# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see .
#
# Copyright(C) 2013-2017 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
import abc
from ..domain_object import DomainObject
class Space(DomainObject):
"""The abstract base class for all NIFTy spaces.
An instance of a space contains information about the manifold's
geometry and enhances the functionality of DomainObject by methods that
are needed for power spectrum analysis and smoothing.
"""
def __init__(self):
super(Space, self).__init__()
@abc.abstractproperty
def harmonic(self):
""" Returns True iff this space is a harmonic space."""
raise NotImplementedError
def get_k_length_array(self):
"""The length of the k vector for every pixel.
This method is only implemented for harmonic spaces.
Returns
-------
Field
An array containing the k vector lengths
"""
raise NotImplementedError
def get_unique_k_lengths(self):
""" Returns an array of floats containing the unique k vector lengths
for this space.
This method is only implemented for harmonic spaces.
"""
raise NotImplementedError
def get_fft_smoothing_kernel_function(self, sigma):
"""This method returns a smoothing kernel function.
This method, which is only implemented for harmonic spaces, helps
smoothing fields that live in a position space that has this space as
its harmonic space. The returned function multiplies field values of a
field with a zero centered Gaussian which corresponds to a convolution
with a Gaussian kernel and sigma standard deviation in position space.
Parameters
----------
sigma : float
A real number representing a physical scale on which the smoothing
takes place. The smoothing is defined with respect to the real
physical field and points that are closer together than one sigma
are blurred together. Mathematically sigma is the standard
deviation of a convolution with a normalized, zero-centered
Gaussian that takes place in position space.
Returns
-------
function (array-like -> array-like)
A smoothing operation that multiplies values with a Gaussian
kernel.
"""
raise NotImplementedError