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sdrangel/modemm17/SlidingDFT.h
2022-07-31 04:54:39 +02:00

129 lines
3.5 KiB
C++

// Copyright 2021 Mobilinkd LLC.
#pragma once
#include <array>
#include <cmath>
#include <complex>
#include <cstddef>
namespace modemm17
{
/**
* A sliding DFT algorithm.
*
* Based on 'Understanding and Implementing the Sliding DFT'
* Eric Jacobsen, 2015-04-23
* https://www.dsprelated.com/showarticle/776.php
*/
template <size_t SampleRate, size_t Frequency, size_t Accuracy = 1000>
class SlidingDFT
{
public:
SlidingDFT()
{
samples_.fill(0);
float pi2 = M_PI * 2.0f;
float kth = float(Frequency) / float(SampleRate);
coeff_ = std::exp(-std::complex<float>{0, 1} * pi2 * kth);
}
std::complex<float> operator()(float sample)
{
auto index = index_;
index_ += 1;
if (index_ == (SampleRate / Accuracy)) index_ = 0;
float delta = sample - samples_[index];
std::complex<float> result = (result_ + delta) * coeff_;
result_ = result * float(0.999999999999999);
samples_[index] = sample;
prev_index_ = index;
return result;
}
private:
std::complex<float> coeff_;
std::array<float, (SampleRate / Accuracy)> samples_;
std::complex<float> result_{0,0};
size_t index_ = 0;
size_t prev_index_ = (SampleRate / Accuracy) - 1;
};
/**
* A sliding DFT algorithm.
*
* Based on 'Understanding and Implementing the Sliding DFT'
* Eric Jacobsen, 2015-04-23
* https://www.dsprelated.com/showarticle/776.php
*
* @tparam float is the floating point type to use.
* @tparam SampleRate is the sample rate of the incoming data.
* @tparam N is the length of the DFT. Frequency resolution is SampleRate / N.
* @tparam K is the number of frequencies whose DFT will be calculated.
*/
template <size_t SampleRate, size_t N, size_t K>
class NSlidingDFT
{
public:
using result_type = std::array<std::complex<float>, K>;
/**
* Construct the DFT with an array of frequencies. These frequencies
* should be less than @tparam SampleRate / 2 and a mulitple of
* @tparam SampleRate / @tparam N. No validation is performed on
* these frequencies passed to the constructor.
*/
NSlidingDFT(const std::array<size_t, K>& frequencies) :
coeff_(make_coefficients(frequencies))
{
samples_.fill(0);
}
/**
* Calculate the streaming DFT from the sample, returning an array
* of results which correspond to the frequencies passed in to the
* constructor. The result is only valid after at least N samples
* have been cycled in.
*/
result_type operator()(float sample)
{
auto index = index_;
index_ += 1;
if (index_ == N) index_ = 0;
float delta = sample - samples_[index];
for (size_t i = 0; i != K; ++i)
{
result_[i] = (result_[i] + delta) * coeff_[i];
}
samples_[index] = sample;
return result_;
}
private:
const std::array<std::complex<float>, K> coeff_;
std::array<float, N> samples_;
std::array<std::complex<float>, K> result_{0,0};
size_t index_ = 0;
size_t prev_index_ = N - 1;
static constexpr std::array<std::complex<float>, K>
make_coefficients(const std::array<size_t, K>& frequencies)
{
std::complex<float> j = std::complex<float>{0, 1};
std::array<std::complex<float>, K> result;
float pi2 = M_PI * 2.0f;
for (size_t i = 0; i != K; ++i)
{
float k = float(frequencies[i]) / float(SampleRate);
result[i] = std::exp(-j * pi2 * k);
}
return result;
}
};
} // modemm17