mirror of
https://github.com/cosmo-sims/monofonIC.git
synced 2024-09-19 17:03:45 +02:00
655 lines
19 KiB
C++
655 lines
19 KiB
C++
#pragma once
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#include <cmath>
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#include <array>
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#include <vector>
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#include <vec3.hh>
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#include <general.hh>
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#include <bounding_box.hh>
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#include <typeinfo>
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enum space_t
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{
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kspace_id,
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rspace_id
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};
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template <typename data_t>
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class Grid_FFT
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{
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protected:
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#if defined(USE_MPI)
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const MPI_Datatype MPI_data_t_type = (typeid(data_t) == typeid(double)) ? MPI_DOUBLE
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: (typeid(data_t) == typeid(float)) ? MPI_FLOAT
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: (typeid(data_t) == typeid(std::complex<float>)) ? MPI_COMPLEX
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: (typeid(data_t) == typeid(std::complex<double>)) ? MPI_DOUBLE_COMPLEX : MPI_INT;
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#endif
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public:
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std::array<size_t, 3> n_, nhalf_;
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std::array<size_t, 4> sizes_;
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size_t npr_, npc_;
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size_t ntot_;
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std::array<real_t, 3> length_, kfac_, dx_;
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space_t space_;
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data_t *data_;
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ccomplex_t *cdata_;
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bounding_box<size_t> global_range_;
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fftw_plan_t plan_, iplan_;
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real_t fft_norm_fac_;
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ptrdiff_t local_0_start_, local_1_start_;
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ptrdiff_t local_0_size_, local_1_size_;
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Grid_FFT(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L, space_t initialspace = rspace_id)
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: n_(N), length_(L), space_(initialspace), data_(nullptr), cdata_(nullptr)
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{
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//invalidated = true;
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this->Setup();
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}
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// avoid implicit copying of data
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Grid_FFT(const Grid_FFT<data_t> &g) = delete;
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~Grid_FFT()
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{
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if (data_ != nullptr)
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{
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fftw_free(data_);
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}
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}
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const Grid_FFT<data_t>* get_grid( size_t ilevel ) const { return this; }
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void Setup();
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//! return the (local) size of dimension i
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size_t size(size_t i) const { return sizes_[i]; }
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//! return the (global) size of dimension i
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size_t global_size(size_t i) const { return n_[i]; }
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//! return locally stored number of elements of field
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size_t local_size( void ) const { return local_0_size_ * n_[1] * n_[2]; }
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//! return a bounding box of the global extent of the field
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const bounding_box<size_t>& get_global_range( void ) const
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{
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return global_range_;
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}
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//! set all field elements to zero
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void zero()
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{
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#pragma omp parallel for
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for (size_t i = 0; i < ntot_; ++i)
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data_[i] = 0.0;
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}
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void copy_from( const Grid_FFT<data_t>& g ){
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// make sure the two fields are in the same space
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if( g.space_ != this->space_ ){
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if( this->space_ == kspace_id ) this->FourierTransformBackward(false);
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else this->FourierTransformForward(false);
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}
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// make sure the two fields have the same dimensions
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assert( this->n_[0] == g.n_[0] );
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assert( this->n_[1] == g.n_[1] );
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assert( this->n_[2] == g.n_[2] );
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// now we can copy all the data over
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#pragma omp parallel for
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for (size_t i = 0; i < ntot_; ++i)
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data_[i] = g.data_[i];
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}
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data_t& operator[]( size_t i ){
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return data_[i];
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}
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data_t &relem(size_t i, size_t j, size_t k)
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{
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size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
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return data_[idx];
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}
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const data_t &relem(size_t i, size_t j, size_t k) const
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{
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size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
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return data_[idx];
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}
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ccomplex_t &kelem(size_t i, size_t j, size_t k)
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{
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size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
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return cdata_[idx];
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}
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const ccomplex_t &kelem(size_t i, size_t j, size_t k) const
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{
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size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
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return cdata_[idx];
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}
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ccomplex_t &kelem(size_t idx) { return cdata_[idx]; }
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const ccomplex_t &kelem(size_t idx) const { return cdata_[idx]; }
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data_t &relem(size_t idx) { return data_[idx]; }
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const data_t &relem(size_t idx) const { return data_[idx]; }
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size_t get_idx(size_t i, size_t j, size_t k) const
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{
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return (i * sizes_[1] + j) * sizes_[3] + k;
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}
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template <typename ft>
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vec3<ft> get_r(const size_t i, const size_t j, const size_t k) const
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{
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vec3<ft> rr;
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rr[0] = real_t(i + local_0_start_) * dx_[0];
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rr[1] = real_t(j) * dx_[1];
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rr[2] = real_t(k) * dx_[2];
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return rr;
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}
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template <typename ft>
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vec3<ft> get_unit_r(const size_t i, const size_t j, const size_t k) const
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{
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vec3<ft> rr;
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rr[0] = real_t(i + local_0_start_) / real_t(n_[0]);
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rr[1] = real_t(j) / real_t(n_[1]);
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rr[2] = real_t(k) / real_t(n_[2]);
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return rr;
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}
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template <typename ft>
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vec3<ft> get_unit_r_staggered(const size_t i, const size_t j, const size_t k) const
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{
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vec3<ft> rr;
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rr[0] = (real_t(i + local_0_start_)+0.5) / real_t(n_[0]);
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rr[1] = (real_t(j)+0.5) / real_t(n_[1]);
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rr[2] = (real_t(k)+0.5) / real_t(n_[2]);
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return rr;
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}
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void cell_pos( int ilevel, size_t i, size_t j, size_t k, double* x ) const {
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x[0] = double(i+local_0_start_)/size(0);
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x[1] = double(j)/size(1);
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x[2] = double(k)/size(2);
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}
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size_t count_leaf_cells( int, int ) const {
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return n_[0]*n_[1]*n_[2];
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}
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real_t get_dx( int idim ) const{
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return dx_[idim];
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}
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const std::array<real_t, 3>& get_dx( void ) const{
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return dx_;
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}
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template <typename ft>
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vec3<ft> get_k(const size_t i, const size_t j, const size_t k) const
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{
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vec3<ft> kk;
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#if defined(USE_MPI)
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auto ip = i + local_1_start_;
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kk[0] = (real_t(j) - real_t(j > nhalf_[0]) * n_[0]) * kfac_[0];
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kk[1] = (real_t(ip) - real_t(ip > nhalf_[1]) * n_[1]) * kfac_[1];
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#else
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kk[0] = (real_t(i) - real_t(i > nhalf_[0]) * n_[0]) * kfac_[0];
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kk[1] = (real_t(j) - real_t(j > nhalf_[1]) * n_[1]) * kfac_[1];
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#endif
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kk[2] = (real_t(k) - real_t(k > nhalf_[2]) * n_[2]) * kfac_[2];
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return kk;
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}
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Grid_FFT<data_t>& operator*=( data_t x ){
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if( space_ == kspace_id){
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this->apply_function_k( [&]( ccomplex_t& f ){ return f*x; } );
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}else{
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this->apply_function_r( [&]( data_t& f ){ return f*x; } );
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}
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return *this;
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}
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Grid_FFT<data_t>& operator/=( data_t x ){
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if( space_ == kspace_id){
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this->apply_function_k( [&]( ccomplex_t& f ){ return f/x; } );
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}else{
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this->apply_function_r( [&]( data_t& f ){ return f/x; } );
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}
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return *this;
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}
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Grid_FFT<data_t>& apply_Laplacian( void ){
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this->FourierTransformForward();
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this->apply_function_k_dep([&](auto x, auto k) {
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real_t kmod2 = k.norm_squared();
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return -x*kmod2;
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});
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this->zero_DC_mode();
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return *this;
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}
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Grid_FFT<data_t>& apply_negative_Laplacian( void ){
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this->FourierTransformForward();
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this->apply_function_k_dep([&](auto x, auto k) {
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real_t kmod2 = k.norm_squared();
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return x*kmod2;
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});
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this->zero_DC_mode();
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return *this;
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}
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Grid_FFT<data_t>& apply_InverseLaplacian( void ){
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this->FourierTransformForward();
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this->apply_function_k_dep([&](auto x, auto k) {
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real_t kmod2 = k.norm_squared();
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return -x/kmod2;
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});
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this->zero_DC_mode();
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return *this;
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}
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template <typename functional>
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void apply_function_k(const functional &f)
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{
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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auto &elem = this->kelem(i, j, k);
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elem = f(elem);
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}
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}
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}
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}
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template <typename functional>
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void apply_function_r(const functional &f)
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{
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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auto &elem = this->relem(i, j, k);
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elem = f(elem);
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}
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}
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}
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}
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double compute_2norm(void)
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{
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real_t sum1{0.0};
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#pragma omp parallel for reduction(+ : sum1)
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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const auto re = std::real(this->relem(i, j, k));
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const auto im = std::imag(this->relem(i, j, k));
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sum1 += re * re + im * im;
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}
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}
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}
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sum1 /= sizes_[0] * sizes_[1] * sizes_[2];
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return sum1;
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}
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double std(void)
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{
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double sum1{0.0}, sum2{0.0};
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size_t count{0};
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#pragma omp parallel for reduction(+ : sum1, sum2)
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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const auto elem = std::real(this->relem(i, j, k));
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sum1 += elem;
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sum2 += elem * elem;
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}
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}
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}
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count = sizes_[0] * sizes_[1] * sizes_[2];
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#ifdef USE_MPI
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double globsum1{0.0}, globsum2{0.0};
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size_t globcount{0};
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MPI_Allreduce( reinterpret_cast<const void*>(&sum1),
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reinterpret_cast<void*>(&globsum1),
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1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
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MPI_Allreduce( reinterpret_cast<const void*>(&sum2),
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reinterpret_cast<void*>(&globsum2),
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1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
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MPI_Allreduce( reinterpret_cast<const void*>(&count),
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reinterpret_cast<void*>(&globcount),
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1, MPI_UNSIGNED_LONG_LONG, MPI_SUM, MPI_COMM_WORLD );
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sum1 = globsum1;
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sum2 = globsum2;
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count = globcount;
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#endif
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sum1 /= count;
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sum2 /= count;
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return std::sqrt(sum2 - sum1 * sum1);
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}
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double mean(void)
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{
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double sum1{0.0};
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size_t count{0};
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#pragma omp parallel for reduction(+ : sum1)
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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const auto elem = std::real(this->relem(i, j, k));
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sum1 += elem;
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}
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}
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}
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count = sizes_[0] * sizes_[1] * sizes_[2];
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#ifdef USE_MPI
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double globsum1{0.0};
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size_t globcount{0};
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MPI_Allreduce( reinterpret_cast<const void*>(&sum1),
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reinterpret_cast<void*>(&globsum1),
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1, MPI_DOUBLE, MPI_SUM, MPI_COMM_WORLD );
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MPI_Allreduce( reinterpret_cast<const void*>(&count),
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reinterpret_cast<void*>(&globcount),
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1, MPI_UNSIGNED_LONG_LONG, MPI_SUM, MPI_COMM_WORLD );
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sum1 = globsum1;
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count = globcount;
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#endif
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sum1 /= count;
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return sum1;
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}
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template <typename functional, typename grid_t>
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void assign_function_of_grids_r(const functional &f, const grid_t &g)
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{
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assert(g.size(0) == size(0) && g.size(1) == size(1)); // && g.size(2) == size(2) );
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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auto &elem = this->relem(i, j, k);
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const auto &elemg = g.relem(i, j, k);
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elem = f(elemg);
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}
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}
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}
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}
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template <typename functional, typename grid1_t, typename grid2_t>
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void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2)
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{
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assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
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assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.size(2) == size(2));
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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//auto idx = this->get_idx(i,j,k);
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auto &elem = this->relem(i, j, k);
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const auto &elemg1 = g1.relem(i, j, k);
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const auto &elemg2 = g2.relem(i, j, k);
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elem = f(elemg1, elemg2);
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}
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}
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}
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}
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template <typename functional, typename grid1_t, typename grid2_t, typename grid3_t>
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void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2, const grid3_t &g3)
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{
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assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
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assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.size(2) == size(2));
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assert(g3.size(0) == size(0) && g3.size(1) == size(1)); // && g3.size(2) == size(2));
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
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{
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for (size_t k = 0; k < sizes_[2]; ++k)
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{
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//auto idx = this->get_idx(i,j,k);
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auto &elem = this->relem(i, j, k);
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const auto &elemg1 = g1.relem(i, j, k);
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const auto &elemg2 = g2.relem(i, j, k);
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const auto &elemg3 = g3.relem(i, j, k);
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elem = f(elemg1, elemg2, elemg3);
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}
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}
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}
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}
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template <typename functional, typename grid_t>
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void assign_function_of_grids_k(const functional &f, const grid_t &g)
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{
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assert(g.size(0) == size(0) && g.size(1) == size(1)); // && g.size(2) == size(2) );
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#pragma omp parallel for
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for (size_t i = 0; i < sizes_[0]; ++i)
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{
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for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
auto &elem = this->kelem(i, j, k);
|
|
const auto &elemg = g.kelem(i, j, k);
|
|
|
|
elem = f(elemg);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename functional, typename grid1_t, typename grid2_t>
|
|
void assign_function_of_grids_k(const functional &f, const grid1_t &g1, const grid2_t &g2)
|
|
{
|
|
assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g.size(2) == size(2) );
|
|
assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g.size(2) == size(2) );
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
auto &elem = this->kelem(i, j, k);
|
|
const auto &elemg1 = g1.kelem(i, j, k);
|
|
const auto &elemg2 = g2.kelem(i, j, k);
|
|
|
|
elem = f(elemg1,elemg2);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename functional, typename grid1_t, typename grid2_t>
|
|
void assign_function_of_grids_kdep(const functional &f, const grid1_t &g1, const grid2_t &g2)
|
|
{
|
|
assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g.size(2) == size(2) );
|
|
assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g.size(2) == size(2) );
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
auto &elem = this->kelem(i, j, k);
|
|
const auto &elemg1 = g1.kelem(i, j, k);
|
|
const auto &elemg2 = g2.kelem(i, j, k);
|
|
|
|
elem = f(this->get_k<real_t>(i, j, k),elemg1,elemg2);
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename functional>
|
|
void apply_function_k_dep(const functional &f)
|
|
{
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
auto &elem = this->kelem(i, j, k);
|
|
elem = f(elem, this->get_k<real_t>(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
template <typename functional>
|
|
void apply_function_r_dep(const functional &f)
|
|
{
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
auto &elem = this->relem(i, j, k);
|
|
elem = f(elem, this->get_r<real_t>(i, j, k));
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
void FourierTransformBackward(bool do_transform = true);
|
|
|
|
void FourierTransformForward(bool do_transform = true);
|
|
|
|
void ApplyNorm(void);
|
|
|
|
void FillRandomReal(unsigned long int seed = 123456ul);
|
|
|
|
void Write_to_HDF5(std::string fname, std::string datasetname) const;
|
|
|
|
void Write_PowerSpectrum( std::string ofname );
|
|
|
|
void Compute_PowerSpectrum(std::vector<double> &bin_k, std::vector<double> &bin_P, std::vector<double> &bin_eP, std::vector<size_t> &bin_count, int nbins);
|
|
|
|
void Write_PDF(std::string ofname, int nbins = 1000, double scale = 1.0, double rhomin = 1e-3, double rhomax = 1e3);
|
|
|
|
void stagger_field( void ){
|
|
FourierTransformForward();
|
|
apply_function_k_dep([&](auto x, auto k) -> ccomplex_t {
|
|
real_t shift = k[0]*get_dx()[0] + k[1]*get_dx()[1] + k[2]*get_dx()[2];
|
|
return x * std::exp(ccomplex_t(0.0,0.5*shift));
|
|
});
|
|
FourierTransformBackward();
|
|
}
|
|
|
|
void zero_DC_mode(void)
|
|
{
|
|
if( space_ == kspace_id ){
|
|
#ifdef USE_MPI
|
|
if (CONFIG::MPI_task_rank == 0)
|
|
#endif
|
|
cdata_[0] = (data_t)0.0;
|
|
}else{
|
|
data_t sum = 0.0;
|
|
// #pragma omp parallel for reduction(+:sum)
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
sum += this->relem(i, j, k);
|
|
}
|
|
}
|
|
}
|
|
#if defined(USE_MPI)
|
|
data_t glob_sum = 0.0;
|
|
MPI_Allreduce(reinterpret_cast<void *>(&sum), reinterpret_cast<void *>(&glob_sum),
|
|
1, GetMPIDatatype<data_t>(), MPI_SUM, MPI_COMM_WORLD);
|
|
sum = glob_sum;
|
|
#endif
|
|
sum /= sizes_[0]*sizes_[1]*sizes_[2];
|
|
|
|
#pragma omp parallel for
|
|
for (size_t i = 0; i < sizes_[0]; ++i)
|
|
{
|
|
for (size_t j = 0; j < sizes_[1]; ++j)
|
|
{
|
|
for (size_t k = 0; k < sizes_[2]; ++k)
|
|
{
|
|
this->relem(i, j, k) -= sum;
|
|
}
|
|
}
|
|
}
|
|
}
|
|
}
|
|
|
|
};
|