portapack-mayhem/firmware/common/dsp_fft.hpp
Bernd Herzog b4da86d491
New app: Spectrum Painter (#988)
* added spectrum painter app
2023-05-14 23:09:43 +02:00

181 lines
5.7 KiB
C++

/*
* Copyright (C) 2013 Jared Boone, ShareBrained Technology, Inc.
*
* This file is part of PortaPack.
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2, or (at your option)
* any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License
* along with this program; see the file COPYING. If not, write to
* the Free Software Foundation, Inc., 51 Franklin Street,
* Boston, MA 02110-1301, USA.
*/
#ifndef __DSP_FFT_H__
#define __DSP_FFT_H__
#include <cstdint>
#include <cstddef>
#include <complex>
#include <cmath>
#include <type_traits>
#include <array>
#include "dsp_types.hpp"
#include "complex.hpp"
#include "hal.h"
#include "utility.hpp"
#include "sine_table_int8.hpp"
namespace std {
/* https://github.com/AE9RB/fftbench/blob/master/cxlr.hpp
* Nice trick from AE9RB (David Turnbull) to get compiler to produce simpler
* fma (fused multiply-accumulate) instead of worrying about NaN handling
*/
inline complex<float>
operator*(const complex<float>& v1, const complex<float>& v2) {
return complex<float> {
v1.real() * v2.real() - v1.imag() * v2.imag(),
v1.real() * v2.imag() + v1.imag() * v2.real()
};
}
} /* namespace std */
template<typename T, size_t N>
void fft_swap(const buffer_c16_t src, std::array<T, N>& dst) {
static_assert(power_of_two(N), "only defined for N == power of two");
for(size_t i=0; i<N; i++) {
const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
const auto s = src.p[i];
dst[i_rev] = {
static_cast<typename T::value_type>(s.real()),
static_cast<typename T::value_type>(s.imag())
};
}
}
template<typename T, size_t N>
void fft_swap(const std::array<complex16_t, N>& src, std::array<T, N>& dst) {
static_assert(power_of_two(N), "only defined for N == power of two");
for(size_t i=0; i<N; i++) {
const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
const auto s = src[i];
dst[i_rev] = {
static_cast<typename T::value_type>(s.real()),
static_cast<typename T::value_type>(s.imag())
};
}
}
template<typename T, size_t N>
void fft_swap(const std::array<T, N>& src, std::array<T, N>& dst) {
static_assert(power_of_two(N), "only defined for N == power of two");
for(size_t i=0; i<N; i++) {
const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
dst[i_rev] = src[i];
}
}
template<typename T, size_t N>
void fft_swap_in_place(std::array<T, N>& data) {
static_assert(power_of_two(N), "only defined for N == power of two");
for(size_t i=0; i<N/2; i++) {
const size_t i_rev = __RBIT(i) >> (32 - log_2(N));
std::swap(data[i], data[i_rev]);
}
}
/* http://beige.ucs.indiana.edu/B673/node14.html */
/* http://www.drdobbs.com/cpp/a-simple-and-efficient-fft-implementatio/199500857?pgno=3 */
template<typename T, size_t N>
void fft_c_preswapped(std::array<T, N>& data, const size_t from, const size_t to) {
static_assert(power_of_two(N), "only defined for N == power of two");
constexpr auto K = log_2(N);
if ((to > K) || (from > K)) return;
constexpr size_t K_max = 8;
static_assert(K <= K_max, "No FFT twiddle factors for K > 8");
static constexpr std::array<std::complex<float>, K_max> wp_table { {
{ -2.0f, 0.0f }, // 2
{ -1.0f, -1.0f }, // 4
{ -0.2928932188134524756f, -0.7071067811865475244f }, // 8
{ -0.076120467488713243872f, -0.38268343236508977173f }, // 16
{ -0.019214719596769550874f, -0.19509032201612826785f }, // 32
{ -0.0048152733278031137552f, -0.098017140329560601994f }, // 64
{ -0.0012045437948276072852f, -0.049067674327418014255f }, // 128
{ -0.00030118130379577988423f, -0.024541228522912288032f }, // 256
} };
/* Provide data to this function, pre-swapped. */
for(size_t k = from; k < to; k++) {
const size_t mmax = 1 << k;
const auto wp = wp_table[k];
T w { 1.0f, 0.0f };
for(size_t m = 0; m < mmax; ++m) {
for(size_t i = m; i < N; i += mmax * 2) {
const size_t j = i + mmax;
const T temp = w * data[j];
data[j] = data[i] - temp;
data[i] += temp;
}
w += w * wp;
}
}
}
/*
ifft(v,N):
[0] If N==1 then return.
[1] For k = 0 to N/2-1, let ve[k] = v[2*k]
[2] Compute ifft(ve, N/2);
[3] For k = 0 to N/2-1, let vo[k] = v[2*k+1]
[4] Compute ifft(vo, N/2);
[5] For m = 0 to N/2-1, do [6] through [9]
[6] Let w.real() = cos(2*PI*m/N)
[7] Let w.imag() = sin(2*PI*m/N)
[8] Let v[m] = ve[m] + w*vo[m]
[9] Let v[m+N/2] = ve[m] - w*vo[m]
*/
template<typename T>
void ifft( T *v, int n, T *tmp )
{
if(n>1) {
int k,m;
T z, w, *vo, *ve;
ve = tmp; vo = tmp+n/2;
for(k=0; k<n/2; k++) {
ve[k] = v[2*k];
vo[k] = v[2*k+1];
}
ifft( ve, n/2, v ); /* FFT on even-indexed elements of v[] */
ifft( vo, n/2, v ); /* FFT on odd-indexed elements of v[] */
for(m=0; m<n/2; m++) {
w.real(sine_table_i8[((int)(m/(double)n * 0x100 + 0x40)) & 0xFF]);
w.imag(sine_table_i8[((int)(m/(double)n * 0x100)) & 0xFF]);
z.real((w.real()*vo[m].real() - w.imag()*vo[m].imag())/127); /* Re(w*vo[m]) */
z.imag((w.real()*vo[m].imag() + w.imag()*vo[m].real())/127); /* Im(w*vo[m]) */
v[ m ].real(ve[m].real() + z.real());
v[ m ].imag(ve[m].imag() + z.imag());
v[m+n/2].real(ve[m].real() - z.real());
v[m+n/2].imag(ve[m].imag() - z.imag());
}
}
return;
}
#endif/*__DSP_FFT_H__*/