#pragma once

#include <cmath>
#include <array>
#include <vector>

#include <vec3.hh>
#include <general.hh>
#include <bounding_box.hh>

enum space_t
{
    kspace_id,
    rspace_id
};

template< typename data_t >
class Grid_FFT;

template <typename array_type>
int get_task(ptrdiff_t index, const array_type &offsets, const array_type& sizes,
             const int ntasks )
{
    int itask = 0;
    while (itask < ntasks - 1 && offsets[itask + 1] <= index)
        ++itask;
    return itask;
}

// template <typename data_t, typename operator_t>
// void unpad(const Grid_FFT<data_t> &fp, Grid_FFT<data_t> &f, operator_t op );

template <typename data_t>
void pad_insert(const Grid_FFT<data_t> &f, Grid_FFT<data_t> &fp);

template< typename data_t >
class OrszagConvolver
{
protected:
    Grid_FFT<data_t> *f1p_, *f2p_;
    std::array<size_t,3> np_;
    std::array<real_t,3> length_;
    
    ccomplex_t *crecvbuf_;
    real_t *recvbuf_;
    ptrdiff_t *offsets_;
	ptrdiff_t *offsetsp_;
	ptrdiff_t *sizes_;
	ptrdiff_t *sizesp_;

private:
    int get_task( ptrdiff_t index, const ptrdiff_t *offsets, const ptrdiff_t *sizes, const int ntasks ) const
    {
        int itask = 0;
        while( itask < ntasks-1 && offsets[itask+1] <= index ) ++itask;
        return itask;
    }

	// void pad_insert( const Grid_FFT<data_t> & f, Grid_FFT<data_t> & fp );
	// void unpad( const Grid_FFT<data_t> & fp, Grid_FFT< data_t > & f );

public:

    
    OrszagConvolver( const std::array<size_t, 3> &N, const std::array<real_t, 3> &L )
    : np_({3*N[0]/2,3*N[1]/2,3*N[2]/2}), length_(L)
    {
        //... create temporaries
        f1p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);
        f2p_ = new Grid_FFT<data_t>(np_, length_, kspace_id);

#if defined(USE_MPI)
        size_t 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_ = new ptrdiff_t[ntasks];
        offsetsp_ = new ptrdiff_t[ntasks];
        sizes_ = new ptrdiff_t[ntasks];
        sizesp_ = new ptrdiff_t[ntasks];

        size_t tsize = N[0], tsizep = f1p_->size(0);

        MPI_Allgather(&f.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
    }

    ~OrszagConvolver()
    {
        delete f1p_;
        delete f2p_;
#if defined(USE_MPI)
        delete[] crecvbuf_;
        delete[] offsets_;
        delete[] offsetsp_;
        delete[] sizes_;
        delete[] sizesp_;
#endif
    }

    //... inplace interface
    template <typename opp>
	void convolve2( Grid_FFT<data_t> & f1, Grid_FFT<data_t> & f2, Grid_FFT<data_t> & res, opp op)// = []( ccomplex_t convres, ccomplex_t res ) -> ccomplex_t{ return convres; } )
    {
        #if 1
        // constexpr real_t fac{ std::pow(1.5,1.5) };
        constexpr real_t fac{ 1.0 };
        
        //... copy data 1
        f1.FourierTransformForward();
        f1p_->FourierTransformForward(false);
        pad_insert(f1, *f1p_);
        //... copy data 2
        f2.FourierTransformForward();
        f2p_->FourierTransformForward(false);
        pad_insert(f2, *f2p_);
        //... convolve
        f1p_->FourierTransformBackward();
        f2p_->FourierTransformBackward();
        for (size_t i = 0; i < f1p_->ntot_; ++i){
            (*f2p_).relem(i) *= fac * (*f1p_).relem(i);
        }
        f2p_->FourierTransformForward();
        //... copy data back
        res.FourierTransformForward();
        unpad(*f2p_, res, op);
        #else
        res.FourierTransformBackward();
        f1.FourierTransformBackward();
        f2.FourierTransformBackward();
        
        for (size_t i = 0; i < res.ntot_; ++i){
            res.relem(i) = op(f1.relem(i)*f2.relem(i),res.relem(i));
        }

        #endif
    }

    //... inplace interface
	/*void convolve3( const Grid_FFT<data_t> & f1, const Grid_FFT<data_t> & f2, const Grid_FFT<data_t> & f3, Grid_FFT<data_t> & res )
    {
        convolve2( f1, f2, res );
        convolve2( res, f3, res );
    }*/
};


template <typename data_t>
class Grid_FFT
{
protected:
#if defined(USE_MPI)
    const MPI_Datatype MPI_data_t_type = (typeid(data_t) == typeid(double)) ? MPI_DOUBLE
       : (typeid(data_t) == typeid(float)) ? MPI_FLOAT
       : (typeid(data_t) == typeid(std::complex<float>)) ? MPI_COMPLEX
       : (typeid(data_t) == typeid(std::complex<double>)) ? MPI_DOUBLE_COMPLEX : MPI_INT;
#endif
public:
    std::array<size_t, 3> n_, nhalf_;
    std::array<size_t, 4> sizes_;
    size_t npr_, npc_;
    size_t ntot_;
    std::array<real_t, 3> length_, kfac_, dx_;

    space_t space_;
    data_t *data_;
    ccomplex_t *cdata_;

    bounding_box<size_t> global_range_;

    fftw_plan_t plan_, iplan_;

    real_t fft_norm_fac_;

    ptrdiff_t local_0_start_, local_1_start_;
    ptrdiff_t local_0_size_, local_1_size_;

    Grid_FFT(const std::array<size_t, 3> &N, const std::array<real_t, 3> &L, space_t initialspace = rspace_id)
        : n_(N), length_(L), space_(initialspace), data_(nullptr), cdata_(nullptr) //, RV_(*this), KV_(*this)
    {
        for (int i = 0; i < 3; ++i)
        {
            kfac_[i] = 2.0 * M_PI / length_[i];
            dx_[i] = length_[i] / n_[i];
        }
        //invalidated = true;
        this->Setup();
    }

    Grid_FFT(const Grid_FFT<data_t> &g)
        : n_(g.n_), length_(g.length_), space_(g.space_), data_(nullptr), cdata_(nullptr)
    {
        for (int i = 0; i < 3; ++i)
        {
            kfac_[i] = g.kfac_[i];
            dx_[i] = g.dx_[i];
        }
        //invalidated = true;
        this->Setup();

        for (size_t i = 0; i < ntot_; ++i)
        {
            data_[i] = g.data_[i];
        }
    }

    ~Grid_FFT()
    {
        if (data_ != nullptr)
        {
            fftw_free(data_);
        }
    }

    const Grid_FFT<data_t>* get_grid( size_t ilevel ) const { return this; }
    bool is_in_mask( size_t ilevel, size_t i, size_t j, size_t k ) const { return true; }
    bool is_refined( size_t ilevel, size_t i, size_t j, size_t k ) const { return false; }
    size_t levelmin() const {return 7;}
    size_t levelmax() const {return 7;}
    
    void Setup();

    size_t size(size_t i) const { return sizes_[i]; }

    void zero()
    {
        for (size_t i = 0; i < ntot_; ++i)
            data_[i] = 0.0;
    }

    data_t &relem(size_t i, size_t j, size_t k)
    {
        size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
        return data_[idx];
    }

    const data_t &relem(size_t i, size_t j, size_t k) const
    {
        size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
        return data_[idx];
    }

    ccomplex_t &kelem(size_t i, size_t j, size_t k)
    {
        size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
        return cdata_[idx];
    }

    const ccomplex_t &kelem(size_t i, size_t j, size_t k) const
    {
        size_t idx = (i * sizes_[1] + j) * sizes_[3] + k;
        return cdata_[idx];
    }

    ccomplex_t &kelem(size_t idx) { return cdata_[idx]; }
    const ccomplex_t &kelem(size_t idx) const { return cdata_[idx]; }
    data_t &relem(size_t idx) { return data_[idx]; }
    const data_t &relem(size_t idx) const { return data_[idx]; }

    size_t get_idx(size_t i, size_t j, size_t k) const
    {
        return (i * sizes_[1] + j) * sizes_[3] + k;
    }

    template <typename ft>
    vec3<ft> get_r(const size_t &i, const size_t &j, const size_t &k) const
    {
        vec3<ft> rr;

#if defined(USE_MPI)
        rr[0] = real_t(i + local_0_start_) * dx_[0];
#else
        rr[0] = real_t(i) * dx_[0];
#endif
        rr[1] = real_t(j) * dx_[1];
        rr[2] = real_t(k) * dx_[2];

        return rr;
    }

    void cell_pos( int ilevel, size_t i, size_t j, size_t k, double* x ) const {
        
        x[0] = double(i)/size(0);
        x[1] = double(j)/size(1);
        x[2] = double(k)/size(2);
    }

    size_t count_leaf_cells( int, int ) const {
        return n_[0]*n_[1]*n_[2];
    }

    template <typename ft>
    vec3<ft> get_k(const size_t &i, const size_t &j, const size_t &k) const
    {
        vec3<ft> kk;

#if defined(USE_MPI)
        auto ip = i + local_1_start_;
        kk[0] = (real_t(j) - real_t(j > nhalf_[0]) * n_[0]) * kfac_[0];
        kk[1] = (real_t(ip) - real_t(ip > nhalf_[1]) * n_[1]) * kfac_[1];
#else
        kk[0] = (real_t(i) - real_t(i > nhalf_[0]) * n_[0]) * kfac_[0];
        kk[1] = (real_t(j) - real_t(j > nhalf_[1]) * n_[1]) * kfac_[1];
#endif
        kk[2] = (real_t(k) - real_t(k > nhalf_[2]) * n_[2]) * kfac_[2];

        return kk;
    }

    template <typename functional>
    void apply_function_k(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);
                }
            }
        }
    }

    template <typename functional>
    void apply_function_r(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);
                }
            }
        }
    }

    double compute_2norm(void)
    {
        real_t sum1{0.0};
#pragma omp parallel for reduction(+ \
                                   : sum1)
        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)
                {
                    const auto re = std::real(this->relem(i, j, k));
                    const auto im = std::imag(this->relem(i, j, k));
                    sum1 += re * re + im * im;
                }
            }
        }

        sum1 /= sizes_[0] * sizes_[1] * sizes_[2];

        return sum1;
    }

    double std(void)
    {
        real_t sum1{0.0}, sum2{0.0};
#pragma omp parallel for reduction(+ \
                                   : sum1, sum2)
        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)
                {
                    const auto elem = std::real(this->relem(i, j, k));
                    sum1 += elem;
                    sum2 += elem * elem;
                }
            }
        }

        sum1 /= sizes_[0] * sizes_[1] * sizes_[2];
        sum2 /= sizes_[0] * sizes_[1] * sizes_[2];

        return std::sqrt(sum2 - sum1 * sum1);
    }
    double mean(void)
    {
        real_t sum1{0.0};
#pragma omp parallel for reduction(+ \
                                   : sum1)
        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)
                {
                    const auto elem = std::real(this->relem(i, j, k));
                    sum1 += elem;
                }
            }
        }

        sum1 /= sizes_[0] * sizes_[1] * sizes_[2];

        return sum1;
    }

    template <typename functional, typename grid_t>
    void assign_function_of_grids_r(const functional &f, const grid_t &g)
    {
        assert(g.size(0) == size(0) && g.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->relem(i, j, k);
                    const auto &elemg = g.relem(i, j, k);

                    elem = f(elemg);
                }
            }
        }
    }

    template <typename functional, typename grid1_t, typename grid2_t>
    void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2)
    {
        assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
        assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.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 idx = this->get_idx(i,j,k);
                    auto &elem = this->relem(i, j, k);

                    const auto &elemg1 = g1.relem(i, j, k);
                    const auto &elemg2 = g2.relem(i, j, k);

                    elem = f(elemg1, elemg2);
                }
            }
        }
    }

    template <typename functional, typename grid1_t, typename grid2_t, typename grid3_t>
    void assign_function_of_grids_r(const functional &f, const grid1_t &g1, const grid2_t &g2, const grid3_t &g3)
    {
        assert(g1.size(0) == size(0) && g1.size(1) == size(1)); // && g1.size(2) == size(2));
        assert(g2.size(0) == size(0) && g2.size(1) == size(1)); // && g2.size(2) == size(2));
        assert(g3.size(0) == size(0) && g3.size(1) == size(1)); // && g3.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 idx = this->get_idx(i,j,k);
                    auto &elem = this->relem(i, j, k);

                    const auto &elemg1 = g1.relem(i, j, k);
                    const auto &elemg2 = g2.relem(i, j, k);
                    const auto &elemg3 = g3.relem(i, j, k);

                    elem = f(elemg1, elemg2, elemg3);
                }
            }
        }
    }

    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);

    void ComputePowerSpectrum(std::vector<double> &bin_k, std::vector<double> &bin_P, std::vector<double> &bin_eP, int nbins);

    void Compute_PDF(std::string ofname, int nbins = 1000, double scale = 1.0, double rhomin = 1e-3, double rhomax = 1e3);

    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 *>(&globsum),
                  1, MPI_DOUBLE, 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;
                    }
                }
            }
        }
    }
};



template <typename data_t, typename operator_t>
void unpad(const Grid_FFT<data_t> &fp, Grid_FFT<data_t> &f, operator_t op )
{
    // assert(fp.n_[0] == 3 * f.n_[0] / 2);
    // assert(fp.n_[1] == 3 * f.n_[1] / 2);
    // assert(fp.n_[2] == 3 * f.n_[2] / 2);

    size_t dn[3] = {
        fp.n_[0] - f.n_[0],
        fp.n_[1] - f.n_[1],
        fp.n_[2] - f.n_[2],
    };

    const double rfac = std::sqrt(fp.n_[0] * fp.n_[1] * fp.n_[2]) / std::sqrt(f.n_[0] * f.n_[1] * f.n_[2]);

#if !defined(USE_MPI) ////////////////////////////////////////////////////////////////////////////////////

    size_t nhalf[3] = {f.n_[0] / 2, f.n_[1] / 2, f.n_[2] / 2};

    for (size_t i = 0; i < f.size(0); ++i)
    {
        size_t ip = (i > nhalf[0]) ? i + dn[0] : i;
        for (size_t j = 0; j < f.size(1); ++j)
        {
            size_t jp = (j > nhalf[1]) ? j + dn[1] : j;
            for (size_t k = 0; k < f.size(2); ++k)
            {
                size_t kp = (k > nhalf[2]) ? k + dn[2] : k;
                // if( i==nhalf[0]||j==nhalf[1]||k==nhalf[2]) continue;
                f.kelem(i, j, k) = op(fp.kelem(ip, jp, kp) / rfac, f.kelem(i, j, k));
            }
        }
    }

#else /// then USE_MPI is defined //////////////////////////////////////////////////////////////

    /////////////////////////////////////////////////////////////////////
    size_t maxslicesz = fp.sizes_[1] * fp.sizes_[3] * 2;

    std::vector<ccomplex_t> crecvbuf_(maxslicesz / 2,0);
    real_t* recvbuf_ = reinterpret_cast<real_t *>(&crecvbuf_[0]);

    std::vector<ptrdiff_t> 
        offsets_(CONFIG::MPI_task_size, 0), 
        offsetsp_(CONFIG::MPI_task_size, 0), 
        sizes_(CONFIG::MPI_task_size, 0), 
        sizesp_(CONFIG::MPI_task_size, 0);

    size_t tsize = f.size(0), tsizep = fp.size(0);

    MPI_Allgather(&f.local_1_start_, 1, MPI_LONG_LONG, &offsets_[0], 1,
                  MPI_LONG_LONG, MPI_COMM_WORLD);
    MPI_Allgather(&fp.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);
    /////////////////////////////////////////////////////////////////////

    double tstart = get_wtime();

    csoca::ilog << "[MPI] Started gather for convolution";

    MPI_Barrier(MPI_COMM_WORLD);

    size_t nf[3] = {f.size(0), f.size(1), f.size(2)};
    size_t nfp[4] = {fp.size(0), fp.size(1), fp.size(2), fp.size(3)};
    size_t fny[3] = {f.n_[1] / 2, f.n_[0] / 2, f.n_[2] / 2};

    size_t slicesz = fp.size(1) * fp.size(3);

    if (typeid(data_t) == typeid(real_t))
        slicesz *= 2; // then sizeof(real_t) gives only half of a complex

    MPI_Datatype datatype =
        (typeid(data_t) == typeid(float))
            ? MPI_FLOAT
            : (typeid(data_t) == typeid(double))
                  ? MPI_DOUBLE
                  : (typeid(data_t) == typeid(std::complex<float>))
                        ? MPI_COMPLEX
                        : (typeid(data_t) == typeid(std::complex<double>))
                              ? MPI_DOUBLE_COMPLEX
                              : MPI_INT;

    MPI_Status status;

    //... local size must be divisible by 2, otherwise this gets too complicated
    // assert( tsize%2 == 0 );

    f.zero();

    std::vector<MPI_Request> req;
    MPI_Request temp_req;

    for (size_t i = 0; i < nfp[0]; ++i)
    {
        size_t iglobal = i + offsetsp_[CONFIG::MPI_task_rank];

        //... sending
        if (iglobal < fny[0])
        {
            int sendto = get_task(iglobal, offsets_, sizes_, CONFIG::MPI_task_size);

            MPI_Isend(&fp.kelem(i * slicesz), (int)slicesz, datatype, sendto, (int)iglobal,
                      MPI_COMM_WORLD, &temp_req);
            req.push_back(temp_req);
        }
        else if (iglobal > 2 * fny[0])
        {
            int sendto = get_task(iglobal - fny[0], offsets_, sizes_, CONFIG::MPI_task_size);
            MPI_Isend(&fp.kelem(i * slicesz), (int)slicesz, datatype, sendto, (int)iglobal,
                      MPI_COMM_WORLD, &temp_req);
            req.push_back(temp_req);
        }
    }

    for (size_t i = 0; i < nf[0]; ++i)
    {
        size_t iglobal = i + offsets_[CONFIG::MPI_task_rank];

        int recvfrom = 0;
        if (iglobal < fny[0])
        {
            recvfrom = get_task(iglobal, offsetsp_, sizesp_, CONFIG::MPI_task_size);
            MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom, (int)iglobal,
                     MPI_COMM_WORLD, &status);
        }
        else if (iglobal > fny[0])
        {
            recvfrom = get_task(iglobal + fny[0], offsetsp_, sizesp_, CONFIG::MPI_task_size);
            MPI_Recv(&recvbuf_[0], (int)slicesz, datatype, recvfrom,
                     (int)(iglobal + fny[0]), MPI_COMM_WORLD, &status);
        }
        else
            continue;

        assert(status.MPI_ERROR == MPI_SUCCESS);

        for (size_t j = 0; j < nf[1]; ++j)
        {

            if (j < fny[1])
            {
                size_t jp = j;
                for (size_t k = 0; k < nf[2]; ++k)
                {
                    // size_t kp = (k>fny[2])? k+fny[2] : k;
                    // f.kelem(i,j,k) = crecvbuf_[jp*nfp[3]+kp];
                    if (k < fny[2])
                        f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k],f.kelem(i, j, k));
                    else if (k > fny[2])
                        f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k + fny[2]], f.kelem(i, j, k));
                }
            }
            if (j > fny[1])
            {
                size_t jp = j + fny[1];
                for (size_t k = 0; k < nf[2]; ++k)
                {
                    // size_t kp = (k>fny[2])? k+fny[2] : k;
                    // f.kelem(i,j,k) = crecvbuf_[jp*nfp[3]+kp];
                    if (k < fny[2])
                        f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k], f.kelem(i, j, k));
                    else if (k > fny[2])
                        f.kelem(i, j, k) = op(crecvbuf_[jp * nfp[3] + k + fny[2]], f.kelem(i, j, k));
                }
            }
        }
    }

    for (size_t i = 0; i < req.size(); ++i)
    {
        // need to preset status as wait does not necessarily modify it to reflect
        // success c.f.
        // http://www.open-mpi.org/community/lists/devel/2007/04/1402.php
        status.MPI_ERROR = MPI_SUCCESS;

        MPI_Wait(&req[i], &status);
        assert(status.MPI_ERROR == MPI_SUCCESS);
    }

    MPI_Barrier(MPI_COMM_WORLD);

    csoca::ilog.Print("[MPI] Completed gather for convolution, took %fs", get_wtime() - tstart);

#endif /// end of ifdef/ifndef USE_MPI //////////////////////////////////////////////////////////////
}