// 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 multiple 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