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https://github.com/cosmo-sims/monofonIC.git
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652 lines
24 KiB
C++
652 lines
24 KiB
C++
// This file is part of monofonIC (MUSIC2)
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// A software package to generate ICs for cosmological simulations
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// Copyright (C) 2020 by Oliver Hahn
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//
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// monofonIC is free software: you can redistribute it and/or modify
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// it under the terms of the GNU General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// monofonIC is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU General Public License for more details.
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//
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// You should have received a copy of the GNU General Public License
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// along with this program. If not, see <http://www.gnu.org/licenses/>.
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#pragma once
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#include <array>
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#include <general.hh>
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#include <grid_fft.hh>
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/// @brief base class for convolutions of two or three fields
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/// @tparam data_t
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/// @tparam derived_t
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template <typename data_t, typename derived_t>
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class BaseConvolver
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{
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protected:
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std::array<size_t, 3> np_;
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std::array<real_t, 3> length_;
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public:
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/// @brief Construct a new Base Convolver object
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/// @param N linear grid size
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/// @param L physical box size
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BaseConvolver(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L)
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: np_(N), length_(L) {}
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/// @brief Construct a new Base Convolver object [deleted copy constructor]
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BaseConvolver( const BaseConvolver& ) = delete;
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/// @brief destructor (virtual)
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virtual ~BaseConvolver() {}
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/// @brief implements convolution of two Fourier-space fields
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/// @tparam kfunc1 field 1
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/// @tparam kfunc2 field 2
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/// @tparam opp output operator
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template <typename kfunc1, typename kfunc2, typename opp>
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void convolve2(kfunc1 kf1, kfunc2 kf2, opp op) {}
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/// @brief implements convolution of three Fourier-space fields
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/// @tparam kfunc1 field 1
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/// @tparam kfunc2 field 2
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/// @tparam kfunc3 field 3
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/// @tparam opp output operator
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template <typename kfunc1, typename kfunc2, typename kfunc3, typename opp>
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void convolve3(kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp op) {}
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public:
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/// @brief convolve two gradient fields in Fourier space a_{,i} * b_{,j}
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/// @tparam opp output operator type
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/// @param inl left input field a
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/// @param d1l direction of first gradient (,i)
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/// @param inr right input field b
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/// @param d1r direction of second gradient (,j)
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/// @param output_op output operator
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template <typename opp>
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void convolve_Gradients(Grid_FFT<data_t> &inl, const std::array<int, 1> &d1l,
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Grid_FFT<data_t> &inr, const std::array<int, 1> &d1r,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of two gradients
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static_cast<derived_t &>(*this).convolve2(
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// first gradient
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[&inl,&d1l](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inl.gradient(d1l[0],{i,j,k});
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return grad1*inl.kelem(i, j, k);
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},
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// second gradient
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[&inr,&d1r](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inr.gradient(d1r[0],{i,j,k});
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return grad1*inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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/// @brief convolve a gradient and a Hessian field in Fourier space a_{,i} * b_{,jk}
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/// @tparam opp output operator type
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/// @param inl left input field a
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/// @param d1l direction of gradient (,i)
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/// @param inr right input field b
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/// @param d2r directions of Hessian (,jk)
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/// @param output_op output operator
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template <typename opp>
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void convolve_Gradient_and_Hessian(Grid_FFT<data_t> &inl, const std::array<int, 1> &d1l,
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Grid_FFT<data_t> &inr, const std::array<int, 2> &d2r,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of gradient and Hessian
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static_cast<derived_t &>(*this).convolve2(
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// gradient
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[&](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto kk = inl.template get_k<real_t>(i, j, k);
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return ccomplex_t(0.0, -kk[d1l[0]]) * inl.kelem(i, j, k);
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},
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// Hessian
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[&](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto kk = inr.template get_k<real_t>(i, j, k);
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return -kk[d2r[0]] * kk[d2r[1]] * inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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/// @brief convolve two Hessian fields in Fourier space a_{,ij} * b_{,kl}
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/// @tparam opp output operator type
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/// @param inl left input field a
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/// @param d2l directions of first Hessian (,ij)
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/// @param inr right input field b
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/// @param d2r directions of second Hessian (,kl)
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/// @param output_op output operator
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template <typename opp>
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void convolve_Hessians(Grid_FFT<data_t> &inl, const std::array<int, 2> &d2l,
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Grid_FFT<data_t> &inr, const std::array<int, 2> &d2r,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t &>(*this).convolve2(
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// first Hessian
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[&inl,&d2l](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inl.gradient(d2l[0],{i,j,k});
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auto grad2 = inl.gradient(d2l[1],{i,j,k});
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return grad1*grad2*inl.kelem(i, j, k);
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},
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// second Hessian
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[&inr,&d2r](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inr.gradient(d2r[0],{i,j,k});
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auto grad2 = inr.gradient(d2r[1],{i,j,k});
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return grad1*grad2*inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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/// @brief convolve three Hessian fields in Fourier space a_{,ij} * b_{,kl} * c_{,mn}
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/// @tparam opp output operator
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/// @param inl first input field a
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/// @param d2l directions of first Hessian (,ij)
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/// @param inm second input field b
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/// @param d2m directions of second Hessian (,kl)
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/// @param inr third input field c
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/// @param d2r directions of third Hessian (,mn)
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/// @param output_op output operator
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template <typename opp>
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void convolve_Hessians(Grid_FFT<data_t> &inl, const std::array<int, 2> &d2l,
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Grid_FFT<data_t> &inm, const std::array<int, 2> &d2m,
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Grid_FFT<data_t> &inr, const std::array<int, 2> &d2r,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inm.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t &>(*this).convolve3(
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// first Hessian
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[&inl, &d2l](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inl.gradient(d2l[0],{i,j,k});
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auto grad2 = inl.gradient(d2l[1],{i,j,k});
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return grad1*grad2*inl.kelem(i, j, k);
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},
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// second Hessian
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[&inm, &d2m](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inm.gradient(d2m[0],{i,j,k});
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auto grad2 = inm.gradient(d2m[1],{i,j,k});
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return grad1*grad2*inm.kelem(i, j, k);
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},
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// third Hessian
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[&inr, &d2r](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inr.gradient(d2r[0],{i,j,k});
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auto grad2 = inr.gradient(d2r[1],{i,j,k});
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return grad1*grad2*inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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/// @brief convolve Hessian field with sum of two Hessian fields in Fourier space a_{,ij} * (b_{,kl} + c_{,mn})
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/// @tparam opp output operator type
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/// @param inl left input field a
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/// @param d2l directions of first Hessian (,ij)
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/// @param inr right input field b
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/// @param d2r1 directions of second Hessian (,kl)
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/// @param d2r2 directions of third Hessian (,mn)
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/// @param output_op output operator
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template <typename opp>
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void convolve_SumOfHessians(Grid_FFT<data_t> &inl, const std::array<int, 2> &d2l,
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Grid_FFT<data_t> &inr, const std::array<int, 2> &d2r1, const std::array<int, 2> &d2r2,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t &>(*this).convolve2(
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// first Hessian
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[&inl, &d2l](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inl.gradient(d2l[0],{i,j,k});
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auto grad2 = inl.gradient(d2l[1],{i,j,k});
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return grad1*grad2*inl.kelem(i, j, k);
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},
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// second two Hessian and sum
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[&inr, &d2r1, &d2r2](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad11 = inr.gradient(d2r1[0],{i,j,k});
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auto grad12 = inr.gradient(d2r1[1],{i,j,k});
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auto grad21 = inr.gradient(d2r2[0],{i,j,k});
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auto grad22 = inr.gradient(d2r2[1],{i,j,k});
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return (grad11*grad12+grad21*grad22)*inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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/// @brief convolve Hessian field with difference of two Hessian fields in Fourier space a_{,ij} * (b_{,kl} - c_{,mn})
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/// @tparam opp output operator type
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/// @param inl left input field a
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/// @param d2l directions of first Hessian (,ij)
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/// @param inr right input field b
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/// @param d2r1 directions of second Hessian (,kl)
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/// @param d2r2 directions of third Hessian (,mn)
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/// @param output_op output operator
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template <typename opp>
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void convolve_DifferenceOfHessians(Grid_FFT<data_t> &inl, const std::array<int, 2> &d2l,
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Grid_FFT<data_t> &inr, const std::array<int, 2> &d2r1, const std::array<int, 2> &d2r2,
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opp output_op)
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{
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// transform to FS in case fields are not
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inl.FourierTransformForward();
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inr.FourierTransformForward();
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// perform convolution of Hessians
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static_cast<derived_t &>(*this).convolve2(
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// first Hessian
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[&inl, &d2l](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad1 = inl.gradient(d2l[0],{i,j,k});
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auto grad2 = inl.gradient(d2l[1],{i,j,k});
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return grad1*grad2*inl.kelem(i, j, k);
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},
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// second two Hessian and difference
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[&inr, &d2r1, &d2r2](size_t i, size_t j, size_t k) -> ccomplex_t {
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auto grad11 = inr.gradient(d2r1[0],{i,j,k});
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auto grad12 = inr.gradient(d2r1[1],{i,j,k});
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auto grad21 = inr.gradient(d2r2[0],{i,j,k});
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auto grad22 = inr.gradient(d2r2[1],{i,j,k});
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return (grad11*grad12-grad21*grad22)*inr.kelem(i, j, k);
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},
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// -> output operator
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output_op);
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}
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};
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//! low-level implementation of convolutions -- naive convolution class, ignoring aliasing (no padding)
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template <typename data_t>
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class NaiveConvolver : public BaseConvolver<data_t, NaiveConvolver<data_t>>
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{
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protected:
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/// @brief buffer for Fourier transformed fields
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Grid_FFT<data_t> *fbuf1_, *fbuf2_;
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/// @brief number of points in each direction
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using BaseConvolver<data_t, NaiveConvolver<data_t>>::np_;
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/// @brief length of each direction
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using BaseConvolver<data_t, NaiveConvolver<data_t>>::length_;
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public:
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/// @brief constructor
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/// @param N number of points in each direction
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/// @param L length of each direction
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NaiveConvolver(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L)
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: BaseConvolver<data_t, NaiveConvolver<data_t>>(N, L)
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{
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fbuf1_ = new Grid_FFT<data_t>(N, length_, true, kspace_id);
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fbuf2_ = new Grid_FFT<data_t>(N, length_, true, kspace_id);
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}
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/// @brief destructor
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~NaiveConvolver()
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{
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delete fbuf1_;
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delete fbuf2_;
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}
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/// @brief convolution of two fields
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template <typename kfunc1, typename kfunc2, typename opp>
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void convolve2(kfunc1 kf1, kfunc2 kf2, opp output_op)
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{
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//... prepare data 1
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fbuf1_->FourierTransformForward(false);
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this->copy_in(kf1, *fbuf1_);
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//... prepare data 2
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fbuf2_->FourierTransformForward(false);
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this->copy_in(kf2, *fbuf2_);
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//... convolve
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fbuf1_->FourierTransformBackward();
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fbuf2_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i)
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{
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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fbuf2_->FourierTransformForward();
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// fbuf2_->dealias();
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//... copy data back
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf2_->ntot_; ++i)
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{
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output_op(i, (*fbuf2_)[i]);
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}
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}
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/// @brief convolution of three fields
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template <typename kfunc1, typename kfunc2, typename kfunc3, typename opp>
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void convolve3(kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp output_op)
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{
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//... prepare data 1
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fbuf1_->FourierTransformForward(false);
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this->copy_in(kf1, *fbuf1_);
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//... prepare data 2
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fbuf2_->FourierTransformForward(false);
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this->copy_in(kf2, *fbuf2_);
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//... convolve
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fbuf1_->FourierTransformBackward();
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fbuf2_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i)
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{
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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//... prepare data 2
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fbuf1_->FourierTransformForward(false);
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this->copy_in(kf3, *fbuf1_);
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//... convolve
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fbuf1_->FourierTransformBackward();
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf1_->ntot_; ++i)
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{
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(*fbuf2_).relem(i) *= (*fbuf1_).relem(i);
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}
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fbuf2_->FourierTransformForward();
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//... copy data back
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#pragma omp parallel for
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for (size_t i = 0; i < fbuf2_->ntot_; ++i)
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{
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output_op(i, (*fbuf2_)[i]);
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}
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}
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//--------------------------------------------------------------------------------------------------------
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private:
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/// @brief copy data into a grid
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/// @tparam kfunc abstract function type generating data
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/// @param kf abstract function generating data
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/// @param g grid to copy data into
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template <typename kfunc>
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void copy_in(kfunc kf, Grid_FFT<data_t> &g)
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{
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#pragma omp parallel for
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for (size_t i = 0; i < g.size(0); ++i)
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{
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for (size_t j = 0; j < g.size(1); ++j)
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{
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for (size_t k = 0; k < g.size(2); ++k)
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{
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g.kelem(i, j, k) = kf(i, j, k);
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}
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}
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}
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}
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};
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//! convolution class, respecting Orszag's 3/2 rule (padding in Fourier space to avoid aliasing)
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template <typename data_t>
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class OrszagConvolver : public BaseConvolver<data_t, OrszagConvolver<data_t>>
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{
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private:
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/// @brief buffer for Fourier transformed fields
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Grid_FFT<data_t> *f1p_, *f2p_, *fbuf_;
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using BaseConvolver<data_t, OrszagConvolver<data_t>>::np_;
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using BaseConvolver<data_t, OrszagConvolver<data_t>>::length_;
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ccomplex_t *crecvbuf_; //!< receive buffer for MPI (complex)
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real_t *recvbuf_; //!< receive buffer for MPI (real)
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size_t maxslicesz_; //!< maximum size of a slice
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std::vector<ptrdiff_t> offsets_, offsetsp_; //!< offsets for MPI
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std::vector<size_t> sizes_, sizesp_; //!< sizes for MPI
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/// @brief get task index for a given index
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/// @param index index
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/// @param offsets offsets
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/// @param sizes sizes
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/// @param ntasks number of tasks
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int get_task(ptrdiff_t index, const std::vector<ptrdiff_t> &offsets, const std::vector<size_t> &sizes, const int ntasks)
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{
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int itask = 0;
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while (itask < ntasks - 1 && offsets[itask + 1] <= index)
|
|
++itask;
|
|
return itask;
|
|
}
|
|
|
|
public:
|
|
|
|
/// @brief constructor
|
|
/// @param N grid size
|
|
/// @param L grid length
|
|
OrszagConvolver(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L)
|
|
: BaseConvolver<data_t, OrszagConvolver<data_t>>({3 * N[0] / 2, 3 * N[1] / 2, 3 * N[2] / 2}, L)
|
|
{
|
|
//... create temporaries
|
|
f1p_ = new Grid_FFT<data_t>(np_, length_, true, kspace_id);
|
|
f2p_ = new Grid_FFT<data_t>(np_, length_, true, kspace_id);
|
|
fbuf_ = new Grid_FFT<data_t>(N, length_, true, kspace_id); // needed for MPI, or for triple conv.
|
|
|
|
#if defined(USE_MPI)
|
|
maxslicesz_ = f1p_->sizes_[1] * f1p_->sizes_[3] * 2;
|
|
|
|
crecvbuf_ = new ccomplex_t[maxslicesz_ / 2];
|
|
recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);
|
|
|
|
int ntasks(MPI::get_size());
|
|
|
|
offsets_.assign(ntasks, 0);
|
|
offsetsp_.assign(ntasks, 0);
|
|
sizes_.assign(ntasks, 0);
|
|
sizesp_.assign(ntasks, 0);
|
|
|
|
size_t tsize = N[0], tsizep = f1p_->size(0);
|
|
|
|
MPI_Allgather(&fbuf_->local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
|
|
MPI_LONG_LONG, MPI_COMM_WORLD);
|
|
MPI_Allgather(&f1p_->local_1_start_, 1, MPI_LONG_LONG, &offsetsp_[0], 1,
|
|
MPI_LONG_LONG, MPI_COMM_WORLD);
|
|
MPI_Allgather(&tsize, 1, MPI_LONG_LONG, &sizes_[0], 1, MPI_LONG_LONG,
|
|
MPI_COMM_WORLD);
|
|
MPI_Allgather(&tsizep, 1, MPI_LONG_LONG, &sizesp_[0], 1, MPI_LONG_LONG,
|
|
MPI_COMM_WORLD);
|
|
#endif
|
|
}
|
|
|
|
/// @brief destructor
|
|
~OrszagConvolver()
|
|
{
|
|
delete f1p_;
|
|
delete f2p_;
|
|
delete fbuf_;
|
|
#if defined(USE_MPI)
|
|
delete[] crecvbuf_;
|
|
#endif
|
|
}
|
|
|
|
/// @brief convolve two fields
|
|
/// @tparam kfunc1 abstract function type generating data for the first field
|
|
/// @tparam kfunc2 abstract function type generating data for the second field
|
|
/// @tparam opp abstract function type for the output operation
|
|
template <typename kfunc1, typename kfunc2, typename opp>
|
|
void convolve2(kfunc1 kf1, kfunc2 kf2, opp output_op)
|
|
{
|
|
//... prepare data 1
|
|
f1p_->FourierTransformForward(false);
|
|
this->pad_insert(kf1, *f1p_);
|
|
|
|
//... prepare data 2
|
|
f2p_->FourierTransformForward(false);
|
|
this->pad_insert(kf2, *f2p_);
|
|
|
|
//... convolve
|
|
f1p_->FourierTransformBackward();
|
|
f2p_->FourierTransformBackward();
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < f1p_->ntot_; ++i)
|
|
{
|
|
(*f2p_).relem(i) *= (*f1p_).relem(i);
|
|
}
|
|
f2p_->FourierTransformForward();
|
|
//... copy data back
|
|
unpad(*f2p_, output_op);
|
|
}
|
|
|
|
/// @brief convolve three fields
|
|
/// @tparam kfunc1 abstract function type generating data for the first field
|
|
/// @tparam kfunc2 abstract function type generating data for the second field
|
|
/// @tparam kfunc3 abstract function type generating data for the third field
|
|
/// @tparam opp abstract function type for the output operation
|
|
template <typename kfunc1, typename kfunc2, typename kfunc3, typename opp>
|
|
void convolve3(kfunc1 kf1, kfunc2 kf2, kfunc3 kf3, opp output_op)
|
|
{
|
|
auto assign_to = [](auto &g) { return [&](auto i, auto v) { g[i] = v; }; };
|
|
fbuf_->FourierTransformForward(false);
|
|
convolve2(kf1, kf2, assign_to(*fbuf_));
|
|
convolve2([&](size_t i, size_t j, size_t k) -> ccomplex_t { return fbuf_->kelem(i, j, k); }, kf3, output_op);
|
|
}
|
|
|
|
// template< typename opp >
|
|
// void test_pad_unpad( Grid_FFT<data_t> & in, Grid_FFT<data_t> & res, opp op )
|
|
// {
|
|
// //... prepare data 1
|
|
// f1p_->FourierTransformForward(false);
|
|
// this->pad_insert( [&in]( size_t i, size_t j, size_t k ){return in.kelem(i,j,k);}, *f1p_ );
|
|
// f1p_->FourierTransformBackward();
|
|
// f1p_->FourierTransformForward();
|
|
// res.FourierTransformForward();
|
|
// unpad(*f1p_, res, op);
|
|
// }
|
|
|
|
private:
|
|
|
|
/// @brief unpad the result of a convolution and copy it to a grid
|
|
/// @tparam kdep_functor abstract function type generating data for the result
|
|
/// @param kfunc abstract function generating data for the result
|
|
/// @param fp grid to copy the result to
|
|
template <typename kdep_functor>
|
|
void pad_insert( kdep_functor kfunc, Grid_FFT<data_t> &fp)
|
|
{
|
|
const real_t rfac = std::pow(1.5, 1.5);
|
|
|
|
#if !defined(USE_MPI)
|
|
const size_t nhalf[3] = {fp.n_[0] / 3, fp.n_[1] / 3, fp.n_[2] / 3};
|
|
|
|
fp.zero();
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < 2 * fp.size(0) / 3; ++i)
|
|
{
|
|
size_t ip = (i > nhalf[0]) ? i + nhalf[0] : i;
|
|
for (size_t j = 0; j < 2 * fp.size(1) / 3; ++j)
|
|
{
|
|
size_t jp = (j > nhalf[1]) ? j + nhalf[1] : j;
|
|
for (size_t k = 0; k < nhalf[2]+1; ++k)
|
|
{
|
|
size_t kp = (k > nhalf[2]) ? k + nhalf[2] : k;
|
|
fp.kelem(ip, jp, kp) = kfunc(i, j, k) * rfac;
|
|
}
|
|
}
|
|
}
|
|
#else
|
|
fbuf_->FourierTransformForward(false);
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->size(0); ++i)
|
|
{
|
|
for (size_t j = 0; j < fbuf_->size(1); ++j)
|
|
{
|
|
for (size_t k = 0; k < fbuf_->size(2); ++k)
|
|
{
|
|
fbuf_->kelem(i, j, k) = kfunc(i, j, k) * rfac;
|
|
}
|
|
}
|
|
}
|
|
|
|
fbuf_->FourierInterpolateCopyTo( fp );
|
|
|
|
#endif //defined(USE_MPI)
|
|
}
|
|
|
|
/// @brief unpad the result of a convolution and write it to an output operator
|
|
/// @tparam operator_t abstract function type for the output operation
|
|
/// @param fp grid to copy the result from
|
|
/// @param output_op abstract function to write the result to
|
|
template <typename operator_t>
|
|
void unpad( Grid_FFT<data_t> &fp, operator_t output_op)
|
|
{
|
|
const real_t rfac = std::sqrt(fp.n_[0] * fp.n_[1] * fp.n_[2]) / std::sqrt(fbuf_->n_[0] * fbuf_->n_[1] * fbuf_->n_[2]);
|
|
|
|
// make sure we're in Fourier space...
|
|
assert(fp.space_ == kspace_id);
|
|
|
|
#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////
|
|
fbuf_->FourierTransformForward(false);
|
|
size_t nhalf[3] = {fbuf_->n_[0] / 2, fbuf_->n_[1] / 2, fbuf_->n_[2] / 2};
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->size(0); ++i)
|
|
{
|
|
size_t ip = (i > nhalf[0]) ? i + nhalf[0] : i;
|
|
for (size_t j = 0; j < fbuf_->size(1); ++j)
|
|
{
|
|
size_t jp = (j > nhalf[1]) ? j + nhalf[1] : j;
|
|
for (size_t k = 0; k < fbuf_->size(2); ++k)
|
|
{
|
|
size_t kp = (k > nhalf[2]) ? k + nhalf[2] : k;
|
|
fbuf_->kelem(i, j, k) = fp.kelem(ip, jp, kp) / rfac;
|
|
// zero Nyquist modes since they are not unique after convolution
|
|
if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]){
|
|
fbuf_->kelem(i, j, k) = 0.0;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
//... copy data back
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->ntot_; ++i)
|
|
{
|
|
output_op(i, (*fbuf_)[i]);
|
|
}
|
|
|
|
#else /// then USE_MPI is defined //////////////////////////////////////////////////////////////
|
|
|
|
fp.FourierInterpolateCopyTo( *fbuf_ );
|
|
|
|
//... copy data back
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < fbuf_->ntot_; ++i)
|
|
{
|
|
|
|
output_op(i, (*fbuf_)[i] / rfac);
|
|
}
|
|
|
|
#endif //defined(USE_MPI)
|
|
}
|
|
};
|