Program Listing for File fourierTransform.hpp

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#ifndef LIBRAPID_ARRAY_FOURIER_TRANFORM_HPP
#define LIBRAPID_ARRAY_FOURIER_TRANFORM_HPP

namespace librapid::fft {
    namespace detail {
        namespace cpu {
            template<typename T>
            void rfft(Complex<T> *output, T *input, size_t n) {
                pocketfft::shape_t shape      = {n};
                pocketfft::stride_t strideIn  = {sizeof(T)};
                pocketfft::stride_t strideOut = {sizeof(Complex<T>)};
                size_t axis                   = 0;
                bool forward                  = true;
                T fct                         = 1.0;
                pocketfft::r2c(shape,
                               strideIn,
                               strideOut,
                               axis,
                               forward,
                               input,
                               reinterpret_cast<std::complex<T> *>(output),
                               fct,
                               global::numThreads);
            }

#if defined(LIBRAPID_HAS_CUDA)
            LIBRAPID_INLINE void rfft(Complex<double> *output, double *input, size_t n) {
                unsigned int mode = FFTW_ESTIMATE;
                fftw_plan plan    = fftw_plan_dft_r2c_1d(
                  (int)n, input, reinterpret_cast<fftw_complex *>(output), mode);
                fftw_execute(plan);
                fftw_destroy_plan(plan);
            }

            LIBRAPID_INLINE void rfft(Complex<float> *output, float *input, size_t n) {
                unsigned int mode = FFTW_ESTIMATE;
                fftwf_plan plan   = fftwf_plan_dft_r2c_1d(
                  (int)n, input, reinterpret_cast<fftwf_complex *>(output), mode);
                fftwf_execute(plan);
                fftwf_destroy_plan(plan);
            }
#elif defined(LIBRAPID_HAS_FFTW)
            LIBRAPID_INLINE void rfft(Complex<double> *output, double *input, size_t n) {
                unsigned int mode = FFTW_ESTIMATE;
                fftw_plan_with_nthreads((int)global::numThreads);
                fftw_plan plan = fftw_plan_dft_r2c_1d(
                  (int)n, input, reinterpret_cast<fftw_complex *>(output), mode);
                fftw_execute(plan);
                fftw_destroy_plan(plan);
            }

            LIBRAPID_INLINE void rfft(Complex<float> *output, float *input, size_t n) {
                unsigned int mode = FFTW_ESTIMATE;
                fftwf_plan_with_nthreads((int)global::numThreads);
                fftwf_plan plan = fftwf_plan_dft_r2c_1d(
                  (int)n, input, reinterpret_cast<fftwf_complex *>(output), mode);
                fftwf_execute(plan);
                fftwf_destroy_plan(plan);
            }
#endif
        } // namespace cpu

#if defined(LIBRAPID_HAS_CUDA)
        namespace gpu {
            LIBRAPID_INLINE void rfft(Complex<double> *output, double *input, size_t n) {
                cufftHandle plan;
                cufftPlan1d(&plan, (int)n, CUFFT_D2Z, 1);
                cufftSetStream(plan, global::cudaStream);
                cufftExecD2Z(plan, input, reinterpret_cast<cufftDoubleComplex *>(output));
                cufftDestroy(plan);
            }

            LIBRAPID_INLINE void rfft(Complex<float> *output, float *input, size_t n) {
                cufftHandle plan;
                cufftPlan1d(&plan, (int)n, CUFFT_R2C, 1);
                cufftSetStream(plan, global::cudaStream);
                cudaStreamSynchronize(global::cudaStream);
                cufftExecR2C(plan, input, reinterpret_cast<cufftComplex *>(output));
                cufftDestroy(plan);
            }
        } // namespace gpu
#endif    // LIBRAPID_HAS_CUDA
    }     // namespace detail

    template<typename ShapeType, typename StorageScalar>
    LIBRAPID_NODISCARD auto rfft(array::ArrayContainer<ShapeType, Storage<StorageScalar>> &array)
      -> Array<Complex<StorageScalar>, backend::CPU> {
        LIBRAPID_ASSERT(array.ndim() == 1, "RFFT only implemented for 1D arrays");
        int64_t outSize = array.shape()[0] / 2 + 1;
        Array<Complex<StorageScalar>, backend::CPU> res(Shape({outSize}));
        StorageScalar *input           = array.storage().begin();
        Complex<StorageScalar> *output = res.storage().begin();
        detail::cpu::rfft(output, input, array.shape()[0]);
        return res;
    }

#if defined(LIBRAPID_HAS_CUDA)
    template<typename ShapeType, typename StorageScalar>
    LIBRAPID_NODISCARD auto
    rfft(array::ArrayContainer<ShapeType, CudaStorage<StorageScalar>> &array)
      -> Array<Complex<StorageScalar>, backend::CUDA> {
        LIBRAPID_ASSERT(array.ndim() == 1, "RFFT only implemented for 1D arrays");
        int64_t outSize = array.shape()[0] / 2 + 1;
        Array<Complex<StorageScalar>, backend::CUDA> res(Shape({outSize}));
        StorageScalar *input           = array.storage().begin().get();
        Complex<StorageScalar> *output = res.storage().begin().get();
        detail::gpu::rfft(output, input, array.shape()[0]);
        return res;
    }
#endif // LIBRAPID_HAS_CUDA
} // namespace librapid::fft

#endif // LIBRAPID_ARRAY_FOURIER_TRANFORM_HPP