ -28,17 +28,25 @@ __all__ = ['dependency_injector', 'nifty_configuration'] ...@@ -28,17 +28,25 @@ __all__ = ['dependency_injector', 'nifty_configuration']
# Setup the dependency injector # Setup the dependency injector
dependency_injector = keepers.DependencyInjector( dependency_injector = keepers.DependencyInjector(
[('mpi4py.MPI', 'MPI'), [('mpi4py.MPI', 'MPI'),
('pyfftw', 'fftw'),
'pyHealpix', 'pyHealpix',
'plotly']) 'plotly'])
dependency_injector.register('pyfftw', lambda z: hasattr(z, 'FFTW_MPI'))
def _fft_module_checker(z):
if z == 'fftw_mpi':
return hasattr(dependency_injector.get('fftw'), 'FFTW_MPI')
if z == 'fftw':
return ('fftw' in dependency_injector)
if z == 'numpy':
return True
return False
# Initialize the variables # Initialize the variables
variable_fft_module = keepers.Variable( variable_fft_module = keepers.Variable(
'fft_module', 'fft_module',
['fftw', 'numpy'], ['fftw_mpi', 'fftw', 'numpy'],
lambda z: (('pyfftw' in dependency_injector) _fft_module_checker)
if z == 'fftw' else True))
def dtype_validator(dtype): def dtype_validator(dtype):
......
This diff is collapsed.
...@@ -23,29 +23,29 @@ from .line_search import LineSearch ...@@ -23,29 +23,29 @@ from .line_search import LineSearch
class LineSearchStrongWolfe(LineSearch): class LineSearchStrongWolfe(LineSearch):
"""Class for finding a step size that satisfies the strong Wolfe conditions. """Class for finding a step size that satisfies the strong Wolfe conditions.
Algorithm contains two stages. It begins whit a trial step length and it Algorithm contains two stages. It begins whit a trial step length and it
keeps increasing the it until it finds an acceptable step length or an keeps increasing the it until it finds an acceptable step length or an
interval. If it does not satisfy the Wolfe conditions it performs the Zoom interval. If it does not satisfy the Wolfe conditions it performs the Zoom
algorithm (second stage). By interpolating it decreases the size of the algorithm (second stage). By interpolating it decreases the size of the
interval until an acceptable step length is found. interval until an acceptable step length is found.
Parameters Parameters
---------- ----------
c1 : float c1 : float
Parameter for Armijo condition rule. (Default: 1e-4) Parameter for Armijo condition rule. (Default: 1e-4)
c2 : float c2 : float
Parameter for curvature condition rule. (Default: 0.9) Parameter for curvature condition rule. (Default: 0.9)
max_step_size : float max_step_size : float
Maximum step allowed in to be made in the descent direction. Maximum step allowed in to be made in the descent direction.
(Default: 50) (Default: 50)
max_iterations : integer max_iterations : integer
Maximum number of iterations performed by the line search algorithm. Maximum number of iterations performed by the line search algorithm.
(Default: 10) (Default: 10)
max_zoom_iterations : integer max_zoom_iterations : integer
Maximum number of iterations performed by the zoom algorithm. Maximum number of iterations performed by the zoom algorithm.
(Default: 10) (Default: 10)
Attributes Attributes
---------- ----------
c1 : float c1 : float
...@@ -53,19 +53,18 @@ class LineSearchStrongWolfe(LineSearch): ...@@ -53,19 +53,18 @@ class LineSearchStrongWolfe(LineSearch):
c2 : float c2 : float
Parameter for curvature condition rule. Parameter for curvature condition rule.
max_step_size : float max_step_size : float
Maximum step allowed in to be made in the descent direction. Maximum step allowed in to be made in the descent direction.
max_iterations : integer max_iterations : integer
Maximum number of iterations performed by the line search algorithm. Maximum number of iterations performed by the line search algorithm.
max_zoom_iterations : integer max_zoom_iterations : integer
Maximum number of iterations performed by the zoom algorithm. Maximum number of iterations performed by the zoom algorithm.
""" """
def __init__(self, c1=1e-4, c2=0.9, def __init__(self, c1=1e-4, c2=0.9,
max_step_size=50, max_iterations=10, max_step_size=50, max_iterations=10,
max_zoom_iterations=10): max_zoom_iterations=10):
super(LineSearchStrongWolfe, self).__init__() super(LineSearchStrongWolfe, self).__init__()
self.c1 = np.float(c1) self.c1 = np.float(c1)
...@@ -76,11 +75,11 @@ class LineSearchStrongWolfe(LineSearch): ...@@ -76,11 +75,11 @@ class LineSearchStrongWolfe(LineSearch):
def perform_line_search(self, energy, pk, f_k_minus_1=None): def perform_line_search(self, energy, pk, f_k_minus_1=None):
"""Performs the first stage of the algorithm. """Performs the first stage of the algorithm.
It starts with a trial step size and it keeps increasing it until it It starts with a trial step size and it keeps increasing it until it
satisfy the strong Wolf conditions. It also performs the descent and satisfy the strong Wolf conditions. It also performs the descent and
returns the optimal step length and the new enrgy. returns the optimal step length and the new enrgy.
Parameters Parameters
---------- ----------
energy : Energy object energy : Energy object
...@@ -89,9 +88,9 @@ class LineSearchStrongWolfe(LineSearch): ...@@ -89,9 +88,9 @@ class LineSearchStrongWolfe(LineSearch):
pk : Field pk : Field
Unit vector pointing into the search direction. Unit vector pointing into the search direction.
f_k_minus_1 : float f_k_minus_1 : float
Value of the fuction (which is being minimized) at the k-1 Value of the fuction (which is being minimized) at the k-1
iteration of the line search procedure. (Default: None) iteration of the line search procedure. (Default: None)
Returns Returns
------- -------