mirror of
https://github.com/portapack-mayhem/mayhem-firmware.git
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139 lines
4.4 KiB
C++
139 lines
4.4 KiB
C++
/*
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* Copyright (C) 2013 Jared Boone, ShareBrained Technology, Inc.
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*
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* This file is part of PortaPack.
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*
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* This program 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 2, or (at your option)
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* any later version.
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*
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* This program 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; see the file COPYING. If not, write to
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* the Free Software Foundation, Inc., 51 Franklin Street,
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* Boston, MA 02110-1301, USA.
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*/
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#ifndef __DSP_FFT_H__
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#define __DSP_FFT_H__
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#include <cstdint>
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#include <cstddef>
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#include <complex>
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#include <cmath>
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#include <type_traits>
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#include <array>
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#include "dsp_types.hpp"
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#include "complex.hpp"
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#include "hal.h"
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#include "utility.hpp"
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namespace std {
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/* https://github.com/AE9RB/fftbench/blob/master/cxlr.hpp
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* Nice trick from AE9RB (David Turnbull) to get compiler to produce simpler
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* fma (fused multiply-accumulate) instead of worrying about NaN handling
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*/
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inline complex<float>
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operator*(const complex<float>& v1, const complex<float>& v2) {
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return complex<float> {
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v1.real() * v2.real() - v1.imag() * v2.imag(),
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v1.real() * v2.imag() + v1.imag() * v2.real()
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};
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}
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} /* namespace std */
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template<typename T, size_t N>
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void fft_swap(const buffer_c16_t src, std::array<T, N>& dst) {
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static_assert(power_of_two(N), "only defined for N == power of two");
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for(size_t i=0; i<N; i++) {
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const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
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const auto s = src.p[i];
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dst[i_rev] = {
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static_cast<typename T::value_type>(s.real()),
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static_cast<typename T::value_type>(s.imag())
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};
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}
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}
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template<typename T, size_t N>
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void fft_swap(const std::array<complex16_t, N>& src, std::array<T, N>& dst) {
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static_assert(power_of_two(N), "only defined for N == power of two");
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for(size_t i=0; i<N; i++) {
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const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
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const auto s = src[i];
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dst[i_rev] = {
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static_cast<typename T::value_type>(s.real()),
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static_cast<typename T::value_type>(s.imag())
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};
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}
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}
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template<typename T, size_t N>
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void fft_swap(const std::array<T, N>& src, std::array<T, N>& dst) {
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static_assert(power_of_two(N), "only defined for N == power of two");
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for(size_t i=0; i<N; i++) {
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const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
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dst[i_rev] = src[i];
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}
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}
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template<typename T, size_t N>
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void fft_swap_in_place(std::array<T, N>& data) {
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static_assert(power_of_two(N), "only defined for N == power of two");
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for(size_t i=0; i<N/2; i++) {
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const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
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std::swap(data[i], data[i_rev]);
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}
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}
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/* http://beige.ucs.indiana.edu/B673/node14.html */
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/* http://www.drdobbs.com/cpp/a-simple-and-efficient-fft-implementatio/199500857?pgno=3 */
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template<typename T, size_t N>
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void fft_c_preswapped(std::array<T, N>& data, const size_t from, const size_t to) {
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static_assert(power_of_two(N), "only defined for N == power of two");
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constexpr auto K = log_2(N);
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if ((to > K) || (from > K)) return;
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constexpr size_t K_max = 8;
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static_assert(K <= K_max, "No FFT twiddle factors for K > 8");
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static constexpr std::array<std::complex<float>, K_max> wp_table { {
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{ -2.0f, 0.0f }, // 2
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{ -1.0f, -1.0f }, // 4
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{ -0.2928932188134524756f, -0.7071067811865475244f }, // 8
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{ -0.076120467488713243872f, -0.38268343236508977173f }, // 16
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{ -0.019214719596769550874f, -0.19509032201612826785f }, // 32
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{ -0.0048152733278031137552f, -0.098017140329560601994f }, // 64
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{ -0.0012045437948276072852f, -0.049067674327418014255f }, // 128
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{ -0.00030118130379577988423f, -0.024541228522912288032f }, // 256
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} };
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/* Provide data to this function, pre-swapped. */
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for(size_t k = from; k < to; k++) {
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const size_t mmax = 1 << k;
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const auto wp = wp_table[k];
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T w { 1.0f, 0.0f };
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for(size_t m = 0; m < mmax; ++m) {
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for(size_t i = m; i < N; i += mmax * 2) {
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const size_t j = i + mmax;
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const T temp = w * data[j];
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data[j] = data[i] - temp;
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data[i] += temp;
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}
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w += w * wp;
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}
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}
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}
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#endif/*__DSP_FFT_H__*/
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