# 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) 2013-2019 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.
from .. import dobj
from .. import fft
from ..domain_tuple import DomainTuple
from ..field import Field
from ..utilities import infer_space
from .linear_operator import LinearOperator
class QHTOperator(LinearOperator):
"""
Does a Hartley transform on LogRGSpace
This operator takes a field on a LogRGSpace and transforms it
according to the Hartley transform. The zero modes are not transformed
because they are infinitely far away.
Parameters
----------
target : domain, tuple of domains or DomainTuple
The full output domain
space : int
The index of the domain on which the operator acts.
target[space] must be a nonharmonic LogRGSpace.
"""
def __init__(self, target, space=0):
self._target = DomainTuple.make(target)
self._space = infer_space(self._target, space)
from ..domains.log_rg_space import LogRGSpace
if not isinstance(self._target[self._space], LogRGSpace):
raise ValueError("target[space] has to be a LogRGSpace!")
if self._target[self._space].harmonic:
raise TypeError("target[space] must be a nonharmonic space")
self._domain = [dom for dom in self._target]
self._domain[self._space] = \
self._target[self._space].get_default_codomain()
self._domain = DomainTuple.make(self._domain)
self._capability = self.TIMES | self.ADJOINT_TIMES
def apply(self, x, mode):
self._check_input(x, mode)
dom = self._domain[self._space]
v = x.val * dom.scalar_dvol
n = self._domain.axes[self._space]
rng = n if mode == self.TIMES else reversed(n)
for i in rng:
sl = (slice(None),)*i + (slice(1, None),)
v, tmp = dobj.ensure_not_distributed(v, (i,))
tmp[sl] = fft.hartley(tmp[sl], axes=(i,))
return Field(self._tgt(mode), dobj.ensure_default_distributed(v))