Source code for nifty8.operators.field_zero_padder

# 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 <http://www.gnu.org/licenses/>.
#
# Copyright(C) 2013-2019 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik.

import numpy as np

from .. import utilities
from ..domain_tuple import DomainTuple
from ..domains.rg_space import RGSpace
from ..field import Field
from .linear_operator import LinearOperator




class FieldZeroPadder(LinearOperator):
    """Operator which applies zero-padding to one of the subdomains of its
    input field

    Parameters
    ----------
    domain : Domain, DomainTuple or tuple of Domain
        The operator's input domain.
    new_shape : list or tuple of int
        The new dimensions of the subdomain which is zero-padded.
        No entry must be smaller than the corresponding dimension in the
        operator's domain.
    space : int
        The index of the subdomain to be zero-padded. If None, it is set to 0
        if domain contains exactly one space. domain[space] must be an RGSpace.
    central : bool
        If `False`, padding is performed at the end of the domain axes,
        otherwise in the middle.

    Notes
    -----
    When doing central padding on an axis with an even length, the "central"
    entry should in principle be split up; this is currently not done.
    """


    def __init__(self, domain, new_shape, space=0, central=False):
        self._domain = DomainTuple.make(domain)
        self._space = utilities.infer_space(self._domain, space)
        self._central = central
        dom = self._domain[self._space]
        if not isinstance(dom, RGSpace):
            raise TypeError("RGSpace required")
        if len(new_shape) != len(dom.shape):
            raise ValueError("Shape mismatch")
        if any([a < b for a, b in zip(new_shape, dom.shape)]):
            raise ValueError("New shape must not be smaller than old shape")
        self._target = list(self._domain)
        self._target[self._space] = RGSpace(new_shape, dom.distances,
                                            dom.harmonic)
        self._target = DomainTuple.make(self._target)
        self._capability = self.TIMES | self.ADJOINT_TIMES




    def apply(self, x, mode):
        self._check_input(x, mode)
        v = x.val
        curshp = list(self._dom(mode).shape)
        tgtshp = self._tgt(mode).shape
        for d in self._target.axes[self._space]:
            if v.shape[d] == tgtshp[d]:  # nothing to do
                continue

            idx = (slice(None),) * d

            if mode == self.TIMES:
                shp = list(v.shape)
                shp[d] = tgtshp[d]
                xnew = np.zeros(shp, dtype=v.dtype)
                if self._central:
                    Nyquist = v.shape[d]//2
                    i1 = idx + (slice(0, Nyquist+1),)
                    xnew[i1] = v[i1]
                    i1 = idx + (slice(None, -(Nyquist+1), -1),)
                    xnew[i1] = v[i1]
#                     if (v.shape[d] & 1) == 0:  # even number of pixels
#                         i1 = idx+(Nyquist,)
#                         xnew[i1] *= 0.5
#                         i1 = idx+(-Nyquist,)
#                         xnew[i1] *= 0.5
                else:
                    xnew[idx + (slice(0, v.shape[d]),)] = v
            else:  # ADJOINT_TIMES
                if self._central:
                    shp = list(v.shape)
                    shp[d] = tgtshp[d]
                    xnew = np.zeros(shp, dtype=v.dtype)
                    Nyquist = xnew.shape[d]//2
                    i1 = idx + (slice(0, Nyquist+1),)
                    xnew[i1] = v[i1]
                    i1 = idx + (slice(None, -(Nyquist+1), -1),)
                    xnew[i1] += v[i1]
#                     if (xnew.shape[d] & 1) == 0:  # even number of pixels
#                         i1 = idx+(Nyquist,)
#                         xnew[i1] *= 0.5
                else:
                    xnew = v[idx + (slice(0, tgtshp[d]),)]

            curshp[d] = xnew.shape[d]
            v = xnew
        return Field(self._tgt(mode), v)