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