soothe2-re/dsp/framed_model.cpp

#include "framed_model.hpp"
#include "twin.hpp"
#include "freqpath.hpp"
#include "rt_mask_tables.hpp"
#include "rt_weights.hpp"
#include <cmath>
#include <cstring>
#include <algorithm>

namespace {

// sens XML -> internal sens_stored = sens * 2.054 (NOTES_TWIN:74: XML 12 -> 24.65 dB).
constexpr float SENS_SCALE = 2.054f;

// ---- Empirical bridge fit (NOTES_LEVEL:147, phase-5 step 5b). ----
// C(f_k) = G·LUT(log10(am_k/res_k)) + W·warp(f_k)^A ;  gain = (1−C)·res^rp(Q).
// The Pchip LUT below IS the runtime BandConfig curve (FUN_180563440/563a60,
// ctx+0x188 A/B/gamma) evaluated at the measured (xv, C) nodes (al_* dataset +
// B.11 anchors). Marked EMPIRICAL (all numbers from the joint dual+al_* fit,
// honest trimmed metric); the structural parametric A/B/gamma form is its
// source (see NOTE below) but live A/B/gamma for the test configs is unset.
constexpr double G_FIT = 0.9963;
constexpr double W_FIT = 0.3335;
constexpr double A_FIT = 0.9807;
constexpr double RP0   = 0.0275;   // res^rp(Q) gain term, rp = RP0·Q^drp
constexpr double DRP   = 0.2159;

// LUT knots (xv = log10(level), level = am/res):
static constexpr double kLX[12] = { -0.75, -0.5012, -0.5, -0.2012, 0.0988, 0.2488,
                                     0.3988, 0.5488, 0.574, 0.61,   0.75,   1.0 };
static constexpr double kLY[12] = { 0.4402, 0.366,  0.4552, 0.459, 0.541, 0.576,
                                     0.608,  0.636,  0.5645, 0.6471, 0.6562, 0.6670 };

static double lut_pchip(double x) {
    int n = 12;
    x = std::min(std::max(x, kLX[0]), kLX[n - 1]);
    // Monotone cubic Hermite (Fritsch–Carlson), matching scipy PchipInterpolator.
    double h[12], d[12];
    for (int i = 0; i < n - 1; i++) h[i] = kLX[i + 1] - kLX[i];
    for (int i = 0; i < n - 1; i++) d[i] = (kLY[i + 1] - kLY[i]) / h[i];
    double sl[12], sr[12];
    sl[0] = d[0]; sr[n - 1] = d[n - 2];
    for (int i = 1; i < n - 1; i++) {
        if (d[i - 1] * d[i] <= 0.0) { sl[i] = sr[i - 1] = 0.0; continue; }
        double w1 = 2 * h[i] + h[i - 1], w2 = h[i] + 2 * h[i - 1];
        sl[i] = (w1 + w2) / (w1 / d[i - 1] + w2 / d[i]);
        sr[i - 1] = sl[i];
    }
    int i = std::upper_bound(kLX, kLX + n, x) - kLX - 1;
    i = std::max(0, std::min(i, n - 2));
    double hh = h[i], t = (x - kLX[i]) / hh;
    double t2 = t * t, t3 = t2 * t;
    double h00 = 2 * t3 - 3 * t2 + 1, h10 = t3 - 2 * t2 + t;
    double h01 = -2 * t3 + 3 * t2,   h11 = t3 - t2;
    double y = h00 * kLY[i] + h10 * hh * sr[i] + h01 * kLY[i + 1] + h11 * hh * sl[i + 1];
    return y;
}

// freq-path warp 0x5406a8 (NOTES_LEVEL:181; build_warp): 0.87·K·x/(K+x), K=exp(2.0723).
static double warp_c(double f) {
    double x = f / 2000.0;
    return 0.87 * 7.942 * x / (7.942 + x);
}

}  // namespace

FramedDetector::FramedDetector(size_t nfft, float sample_rate)
    : nfft_(nfft), sample_rate_(sample_rate), wsum_(0) {
    am_.resize(nfft / 2 + 1, 0.0f);
}

FramedDetector::~FramedDetector() {}

void FramedDetector::setParams(const std::vector<DetectorBand>& bands) {
    bands_ = bands;
    size_t half = nfft_ / 2;
    res_.clear();
    track_.clear();

    for (const auto& b : bands_) {
        std::vector<float> r(half + 1, 1.0f);
        float sens_lin = std::pow(10.0f, b.sens * SENS_SCALE / 20.0f);  // param_5
        detkernel::twin_coeff c = detkernel::build_twin_coeff(
            static_cast<double>(sample_rate_), static_cast<double>(b.fc),
            static_cast<double>(b.q), sens_lin);
        std::vector<detkernel::cplxf> z(half + 1);
        std::vector<detkernel::cplxf> out(half + 1);
        for (size_t k = 0; k <= half; k++) {
            double theta = 2.0 * M_PI * static_cast<double>(k) / static_cast<double>(nfft_);
            z[k].re = static_cast<float>(std::cos(theta));
            z[k].im = static_cast<float>(std::sin(theta));
        }
        detkernel::twin_apply(c, z.data(), half + 1, out.data());
        for (size_t k = 0; k <= half; k++) {
            r[k] = std::sqrt(out[k].re * out[k].re + out[k].im * out[k].im);
            r[k] = std::max(r[k], 1e-12f);
        }
        res_.push_back(std::move(r));
    }
    track_.assign(bands_.size(), std::vector<float>(half + 1, 1.0f));
}

void FramedDetector::processFrame(const std::complex<double>* spectrum, float* mask) {
    size_t half = nfft_ / 2;
    if (wsum_ == 0.0) {
        double s = 0.0;
        for (size_t i = 0; i < nfft_; i++) {
            s += std::sqrt(0.5 * (1.0 - std::cos(2.0 * M_PI * i / (nfft_ - 1))));
        }
        wsum_ = s;
    }

    double tatt = 0.011, trel = 0.08;
    double att = std::exp(-1.0 * (nfft_ / 4) / (tatt * sample_rate_));
    double rel = std::exp(-1.0 * (nfft_ / 4) / (trel * sample_rate_));

    for (size_t k = 0; k <= half; k++) {
        double a_cur = 2.0 * std::abs(spectrum[k]) / wsum_;
        double am = am_[k];
        if (a_cur > am) am = att * am + (1.0 - att) * a_cur;
        else am = rel * am + (1.0 - rel) * a_cur;
        am_[k] = static_cast<float>(am);
    }

    for (size_t k = 0; k <= half; k++) mask[k] = 1.0f;

    for (size_t b = 0; b < bands_.size(); b++) {
        double rp = RP0 * std::pow(static_cast<double>(bands_[b].q), DRP);
        double fk = 0.0;
        double fstep = (sample_rate_ * 0.5) / static_cast<double>(half);
        for (size_t k = 0; k <= half; k++) {
            double res_k = std::max(static_cast<double>(res_[b][k]), 1e-12);
            double lvl = static_cast<double>(am_[k]) / res_k;
            double xv = std::log10(std::max(lvl, 1e-9));
            double C = G_FIT * lut_pchip(xv) + W_FIT * std::pow(warp_c(fk), A_FIT);
            double g = std::max(1.0 - C, 1e-9) * std::pow(res_k, rp);
            mask[k] = std::min(static_cast<float>(g), mask[k]);
            fk += fstep;
        }
    }
    for (size_t k = half + 1; k < nfft_; k++) {
        mask[k] = mask[nfft_ - k];
    }
}