# 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) 2013-2018 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.
from __future__ import absolute_import, division, print_function
from ..compat import *
from .linear_operator import LinearOperator
import numpy as np
class EndomorphicOperator(LinearOperator):
""" NIFTy class for endomorphic operators.
The NIFTy EndomorphicOperator class is a class derived from the
LinearOperator. By definition, domain and target are the same in
EndomorphicOperator.
"""
@property
def target(self):
"""DomainTuple : returns :attr:`domain`
Returns `self.domain`, because this is also the target domain
for endomorphic operators."""
return self.domain
def draw_sample(self, from_inverse=False, dtype=np.float64):
"""Generate a zero-mean sample
Generates a sample from a Gaussian distribution with zero mean and
covariance given by the operator.
Parameters
----------
from_inverse : bool (default : False)
if True, the sample is drawn from the inverse of the operator
dtype : numpy datatype (default : numpy.float64)
the data type to be used for the sample
Returns
-------
Field
A sample from the Gaussian of given covariance.
"""
raise NotImplementedError