# 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) 2013-2020 Max-Planck-Society # Authors: Philipp Arras # # NIFTy is being developed at the Max-Planck-Institut fuer Astrophysik. import numpy as np from ..domains.power_space import PowerSpace from ..operators.adder import Adder from ..operators.contraction_operator import ContractionOperator from ..operators.distributors import PowerDistributor from ..operators.harmonic_operators import HarmonicTransformOperator from ..operators.normal_operators import LognormalTransform, NormalTransform from .correlated_fields import _TwoLogIntegrations from ..operators.operator import Operator from ..operators.simple_linear_operators import ducktape from ..operators.value_inserter import ValueInserter from ..sugar import full, makeField, makeOp from .correlated_fields import (_log_vol, _Normalization, _relative_log_k_lengths, _SlopeRemover) class SimpleCorrelatedField(Operator): def __init__(self, target, offset_mean, offset_std_mean, offset_std_std, fluctuations_mean, fluctuations_stddev, flexibility_mean, flexibility_stddev, asperity_mean, asperity_stddev, loglogavgslope_mean, loglogavgslope_stddev, prefix='', harmonic_partner=None): if harmonic_partner is None: harmonic_partner = target.get_default_codomain() else: target.check_codomain(harmonic_partner) harmonic_partner.check_codomain(target) fluct = LognormalTransform(fluctuations_mean, fluctuations_stddev, prefix + 'fluctuations', 0) flex = LognormalTransform(flexibility_mean, flexibility_stddev, prefix + 'flexibility', 0) asp = LognormalTransform(asperity_mean, asperity_stddev, prefix + 'asperity', 0) avgsl = NormalTransform(loglogavgslope_mean, loglogavgslope_stddev, prefix + 'loglogavgslope', 0) zm = LognormalTransform(offset_std_mean, offset_std_std, prefix + 'zeromode', 0) pspace = PowerSpace(harmonic_partner) twolog = _TwoLogIntegrations(pspace) dom = twolog.domain[0] vflex = np.zeros(dom.shape) vasp = np.zeros(dom.shape, dtype=np.float64) shift = np.ones(dom.shape, dtype=np.float64) vflex[0] = vflex[1] = np.sqrt(_log_vol(pspace)) vasp[0] = 1 shift[0] = _log_vol(pspace)**2/12. vflex = makeOp(makeField(dom, vflex)) vasp = makeOp(makeField(dom, vasp)) shift = makeField(dom, shift) vslope = makeOp(makeField(pspace, _relative_log_k_lengths(pspace))) expander = ContractionOperator(twolog.domain, 0).adjoint ps_expander = ContractionOperator(pspace, 0).adjoint slope = vslope @ ps_expander @ avgsl sig_flex = vflex @ expander @ flex sig_asp = vasp @ expander @ asp xi = ducktape(dom, None, prefix + 'spectrum') smooth = xi*sig_flex*(Adder(shift) @ sig_asp).ptw("sqrt") smooth = _SlopeRemover(pspace, 0) @ twolog @ smooth op = _Normalization(pspace, 0) @ (slope + smooth) maskzm = np.ones(pspace.shape) maskzm[0] = 0 maskzm = makeOp(makeField(pspace, maskzm)) insert = ValueInserter(pspace, (0,)) a = (maskzm @ ((ps_expander @ fluct)*op)) + insert(zm) self._a = a.scale(target.total_volume) ht = HarmonicTransformOperator(harmonic_partner, target) pd = PowerDistributor(harmonic_partner, pspace) xi = ducktape(harmonic_partner, None, prefix + 'xi') op = ht(pd(self._a)*xi) if offset_mean is not None: op = Adder(full(op.target, float(offset_mean))) @ op self.apply = op.apply self._domain = op.domain self._target = op.target