log_rg_space.py 3.21 KB
Newer Older
Martin Reinecke's avatar
Martin Reinecke committed
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18
# 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) 2013-2018 Max-Planck-Society
#
# NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik
# and financially supported by the Studienstiftung des deutschen Volkes.

19
from __future__ import absolute_import, division, print_function
Philipp Arras's avatar
Philipp Arras committed
20

21
import numpy as np
Philipp Arras's avatar
Philipp Arras committed
22

23
from .. import dobj
Philipp Arras's avatar
Philipp Arras committed
24
from ..compat import *
25
from ..field import Field
Philipp Arras's avatar
Philipp Arras committed
26
from ..sugar import exp
27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70
from .structured_domain import StructuredDomain


class LogRGSpace(StructuredDomain):

    _needed_for_hash = ['_shape', '_bindistances', '_t_0', '_harmonic']

    def __init__(self, shape, bindistances, t_0, harmonic=False):
        self._harmonic = bool(harmonic)

        if np.isscalar(shape):
            shape = (shape,)
        self._shape = tuple(int(i) for i in shape)

        self._bindistances = tuple(bindistances)
        self._t_0 = tuple(t_0)

        self._dim = int(reduce(lambda x, y: x * y, self._shape))
        self._dvol = float(reduce(lambda x, y: x * y, self._bindistances))

    @property
    def harmonic(self):
        return self._harmonic

    @property
    def shape(self):
        return self._shape

    def scalar_dvol(self):
        return self._dvol

    @property
    def bindistances(self):
        return np.array(self._bindistances)

    @property
    def size(self):
        return np.prod(self._shape)

    @property
    def t_0(self):
        return np.array(self._t_0)

    def __repr__(self):
Martin Reinecke's avatar
Martin Reinecke committed
71 72
        return ("LogRGSpace(shape={}, harmonic={})"
                .format(self.shape, self.harmonic))
73 74 75 76

    def get_default_codomain(self):
        codomain_bindistances = 1. / (self.bindistances * self.shape)
        return LogRGSpace(self.shape, codomain_bindistances,
Martin Reinecke's avatar
Martin Reinecke committed
77
                          self._t_0, True)
78 79

    def get_k_length_array(self):
80 81
        ib = dobj.ibegin_from_shape(self._shape)
        res = np.arange(self.local_shape[0], dtype=np.float64) + ib[0]
82 83
        res = np.minimum(res, self.shape[0]-res)*self.bindistances[0]
        if len(self.shape) == 1:
84
            return Field.from_local_data(self, res)
85 86
        res *= res
        for i in range(1, len(self.shape)):
87
            tmp = np.arange(self.local_shape[i], dtype=np.float64) + ib[i]
88 89 90
            tmp = np.minimum(tmp, self.shape[i]-tmp)*self.bindistances[i]
            tmp *= tmp
            res = np.add.outer(res, tmp)
91
        return Field.from_local_data(self, np.sqrt(res))
92 93 94

    def get_expk_length_array(self):
        # FIXME This is a hack! Only for plotting. Seems not to be the final version.
95
        out = exp(self.get_k_length_array()).to_global_data_rw()
96 97 98
        out[1:] = out[:-1]
        out[0] = 0
        return Field.from_global_data(self, out)